基于遗传算法的追踪列车节能优化

卢启衡; 冯晓云; 王青元

doi:10.3969/j.issn.0258-2724.2012.02.016

基于遗传算法的追踪列车节能优化

doi: 10.3969/j.issn.0258-2724.2012.02.016

基金项目:

国家科技支撑计划资助项目(2009BAG12A05)

详细信息

作者简介:
卢启衡(1972－),男,博士研究生,研究方向为轨道交通电气化与自动化,电话:13683435672,E-mail:luqiheng@gmail.com

通讯作者:
冯晓云(1962－),女,教授,博士生导师,研究方向为现代交流传动及其控制

计量
- 文章访问数: 1672
- HTML全文浏览量: 80
- PDF下载量: 521
- 被引次数: 0
出版历程
- 收稿日期: 2010-04-05
- 修回日期: 2010-10-27
- 刊出日期: 2012-04-25

Energy-Saving Optimal Control of Following Trains Based on Genetic Algorithm

摘要

摘要: 为了研究追踪列车的节能优化操纵策略,提出了四显示固定闭塞系统下的列车静态速度约束条件和追踪列车动态速度约束条件.在此基础上,建立了以列车操纵手柄级位和工况转换点为控制变量的追踪列车节能优化模型.采用染色体长度可变多目标遗传算法,结合外部惩罚函数对该模型进行了求解，并利用遗传算法中的染色体变长算子对列车操纵手柄变换策略进行了优化.在四显示固定闭塞平台上的仿真结果表明,该方法可在安全、准点的前提下,使追踪列车的能耗下降4.3%,运行时间误差减小1.7%.
- 列车节能优化控制 /
- 追踪列车 /
- 动态速度约束 /
- 列车操纵手柄变换策略优化 /
- 染色体长度可变多目标遗传算法
Abstract: In order to study the optimum operating strategy for energy saving of the following train in a following operation, the static speed constraints of the trains and the dynamic speed constraints of the following train were put forward under a four-aspect fixed autoblock system. On this basis, an energy-saving optimal operation model of the following train was created taking the train control notch and the corresponding train position as control variables. With the help of the external punishment function, the model was solved by the changeable chromosome length multi-objective genetic algorithm (GA). The shifting strategy of the train control notch was optimized using the chromosome length mutation operator of GA to determine the change times of the train control notch during the whole trip. The simulation result from a four-aspect fixed autoblock system simulation platform shows that the method can reduce the energy consumption and trip time error of the following train by 4.3% and 1.7%, respectively, on the premise of safety and punctuality.

HTML全文

参考文献(1)

　冯晓云. 模糊预测控制及其在列车自动驾驶中的应用研究[D. 成都:西南交通大学,2001. 　　　　　[2]　LI Keping, GAO Ziyou, NING Bing. Cellular automaton model for railway traffic[J. Journal of Computational Physics, 2005, 209(1): 179-192. 　　　　　[3]　LI Keping, GAO Ziyou, NING Bing. Modeling the railway traffic using cellular automation model[J. International Journal of Modern Physics C, 2005, 16(6): 921-932. 　　　　　[4]　周华亮,高自友,李克平. 准移动闭塞系统的元胞自动机模型及列车延误传播规律的研究[J. 物理学报,2006,55(4): 1706-1710. 　　　　　ZHOU Hualiang, GAO Ziyou, LI Keping. Cellular automaton model for moving-like block system and study of train's delay propagation[J. Acta Physica Sinica, 2006, 55(4): 1706-1710. 　　　　　[5]　付印平. 列车追踪运行与节能优化建模及模拟研究[D. 北京:北京交通大学,2009. 　　　　　[6]　CHANG C S, SIM S S. Optimizing train movements through coast control using genetic algorithm[J. IEEE Proc. of Electr. Power Appl., 1997, 144(1): 65-73. 　　　　　[7]　苟先太. 列车操纵优化及遗传算法的应用研究[D. 成都:西南交通大学,1997. 　　　　　[8]　HAN S H, BYEN Y S, BAEK J H, et al. An optimal automatic train operation(ATO) control using genetic algorithms(GA)[J. IEEE TENCON: 1999(1): 360-362. 　　　　　[9]　朱金陵,李会超,王青元,等. 列车节能控制的优化分析[J. 中国铁道科学,2008,29(2): 104-108. 　　　　　ZHU Jinling, LI Huichao, WANG Qingyuan, et al. Optimization analysis on the energy saving control for trains[J. China Railway Science, 2008, 29(2): 104-108. 　　　　　[10]　丁勇,毛保华. 定时约束条件下列车节能操纵仿真算法研究[J. 系统仿真学报,2004,16(10): 2241-2244. 　　　　DING Yong, MAO Baohua. An algorithm for energy-efficient train operation simulation with fixed running time[J. Journal of System Simulation, 2004, 16(10): 2241-2244. 　　　　[11]　刘海东,毛保华,丁勇,等. 城市轨道交通列车节能问题及方案研究[J. 交通运输系统工程与信息,2007,7(5): 68-73. 　　　　LIU Haidong, MAO Baohua, DING Yong, et al. Train energy-saving scheme with evaluation in urban mass transit systems[J. Journal of Transportation Systems Engineering and Information Technology, 2007, 7(5): 68-73. 　　　　[12]　LU Qiheng, FENG Xiaoyun. Optimal control strategy for energy saving in trains under the four-aspect fixed autoblock system[J. Journal of Modern Transportation, 2011, 19(2): 82-87. 　　　　[13]　中华人民共和国铁道部. TB/T 14071998 列车牵引计算规程[S. 北京:中国铁道出版社,1998. 　　　　[14]　李玉生,侯忠生. 基于遗传算法的列车节能控制研究系统[J. 系统仿真学报,2007,19(2): 1-4. 　　　　LI Yusheng, HOU Zhongsheng. Study on energy-saving control for train based on genetic algorithm[J. Journal of System Simulation, 2007, 19(2): 1-4. 　　　　[15]　石红国. 列车运行过程仿真及优化研究[D. 成都: 西南交通大学,2006.

施引文献

附加材料(0)

访问统计