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

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 bi-level optimal control method is designed to calculate energy-optimal speed profile in real-time. Specifically, the upper level is to calculate the min-time speed profile based on the 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 on-line. To highlight the achievable improvements of the proposed optimal control method, a pseudo-spectral method and a quadratic programming method are introduced as performance comparison. Simulation results show that the proposed method yields 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 performances of punctuality and energy efficiency.