Research on the Driving Strategy of Heavy-haul Train Based on Fuzzy Predictive Control

Aiming at the difficult point of generating driving strategy of heavy-haul trains under moving block system, a driving strategy generation method based on fuzzy predictive control is proposed for alleviating the labor intensity of drivers and better guaranteeing the operation safety of heavy-haul trains. Firstly, by analyzing the difficulties of driving heavy-haul trains in neutral sections and steep slopes, constraint models of driving strategy are established, and a speed curve optimization algorithm based on adaptive step size is designed. Then, the target speed curve is obtained by locally optimizing the driving strategy in difficult sections based on the principle of time equivalence and a fuzzy predictive controller is designed. Finally, use the actual train data and line data to validate the method. The results show that compared to the proportional integral derivative (PID) control method, the method proposed in this paper can control the train to run more placidly and the maximum error of tracking target speed is $\pm 0.23\mathrm{m}/\mathrm{s}$, which proves that the proposed method is applicable.