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Propulsion control strategies for ship emergency manoeuvres
Ocean Engineering 137 (2017) 99–109
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Ocean Engineering journal homepage: www.elsevier.com/locate/oceaneng
Propulsion control strategies for ship emergency manoeuvres
MARK
⁎
M. Altosole , M. Martelli Polytechnic School of Genoa University, DITEN, Via all’Opera Pia 11 A, 16145 Genova, Italy
A R T I C L E I N F O
A BS T RAC T
Keywords: Ship propulsion control Simulation based design Slam start Crash stop Engine Propeller pitch
This work deals with the propulsion control aspects relating to some of the most critical emergency manoeuvres of a ship: slam start and crash stop. In these particular situations a very important role is played by the automation system that has to manage the whole propulsive chain (i.e. main engine, mechanical transmission and propeller) in a safe and efficient way. With regard to this, a simulation based design methodology is adopted to develop and test new control schemes for ship propulsion. The proposed control layout is applicable to any type of propulsion systems equipped with controllable pitch propellers, since it is mainly based on the automatic adjustment of the propeller pitch. Thus the desired performance requirements are met through adaptive control strategies able to address the complex issues of slam start, crash stop and similar stressful manoeuvres. The adaptivity of the automation process to several critical propulsive conditions reduces significantly the number of the control parameters to be estimated, as recently demonstrated by the automation design of a new twin-screw ship. For this application, the comparison between simulation results and sea trials data is finally shown for validation design purposes.
1. Introduction Current marine propulsion systems are notable for their high performance and flexibility, difficult features to be achieved without the development of an efficient control system. The large power available to the propellers entails a careful management of the propulsion machinery, in every propulsive condition. Especially during critical manoeuvres (e.g. slam start, crash stop, tight turning circles, …), the automation designers have to develop proper control strategies and set a lot of parameters, normally based on their experience, in several ship propulsion modes. The identification of the proper solution among all the possible combinations is rather difficult and time consuming. In light of this, special control functions, characterized by an adaptive behaviour, could be very useful because they would reduce the number of variables to be assessed. Time-domain simulation can be used to evaluate the effectiveness of these algorithms, especially for the representation of ship critical manoeuvres that could dangerously stress the whole propulsion system (Altosole et al., 2012). Many simulation studies on ship manoeuvrability can be found in the scientific literature but it is not easy to represent every manoeuvre by a single numerical model. An attempt to develop a comprehensive unified versatile mathematical model, suitable for the all types of manoeuvres in still water, has been recently undertaken by Sutulo and Guedes Soares (2015): in their study, the comparisons with full-scale data (available for the full helm turning ⁎
tests, crash stop tests and bow thruster turning of a shuttle LNG carrier) show reliable simulation results, practically without special tuning of the model. On the contrary to what happens for manoeuvrability issues, the machinery behaviour during demanding manoeuvres is rather less investigated in the available literature. The most stressful conditions for the prime mover, propeller and mechanical transmission can be experienced during the ship emergency manoeuvring, as in the case of slam start and crash stop. As well known, the first one is traditionally referred to the vessel acceleration from zero speed to the full power condition, while the second one is the ship stopping, as quickly as possible, starting from the maximum speed of the vessel. Especially during crash stop, usually performed to avoid collisions, the main engine and propeller are subjected to severe stress and loading. From this point of view, relevant scientific papers exist on the propeller structural safety in this particular emergency situation. In the available literature, the prediction of loads on the propeller during crash stop is usually performed by using propeller series charts or, more specifically, CFD analyses, in order to evaluate the structural safety of the blades. In Hur et al. (2011), propeller torque values are estimated by Wageningen B series characteristics and compared with sea trial data, in spite of the difference of the propeller blade shape and flow steadiness between series and recordings. Wageningen results during crash stop provide slightly higher torque values but the discrepancies can be considered marginal in evaluation of the structural safety. However, series charts
Corresponding author. E-mail address: [email protected] (M. Altosole).
http://dx.doi.org/10.1016/j.oceaneng.2017.03.053 Received 26 November 2015; Received in revised form 15 February 2017; Accepted 25 March 2017 0029-8018/ © 2017 Published by Elsevier Ltd.
Ocean Engineering 137 (2017) 99–109
M. Altosole, M. Martelli
Nomenclature
A B Cip C e n n nc poil t KD KI KP Ib Ip M qi QE
QElim Qf Qhyd QP QS QSlim Q−ϕ
yoke area oil bulk modulus oil leakage coefficient Coriolis centripetal matrix error rotational speed rotational speed corresponding to the maximum lever position commanded rotational speed oil pressure time derivative gain integral gain proportional gain moment of inertia of the propeller blade polar inertia ship inertia matrix oil volumetric flow engine torque
Si v Vc xp τH τP τR φ φc φr ∆φ ∆rpm
engine torque limit shaft friction torque hydraulic torque propeller torque shaft torque shaft torque limit torque due to the forces interaction between blade and bearing of the propeller automation signal value ship speed vector chamber volume piston position forces and moments acting on ship hull forces and moments acting on ship hull forces and moments acting on ship rudder propeller pitch commanded propeller pitch propeller pitch reduction value propeller pitch tolerance revolutions per minute tolerance
tion was considered during the control scheme design of an innovative propulsion system (Altosole et al., 2012) characterized by a very flexible use of the different engine types onboard (gas turbine and electric motor). Simulation results are shown and discussed, in order to justify the choice of the proposed special control functions. Similar simulation approaches to represent crash stop dynamics are adopted by Krüger and Haack (2004) and Schoop-Zipfel et al. (2012). In both works, the authors address the negative influence of the wind milling effect (i.e. propeller driven by the water) on the whole propulsion system during the ship stopping but do not provide any details concerning the control procedure to manage this critical situation. The automation logics presented in this study are suitable for CPP propulsion systems, since they are characterized by an adaptive behaviour due to the automatic computation of the propeller pitch reference. By this way, it is possible to drive a wide range of possible heavy accelerations and stopping manoeuvres, as demonstrated by the full-scale validation shown at the end of the article.
cannot predict the pressure distribution on the propeller blade; hence CFD simulation is suggested to represent the hydrodynamic load acting on the propeller. About this, Black and Swithenbank (2009) have examined the water flow velocities, measured during a crash-back test of a model propeller: experimental data, concerning mean and extreme loading conditions, have been used in a strip theory approach to develop loads for finite element analysis, in order to assess stresses on the individual blades. Structural safety of the several propulsion components (propeller, shaft line, thrust-bearing and main engine) can be ensured also by adopting proper control strategies to avoid overloading during critical manoeuvres. From this point of view, numerical simulation can be used to evaluate the effectiveness of original control devices, as reported by Yabuki and Yoshimura (2010) and Wirz (2012). In the first mentioned work, a simulation study is described to evaluate the ship-handling method during the stopping manoeuvre: a turning moment is applied to the ship by the maximum rudder angle steering prior to the reversing operation of the Controllable Pitch Propeller (CPP). The simulation analysis confirms that CPP ships can be sufficiently controlled by the proposed method. The combination of a slow-speed two-stroke diesel engine and a Fixed Pitch Propeller (FPP) is rather disadvantageous from the point of view of the crash stop performance. Consequently, Wirz (2012) proposes and simulates a novel method of applying a braking torque to the FPP by means of water injection into the engine cylinders during unfired operation. As regards the characteristics and requirements of a good control propulsion system, able to prevent overloads and possible failures of the ship machinery, very little was written so far. Banning et al. (1997) introduce a tracking control system aimed at saving fuel and optimizing efficiency. A propulsion control procedure, based on several controllers switching between them to cover the whole operating range of the vessel, is proposed by Lopez et al. (2010). However, except for occasional works, the control issue in marine literature is often addressed from the manoeuvring point of view, such as in the path-following problems (Skjetne et al., 2005; Fossen, 2011) and unmanned surface vehicles (Breivik et al., 2008) but a proper investigation of the engines and actuators behaviour is a key point for the correct evaluation of every ship manoeuvre (Martelli, 2015). In line with the latter consideration, the present article deals with the development of some proper control algorithms for the ship handling during slam start and crash stop. A first theoretical applica-
2. Overall control system and design methodology In this section, the main characteristics of a possible control system layout are described for a generic marine propulsion system. Prime movers can be diesel engines, gas turbines or even electric motors. The controller architecture is based on machinery regulation and protection functions. The purpose of the main propulsive regulation is to provide the proper revolutions signal to the engine, in order to keep the commanded propeller speed value achieving the desired velocity of the vessel. Protection logics aim at preserving propulsion machinery from overloads (i.e. over-torque, over-speed, over-temperature, etc…). All three types of engines above mentioned are usually controlled in terms of their rotational speed. In fact the overall controller calculates the signal reference to the engine governor over time, based on PID algorithms applied to revolutions error between commanded and actual values. This control signal is finally transformed by the governor into the required mechanical torque, by means of acting on the fuel flow in the cases of diesel engines and gas turbines, or on the frequency in the case of electric motors. For the sake of clarity, the main control features are resumed through the control scheme of Fig. 1, referring to the single shaftline of a generic propulsion system equipped with Controllable Pitch Propellers (CPPs).
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Fig. 1. Overall propulsion control scheme.
of the engine torque QE :
The overall controller has to manage propeller pitch as well as prime movers dynamics. The left side of Fig. 1 shows the control signal of the bridge lever position, split into two components, acting on the propeller revolutions and pitch angle respectively. The two signals are modulated over time by ramps. In detail, the ramp function generates a signal that begins to increase, or decrease, at a constant rate (i.e. the slope of the ramp) until the target value is reached. The ramp function is usually required to dampen the dynamic effects on the plant due to the input signals variation. Next, the modulated signals are converted into reference values for propeller revolutions and pitch angle, via the combinator laws (i.e. the steady state numerical correspondence of the lever position with propeller rotational speed and pitch) illustrated in Fig. 1 by the speed and pitch combinator tables. Thus, the two propeller setpoints are compared with the field data to calculate the error signals, to which PID algorithms are applied to obtain the two target values, respectively for the engine governor and propeller pitch change mechanism. Referring to the well-known Eq. (1), the calculation of the PID output Si over the time t is based on the error between setpoint and feedback, through the action of the proportional gain KP, the integral gain KI and the derivative gain KD.
Si(t ) = KPei(t ) + KI
∫0
t
de (t ) ei(t )dt +KD i dt
e2(t ) = QElim − QE (t )
3) Shaft torque protection: i.e. Eq. (1) applied to the error between the shaft torque limit QSlim (the maximum load torque of the shaftline) and the shaft actual torque QS :
e3(t ) = QSlim − QS (t )
(4)
A control function reducing the propeller pitch reference is introduced in case of shaft line over torque. Therefore, the final value of the propeller pitch setpoint φ can be expressed as the difference between the propeller pitch φc (commanded by the combinator) and the correction φr :
φ(t ) = φc(t )−φr (t )
(5)
The pitch reduction is calculated by a PID algorithm too:
φr (t ) = KPe3(t ) + KI
∫0
t
e3(t )dt +KD
de3(t ) dt
(6)
where:
⎧ 0 φ ≤0 r ⎪ φr (t ) = ⎨ φr & φr >0 ⎪ ⎩∆φφr ≥∆φ
(1)
On the top of Fig. 1 it is shown that the final setpoint to the engine governor is calculated as the minimum value among three signals Si, achieved through the following i actions (i=1–3):
(7)
The conditions represented by Eq. (7) are provided by the saturation block illustrated on the bottom of Fig. 1. In such a way, the φc value can be only reduced and not increased. The pitch reduction can never be greater than a limit value ∆φ , decided by the automation designer (anyway ∆φ is relatively small to avoid losing excessive performance in terms of ship speed). In the case of a twin-screw ship, the pitch reduction for over torque protection can be made on the two shaftlines independently: this is why during tight turning circles, the two shaft lines dynamics can be quite different in terms of required power and torque. In accordance with the control scheme of Fig. 1, the numerical values of the several control parameters (i.e. PID gains) are chosen so that overload protection can be firstly achieved by reducing the
1) Shaft speed regulation by means of Eq. (1), applied to the error e1between the commanded rotational speed nc and the actual shaft speed n :
e1(t ) = nc(t )−n(t )
(3)
(2)
2) Engine torque protection: i.e. the signal calculated by Eq. (1), on the basis of the error between the engine torque limit QElim (the maximum continuous torque of the engine) and the actual value
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propeller pitch and secondly by decreasing the fuel flow rate (if the first action is not sufficient), resulting into a rotational speed reference reduction. Proportional, integral and derivative gains are generically named in the text as KP, KI and KD, assuming different numerical values in all the above equations according to their specific task. The proper tuning of such gains is one of the main activities of the automation designer. This task, usually time consuming and expensive, can be facilitated by the use of numerical simulation during the preliminary design phase, although the behaviour of the real hardware on shipboard could be quite different from that one simulated. In accordance with the scheme of Fig. 2, the Central Processing Units (CPUs, i.e. the control units) work in real time, exchanging data with the field via their Input/Output boards (named IO boards in Fig. 2). The automation designer should be sure that the performance foreseen by simulation is maintained in a real ship environment. To this end, it is necessary to limit, as far as possible, most of the differences between CPUs behaviour and numerical simulation. The main discrepancies could be due to: the cyclic time of the CPUs, the different time delay in exchanging data among controllers and the native functions that can be implemented. Further differences could be represented by the presence of many functionalities usually not implemented in the ship numerical model (but that interact with the propulsion control) and the thousands of signals that the automation has to monitor on the real system. To cancel the influence of these kinds of differences on the design process, the Real Time Hardware in the Loop (RT HIL) method can be adopted. The RT HIL simulation, born primarily in the automotive industry, is becoming a standard part of the design process for the propulsion controller of some recent naval vessels, as fully described by Altosole et al. (2007) and Altosole et al. (2010). According to this design approach, the ship propulsion system is simulated by a numerical code that is directly linked to the CPU. In detail, the numerical model is compiled as an executable file, able to perform simulation in real time and installed on the same computer of the real controller. The exchanging of data between controller and propulsion model is possible by using the OPC (i.e. object linking and embedding for process control) protocol. The executable file is an OPC client and reads the command input of the controller that acts as an OPC server. All the parameters exchanged via OPC can be logged to a file, but they are also available to the operator by means of a graphical panel. By this way it is possible to have a comprehensive view of all the working parameters and the designer can have a realistic feedback about the hardware behaviour, before its installation on board. Traditionally, the test and tuning of the real controller is made onboard during the ship delivery period. These trials are time consuming and very expensive, also because they require the full availability of the vessel. By using RT HIL simulation, the physical availability of the ship is not needed, therefore time and costs can be significantly reduced. For the recent applications followed by the authors, the automation designer has selected the numerical values of the main control parameters by using a “trial and error” approach.
3. Control design in emergency manoeuvres A propulsion controller, as represented in Fig. 1, is characterized by many variables to be estimated. In detail, for a telegraph consisting of twenty one possible steps of the lever (i.e. the zero thrust position, ten positions for the ahead running of the vessel and ten for the astern condition), the automation designer has to set the numerical values of the following control parameters: – twenty one values of the shaft speed, corresponding to other twenty one pitch angles of the propeller, to be inserted into the pertinent combinator tables; – ten values of the ramp slopes for the ship acceleration and other ten for the deceleration condition, referring to revolutions setpoint calculation; – twenty slope rates for the ramp referred to the propeller pitch setpoint; – proportional, integral and derivative values of the three PID algorithms to calculate the engine setpoint; – proportional, integral and derivative values of the PID algorithm for the possible pitch setpoint reduction. In addition, at least two propulsion conditions exist for a ship: cruising and manoeuvring, each one represented by a different combinator table. Therefore most of the previous control parameters should be set twice, increasing both complexity and time of the controller design phase. Moreover, the numerical tuning carried out for standard and soft manoeuvres is often not suitable for emergency propulsive conditions as slam start and crash stop. The combinator table, together with the pertinent ramps slopes acting on each signal, can significantly affect the dynamic behaviour of the whole propulsion system during heavy accelerations and decelerations. During this kind of transients, the reference values of propeller revolutions and pitch are commanded by a combinator that is usually designed for the desired steady state performance. Consequently, its numerical values cannot be optimized for non-standard operating conditions. Without a dedicated control logic for the most critical manoeuvres, the propulsion performance can be largely reduced and the desired requirements (e.g. time to reach the maximum ship speed during slam start or stopping space to perform crash stop) may not be met. This could be due to the intervention of several protections of the engine governor, responsible for a sudden cut off of the fuel supply in case of engine over-torque or over-speed. As an example, a similar situation will be further detailed in the paragraph 4.1, to highlight the need of the control optimization process during a typical slam start. Therefore, to improve the control system behaviour also in offdesign conditions, original control functions are introduced and analysed in the following. They are planned to manage heavy acceleration and decelerations of the ship in a safe and efficient way, through a systematic design process able to avoid a further different tuning of all the control parameters, previously listed. The core of the proposed control scheme is represented by the automatic computation of the propeller pitch setpoint on the basis of the actual propeller speed. Thus, a proper combinator table, representing the relationship between pitch and revolutions for all the several lever positions, is no longer required. By preventing the engine over-torque as main objective, it is assumed that other possible kinds of mechanical overloads (e.g. overloads for shaftline and thrust-bearing) will probably be avoided (or at least reduced). In the next sections, the definition of slam start and crash stop is given from the point of view of the automation system, together with the description of the pertinent control logics. In general, the automatic computation over time of the propeller
Fig. 2. Example of a ship propulsion controller architecture.
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Fig. 5. Example of propeller pitch dynamics during a slam start.
Fig. 3. Flow chart of the slam start control logic.
pitch setpoint is based on the introduction of two distinct parameters regarding propeller revolutions: a rotational speed tolerance (in the following named ∆rpm ) to be used for demanding ship accelerations (e.g. slam start) and a reference constant threshold acting during crash stop.
Fig. 6. Example of propeller speed dynamics during a slam start.
The pitch reference computation represents the main core of the control logic during the slam start of the ship. The purpose is to obtain the automatic calculation of the pitch reference value during each heavy acceleration of the vessel, without providing new dedicated combinator tables and ramps slope rates. This is why it would be very difficult to foresee a proper unique combinator law for any possible critical acceleration. The flow chart of Fig. 3 summarizes the whole control process, where the computation of the increasing of the pitch setpoint (i.e. the pitch variation to be added to the initial value) is detailed in Fig. 4. The proposed control function calculates the propeller pitch reference up to its design value, making sure that the actual propeller speed (in Fig. 4 named rpm feedback, i.e. revolutions per minute) follows its increasing setpoint in a smooth and linear way. Referring to Fig. 4, the saturation up to zero for negative errors (between setpoint and actual revolutions) is responsible for the activation of the pitch “freezing”. This condition is studied to be
3.1. Slam start control process In this work, “slam start” condition means every manoeuvre for which the bridge lever is suddenly moved to its maximum position (100%), starting from a step value lower than 70%. On this general basis, slam start manoeuvre can start also when the vessel is moving astern: in this case, both propeller pitch and speed are managed according to a proper combinator law, up to the zero thrust condition of the propeller. On the contrary, if the pitch value φ at the beginning of the manoeuvre is greater than the one corresponding to the zero thrust (φ0), a PID algorithm calculates the propeller pitch reference, while the commanded rotational speed linearly assumes its maximum value via a ramp function.
Fig. 4. Calculation process of the propeller pitch setpoint variation during slam start.
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of the whole propulsion plant dynamics, influenced by the ship motions in six degrees of freedom (i.e. surge, sway, yaw, roll, heave and pitch). The full description of the motion equations can be found in Martelli et al. (2014b), where the ship model validation by specific manoeuvring sea trials (i.e. turning circles, zig zag, etc.) is also discussed. A good correlation between the experimental and simulated values has been experienced. The ship dynamics is deduced by applying the forces and moments equations for a rigid body. Hull, propeller and rudder forces are considered while environmental forces are not taken into account. The added masses are evaluated by means of regression formulas. Given the importance of the control aspects, particular attention has been paid to the numerical modelling of the engine (Altosole et al., 2009, 2014) and the CPP mechanism behaviour (Altosole et al., 2012; Martelli et al., 2014a). Each component of the engine is represented by steady-state performance maps and thermodynamic equations. The dynamics of the engine is influenced by its governor behaviour, that in this study is simulated in accordance with the indications available from the manufacturer. The simulation process can be summarized by solving the following main differential equations:
activated when the CPP actual speed is too far from its setpoint, in order to avoid that any increase of the pitch value results in a sudden and significant drop of CPP revolutions, with a consequent drop in ship performance. The meaning of “pitch freezing” action during a slam start is graphically explained by Fig. 5. The stopping of the pitch setpoint is evident in the whole period in which the propeller speed is too far from its reference value, as shown in Fig. 6. The proposed control strategy allows the increase of the pitch setpoint up to the desired value when the following mathematical condition is met:
n (t )−n(t )−∆rpm<0
(8)
where n(t ) is the actual speed of the propeller depending on time t and n (t ) is the corresponding final setpoint corresponding to the maximum lever position (depending on time t because it is modulated by the ramp over time). When the difference between reference and actual value is lower than ∆rpm , the pitch setpoint grows up to its final value, otherwise a zero signal (produced by the saturation effect) feeds the PID algorithm and consequently the pitch reference increase is stopped (“freezing” action). Numerical simulation allows to tune the value of the speed tolerance ∆rpm .
Mv ̇ + C (v)v = τH + τP + τR
(9)
2πIpn ̇ = QE + QP + Qf
(10)
3.2. Crash stop control process
Ibφ̈ = Qhyd + Qs + Q−ϕ
(11)
As in slam start condition, the definition of crash stop can be extended to several possible critical manoeuvres from the automation point of view. In the present proposal, crash stop means every condition in which the bridge lever is moved from any forward position higher than 20%, up to an astern step at least equal to −100%. This assumption significantly increases the special cases to be analysed by the automation designer, complicating the control optimization process during the design stage. In order to reduce the parameters range to be set for any possible case, the propeller pitch is automatically adapted to the engine revolutions variation, in accordance with the control logic summarized through the flow chart of Fig. 7. As long as the propeller pitch values φ are greater than pitch corresponding to zero thrust (φ0), the pitch setpoint is calculated by the proper function described in Fig. 8, based on a PID algorithm acting on the error between revolutions feedback and a constant threshold, selected by the automation designer. The PID result is added to the initial value corresponding to combinator pitch angle at the beginning of the crash stop manoeuvre. The saturation block illustrated in Fig. 8 allows the pitch freezing if the propeller rotational speed increases too much due to a quick reduction of the pitch angle. At the same time, the shaft dynamics is managed acting on the throttle valve of the engine: if the actual rotational speed is greater than the considered threshold, the engine is immediately commanded to the idle condition; otherwise it is driven by its governor on the basis of the usual and standard speed regulation. On the contrary, for pitch values lower than φ0 (i.e. values corresponding to the astern condition of the vessel), the calculation of both pitch and shaft speed reference values is managed according to the combinator law. In light of the latter, revolutions threshold and combinator values should be chosen high enough to ensure a good astern thrust of the propeller.
Vc p ̇ = q − Cippoil − Axṗ i B oil
(12)
Eq. (9), representing the ship motions in six degrees of freedom, is
4. Simulation results and shipboard application The algorithms previously illustrated have been recently proposed within the control design process of a twin-screw ship propulsion system, equipped with CPPs. In particular, this new automatic control system was implemented into a propulsion simulation code, developed in Matlab-Simulink® environment, that was used for the representation
Fig. 7. Flow chart of the crash stop control logic.
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Fig. 8. Calculation process of the pitch angle setpoint during crash stop.
Fig. 9. Ship speed simulation during slam start.
Fig. 11. Propeller pitch simulation during slam start.
Fig. 10. Shaft speed simulation during slam start.
Fig. 12. Propeller thrust simulation during slam start.
expressed in vector form for sake of compactness (the whole equations system, including hydrodynamic terms, is fully described in Martelli et al., 2014b); v is the ship velocities vector; M is the inertia matrix including added masses; C is the Coriolis centripetal matrix; τH , τP and τR represent forces and moments acting on hull, propeller and rudder. Eq. (10) describes the shaft dynamics for the computation of the propeller rotational speed n , depending on the engine torque QE , the propeller torque QP and the shaft friction torque Qf ; Ip is the polar inertia of the rotating masses involved in the shaftline dynamics. Propeller thrust and torque are simulated by means of the open water diagrams. Under this assumption, the propeller dynamics is only modelled as a consequence of the pitch change mechanism behaviour, represented by Eqs. (11) and (12). In particular, Eq. (11) shows the motion of the propeller blade around its spindle axis in terms of angular acceleration φ̈ , depending on the blade loads (i.e. the hydraulic torque Qhyd acting on the pin slot, the spindle torque Qs and the torque
Q−ϕ that is due to the interaction forces between propeller blade and blade bearing). Ib is the moment of inertia of the blade. In Eq. (12), representing the oil pressure poil that is required to turn or to hold the blade position, qi is the inlet volumetric flow, Cip is the oil leakage coefficient, A is the yoke area, xp is the piston position, B is the oil bulk modulus and Vc is the chamber volume of the actuator. 4.1. Simulation analysis For the same vessel, the authors carried out a sensitivity analysis by simulation (Altosole et al., 2012) that is shown again in this section to analyse the effects of the proposed control logics on the propulsion system performance. Fig. 9–16 deal with a slam start manoeuvre, while Figs. 17–23 illustrate a crash stop. The considered variables are ship and shaft speeds, propeller pitch and thrust, automation signal driving the
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Fig. 13. Engine signal simulation during slam start.
Fig. 16. Engine behaviour comparison between standard and optimum control (slam start).
Fig. 14. Engine torque simulation during slam start. Fig. 17. Ship speed simulation during crash stop.
Fig. 15. Ship speed comparison between standard and optimum control (slam start). Fig. 18. Ship stopping space simulation.
engine governor and the corresponding brake torque. All results are reported as percentages of their maximum values: in particular, the considered maximum torque and thrust correspond to the continuous engine torque limit and to the thrust-bearing limit. The simulated slam start consists in a fast acceleration from zero speed up to full ahead. Three different simulations have been performed, each one with a distinct value of the speed tolerance (i.e. ∆rpm1 < ∆rpm2 < ∆rpm3). The increase of the parameter ∆rpm leads to a positive effect on the ship acceleration, as it is evident in Fig. 9. Figs. 10 and 11 show the propeller revolutions and pitch, following
their corresponding automation setpoints. From Fig. 10 it is possible to derive the slope rate of the ramp considered for the speed reference. The pitch signal is greatly influenced by ∆rpm , given that the freezing action is more significant at low values of ∆rpm . As ∆rpm increases, thrust and torque are closer to their maximum limit values (Figs. 12 and 14). Especially engine torque reaches the 100% in correspondence of the highest ∆rpm value. In conclusion, a too high ∆rpm produces a good ship acceleration but it significantly increases the risk of the engine over-torque. In this
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Fig. 19. Propeller speed simulation during crash stop.
Fig. 22. Engine signal simulation during crash stop.
Fig. 20. Propeller pitch simulation during crash stop.
Fig. 23. Engine torque simulation during crash stop.
Fig. 21. Propeller thrust simulation during crash stop.
Fig. 24. Engine signal comparison (crash stop).
light the speed tolerance value ∆rpm2 could represent a valid compromise to optimise the slam start manoeuvre both from the points of view of the ship performance and engine behaviour. To underline the effectiveness of the proposed control algorithm, the same kind of slam start, but performed in accordance with the traditional control scheme of Fig. 1, is simulated in terms of ship speed (Fig. 15) and working points over the engine load diagram (Fig. 16). In the two figures, the propulsion performance curves, achieved by the optimization corresponding to ∆rpm2 (dash line) and by the standard control (solid line), are compared. Through the comparison, it is
possible to note that the ship acceleration time is very similar (i.e. about 140 s to reach the maximum speed of the vessel) but the standard control scheme is responsible for a worse behaviour of the engine. In fact, during the last part of the manoeuvre, the working points correspond to the maximum power limit of the engine, denoting a saturation of the throttle valve actuator (in Fig. 16, the dash dot line represents the maximum output power and speed - and consequently the maximum torque – available from the engine governor). As known, the saturation on a control system mainly means poor performance and/or even instability (Levine, 2000). Moreover, the engine is forced 107
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Fig. 25. Propeller pitch angle comparison (crash stop).
Fig. 28. Propeller thrust comparison (crash stop).
Fig. 26. Engine speed comparison (crash stop).
Fig. 29. Ship speed comparison (crash stop).
Fig. 19 and Fig. 20 report the propeller behaviour in terms of rotational speed and pitch. The latter is greatly influenced by the revolutions threshold. In detail, the pitch freezing action is evident at the beginning of the manoeuvre and around the zero thrust pitch angle (φ0). The first freezing is due to the actual propeller speed that is higher than threshold value, while the second action is due to the transition to a different pitch setpoint calculation (i.e. the combinator is considered when the actual pitch angle is lower than φ0). In general, the selection of a greater threshold tends to improve the ship stopping performance but also makes the automation signal less stable during the engine acceleration (Fig. 22). In addition, Figs. 21 and 23 show that the threshold variation does not significantly affect the maximum values of the propeller thrust and engine torque.
4.2. Results validation by sea trials data Fig. 27. Engine torque comparison (crash stop).
The control logics developed during the simulation based design have been implemented in the automation software on shipboard. During sea trials, it was possible to achieve the crash stop performance illustrated from Fig. 24 to Fig. 29. In the same figures, also simulation results are reported in order to evaluate the reliability of the design methodology. All the numerical values are given in dimensionless form for confidential reasons. In the considered case, the ship stopping is performed moving the bridge lever from 90% up to its maximum astern position. The general dynamics is well predicted although some differences between simulation and experimental data are present. It should be considered that the final tuning of some important
to work in a high fuel consumption zone. Based on these considerations, the proposed control strategy during heavy ship accelerations results certainly better than the standard control procedure. The same kind of simulation analysis is carried out for the crash stop manoeuvre. Three simulations have been performed, each one characterized by a different value of the revolutions threshold (threshold1 < threshold2 < threshold3). Increasing the threshold value, the ship stopping is faster (Fig. 17). Fig. 18 shows that all three considered thresholds allow to achieve ship stopping distances below 100%, representing the desired requirement for the specific application. 108
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80%. Moreover, the adaptive control can be extended to other propulsive conditions (e.g. accelerations during demanding turning circles) further reducing the design activity. The efforts, due to the simulator development and to the controller optimization, are largely balanced by the savings obtained in time and costs to meet the main requirements of efficiency and safety. The good effectiveness of the method is demonstrated by the comparison between simulation results and sea trials data for a specific application: the positive response suggests that both the model based design procedure and the presented control algorithms can be applied successfully to other new projects.
control parameters (i.e. combinator laws, ramps slope and PID gains) has never been available from the automation provider. Thus the present simulation is performed assuming the same numerical identification carried out during the control design stage and previously discussed (only the threshold value of shaft revolutions was confirmed to be equal to threshold2). In this light, the comparison is certainly affected by the not exact correspondence between simulation and actual input data, however other interesting considerations can be made. In particular, Fig. 24 shows an early starting of the engine in comparison with simulation, due to a different calculation of the propeller pitch setpoint. The latter, in the real system, is characterized by a faster decreasing (Fig. 25): therefore the zero thrust pitch and consequently the engine starting are reached about six seconds earlier than simulation. Since the pitch setpoint is calculated through the error between a constant threshold of the propeller revolutions and the actual rotational speed, the time discrepancy between the two pitch behaviours is essentially due to a different representation of the shaftline dynamics by simulation. Experimental data of Fig. 26 show an earlier revolutions drop that could mean an imperfect modelling of the propeller load to the engine. In this regard, it is proper to underline that the propeller thrust and torque are simulated through the open water characteristics, so the shaft dynamics equation is solved by using a steady state representation of the propeller torque. This approach is usually reliable to simulate ship soft manoeuvres but it may lose precision for fast decelerations and accelerations of the vessel. An even better agreement between simulation and sea trials could be achieved considering a dynamic model for the propeller performance description. The final oscillation of the engine speed (solid line of Fig. 26) is due to the instability of the engine signal, and therefore of the engine torque, in the last part of the manoeuvre (Fig. 24 and Fig. 27). It may be a consequence of the interaction between the overall controller and the engine governor. Simulation does not reproduce this behaviour, probably because of a not very accurate modelling of the engine governor (e.g. different numerical values of the PID gains between reality and simulation). The different behaviour of the simulated propeller pitch and speed affect also the thrust, especially during the first period of the manoeuvre. In detail, the simulation result of Fig. 28 reports a lower thrust of the propeller from the beginning up to fifty seconds and a higher negative magnitude at the end. This final overestimation leads to a minor stopping time of the vessel in comparison with sea trials data, as evident in Fig. 29.
Acknowledgements The authors wish to thank SEASTEMA S.p.A. (Fincantieri Company) and Italian Navy for the support received during the research activity and the sea trials campaign. References Altosole, M., Bagnasco A., Figari, M., Maffioletti, L., 2007. Design and test of the propulsion control of the aircraft carrier “Cavour” using real-time hardware in the loop simulation. In: Proceedings of the EuroSiw 2007. June 2007, Genoa, Italy. Altosole, M., Benvenuto, G., Campora, U., Figari, M., 2009. Real-time simulation of a COGAG naval ship propulsion system. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 223 (1), 47–62. Altosole, M., Dubbioso, G., Figari, M., Michetti, S., Millerani Trapani, A., Viviani, M., 2010. Simulation of the dynamic behaviour of a CODLAG propulsion plant. In: Proceeding of Warship 2010 Conference. London, UK. Altosole, M., Figari, M., Martelli, M., Orrù, G., 2012. Propulsion control optimisation for emergency manoeuvres of naval vessels. In: Proceedings of the 11th International Naval Engineering Conference and Exhibition, INEC 2012. May 2012, Edinburgh, UK. Altosole, M., Campora, U., Martelli, M., Figari, M., 2014. Performance decay analysis of a marine gas turbine propulsion system. J. Ship Res. 58 (3), 117–129. Banning, R., Johnson, M.A., Grimble, M.J., 1997. Advanced control design for marine diesel engine propulsion systems. J. Dyn. Syst.-T ASME 119 (2), 167–174. Black, S., Swithenbank, S., 2009. Analysis of crashback forces compared with experimental results. In: Proceedings of the 1th International Symposium on Marine Propulsors (SMP’09). June 2009, Trondheim, Norway. Breivik, M., Hovstein, V.E., Fossen, T.I., 2008. Straight-line target tracking for unmanned surface vehicles. Model Ident. Control 29 (4), 131–149. Fossen, T.I., 2011. Nonlinear maneuvering theory and path-following control. Mar. Technol. Eng. 11 (2011), 445–460. Hur, J.W., Lee, H., Chang, B.J., 2011. Propeller loads of large commercial vessels at crash stop. In: Proceedings of the 2nd International Symposium on Marine Propulsors (SMP’11). June 2011, Hamburg, Germany. Krüger, S., Haack, T., 2004. Design of propulsion control systems based on the simulation of nautical manoeuvres. In: Proceedings of the 9th Symposium on Practical Design of Ships and Other Floating Structures. Luebeck-Travemuende, Germany. Levine, W.S., 2000. Control System Fundamentals. CRC Press LLC, USA. Lopez, M.J., Garcia, L., Lorenzo, J., Consegliere, A., 2010. Design methodology based on H∞ control theory for marine propulsion system with bumpless transfer function. WSEAS Trans. Syst. 9 (3), 253–262. Martelli, M., 2015. Marine Propulsion Simulation: Methods and Results. Walter de Gruyter GmbH & Co KG, Berlin, Collection: engineering. Martelli, M., Figari, M., Altosole, M., Vignolo, S., 2014a. Controllable pitch propeller actuating mechanism, modelling and simulation. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 228 (1), 29–43. Martelli, M., Viviani, M., Altosole, M., Figari, M., Vignolo, S., 2014b. Numerical modelling of propulsion, control and ship motions in 6 degrees of freedom. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 228 (4), 373–397. Schoop-Zipfel, J., Abdel-Maksoud, M., Tigges, K., 2012. Stopping simulations and sea trial measurements of a ship with diesel-electric propulsion and controllable pitch propellers. In: Proceedings of International Conference on Marine Simulation and Ship Manoeuvrability (MARSIM 2012). April 2012, Singapore. Skjetne, R., Fossen, T.I., Kokotović, P.V., 2005. Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory. Automatica 41 (2), 289–298. Sutulo, S., Guedes Soares, C., 2015. Development of a core mathematical model for arbitrary manoeuvres of a shuttle tanker. Appl. Ocean Res. 51, 293–308. Wirz, F., 2012. Optimisation of the crash-stop manoeuvre of vessels employing slowspeed two-stroke engines and fixed pitch propellers. J. Mar. Eng. Technol. 11 (1), 35–43, (9). Yabuki, H., Yoshimura, Y., 2010. On the control of CPP ships by steering during inharbour ship-handling. Trans. Nav. 4 (2), 157–162.
5. Conclusions The article provides general control schemes to drive CPP propulsion systems during standard and emergency manoeuvres of a vessel. The proposed algorithms are evaluated through numerical simulation, providing a realistic feedback before the installation on board of the real control system. An overview of the several control parameters, to be set by the automation designer, is given in reference to a generic propulsion plant: simulation shows that their numerical tuning, carried out for standard and soft manoeuvres, can hardly meet high and safe performance requirements also during the most critical transient conditions. Therefore, in order to avoid a new and demanding evaluation of the several parameters, special control strategies are proposed for the most stressful manoeuvres (slam start and crash stop). They are essentially based on the introduction of a reference rotational speed, to be used for the automatic calculation of the propeller pitch setpoint. Compared to a standard control procedure, the two algorithms, developed for fast accelerations and ship stopping, lead to a reduction of the parameters number to be estimated around
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Ocean Engineering journal homepage: www.elsevier.com/locate/oceaneng
Propulsion control strategies for ship emergency manoeuvres
MARK
⁎
M. Altosole , M. Martelli Polytechnic School of Genoa University, DITEN, Via all’Opera Pia 11 A, 16145 Genova, Italy
A R T I C L E I N F O
A BS T RAC T
Keywords: Ship propulsion control Simulation based design Slam start Crash stop Engine Propeller pitch
This work deals with the propulsion control aspects relating to some of the most critical emergency manoeuvres of a ship: slam start and crash stop. In these particular situations a very important role is played by the automation system that has to manage the whole propulsive chain (i.e. main engine, mechanical transmission and propeller) in a safe and efficient way. With regard to this, a simulation based design methodology is adopted to develop and test new control schemes for ship propulsion. The proposed control layout is applicable to any type of propulsion systems equipped with controllable pitch propellers, since it is mainly based on the automatic adjustment of the propeller pitch. Thus the desired performance requirements are met through adaptive control strategies able to address the complex issues of slam start, crash stop and similar stressful manoeuvres. The adaptivity of the automation process to several critical propulsive conditions reduces significantly the number of the control parameters to be estimated, as recently demonstrated by the automation design of a new twin-screw ship. For this application, the comparison between simulation results and sea trials data is finally shown for validation design purposes.
1. Introduction Current marine propulsion systems are notable for their high performance and flexibility, difficult features to be achieved without the development of an efficient control system. The large power available to the propellers entails a careful management of the propulsion machinery, in every propulsive condition. Especially during critical manoeuvres (e.g. slam start, crash stop, tight turning circles, …), the automation designers have to develop proper control strategies and set a lot of parameters, normally based on their experience, in several ship propulsion modes. The identification of the proper solution among all the possible combinations is rather difficult and time consuming. In light of this, special control functions, characterized by an adaptive behaviour, could be very useful because they would reduce the number of variables to be assessed. Time-domain simulation can be used to evaluate the effectiveness of these algorithms, especially for the representation of ship critical manoeuvres that could dangerously stress the whole propulsion system (Altosole et al., 2012). Many simulation studies on ship manoeuvrability can be found in the scientific literature but it is not easy to represent every manoeuvre by a single numerical model. An attempt to develop a comprehensive unified versatile mathematical model, suitable for the all types of manoeuvres in still water, has been recently undertaken by Sutulo and Guedes Soares (2015): in their study, the comparisons with full-scale data (available for the full helm turning ⁎
tests, crash stop tests and bow thruster turning of a shuttle LNG carrier) show reliable simulation results, practically without special tuning of the model. On the contrary to what happens for manoeuvrability issues, the machinery behaviour during demanding manoeuvres is rather less investigated in the available literature. The most stressful conditions for the prime mover, propeller and mechanical transmission can be experienced during the ship emergency manoeuvring, as in the case of slam start and crash stop. As well known, the first one is traditionally referred to the vessel acceleration from zero speed to the full power condition, while the second one is the ship stopping, as quickly as possible, starting from the maximum speed of the vessel. Especially during crash stop, usually performed to avoid collisions, the main engine and propeller are subjected to severe stress and loading. From this point of view, relevant scientific papers exist on the propeller structural safety in this particular emergency situation. In the available literature, the prediction of loads on the propeller during crash stop is usually performed by using propeller series charts or, more specifically, CFD analyses, in order to evaluate the structural safety of the blades. In Hur et al. (2011), propeller torque values are estimated by Wageningen B series characteristics and compared with sea trial data, in spite of the difference of the propeller blade shape and flow steadiness between series and recordings. Wageningen results during crash stop provide slightly higher torque values but the discrepancies can be considered marginal in evaluation of the structural safety. However, series charts
Corresponding author. E-mail address: [email protected] (M. Altosole).
http://dx.doi.org/10.1016/j.oceaneng.2017.03.053 Received 26 November 2015; Received in revised form 15 February 2017; Accepted 25 March 2017 0029-8018/ © 2017 Published by Elsevier Ltd.
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Nomenclature
A B Cip C e n n nc poil t KD KI KP Ib Ip M qi QE
QElim Qf Qhyd QP QS QSlim Q−ϕ
yoke area oil bulk modulus oil leakage coefficient Coriolis centripetal matrix error rotational speed rotational speed corresponding to the maximum lever position commanded rotational speed oil pressure time derivative gain integral gain proportional gain moment of inertia of the propeller blade polar inertia ship inertia matrix oil volumetric flow engine torque
Si v Vc xp τH τP τR φ φc φr ∆φ ∆rpm
engine torque limit shaft friction torque hydraulic torque propeller torque shaft torque shaft torque limit torque due to the forces interaction between blade and bearing of the propeller automation signal value ship speed vector chamber volume piston position forces and moments acting on ship hull forces and moments acting on ship hull forces and moments acting on ship rudder propeller pitch commanded propeller pitch propeller pitch reduction value propeller pitch tolerance revolutions per minute tolerance
tion was considered during the control scheme design of an innovative propulsion system (Altosole et al., 2012) characterized by a very flexible use of the different engine types onboard (gas turbine and electric motor). Simulation results are shown and discussed, in order to justify the choice of the proposed special control functions. Similar simulation approaches to represent crash stop dynamics are adopted by Krüger and Haack (2004) and Schoop-Zipfel et al. (2012). In both works, the authors address the negative influence of the wind milling effect (i.e. propeller driven by the water) on the whole propulsion system during the ship stopping but do not provide any details concerning the control procedure to manage this critical situation. The automation logics presented in this study are suitable for CPP propulsion systems, since they are characterized by an adaptive behaviour due to the automatic computation of the propeller pitch reference. By this way, it is possible to drive a wide range of possible heavy accelerations and stopping manoeuvres, as demonstrated by the full-scale validation shown at the end of the article.
cannot predict the pressure distribution on the propeller blade; hence CFD simulation is suggested to represent the hydrodynamic load acting on the propeller. About this, Black and Swithenbank (2009) have examined the water flow velocities, measured during a crash-back test of a model propeller: experimental data, concerning mean and extreme loading conditions, have been used in a strip theory approach to develop loads for finite element analysis, in order to assess stresses on the individual blades. Structural safety of the several propulsion components (propeller, shaft line, thrust-bearing and main engine) can be ensured also by adopting proper control strategies to avoid overloading during critical manoeuvres. From this point of view, numerical simulation can be used to evaluate the effectiveness of original control devices, as reported by Yabuki and Yoshimura (2010) and Wirz (2012). In the first mentioned work, a simulation study is described to evaluate the ship-handling method during the stopping manoeuvre: a turning moment is applied to the ship by the maximum rudder angle steering prior to the reversing operation of the Controllable Pitch Propeller (CPP). The simulation analysis confirms that CPP ships can be sufficiently controlled by the proposed method. The combination of a slow-speed two-stroke diesel engine and a Fixed Pitch Propeller (FPP) is rather disadvantageous from the point of view of the crash stop performance. Consequently, Wirz (2012) proposes and simulates a novel method of applying a braking torque to the FPP by means of water injection into the engine cylinders during unfired operation. As regards the characteristics and requirements of a good control propulsion system, able to prevent overloads and possible failures of the ship machinery, very little was written so far. Banning et al. (1997) introduce a tracking control system aimed at saving fuel and optimizing efficiency. A propulsion control procedure, based on several controllers switching between them to cover the whole operating range of the vessel, is proposed by Lopez et al. (2010). However, except for occasional works, the control issue in marine literature is often addressed from the manoeuvring point of view, such as in the path-following problems (Skjetne et al., 2005; Fossen, 2011) and unmanned surface vehicles (Breivik et al., 2008) but a proper investigation of the engines and actuators behaviour is a key point for the correct evaluation of every ship manoeuvre (Martelli, 2015). In line with the latter consideration, the present article deals with the development of some proper control algorithms for the ship handling during slam start and crash stop. A first theoretical applica-
2. Overall control system and design methodology In this section, the main characteristics of a possible control system layout are described for a generic marine propulsion system. Prime movers can be diesel engines, gas turbines or even electric motors. The controller architecture is based on machinery regulation and protection functions. The purpose of the main propulsive regulation is to provide the proper revolutions signal to the engine, in order to keep the commanded propeller speed value achieving the desired velocity of the vessel. Protection logics aim at preserving propulsion machinery from overloads (i.e. over-torque, over-speed, over-temperature, etc…). All three types of engines above mentioned are usually controlled in terms of their rotational speed. In fact the overall controller calculates the signal reference to the engine governor over time, based on PID algorithms applied to revolutions error between commanded and actual values. This control signal is finally transformed by the governor into the required mechanical torque, by means of acting on the fuel flow in the cases of diesel engines and gas turbines, or on the frequency in the case of electric motors. For the sake of clarity, the main control features are resumed through the control scheme of Fig. 1, referring to the single shaftline of a generic propulsion system equipped with Controllable Pitch Propellers (CPPs).
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Fig. 1. Overall propulsion control scheme.
of the engine torque QE :
The overall controller has to manage propeller pitch as well as prime movers dynamics. The left side of Fig. 1 shows the control signal of the bridge lever position, split into two components, acting on the propeller revolutions and pitch angle respectively. The two signals are modulated over time by ramps. In detail, the ramp function generates a signal that begins to increase, or decrease, at a constant rate (i.e. the slope of the ramp) until the target value is reached. The ramp function is usually required to dampen the dynamic effects on the plant due to the input signals variation. Next, the modulated signals are converted into reference values for propeller revolutions and pitch angle, via the combinator laws (i.e. the steady state numerical correspondence of the lever position with propeller rotational speed and pitch) illustrated in Fig. 1 by the speed and pitch combinator tables. Thus, the two propeller setpoints are compared with the field data to calculate the error signals, to which PID algorithms are applied to obtain the two target values, respectively for the engine governor and propeller pitch change mechanism. Referring to the well-known Eq. (1), the calculation of the PID output Si over the time t is based on the error between setpoint and feedback, through the action of the proportional gain KP, the integral gain KI and the derivative gain KD.
Si(t ) = KPei(t ) + KI
∫0
t
de (t ) ei(t )dt +KD i dt
e2(t ) = QElim − QE (t )
3) Shaft torque protection: i.e. Eq. (1) applied to the error between the shaft torque limit QSlim (the maximum load torque of the shaftline) and the shaft actual torque QS :
e3(t ) = QSlim − QS (t )
(4)
A control function reducing the propeller pitch reference is introduced in case of shaft line over torque. Therefore, the final value of the propeller pitch setpoint φ can be expressed as the difference between the propeller pitch φc (commanded by the combinator) and the correction φr :
φ(t ) = φc(t )−φr (t )
(5)
The pitch reduction is calculated by a PID algorithm too:
φr (t ) = KPe3(t ) + KI
∫0
t
e3(t )dt +KD
de3(t ) dt
(6)
where:
⎧ 0 φ ≤0 r ⎪ φr (t ) = ⎨ φr & φr >0 ⎪ ⎩∆φφr ≥∆φ
(1)
On the top of Fig. 1 it is shown that the final setpoint to the engine governor is calculated as the minimum value among three signals Si, achieved through the following i actions (i=1–3):
(7)
The conditions represented by Eq. (7) are provided by the saturation block illustrated on the bottom of Fig. 1. In such a way, the φc value can be only reduced and not increased. The pitch reduction can never be greater than a limit value ∆φ , decided by the automation designer (anyway ∆φ is relatively small to avoid losing excessive performance in terms of ship speed). In the case of a twin-screw ship, the pitch reduction for over torque protection can be made on the two shaftlines independently: this is why during tight turning circles, the two shaft lines dynamics can be quite different in terms of required power and torque. In accordance with the control scheme of Fig. 1, the numerical values of the several control parameters (i.e. PID gains) are chosen so that overload protection can be firstly achieved by reducing the
1) Shaft speed regulation by means of Eq. (1), applied to the error e1between the commanded rotational speed nc and the actual shaft speed n :
e1(t ) = nc(t )−n(t )
(3)
(2)
2) Engine torque protection: i.e. the signal calculated by Eq. (1), on the basis of the error between the engine torque limit QElim (the maximum continuous torque of the engine) and the actual value
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propeller pitch and secondly by decreasing the fuel flow rate (if the first action is not sufficient), resulting into a rotational speed reference reduction. Proportional, integral and derivative gains are generically named in the text as KP, KI and KD, assuming different numerical values in all the above equations according to their specific task. The proper tuning of such gains is one of the main activities of the automation designer. This task, usually time consuming and expensive, can be facilitated by the use of numerical simulation during the preliminary design phase, although the behaviour of the real hardware on shipboard could be quite different from that one simulated. In accordance with the scheme of Fig. 2, the Central Processing Units (CPUs, i.e. the control units) work in real time, exchanging data with the field via their Input/Output boards (named IO boards in Fig. 2). The automation designer should be sure that the performance foreseen by simulation is maintained in a real ship environment. To this end, it is necessary to limit, as far as possible, most of the differences between CPUs behaviour and numerical simulation. The main discrepancies could be due to: the cyclic time of the CPUs, the different time delay in exchanging data among controllers and the native functions that can be implemented. Further differences could be represented by the presence of many functionalities usually not implemented in the ship numerical model (but that interact with the propulsion control) and the thousands of signals that the automation has to monitor on the real system. To cancel the influence of these kinds of differences on the design process, the Real Time Hardware in the Loop (RT HIL) method can be adopted. The RT HIL simulation, born primarily in the automotive industry, is becoming a standard part of the design process for the propulsion controller of some recent naval vessels, as fully described by Altosole et al. (2007) and Altosole et al. (2010). According to this design approach, the ship propulsion system is simulated by a numerical code that is directly linked to the CPU. In detail, the numerical model is compiled as an executable file, able to perform simulation in real time and installed on the same computer of the real controller. The exchanging of data between controller and propulsion model is possible by using the OPC (i.e. object linking and embedding for process control) protocol. The executable file is an OPC client and reads the command input of the controller that acts as an OPC server. All the parameters exchanged via OPC can be logged to a file, but they are also available to the operator by means of a graphical panel. By this way it is possible to have a comprehensive view of all the working parameters and the designer can have a realistic feedback about the hardware behaviour, before its installation on board. Traditionally, the test and tuning of the real controller is made onboard during the ship delivery period. These trials are time consuming and very expensive, also because they require the full availability of the vessel. By using RT HIL simulation, the physical availability of the ship is not needed, therefore time and costs can be significantly reduced. For the recent applications followed by the authors, the automation designer has selected the numerical values of the main control parameters by using a “trial and error” approach.
3. Control design in emergency manoeuvres A propulsion controller, as represented in Fig. 1, is characterized by many variables to be estimated. In detail, for a telegraph consisting of twenty one possible steps of the lever (i.e. the zero thrust position, ten positions for the ahead running of the vessel and ten for the astern condition), the automation designer has to set the numerical values of the following control parameters: – twenty one values of the shaft speed, corresponding to other twenty one pitch angles of the propeller, to be inserted into the pertinent combinator tables; – ten values of the ramp slopes for the ship acceleration and other ten for the deceleration condition, referring to revolutions setpoint calculation; – twenty slope rates for the ramp referred to the propeller pitch setpoint; – proportional, integral and derivative values of the three PID algorithms to calculate the engine setpoint; – proportional, integral and derivative values of the PID algorithm for the possible pitch setpoint reduction. In addition, at least two propulsion conditions exist for a ship: cruising and manoeuvring, each one represented by a different combinator table. Therefore most of the previous control parameters should be set twice, increasing both complexity and time of the controller design phase. Moreover, the numerical tuning carried out for standard and soft manoeuvres is often not suitable for emergency propulsive conditions as slam start and crash stop. The combinator table, together with the pertinent ramps slopes acting on each signal, can significantly affect the dynamic behaviour of the whole propulsion system during heavy accelerations and decelerations. During this kind of transients, the reference values of propeller revolutions and pitch are commanded by a combinator that is usually designed for the desired steady state performance. Consequently, its numerical values cannot be optimized for non-standard operating conditions. Without a dedicated control logic for the most critical manoeuvres, the propulsion performance can be largely reduced and the desired requirements (e.g. time to reach the maximum ship speed during slam start or stopping space to perform crash stop) may not be met. This could be due to the intervention of several protections of the engine governor, responsible for a sudden cut off of the fuel supply in case of engine over-torque or over-speed. As an example, a similar situation will be further detailed in the paragraph 4.1, to highlight the need of the control optimization process during a typical slam start. Therefore, to improve the control system behaviour also in offdesign conditions, original control functions are introduced and analysed in the following. They are planned to manage heavy acceleration and decelerations of the ship in a safe and efficient way, through a systematic design process able to avoid a further different tuning of all the control parameters, previously listed. The core of the proposed control scheme is represented by the automatic computation of the propeller pitch setpoint on the basis of the actual propeller speed. Thus, a proper combinator table, representing the relationship between pitch and revolutions for all the several lever positions, is no longer required. By preventing the engine over-torque as main objective, it is assumed that other possible kinds of mechanical overloads (e.g. overloads for shaftline and thrust-bearing) will probably be avoided (or at least reduced). In the next sections, the definition of slam start and crash stop is given from the point of view of the automation system, together with the description of the pertinent control logics. In general, the automatic computation over time of the propeller
Fig. 2. Example of a ship propulsion controller architecture.
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Fig. 5. Example of propeller pitch dynamics during a slam start.
Fig. 3. Flow chart of the slam start control logic.
pitch setpoint is based on the introduction of two distinct parameters regarding propeller revolutions: a rotational speed tolerance (in the following named ∆rpm ) to be used for demanding ship accelerations (e.g. slam start) and a reference constant threshold acting during crash stop.
Fig. 6. Example of propeller speed dynamics during a slam start.
The pitch reference computation represents the main core of the control logic during the slam start of the ship. The purpose is to obtain the automatic calculation of the pitch reference value during each heavy acceleration of the vessel, without providing new dedicated combinator tables and ramps slope rates. This is why it would be very difficult to foresee a proper unique combinator law for any possible critical acceleration. The flow chart of Fig. 3 summarizes the whole control process, where the computation of the increasing of the pitch setpoint (i.e. the pitch variation to be added to the initial value) is detailed in Fig. 4. The proposed control function calculates the propeller pitch reference up to its design value, making sure that the actual propeller speed (in Fig. 4 named rpm feedback, i.e. revolutions per minute) follows its increasing setpoint in a smooth and linear way. Referring to Fig. 4, the saturation up to zero for negative errors (between setpoint and actual revolutions) is responsible for the activation of the pitch “freezing”. This condition is studied to be
3.1. Slam start control process In this work, “slam start” condition means every manoeuvre for which the bridge lever is suddenly moved to its maximum position (100%), starting from a step value lower than 70%. On this general basis, slam start manoeuvre can start also when the vessel is moving astern: in this case, both propeller pitch and speed are managed according to a proper combinator law, up to the zero thrust condition of the propeller. On the contrary, if the pitch value φ at the beginning of the manoeuvre is greater than the one corresponding to the zero thrust (φ0), a PID algorithm calculates the propeller pitch reference, while the commanded rotational speed linearly assumes its maximum value via a ramp function.
Fig. 4. Calculation process of the propeller pitch setpoint variation during slam start.
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of the whole propulsion plant dynamics, influenced by the ship motions in six degrees of freedom (i.e. surge, sway, yaw, roll, heave and pitch). The full description of the motion equations can be found in Martelli et al. (2014b), where the ship model validation by specific manoeuvring sea trials (i.e. turning circles, zig zag, etc.) is also discussed. A good correlation between the experimental and simulated values has been experienced. The ship dynamics is deduced by applying the forces and moments equations for a rigid body. Hull, propeller and rudder forces are considered while environmental forces are not taken into account. The added masses are evaluated by means of regression formulas. Given the importance of the control aspects, particular attention has been paid to the numerical modelling of the engine (Altosole et al., 2009, 2014) and the CPP mechanism behaviour (Altosole et al., 2012; Martelli et al., 2014a). Each component of the engine is represented by steady-state performance maps and thermodynamic equations. The dynamics of the engine is influenced by its governor behaviour, that in this study is simulated in accordance with the indications available from the manufacturer. The simulation process can be summarized by solving the following main differential equations:
activated when the CPP actual speed is too far from its setpoint, in order to avoid that any increase of the pitch value results in a sudden and significant drop of CPP revolutions, with a consequent drop in ship performance. The meaning of “pitch freezing” action during a slam start is graphically explained by Fig. 5. The stopping of the pitch setpoint is evident in the whole period in which the propeller speed is too far from its reference value, as shown in Fig. 6. The proposed control strategy allows the increase of the pitch setpoint up to the desired value when the following mathematical condition is met:
n (t )−n(t )−∆rpm<0
(8)
where n(t ) is the actual speed of the propeller depending on time t and n (t ) is the corresponding final setpoint corresponding to the maximum lever position (depending on time t because it is modulated by the ramp over time). When the difference between reference and actual value is lower than ∆rpm , the pitch setpoint grows up to its final value, otherwise a zero signal (produced by the saturation effect) feeds the PID algorithm and consequently the pitch reference increase is stopped (“freezing” action). Numerical simulation allows to tune the value of the speed tolerance ∆rpm .
Mv ̇ + C (v)v = τH + τP + τR
(9)
2πIpn ̇ = QE + QP + Qf
(10)
3.2. Crash stop control process
Ibφ̈ = Qhyd + Qs + Q−ϕ
(11)
As in slam start condition, the definition of crash stop can be extended to several possible critical manoeuvres from the automation point of view. In the present proposal, crash stop means every condition in which the bridge lever is moved from any forward position higher than 20%, up to an astern step at least equal to −100%. This assumption significantly increases the special cases to be analysed by the automation designer, complicating the control optimization process during the design stage. In order to reduce the parameters range to be set for any possible case, the propeller pitch is automatically adapted to the engine revolutions variation, in accordance with the control logic summarized through the flow chart of Fig. 7. As long as the propeller pitch values φ are greater than pitch corresponding to zero thrust (φ0), the pitch setpoint is calculated by the proper function described in Fig. 8, based on a PID algorithm acting on the error between revolutions feedback and a constant threshold, selected by the automation designer. The PID result is added to the initial value corresponding to combinator pitch angle at the beginning of the crash stop manoeuvre. The saturation block illustrated in Fig. 8 allows the pitch freezing if the propeller rotational speed increases too much due to a quick reduction of the pitch angle. At the same time, the shaft dynamics is managed acting on the throttle valve of the engine: if the actual rotational speed is greater than the considered threshold, the engine is immediately commanded to the idle condition; otherwise it is driven by its governor on the basis of the usual and standard speed regulation. On the contrary, for pitch values lower than φ0 (i.e. values corresponding to the astern condition of the vessel), the calculation of both pitch and shaft speed reference values is managed according to the combinator law. In light of the latter, revolutions threshold and combinator values should be chosen high enough to ensure a good astern thrust of the propeller.
Vc p ̇ = q − Cippoil − Axṗ i B oil
(12)
Eq. (9), representing the ship motions in six degrees of freedom, is
4. Simulation results and shipboard application The algorithms previously illustrated have been recently proposed within the control design process of a twin-screw ship propulsion system, equipped with CPPs. In particular, this new automatic control system was implemented into a propulsion simulation code, developed in Matlab-Simulink® environment, that was used for the representation
Fig. 7. Flow chart of the crash stop control logic.
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Fig. 8. Calculation process of the pitch angle setpoint during crash stop.
Fig. 9. Ship speed simulation during slam start.
Fig. 11. Propeller pitch simulation during slam start.
Fig. 10. Shaft speed simulation during slam start.
Fig. 12. Propeller thrust simulation during slam start.
expressed in vector form for sake of compactness (the whole equations system, including hydrodynamic terms, is fully described in Martelli et al., 2014b); v is the ship velocities vector; M is the inertia matrix including added masses; C is the Coriolis centripetal matrix; τH , τP and τR represent forces and moments acting on hull, propeller and rudder. Eq. (10) describes the shaft dynamics for the computation of the propeller rotational speed n , depending on the engine torque QE , the propeller torque QP and the shaft friction torque Qf ; Ip is the polar inertia of the rotating masses involved in the shaftline dynamics. Propeller thrust and torque are simulated by means of the open water diagrams. Under this assumption, the propeller dynamics is only modelled as a consequence of the pitch change mechanism behaviour, represented by Eqs. (11) and (12). In particular, Eq. (11) shows the motion of the propeller blade around its spindle axis in terms of angular acceleration φ̈ , depending on the blade loads (i.e. the hydraulic torque Qhyd acting on the pin slot, the spindle torque Qs and the torque
Q−ϕ that is due to the interaction forces between propeller blade and blade bearing). Ib is the moment of inertia of the blade. In Eq. (12), representing the oil pressure poil that is required to turn or to hold the blade position, qi is the inlet volumetric flow, Cip is the oil leakage coefficient, A is the yoke area, xp is the piston position, B is the oil bulk modulus and Vc is the chamber volume of the actuator. 4.1. Simulation analysis For the same vessel, the authors carried out a sensitivity analysis by simulation (Altosole et al., 2012) that is shown again in this section to analyse the effects of the proposed control logics on the propulsion system performance. Fig. 9–16 deal with a slam start manoeuvre, while Figs. 17–23 illustrate a crash stop. The considered variables are ship and shaft speeds, propeller pitch and thrust, automation signal driving the
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Fig. 13. Engine signal simulation during slam start.
Fig. 16. Engine behaviour comparison between standard and optimum control (slam start).
Fig. 14. Engine torque simulation during slam start. Fig. 17. Ship speed simulation during crash stop.
Fig. 15. Ship speed comparison between standard and optimum control (slam start). Fig. 18. Ship stopping space simulation.
engine governor and the corresponding brake torque. All results are reported as percentages of their maximum values: in particular, the considered maximum torque and thrust correspond to the continuous engine torque limit and to the thrust-bearing limit. The simulated slam start consists in a fast acceleration from zero speed up to full ahead. Three different simulations have been performed, each one with a distinct value of the speed tolerance (i.e. ∆rpm1 < ∆rpm2 < ∆rpm3). The increase of the parameter ∆rpm leads to a positive effect on the ship acceleration, as it is evident in Fig. 9. Figs. 10 and 11 show the propeller revolutions and pitch, following
their corresponding automation setpoints. From Fig. 10 it is possible to derive the slope rate of the ramp considered for the speed reference. The pitch signal is greatly influenced by ∆rpm , given that the freezing action is more significant at low values of ∆rpm . As ∆rpm increases, thrust and torque are closer to their maximum limit values (Figs. 12 and 14). Especially engine torque reaches the 100% in correspondence of the highest ∆rpm value. In conclusion, a too high ∆rpm produces a good ship acceleration but it significantly increases the risk of the engine over-torque. In this
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Fig. 19. Propeller speed simulation during crash stop.
Fig. 22. Engine signal simulation during crash stop.
Fig. 20. Propeller pitch simulation during crash stop.
Fig. 23. Engine torque simulation during crash stop.
Fig. 21. Propeller thrust simulation during crash stop.
Fig. 24. Engine signal comparison (crash stop).
light the speed tolerance value ∆rpm2 could represent a valid compromise to optimise the slam start manoeuvre both from the points of view of the ship performance and engine behaviour. To underline the effectiveness of the proposed control algorithm, the same kind of slam start, but performed in accordance with the traditional control scheme of Fig. 1, is simulated in terms of ship speed (Fig. 15) and working points over the engine load diagram (Fig. 16). In the two figures, the propulsion performance curves, achieved by the optimization corresponding to ∆rpm2 (dash line) and by the standard control (solid line), are compared. Through the comparison, it is
possible to note that the ship acceleration time is very similar (i.e. about 140 s to reach the maximum speed of the vessel) but the standard control scheme is responsible for a worse behaviour of the engine. In fact, during the last part of the manoeuvre, the working points correspond to the maximum power limit of the engine, denoting a saturation of the throttle valve actuator (in Fig. 16, the dash dot line represents the maximum output power and speed - and consequently the maximum torque – available from the engine governor). As known, the saturation on a control system mainly means poor performance and/or even instability (Levine, 2000). Moreover, the engine is forced 107
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Fig. 25. Propeller pitch angle comparison (crash stop).
Fig. 28. Propeller thrust comparison (crash stop).
Fig. 26. Engine speed comparison (crash stop).
Fig. 29. Ship speed comparison (crash stop).
Fig. 19 and Fig. 20 report the propeller behaviour in terms of rotational speed and pitch. The latter is greatly influenced by the revolutions threshold. In detail, the pitch freezing action is evident at the beginning of the manoeuvre and around the zero thrust pitch angle (φ0). The first freezing is due to the actual propeller speed that is higher than threshold value, while the second action is due to the transition to a different pitch setpoint calculation (i.e. the combinator is considered when the actual pitch angle is lower than φ0). In general, the selection of a greater threshold tends to improve the ship stopping performance but also makes the automation signal less stable during the engine acceleration (Fig. 22). In addition, Figs. 21 and 23 show that the threshold variation does not significantly affect the maximum values of the propeller thrust and engine torque.
4.2. Results validation by sea trials data Fig. 27. Engine torque comparison (crash stop).
The control logics developed during the simulation based design have been implemented in the automation software on shipboard. During sea trials, it was possible to achieve the crash stop performance illustrated from Fig. 24 to Fig. 29. In the same figures, also simulation results are reported in order to evaluate the reliability of the design methodology. All the numerical values are given in dimensionless form for confidential reasons. In the considered case, the ship stopping is performed moving the bridge lever from 90% up to its maximum astern position. The general dynamics is well predicted although some differences between simulation and experimental data are present. It should be considered that the final tuning of some important
to work in a high fuel consumption zone. Based on these considerations, the proposed control strategy during heavy ship accelerations results certainly better than the standard control procedure. The same kind of simulation analysis is carried out for the crash stop manoeuvre. Three simulations have been performed, each one characterized by a different value of the revolutions threshold (threshold1 < threshold2 < threshold3). Increasing the threshold value, the ship stopping is faster (Fig. 17). Fig. 18 shows that all three considered thresholds allow to achieve ship stopping distances below 100%, representing the desired requirement for the specific application. 108
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80%. Moreover, the adaptive control can be extended to other propulsive conditions (e.g. accelerations during demanding turning circles) further reducing the design activity. The efforts, due to the simulator development and to the controller optimization, are largely balanced by the savings obtained in time and costs to meet the main requirements of efficiency and safety. The good effectiveness of the method is demonstrated by the comparison between simulation results and sea trials data for a specific application: the positive response suggests that both the model based design procedure and the presented control algorithms can be applied successfully to other new projects.
control parameters (i.e. combinator laws, ramps slope and PID gains) has never been available from the automation provider. Thus the present simulation is performed assuming the same numerical identification carried out during the control design stage and previously discussed (only the threshold value of shaft revolutions was confirmed to be equal to threshold2). In this light, the comparison is certainly affected by the not exact correspondence between simulation and actual input data, however other interesting considerations can be made. In particular, Fig. 24 shows an early starting of the engine in comparison with simulation, due to a different calculation of the propeller pitch setpoint. The latter, in the real system, is characterized by a faster decreasing (Fig. 25): therefore the zero thrust pitch and consequently the engine starting are reached about six seconds earlier than simulation. Since the pitch setpoint is calculated through the error between a constant threshold of the propeller revolutions and the actual rotational speed, the time discrepancy between the two pitch behaviours is essentially due to a different representation of the shaftline dynamics by simulation. Experimental data of Fig. 26 show an earlier revolutions drop that could mean an imperfect modelling of the propeller load to the engine. In this regard, it is proper to underline that the propeller thrust and torque are simulated through the open water characteristics, so the shaft dynamics equation is solved by using a steady state representation of the propeller torque. This approach is usually reliable to simulate ship soft manoeuvres but it may lose precision for fast decelerations and accelerations of the vessel. An even better agreement between simulation and sea trials could be achieved considering a dynamic model for the propeller performance description. The final oscillation of the engine speed (solid line of Fig. 26) is due to the instability of the engine signal, and therefore of the engine torque, in the last part of the manoeuvre (Fig. 24 and Fig. 27). It may be a consequence of the interaction between the overall controller and the engine governor. Simulation does not reproduce this behaviour, probably because of a not very accurate modelling of the engine governor (e.g. different numerical values of the PID gains between reality and simulation). The different behaviour of the simulated propeller pitch and speed affect also the thrust, especially during the first period of the manoeuvre. In detail, the simulation result of Fig. 28 reports a lower thrust of the propeller from the beginning up to fifty seconds and a higher negative magnitude at the end. This final overestimation leads to a minor stopping time of the vessel in comparison with sea trials data, as evident in Fig. 29.
Acknowledgements The authors wish to thank SEASTEMA S.p.A. (Fincantieri Company) and Italian Navy for the support received during the research activity and the sea trials campaign. References Altosole, M., Bagnasco A., Figari, M., Maffioletti, L., 2007. Design and test of the propulsion control of the aircraft carrier “Cavour” using real-time hardware in the loop simulation. In: Proceedings of the EuroSiw 2007. June 2007, Genoa, Italy. Altosole, M., Benvenuto, G., Campora, U., Figari, M., 2009. Real-time simulation of a COGAG naval ship propulsion system. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 223 (1), 47–62. Altosole, M., Dubbioso, G., Figari, M., Michetti, S., Millerani Trapani, A., Viviani, M., 2010. Simulation of the dynamic behaviour of a CODLAG propulsion plant. In: Proceeding of Warship 2010 Conference. London, UK. Altosole, M., Figari, M., Martelli, M., Orrù, G., 2012. Propulsion control optimisation for emergency manoeuvres of naval vessels. In: Proceedings of the 11th International Naval Engineering Conference and Exhibition, INEC 2012. May 2012, Edinburgh, UK. Altosole, M., Campora, U., Martelli, M., Figari, M., 2014. Performance decay analysis of a marine gas turbine propulsion system. J. Ship Res. 58 (3), 117–129. Banning, R., Johnson, M.A., Grimble, M.J., 1997. Advanced control design for marine diesel engine propulsion systems. J. Dyn. Syst.-T ASME 119 (2), 167–174. Black, S., Swithenbank, S., 2009. Analysis of crashback forces compared with experimental results. In: Proceedings of the 1th International Symposium on Marine Propulsors (SMP’09). June 2009, Trondheim, Norway. Breivik, M., Hovstein, V.E., Fossen, T.I., 2008. Straight-line target tracking for unmanned surface vehicles. Model Ident. Control 29 (4), 131–149. Fossen, T.I., 2011. Nonlinear maneuvering theory and path-following control. Mar. Technol. Eng. 11 (2011), 445–460. Hur, J.W., Lee, H., Chang, B.J., 2011. Propeller loads of large commercial vessels at crash stop. In: Proceedings of the 2nd International Symposium on Marine Propulsors (SMP’11). June 2011, Hamburg, Germany. Krüger, S., Haack, T., 2004. Design of propulsion control systems based on the simulation of nautical manoeuvres. In: Proceedings of the 9th Symposium on Practical Design of Ships and Other Floating Structures. Luebeck-Travemuende, Germany. Levine, W.S., 2000. Control System Fundamentals. CRC Press LLC, USA. Lopez, M.J., Garcia, L., Lorenzo, J., Consegliere, A., 2010. Design methodology based on H∞ control theory for marine propulsion system with bumpless transfer function. WSEAS Trans. Syst. 9 (3), 253–262. Martelli, M., 2015. Marine Propulsion Simulation: Methods and Results. Walter de Gruyter GmbH & Co KG, Berlin, Collection: engineering. Martelli, M., Figari, M., Altosole, M., Vignolo, S., 2014a. Controllable pitch propeller actuating mechanism, modelling and simulation. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 228 (1), 29–43. Martelli, M., Viviani, M., Altosole, M., Figari, M., Vignolo, S., 2014b. Numerical modelling of propulsion, control and ship motions in 6 degrees of freedom. Proc. Inst. Mech. Eng. Part M: J. Marit. Environ. 228 (4), 373–397. Schoop-Zipfel, J., Abdel-Maksoud, M., Tigges, K., 2012. Stopping simulations and sea trial measurements of a ship with diesel-electric propulsion and controllable pitch propellers. In: Proceedings of International Conference on Marine Simulation and Ship Manoeuvrability (MARSIM 2012). April 2012, Singapore. Skjetne, R., Fossen, T.I., Kokotović, P.V., 2005. Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory. Automatica 41 (2), 289–298. Sutulo, S., Guedes Soares, C., 2015. Development of a core mathematical model for arbitrary manoeuvres of a shuttle tanker. Appl. Ocean Res. 51, 293–308. Wirz, F., 2012. Optimisation of the crash-stop manoeuvre of vessels employing slowspeed two-stroke engines and fixed pitch propellers. J. Mar. Eng. Technol. 11 (1), 35–43, (9). Yabuki, H., Yoshimura, Y., 2010. On the control of CPP ships by steering during inharbour ship-handling. Trans. Nav. 4 (2), 157–162.
5. Conclusions The article provides general control schemes to drive CPP propulsion systems during standard and emergency manoeuvres of a vessel. The proposed algorithms are evaluated through numerical simulation, providing a realistic feedback before the installation on board of the real control system. An overview of the several control parameters, to be set by the automation designer, is given in reference to a generic propulsion plant: simulation shows that their numerical tuning, carried out for standard and soft manoeuvres, can hardly meet high and safe performance requirements also during the most critical transient conditions. Therefore, in order to avoid a new and demanding evaluation of the several parameters, special control strategies are proposed for the most stressful manoeuvres (slam start and crash stop). They are essentially based on the introduction of a reference rotational speed, to be used for the automatic calculation of the propeller pitch setpoint. Compared to a standard control procedure, the two algorithms, developed for fast accelerations and ship stopping, lead to a reduction of the parameters number to be estimated around
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