基于遗传算法的电动汽车TBW综合换档优化方法研究

Research on TBW comprehensive shift optimization method for electric vehicle based on genetic algorithm

为解决电动汽车动力不足和行驶里程短的问题,提出了一种基于遗传算法的电动汽车三档线控自动变速器综合换档优化方法。在分析了加速性能最优的动力性换档方法和电机效率最优的经济性换档方法的基础上,把加速度变化率和能量消耗变化率分别作为动力性和经济性评价函数,利用遗传算法建立换档优化模型,通过反复迭代优化得到电动汽车三档线控自动变速器综合换档方法曲线,并从加速度变化率和电机功率偏移率两个方面分别对优化前后的动力性和经济性进行对比分析。结果表明:优化后换档过程(一档升二档、二档升三档)的动力性能分别平均提高了4.96%和14.23%;加速踏板开度在70%以下时经济性能分别平均提高了10.61%和2.54%,但当加速踏板开度大于70%时电机功率均达到峰值则无法体现优化效果。可见,经过遗传算法优化后的综合换档方法能有效地提升整车动力性并增加行驶里程。

In order to solve the problem of power shortage and limited driving range for electric vehicle,an optimization method based on genetic algorithm for electric vehicle three-gear TBW shifting was proposed.Based on the analysis of dynamic gear-shift method with optimal acceleration performance and economic gear-shift method with optimal motor efficiency,the acceleration change rate and energy consumption change rate were defined as dynamic and economic evaluation function respectively.The gear-shift optimization model was established by using genetic algorithm.The electric vehicle three-gear TBW overall gear-shift method curve was obtained by repeated iteration optimization.And the dynamic and economic performance before and after optimization were analyzed from the perspective of acceleration rate and motor power migration rate.The optimized results indicate that the dynamic performances were increased by average of 4.96%and 14.23%respectively during the process of shifting(first gear up-to second gear,second gear up-to third gear),and economic performances were increased by average of 10.61%and 2.54%respectively when the accelerator pedal opening was below 70%.The optimization effect is unable to be available when the accelerator pedal opening was greater than 70%and when the motor power reached peak state.The overall gear-shift method optimized based on genetic algorithm can effectively improve dynamic performance and increase the mileage.