A novel method for identifying inertial parameters of electric vehicles based on the dual H infinity filter

• Published in: Vehicle system dynamics Vol. 58; no. 1; pp. 28 - 48
• Main Authors: Gong, Xinle, Suh, Jongsang, Lin, Cheng
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.01.2020; Taylor & Francis Ltd
• Subjects: Algorithms; Computer simulation; Control systems design; Dual H infinity filter (DHIF); Electric vehicles; electric vehicles (EVs); H-infinity control; hardware-in-the-loop (HIL); Hardware-in-the-loop simulation; nonlinear vehicle model; Order parameters; Parameter estimation; Parameter identification; state estimation
• ISSN: 0042-3114; 1744-5159
• DOI: 10.1080/00423114.2019.1566559

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.