Optimization Strategies for High-Speed Electrical Trains Based on Artificial Intelligence for Cost and Energy Reduction

Nature-inspired evolutionary algorithms are used to optimize a train’s operation by decreasing its traction energy under various limitations. During the optimization process, cruising and coasting phases of driving can be initiated by a series of switch points. High-speed train energy efficiency is studied using an ATC method to optimize the speed curve across the entire line. The goal is to create a first stage optimization speed curve that can be used as a baseline. Artificial intelligence has seen widespread use in the creation of high-speed trains in recent years (AI). An overview of relevant fields in high-speed train engineering, including as civil engineering, mechanical design, electrical design and signal and control systems design, is provided in the first section of this study. On to a look at the state of the art of artificial intelligence (AI) in the context of high-speed train system design, control, and maintenance. As a final point, a framework for future high-speed train systems where AI is likely to play a significant role is offered.