基于IWOA的高速列车运行曲线节能优化研究

Energy-Saving Optimization of High-Speed Train Operation Curve Based on IWOA

为降低高速列车运行能耗,使列车经过变坡点和变曲率点的附加阻力计算更精确、更贴近实际,提出了一种改进的鲸鱼优化算法(improved whale optimization algorithm,IWOA),对高速列车的运行曲线进行节能优化。首先,建立高速列车多质点附加阻力模型;其次,考虑满载率对列车运行能耗的影响,以准时、准点、限速为约束条件,构建新的能耗模型;然后,用IWOA对中间线路牵引-惰性工况转换点的最优位置进行搜索,IWOA引入混沌映射策略、自适应收敛因子和哈里斯鹰围攻机制,能有效提高算法的收敛速度和寻优精度,全局搜索能力显著增强,从而实现高速列车进一步节能运行的目的。最后,以合肥站—蚌埠站线路参数与CRH3型高速列车参数为实例,基于MATLAB平台进行仿真。仿真结果表明:采用PSO算法、GA算法和IWOA对高速列车运行曲线进行节能优化,优化后的曲线使列车运行能耗分别降低了7.81%,10.16%和15.95%。因此,IWOA对列车节能优化效果更加明显。

In order to reduce the energy consumption of high-speed train operation and make the calculation of the additional resistance of the train passing through the point of variable slope and variable curvature more accurate and closer to the reality,an improved whale optimization algorithm(IWOA)was put forward to optimize the energy saving of high-speed train\s operation curve.Firstly,the multi-mass additional resistance model of high-speed train was established.Secondly,the influence of full load rate on the energy consumption of train operation was considered,and a new energy consumption model was constructed with ontime,punctuality,and speedlimit as the constraints.Thirdly,the optimal position of the intermediate line traction-inert condition transition point was searched by IWOA.IWOA introduced the chaotic mapping strategy,the self-adaptive convergence factor and the Harris Hawk siege mechanism,which could effectively improve the convergence speed and optimization accuracy of the algorithm,and its global search capability was greatly enhanced,so as to achieve the purpose of further energy-saving operation of high-speed trains.Finally,the simulation was carried out based on the MATLAB platform with the parameters of the Hefei Station-Bengbu Station line and the parameters of the CRH3 high-speed train as examples.The simulation results show that the PSO,GA algorithms and IWOA are used to optimize the energy saving of high-speed train operation curves,and the optimized curves reduce the energy consumption of train operation by 7.81%,10.16%and 15.95%respectively.Therefore,the effect of IWOA on train energy saving optimization is more obvious.