Parameter Optimization of Pure Electric Vehicle Power System Based on Genetic Algorithm

Zheng Ying, Qin Peng, Zheng Xianfeng, Wu Hao, Lin Zihan

Abstract


In this paper, the ADVISOR software was used to establish a complete vehicle model of an electric vehicle, and the model was verified by CYC_NEDC under European urban conditions to meet the requirements. The maximum power of the driving motor, the speed ratio of the transmission system and the capacity of the storage battery are taken as the optimization objectives to carry out multi-objective optimization. Connect the model built by genetic algorithm and ADVISOR, run the program to simulate the two together, and get the result of parameter optimization of dynamic system. Through the simulation analysis and comparison under CYC_NEDC cycle conditions, the maximum speed, maximum climb slope, acceleration time and other dynamic performance parameters of this electric vehicle are effectively improved after optimization.

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DOI: https://doi.org/10.22158/jetr.v1n2p1

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Copyright (c) 2020 Zheng Ying, Qin Peng, Zheng Xianfeng, Wu Hao, Lin Zihan

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