Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter

被引：15

作者：

Moaveni, Bijan ^{[1
]}

Abad, Mahdi Khosravi Roqaye ^{[1
]}

Nasiri, Sayyad ^{[2
]}

机构：

[1] Iran Univ Sci & Technol, Sch Railway Engn, POB 16846-13114, Tehran, Iran

[2] Sharif Univ Technol, RADA, Tehran, Iran

来源：

VEHICLE SYSTEM DYNAMICS | 2015年 / 53卷 / 10期

关键词：

vehicle longitudinal velocity estimation; Kalman filter; unknown input; real-time systems; STATE; SYSTEMS; DESIGN; OBSERVER; FORCES;

D O I：

10.1080/00423114.2015.1038279

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

In this paper, vehicle longitudinal velocity during the braking process is estimated by measuring the wheels speed. Here, a new algorithm based on the unknown input Kalman filter is developed to estimate the vehicle longitudinal velocity with a minimum mean square error and without using the value of braking torque in the estimation procedure. The stability and convergence of the filter are analysed and proved. Effectiveness of the method is shown by designing a real experiment and comparing the estimation result with actual longitudinal velocity computing from a three-axis accelerometer output.

引用

页码：1373 / 1392

页数：20

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