|Table of Contents|

Performance parameter estimation method of high-speed train based on Rao-Blackwellised particle filter(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2014年03期
Page:
52-57
Research Field:
载运工具运用工程
Publishing date:

Info

Title:
Performance parameter estimation method of high-speed train based on Rao-Blackwellised particle filter
Author(s):
DING Jian-ming1;  LIN Jian-hui1;  WANG Han2;  HUANG Chen-guang1;  ZHAO Jie1
1. State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, Sichuan, China; 2. CSR Sifang Co., Ltd., Qingdao 266111, Shandong, China
Keywords:
high-speed train;  performance parameter;  RBPF;  parameter estimation
PACS:
U260.11
DOI:
-
Abstract:
In order to solve the nonlinear problems caused in augmenting the state vector of the performance parameters of high-speed train, a method of parameter estimation based on Rao-Blackwellised particle filter(RBPF)was developed. Under the framework of Rao-Blackwellised(RB)principle, the probabilistic model of parameter estimation was divided. The Kalman filter(KF)was applied for the prediction time step and measurement update of linear state block and the RBPF was applied for the prediction time step and measurement update of nonlinear parameter block to realize the dynamic estimation. Through theoretical analysis and parameter estimation example of high-speed train, the validity of RBPF method for parameter dynamic estimation was verified. Analysis result shows that compared with the classical extended KF(EKF)method, RBPF method has the characteristics of initial immunity and algorithm stability. RBPF method shows its good engineering applicability for the minor parameter estimation error which is less than 5%, and inexistence of estimation deviation. 7 figs, 15 refs.

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Last Update: 2014-06-30