基于双重优化的高速列车节能运行研究

A Study on Energy-saving Operation of High-speed Trains based on Double Optimization

为了降低高速列车运行能耗,首先构建多质点列车模型,从而提高能耗计算的精准度,在此基础上,通过牵引计算,建立满足时间与限速约束条件的列车操纵模型,提出基于遗传算法的双重优化控制方法。第1重优化结合遗传算法得到离散子区间线路的列车运行最小能耗基础速度曲线;第2重优化是在基础速度曲线平稳运行阶段再次利用遗传算法搜索操纵工况转换点的最优位置,利用牵引-惰行模式进一步降低能耗。以合肥-蚌埠站间线路为例,利用MATLAB进行仿真,仿真结果表明,在满足列车准时到站的前提下,通过双重优化后的运行速度曲线能够使列车运行能耗降低15.53%。

In order to reduce the energy consumption during high-speed train operation,a multiparticle train model is built first to improve the precision of energy consumption calculation.Then the train control model that satisfies the constraints of time and speed limit is established on the basis of traction calculation,and a dual optimization control method based on genetic algorithm is put forward.The first optimization and genetic algorithm are combined to obtain the minimum energy consumption basic speed curve for trains running on discrete sub-interval lines.The second level of optimization reuses the genetic algorithm to search for the optimal position of the operating condition transition point again during the steady operation of the basic speed curve.Traction-idle mode reduces energy consumption again.When building a train optimization model,a multi-mass train model is used,which can make the calculation of energy consumption more accurate.In this paper,the line between Hefei and Bengbu stations is used as an example for simulation with MATLAB.The simulation results show that the energy consumption of high-speed train has been reduced by 15.53%after using the double optimization of the operating speed curve,which achieved the goal of energy-saving operation and the requirement of punctual arrival of the train.