Cascaded method for running state estimation of four-wheel independent drive electric vehicles

被引：0
|
作者：
Chen T. [1 ]
Chen L. [1 ,2 ]
Cai Y. [1 ,2 ]
Xu X. [1 ,2 ]
Jiang H. [1 ,2 ]
机构：
[1] School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang
[2] Automotive Engineering Research Institute, Jiangsu University, Zhenjiang
来源：
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | 2019年 / 50卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Electric vehicle; Four-wheel independent drive; High order sliding mode observer; Longitudinal force estimation; Vehicle state;
D O I：
10.11817/j.issn.1672-7207.2019.01.030
中图分类号：
学科分类号：
摘要：
The vehicle model with 3 degree of freedom and the tire model were established. An electric drive wheel model was presented and applied to the longitudinal force estimation. The estimation of tire longitudinal force was realized based on the adaptive high order sliding mode observer. Using the output values of longitudinal force observer as the known input and combining the information fusion filter algorithm, a vehicle state joint estimation method was proposed. The simulation, bench test and road test were carried out. The results show that the designed longitudinal force observer has high estimation accuracy, and the information fusion filter-based vehicle state estimation method can track the vehicle state in real time and has better estimation performance than extended Kalman filter. © 2019, Central South University Press. All right reserved.
引用
收藏
页码：241 / 249
页数：8
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