Abstract
The learning-based energy management strategy (EMS) is able to optimize the control of the heterogeneous multi-energy drive system (HMDS) by learning relevant offline data or online data and centralized training, and therefore realizes lower consumption and higher efficiency. Moreover, it is equally of great important for HMDS to select an appropriate drive structure as it is to develop a suitable energy management strategy. In this paper, domestic and overseas development situation of HMDS is discussed. Moreover, it describes the drive structure of the present HMDS and then introduces the research status of two learning-based EMS in HMDS. In addition, the actual implementation prospect and challenges of learning-based energy management strategy are proposed by further analysis.
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Acknowledgements
This work is supported by National Key R&D Program of China, No. 2017YFB1201003, Basic Research, No. JCKY2018110C113.
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Ren, X., Zhang, X., Duan, D., Diao, L. (2020). A Survey: Learning-Based Energy Management Strategy for Heterogeneous Multi-energy Drive System. In: Jia, L., Qin, Y., Liu, B., Liu, Z., Diao, L., An, M. (eds) Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019. EITRT 2019. Lecture Notes in Electrical Engineering, vol 638. Springer, Singapore. https://doi.org/10.1007/978-981-15-2862-0_38
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DOI: https://doi.org/10.1007/978-981-15-2862-0_38
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