• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2020, Vol. 56 ›› Issue (18): 123-133.doi: 10.3901/JME.2020.18.123

• 运载工程 • 上一篇    下一篇

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考虑复杂激励条件的分布式驱动电动汽车路面附着系数自适应估计方法

熊璐1,2, 金达1,2, 冷搏1,2, 余卓平1,2, 杨兴1,2   

  1. 1. 同济大学汽车学院 上海 201804;
    2. 同济大学新能源汽车工程中心 上海 201804
  • 收稿日期:2019-12-05 修回日期:2020-05-27 出版日期:2020-09-20 发布日期:2020-11-17
  • 通讯作者: 冷搏(通信作者),男,1991年出生,博士。主要研究方向为车辆运动控制、状态辨识与参数估计。E-mail:harrisonleng@gmail.com
  • 作者简介:熊璐,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为汽车系统动力学与控制。E-mail:xiong_lu@tongji.edu.cn
  • 基金资助:
    国家重点研发计划(2018YFB0104805)和国家自然科学基金(51975414,U1564207)资助项目。

Adaptive Tire-road Friction Estimation Method for Distributed Drive Electric Vehicles Considering Multiple Road Excitations

XIONG Lu1,2, JIN Da1,2, LENG Bo1,2, YU Zhuoping1,2, YANG Xing1,2   

  1. 1. School of Automotive Studies, Tongji University, Shanghai 201804;
    2. Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804
  • Received:2019-12-05 Revised:2020-05-27 Online:2020-09-20 Published:2020-11-17

摘要: 路面峰值附着系数是实现车辆高品质运动控制的关键参数,参数估计的精度与实时性会极大地影响控制的效果,而多数动力学估计算法受限于车辆的激励条件,难以达到满意的估计效果。设计一种模糊自适应路面附着系数融合估计方法,充分利用车辆纵侧向激励,以实现算法对车辆不同行驶工况的估计适应能力。分别设计不同激励条件下的路面附着系数估计方法,通过车辆状态参数判断满足的激励条件,模糊推理出当前纵侧向轮胎力所能达到的极限,并据此设计融合观测器进行估计结果融合。多工况仿真和实车试验的结果表明,融合观测器在高低附路面下和不同轮胎力激励时能快速估计出路面的峰值附着系数,估计精度较高,同时对轮胎力纵侧耦合的工况具有一定的鲁棒自适应性。

关键词: 分布式驱动电动汽车, 路面估计, 模糊自适应, 信息融合

Abstract: The road friction coefficient is a key parameter for high-quality vehicle motion control. The accuracy and real-time of the parameter estimation results greatly affect the quality of control and most of the dynamic estimation methods are limited by the vehicle's excitation conditions and it is difficult to achieve satisfactory results. So, a fuzzy adaptive road friction coefficient fusion estimation method is designed to make full use of the vehicle's longitudinal and lateral excitations to achieve the algorithm's ability to adapt to different driving conditions of the vehicle. The road friction coefficient estimation methods under different excitation conditions are designed respectively. The vehicle condition parameters are used to determine the excitation conditions and the limit of the current longitudinal and lateral tire force can be inferred by fuzzy logic, and a fusion observer is designed to estimate the results. The results of simulation and real test show that the fusion method can quickly estimate the road friction coefficient under high μ and low μ roads and different tire force excitations and the estimation accuracy is high. The method has robust self-adaptability to the working conditions of tire force longitudinal and lateral coupling.

Key words: distributed drive electric vehicle, road estimation, fuzzy adaptive, information fusion

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