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基于模糊控制的电驱动2AMT换挡控制策略
引用本文:刘成强,徐海港,张建武,林连华. 基于模糊控制的电驱动2AMT换挡控制策略[J]. 山东科学, 2020, 33(4): 101-109. DOI: 10.3976/j.issn.1002-4026.2020.04.013
作者姓名:刘成强  徐海港  张建武  林连华
作者单位:山东时风(集团)有限责任公司,山东 聊城252800;上海交通大学 机械与动力工程学院,上海200240
基金项目:泰山领军人才工程项目(SF1503002002);山东省科技重大专项(2015ZDXX0601C01)
摘    要:换挡控制直接影响电动汽车的动力性和经济性,已成为电动汽车发展方向之一。由于各个厂家设计开发差异,动力性与经济性的换挡规律有较大差别。针对时风D102车型,通过检测车辆加速度得到驾驶风格,并将模糊控制算法引入到换挡规律中,实现车辆动力性和经济性的协调。最后利用Simulink模型进行循环工况下的仿真分析,得出模糊控制算法换挡规律在减少耗电量的同时能够兼顾汽车的动力性,使汽车具有较好的综合性能,能适用于大部分工作状态。

关 键 词:电驱动自动机械式变速器  换挡规律  模糊控制  仿真分析
收稿时间:2020-02-02

Development of a shift control strategy for an electric 2AMTusing fuzzy control logic
LIU Cheng-qiang,XU Hai-gang,ZHANG Jian-wu,LIN Lian-hua. Development of a shift control strategy for an electric 2AMTusing fuzzy control logic[J]. Shandong Science, 2020, 33(4): 101-109. DOI: 10.3976/j.issn.1002-4026.2020.04.013
Authors:LIU Cheng-qiang  XU Hai-gang  ZHANG Jian-wu  LIN Lian-hua
Affiliation:1.Shifeng Group Co.,Ltd.,Liaocheng 252800, China;2.School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;
Abstract:Shift control directly impacts the power and cost of electric vehicles.It is one of the important development directions for intelligent automobiles. Owing to the differences in design and development approaches of various manufacturers, there is a considerable difference in the dynamic and economic shift rules. This study focuses on the Shifeng D102 model.The dirving style is obtained by detecting the acceleration of the vehicle, and the fuzzy control algorithm is introduced into the shift rule to achieve the coordination of vehicle dynamics and cost. Finally, the Simulink model is used for performing simulation analysis under cyclic conditions, and the fuzzy control algorithm shift rule is considered to reduce power consumption while with respect to the vehicle′s dynamic performance, which results in an enhanced comprehensive performance, rendering it suitable for most working conditions.
Keywords:electric automated mechanical transmission  shift rule  fuzzy control  simulation analysis  
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