基于maFOA算法的多列货运车节能优化方法研究  

Energy-saving optimization solution for multiple freight trains based on maFOA algorithm

作　　者：兰力 李乐 马睿杰 LAN Li;LI Le;MA Ruijie(CHN ENERGY Shuohuang Railway Development Co.,Ltd.,Beijing 100080,China)

机构地区：[1]国能朔黄铁路发展有限责任公司,北京100080

出　　处：《机车电传动》2024年第5期17-25,共9页Electric Drive for Locomotives

基　　金：国家自然科学基金项目(U2268210)。

摘　　要：传统的货运列车节能优化方法只能降低列车机械能耗,而结合传动系统和交流牵引网模型的货运列车节能优化可以降低牵引变电所的能耗。文章首先构建了列车动力学模型、牵引传动系统模型和交流牵引网模型,通过它们之间的耦合关系形成“车-线-网”模型,同时利用线性插值的方法完成状态量从空间域到时间域的转换,但是现有的算法在解决复杂的非线性“车-线-网”模型存在困难,导致模型的收敛精确度不高。针对该问题,文章提出了多策略自适应果蝇优化算法(multi strategy adaptive fruit fly optimization algorithm for population partitioning,maFOA)。最后,通过试验验证了文章提出的货运多列车节能优化策略的有效性。试验结果表明,该策略可提高49.2%的再生制动能量利用率,降低0.35%的牵引网损耗。Unlike traditional energy-saving optimization methods for freight trains,which focus solely on reducing the mechanical energy consumption of the trains,the freight train energy-saving optimization approach integrating the traction drive system and AC trac-tion network models concentrates on lowering energy consumption at traction substations.This study began by building models to simu-late train dynamics,traction drive systems,and AC traction networks,collectively forming a"train-track-grid"model based on their cou-pling relationships.Relevant state variables were converted from the spatial domain to the time domain using a linear interpolation meth-od.Additionally,a multi-strategy adaptive fruit fly optimization algorithm for population partitioning(maFOA)was proposed,to address the challenges faced by existing algorithms in solving complex nonlinear"train-track-grid"models,which often result in low conver-gence accuracy.The effectiveness of the proposed energy-saving optimization strategy for multiple freight trains was verified through ex-periments.The results exhibit a 49.2%improvement from the strategy in the regenerative braking energy utilization rate,along with a 0.35%reduction in traction network losses.

关 键 词：货运多列车 “车-线-网”模型 节能优化 maFOA算法 重载列车 

分 类 号：U268.6[机械工程—车辆工程]