Estimation of longitudinal force, lateral vehicle speed and yaw rate for four-wheel independent driven electric vehicles

被引：89

作者：

Chen, Te ^{[1
]}

Xu, Xing ^{[1
,2
]}

Chen, Long ^{[1
,2
]}

Jiang, Haobing ^{[1
]}

Cai, Yingfeng ^{[1
,2
]}

Li, Yong ^{[1
,2
]}

机构：

[1] Jiangsu Univ, Sch Automot & Traff Engn, Zhenjiang 212013, Peoples R China

[2] Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Peoples R China

来源：

MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2018年 / 101卷

基金：

中国国家自然科学基金;

关键词：

Longitudinal force; Lateral vehicle speed; Yaw rate; High-order Sliding Mode Observer (HSMO); Electric vehicle; EXTENDED KALMAN FILTER; SIDESLIP ANGLE ESTIMATION; TIRE CORNERING STIFFNESS; DYNAMICS CONTROL; GROUND VEHICLE; ROAD; COEFFICIENT; GPS/INS; SENSORS; MODEL;

D O I：

10.1016/j.ymssp.2017.08.041

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Accurate estimation of longitudinal force, lateral vehicle speed and yaw rate is of great significance to torque allocation and stability control for four-wheel independent driven electric vehicle (4WID-EVs). A fusion method is proposed to estimate the longitudinal force, lateral vehicle speed and yaw rate for 4WID-EVs. The electric driving wheel model (EDWM) is introduced into the longitudinal force estimation, the longitudinal force observer (LFO) is designed firstly based on the adaptive high-order sliding mode observer (HSMO), and the convergence of LFO is analyzed and proved. Based on the estimated longitudinal force, an estimation strategy is then presented in which the strong tracking filter (STF) is used to estimate lateral vehicle speed and yaw rate simultaneously. Finally, co-simulation via Carsim and Matlab/Simulink is carried out to demonstrate the effectiveness of the proposed method. The performance of LFO in practice is verified by the experiment on chassis dynamometer bench. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：377 / 388

页数：12

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