汽车工程

汽车工程 ›› 2019, Vol. 41 ›› Issue (1): 14-20.doi: 10.19562/j.chinasae.qcgc.2019.01.003

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基于模式切换预估算法的DM-EV瞬时能耗最小控制策略*

林歆悠, 王黎明, 翟柳清   

  1. 1.福州大学机械工程及自动化学院,福州 350002;
    2.福建省高端装备制造协同创新中心,福州 350002
  • 收稿日期:2017-11-17 出版日期:2019-01-25 发布日期:2019-01-25
  • 通讯作者: 林歆悠,讲师,工学博士,E-mail:linxinyoou@fzu.edu.cn
  • 基金资助:
    *国家自然科学基金(51505086)和CAD/CAM福建省高校工程研究中心项目(K201710)资助。

A Study on Minimum Instantaneous Energy Consumption Control Strategy ofDM-EV Based on Mode Switching Prediction Algorithm

Lin Xinyou, Wang Liming, Zhai Liuqing   

  1. 1.College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350002;
    2.Collaborative Innovation Center of High-End Equipment Manufacturing in Fujian, Fuzhou 350002
  • Received:2017-11-17 Online:2019-01-25 Published:2019-01-25

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摘要： 为提高电动汽车经济性从而延长其续驶里程,以一款新型的多模式双电机耦合驱动构型电动汽车(DM-EV)作为研究对象,针对该电动汽车的系统构型及工作模式进行分析,重点研究了以瞬时能耗最小为目标,结合模式切换预估算法来进行优化的控制策略。通过仿真与台架试验验证了所提出控制策略与驱动构型的有效性。仿真结果表明,在城市拥堵工况、城市一般工况、高速公路工况下,采用模式切换预估算法可使汽车能量利用率分别提高2.2%,3.6%,1.7%。台架试验验证结果表明,所研究的驱动系统与一般单电机驱动系统对比,其能量利用率比后者分别提高14.2%,11.5%,10.1%。

关键词: 双电机驱动, 控制策略, 瞬时能耗最小, 预估算法, 台架试验

Abstract: In order to improve the economy of electric vehicles and extend the driving range, a new type of multi-mode dual-motor coupled drive electric vehicle (DM-EV) is taken as the research object, and the system configuration and working mode of the electric vehicle are analyzed, aiming at minimizing the instantaneous energy consumption, a control strategy based on the mode switching predictive algorithm is studied. The effectiveness of the proposed control strategy and drive configuration is verified by simulation and bench tests. The simulation results show that under urban congestion conditions, the urban general conditions and the highway conditions, the car energy utilization rate can increase by 2.2%,3.6%,1.7% respectively using the mode switch prediction algorithm. The bench test results show that compared with the general single motor drive system, the energy efficiency of the proposed drive system is improved by 14.2%,11.5%,10.1% respectively.

Key words: dual motor drive, control strategy, minimum instantaneous energy consumption, prediction algorithm, bench test