Nonlinear Hybrid Multipoint Model of High-Speed Train with Traction/Braking Dynamic and Speed Estimation Law

Chao Jia, Hongze Xu and Longsheng Wang

Mathematical Problems in Engineering, 2019, vol. 2019, 1-14

Abstract:

This paper establishes a NHMPM (Nonlinear Hybrid Multipoint Model) for HST (High-Speed Train) with the traction/braking dynamic and speed estimation law. Firstly, a full-order flux observer is designed using regional pole assignment theory to calculate the electromagnetic torque. The traction and braking forces are obtained according to this electromagnetic torque. Then the basic running resistance force is reformulated by considering the aerodynamic drag distribution characteristics, and the nonlinear in-train coupling force is analyzed as well. Next, the NHMPM including integer variables of running status and car types is built, where an adaptive parameter estimation algorithm and a speed estimation law are proposed to estimate unknown resistance coefficients and train speed, respectively. The effectiveness of the proposed algorithm, law, and NHMPM is verified through numerical simulations last.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1364657

DOI: 10.1155/2019/1364657

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