System design and energetic characterization of a four-wheel-driven series–parallel hybrid electric powertrain for heavy-duty applications

Energy Conversion and Management 106 (2015) 1264–1275

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Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman

System design and energetic characterization of a four-wheel-driven series–parallel hybrid electric powertrain for heavy-duty applications Enhua Wang a,b, Di Guo c, Fuyuan Yang a,⇑ a

State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Qinghuayuan, Beijing 100084, China Systems, Power & Energy Research Division, School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK c Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Hubei 430070, China b

a r t i c l e

i n f o

Article history: Received 13 July 2015 Accepted 20 October 2015 Available online 11 November 2015 Keywords: Series–parallel hybrid powertrain Hybrid electric vehicle Topology design System analysis Energy efficiency Supercapacitor

a b s t r a c t Powertrain topology design is vital for system performance of a hybrid electric vehicle. In this paper, a novel four-wheel-driven series–parallel hybrid electric powertrain is proposed. A motor is connected to the differential of the rear axle. An auxiliary power unit is linked to the differential of the front axle via a clutch. First, a mathematical model was established to evaluate the fuel-saving potential. A rulebased energy management algorithm was subsequently designed, and its working parameters were optimized. The hybrid powertrain system was applied to a transit bus, and the system characteristics were analyzed. Compared to an existing coaxial power-split hybrid powertrain, the fuel economy of the four-wheel-driven series–parallel hybrid powertrain can be at the same level under normal road conditions. However, the proposed four-wheel-driven series–parallel hybrid powertrain can recover braking energy more efficiently under road conditions with a low adhesive coefficient and can alleviate the torsional oscillation occurring at the existing coaxial power-split hybrid powertrain. Therefore, the fourwheel-driven series–parallel hybrid powertrain is a good solution for transit buses toward more robust performance. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction Vehicle electrification is gaining popularity in the global vehicle market and has the potential to reduce lifecycle energy consumption and greenhouse gas emissions [1]. Currently, the mileage and lifetime of a pure electric vehicle are still less than those of a conventional vehicle. Therefore, using HEVs to save energy and improve the environment is a feasible and necessary approach. The fusion of electric machines into powertrains greatly diversifies powertrain architectures and enriches the means of saving energy. Essentially, series, parallel, power-split, and series–parallel hybrid powertrains are currently in used [2]. The main architectures of the hybrid powertrains for heavy-duty applications are shown in Fig. 1. A basic series hybrid topology is shown in Fig. 1a. A motor is connected to the driving axle to propel the vehicle or recover braking energy. An engine and a generator are combined as an auxiliary power unit (APU), which can provide electric energy to the power line. Two parallel hybrid topologies are shown in Fig. 1b and c, respectively. An engine is linked to the powertrain via a clutch. If the clutch is disengaged, the entire system operates ⇑ Corresponding author. Tel./fax: +86 10 6278 5708. E-mail address: [email protected] (F. Yang). http://dx.doi.org/10.1016/j.enconman.2015.10.056 0196-8904/Ó 2015 Elsevier Ltd. All rights reserved.

in the pure electric mode; otherwise, the engine and the electric propelling system output energy together to drive the vehicle. A dual-mode hybrid powertrain developed by Allision and GM that operates based on the power-split principle is shown in Fig. 1d [3]. A series–parallel hybrid powertrain for heavy-duty transit bus applications was studied by Ouyang et al., and the topology is given in Fig. 1e. When the clutch is disengaged, the system works in the series control mode. Once the clutch is engaged, the system switches to the parallel control mode [4]. The performance of a plug-in series hybrid electric powertrain developed for urban buses was evaluated through experimental tests, and impressive energy savings are achieved [5]. Damiani et al. studied a mild parallel hybrid powertrain adopting an intelligent transmission control and start/stop control and found that the fuel consumption can be reduced by 23% [6]. Bishop et al. also indicated that a parallel hybrid powertrain could obviously reduce fuel consumption [7]. Finesso et al. investigated the energy efficiency of a four-wheel-driven parallel hybrid powertrain [8]. Asaei presented the design, simulation, and manufacturing of a throughthe-road parallel hybrid electric motorcycle with a brushless direct current motor in the front wheel [9]. A full hybrid electric motorcycle with power split e-CVT was studied by Chung and Hung, and a maximum fuel economy improvement of 32% was obtained

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Nomenclature A C CD F f g hg i J L La Lb m P q Q R rd s T t U v W

vehicle frontal area (m2) capacitance (F) aerodynamic drag coefficient tractive force (N) rolling resistance coefficient standard gravitational acceleration (9.8067 m/s2) height of center of gravity of the vehicle speed ratio, current (A) inertia (kg m2) wheelbase distance between front axle and center of gravity of the vehicle distance between rear axle and center of gravity of the vehicle vehicle mass (kg) power (W) instantaneous fuel consumption (kg/s) equivalent fuel consumption (L/100 km) resistance (X) wheel radius (m) slip of a tire torque (N m) time (s) voltage (V) vehicle velocity (m/s) normal load acting on the axle

Greek letters a road angle (°) b ratio of front axle braking force to total braking force d mass factor g efficiency (%) l tractive force coefficient of a tire

[10]. All of these studies were concentrated on series, parallel, or power-split hybrid powertrains. Few of them focused on the four-wheel-driven hybrid architecture. To the best of our knowledge, no series–parallel hybrid topology was investigated. In fact, Hutchinson et al. analyzed 44 hybrid cars available in the US and found that most of the hybrid architectures are mild parallel and power-split hybrid powertrains at present [11]. Supercapacitors are the most direct method to store electricity, offering fast response with lifecycles of tens of thousands and very high efficiency, which make them very suitable for transit buses to smooth the short-term high-frequency fluctuations [12]. Supercapacitors are not only used for HEVs but also for other energy storage applications such as wind energy systems [13]. An equivalent circuit model is preferred to calculate the general performance of a supercapacitor instead of a detailed high-order model such as that proposed by Drummond et al. [14]. Sedlakova et al. designed a second-order two-branch equivalent circuit, and the results of NessCap supercapacitors show that the relative error is less than 5% [15]. Generally, rule-based strategies can be successfully used in the energy management of independent microgrids [16]. Similarly, this type of strategy can also be used for an HEV. Shabbir and Evangelou used a control map for the optimal power share between the engine and batteries [17]. Zhang et al. presented a sliding mode controller for a series hybrid powertrain [18]. An intelligent management system was designed using a fuzzy logic controller by Khayyama and Bab-Hadiashar [19]. On the other hand, a rulebased control can be combined with an optimal approach to form

q x

air density (kg/m3) angular speed of a tire

Subscripts bf braking force of the front axle br braking force of the rear axle clt clutch df driving force of the front axle dr driving force of the rear axle eng engine f front, fuel fd front differential gen generator mot motor r rear rd rear differential sc supercapacitor Acronyms APU auxiliary power unit CNG compressed natural gas CTBCDC Chinese transit bus city driving cycle DC/AC direct current/alternating current inverter ESS energy storage system e-CVT electronic continuous variable transmission FWD four-wheel-driven HEV hybrid electric vehicle ICE internal combustion engine OOL optimal operation line PMSG permanent magnetic synchronous generator PMSM permanent magnetic synchronous motor RWD rear-wheel-driven SOC state of charge

a suboptimal strategy for real-time applications. Torres et al. developed a rule-based optimal controller for a plug-in hybrid electric vehicle [20]. The optimal problem was calculated offline in advance. Hemi et al. employed Pontryagin’s minimum principle and the Markov chain approach for the optimal energy management of a fuel cell/supercapacitor electric vehicle [21]. These rule-based control strategies can be implemented within a very short time. However, they must be optimized by a wide range of tests before being actually used. Recently, more advanced optimal algorithms such as nonlinear programming [22], gravitational search [23], and artificial bee colony [24] were applied to the energy management systems for islanded microgrids. However, the effectiveness of these approaches for an HEV is still not estimated. In our previous investigation, the performance of a coaxial series–parallel hybrid powertrain was analyzed [4]. The coaxial series–parallel hybrid powertrain is a very high-efficiency topology for a transit bus under normal road driving conditions. However, if running on an icy road with a low adhesive coefficient, the acceleration time will be extended, and the recovered braking energy will obviously decrease. On the other hand, the engine, generator, clutch, and motor are connected by a long axle, which may cause serious vibration. Torsional oscillation is a common problem for HEVs owing to quick transient processes in which some of the components must alter their output torques swiftly [25], especially if a clutch is adopted [26]. To reduce the torsional oscillation of the coaxial series–parallel hybrid powertrain and improve the energy efficiency and driving

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Fig. 1. Architectures of hybrid electric powertrain for heavy-duty applications.

performance under bad road conditions, a novel four-wheel-driven series–parallel hybrid powertrain is proposed in this study. First, the system architecture is presented, and a mathematical model is established. A rule-based energy management strategy is then designed. Finally, the system characteristics and energy efficiency are evaluated. The results indicate that the designed hybrid powertrain is a promising solution for transit buses.

2. System description The architecture of the designed four-wheel-driven series– parallel hybrid powertrain for a transit bus is shown in Fig. 2. The hybrid powertrain system consists of a compressed natural gas (CNG) engine, a permanent magnetic synchronous generator (PMSG), a permanent magnetic synchronous motor (PMSM), a

Fig. 2. Topology of the designed four-wheel-driven series–parallel hybrid powertrain.

E. Wang et al. / Energy Conversion and Management 106 (2015) 1264–1275

clutch, and an energy storage system (ESS). The PMSM is linked to the differential of the rear axle and can be used to drive or brake the transit bus. The output shaft of the PMSG is associated with the CNG engine via a single reduction gear unit. The output shaft of the APU is connected to one end of the clutch axle, and the other end of the clutch is linked to the differential of the front axle. The motor and the generator connect to the power line via two bidirectional DC/AC inverters. The energy storage system (ESS) can supply or absorb electric energy to the power line. The main technical parameters of the designed four-wheeldriven series–parallel hybrid powertrain are listed in Table 1. The internal combustion engine is a 6.5 L YC6J190 CNG engine manufactured by Yuchai Machinery Co., Ltd. The supercapacitor pack consists of three parallel groups, each of which is serially composed of 13 units of Maxwell 48 V modules. Both the PMSG and the PMSM are low-speed high-power electric machines designed by Jing-Jin Electric Technologies Co., Ltd. 3. Mathematical model To analyze the energetic characterization of the four-wheeldriven series–parallel hybrid powertrain, a methodology to establish the mathematical model of the system is presented. For the purpose of fuel economy estimation, quasi-static models based on efficiency maps measured under stationary operation of the various components are sufficient to assess the system performance of an HEV [27]. Hence, in this study, a lumped-parameter model was set up based on the working principle of the overall system. 3.1. Vehicle dynamics To evaluate vehicle performance, many standard driving cycles are defined by vehicle velocity as a function of time. In this study, a standard driving cycle is employed whose vehicle velocity profile is used as an input variable. The tractive force of the vehicle F can then be determined, which is a summation of the rolling resistance, aerodynamic resistance, grade resistance, and acceleration force according to the longitudinal dynamics equation [28].

1 dv F ¼ mg cos aðf 1 þ f 2 v Þ þ qAC D v 2 þ mg sin a þ dm 2 dt

ð1Þ

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v is the vehicle speed, q is the air density, A is the vehicle frontal area, CD is the aerodynamic drag coefficient, and d is the mass factor considering the equivalent mass increase due to the angular moments of the rotating components. 3.2. Wheel and axle For the designed four-wheel-driven series–parallel hybrid powertrain, the vehicle control strategy is in charge of driving force distribution on the front and rear axles. When the vehicle is not braking, the tractive force is positive, and the driving force of the rear axle Fdr is determined by




F dr ¼

F;

if the clutch is disengaged

F  F df ; if the clutch is engaged

ð2Þ

If the clutch is disengaged, all driving force is provided by the rear axle. If the clutch is engaged, the driving force of the rear axle is the difference between the overall driving force and the front axle. The driving force of the front axle Fdf is supplied by the output torque of the APU and is specified by the energy management strategy. When the vehicle is braking, the tractive force is negative, and the braking forces of the front and rear axles are determined by Eqs. (3) and (4), respectively.

F br ¼ bF

ð3Þ

F bf ¼ ð1  bÞF

ð4Þ

where b is the braking force distribution coefficient, which is specified to ensure that the front tires are locked first to maintain the drive stability of the vehicle under various road adhesive conditions. In this study, according to the transit bus design parameters, b is set to 0.461. Because slip phenomenon occurs when a tire is rotating, the angular speeds of the front and rear axles must be computed according to the vehicle velocity and the tire slip. In this study, the tire slip is expressed as a function of the road adhesive coefficient. Therefore, the road adhesive coefficients of the front and rear axles must be determined first. According to vehicle dynamics theory, the front axle load Wf and the rear axle load Wr can be expressed by [28]

where m is the vehicle mass, g is the standard gravitational acceleration, a is the road angle, f1 and f2 are rolling resistance coefficients,

Wf ¼

   Lb hg rd mg cos a  F  Fr 1  L L hg

ð5Þ

Table 1 Technical specifications of the four-wheel-driven series–parallel hybrid powertrain.

Wr ¼

   La hg rd mg cos a þ F  Fr 1  L L hg

ð6Þ

Component

Parameter

Value

Unit

Engine

Type Rated power Rated speed Maximum torque Peak efficiency

YC6J190 CNG engine 140 2500 650 36.8

– kW r/min Nm %

Supercapacitors

Type Number of modules Energy capacity Rated voltage Voltage range

Maxwell 48 V module 39 2.115 624 300624

– – kW h V V

Type Rated power Rated speed Maximum torque Peak efficiency

Jing-Jin electric PMSM 150 3000 2100 93.5

– kW r/min Nm %

Type Rated power Rated speed Maximum torque Peak efficiency

Jing-Jin electric PMSG 135 3000 850 94.5

– kW r/min Nm %

Motor

Generator

where hg is the height of the gravity center of the vehicle, rd is the effective radius of the wheel, L is the wheelbase of the vehicle, La and Lb are the distance between the front and rear axles and the gravity center of the vehicle, and Fr is the rolling resistance. The road adhesive coefficient l for each of the tires can be obtained based on the tractive force F and the corresponding axle load W.

l¼

F ¼ f l ðsÞ W

ð7Þ

The slip of the tires s can be computed as the inverse function of fl, which is stored as a one-dimensional lookup table similar to that of the software Advisor [29]. Finally, when a vehicle is running, the angular speed of the tire x can be calculated by

(

x¼

v

½r d ð1sÞ

v ð1sÞ rd

;

; if dv =dt > 0 otherwise

ð8Þ

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specified by the energy management strategy. Hence, the effective power can be computed during the driving cycle.

3.3. Rear differential If the driving force of the rear axle Fdr and the rotating speed

xrd,out are obtained, the input torque Trd,in and speed xrd,in of the rear differential are determined according to the speed ratio ird and the inertia Jrd.

dxrd;out 1 ¼ ðird T rd;in  F dr rd Þ J rd dt

ð9Þ

xrd;in ¼ ird xrd;out

ð10Þ

3.4. Motor Because the motor is connected to the rear differential, the output variables of the motor equal the input variables of the rear differential. Considering the motor inertia Jmot, the rotating speed of the motor is computed by

  dxmot 1 Pmot  T mot ¼ J mot xmot dt

ð11Þ

where Pmot is the input electric power and can be calculated according to the output mechanical power and the motor efficiency, which is modeled as a function map of the output torque and speed of the motor. If the motor outputs mechanical power, the input electric power Pmot is positive. Otherwise, it is negative for the generating state.

(

P mot ¼

xmot T mot gmot ðxmot ;T mot Þ ;

if dv =dt > 0

xmot T mot gmot ðxmot ; T mot Þ; otherwise

ð12Þ

3.5. Front differential Similar to the rear differential model, once the driving force of the front axle Fdf and the rotating speed xfd,out are calculated, the input torque and speed of the front differential can be computed with regard to the inertia on the output shaft Jfd and the speed ratio ifd.

dxfd;out 1 ¼ ðifd T fd;in  F df rd Þ J fd dt

ð13Þ

xfd;in ¼ ifd xfd;out

ð14Þ

  dxeng 1 Peng  T eng;out ¼ J eng xeng dt

Subsequently, the instantaneous fuel consumption qeng is determined from a 2-dimensional map whose data are measured via engine tests.

qeng ¼ f ðxeng ; Peng Þ

R Tc

Q eng ¼

qeng dt R Tc qf 0 v dt

ð19Þ

0

where Tc is the duration time of the driving cycle. 3.8. Generator The mathematical model of the generator is similar to that of the motor. The rotating speed of the generator is determined according to the input torque and the output electric power.

  dxgen 1 Pgen T gen;in  ¼ J gen dt xgen

ð20Þ

xgen ¼ i1 xeng

ð21Þ

where i1 is the speed ratio of the single reduction gear unit between the generator and the engine. The output electric power Pgen is defined as a function map of the generator speed xgen and torque Tgen,in.

Pgen ¼ xgen T gen;in ggen ðxgen ; T gen;in Þ

dxclt;in 1 ðT clt  T fd;in Þ ¼ J clt;in dt dxclt;out 1 ðT eng;out  T clt  T gen;in Þ ¼ J clt;out dt

ð15Þ

The energy storage system consisting of supercapacitors can be modeled as a one-order RC circuit with time-dependent series resistance and capacitance if the long-term dynamics and current leakage are ignored. Given the stored energy power of the supercapacitors Psc, the energy equation of the supercapacitor circuit is expressed as

ð23Þ

where Rsc is the equivalent series resistance, Usc is the output voltage of the ESS, and isc is the current of the ESS. The current of the ESS is then obtained by

isc ¼

U sc 

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi U 2sc  4Rsc P sc 2Rsc

ð24Þ

The state of charge (SOC) of the supercapacitors is denoted by

SOC ¼ ð16Þ

ð22Þ

3.9. Supercapacitors

2

Because the clutch is linked to the front differential, the output variables of the clutch equal the input variables of the front differential. Meanwhile, the input variables of the clutch are consistent with the output of the APU. Therefore, the model of the clutch is expressed by

ð18Þ

Next, the overall fuel consumption can be calculated according to the total fuel quantity and the driving distance. With regard to the CNG engine, the equivalent fuel consumption Qeng is determined using the density of diesel fuel qf:

Rsc isc  U sc isc þ Psc ¼ 0

3.6. Clutch

ð17Þ

U sc U sc;max

R

¼

isc dt C sc U sc;max

ð25Þ

Finally, the state equation of the ESS is expressed by

3.7. CNG engine

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 4Rsc P sc dSOC SOC  SOC  Usc;max ¼ dt 2Rsc C sc

The CNG engine model considers the engine speed xeng according to the engine output torque and the effective power generated by the fuel combustion process. The engine output torque Teng,out is

The SOC of supercapacitors is proportional to its output voltage. However, if batteries are used, a complicated algorithm is required to estimate the SOC [30]. Usually, a Kalman filter-based method can achieve sufficient online precision [31].

where Tclt is the torque transferred by the clutch.

ð26Þ

E. Wang et al. / Energy Conversion and Management 106 (2015) 1264–1275

4. Energy management strategy The designed energy management strategy for the four-wheeldriven series–parallel hybrid powertrain is shown in Fig 3. If the vehicle velocity is less than a prescribed value, the hybrid powertrain system operates in the series mode to utilize the highefficiency characteristics of the electric propulsion path. If the vehicle velocity exceeds the set value, the parallel control mode is activated. Once the vehicle is working in the braking state, the energy management strategy switches to the braking control mode to make both electric machines work in the generating mode. Therefore, the vehicle kinetic energy can be recovered completely. Normally, the control strategies for the series control mode are the thermostatic control, the power follower control, and the optimal control [32]. The most used control methods for the parallel control mode are the parallel electric assist control, the adaptive control, and the fuzzy logic control. Studies show that the performance of the rule-based control strategy can approximate that of the optimal control after the optimization of the parameters of the rule-based control [33]. Therefore, in this study, a rule-based control strategy for the four-wheel-driven series–parallel hybrid powertrain is designed. 4.1. Series control mode The series control mode uses a power follower control and its control flowchart is shown as the left branch of Fig. 3. First, the control strategy of the series mode disengages the clutch. The driving power demand of the vehicle is then computed according to the required vehicle velocity. Subsequently, the engine on/off state is decided based on a power follower control method according to the driving power demand and the SOC of the ESS. If the engine is set to off state, the motor must supply the total driving power of the vehicle. Herein, the motor control unit regulates the field current according to the motor speed to output the required driving power. Meanwhile, the control module of the ESS determines the output power and the new SOC. If the energy management strategy configures the engine to the on state, the engine output power is calculated, including the correction power with regard to SOC deviation. After that, the engine output torque and speed are determined according to the optimal operation line (OOL) defined previously. Because the output variables of the engine equal the input variables of the generator, the control unit of the generator regulates the output electric power according to the input torque and speed values. The motor alone provides the driving torque of the vehicle; thus, the energy management strategy sets the output power of the motor equivalent to the driving power demand, which is executed by the motor control unit. Finally, the control module of the ESS regulates the output current according to the power difference between the motor and the generator, and a new SOC value is calculated. 4.2. Parallel control mode If the vehicle velocity is greater than the set value, the system changes to the parallel mode control. A parallel electric assist control strategy is used in this research and is shown as the middle branch of Fig. 3. First, the engine state is decided according to the vehicle velocity, the driving power demand of the vehicle, and the SOC of the ESS. If the energy management strategy sets the engine to the off state, the clutch must be disengaged, and the engine control unit shuts down the engine. The control modules of the motor and the ESS then regulate the working currents, and a new SOC value and bus voltage are calculated. If the engine is set to the on state, the energy management strategy notifies the

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engine control unit to start the engine and engage the clutch. Subsequently, considering the correction power of the SOC deviation, the target output torque of the engine is determined based on the required vehicle velocity, and the engine control unit regulates the practical output torque. Then, if the SOC is less than the midpoint of the operation range, the generator will start and output the required charge power. Finally, the control modules of the motor and the ESS regulate the output powers according to the commands of the energy management strategy. 4.3. Braking control mode If the energy management strategy judges the vehicle to be braking, the designed four-wheel-driven series–parallel hybrid powertrain can use the generator and the motor to recover the braking energy simultaneously. The detailed control strategy is shown as the right branch of Fig. 3. The braking force distribution between the front and rear axles is performed by the energy management strategy. First, the engine is shut off, and the clutch is engaged. The motor is then set to the generating state. The input torques of the generator and the motor are determined according to Eqs. (3) and (4). The output powers of both the generator and the motor are stored by the ESS. Finally, the ESS control module computes the new SOC value and bus voltage. 5. Results and discussion The energetic characterization of a coaxial series–parallel hybrid powertrain was investigated previously [4]. In this study, to improve the energy recovery efficiency during regenerative braking under low road adhesive coefficient conditions, a new four-wheel-driven series–parallel hybrid powertrain is proposed. Using the established mathematical model and energy management strategy, an analysis program was developed based on Matlab/Simulink and Advisor. The system performance of the four-wheel-driven series–parallel hybrid powertrain is estimated using the standard Chinese Transit Bus City Driving Cycle (CTBCDC) [34], which is used to describe typical bus drivers’ behaviors in Chinese urban areas. Furthermore, the results are compared with the coaxial series–parallel hybrid powertrain using the same energy management strategy. The main parameters of the transit bus are given in Table 2. The estimated vehicle performance is shown in Fig. 4. The target and available vehicle speeds are given in Fig. 4a. The available vehicle speed was computed using the developed program, and the results show that the available speed can follow the target speed perfectly. The acceleration performance of the four-wheel-driven hybrid powertrain can obviously fulfill the vehicle requirements. The driving power demand of the vehicle is given by the blue solid lines of Fig. 4b. By contrast, the output power of the CNG engine is also shown by the red1 dashed lines. When the vehicle is driving, the power demand of the vehicle increases with the vehicle velocity, and the CNG engine operates intermittently. When the vehicle is working in the parallel hybrid mode, a large part of the output power of the CNG engine is used to drive the vehicle, and the remaining power is used to charge the ESS. The system operation modes are shown as Fig. 5a, where 0 represents the series mode and 1 denotes the parallel mode. If the vehicle driving velocity is greater than 30 km/h, the operation mode switches from the series mode to the parallel mode. Meanwhile, the engine states are given in Fig. 5b, where 0 represents the off state and 1 denotes the on state. The hybrid powertrain 1 For interpretation of color in ‘Figs. 4, 6, 8, 10 and 12’, the reader is referred to the web version of this article.

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Fig. 3. Control strategy for the four-wheel-driven series–parallel hybrid powertrain.

Table 2 Parameters of the transit bus. Parameter

Value

Unit

Vehicle mass Dimensions Rolling resistance coefficient Aerodynamic drag coefficient Vehicle frontal area Wheel radius Final gear

18,000 12  2.55  3 0.0094 0.70 7.65 0.506 5.833

kg mmm – – m2 m –

system operates in the pure electric mode if the CNG engine is off. From the results of Fig. 5, both the series mode and the parallel mode can switch to the pure electric mode. A comparison of the engine performance between the fourwheel-driven series–parallel hybrid powertrain and the coaxial series–parallel hybrid powertrain is shown in Fig. 6, where the thin red lines denote the results of the four-wheel-driven series– parallel hybrid powertrain, and the thick blue lines represent the results of the coaxial series–parallel hybrid powertrain. In addition, the FWD in the legend denotes the four-wheel-driven series– parallel hybrid powertrain, while the RWD represents the coaxial

Fig. 4. Vehicle performance of the four-wheel-driven series–parallel hybrid powertrain.

E. Wang et al. / Energy Conversion and Management 106 (2015) 1264–1275

Fig. 5. System operation modes and engine states.

Fig. 6. Engine performance comparison between the four-wheel-driven series– parallel hybrid powertrain (FWD) and the coaxial series–parallel hybrid powertrain (RWD).

series–parallel hybrid powertrain; these two abbreviations are also used for the following figures. The engine output powers are given in Fig. 6a. The variation tendencies of the engine output power are similar for these two hybrid powertrains. For the time intervals

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694–700 s and 813–821 s, only the engine of the four-wheeldriven series–parallel hybrid powertrain is started. The results of the engine speed and torque during the driving cycle are compared in Fig. 6b and c, respectively. In the series mode, the engine speed and torque vary along the OOL because the power following strategy is used. In the parallel mode, the engine speed must be proportional to the vehicle velocity, and the engine output torque maintains a high level of 506.1–650 N m if the engine state is on. The hybrid powertrain shown in Fig. 1(e) uses only one axle to drive the vehicle, and the traction control is relatively simple compared to a four-wheel-driven powertrain. However, when the vehicle is braking, a hybrid powertrain with one driving axle can recover the braking energy of only the driving axle. For instance, if an ice road is encountered, to ensure that the rear wheels lock later than the front wheels to maintain the vehicle’s stability, only a small part of the braking energy will be recovered by the oneaxle-driven hybrid powertrain. In this study, the designed fourwheel-driven hybrid powertrain can still recover most of the braking energy due to a reasonable distribution of the braking forces between the front and rear axles because each of the vehicle axles is connected to an electric machine. On the other hand, to reduce the torsional oscillation problem of the one-axle-driven coaxial series–parallel hybrid powertrain, a damper is mounted between the engine and the generator as shown in Fig. 1(e). Because the driving and braking forces are assigned to the front and rear axles of the four-wheel-driven hybrid powertrain, respectively, this problem can be decreased, and the working life can be extended. The driving torque profile of the rear axle for the coaxial series– parallel hybrid powertrain is shown in Fig. 7a. All driving and braking torques are imposed on the rear axle when the vehicle is running. The corresponding rate of the driving torque is given in Fig. 7b. The maximum driving torque of the coaxial series–parallel hybrid powertrain is 1717 N m, and the corresponding maximum rate of the driving torque is 1795 N m/s. The maximum braking torque is 1725 N m, and the corresponding maximum rate is 1874 N m/s. The results of the four-wheel-driven series–parallel hybrid powertrain are given in Fig. 7c–f. The driving torque of the rear axle is shown in Fig. 7c. Compared to the coaxial series– parallel hybrid powertrain, the driving torque of the rear axle decreases slightly. However, the braking torque of the rear axle drops significantly. The maximum driving torque is 1465 N m, a decrease of only 14.7% compared to the coaxial series–parallel hybrid powertrain. The maximum braking torque is 954 N m, a decrease of 44.7%. The rate of the driving torque for the rear axle is shown in Fig. 7d. Correspondingly, the maximum rate of the driving torque is 1460 N m/s, and the maximum rate of the braking torque is 1307 N m/s. Both are apparently decreased. The driving torque of the front axle is shown in Fig. 7e. It is found that most of the output torque of the engine is delivered to the front axle when the clutch is engaged. This will be helpful to enhance the overall efficiency. During the braking process, a considerable part of the braking torque is inputted to the front axle. The corresponding torque rate of the front axle is shown in Fig. 7f. During the driving cycle, the maximum driving torque and its rate for the front axle are 641 N m and 714 N m/s, respectively. The maximum braking torque and its rate are 816 N m and 855 N m/s, respectively. The performance of the ESS for the four-wheel-driven series– parallel hybrid powertrain is displayed by the thin red lines and the results of the coaxial series–parallel hybrid powertrain are shown by the thick blue lines in Fig. 8. The output powers of the ESS are shown in Fig. 8a, where positive values represent the discharging process and negative values denote charging. Essentially, the output power of the ESS varies with the power demand of the vehicle. The maximum and minimum output powers of the fourwheel-driven series–parallel hybrid powertrain are 116.8 kW and 204.4 kW, respectively. By contrast, the maximum and minimum

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Fig. 7. Comparison of the driving torques between the four-wheel-driven series–parallel hybrid powertrain (FWD) and the coaxial series–parallel hybrid powertrain (RWD).

Fig. 8. ESS performance comparison between the four-wheel-driven series–parallel hybrid powertrain (FWD) and the coaxial series–parallel hybrid powertrain (RWD).

output powers of the coaxial series–parallel hybrid powertrain are 116.5 kW and 140.1 kW, respectively. When the vehicle is braking, the charging power of the four-wheel-driven hybrid powertrain is larger than that of the coaxial series–parallel hybrid

powertrain. The SOC profile for the ESS is shown in Fig. 8b. During the driving cycle, the SOC of the four-wheel-driven hybrid powertrain varies from 0.89 to 0.58 whereas the SOC of the coaxial series–parallel hybrid powertrain ranges from 0.88 to 0.58. Because

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Fig. 9. Comparison of the electric machines between the four-wheel-driven series–parallel hybrid powertrain (FWD) and the coaxial series–parallel hybrid powertrain (RWD).

the output voltage of the supercapacitors is proportional to the SOC, the variation tendency of the bus voltage shown in Fig. 8c is similar to the SOC profile. In summary, the supercapacitors can be charged or discharged with large power in a short time, which is very helpful for braking energy recovery. In addition, the bus voltage changes with the SOC of the ESS. Therefore, to ensure that the bus voltage is greater than 300 V, the energy management strategy must set a relatively high value for the lower SOC limit. The currents of the ESS are displayed in Fig. 8d. During the driving cycle, the maximum charging current of the four-wheel-driven hybrid powertrain is 463.5 A, and the maximum discharging current is 299.5 A. By contrast, the maximum charging and discharging currents of the coaxial series–parallel hybrid powertrain are 276.0 A and 303.2 A, respectively. The charging current of the ESS for the four-wheel-driven hybrid powertrain is greater than the coaxial series–parallel hybrid powertrain because the charging power of the four-wheel-driven hybrid powertrain is larger. The performance results of the motor and the generator for the four-wheel-driven series–parallel hybrid powertrain are shown in Fig. 9. When the motor output power is positive, the vehicle is driven by the motor. The motor output power basically follows the vehicle driving power demand except for the conditions in which the engine starts and the clutch is engaged. The working currents of the motor are given in Fig. 9b. The maximum currents for the driving and braking states are 292.1 A and 276.1 A, respectively, for the four-wheel-driven hybrid powertrain. The maximum currents for the driving and braking states of the coaxial series– parallel hybrid powertrain are 292.4 A and 286.5 A, respectively. The input powers of the generator are shown in Fig. 9c. Most of the time, the input power of the four-wheel-driven series–parallel hybrid powertrain is generated by the braking process, and the others are caused by the generating state in the series control mode. Therefore, compared with the results of the coaxial series– parallel hybrid powertrain, the operation frequency of the generator for the four-wheel-driven hybrid powertrain is obviously increased. The generator currents are shown in Fig. 9d. Considering

the four-wheel-driven hybrid powertrain, the output current for the series control mode is apparently greater than that of the braking control mode because the engine output power is very high for the series control mode so that the engine working efficiency can be improved. To evaluate the potential of fuel savings for the designed fourwheel-driven series–parallel hybrid powertrain, the fuel consumptions of three various powertrains are computed using the CTBCDC driving cycle, and the results are listed in Table 3. Compared to the conventional powertrain powered only by a John Deere 6081H CNG engine, the fuel consumption of the four-wheel-driven series–parallel hybrid powertrain can be decreased by 47.45% and the coaxial series–parallel hybrid powertrain can even decline by 50.87%. The working efficiencies of the motor of the coaxial series–parallel hybrid powertrain for the braking process are relatively high because all braking torques are absorbed by the motor. However, the average efficiencies of the motor and the generator of the four-wheel-driven hybrid powertrain are less than those of the coaxial series–parallel hybrid powertrain because the braking torques are split to the motor and generator. If the motor and generator can be redesigned for the operation conditions of the four-wheel-driven hybrid powertrain, the fuel economy of this powertrain will increase further. The reason for such great fuel economy of the four-wheeldriven hybrid powertrain is explained from the viewpoint of

Table 3 Results of fuel consumption.

a

Powertrain

Fuel consumption (l/ 100 km)

Energy reduction (%)

Conventional powertraina Coaxial power-split hybrid Four-wheel-driven series– parallel hybrid

46.39 22.79 24.38

50.87 47.45

A John Deere 6081H CNG engine is used.

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Fig. 10. Engine efficiency map and its operating points.

energy efficiency. The effective thermal efficiency map of the YC6J190 CNG engine measured on an engine test bench is shown in Fig. 10. The green line in Fig. 10 is the OOL line of the series control mode, and the engine working points are given as well. If the series control mode is activated, the engine operates along the OOL line. On the other hand, taking into account the parallel control mode, the engine runs within a high-load region in which the engine speed varies from 900 to 1842 r/min. As a result, it is because the engine can work in the high-efficiency region and the braking energy can be fully recovered that the four-wheeldriven series–parallel hybrid powertrain can achieve such good fuel economy. The motor efficiency map and its working points are given in Fig. 11. Compared to the results of the coaxial series–parallel hybrid powertrain, the maximum output torque of the motor apparently decreases. The generator efficiency map and the corresponding working points are shown in Fig. 12, where the red points denote the series control mode, the blue points represent the parallel control mode, and the green points indicate the braking control mode. The generator speed increases because of the single reduction gear unit, which is beneficial for improving the generator efficiency during the driving cycle. 6. Conclusions

Fig. 11. Motor efficiency map and its operating points.

In this study, the system design of a four-wheel-driven series–parallel hybrid powertrain was presented for a transit bus application, and the energetic performance is evaluated using the established mathematical model. The equivalent fuel consumption of the designed four-wheel-driven series–parallel hybrid powertrain decreases significantly by approximately 47.45% compared to a conventional powertrain. Only a front differential is additionally required in comparison with a coaxial series–parallel hybrid powertrain. The other components are the same. Therefore, the relative error of the curb mass between these two powertrains is less than 1%, which will not apparently affect the vehicle performance. Because the fourwheel-driven series–parallel hybrid powertrain can recover the braking energy during the driving state even under low road adhesive coefficient conditions and can alleviate the torsional oscillation problem of the coaxial series–parallel hybrid powertrain, it is a more robust and promising technology for heavy-duty HEVs. In this study, the ESS is set to a large capacity to recover the braking energy completely, which leads to a high cost. In the future, a more advanced optimal energy management strategy must be used, and the effects of the ESS size will be evaluated. References

Fig. 12. Generator efficiency map and its operating points.

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