Energy Management System Comparison Among Fuzzy Strategies

This study evaluates and compares energy management systems (EMS) for hybrid vehicles using fuzzy logic strategies to optimize energy distribution between fuel cells (FC) and batteries. Key components, including the Proton Exchange Membrane Fuel Cell (PEMFC) and the Permanent Magnet Synchronous Moto...

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Main Authors: Julio C. Pena-Aguirre, Francisco J. Perez-Pinal, Yosafat J. Samano-Flores, Alejandro I. Barranco-Gutierrez, Gilberto Gonzalez Gomez, Tomas Serrano-Ramirez
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/11072445/
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author Julio C. Pena-Aguirre
Francisco J. Perez-Pinal
Yosafat J. Samano-Flores
Alejandro I. Barranco-Gutierrez
Gilberto Gonzalez Gomez
Tomas Serrano-Ramirez
author_facet Julio C. Pena-Aguirre
Francisco J. Perez-Pinal
Yosafat J. Samano-Flores
Alejandro I. Barranco-Gutierrez
Gilberto Gonzalez Gomez
Tomas Serrano-Ramirez
author_sort Julio C. Pena-Aguirre
collection DOAJ
description This study evaluates and compares energy management systems (EMS) for hybrid vehicles using fuzzy logic strategies to optimize energy distribution between fuel cells (FC) and batteries. Key components, including the Proton Exchange Membrane Fuel Cell (PEMFC) and the Permanent Magnet Synchronous Motor (PMSM), were modeled and validated using MATLAB-Simulink, LabVIEW, and Hardware-in-the-Loop (HIL) testing. The proposed EMS achieves the highest efficiency, up to a fuel cell average power output of 8.5 kW, an efficiency of 74.35%, and a state of charge (SoC) improvement of 34.25%. Other strategies, including those of (Esoufi et al., 2020, Hemi et al., 2014, and Zhao et al. 2021), exhibited average power outputs ranging from 7.28 to 7.79 kW and SoC improvements of 22.96% to 28.35%. These results emphasize the advantages of the proposed strategy fuzzy logic-based EMS in balancing energy demands, reducing battery stress, and extending battery life under urban driving conditions. The findings highlight fuzzy logic as a superior approach to traditional methods for managing hybrid vehicle powertrains, particularly in scenarios with frequent acceleration and deceleration.
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spelling doaj-art-2e97c778d1a24b3d8d338a47b47638632025-08-20T03:32:55ZengIEEEIEEE Access2169-35362025-01-011312904012905510.1109/ACCESS.2025.358675411072445Energy Management System Comparison Among Fuzzy StrategiesJulio C. Pena-Aguirre0https://orcid.org/0000-0002-6211-7760Francisco J. Perez-Pinal1https://orcid.org/0000-0002-6116-6464Yosafat J. Samano-Flores2Alejandro I. Barranco-Gutierrez3https://orcid.org/0000-0002-5050-6208Gilberto Gonzalez Gomez4https://orcid.org/0000-0001-8550-888XTomas Serrano-Ramirez5https://orcid.org/0000-0001-6118-3830Ingeniería automotriz, Universidad Politécnica de Guanajuato, Cortazar, MexicoInstituto Tecnológico de Celaya, Tecnológico Nacional de México, Celaya, MexicoIngeniería automotriz, Universidad Politécnica de Guanajuato, Cortazar, MexicoInstituto Tecnológico de Celaya, Tecnológico Nacional de México, Celaya, MexicoInstituto Tecnológico de Celaya, Tecnológico Nacional de México, Celaya, MexicoIngeniería automotriz, Universidad Politécnica de Guanajuato, Cortazar, MexicoThis study evaluates and compares energy management systems (EMS) for hybrid vehicles using fuzzy logic strategies to optimize energy distribution between fuel cells (FC) and batteries. Key components, including the Proton Exchange Membrane Fuel Cell (PEMFC) and the Permanent Magnet Synchronous Motor (PMSM), were modeled and validated using MATLAB-Simulink, LabVIEW, and Hardware-in-the-Loop (HIL) testing. The proposed EMS achieves the highest efficiency, up to a fuel cell average power output of 8.5 kW, an efficiency of 74.35%, and a state of charge (SoC) improvement of 34.25%. Other strategies, including those of (Esoufi et al., 2020, Hemi et al., 2014, and Zhao et al. 2021), exhibited average power outputs ranging from 7.28 to 7.79 kW and SoC improvements of 22.96% to 28.35%. These results emphasize the advantages of the proposed strategy fuzzy logic-based EMS in balancing energy demands, reducing battery stress, and extending battery life under urban driving conditions. The findings highlight fuzzy logic as a superior approach to traditional methods for managing hybrid vehicle powertrains, particularly in scenarios with frequent acceleration and deceleration.https://ieeexplore.ieee.org/document/11072445/Driving cycleenergy management systemfuzzy logicfuzzy strategiesvehicle hybrid
spellingShingle Julio C. Pena-Aguirre
Francisco J. Perez-Pinal
Yosafat J. Samano-Flores
Alejandro I. Barranco-Gutierrez
Gilberto Gonzalez Gomez
Tomas Serrano-Ramirez
Energy Management System Comparison Among Fuzzy Strategies
IEEE Access
Driving cycle
energy management system
fuzzy logic
fuzzy strategies
vehicle hybrid
title Energy Management System Comparison Among Fuzzy Strategies
title_full Energy Management System Comparison Among Fuzzy Strategies
title_fullStr Energy Management System Comparison Among Fuzzy Strategies
title_full_unstemmed Energy Management System Comparison Among Fuzzy Strategies
title_short Energy Management System Comparison Among Fuzzy Strategies
title_sort energy management system comparison among fuzzy strategies
topic Driving cycle
energy management system
fuzzy logic
fuzzy strategies
vehicle hybrid
url https://ieeexplore.ieee.org/document/11072445/
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AT yosafatjsamanoflores energymanagementsystemcomparisonamongfuzzystrategies
AT alejandroibarrancogutierrez energymanagementsystemcomparisonamongfuzzystrategies
AT gilbertogonzalezgomez energymanagementsystemcomparisonamongfuzzystrategies
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