Energy-Efficient Operation Curve Optimization for High-Speed Train Based on GSO Algorithm

The demand for high-speed automatic train operation (ATO) system brings new opportunities and challenges for the high-speed railway field. The requirements of energy consumption, punctuality, safety and smoothness are also increasing, especially the research on energy saving of high-speed trains ushers in a broader development space. This paper proposes quantitative functions of four energy-saving performance indexes and the multi-objective optimization model of train operation curve considering the characteristics of high-speed train ATO system. An energy-saving optimization method of train operation curve based on Glowworm Swarm Optimization (GSO) algorithm is proposed. The simulation results show that the train operation using the high-speed train operation curve optimization method based on the GSO algorithm can save about 16.9% of electrical energy consumption per kilometer compared with that by other optimization algorithms, which verifies the effectiveness of the method. The result from this paper provides theoretical support for practical application.