铁道标准设计2024，Vol.68Issue(7)：192-199,8.DOI:10.13238/j.issn.1004-2954.202210190004
改进麻雀算法在列车ATO多目标优化中的应用
Application of Improved Sparrow Algorithm in Multi-objective Optimization of Train ATO
摘要
Abstract
Aiming at the multi-objective optimization problem of automatic train operation(ATO)process,a multi-objective optimization model is established by using fuzzy membership functions,taking train operation safety,train dynamics model and other factors as constraints,and considering train punctuality,energy consumption,comfort and other indicators.The penalty function is used to deal with the constraints.The parking error and speed limit are used as penalty terms and appropriate penalty functions are constructed and added to the original objective function to obtain the augmented objective function,and a solution strategy based on improved sparrow algorithm(ISSA)is proposed.In order to improve the global optimization ability of sparrow algorithm(SSA)and avoid converging to local optimum,Logistic mapping,adaptive hyper-parameters and mutation operator are introduced to improve the traditional sparrow algorithm.The performance of sparrow algorithm is verified by test functions,which shows that the convergence speed and optimization precision of ISSA algorithm are better than those of traditional SSA algorithm.Taking the operation mode transition point as the decision variable,the ISSA algorithm is used to optimize the position and speed of the operation mode transition point,and then the target speed-distance curve is obtained.Finally,vehicle parameters and line data of urban rail transit are selected for simulation verification.The simulation results show that the comfort of the proposed optimization strategy is improved by 21.22% and the energy consumption is reduced by 22.41% compared with those before optimization.The punctuality and parking error meet the requirements.Compared with the PSO optimization method,the convergence speed is faster,the energy consumption is reduced by 12.74% under the condition of almost the same running time,and the energy saving effect is better.The parking error is reduced by 20.45%,and the comfort is maintained within the comfort range.For the speed-distance curve,the cruising distance is longer,the coasting distance is shorter,and the maximum running speed is reduced.It can be seen that the purpose of comprehensive optimization of ATO is achieved,which verifies the effectiveness of the ISSA optimization strategy.关键词
城市轨道交通/列车自动驾驶/多目标优化/目标速度曲线/改进麻雀算法/模糊隶属度/罚函数Key words
urban rail transit/automatic train operation(ATO)/multi-objective optimization/target speed curve/improved sparrow search algorithm(ISSA)/fuzzy membership functions/penalty functions分类
交通工程引用本文复制引用
王一栋,肖宝弟,岳丽丽,李茂青,林俊亭..改进麻雀算法在列车ATO多目标优化中的应用[J].铁道标准设计,2024,68(7):192-199,8.基金项目
中国国家铁路集团有限公司科技研究开发计划项目(N2021G045) （N2021G045）
甘肃省教育厅优秀研究生"创新之星"项目(2022CXZX-535) （2022CXZX-535）
