摘要
为改进列车节能优化策略,结合既有节能操纵经验与典型子区间思想,引入自适应遗传算法,在列车满足安全、准点、乘车舒适等约束条件的前提下,寻找各工况转换点,使列车运行能耗最小。首先介绍列车停车制动曲线,限速防护曲线的计算方法,通过预制列车停车制动曲线,限速防护曲线,修正列车速度曲线,达到了提高遗传算法可行解比例,加速算法的迭代进程的目的。然后详细说明了遗传算法染色体、遗传算子,适应度函数及迭代收敛条件;自适应机制的应用增强遗传算法全局搜索能力。最后以武汉至新乌龙泉线路为案例,验证了节能优化算法的有效性。
In order to improve the train energy saving optimization strategy, the existing energy saving operation experiences and typical sub-interval thought were combined and the Adaptive Genetic Algorithm was introduced, to seek for the switching point and make the train operation energy consumption minimum, under different working con- ditions. Fire, the preconditions of safety, punctuality and comfortable were fulfilled, the train parking brake curve and the computing method of speed limit protection curve were introduced, and the train speed curve was fixed by prefabricating the train parking brake curve and the speed limit protection curve to achieve the purpose of enhancing the proportion of feasible genetic algorithm solution and accelerating the algorithm iterative process. Then, we ex- plained the choice method of chromosomes and operator of genetic algorithm as well as the fitness function and itera- tive convergence conditions in detail. The application of adaptive mechanism strengthens the global searching capabil- ity of genetic algorithm. The line of Wuhan toXinwulongquan was taken as an example which shows that this energy saving optimization algorithm is of validity.
出处
《计算机仿真》
CSCD
北大核心
2012年第11期350-354,共5页
Computer Simulation
基金
列车运行控制及牵引供电系统仿真技术研究(2009BAG12A01-A04-1)
关键词
节能优化
自适应
遗传算法
Energy-saving optimization
Self-adaptive
Genetic algorithm
