Overview of improved dynamic programming algorithm for optimizing energy distribution of hybrid electric vehicles
•Analyzed how dynamic programming algorithms participate in the control optimization of energy management strategies.•Discussed the limitations and improvement directions of dynamic programming algorithms in energy management control optimization.•Proposed improvements to dynamic programming algorit...
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| Veröffentlicht in: | Electric power systems research Jg. 232; S. 110372 |
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| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier B.V
01.07.2024
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| Schlagworte: | |
| ISSN: | 0378-7796, 1873-2046 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •Analyzed how dynamic programming algorithms participate in the control optimization of energy management strategies.•Discussed the limitations and improvement directions of dynamic programming algorithms in energy management control optimization.•Proposed improvements to dynamic programming algorithms from the perspectives of the curse of dimensionality and real-time performance.•Conducted a comprehensive comparison and evaluation of the optimization effects of the enhanced DP algorithms in energy management strategies.
An effective energy management strategy can effectively distribute output power between different power sources in the hybrid system to improve the dynamic performance of hybrid electric vehicles. As a global optimization algorithm, dynamic programming algorithm has the characteristics of multi-stage decision-making and recursive calculation. It can solve the theoretical optimal solutions of fuel economy, charging cost in energy management strategies, and provide optimization references for other control strategies. Research has shown that energy management strategies based on dynamic programming can achieve a 20 % to 50 % improvement in fuel economy and a 10 % to 30 % savings in charging costs. On the basis of analyzing the process and problems of dynamic programming algorithms, this article systematically analyzes the correlation and prominent characteristics between dynamic programming algorithms and energy management strategies for electric vehicles, and explains in detail how dynamic programming algorithms participate in the control optimization of energy management strategies. An in-depth analysis was conducted on the improvement research of dynamic programming algorithms in terms of "dimensional disaster" and real-time performance, as well as their performance in energy management neighborhood optimization control. And based on these improved dynamic programming algorithms, the optimization results of the electromagnetic system of electric vehicles were evaluated and relevant predictions were made. These comprehensive and summary conclusions provide innovative ideas and theoretical support for current researchers to explore the potential of global optimization strategies and the future improvement direction of dynamic programming algorithms. |
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| ISSN: | 0378-7796 1873-2046 |
| DOI: | 10.1016/j.epsr.2024.110372 |