Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4916385 | Applied Energy | 2017 | 8 Pages |
Abstract
In order to ensure the safety and reliability of electric vehicles (EVs), the accurate center of gravity (CG) position estimation is of great significance. In this study, a novel approach based on combined Hâ-extended Kalman filter (Hâ-EKF) is proposed. Utilizing the characteristics of the wheel torque controlled independently, the estimation method only requires the longitudinal stimulus of vehicles and avoids other possible disadvantageous stimulus, such as the vehicle yaw or roll motion. Furthermore, additional parameters (suspension parameters, tire parameters, etc.) are unessential. To implement this estimation algorithm, a simplified vehicle dynamics model is applied to the filter formulation considering of the front wheel speed, the rear wheel speed and the longitudinal velocity of the vehicle. The designed estimator consists of two layers: the Hâ estimator is employed to filter states by means of minimizing the influence of unexpected noise whose statistics are unknown. Simultaneously, the other EKF estimator uses the states derived by the former filter to identify the CG position of the vehicle. Results indicate that the performance of the Hâ filter is superior to the standard KF and the proposed synthetic estimation algorithm is able to estimate the longitudinal location and the height of CG with acceptable accuracy.
Related Topics
Physical Sciences and Engineering
Energy
Energy Engineering and Power Technology
Authors
Cheng Lin, Xinle Gong, Rui Xiong, Xingqun Cheng,