A study on the vehicle state estimation for a distributed-drive EV based on LO-EKF algorithms

作者：Lin Cheng^*; Wang Gang; Cao Wanke; Zhou Fengjun

来源：Qiche Gongcheng/automotive Engineering, 2014, 36(11): 1316-1320.

• Distributed-drive electric vehicle
• Extended Kalman filter
• Luenberger observer
• Road slope observation
• Vehicle state estimation

A study on vehicle state estimation is conducted for a distributed-drive electric vehicle in this paper. Firstly Luenberger observer (LO) is adopted to observe the road slope, which has significant effects on vehicle state estimation. Then extended Kalman filter (EKF) algorithm is used with the data information obtained from ESP sensor as observed value, the dynamics state variables of distributed-drive electric vehicle are estimated. Finally a Carsim-Matlab co-simulation is performed. The results show that the proposed vehicle state estimation algorithm based on LO and EKF is feasible and can well estimate the relevant dynamics state variables of vehicle with a rather high convergence speed.

• 出版日期2014
• 单位北京理工大学