Road Friction Estimation using Recursive Total Least Squares

被引：0

作者：

Shao, Liang ^{[1
]}

Lex, Cornelia ^{[2
]}

Hackl, Andreas ^{[2
]}

Eichberger, Arno ^{[2
]}

机构：

[1] Graz Univ Technol, Graz, Austria

[2] Graz Univ Technol, Inst Automot Engn, Graz, Austria

来源：

2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2016年

关键词：

SYSTEMS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automated vehicles require information on the current road condition, i.e. the tire-road friction coefficient (mu(max)) for trajectory planning and braking or steering interventions. Recursive Total Least Squares (RTLS) is used to estimate mu(max) only utilizing the information from Electric Power System (EPS) and other sensors installed in production vehicles. A new state alpha(f)/mu(max) (front wheel slip angle divided by mu(max)) is introduced which is observed by a proposed nonlinear observer. This state serves as a measurement for friction estimation and judge when the estimation result is reliable. The proposed method is verified in IPG CarMaker.

引用

页码：533 / 538

页数：6

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