Title: Active front steering control strategy based on estimation of vehicle state and mass identification

Authors: Changqing Jing; Hongyu Shu; Yitong Song; Tong Wu

Addresses: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China ' College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China ' College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China ' College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400044, China

Abstract: This paper mainly focuses on the application and feasibility of the active front steering controller. The desired yaw rate is a key input of AFS controller, but the desired yaw rate needs to be calculated by the two degrees of freedom vehicle model when the actual mass of the vehicle changes, when the mass of the reference model does not change, this will have a great influence on the AFS controller. Furthermore, the vehicle state and vehicle mass are difficult to measure in real-time. To solve these problems, the AFS control strategy based on estimation of vehicle state and mass identification is proposed. The simulation results demonstrate that the AFS controller based on vehicle state estimation and mass identification could effectively improve the vehicle lateral stability when the vehicle mass changes.

Keywords: unscented Kalman filter; UKF; state estimation; active front steering; AFS; mass identification.

DOI: 10.1504/IJVNV.2021.123426

International Journal of Vehicle Noise and Vibration, 2021 Vol.17 No.3/4, pp.253 - 272

Received: 03 Jul 2020
Accepted: 04 May 2021
Published online: 20 Jun 2022 *

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