关键词: 交通运输工程；高速列车；节能优化；多质点模型；满载率；鲸鱼算法

Abstract: 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.

Key words: traffic and transportation engineering; high-speed train; energy-saving optimization; multi-mass model; full load rate; whale algorithm