Non-linear tyre model-based non-singular terminal sliding mode observer for vehicle velocity and side-slip angle estimation

被引:16
作者
Li, Boyuan [1 ,2 ]
Du, Haiping [2 ]
Li, Weihua [3 ]
Zhang, Bangji [1 ]
机构
[1] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha, Hunan, Peoples R China
[2] Univ Wollongong Australia, Sch Elect Comp & Telecommun Engn, Wollongong, NSW 2522, Australia
[3] Univ Wollongong Australia, Sch Mech Mat & Mechatron Engn, Wollongong, NSW, Australia
基金
澳大利亚研究理事会;
关键词
Side-slip angle estimation; Dugoff tyre model; sliding mode method; EXTENDED KALMAN FILTER; TIRE FORCE ESTIMATION; ELECTRIC VEHICLES; FUSION ALGORITHM; DESIGN; IDENTIFICATION; STATE;
D O I
10.1177/0954407018788720
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Vehicle velocity and side-slip angle are important vehicle states for the electronic stability programme and traction control system in vehicle safety control system and for the control allocation method of electric vehicles with in-wheel motors. This paper proposes an innovative side-slip angle estimator based on the non-linear Dugoff tyre model and non-singular terminal sliding mode observer. The proposed estimation method based on the non-linear tyre model can accurately present the tyre's non-linear characteristics and can show advantages over estimation methods based on the linear tyre model. The utilised Dugoff tyre model has a relatively simple structure with few parameters, and the proposed non-linear observer can be applied in various vehicle tyres and various road conditions. Precise determination of the Dugoff tyre model parameters is not required and the proposed observer can still perform good estimation results even though tyre parameters and the tyre-road friction coefficient are not accurate. The proposed non-singular terminal sliding mode observer can achieve fast convergence rate and better estimation performance than the traditional sliding mode observer. At the end of this paper, simulations in various conditions are presented to validate the proposed non-linear estimator.
引用
收藏
页码:38 / 54
页数:17
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