• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2019, Vol. 55 ›› Issue (18): 112-124.doi: 10.3901/JME.2019.18.112

• 运载工程 • 上一篇    

基于驾驶意图识别的多模耦合驱动系统能量管理

张利鹏1, 贾启康1, 刘威1, 赵玉勤2   

  1. 1. 燕山大学河北省特种运载装备重点实验室 秦皇岛 066004;
    2. 燕山大学河北省并联机器人与机电系统重点实验室 秦皇岛 066004
  • 收稿日期:2018-11-10 修回日期:2019-06-19 发布日期:2020-01-07
  • 通讯作者: 赵玉勤(通信作者),女,1963年出生,高级实验师。主要研究方向为复杂机电系统控制。E-mail:yqzhao@ysu.edu.cn
  • 作者简介:张利鹏,男,1979年出生,博士,教授。主要研究方向为车辆动力学与控制、新能源汽车复合传动。
  • 基金资助:
    国家自然科学基金(51775478)和河北省自然科学基金(E2016203173)资助项目。

Energy Management of Multi-mode Coupling Drive System Based on Driver Intention Recognition

ZHANG Lipeng1, JIA Qikang1, LIU Wei1, ZHAO Yuqin2   

  1. 1. Hebei Key Laboratory of Special Delivery Equipment, Yanshan University, Qinhuangdao 066004;
    2. Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao 066004
  • Received:2018-11-10 Revised:2019-06-19 Published:2020-01-07

摘要: 匹配多模耦合驱动系统可以使插电式混合动力汽车具备高效的集中式与分布式耦合驱动功能,但基于该系统所开展的整车经济性研究尚且不足。为降低整车能耗,开展基于驾驶意图识别的系统能量优化管理。利用模糊推理控制器识别不同工况驾驶员的驾驶意图,根据该驱动系统动力耦合方式、发动机工作特性和电机效率进行驱动模式分类;建立燃油经济性目标函数,采用瞬时优化方法分配发动机和主副电机转矩输出,以此为基础提出基于驾驶意图识别的能量管理策略;搭建模糊推理模型和整车模型,将新欧洲驾驶循环工况和实际车速采集结果作为测试工况,进行整车经济性的仿真分析。结果表明,所搭建模糊推理模型能准确识别驾驶员意图,采用所制定能量管理策略进行系统工作模式优选和转矩分配,使整车的燃油经济性得到了明显提高。针对多模耦合驱动系统开的这一能量优化研究,为系统高效利用奠定了理论基础。

关键词: 插电式混合动力汽车, 多模耦合驱动系统, 模糊推理, 驾驶意图, 能量管理

Abstract: The matched multi-mode coupling drive system can make the plug-in hybrid vehicle have high-efficiency centralized and distributed coupling drive functions, but the research on the vehicle economics based on the system is still insufficient. In order to reduce the vehicle energy consumption, the system energy optimization management based on driving intention identification is carried out. A fuzzy inference controller is used to identify the driver intention under different driving conditions. The working mode is classified according to the system dynamic coupling modes, the engine operating characteristic and the motors efficiency. The fuel economy objective function is established. The equivalent consumption minimization strategy (ECMS) as instantaneous optimization method is used to distributed the engine, the main motor and the auxiliary motor's torque. Finally, the energy management strategy based on the driver intention recognition is proposed. The fuzzy inference model and the vehicle model are built, and the new europe driving cycle (NEDC)and actual speed test results are taken as the simulated cycle to carry out the simulation analysis of the vehicle economy. Research results indicate that the fuzzy inference model canidentify the driver intentions effectively, the drive modes switchand the drive torque distribution can be easily implemented according to the control strategy, which significantly improves the vehicle fuel economy. This energy optimization study for the multi-mode coupling drive system for the first time laid the theoretical foundation for efficient use of the system.

Key words: plug-in hybrid electric vehicle, multi-mode coupling drive system, fuzzy inference, driver intention, energy management

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