Energy-saving optimization solution for multiple freight trains based on maFOA algorithm
Unlike traditional energy-saving optimization methods for freight trains, which focus solely on reducing the mechanical energy consumption of the trains, the freight train energy-saving optimization approach integrating the traction drive system and AC traction network models concentrates on lowerin...
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| Format: | Article |
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Editorial Department of Electric Drive for Locomotives
2024-09-01
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| Series: | 机车电传动 |
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| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.05.003 |
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| author | LAN Li LI Le MA Ruijie |
| author_facet | LAN Li LI Le MA Ruijie |
| author_sort | LAN Li |
| collection | DOAJ |
| description | Unlike traditional energy-saving optimization methods for freight trains, which focus solely on reducing the mechanical energy consumption of the trains, the freight train energy-saving optimization approach integrating the traction drive system and AC traction network models concentrates on lowering energy consumption at traction substations. This study began by building models to simulate train dynamics, traction drive systems, and AC traction networks, collectively forming a "train-track-grid" model based on their coupling relationships. Relevant state variables were converted from the spatial domain to the time domain using a linear interpolation method. Additionally, a multi-strategy adaptive fruit fly optimization algorithm for population partitioning (maFOA) was proposed, to address the challenges faced by existing algorithms in solving complex nonlinear “train-track-grid" models, which often result in low convergence accuracy. The effectiveness of the proposed energy-saving optimization strategy for multiple freight trains was verified through experiments. The results exhibit a 49.2% improvement from the strategy in the regenerative braking energy utilization rate, along with a 0.35% reduction in traction network losses. |
| format | Article |
| id | doaj-art-894521d07c624bed8190be7ed92fdb6d |
| institution | OA Journals |
| issn | 1000-128X |
| language | zho |
| publishDate | 2024-09-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-894521d07c624bed8190be7ed92fdb6d2025-08-20T02:28:58ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2024-09-01172578096649Energy-saving optimization solution for multiple freight trains based on maFOA algorithmLAN LiLI LeMA RuijieUnlike traditional energy-saving optimization methods for freight trains, which focus solely on reducing the mechanical energy consumption of the trains, the freight train energy-saving optimization approach integrating the traction drive system and AC traction network models concentrates on lowering energy consumption at traction substations. This study began by building models to simulate train dynamics, traction drive systems, and AC traction networks, collectively forming a "train-track-grid" model based on their coupling relationships. Relevant state variables were converted from the spatial domain to the time domain using a linear interpolation method. Additionally, a multi-strategy adaptive fruit fly optimization algorithm for population partitioning (maFOA) was proposed, to address the challenges faced by existing algorithms in solving complex nonlinear “train-track-grid" models, which often result in low convergence accuracy. The effectiveness of the proposed energy-saving optimization strategy for multiple freight trains was verified through experiments. The results exhibit a 49.2% improvement from the strategy in the regenerative braking energy utilization rate, along with a 0.35% reduction in traction network losses.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.05.003multiple freight trains"train-track-grid" modelenergy-saving optimizationmaFOA algorithmheavy-haul train |
| spellingShingle | LAN Li LI Le MA Ruijie Energy-saving optimization solution for multiple freight trains based on maFOA algorithm 机车电传动 multiple freight trains "train-track-grid" model energy-saving optimization maFOA algorithm heavy-haul train |
| title | Energy-saving optimization solution for multiple freight trains based on maFOA algorithm |
| title_full | Energy-saving optimization solution for multiple freight trains based on maFOA algorithm |
| title_fullStr | Energy-saving optimization solution for multiple freight trains based on maFOA algorithm |
| title_full_unstemmed | Energy-saving optimization solution for multiple freight trains based on maFOA algorithm |
| title_short | Energy-saving optimization solution for multiple freight trains based on maFOA algorithm |
| title_sort | energy saving optimization solution for multiple freight trains based on mafoa algorithm |
| topic | multiple freight trains "train-track-grid" model energy-saving optimization maFOA algorithm heavy-haul train |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2024.05.003 |
| work_keys_str_mv | AT lanli energysavingoptimizationsolutionformultiplefreighttrainsbasedonmafoaalgorithm AT lile energysavingoptimizationsolutionformultiplefreighttrainsbasedonmafoaalgorithm AT maruijie energysavingoptimizationsolutionformultiplefreighttrainsbasedonmafoaalgorithm |