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Urban rail transit, characterized by safety, efficiency, punctuality, and speed, plays a significant role in urban transportation, facilitating people's mobility. However, the operation of urban rail transit consumes a consider- able amount of energy, resulting in high operating costs and impeding its further development. In this study, focusing on the operation within a single train interval, an improved genetic algorithm is employed to optimize the train's speed profile, aiming to minimize the traction energy consumption within the interval. Additionally, the deviation in speed profiles due to variations in train's basic resistance parameters is analyzed, and corresponding correction schemes are proposed. Simulation results demonstrate that a single traction/braking scheme in the train correction plan leads to lower traction energy consumption and better alignment with the operational requirements of urban rail transit.
Zhang et al. (Tue,) studied this question.