Title: A strategy for vehicle air resistance and rolling resistance calculation based on the hierarchical estimation method
Authors: Jun Luo; Jiaxi Guan; Xinglin Zhou; Pan Zhu
Addresses: School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China ' Hubei Institute of Measurement and Testing Technology, Wuhan, Hubei, 434000, China ' School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China ' School of Machinery and Automation, Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China
Abstract: To accurately calculate the air resistance and rolling resistance of the moving vehicle, we propose an adaptive hierarchical estimation method. Firstly, real-time road slope is obtained by correcting the accelerometer with angular velocity short-time integration. Then, a sliding mode observer (SMO) is employed to estimate the vehicle's longitudinal driving force and tyre lateral force. The road slope estimated by fusion algorithm and tyre force obtained from sliding mode observer are used as inputs for an adaptive extended Kalman filter (AEKF) with proportional parameters, enabling the separate estimation of tyre rolling resistance coefficient and air resistance coefficient. Further, the rolling resistance for different tyres is calculated by applying vertical loads. In the hierarchical algorithm, a new SMO, AEKF, and fast slope fusion algorithm are introduced, enhancing the precision and robustness of the algorithm. Finally, the effectiveness of the algorithm is validated through simulation tests and real vehicle experiments.
Keywords: vehicle dynamics; rolling resistance; air resistance; parameter estimation; EKF; extended Kalman filter.
DOI: 10.1504/IJVSMT.2024.140497
International Journal of Vehicle Systems Modelling and Testing, 2024 Vol.18 No.2, pp.152 - 174
Received: 17 Feb 2024
Accepted: 16 Apr 2024
Published online: 20 Aug 2024 *