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分布式电驱动车辆状态感知与控制研究综述
引用本文:徐坤,骆媛媛,杨影,徐国卿. 分布式电驱动车辆状态感知与控制研究综述[J]. 机械工程学报, 2019, 55(22): 60-79. DOI: 10.3901/JME.2019.22.060
作者姓名:徐坤  骆媛媛  杨影  徐国卿
作者单位:1. 中国科学院深圳先进技术研究院 深圳 518055;2. 上海大学机电工程与自动化学院 上海 200444
基金项目:国家自然科学基金(61603377)、国家重点研发计划课题(2018YFB0104803)和台达电力电子科教发展基金(DREK2018011)资助项目。
摘    要:分布式电驱动车辆转矩响应快、全轮独立可控、制动能量可回收且可大幅度提升整车能效,对增强车辆安全性、操纵稳定性和运行节能性具有重要的意义。但须研究解决过驱动系统复杂性、非线性耦合、轮路接触非线性和不确定性等核心问题,这依赖于研究先进的状态感知和控制方法。从控制和状态感知的角度,基于功能目标对现有研究进行分类,综述分布式电驱动车辆的最新研究进展。状态感知为控制系统提供准确、可靠、快速的运动状态反馈信号,但面临车速估计难、传统检测方法带宽受限、复杂未知路面影响等挑战。控制系统首要目标是车辆安全稳定性,进而提升整车能效,并可通过多目标优化拓展其他复合功能,但面临多目标耦合干涉、异构多尺度执行系统同步协调、附着条件未知不确定、在线实时计算与全工况测试等关键挑战。充分利用分布式电驱动系统机电信号测量准确、简便、带宽高的优势,协同利用智能车体系的多源异构传感信息,是状态感知技术发展的重要思路;进一步挖掘分布式电驱动转矩响应快、全轮电制动能量回馈等优势,突破复杂、全工况、不确定条件下的多目标优化控制方法,是解决控制系统所面临挑战的重要思路。

关 键 词:分布式驱动  控制分配  状态感知  电动车辆  
收稿时间:2019-08-31

Review on State Perception and Control for Distributed Drive Electric Vehicles
XU Kun,LUO Yuanyuan,YANG Ying,XU Guoqing. Review on State Perception and Control for Distributed Drive Electric Vehicles[J]. Chinese Journal of Mechanical Engineering, 2019, 55(22): 60-79. DOI: 10.3901/JME.2019.22.060
Authors:XU Kun  LUO Yuanyuan  YANG Ying  XU Guoqing
Affiliation:1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055;2. School of Mechanics Engineering and Automation, Shanghai University, Shanghai 200444
Abstract:With the advantages of fast torque response, all-wheel independent control and braking energy recovering, the distributed drive electric vehicles (DDEVs) can significantly enhance vehicle's safety, handling, stability and energy saving. However, it needs to deal with the challenges, e.g., the over-actuated system complexity, nonlinear coupling, tire-road contact nonlinearity and uncertainty, which requires advanced state estimation and control technology. This paper surveys the recent research progress of DDEVs from the perspectives of control and state perception respectively. The state perception of DDEVs provides accurate, reliable and fast motion state feedback signals to the control system, which, however, needs to consider the limited bandwidth of traditional methods, and the unknown complex road surface. The control system improves the safety, efficiency and other motion performances via multi-objective optimization. However, it still faces the challenges involving coupling interference, multi heterogeneous actuation coordination, complex and uncertain adhesion conditions, online real-time optimization and field testing. Future research on state perception may further take advantage of the accurate and high bandwidth measurement of electromechanical signals, and use the multi-sensor information of intelligent vehicles. Exploring new multi-objective methods to use fast distributed torque and regenerative braking under complex and uncertain conditions is the research trend of advanced control system for DDEVs.
Keywords:distributed drive  control allocation  state estimation  electric vehicles  
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