Adaptive anti-slip control of train based on online adhesion sensing

Abstract

This work aims to improve the anti-slip control of railway trains during the braking process and enhance the braking performance of the trains. Taking the air braking system of rail vehicles as the research object, and centering on the wheel-rail adhesion-slip characteristics and the theory of online parameter estimation, an adaptive anti-slip control strategy for trains based on online adhesion perception is proposed. Firstly, an online parameter estimator is built to conduct online perception of the rail surface adhesion coefficient. The slope of the wheel-rail adhesion-slip characteristic curve is parametrically estimated, and an anti-slip control strategy based on adhesion perception is established to achieve adaptive anti-slip control of the train during the braking process. A semi-physical simulation test bench based on the air braking system verified the accuracy of the adhesion perception method and compared and analyzed the anti-slip control strategies under different working conditions. The test results show that adaptive control during the braking process can be achieved, the braking distance can be shortened, and the braking performance of the train can be improved.

Keywords

rolling stock braking anti-slip parameter estimation adhesion sensing adaptive control

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