A novel method for identifying inertial parameters of electric vehicles based on the dual H infinity filter. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Gong, Xinle; Suh, Jongsang; Lin, Cheng
• Is Part Of: Vehicle system dynamics. Volume 58:Issue 1(2020)
• Page Start: 28
• Page End: 48
• Publication Date: 2020-01-02
• Subjects: Dual H infinity filter (DHIF) -- nonlinear vehicle model -- state estimation -- parameter identification -- electric vehicles (EVs) -- hardware-in-the-loop (HIL); Motor vehicles -- Dynamics -- Periodicals; Electronic journals; 629.231
• DOI: 10.1080/00423114.2019.1566559
• Languages: English
• ISSNs: 0042-3114

Abstract

ABSTRACT: Accurate identification of vehicle inertial parameters is essential to the design of vehicle dynamics control systems. In this paper, a novel vehicle inertial parameter identification method based on the dual H infinity filter (DHIF) for electric vehicles (EVs) is proposed. The filter algorithm employs a nonlinear longitudinal vehicle model with three vehicle states. A hierarchical framework is engaged by the DHIF to estimate the vehicle states and inertial parameters concurrently. In order to minimise the disturbance of unknown noise, the vehicle states are estimated by using the linear H infinity filter (LHIF), while the nonlinear H infinity filter (NHIF) utilises the observed states to identify the vehicle inertial parameters. Finally, the proposed estimation method is verified and compared through the dSPACE based hardware-in-the-loop (HIL) simulation experiments. The results indicate that the DHIF-based estimation method is effective to identify the vehicle inertial parameters with high precision, remarkable robustness, and quick convergence.