Real-time energy-efficient optimal control of high-speed electric train

This paper studies the real-time energy-efficient optimal control of high-speed electric trains within a given trip time. In particular, we focus on the re-optimization of the driving strategy, in the case that the actual train speed deviates from the planned optimal speed profile due to uncertainties. The proposed optimization algorithm has a double-loop structure with simultaneous action implementation. It results in reduced computation complexity and shortened control period, compared to the conventional double-loop algorithm with delayed action implementation. Existence and uniqueness of the solution to the re-optimization problem are discussed, and the convergence of the proposed simultaneous action method is proved. Moreover, it is shown by perturbation analysis that the resulting energy consumption during speed switching process is reduced. The effectiveness of the proposed method is demonstrated by the simulation study on two tracks of Dongguan-Huizhou intercity railway in China.