An Indirect Identification Method for Train Basic Resistance Parameters

Abstract

The train basic resistance characteristic is crucial for ATO performance. However, this characteristic is slow time-varying with wheel rail wear and fast time-varying with weather conditions. The parameters of train basic resistance are difficult to measure directly, usually only a set of empirical parameters can be obtained through repeated experiments. These factors result in an inconsistency between the model parameters in the ATO controller and the actual train basic resistance parameters (TBRP), leading to a decrease in the effectiveness of the model-based controller. Therefore, this paper proposes an indirect TBRP identification method based on speed trajectory fitting to improve the effectiveness of the TBRP for model-based ATO controllers. Firstly, the original TBRP identification problem is transformed into an optimization problem, which is to minimize the deviation between the actual speed trajectory and the model-calculated one. Then, the Newton’s method is used to accelerate the search for the best set of TBRPs with minimum deviation. Finally, case studies are used to verify the effectiveness of the proposed method.