Energy-saving operation optimization of middle-low-speed Maglev train based on genetic algorithm

摘要

This paper reviews prior Maglev train traction calculation methods and proposes one traction strategy depending on fixed time. Meanwhile, minimum energy consumption model is built under limited Maglev train operation time. Multi-population evolutionary algorithm is used to optimize the train's energy saving. Based on elitism preservation and immigrant strategies, the optimization process is rapidly converge and the stability is enhanced. Finally, the validity and advancement of the proposed strategy is verified by an actual calculation.