Energy management strategy for electrically-powered hydraulic vehicle based on driving mode recognition

The effectiveness of the energy management strategy directly impacts the overall system performance of a vehicle, particularly under various driving modes. This paper proposes a novel electrically-powered hydraulic vehicle that integrates a hydraulic transmission system with an electric powertrain....

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Vydané v:Energy sources. Part A, Recovery, utilization, and environmental effects Ročník 47; číslo 1; s. 2480 - 2503
Hlavní autori: Lin, Yanhong, Liu, Benyou, Zhang, Tiezhu, Zhang, Hongxin, Zhang, Zhen
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Taylor & Francis 31.12.2025
Predmet:
Active energy management
Electrically-powered hydraulic vehicle
Fuzzy control
genetic algorithm-backpropagation neural network
K-means clustering analysis
ISSN:1556-7036, 1556-7230
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Shrnutí:The effectiveness of the energy management strategy directly impacts the overall system performance of a vehicle, particularly under various driving modes. This paper proposes a novel electrically-powered hydraulic vehicle that integrates a hydraulic transmission system with an electric powertrain. A rule-based energy management strategy is developed to validate the feasibility of the system through steady-state simulation. To enhance system performance, Random Forest and gradient boosting tree algorithms are employed for velocity feature dimensionality reduction, while K-means clustering is used to segment driving modes. Subsequently, a genetic algorithm-optimized backpropagation neural network enables precise online driving mode recognition, and a fuzzy controller actively regulates energy flow in real time. Experimental results indicate that GBF-EMS achieves a final state of charge of 78.77%, reducing battery energy consumption by 16.26% compared to RB-EMS, 8.92% compared to RF-EMS and 2.52% compared to PMP-EMS. This study provides new insights into the further development and optimization of electro-hydraulic power systems.
ISSN:1556-7036
1556-7230
DOI:10.1080/15567036.2025.2452254