基于智能计算的城轨列车节能优化操纵研究

Research on Energy-saving Optimized Control Technology of Urban Rail Transit Trains Based on Intelligent Computing

伴随着城市轨道交通运营里程的增长,城轨列车节能优化操纵技术是近年研究的热点课题.节能优化操纵对城轨列车高效运营具有重要的经济意义和社会效益.目前,对于这一问题的研究,主要依靠现场试验和专家经验为主.本文针对某市城轨交通实际线路,提出一种基于巡航速度和距离结合的非线性约束优化方案,分别采用智能计算领域的粒子群算法与遗传算法对节能优化操纵曲线进行求解.结果表明,使用粒子群算法和遗传算法计算得到的节能优化操纵曲线可对列车运营提供指导建议.

With the rapid growth of urban rail transit mileage, the energy-saving optimised control technology of urban rail trains is a hot topic in recent years. The optimised operation of energy-saving is of great economic significance and social benefit to the actual operation of urban rail transit. At present, the research on this issue mainly relies on field trials and experts experience. In this paper, a nonlinearly constrained optimisation scheme based on the combination of cruising speed and cruising distance is proposed for an actual urban rail transit line. The particle swarm optimisation and genetic algorithm in the intelligent computing field are used to solve the energy-saving optimisation operation curve. The experimental results show that the results obtained by particle swarm optimisation and genetic algorithm can guide train operation.