Research on vehicle speed estimation algorithm based on AMESim platform

Author

Xi, Lian ; Xiaohua, Xie ; Fankunr, Meng

Author_Institution

State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China

fYear

2012

fDate

23-25 May 2012

Firstpage

3039

Lastpage

3044

Abstract

To get the exact vehicle speed can effectively improve vehicle control performance in the vehicle´s safety control system. Depending on the simulation advantage of AMESim, the highly precise vehicle model is built as an experimental model reference model, and then adaptive kalman filter algorithm combining with the AMESim and matlab co-simulation was adopted to realize estimation of vehicle speed. In the AMESim simulation environment the algorithm was verified with the different working conditions. The simulation results show that the estimated effect is good.

Keywords

Kalman filters; adaptive filters; control engineering computing; mathematics computing; road safety; road vehicles; traffic engineering computing; AMESim platform; MATLAB cosimulation; adaptive Kalman filter algorithm; experimental model reference model; vehicle control performance improvement; vehicle safety control system; vehicle speed estimation algorithm; Adaptation models; Estimation; Kalman filters; Mathematical model; Tires; Vehicles; Wheels; AMESim and matlab Co-Simulation; Adaptive kalman filter; vehicle speed;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244478

Filename

6244478