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The effects of operating conditions and structural parameters on the dynamic, electric consumption and power generation characteristics of an electric assisted bicycle
Applied Energy 247 (2019) 285–296
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Applied Energy journal homepage: www.elsevier.com/locate/apenergy
The effects of operating conditions and structural parameters on the dynamic, electric consumption and power generation characteristics of an electric assisted bicycle Nguyen Ba Hung, Ocktaeck Lim
T
⁎
School of Mechanical Engineering, University of Ulsan, Ulsan 44610, Republic of Korea
H I GH L IG H T S
operation of an EAB is described by dynamic models and battery model. • The of input parameters on the electric consumption of the EAB are investigated. • Effects for electric power generation is conducted using a modeling approach. • AAnstudy • experimental study for motion and electric consumption of the EAB is conducted.
A R T I C LE I N FO
A B S T R A C T
Keywords: Electric assisted bicycle Bicycle dynamic models Sprocket transmission ratio Regenerative energy
A study is conducted to examine the motion, dynamic and electric consumption characteristics of an electric assisted bicycle based on the effects of certain operating conditions and structural parameters. Simulation models for operation of the electric assisted bicycle, including dynamic models of the electric assisted bicycle and battery models, are established. These simulation models are solved by MATLAB-Simulink to provide the operating characteristics of the electric assisted bicycle. Based on the established mathematical models, the motion, dynamic and electric consumption of the electric assisted bicycle are analyzed and optimized under the effects of slope, bicycle mass, wheel radius, crank length, and sprocket transmission ratio. The simulation results show that the dynamic performance and electric consumption of the electric assisted bicycle are significantly improved by reducing the bicycle mass, wheel radius, and increasing the sprocket transmission ratio. The dynamic performance and electric consumption are optimal when the slope grade, bicycle mass, wheel radius, crank length, and sprocket transmission ratio are 0%, 12 kg, 0.32 m, 0.17 m and 3.43, respectively. A study for using the regenerative energy generated during the downhill movement of the electric assisted bicycle to create electrical power is presented under the effects of rider mass and slope angle. An experimental study is also conducted to examine the motion and electric consumption characteristics of the electric assisted bicycle under real operating conditions. This study shows agreement between simulation and experimental results at the same initial conditions.
1. Introduction Environmental pollution is becoming a major concern for many countries around the world. One of the main pollution sources is vehicles with internal combustion engines using as diesel and gasoline, which cause toxic emissions such as hydrocarbons (HC), nitrogen oxides (NOx), carbon monoxide (CO), and particulate matter (PM) [1–5]. Another important issue is energy security [6–10]; depletion of fossil fuels and global warming caused by exhaust emissions from fossil-
⁎
fueled vehicles are motivating researchers worldwide to investigate and develop alternative fuels as well as new types of vehicles. One promising solution is the use of electric bicycles (EBs), which help reduce the toxic emissions and address the energy security problems [11–15]. EBs are receiving great worldwide attention due to their many benefits. In general, the EBs are not only suitable for driving on many varied terrains such as flat, hilly, and mixed terrains, but also more practical than other electric vehicles in terms of accessibility, price, maintenance, and repair costs [16]. Besides, the EB market is a rising market and is
Corresponding author. E-mail address: [email protected] (O. Lim).
https://doi.org/10.1016/j.apenergy.2019.04.002 Received 4 December 2018; Received in revised form 19 March 2019; Accepted 5 April 2019 0306-2619/ © 2019 Published by Elsevier Ltd.
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expected to further grow in the future. According to a report from Navigant Research [17], China is predicted to become the world’s largest EB market, with an average sale of about 30 million units from 2016 to 2025, which is much higher than in the rest of the world. Many auto companies are also interested in the EB field, including Ford, Honda, Peugeot, Mercedes, BMW, Volkswagen, Opel, Hyundai, Lexus, and General Motors [18]. Jamerson and Benjamin [18] estimate that EB sales will rise to 130 million by 2025 and 800 million by 2100. Electric bicycles can be classified into three main types: pure EB, power-assisted bicycle or electric assisted bicycle (EAB), and EB with two modes, pure and power-assisted. The pure EB utilizes an electric motor installed on the bicycle frame or wheels, and the driving power is controlled through a handlebar throttle. The rider simply twists the handlebar throttle to drive the pure EB without any human power, making this type very convenient. However, the pure EB has high electric consumption because its driving power is generated only by the electric motor. Furthermore, the pure EB might not be suitable for the rider who seeks the health benefits of bicycle use. The EAB, also called a pedelec (pedal electric cycle), is an EB in which an electric motor installed on the bicycle frame or wheels assists the rider when pedaling. Because the electric motor is used only as power assistance, the motor power of a pedelec is usually less than that of a pure EB. For people living in hilly areas or riders need some assistance or want to exercise to improve health, pedelecs are especially useful. Many previous studies on EABs have been conducted [11,12,14,19–28]. Hung et al. [11] studied the effects of input parameters on the dynamics and required power of an EAB equipped with an electric motor installed on the rear wheel. They also conducted a simulation and experimental study of the operating performance of an EB integrated with a nine-speed semi-automatic transmission [12]. Cardone et al. [19] presented dynamic models and controller designs based on torque control of an EAB, in which the input was voltage to the electric motor. A performance evaluation of an EAB was conducted by Muetze et al. [20], in which the total power required by the EAB was examined under the effects of rider mass, slope, and wind speed. Abagnale et al. [21] presented a performance and environmental analysis of an EAB compared to a thermal moped. Cheon and Nam [22] presented a model-based control method to assist human force acting on an EAB without using torque sensors, in which a power assist control algorithm was designed based on a PI-type feedback controller, an inverse model-based feed forward controller, and a pedaling torque observer. These previous studies provided useful information in the study and design of EABs, but they rarely mentioned the effects of operating conditions and design parameters on EAB electric consumption, which is an important factor in the design of a highly efficient EAB. In addition, the regenerating energy is also one of interesting subjects for studying highly efficient EABs, however it was rarely mentioned in the previous studies. This paper presents a simulation study of the motion, dynamic and electric consumption characteristics of an EAB under the effects of certain operating conditions and design parameters, specifically slope, bicycle mass, wheel radius, crank length and sprocket transmission ratio. Therein, sprocket transmission ratio is a transmission ratio between a front sprocket and rear sprockets of the EAB, which is calculated based on the number of teethes on the front and rear sprockets. Simulation models, including dynamic and battery models, are established to describe the operation of the EAB. These models are calculated and solved by a code programmed in MATLAB-Simulink. Based on the solutions of the simulation models, an optimal analysis for dynamic performance and electric consumption is conducted under the effects of the operating conditions and design parameters mentioned above. Besides, a study for using the energy generated during the downhill movement of the electric bicycle to create electrical power is presented. An experimental study is also conducted to examine the motion and electric consumption characteristics of the EAB.
Fig. 1. Force analysis model of the EAB.
2. Simulation study 2.1. Dynamic models of the electric bicycle Fig. 1 shows a force analysis model of the EAB, in which the rider’s power is assisted by an electric motor during pedaling. The specification parameters of the EAB are illustrated in Table 1. The motion of the bicycle obeys Newton’s second law, which is described by:
Fp − Fs − Fw − Fr = M
d 2x dt 2
(1)
where Fp is the propulsion force, Fs is the slope resistance force, Fr is the rolling resistance force, Fw is the wind resistance force, x is the moving distance of the electric bicycle, M is the total mass of the electric bicycle (Mb) and rider (Mr), and t is time. The slope resistance force is calculated by: (2)
Fs = 9.81MG where G is the slope grade (%) [20]. The wind resistance force is calculated by:
Fw =
1 Cd DA (vw + vg )2 2
(3) 3
where Cd is the coefficient of drag, D is the density of air (kg/m ), A is the frontal area (m2), vw is the wind speed (m/s), vg is the ground speed (m/s) [29]. The rolling resistance force is calculated by: (4)
Fr = 9.81MCr cos α
where Cr is the rolling resistance coefficient [29], α is the slope angle (°) The propulsion force is calculated by:
Fp·Rw = Tp = Tr + Tm
(5)
where Tp is the propulsion torque (N·m), which is the total of rider Table 1 Specification parameters of the EAB.
286
Parameters
Values
Electric bicycle mass, kg Crank length, m Wheel radius, m Number of speed Motor power, W Battery type Battery nominal voltage, V Rated capacity
21 0.17 0.33 7 250 Li-ion 36 9.3 Ah
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Fig. 2. Force analysis models of the EAB.
Fig. 3. Effects of slope grade on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
torque (Tr) and motor torque (Tm) generated when pedaling. Based on Fig. 1, Tr can be expressed as follows:
Tr = Fch Rrg
Tr =
1 1 Lc Fh cos θfg = Lc Fh cos θfg Rfg γRrg
Rfg
Lc Fh cos θfg =
1 Lc Fh cos θfg γ
(8)
This EAB uses a DC electric motor installed in the rear wheel. The electric motor receives the control signals detected by rider’s torque when pedaling to generate a motor torque, which assists the rider’s power. The dynamics of the DC electric motor are modeled by Eqs. (9) and (10) [30]:
(6)
where Fch is the chain force, and Rrg is the radius of the rear gear. Based on the force analysis model of the EAB shown in Fig. 1, Fch can be calculated as:
Fch =
Rrg
dia + ia (t ) Ra + Kb ωm = Ua dt
(9)
dωm + B1 ωm + Tm = Kb ia (t ) dt
(10)
La (7)
J
where Rfg is the radius of the front gear, Lc is the length of the crank, Fh is the human force, Rrg is the radius of the rear gear, and γ is the sprocket transmission ratio. By combining Eqs. (6) and (7), the rider torque can be derived as follows:
where ia is the armature current, Ra is the armature resistance, Ua is the terminal voltage of the DC motor, La is the armature inductance, Kb is the back EMF constant, J is the torque of inertia, B1 is the viscous friction coefficient, Tm is the motor torque acting on the shaft of the rear 287
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Fig. 4. Effects of EAB mass on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Fig. 5. Effects of wheel radius on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Fig. 6. Effects of crank length on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
wheel, and ωm is the speed of the motor. By combining Eqs. (5), (8), (9), and (10), the propulsion force can be derived as follows:
Fp =
2.2. Battery model A lithium-ion battery is used to provide the input voltage to the electric motor. The battery model used in this study is described by a discharge model [31,32] which presents the decrease of battery voltage as a function of current. The discharge model of the lithium-ion battery is described by Eq. (12) [31,32]:
1 1 ⎡ Kb Tr + Tm K L di dω = Lc Fh cos θfg + Ua − b a a −J m Rw γRw Rw ⎢ Ra dt dt ⎣ Ra K2 − ⎜⎛B1 + b ⎟⎞ ωm⎤ Ra ⎠ ⎥ ⎝ ⎦
(11) 288
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Fig. 7. Effects of sprocket ratio on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Vb = E0 − K
Q Q i (t ) − K i ∗ − Ri + Ae (−Bi (t )) Q − i (t ) Q − i (t )
Fd = Mt g sin β (12)
where Fd is the downhill force and Frg is the rolling resistance force caused by roller of the DC generator. In the case of moving downhill, the electrical power is generated, and its model is described through the differential equations below [34]:
where Vb is the battery voltage, E0 is the battery constant voltage, K is the polarization constant, Q is the battery capacity, i(t) is the actual battery charge (i(t) = ʃidt), A is the exponential zone amplitude, B is the exponential zone time constant inverse, R is the internal resistance, i is the battery current, and i* is the filtered current.
Eg = k g ωg φ
2.3. Dynamic and electrical power generation models when moving downhill
d 2x dt 2
d 2x dt 2
diag
TL = kL Iag φ
Ts = TL + Jg
dt
(17) (18)
dωg dt
+ Bωg
(19)
Vt = Iag RL
(20)
Pt = Vt Iag
(21)
where Eg is the total of generated voltage, kg is the voltage constant, ωg is the speed of DC generator, φ is field flux, Vt is the terminal voltage, Lag is the armature inductance, Iag is the armature current, Rag is the armature resistance, TL is the load torque, kL is the load constant, Ts is the shaft torque, Jg is the moment of inertia, B is viscous friction, RL is the load resistance, and Pt is generated power. 2.4. Simulation results 2.4.1. Effects of operating conditions and design parameters Slope grade (G) directly affects the motion of the electric bicycle due to its relationship with the slope resistance force shown in Eq. (1). The effects of slope grade on the velocity and moving distance of the EAB are shown in Fig. 3(a). The bicycle velocity significantly reduces by about 8.1% when the slope grade is increased from 0% to 1.74%. This is because the slope resistance force is increased when the slope grade is increased. Furthermore, increasing the slope grade also requires more energy to overcome the slope resistance force. Thus, the propulsion torque is increased, as shown in Fig. 3(b). Increasing the slope grade results in a greater electric consumption through battery voltage reduction, as shown in Fig. 3(c). This is explained by the increased torque acting on the motor to overcome the slope resistance force. As shown in Fig. 13(c), the battery voltage is considerably decreased in 10 s for each slope grade due to the small initial rider torque. The battery voltage is then increased again to reach a stable value depending on slope grade. This is because the load on the motor is increased due to the increased rider torque when pedaling. During the stable period (from 40 s to 60 s), the electric consumption
(13)
where Mt is the total mass of EAB, rider, load and DC generator When the EAB moves on the slope terrain, it is moved downhill by itself due to the influence of gravitational force, while the propulsion force cause by pedaling is eliminated. Therefore, the force analysis model in this case is described by the following equations:
Fd − Fr − Fw − Frg = Mt
(16)
Vt = Eg − Rag Iag − Lag
When the EAB moves downhill, the propulsion force caused by pedaling could be eliminated, and the EAB moves by itself due to the influence of gravitational force. The energy generated by the downhill movement could be wasted if it is only used to move the EAB. Therefore, this section presents an idea for using the wasted energy of the EAB when moving downhill to generate electrical power which could be used for charging a battery. In this study, a DC (direct current) generator is selected for generating electrical power because it has advantages over AC (alternating current) generator such as low weight and no conversion of supply is required from AC to DC [33]. Fig. 2 shows force analysis models when the EAB moves on flat and slope terrains. As shown in Fig. 2, the DC generator is installed on the bicycle frame, which is detached from the front wheel tire to avoid the rolling resistance force caused by the DC generator when the EAB moves on the flat terrain. When the EAB moves downhill, the DC generator is contacted with the front wheel tire through a roller located at the top of the DC generator. Thus, the downhill movement of the EAB will turn the roller of the DC generator and generate electrical power. To determine the electrical power generation, the output of the DC generator is connected to a load as shown in Fig. 2. In this study, the EAB moves continuously on both flat and slope terrains, in which the EAB will be oriented to move on the slope terrain after 40 s of running on the flat terrain. When the EAB moves on the flat terrain, its force analysis model is described by the following equation:
Fp − Fs − Fw − Fr = Mt
(15)
(14) 289
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Fig. 8. Effects of rider mass on (a) the velocity and (b) the moving distance of EAB.
increases 0.25% when the slope grade is increased from 0% to 1.74%. The EAB mass (Mb) is a design parameter that directly affects the motion of the EAB due to its relationship with inertial force, as shown in Eq. (1). The effects of EAB mass on velocity, moving distance, propulsion torque, and battery voltage are shown in Fig. 4. As shown in Fig. 4(a), the velocity and moving distance of the EAB slightly increases by 1.4% and 3.3%, respectively when EAB mass is reduced from 24 kg to 12 kg. The increase of the velocity and moving distance is explained by the decrease of inertial force when EAB mass is reduced. Besides, when the EAB mass is reduced from 24 kg to 12 kg, the propulsion torque decreases by 0.47% due to the decrease of inertial force caused by the reduced EAB mass, as shown in Fig. 4(b). The increase of bicycle mass results in a slight increment of electric consumption through a small reduction of battery voltage, as shown in Fig. 4(c). Based on these results, the bicycle mass Mb = 12 kg is selected as an input parameter for the next investigations.
Fig. 9. Effects of rider mass on (a) DC generated current (b) DC generated voltage and (c) DC generated power.
Wheel radius (Rw) is the second design parameter selected to investigate because it relates to rotational inertia of the wheel as well as EAB motion. Fig. 5 describes the effects of wheel radius on velocity, moving distance, propulsion torque, and battery voltage of the EAB. As
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Fig. 10. Effects of slope angle β on (a) the velocity and (b) the moving distance of EAB.
can be observed in Fig. 5(a), the bicycle velocity increases by 3.39% when the wheel radius is reduced from 0.36 m to 0.32 m. In addition, the increase of wheel radius results in an increase in propulsion torque, as shown in Fig. 5(b). This is because the larger wheel radius has higher rotational inertia and so requires a higher input of energy to obtain a certain velocity. However, the input energy is constant due to the same rider mass; thus, bicycle velocity and distance decrease, while propulsion torque increases when wheel radius is increased. It can be found that the electric consumption increases by about 0.41% through a reduction of battery voltage when the wheel radius is increased from 0.32 m to 0.36 m, as shown in Fig. 5(c). This is because the load torque on the motor is increased to overcome the rotational inertia of the wheel when the wheel radius is increased. Based on the obtained results, the wheel radius Rw = 0.32 m is selected as one of input parameters for the next investigation.
Fig. 11. Effects of slope angle β on (a) DC generated current (b) DC generated voltage and (c) DC generated power.
Crank length (Lc) is the third design parameter selected to investigate because it relates to propulsion force of the EAB, which is shown in Eq. (11). The effects of crank length on velocity, moving distance, propulsion torque, and battery voltage of the EAB are depicted in Fig. 6, in which Lc is changed from 0.110 m to 0.170 m. The initial 291
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Fig. 12. Experimental system setup for the EAB.
12 kg, 0.32 m, 0.17 m, and 3.43, respectively. 2.4.2. Motion and electrical power generation characteristics 2.4.2.1. Effects of rider mass. The effects of rider mass on the motion characteristics are shown in Fig. 8, in which the rider mass is varied at 47 kg, 57 kg, 67 kg, 77 kg and 87 kg, while the initial conditions including wind speed, air density, bicycle mass and wheel radius are 0 m/s, 1.225 kg/m3, 21 kg and 0.32 m, respectively. As shown in Fig. 8, slope angle β is changed from 0° to 5° after the electric bicycle moved stably at 40 s. It can be seen that, the velocity of the electric bicycle has a decreased trend and then obtain stable value for each rider mass, including Mr = 47 kg, Mr = 57 kg and Mr = 67 kg. This is because when the EAB moves downhill, the propulsion force cause by pedaling is eliminated, and thus the bicycle velocity is temporarily decreased. Afterwards, the rider mass as well as gravitational force will help the EAB to maintain its stable velocity. It can be seen that the decreased trend is reduced when the rider mass is increased from 47 kg to 67 kg due to the increased gravitational force. As can be seen in Fig. 8(a), when the rider mass is increased to 87 kg, the velocity of the electric bicycle has an increased trend just after β is adjusted to 5°, and then obtains a stable value which is higher than bicycle velocity at the slope angle of 0°. As the result, the moving distance is significantly increased when the rider mass is changed from 47 kg to 87 kg, as shown in Fig. 8(b). Fig. 9 shows the electrical generation characteristics of the DC generator. The simulation results show that the DC generated current, voltage and power start to increase when the DC generator is contacted with the front wheel tire of electric bicycle during movement downhill with the slope angle of 5°. It can be found that the generated current, voltage and power of the DC generator are increased 20.6%, 20.6% and 36.9%, respectively when the rider mass is changed from 47 kg to 87 kg, as shown in Fig. 9(a), (b), and (c).
Fig. 13. Road test for the EAB.
conditions including slope grade, rider mass, wind speed, EAB mass, sprocket transmission ratio, air density and wheel radius are kept at 0%, 57 kg, 0 m/s, 12 kg, 3.43, 1.145 kg/m3, and 0.32 m, respectively. Fig. 6(a) and (b) show that the bicycle velocity is increased 3.4%, while the maximum propulsion torque is increased 10.3% when Lc is changed from 0.110 m to 0.170 m. This is because the propulsion force is increased, which is proportional to the crank length, as shown in Eq. (11). Fig. 6(c) shows that the increase of crank length results in a smaller decrement of battery voltage during the stable stage, which implies that a lower electric consumption could be obtained by increasing the crank length. The increase of crank length results in the increase of bicycle velocity as well as the load on the motor. As the result, it reduces the voltage supplying to the motor during the stable stage. The sprocket ratio, which is denoted by γ, is the fourth design parameter that directly affects the dynamics and thus the electric consumption of the EAB because of its relationship with the propulsion torque. The effects of sprocket ratio on the velocity, moving distance, propulsion torque, and battery voltage of the EAB are shown in Fig. 7. By adjusting the sprocket ratio from 2.18 to 3.43, the velocity and moving distance are significantly increased, by about 28.02% and 27.69%, respectively, as shown in Fig. 7(a). A smaller sprocket ratio results in a larger propulsion torque, as shown in Fig. 7(b). In addition, the electric consumption is increased by about 0.82%, which is illustrated through a reduction of battery voltage when the sprocket ratio decreases from 3.43 to 2.18, as shown in Fig. 7(c). This can be explained by the decrease of bicycle velocity as well as load on the motor, which results in the increase of the voltage supplying to the motor when the sprocket ratio is changed from 3.43 to 2.18. Based on the results obtained, the optimal sprocket ratio is 3.43. In summary, dynamic performance and electric consumption of the EAB are optimized when the key parameters including slope, bicycle mass, wheel radius, crank length and sprocket ratio are adjusted at 0%,
2.4.2.2. Effects of slope angle β. Fig. 10 describes the effects of slope on the motion characteristics of the EAB, in which the rider mass is kept at 87 kg which was optimized in the previous section. Fig. 10 shows that the moving distance and velocity of the electric bicycle are same during 40 s of running because the propulsion force caused by pedaling is used, while the slope angle β is kept constant with the value of 0°. As shown in Fig. 10, when β is still kept 0° after 40 s of running, the velocity of the EAB is reduced to zero, while the moving distance is constant because the propulsion force caused by pedaling is eliminated in this stage. When β is adjusted to a certain value larger than 0°, the moving distance and velocity of the electric bicycle are different for each value of β. When β is increased from 3° to 9°, the moving distance and bicycle velocity are significantly increased when compared with that of the 292
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Fig. 15. Effects of sprocket ratio on (a) moving distance and (b) bicycle velocity.
the DC generator, as shown in Fig. 11. When β is increased from 3° to 9°, the generated current, voltage and power are increased 45.4%, 45.4%, and 70.2%, respectively.
3. Experimental study 3.1. Experimental system setup An experimental system for the EAB is illustrated in Fig. 12. This experimental system includes an EAB equipped with a lithium-ion battery and a DC electric motor installed in the rear wheel. In addition, the EAB is also equipped with signal processing and measurement devices to collect experimental data. A photoelectric sensor LM393 is installed on the bicycle frame, which is used to detect EAB motion. This sensor is provided by a 5 V DC source from an electronic control unit (ECU). The signals from the photo sensor are sent to the ECU which is connected to a computer containing LabVIEW program to calculate the motion characteristics of the EAB, such as velocity and moving distance. Meanwhile, an NI-9221 voltage input module with sample rate of 800 kS/s [35] is used to measure battery voltage when the EAB is in motion. The measurement signals of NI-9221 are transferred to the computer to collect battery voltage data. The EAB experiment is conducted on a test road as shown in Fig. 13.
Fig. 14. Comparison between simulation and experiment in (a) moving distance, (b) bicycle velocity, and (c) battery voltage.
slope angle of 0° due to the considerable increase of gravitational force caused by the increased slope angle β. The generated current, voltage and power start to increase with the various values depending on the varied slopes. The significant increase of bicycle velocity leads to the considerable increase of the generated current, voltage and power of 293
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Fig. 17. Effects of rider mass on (a) moving distance and (b) bicycle velocity.
battery voltage of the EAB, are compared with the corresponding simulation results in the same initial conditions, specifically wind speed vw = 0 m/s, slope grade G = 0%, rider mass Mr = 57 kg, bicycle mass Mb = 21 kg, radius of wheel Rw = 0.33 m, crank length Lc = 0.17 m, and sprocket ratio γ = 3.43. These results are described in Fig. 14. As can be seen in Fig. 14, the experimental results show the same trends as the simulation results in moving distance, velocity, and battery voltage. Both the experiment and the simulation show that battery voltage is significantly reduced in 10 s to assist rider power because of the small initial rider torque when pedaling. When rider torque is increasing, the load on the motor also increases so that it reduces the voltage supplying to the motor. Thus, battery voltage increases again after declining to a certain value, as shown in Fig. 14(c). In this experiment, the fluctuation of experimental battery voltage could be due to the fluctuation of experimental velocity caused by the sudden appearance of wind speed.
3.2.2. Effects of sprocket ratio The effects of sprocket ratio (γ) on motion characteristics of the EAB are shown in Fig. 15, in which the sprocket ratio is varied at 2.18, 2.66 and 3.43, while the initial conditions, including wind speed, slope grade, rider’s mass, EAB’s mass, crank length, and wheel radius, are 0 m/s, 0%, 57 kg, 21 kg, 0.17 m, and 0.33 m, respectively. The experimental results are similar to the simulation results for moving distance of the EAB, as shown in Fig. 15(a). When the sprocket ratio decreases from 3.43 to 2.18, both the experiment and the simulation shows reduction of moving distance. This is because the velocity of the EAB is
Fig. 16. Effects of sprocket ratio on battery voltage with (a) γ = 3.43, (b) γ = 2.66, and (c) γ = 2.18.
3.2. Experimental results 3.2.1. Comparison between experimental and simulation results The experimental results, including moving distance, velocity, and 294
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corresponding simulation results at the different rider masses. When the rider mass is increased from 57 kg to 67 kg, both the experiment and the simulation shows an increase of moving distance. This is because the velocity of the EAB is increased when the rider mass is increased, as shown in Fig. 17(b). For the rider mass of 57 kg, the experimental distance is a little smaller than the simulated distance. This is because the experimental velocity is a little smaller than the simulated velocity, which could be caused by the sudden appearance of wind speed. Fig. 18 shows experimental and simulation results for battery voltage under the effects of rider mass. This figure shows that when rider mass is increased from 57 kg to 67 kg, the experimental and simulation results show a decrease in electric consumption through the increase of battery voltage during stable operation of the EAB. 4. Conclusion An EAB was modeled and simulated based on the dynamic and battery models solved by a program written in MATLAB-Simulink. The effects of operating conditions and structural parameters such as slope, bicycle mass, wheel radius, crank length, and sprocket transmission ratio on the dynamic performance and electric consumption of the EAB were investigated. The simulation results showed that by suitably adjusting the operating conditions and structural parameters, the dynamic performance and electric consumption could be easily optimized. This study found that the dynamic performance and electric consumption were optimal when the slope grade, bicycle mass, wheel radius, crank length, and sprocket transmission ratio were 0%, 12 kg, 0.32 m, 0.17 m, and 3.43, respectively. Besides, a study for using the energy generated during the downhill movement of the EAB to create electrical power was conducted. This study showed that the increase of rider mass and slope angle β significantly contributed to improving the generated power of the DC generator. Aside from the simulation studies, an experimental study was conducted to examine the motion and electric consumption characteristics of the electric bicycle under the effects of real operating conditions (a road test). The experimental results had the same trends with the simulation results at the same initial conditions, which could be useful information for further study and development of a high-performance EAB in the future. Fig. 18. Effects of rider mass on battery voltage with (a) Mr = 57 kg and (b) Mr = 67 kg.
Acknowledgment This work was supported by the 2019 Research Fund of University of Ulsan, South Korea.
decreased when the sprocket ratio is decreased from 3.43 to 2.18, which is described in Fig. 15(b). For the sprocket transmission ratios of 3.43 and 2.66, the experimental velocity is a little smaller than the simulated velocity. The sudden appearance of wind speed could be a cause of this error. As the result, the experimental distance is a little smaller than the simulated distance for the sprocket transmission ratios of 3.43 and 2.66. When the experiment is conducted with the sprocket transmission ratios of 2.18, the experimental velocity is almost similar with simulated velocity. As the result, the experimental distance is also same with the simulated distance, as shown in Fig. 15(a). Fig. 16 shows the experimental and simulation results for battery voltage under the effects of sprocket ratio. It can be seen that when the sprocket ratio is reduced from 3.43 to 2.18, the experimental and simulation results show a decreased trend of battery voltage during stable EAB operation (after 30 s), which implies that the electric consumption increases when the sprocket ratio is reduced from 3.43 to 2.18.
References [1] Bauer C, Hofer J, Althaus HJ, Duce AD, Simons A. The environmental performance of current and future passenger vehicles: life cycle assessment based on a novel scenario analysis framework. Appl Energy 2015;157:871–83. [2] Jiang J, Li D. Theoretical analysis and experimental confirmation of exhaust temperature control for diesel vehicle NOx emissions reduction. Appl Energy 2016;174:232–44. [3] Nelson PF, Tibbett AR, Day SJ. Effects of vehicle type and fuel quality on real world toxic emissions from diesel vehicles. Atmos Environ 2008;42:5291–303. [4] He L, Hu J, Zang S, Wu Y, Zhu R, Zu L, et al. The impact from the direct injection and multi-port fuel injection technologies for gasoline vehicles on solid particle number and black carbon emissions. Appl Energy 2018;226:819–26. [5] Thangaraja J, Kannan C. Effect of exhaust gas recirculation on advanced diesel combustion and alternate fuels – a review. Appl Energy 2016;180:169–84. [6] Jewell J, Cherp A, Riahi K. Energy security under de-carbonization scenarios: an assessment framework and evaluation under different technology and policy choices. Energy Policy 2014;65:743–60. [7] Kiriyama E, Kajikawa Y. A multilayered analysis of energy security research and the energy supply process. Appl Energy 2014;123:415–23. [8] Radovanović M, Filipović S, Pavlović D. Energy security measurement – a sustainable approach. Renew Sustain Energy Rev 2017;68:1020–32. [9] Wang Q, Zhou K. A framework for evaluating global national energy security. Appl Energy 2017;188:19–31. [10] Daina N, Sivakumar A, Polak JW. Modelling electric vehicles use: a survey on the methods. Renew Sustain Energy Rev 2017;68:447–60. [11] Manzano ES, Agugliaro FM. The electric bicycle: worldwide research trends.
3.2.3. Effects of rider mass Fig. 17 shows the effects of rider mass on the motion characteristics of the EAB, in which the rider mass is varied at 57 kg and 67 kg, while the initial conditions, including wind speed, slope grade, EAB’s mass, wheel radius, crank length, and sprocket ratio, are 0 m/s, 0%, 21 kg, 0.33 m, 0.17 m, and 3.43, respectively. Fig. 17(a) shows that the experimental results for moving distance of the EAB are similar to the 295
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[23] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Model-based control for an innovative power-assisted bicycle. Energy Procedia 2015;81:606–17. [24] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Derivation and validation of a mathematical model for a novel electric bicycle. Proceedings of the World Congress on Engineering, London, U.K. 2015. [25] Timmermans JM, Matheys J, Lataire P, Mierlo JV, Cappelle J. A comparative study of 12 electrically assisted bicycles. World Electr Veh J 2009;3:0093–103. [26] Langford BC, Cherry CR, Bassett DR, Fitzhugh EC, Dhakal N. Comparing physical activity of pedal-assist electric bikes with walking and conventional bicycles. J Transp Health 2017;6:463–73. [27] Berntsen S, Malnes L, Langåker A, Bere E. Physical activity when riding an electric assisted bicycle. Int J Behav Nutr Phys Activity 2017;14:55. [28] Cairns S, Behrendt F, Raffo D, Beaumont C, Kiefer C. Electrically-assisted bikes: potential impacts on travel behavior. Transp Res Part A: Policy Pract 2017;103:327–42. [29] Morchin WC, Oman H. Electric bicycles: a guide to design and use. Wiley-IEEE Press; 2006. [30] Yildiz AB. Electrical equivalent circuit based modeling and analysis of direct current motors. Electr Power Energy Syst 2012;43:1043–7. [31] Tremblay O, Dessaint LA. Experimental validation of a battery dynamic model for EV applications. World Electr Veh J 2009;3:0289–98. [32] Patil PJ, Koujalagi JP. Modeling of BLDC motor powered from Li-ion battery for electric bicycle application. Int J Res Sci Adv Technol 2014;2:047–53. [33] Tayde SU, Makode NW, Laybar UM, Rakhonde BS. Self power generating electrical bicycle. Int Res J Eng Technol 2017;4:741–5. [34] Pal D. An introduction to DC generator using Matlab/Simulink. Imperial J Interdiscip Res 2016;2:935–8. [35] http://www.ni.com/pdf/manuals/375905a_02.pdf.
Energies 2018;11:1–16. [12] Hung NB, Sung J, Lim O. A simulation and experimental study of operating performance of an electric bicycle integrated with a semi-automatic transmission. Appl Energy 2018;221:319–33. [13] Weiss M, Dekker P, Moro A, Scholz H, Patel MK. On the electrification of road transportation – a review of the environmental, economic, and social performance of electric two-wheelers. Transp Res Part D 2015;41:348–66. [14] Hung NB, Sung J, Kim K, Lim O. A simulation and experimental study of operating characteristics of an electric bicycle. Energy Procedia 2017;105:2512–7. [15] Kheirandish A, Motlagh F, Shafiabady N, Dahari M, Khairi A, Wahab A. Dynamic fuzzy cognitive network approach for modelling and control of PEM fuel cell for power electric bicycle system. Appl Energy 2017;202:20–31. [16] Wang Q, Jiang B, Li B, Yan Y. A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles. Renew Sustain Energy Rev 2016;64:106–28. [17] Citron RJG. Electric bicycles: Li-ion and SLA E-bikes: drivetrain, motor, and battery technology trends, competitive landscape, and global market forecasts. Boulder, CO, USA: Navigant Research; 2016. [18] Jamerson FE, Benjamin E. Worldwide electric powered two wheel market. World Electr Veh J 2012;5:0269–75. [19] Cardone M, Strano S, Terzo M. Optimal power-assistance system for a new pedelec model. Proc ImechE Part C: J Mech Eng Sci 2015;230:3012–25. [20] Muetze A, Tan YC. Electric bicycles: a performance evaluation. IEEE Ind Appl Mag 2011;13:12–21. [21] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. A dynamic model for the performance and environmental analysis of an innovative e-bike. Energy Procedia 2015;81:618–27. [22] Cheon DS, Nam KH. Pedaling torque sensor-less power assist control of an electric bike via model-based impedance control. Int J Automot Technol 2017;18:327–33.
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Contents lists available at ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
The effects of operating conditions and structural parameters on the dynamic, electric consumption and power generation characteristics of an electric assisted bicycle Nguyen Ba Hung, Ocktaeck Lim
T
⁎
School of Mechanical Engineering, University of Ulsan, Ulsan 44610, Republic of Korea
H I GH L IG H T S
operation of an EAB is described by dynamic models and battery model. • The of input parameters on the electric consumption of the EAB are investigated. • Effects for electric power generation is conducted using a modeling approach. • AAnstudy • experimental study for motion and electric consumption of the EAB is conducted.
A R T I C LE I N FO
A B S T R A C T
Keywords: Electric assisted bicycle Bicycle dynamic models Sprocket transmission ratio Regenerative energy
A study is conducted to examine the motion, dynamic and electric consumption characteristics of an electric assisted bicycle based on the effects of certain operating conditions and structural parameters. Simulation models for operation of the electric assisted bicycle, including dynamic models of the electric assisted bicycle and battery models, are established. These simulation models are solved by MATLAB-Simulink to provide the operating characteristics of the electric assisted bicycle. Based on the established mathematical models, the motion, dynamic and electric consumption of the electric assisted bicycle are analyzed and optimized under the effects of slope, bicycle mass, wheel radius, crank length, and sprocket transmission ratio. The simulation results show that the dynamic performance and electric consumption of the electric assisted bicycle are significantly improved by reducing the bicycle mass, wheel radius, and increasing the sprocket transmission ratio. The dynamic performance and electric consumption are optimal when the slope grade, bicycle mass, wheel radius, crank length, and sprocket transmission ratio are 0%, 12 kg, 0.32 m, 0.17 m and 3.43, respectively. A study for using the regenerative energy generated during the downhill movement of the electric assisted bicycle to create electrical power is presented under the effects of rider mass and slope angle. An experimental study is also conducted to examine the motion and electric consumption characteristics of the electric assisted bicycle under real operating conditions. This study shows agreement between simulation and experimental results at the same initial conditions.
1. Introduction Environmental pollution is becoming a major concern for many countries around the world. One of the main pollution sources is vehicles with internal combustion engines using as diesel and gasoline, which cause toxic emissions such as hydrocarbons (HC), nitrogen oxides (NOx), carbon monoxide (CO), and particulate matter (PM) [1–5]. Another important issue is energy security [6–10]; depletion of fossil fuels and global warming caused by exhaust emissions from fossil-
⁎
fueled vehicles are motivating researchers worldwide to investigate and develop alternative fuels as well as new types of vehicles. One promising solution is the use of electric bicycles (EBs), which help reduce the toxic emissions and address the energy security problems [11–15]. EBs are receiving great worldwide attention due to their many benefits. In general, the EBs are not only suitable for driving on many varied terrains such as flat, hilly, and mixed terrains, but also more practical than other electric vehicles in terms of accessibility, price, maintenance, and repair costs [16]. Besides, the EB market is a rising market and is
Corresponding author. E-mail address: [email protected] (O. Lim).
https://doi.org/10.1016/j.apenergy.2019.04.002 Received 4 December 2018; Received in revised form 19 March 2019; Accepted 5 April 2019 0306-2619/ © 2019 Published by Elsevier Ltd.
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expected to further grow in the future. According to a report from Navigant Research [17], China is predicted to become the world’s largest EB market, with an average sale of about 30 million units from 2016 to 2025, which is much higher than in the rest of the world. Many auto companies are also interested in the EB field, including Ford, Honda, Peugeot, Mercedes, BMW, Volkswagen, Opel, Hyundai, Lexus, and General Motors [18]. Jamerson and Benjamin [18] estimate that EB sales will rise to 130 million by 2025 and 800 million by 2100. Electric bicycles can be classified into three main types: pure EB, power-assisted bicycle or electric assisted bicycle (EAB), and EB with two modes, pure and power-assisted. The pure EB utilizes an electric motor installed on the bicycle frame or wheels, and the driving power is controlled through a handlebar throttle. The rider simply twists the handlebar throttle to drive the pure EB without any human power, making this type very convenient. However, the pure EB has high electric consumption because its driving power is generated only by the electric motor. Furthermore, the pure EB might not be suitable for the rider who seeks the health benefits of bicycle use. The EAB, also called a pedelec (pedal electric cycle), is an EB in which an electric motor installed on the bicycle frame or wheels assists the rider when pedaling. Because the electric motor is used only as power assistance, the motor power of a pedelec is usually less than that of a pure EB. For people living in hilly areas or riders need some assistance or want to exercise to improve health, pedelecs are especially useful. Many previous studies on EABs have been conducted [11,12,14,19–28]. Hung et al. [11] studied the effects of input parameters on the dynamics and required power of an EAB equipped with an electric motor installed on the rear wheel. They also conducted a simulation and experimental study of the operating performance of an EB integrated with a nine-speed semi-automatic transmission [12]. Cardone et al. [19] presented dynamic models and controller designs based on torque control of an EAB, in which the input was voltage to the electric motor. A performance evaluation of an EAB was conducted by Muetze et al. [20], in which the total power required by the EAB was examined under the effects of rider mass, slope, and wind speed. Abagnale et al. [21] presented a performance and environmental analysis of an EAB compared to a thermal moped. Cheon and Nam [22] presented a model-based control method to assist human force acting on an EAB without using torque sensors, in which a power assist control algorithm was designed based on a PI-type feedback controller, an inverse model-based feed forward controller, and a pedaling torque observer. These previous studies provided useful information in the study and design of EABs, but they rarely mentioned the effects of operating conditions and design parameters on EAB electric consumption, which is an important factor in the design of a highly efficient EAB. In addition, the regenerating energy is also one of interesting subjects for studying highly efficient EABs, however it was rarely mentioned in the previous studies. This paper presents a simulation study of the motion, dynamic and electric consumption characteristics of an EAB under the effects of certain operating conditions and design parameters, specifically slope, bicycle mass, wheel radius, crank length and sprocket transmission ratio. Therein, sprocket transmission ratio is a transmission ratio between a front sprocket and rear sprockets of the EAB, which is calculated based on the number of teethes on the front and rear sprockets. Simulation models, including dynamic and battery models, are established to describe the operation of the EAB. These models are calculated and solved by a code programmed in MATLAB-Simulink. Based on the solutions of the simulation models, an optimal analysis for dynamic performance and electric consumption is conducted under the effects of the operating conditions and design parameters mentioned above. Besides, a study for using the energy generated during the downhill movement of the electric bicycle to create electrical power is presented. An experimental study is also conducted to examine the motion and electric consumption characteristics of the EAB.
Fig. 1. Force analysis model of the EAB.
2. Simulation study 2.1. Dynamic models of the electric bicycle Fig. 1 shows a force analysis model of the EAB, in which the rider’s power is assisted by an electric motor during pedaling. The specification parameters of the EAB are illustrated in Table 1. The motion of the bicycle obeys Newton’s second law, which is described by:
Fp − Fs − Fw − Fr = M
d 2x dt 2
(1)
where Fp is the propulsion force, Fs is the slope resistance force, Fr is the rolling resistance force, Fw is the wind resistance force, x is the moving distance of the electric bicycle, M is the total mass of the electric bicycle (Mb) and rider (Mr), and t is time. The slope resistance force is calculated by: (2)
Fs = 9.81MG where G is the slope grade (%) [20]. The wind resistance force is calculated by:
Fw =
1 Cd DA (vw + vg )2 2
(3) 3
where Cd is the coefficient of drag, D is the density of air (kg/m ), A is the frontal area (m2), vw is the wind speed (m/s), vg is the ground speed (m/s) [29]. The rolling resistance force is calculated by: (4)
Fr = 9.81MCr cos α
where Cr is the rolling resistance coefficient [29], α is the slope angle (°) The propulsion force is calculated by:
Fp·Rw = Tp = Tr + Tm
(5)
where Tp is the propulsion torque (N·m), which is the total of rider Table 1 Specification parameters of the EAB.
286
Parameters
Values
Electric bicycle mass, kg Crank length, m Wheel radius, m Number of speed Motor power, W Battery type Battery nominal voltage, V Rated capacity
21 0.17 0.33 7 250 Li-ion 36 9.3 Ah
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Fig. 2. Force analysis models of the EAB.
Fig. 3. Effects of slope grade on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
torque (Tr) and motor torque (Tm) generated when pedaling. Based on Fig. 1, Tr can be expressed as follows:
Tr = Fch Rrg
Tr =
1 1 Lc Fh cos θfg = Lc Fh cos θfg Rfg γRrg
Rfg
Lc Fh cos θfg =
1 Lc Fh cos θfg γ
(8)
This EAB uses a DC electric motor installed in the rear wheel. The electric motor receives the control signals detected by rider’s torque when pedaling to generate a motor torque, which assists the rider’s power. The dynamics of the DC electric motor are modeled by Eqs. (9) and (10) [30]:
(6)
where Fch is the chain force, and Rrg is the radius of the rear gear. Based on the force analysis model of the EAB shown in Fig. 1, Fch can be calculated as:
Fch =
Rrg
dia + ia (t ) Ra + Kb ωm = Ua dt
(9)
dωm + B1 ωm + Tm = Kb ia (t ) dt
(10)
La (7)
J
where Rfg is the radius of the front gear, Lc is the length of the crank, Fh is the human force, Rrg is the radius of the rear gear, and γ is the sprocket transmission ratio. By combining Eqs. (6) and (7), the rider torque can be derived as follows:
where ia is the armature current, Ra is the armature resistance, Ua is the terminal voltage of the DC motor, La is the armature inductance, Kb is the back EMF constant, J is the torque of inertia, B1 is the viscous friction coefficient, Tm is the motor torque acting on the shaft of the rear 287
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Fig. 4. Effects of EAB mass on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Fig. 5. Effects of wheel radius on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Fig. 6. Effects of crank length on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
wheel, and ωm is the speed of the motor. By combining Eqs. (5), (8), (9), and (10), the propulsion force can be derived as follows:
Fp =
2.2. Battery model A lithium-ion battery is used to provide the input voltage to the electric motor. The battery model used in this study is described by a discharge model [31,32] which presents the decrease of battery voltage as a function of current. The discharge model of the lithium-ion battery is described by Eq. (12) [31,32]:
1 1 ⎡ Kb Tr + Tm K L di dω = Lc Fh cos θfg + Ua − b a a −J m Rw γRw Rw ⎢ Ra dt dt ⎣ Ra K2 − ⎜⎛B1 + b ⎟⎞ ωm⎤ Ra ⎠ ⎥ ⎝ ⎦
(11) 288
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Fig. 7. Effects of sprocket ratio on (a) velocity and distance, (b) propulsion torque, and (c) battery voltage.
Vb = E0 − K
Q Q i (t ) − K i ∗ − Ri + Ae (−Bi (t )) Q − i (t ) Q − i (t )
Fd = Mt g sin β (12)
where Fd is the downhill force and Frg is the rolling resistance force caused by roller of the DC generator. In the case of moving downhill, the electrical power is generated, and its model is described through the differential equations below [34]:
where Vb is the battery voltage, E0 is the battery constant voltage, K is the polarization constant, Q is the battery capacity, i(t) is the actual battery charge (i(t) = ʃidt), A is the exponential zone amplitude, B is the exponential zone time constant inverse, R is the internal resistance, i is the battery current, and i* is the filtered current.
Eg = k g ωg φ
2.3. Dynamic and electrical power generation models when moving downhill
d 2x dt 2
d 2x dt 2
diag
TL = kL Iag φ
Ts = TL + Jg
dt
(17) (18)
dωg dt
+ Bωg
(19)
Vt = Iag RL
(20)
Pt = Vt Iag
(21)
where Eg is the total of generated voltage, kg is the voltage constant, ωg is the speed of DC generator, φ is field flux, Vt is the terminal voltage, Lag is the armature inductance, Iag is the armature current, Rag is the armature resistance, TL is the load torque, kL is the load constant, Ts is the shaft torque, Jg is the moment of inertia, B is viscous friction, RL is the load resistance, and Pt is generated power. 2.4. Simulation results 2.4.1. Effects of operating conditions and design parameters Slope grade (G) directly affects the motion of the electric bicycle due to its relationship with the slope resistance force shown in Eq. (1). The effects of slope grade on the velocity and moving distance of the EAB are shown in Fig. 3(a). The bicycle velocity significantly reduces by about 8.1% when the slope grade is increased from 0% to 1.74%. This is because the slope resistance force is increased when the slope grade is increased. Furthermore, increasing the slope grade also requires more energy to overcome the slope resistance force. Thus, the propulsion torque is increased, as shown in Fig. 3(b). Increasing the slope grade results in a greater electric consumption through battery voltage reduction, as shown in Fig. 3(c). This is explained by the increased torque acting on the motor to overcome the slope resistance force. As shown in Fig. 13(c), the battery voltage is considerably decreased in 10 s for each slope grade due to the small initial rider torque. The battery voltage is then increased again to reach a stable value depending on slope grade. This is because the load on the motor is increased due to the increased rider torque when pedaling. During the stable period (from 40 s to 60 s), the electric consumption
(13)
where Mt is the total mass of EAB, rider, load and DC generator When the EAB moves on the slope terrain, it is moved downhill by itself due to the influence of gravitational force, while the propulsion force cause by pedaling is eliminated. Therefore, the force analysis model in this case is described by the following equations:
Fd − Fr − Fw − Frg = Mt
(16)
Vt = Eg − Rag Iag − Lag
When the EAB moves downhill, the propulsion force caused by pedaling could be eliminated, and the EAB moves by itself due to the influence of gravitational force. The energy generated by the downhill movement could be wasted if it is only used to move the EAB. Therefore, this section presents an idea for using the wasted energy of the EAB when moving downhill to generate electrical power which could be used for charging a battery. In this study, a DC (direct current) generator is selected for generating electrical power because it has advantages over AC (alternating current) generator such as low weight and no conversion of supply is required from AC to DC [33]. Fig. 2 shows force analysis models when the EAB moves on flat and slope terrains. As shown in Fig. 2, the DC generator is installed on the bicycle frame, which is detached from the front wheel tire to avoid the rolling resistance force caused by the DC generator when the EAB moves on the flat terrain. When the EAB moves downhill, the DC generator is contacted with the front wheel tire through a roller located at the top of the DC generator. Thus, the downhill movement of the EAB will turn the roller of the DC generator and generate electrical power. To determine the electrical power generation, the output of the DC generator is connected to a load as shown in Fig. 2. In this study, the EAB moves continuously on both flat and slope terrains, in which the EAB will be oriented to move on the slope terrain after 40 s of running on the flat terrain. When the EAB moves on the flat terrain, its force analysis model is described by the following equation:
Fp − Fs − Fw − Fr = Mt
(15)
(14) 289
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Fig. 8. Effects of rider mass on (a) the velocity and (b) the moving distance of EAB.
increases 0.25% when the slope grade is increased from 0% to 1.74%. The EAB mass (Mb) is a design parameter that directly affects the motion of the EAB due to its relationship with inertial force, as shown in Eq. (1). The effects of EAB mass on velocity, moving distance, propulsion torque, and battery voltage are shown in Fig. 4. As shown in Fig. 4(a), the velocity and moving distance of the EAB slightly increases by 1.4% and 3.3%, respectively when EAB mass is reduced from 24 kg to 12 kg. The increase of the velocity and moving distance is explained by the decrease of inertial force when EAB mass is reduced. Besides, when the EAB mass is reduced from 24 kg to 12 kg, the propulsion torque decreases by 0.47% due to the decrease of inertial force caused by the reduced EAB mass, as shown in Fig. 4(b). The increase of bicycle mass results in a slight increment of electric consumption through a small reduction of battery voltage, as shown in Fig. 4(c). Based on these results, the bicycle mass Mb = 12 kg is selected as an input parameter for the next investigations.
Fig. 9. Effects of rider mass on (a) DC generated current (b) DC generated voltage and (c) DC generated power.
Wheel radius (Rw) is the second design parameter selected to investigate because it relates to rotational inertia of the wheel as well as EAB motion. Fig. 5 describes the effects of wheel radius on velocity, moving distance, propulsion torque, and battery voltage of the EAB. As
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Fig. 10. Effects of slope angle β on (a) the velocity and (b) the moving distance of EAB.
can be observed in Fig. 5(a), the bicycle velocity increases by 3.39% when the wheel radius is reduced from 0.36 m to 0.32 m. In addition, the increase of wheel radius results in an increase in propulsion torque, as shown in Fig. 5(b). This is because the larger wheel radius has higher rotational inertia and so requires a higher input of energy to obtain a certain velocity. However, the input energy is constant due to the same rider mass; thus, bicycle velocity and distance decrease, while propulsion torque increases when wheel radius is increased. It can be found that the electric consumption increases by about 0.41% through a reduction of battery voltage when the wheel radius is increased from 0.32 m to 0.36 m, as shown in Fig. 5(c). This is because the load torque on the motor is increased to overcome the rotational inertia of the wheel when the wheel radius is increased. Based on the obtained results, the wheel radius Rw = 0.32 m is selected as one of input parameters for the next investigation.
Fig. 11. Effects of slope angle β on (a) DC generated current (b) DC generated voltage and (c) DC generated power.
Crank length (Lc) is the third design parameter selected to investigate because it relates to propulsion force of the EAB, which is shown in Eq. (11). The effects of crank length on velocity, moving distance, propulsion torque, and battery voltage of the EAB are depicted in Fig. 6, in which Lc is changed from 0.110 m to 0.170 m. The initial 291
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Fig. 12. Experimental system setup for the EAB.
12 kg, 0.32 m, 0.17 m, and 3.43, respectively. 2.4.2. Motion and electrical power generation characteristics 2.4.2.1. Effects of rider mass. The effects of rider mass on the motion characteristics are shown in Fig. 8, in which the rider mass is varied at 47 kg, 57 kg, 67 kg, 77 kg and 87 kg, while the initial conditions including wind speed, air density, bicycle mass and wheel radius are 0 m/s, 1.225 kg/m3, 21 kg and 0.32 m, respectively. As shown in Fig. 8, slope angle β is changed from 0° to 5° after the electric bicycle moved stably at 40 s. It can be seen that, the velocity of the electric bicycle has a decreased trend and then obtain stable value for each rider mass, including Mr = 47 kg, Mr = 57 kg and Mr = 67 kg. This is because when the EAB moves downhill, the propulsion force cause by pedaling is eliminated, and thus the bicycle velocity is temporarily decreased. Afterwards, the rider mass as well as gravitational force will help the EAB to maintain its stable velocity. It can be seen that the decreased trend is reduced when the rider mass is increased from 47 kg to 67 kg due to the increased gravitational force. As can be seen in Fig. 8(a), when the rider mass is increased to 87 kg, the velocity of the electric bicycle has an increased trend just after β is adjusted to 5°, and then obtains a stable value which is higher than bicycle velocity at the slope angle of 0°. As the result, the moving distance is significantly increased when the rider mass is changed from 47 kg to 87 kg, as shown in Fig. 8(b). Fig. 9 shows the electrical generation characteristics of the DC generator. The simulation results show that the DC generated current, voltage and power start to increase when the DC generator is contacted with the front wheel tire of electric bicycle during movement downhill with the slope angle of 5°. It can be found that the generated current, voltage and power of the DC generator are increased 20.6%, 20.6% and 36.9%, respectively when the rider mass is changed from 47 kg to 87 kg, as shown in Fig. 9(a), (b), and (c).
Fig. 13. Road test for the EAB.
conditions including slope grade, rider mass, wind speed, EAB mass, sprocket transmission ratio, air density and wheel radius are kept at 0%, 57 kg, 0 m/s, 12 kg, 3.43, 1.145 kg/m3, and 0.32 m, respectively. Fig. 6(a) and (b) show that the bicycle velocity is increased 3.4%, while the maximum propulsion torque is increased 10.3% when Lc is changed from 0.110 m to 0.170 m. This is because the propulsion force is increased, which is proportional to the crank length, as shown in Eq. (11). Fig. 6(c) shows that the increase of crank length results in a smaller decrement of battery voltage during the stable stage, which implies that a lower electric consumption could be obtained by increasing the crank length. The increase of crank length results in the increase of bicycle velocity as well as the load on the motor. As the result, it reduces the voltage supplying to the motor during the stable stage. The sprocket ratio, which is denoted by γ, is the fourth design parameter that directly affects the dynamics and thus the electric consumption of the EAB because of its relationship with the propulsion torque. The effects of sprocket ratio on the velocity, moving distance, propulsion torque, and battery voltage of the EAB are shown in Fig. 7. By adjusting the sprocket ratio from 2.18 to 3.43, the velocity and moving distance are significantly increased, by about 28.02% and 27.69%, respectively, as shown in Fig. 7(a). A smaller sprocket ratio results in a larger propulsion torque, as shown in Fig. 7(b). In addition, the electric consumption is increased by about 0.82%, which is illustrated through a reduction of battery voltage when the sprocket ratio decreases from 3.43 to 2.18, as shown in Fig. 7(c). This can be explained by the decrease of bicycle velocity as well as load on the motor, which results in the increase of the voltage supplying to the motor when the sprocket ratio is changed from 3.43 to 2.18. Based on the results obtained, the optimal sprocket ratio is 3.43. In summary, dynamic performance and electric consumption of the EAB are optimized when the key parameters including slope, bicycle mass, wheel radius, crank length and sprocket ratio are adjusted at 0%,
2.4.2.2. Effects of slope angle β. Fig. 10 describes the effects of slope on the motion characteristics of the EAB, in which the rider mass is kept at 87 kg which was optimized in the previous section. Fig. 10 shows that the moving distance and velocity of the electric bicycle are same during 40 s of running because the propulsion force caused by pedaling is used, while the slope angle β is kept constant with the value of 0°. As shown in Fig. 10, when β is still kept 0° after 40 s of running, the velocity of the EAB is reduced to zero, while the moving distance is constant because the propulsion force caused by pedaling is eliminated in this stage. When β is adjusted to a certain value larger than 0°, the moving distance and velocity of the electric bicycle are different for each value of β. When β is increased from 3° to 9°, the moving distance and bicycle velocity are significantly increased when compared with that of the 292
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Fig. 15. Effects of sprocket ratio on (a) moving distance and (b) bicycle velocity.
the DC generator, as shown in Fig. 11. When β is increased from 3° to 9°, the generated current, voltage and power are increased 45.4%, 45.4%, and 70.2%, respectively.
3. Experimental study 3.1. Experimental system setup An experimental system for the EAB is illustrated in Fig. 12. This experimental system includes an EAB equipped with a lithium-ion battery and a DC electric motor installed in the rear wheel. In addition, the EAB is also equipped with signal processing and measurement devices to collect experimental data. A photoelectric sensor LM393 is installed on the bicycle frame, which is used to detect EAB motion. This sensor is provided by a 5 V DC source from an electronic control unit (ECU). The signals from the photo sensor are sent to the ECU which is connected to a computer containing LabVIEW program to calculate the motion characteristics of the EAB, such as velocity and moving distance. Meanwhile, an NI-9221 voltage input module with sample rate of 800 kS/s [35] is used to measure battery voltage when the EAB is in motion. The measurement signals of NI-9221 are transferred to the computer to collect battery voltage data. The EAB experiment is conducted on a test road as shown in Fig. 13.
Fig. 14. Comparison between simulation and experiment in (a) moving distance, (b) bicycle velocity, and (c) battery voltage.
slope angle of 0° due to the considerable increase of gravitational force caused by the increased slope angle β. The generated current, voltage and power start to increase with the various values depending on the varied slopes. The significant increase of bicycle velocity leads to the considerable increase of the generated current, voltage and power of 293
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Fig. 17. Effects of rider mass on (a) moving distance and (b) bicycle velocity.
battery voltage of the EAB, are compared with the corresponding simulation results in the same initial conditions, specifically wind speed vw = 0 m/s, slope grade G = 0%, rider mass Mr = 57 kg, bicycle mass Mb = 21 kg, radius of wheel Rw = 0.33 m, crank length Lc = 0.17 m, and sprocket ratio γ = 3.43. These results are described in Fig. 14. As can be seen in Fig. 14, the experimental results show the same trends as the simulation results in moving distance, velocity, and battery voltage. Both the experiment and the simulation show that battery voltage is significantly reduced in 10 s to assist rider power because of the small initial rider torque when pedaling. When rider torque is increasing, the load on the motor also increases so that it reduces the voltage supplying to the motor. Thus, battery voltage increases again after declining to a certain value, as shown in Fig. 14(c). In this experiment, the fluctuation of experimental battery voltage could be due to the fluctuation of experimental velocity caused by the sudden appearance of wind speed.
3.2.2. Effects of sprocket ratio The effects of sprocket ratio (γ) on motion characteristics of the EAB are shown in Fig. 15, in which the sprocket ratio is varied at 2.18, 2.66 and 3.43, while the initial conditions, including wind speed, slope grade, rider’s mass, EAB’s mass, crank length, and wheel radius, are 0 m/s, 0%, 57 kg, 21 kg, 0.17 m, and 0.33 m, respectively. The experimental results are similar to the simulation results for moving distance of the EAB, as shown in Fig. 15(a). When the sprocket ratio decreases from 3.43 to 2.18, both the experiment and the simulation shows reduction of moving distance. This is because the velocity of the EAB is
Fig. 16. Effects of sprocket ratio on battery voltage with (a) γ = 3.43, (b) γ = 2.66, and (c) γ = 2.18.
3.2. Experimental results 3.2.1. Comparison between experimental and simulation results The experimental results, including moving distance, velocity, and 294
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corresponding simulation results at the different rider masses. When the rider mass is increased from 57 kg to 67 kg, both the experiment and the simulation shows an increase of moving distance. This is because the velocity of the EAB is increased when the rider mass is increased, as shown in Fig. 17(b). For the rider mass of 57 kg, the experimental distance is a little smaller than the simulated distance. This is because the experimental velocity is a little smaller than the simulated velocity, which could be caused by the sudden appearance of wind speed. Fig. 18 shows experimental and simulation results for battery voltage under the effects of rider mass. This figure shows that when rider mass is increased from 57 kg to 67 kg, the experimental and simulation results show a decrease in electric consumption through the increase of battery voltage during stable operation of the EAB. 4. Conclusion An EAB was modeled and simulated based on the dynamic and battery models solved by a program written in MATLAB-Simulink. The effects of operating conditions and structural parameters such as slope, bicycle mass, wheel radius, crank length, and sprocket transmission ratio on the dynamic performance and electric consumption of the EAB were investigated. The simulation results showed that by suitably adjusting the operating conditions and structural parameters, the dynamic performance and electric consumption could be easily optimized. This study found that the dynamic performance and electric consumption were optimal when the slope grade, bicycle mass, wheel radius, crank length, and sprocket transmission ratio were 0%, 12 kg, 0.32 m, 0.17 m, and 3.43, respectively. Besides, a study for using the energy generated during the downhill movement of the EAB to create electrical power was conducted. This study showed that the increase of rider mass and slope angle β significantly contributed to improving the generated power of the DC generator. Aside from the simulation studies, an experimental study was conducted to examine the motion and electric consumption characteristics of the electric bicycle under the effects of real operating conditions (a road test). The experimental results had the same trends with the simulation results at the same initial conditions, which could be useful information for further study and development of a high-performance EAB in the future. Fig. 18. Effects of rider mass on battery voltage with (a) Mr = 57 kg and (b) Mr = 67 kg.
Acknowledgment This work was supported by the 2019 Research Fund of University of Ulsan, South Korea.
decreased when the sprocket ratio is decreased from 3.43 to 2.18, which is described in Fig. 15(b). For the sprocket transmission ratios of 3.43 and 2.66, the experimental velocity is a little smaller than the simulated velocity. The sudden appearance of wind speed could be a cause of this error. As the result, the experimental distance is a little smaller than the simulated distance for the sprocket transmission ratios of 3.43 and 2.66. When the experiment is conducted with the sprocket transmission ratios of 2.18, the experimental velocity is almost similar with simulated velocity. As the result, the experimental distance is also same with the simulated distance, as shown in Fig. 15(a). Fig. 16 shows the experimental and simulation results for battery voltage under the effects of sprocket ratio. It can be seen that when the sprocket ratio is reduced from 3.43 to 2.18, the experimental and simulation results show a decreased trend of battery voltage during stable EAB operation (after 30 s), which implies that the electric consumption increases when the sprocket ratio is reduced from 3.43 to 2.18.
References [1] Bauer C, Hofer J, Althaus HJ, Duce AD, Simons A. The environmental performance of current and future passenger vehicles: life cycle assessment based on a novel scenario analysis framework. Appl Energy 2015;157:871–83. [2] Jiang J, Li D. Theoretical analysis and experimental confirmation of exhaust temperature control for diesel vehicle NOx emissions reduction. Appl Energy 2016;174:232–44. [3] Nelson PF, Tibbett AR, Day SJ. Effects of vehicle type and fuel quality on real world toxic emissions from diesel vehicles. Atmos Environ 2008;42:5291–303. [4] He L, Hu J, Zang S, Wu Y, Zhu R, Zu L, et al. The impact from the direct injection and multi-port fuel injection technologies for gasoline vehicles on solid particle number and black carbon emissions. Appl Energy 2018;226:819–26. [5] Thangaraja J, Kannan C. Effect of exhaust gas recirculation on advanced diesel combustion and alternate fuels – a review. Appl Energy 2016;180:169–84. [6] Jewell J, Cherp A, Riahi K. Energy security under de-carbonization scenarios: an assessment framework and evaluation under different technology and policy choices. Energy Policy 2014;65:743–60. [7] Kiriyama E, Kajikawa Y. A multilayered analysis of energy security research and the energy supply process. Appl Energy 2014;123:415–23. [8] Radovanović M, Filipović S, Pavlović D. Energy security measurement – a sustainable approach. Renew Sustain Energy Rev 2017;68:1020–32. [9] Wang Q, Zhou K. A framework for evaluating global national energy security. Appl Energy 2017;188:19–31. [10] Daina N, Sivakumar A, Polak JW. Modelling electric vehicles use: a survey on the methods. Renew Sustain Energy Rev 2017;68:447–60. [11] Manzano ES, Agugliaro FM. The electric bicycle: worldwide research trends.
3.2.3. Effects of rider mass Fig. 17 shows the effects of rider mass on the motion characteristics of the EAB, in which the rider mass is varied at 57 kg and 67 kg, while the initial conditions, including wind speed, slope grade, EAB’s mass, wheel radius, crank length, and sprocket ratio, are 0 m/s, 0%, 21 kg, 0.33 m, 0.17 m, and 3.43, respectively. Fig. 17(a) shows that the experimental results for moving distance of the EAB are similar to the 295
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[23] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Model-based control for an innovative power-assisted bicycle. Energy Procedia 2015;81:606–17. [24] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. Derivation and validation of a mathematical model for a novel electric bicycle. Proceedings of the World Congress on Engineering, London, U.K. 2015. [25] Timmermans JM, Matheys J, Lataire P, Mierlo JV, Cappelle J. A comparative study of 12 electrically assisted bicycles. World Electr Veh J 2009;3:0093–103. [26] Langford BC, Cherry CR, Bassett DR, Fitzhugh EC, Dhakal N. Comparing physical activity of pedal-assist electric bikes with walking and conventional bicycles. J Transp Health 2017;6:463–73. [27] Berntsen S, Malnes L, Langåker A, Bere E. Physical activity when riding an electric assisted bicycle. Int J Behav Nutr Phys Activity 2017;14:55. [28] Cairns S, Behrendt F, Raffo D, Beaumont C, Kiefer C. Electrically-assisted bikes: potential impacts on travel behavior. Transp Res Part A: Policy Pract 2017;103:327–42. [29] Morchin WC, Oman H. Electric bicycles: a guide to design and use. Wiley-IEEE Press; 2006. [30] Yildiz AB. Electrical equivalent circuit based modeling and analysis of direct current motors. Electr Power Energy Syst 2012;43:1043–7. [31] Tremblay O, Dessaint LA. Experimental validation of a battery dynamic model for EV applications. World Electr Veh J 2009;3:0289–98. [32] Patil PJ, Koujalagi JP. Modeling of BLDC motor powered from Li-ion battery for electric bicycle application. Int J Res Sci Adv Technol 2014;2:047–53. [33] Tayde SU, Makode NW, Laybar UM, Rakhonde BS. Self power generating electrical bicycle. Int Res J Eng Technol 2017;4:741–5. [34] Pal D. An introduction to DC generator using Matlab/Simulink. Imperial J Interdiscip Res 2016;2:935–8. [35] http://www.ni.com/pdf/manuals/375905a_02.pdf.
Energies 2018;11:1–16. [12] Hung NB, Sung J, Lim O. A simulation and experimental study of operating performance of an electric bicycle integrated with a semi-automatic transmission. Appl Energy 2018;221:319–33. [13] Weiss M, Dekker P, Moro A, Scholz H, Patel MK. On the electrification of road transportation – a review of the environmental, economic, and social performance of electric two-wheelers. Transp Res Part D 2015;41:348–66. [14] Hung NB, Sung J, Kim K, Lim O. A simulation and experimental study of operating characteristics of an electric bicycle. Energy Procedia 2017;105:2512–7. [15] Kheirandish A, Motlagh F, Shafiabady N, Dahari M, Khairi A, Wahab A. Dynamic fuzzy cognitive network approach for modelling and control of PEM fuel cell for power electric bicycle system. Appl Energy 2017;202:20–31. [16] Wang Q, Jiang B, Li B, Yan Y. A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles. Renew Sustain Energy Rev 2016;64:106–28. [17] Citron RJG. Electric bicycles: Li-ion and SLA E-bikes: drivetrain, motor, and battery technology trends, competitive landscape, and global market forecasts. Boulder, CO, USA: Navigant Research; 2016. [18] Jamerson FE, Benjamin E. Worldwide electric powered two wheel market. World Electr Veh J 2012;5:0269–75. [19] Cardone M, Strano S, Terzo M. Optimal power-assistance system for a new pedelec model. Proc ImechE Part C: J Mech Eng Sci 2015;230:3012–25. [20] Muetze A, Tan YC. Electric bicycles: a performance evaluation. IEEE Ind Appl Mag 2011;13:12–21. [21] Abagnale C, Cardone M, Iodice P, Strano S, Terzo M, Vorrano G. A dynamic model for the performance and environmental analysis of an innovative e-bike. Energy Procedia 2015;81:618–27. [22] Cheon DS, Nam KH. Pedaling torque sensor-less power assist control of an electric bike via model-based impedance control. Int J Automot Technol 2017;18:327–33.
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