基于人工蜂群算法的高速列车运行节能优化研究

合理的列车操纵方式能在很大程度上降低列车运行过程中的能耗,为了有效降低高速列车运行能耗,从研究高速列车的操纵方式入手,首先建立列车牵引计算模型和列车运行能耗计算模型,其次通过对比人工蜂群算法(ABC算法)和粒子群算法(PSO算法)的优化性能证明ABC算法优于PSO算法,提出了在满足运行速度、运行时间以及运行区间等约束条件下,采用ABC算法与操纵工况序列相结合的方法来优化计算确定高速列车操纵工况关键转换点最优位置和速度。最后通过对选取线路的MATLAB仿真模拟,验算了ABC算法在降低列车运行能耗方面的有效性。研究表明,经过ABC算法优化后的结果均能满足优化操纵方式的基本操纵策略且达到了良好的优化效果,能较好地解决列车节能操纵优化问题。

Research on High-speed Train Operation Energy-saving Optimization Based on ABC Algorithm

Reasonable train control can reduce energy consumption during train operation to a large extent. In order to effectively reduce the energy consumption of high-speed train operation, we start from the research on train operation mode. Firstly, the train traction calculation model and train operation energy consumption calculation model are established. Then, optimization performance of artificial bee colony algorithm(ABC algorithm) is compared with that of the particle swarm optimization algorithm(PSO algorithm), which proves that the ABC algorithm is better than the PSO algorithm. Therefore the method of combining ABC algorithm with train control sequence is proposed to optimize and determine the optimal transition point position and the speed of high-speed train control under the condition that the speed, time, range and other constrains in operation are satisfied. Finally, through the MATLAB simulation of the selected line, the ABC algorithm is very effective in reducing energy consumption of the train. The research shows that the results obtained by ABC algorithm satisfies the basic control strategy of optimal operation mode and achieve good optimization effect, which can better solve the problem of train energy-saving operation optimization.