Parameter Matching of Power Systems and Design of Vehicle Control Strategies for Mini-Electric Trucks
Abstract
:1. Introduction
2. Power System Parameter Design
2.1. Basic Parameters and Performance Indicators
2.2. Selection of Operation Conditions
2.3. Calculation of Motor Parameters
2.4. Determination of Transmission System Parameters
2.5. Determination of Power Battery Parameters
3. Establishment of the Power Model Based on CRUISE Software
4. Vehicle Control Strategy Design
4.1. Vehicle Control Strategy Modeling
4.2. Implementation of Brake Priority
4.3. Implementation of Prohibiting Vehicle Driving on Charging
4.4. Implementation of Vehicle Driving
4.5. Implementation of Fault Handling
4.6. Implementation of Drive Control
4.7. Implementation of Braking Energy Recovery
5. Analysis of Simulation Results
6. Performance Test
6.1. Maximum Speed Test
6.2. Acceleration Test
7. Theoretical Calculation of Dynamic Performance
8. Analysis of Dynamic Performance
9. Analysis of Economy
10. Conclusions
- (1)
- According to the power demand of the whole vehicle, to enhance the accuracy of dynamic parameters of mini−electric trucks, combining the characteristics of mini trucks, the parameters of the driving motor, power battery, and the transmission ratio of the main reducer are designed using the automobile theory and the types of drive motors and power batteries are selected, the dynamic model of mini−electric trucks is established.
- (2)
- The vehicle control strategy including how working condition switching is developed according to the work conditions of mini−electric trucks, and the control strategy model is built using the simulation software, and the realization method of each function of the control strategy and the realization process of each function are analyzed.
- (3)
- According to the matched parameters of the power system, the power performance is calculated theoretically.
- (4)
- The dynamic performance is analyzed through the simulation results were compared with theoretical calculation and performance tests results respectively, the comparison results show an error rate of maximum speed, acceleration time and maximum gradient between simulation results and test results are 0.641% and 5.63% (15.328%), respectively, the dynamic index have reached the expected value, it proves that the design method of dynamic parameters is reasonable, and the dynamic performance is analyzed through co−simulation, endurance mileage is up to 295 Km under UDC conditions, increased by 5% after the vehicle control strategy adopted. The economy is improved. It has practical guiding significance for the power system design of mini−electric trucks.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Items | Length/Width/Height (mm) | Curb Weight (kg) | Max Total Mass (kg) | Air Resistance Coefficient | Windward Area (m2) | Rolling Radius (m) | Rolling Resistance Coefficient | Transmission Efficiency (%) |
---|---|---|---|---|---|---|---|---|
Index | 4995/2050/1900 | 1185 | 2505 | 0.8 | 2.5 | 0.301 | 0.016 | 94 |
Performance Indicators | Maximum Speed | Maximum Climbable Gradient | Acceleration Time | Endurance Mileage | |
---|---|---|---|---|---|
0–50 km/h | 0–100 km/h | ||||
Value of parameter | 180 km/h | 35% | 6 s | 14 s | 280 |
Parameters | Rated Power (kW) | Peak Power (kW) | Rated Torque (N∙m) | Peak Torque (N∙m) | Rated Speed (r/min) | Peak Speed (r/min) | Rated Voltage (V) | Efficiency (%) |
---|---|---|---|---|---|---|---|---|
Value | 80 | 240 | 90 | 240 | 3000 | 10,000 | 320 | 0.9 |
Items | Battery Type | Nominal Voltage | Capacity | Max Continuous Charging/Discharge Current | Max Transient Charging/Discharge Current | Monomer Mass | Cyclic-Life (80%) |
---|---|---|---|---|---|---|---|
Index | Lithium iron phosphate | 3.2 V | 50 Ah | 15 A/50 A | 50 A/50 A | 1.5 kg | 2000 times |
Serial Number | Direction | Driving Distance (m) | Time (s) | Average Speed (km/h) |
---|---|---|---|---|
1 | Positive | 1000 | 19.37 | 185.86 |
2 | Reverse | 1000 | 19.37 |
Serial Number | Direction | Time (s) | Average Time (s) |
---|---|---|---|
1 | Positive | 4.95 | 4.965 |
2 | Reverse | 4.98 |
Serial Number | Direction | Time (s) | Average Time (s) |
---|---|---|---|
1 | Positive | 13.692 | 13.688 |
2 | Reverse | 13.685 |
Maximum Speed (km/h) | Acceleration Time from 0 to 50 km/h (s) | Acceleration Time from 0 to 100 km/h (s) | Maximum Gradient (%) | |
---|---|---|---|---|
Simulation results | 187 | 4.7 | 11.59 | 40.34 |
Theoretical calculation results | 186.69 | — | — | 39.8 |
Test results | 185.8 | 4.965 | 13.688 | — |
Error rate (%) between simulation results and theoretical calculation results | 0.166 | — | — | 1.35 |
Error rate (%) between simulation results and test results | 0.641 | 5.63 | 15.328 | — |
Time (s) | Signal status | Mode |
---|---|---|
0–12 | err_flg = 0; BPS_Brake_Enble = 1; APS_Brake_Enble = 0 | Neutral |
13–28 | err_flg = 0; APS_Brake_Enble = 0; Gear_position = 1; Acc_pedal = 1 | Motor drive |
29–32 | BPS_Brake_Enble = 1; Gear_position = 0; Acc_pedal = 0 | Brake energy recovery |
32–45 | err_flg = 0; BPS_Brake_Enble = 1; APS_Brake_Enble = 0 | Neutral mode |
45–74 | err_flg = 0; APS_Brake_Enble = 0; Gear_position = 1; Acc_pedal = 1 | Motor drive mode |
74–82 | err_flg = 0; BPS_Brake_Enble = 1; Gear_position = 0; Acc_pedal = 0 | Brake energy recovery |
82–117 | err_flg = 0; BPS_Brake_Enble = 1; APS_Brake_Enble = 0 | Neutral |
117–154 | err_flg = 0; APS_Brake_Enble = 0; Gear_position = 1; Acc_pedal = 1 | Motor drive |
160–165 | err_flg = 0; BPS_Brake_Enble = 1; APS_Brake_Enble = 0 | Neutral |
165–175 | err_flg = 0; APS_Brake_Enble = 0; Gear_position = 1; Acc_pedal = 1 | Motor drive |
175–188 | err_flg = 0; BPS_Brake_Enble = 1; Gear_position = 0; Acc_pedal = 0 | Brake energy recovery |
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Ma, J.; Gu, F.; Feng, Z.; Zhang, S. Parameter Matching of Power Systems and Design of Vehicle Control Strategies for Mini-Electric Trucks. World Electr. Veh. J. 2023, 14, 207. https://doi.org/10.3390/wevj14080207
Ma J, Gu F, Feng Z, Zhang S. Parameter Matching of Power Systems and Design of Vehicle Control Strategies for Mini-Electric Trucks. World Electric Vehicle Journal. 2023; 14(8):207. https://doi.org/10.3390/wevj14080207
Chicago/Turabian StyleMa, Jianwei, Fengyi Gu, Ziliang Feng, and Shaohang Zhang. 2023. "Parameter Matching of Power Systems and Design of Vehicle Control Strategies for Mini-Electric Trucks" World Electric Vehicle Journal 14, no. 8: 207. https://doi.org/10.3390/wevj14080207