Real-Time Energy-Efficient Driver Advisory System for High-Speed Trains

Abstract

An on-board energy-efficient driving advisory system is proposed for a high-speed train, which runs on a vehicle control unit. A data interaction framework is presented to monitor train real-time state and temporary speed limitations. A bilevel optimal control method is designed to calculate the energy-optimal speed profile in real time. Specifically, the upper level is to calculate the min-time speed profile based on Pontryagin’s maximum principle, and the lower level is to determine coast profiles according to the Lagrange multiplier technique. The driving advice is extracted from the optimized trajectories. If the deviation of the train trajectory is detected, the speed profile is updated online. To highlight the achievable improvements of the proposed optimal control method, a pseudospectral method and a quadratic programming method are introduced as performance comparison. Simulation results show that the proposed method yields an energy-optimal solution within a control cycle of 256 ms. The driver-in-the-loop tests prove that the driving advice can be exactly followed by drivers. The proposed driver advisory system can improve the performance of punctuality and energy efficiency.