Study on Generation of Energy-saving Driving Curves of High-speed Train Based on Pareto Multi-objective Optimization

被引：0

作者：

Zhang H. ^{[1
,3
]}

Jia L. ^{[1
,4
]}

Wang L. ^{[2
,3
]}

机构：

[1] State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing

[2] School of Traffic and Transportation, Beijng Jiaotong University, Beijing

[3] Beijing Engineering Research Center of Urban Traffic Information Intelligent Sensing and Service Technologies, Beijing

[4] National Engineering Laboratory for System Safety and Operation Assurance of Urban Rail Transit, Guangzhou

来源：

Tiedao Xuebao/Journal of the China Railway Society | 2021年 / 43卷 / 03期

关键词：

Energy-efficient driving; Multi-objective optimization; Pareto curve; Railway transportation; Simulation;

D O I：

10.3969/j.issn.1001-8360.2021.03.011

中图分类号：

学科分类号：

摘要：

Energy-saving driving refers to the driving method with the least energy consumed by a train in a given running time, which is an important energy-saving measure for the railway system. Considering the long distance and complex line conditions of high-speed railway, and the characteristics of train operation being easily disturbed and deviating from the original plan, this paper aims to generate a set of energy-saving driving curves balancing the energy consumption and time. A method capable of simplifying the frequently changing line conditions was designed and an improved algorithm was proposed, namely Non-dominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ), which combines differential evolution algorithm and a new congestion distance operator. On the basis of non-fixed step size simulation method, the generation of energy-saving driving curve set with energy consumption-time balance was realized. In the case of actual high-speed railway data, a set of feasible strategies was obtained by simulation calculation, which can provide railway managers with effective alternatives under disturbance conditions and lay a foundation for the optimization of energy-saving timetable. © 2021, Department of Journal of the China Railway Society. All right reserved.

引用

页码：85 / 91

页数：6