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An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

by Jiang, Dafa , Wang, Chao , Pei, Haoying , Xu, Chunmei , Huang, Yuanju , Li, Wang , Deng, Jiangming , Lin, Gengyi

in Algorithms / Artificial neural networks / Cost control / Design factors / Design optimization / Diesel engines / Diesel fuels / Dynamic programming / Efficiency / Electric power distribution / Energy conservation / Energy consumption / Energy distribution / Energy management / Energy management systems / Energy storage / Energy use / Environmental protection / Fuel consumption / Fuzzy logic / Hybrid propulsion / Hybrid propulsion systems / Hybrid systems / Locomotives / Methods / Neural networks / Optimization / Power sources

2023

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An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

by Jiang, Dafa , Wang, Chao , Pei, Haoying , Xu, Chunmei , Huang, Yuanju , Li, Wang , Deng, Jiangming , Lin, Gengyi

2023

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An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

by Jiang, Dafa , Wang, Chao , Pei, Haoying , Xu, Chunmei , Huang, Yuanju , Li, Wang , Deng, Jiangming , Lin, Gengyi

2023

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Journal Article

An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

Jiang, Dafa,

Wang, Chao,

Pei, Haoying,

Xu, Chunmei,

Huang, Yuanju,

Li, Wang,

Deng, Jiangming,

Lin, Gengyi

2023

Overview

Diesel-electric hybrid propulsion system (HPS) is widely applied for shunting locomotive due to the characteristics of flexible configuration, economic and environmental protection in the world. Energy management strategy (EMS) is an important design factor of HPS that can optimize the energy distribution of each power sources, improve system efficiency, and reduce fuel consumption. In this paper, the model of HPS for shunting locomotive and system operating profile are firstly carried out. Then the EMS consist of the conventional rule-based (RB) strategy rule, and a fuzzy neural network base on dynamic programming (FNN-DP) strategy are studied. Finally, the simulations were carried out with these EMSs in the system model at full operating conditions to derive the fuel consumption. The conclusion is that the theoretical optimal solution of DP provides reference and guidance for the fuzzy neural network strategy to improve the rules, and the fuel consumption of the FNN-DP strategy is 10.2% lower than the conventional RB strategy.

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Publisher

MDPI AG

Subject

Algorithms

/ Artificial neural networks

/ Cost control

/ Design factors

/ Design optimization

/ Diesel engines

/ Diesel fuels