Abstract

Emergency rescue vehicles are special equipment for fire, flood, earthquake and other disasters. They need to have high efficiency and high mobility under various terrain and road conditions. The fuel economy of emergency rescue vehicles is very poor in climbing and complex terrain due to the heavy weight of vehicle chassis and upper loading. The dual-motor torque increasing hybrid power system designed in this paper greatly improves the dynamic performance and mobility of emergency rescue vehicles, and the use of dual-motor drive in steep slopes and complex terrain can avoid the engine working in low efficiency area. In order to further improve the fuel economy of vehicles under various working conditions, a fuzzy logic control strategy based on improved particle swarm optimization (PSO) is proposed in this paper. The torques of engine and dual-motor are reasonably distributed under different working conditions. A novel fuzzy parameter optimization mode is designed, which reduces the workload of optimization calculation and ensures the optimization accuracy. The off-line simulation and hardware-in-the-loop experiments are carried out for the dual-motor torque increasing hybrid power system model and the proposed improved energy control strategy. The results show that the fuzzy logic control strategy optimized by simulated annealing particle swarm optimization algorithm (SimuAPSO-FLC) has the best effect and meets the requirements of high efficiency, high mobility and stability of the emergency rescue vehicle.

Highlights

  • If the power is less than 100kW and the state of charge (SOC) is in the dischargeable range, the vehicle will run in the pure electric mode, otherwise the vehicle control mode is determined by the fuzzy logic control strategy

  • particle swarm optimization (PSO) algorithm is selected as the basic optimization algorithm, the nine parameters x1-x9 are taken as the spatial dimensions of the particle swarm, and the fuel consumption of the vehicle is taken as the optimization objective

  • SIMULATION AND EXPERIMENT In order to verify the correctness and practicability of the fuzzy control strategy and optimization algorithm designed in this study, the emergency rescue hybrid power simulation model is first built on the Simulink platform, and offline simulation was performed; the hardware in the loop simulation system of driver-vehicle controller is built on dSPACE platform, and the real-time performance and effectiveness of the optimized control strategy are verified by the experiment

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Summary

INTRODUCTION

The multi-power sources hybrid electric system can adapt to different driving conditions by changing the energy distribution between the several power sources, thereby it can improve the rapid response and fuel economy of the emergency rescue vehicle. J. Xue et al.: Improved Energy Management Strategy for 24t Heavy-Duty Hybrid Emergency Rescue Vehicle the control strategy based on fuzzy rules has better robustness and adaptability [9]–[13]. B. MAIN CONTRIBUTIONS In this paper, a new method of fuzzy control parameter configuration is proposed considering the optimization accuracy and difficulty, and the simulated annealing algorithm is introduced into the improved PSO algorithm, which absorbs the advantages of fast convergence speed, simple algorithm, high optimization efficiency and good optimizing ability.

CONTROL MODEL OF THE HYBRID ELECTRIC SYSTEM
DESIGN OF VEHICLE ENERGY MANAGEMENT
VARIABLE FUZZIFICATION
FUZZY PARAMETERS OPTIMIZATION BASED ON IMPROVED PSO ALGORITHMS
SimuAPSO ALGORITHM
SIMULATION AND EXPERIMENT
CONCLUSION
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