Longitudinal force estimation for motorized wheels driving electric vehicle based on improved closed-loop subspace identification
1. School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China; 2. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu 212013, China
Abstract:In order to realize the control and coordinated allocation of tire longitudinal force for motorized wheels driving electric vehicle, a longitudinal force estimation method was proposed based on improved closed-loop subspace identification. The characteristics of electric drive system of motorized wheels driving vehicle was analyzed to propose a longitudinal force estimation model. The road simulation test on chassis dynamometer was carried out, and the experimental data were collected. The subspace identification algorithm N4SID was deviated when model input and noise were correlated. To solve the problem, an improved closed-loop subspace identification method was investigated. The results show that compared with N4SID identification method, the improved closed-loop subspace identification method has better anti-interference ability with higher longitudinal force estimation accuracy and better real-time tracking capability, which can meet the requirements of driving force model predictive control based on data driving.