Driving Force Control of Hub Motor Vehicle Based on Off-road Condition Identification

doi:10.3969/j.issn.1004-132X.2023.08.010

China Mechanical Engineering ›› 2023, Vol. 34 ›› Issue (08): 955-965.DOI: 10.3969/j.issn.1004-132X.2023.08.010

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Driving Force Control of Hub Motor Vehicle Based on Off-road Condition Identification

FU Xiang1，2，3;WANG Yuxin1，2，3;LIU Daoyuan1，2，3;WANG Jijie1，2，3

1.Hubei Key Laboratory ofAdvanced Technology for Automotive Components，Wuhan University
of Technology，Wuhan，430070
2.Hubei Collaborative Innovation Center for Automotive Components Technology，Wuhan University
of Technology，Wuhan，430070
3.Hubei Research Center for New Energy & Intelligent Connected Vehicle，Wuhan University of
Technology，Wuhan，430070

Online:2023-04-25 Published:2023-05-17

基于越野工况辨识的轮毂电机车辆驱动力控制

付翔1，2，3;王玉新1，2，3;刘道远1，2，3;王纪杰1，2，3

1.武汉理工大学现代汽车零部件技术湖北省重点实验室，武汉，430070
2.武汉理工大学汽车零部件技术湖北省协同创新中心，武汉，430070
3.武汉理工大学湖北省新能源与智能网联车工程技术研究中心，武汉，430070

作者简介:付翔，女，1973年生，副教授。研究方向为新能源汽车整车控制技术、动力系统。发表论文23篇。E-mail：759263695@qq.com。

Abstract

Abstract: According to the shortcomings of the existing condition recognition strategy in identifying undulating terrain and variable adhesion road surfaces， based on the LuGre tire model， observation space equations were constructed to quickly identify the transient changes of adhesion conditions. The real-time working conditions were mapped with 6 typical working conditions based on fuzzy control algorithm， and a closed-loop control strategy was designed to adaptively adjust the real-time output torque of hub motors based on the working condition identification results. Simulation test and real vehicle verification show that the drive force control strategy based on the off-road condition identification may quickly track the transient changes of each wheel adhesion limit and grounding state， and adaptively adjust the real-time driving power of the vehicle to achieve comprehensive optimization of vehicle power performance and stability.

Key words: , hub motor vehicle, fuzzy control algorithm, off-road condition identification, driving force control

摘要： 针对现有工况辨识策略在识别地形起伏度、变附着路面的不足，基于LuGre轮胎模型构建观测空间方程来快速捕捉附着条件的瞬态变化，基于模糊控制算法将实时工况与6种典型工况映射，根据工况辨识结果设计了闭环控制策略以自适应调节轮毂电机的实时输出力矩。仿真测试与实车验证表明，基于越野工况辨识的驱动力控制策略可快速跟踪各轮附着极限和接地状态的瞬态变化，自适应调节车辆的实时驱动功率，达到车辆动力性与稳定性的综合优化。

关键词: 轮毂电机车辆, 模糊控制算法, 越野工况辨识, 驱动力控制

CLC Number:

U467

FU Xiang, WANG Yuxin, LIU Daoyuan, WANG Jijie, . Driving Force Control of Hub Motor Vehicle Based on Off-road Condition Identification[J]. China Mechanical Engineering, 2023, 34(08): 955-965.

付翔, 王玉新, 刘道远, 王纪杰, . 基于越野工况辨识的轮毂电机车辆驱动力控制[J]. 中国机械工程, 2023, 34(08): 955-965.

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Driving Force Control of Hub Motor Vehicle Based on Off-road Condition Identification

基于越野工况辨识的轮毂电机车辆驱动力控制

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