Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.