Citation

Singh KB, Arat MA, Taheri S. Veh. Syst. Dyn. 2019; 57(11): 1643-1665.

Copyright

(Copyright © 2019, Informa - Taylor and Francis Group)

DOI

10.1080/00423114.2018.1544373

PMID

unavailable

Abstract

Most modern day automotive chassis control systems employ a feedback control structure. Therefore, real-time estimates of the vehicle dynamic states and tire-road contact parameters are invaluable for enhancing the performance of vehicle control systems, such as anti-lock brake system (ABS) and electronic stability program (ESP). Today's production vehicles are equipped with onboard sensors (e.g. a 3-axis accelerometer, 3-axis gyroscope, steering wheel angle sensor, and wheel speed sensors), which when used in conjunction with certain model-based or kinematics-based observers can be used to identify relevant tire and vehicle states for optimal control of comfort, stability and handling. Vehicle state estimation is becoming ever more relevant with the increased sophistication of chassis control systems. This paper presents a comprehensive overview of the state-of-the-art in the field of vehicle and tire state estimation. It is expected to serve as a resource for researchers interested in developing vehicle state estimation algorithms for usage in advanced vehicle control and safety systems.

Language: en

Keywords

Kalman filter; recursive least squares; sliding mode observer; State estimation; vehicle dynamics