Group-SMA Algorithm Based Joint Estimation of Train Parameter and State

Wei Zheng
National Research Center of Rail Transportation Operation and Control System,Beijing Jiaotong University,Beijing,China; Humboldt Researcher in the institute of traffic safety and automation engineering,Technical University of Braunschwieg,Braunschweig, Germany

Juan Han
National Research Center of Rail Transportation Operation and Control System,Beijing Jiaotong University,Beijing,China;

Weijie Kong
National Research Center of Rail Transportation Operation and Control System,Beijing Jiaotong University,Beijing,China;

Lixiang Wang
National Engineering Research Center of Rail Transportation Operation and Control System,
Beijing Jiaotong University,
No.3 Shangyuancun, Xizhimenwai, Haidian District,Beijing, 100044, China


Abstract

The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA) based on Rao-Blackwellization Particle Filter (RBPF) algorithm and Stochastic M-algorithm (SMA) is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA.