微型电脑应用2017，Vol.33Issue(2)：54-57,65,5.
基于遗传算法的电动车动力系统性能匹配优化设计
Performance Optimization Design of Power Systems of Electric Vehicle Based on Genetic Algorithm
摘要
Abstract
In order to increase the driving range and improve the overall performance of all-electric vehicles,a new dual-motor hybrid driving system with two power sources was proposed.The system achieved torque-speed coupling between the two power sources and greatly improved the high performance working range of the motors;at the same time,continuously variable transmission (CVT) was achieved to efciently increase the driving range.The power system parameters were determined using the global optimization method where the vehicle's dynamics and economy were used as the optimization indexes.Based on preliminary matches,quantum genetic algorithm was introduced to optimize the matching in the dual-motor hybrid power system.Backward simulation was performed on the combined simulation platform of Matlab/Simulink and AVL-Cruise to optimize,simulate,and verify the system parameters of the transmission system.Results showed that quantum genetic algorithms exhibited good global optimization capability and convergence in dealing with muhiobjective and multiparameter optimization.The dual-motor hybriddriving system satisfied the dynamic performance and economy requirements of electric cars,efciently increased the driving range of the car,had high performance,and reduceq energy consumption of 15.6 ％ compared with the conventional electric vehicle with single-speed reducers.关键词
电动汽车/动力系统/遗传算法/优化/匹配Key words
Electric vehicles/Driving system/Genetic algorithm/Optimization/Matching分类
信息技术与安全科学引用本文复制引用
魏胜君..基于遗传算法的电动车动力系统性能匹配优化设计[J].微型电脑应用,2017,33(2):54-57,65,5.
