摘要
针对有轨电车节能优化的问题,提出了基于粒子群优化算法的有轨电车节能优化方法。首先,从操纵策略的角度提出有轨电车节能优化问题;其次,分析有轨电车在站间运行时的操纵策略,研究不同操纵策略对有轨电车节能优化的影响;然后,引入粒子群优化算法,结合当前有轨电车广泛采用的2次巡航的经典操纵策略,建立基于粒子群优化算法的有轨电车多约束节能优化模型;最后,以某城市的有轨电车为算例,与同一司机多次驾驶和不同司机分别驾驶过程中的实际操纵策略进行对比,表明提出的优化方法可节省15%-28%的能耗。
To address the problem of energy-saving optimization of tram,an energy-saving optimization method of tram based on particle swarm optimization algorithm is proposed.First,the problem of tram energy-saving optimization is proposed from the perspective of maneuvering strategy;then,the maneuvering strategy of tram running between stations is analyzed to study the influence of different maneuvering strategies on tram energy-saving optimization;subsequently,the particle swarm optimization algorithm is introduced to establish a multi-constrained energy-saving optimization model of tram based on particle swarm optimization algorithm by combining the classical maneuvering strategy of 2 cruises which is widely used in trams at present;finally,a city tram is used as an arithmetic example to compare with the actual maneuvering strategy during multiple driving by the same driver and separate driving by different drivers,showing that the proposed optimization method can save 15%-28%of energy consumption.
作者
侯宇婷
蔡煊
Hou Yu-ting;Cai Xuan(School of Automobile and Transportation,Chengdu Technological University,Chengdu 611730,Sichuan Province,China)
出处
《科学与信息化》
2023年第2期85-90,共6页
Technology and Information
基金
成都工业学院校级科研项目,项目名称:100%低地板有轨电车牵引能耗优化研究,项目编号:2020ZR018。
关键词
有轨电车
操纵策略
节能优化
粒子群优化
tram
maneuvering strategy
energy-saving optimization
particle swarm optimization
