基于知识的纯电动汽车两挡变速器挡位决策研究  

Research on Shift Decision of Two-Speed Transmissions in Battery Electric Vehicles Based on Knowledge

作　　者：翟克宁 张静晨 刘永刚[2] Zhai Kening;Zhang Jingchen;Liu Yonggang(Passenger Car Technology Center of Dongfeng Liuzhou Automobile Co.,Ltd.,Liuzhou 545005;State Key Laboratory of Mechanical Transmissions,Chongqing University,Chongqing 400044)

机构地区：[1]东风柳州汽车有限公司乘用车技术中心,柳州545005 [2]重庆大学,机械传动国家重点实验室,重庆400044

出　　处：《汽车技术》2023年第4期29-35,共7页Automobile Technology

基　　金：广西科技计划项目(2020GAAA0402)。

摘　　要：为了解决采用传统换挡规律时纯电动汽车在不同工况下难以获得最佳换挡性能的问题,提出了一种基于知识的两挡变速器挡位决策方法。首先,建立纯电动汽车动力学模型,通过动态规划获得最优挡位数据,基于支持向量机制定静态两参数换挡规律;然后采集驾驶员手动换挡数据构建专属知识库,基于长短时记忆网络建立智能挡位决策模型,通过空中下载技术实现挡位决策模型更新;最后通过仿真验证所提出方法的有效性。仿真结果表明,长短时记忆网络模型具有较高的挡位决策精度,所提出的基于知识的智能挡位决策方法相较于传统两参数换挡规律具有更好的换挡性能。To solve the problem that the traditional shift schedule of two-speed transmissions for battery electric vehicles cannot obtain the optimal shift performance under different conditions,this paper proposes a knowledge-based method for shift decision-making.Firstly,the dynamic model of battery electric vehicles was established,the optimal shift data was obtained by dynamic programming.The two-parameter shift schedule was extracted based on support vector machine.Secondly,the data of manual shift was collected to build an exclusive database.The intelligent shift decision model was built based on the long short-term memory network,and the shift decision model was updated online by overthe-air technology.Finally the proposed shift decision method was verified by simulation.The results show that long shortterm memory network model has high shift decision accuracy,the proposed knowledge-based shift decision method has better shifting performance than traditional two-parameter shift schedule.

关 键 词：纯电动汽车 挡位决策 动态规划 长短时记忆网络 

分 类 号：U463.21[机械工程—车辆工程]