Fuzzy Control and Rule-Based Control for Energy Management in Hybrid Vehicles

This paper presents the design and simulation of fuzzy control and rule-based control for energy management in a parallel mild hybrid electric vehicle. The management system must minimize fuel consumption while ensuring load maintenance and ensuring component limitations. Equivalent fuel consumption is used to evaluate control performance, which penalizes the battery's use of electrical energy and fuel consumption but does not reward the storage of electrical energy in the battery. The presented model was tested in two different driving cycles, Europe: NEDC and USA: FTP-75 with an efficiency of 17.6% and 18.3% respectively. However, this result could be improved with more in-depth testing and error estimation, as well as more advanced simulations. In addition, more rules can be added to the proposed model, giving this approach scalable functionality.

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Publication Details

Journal
Universidad Ciencia y Tecnología
Published
2025-06-28
DOI
https://doi.org/10.47460/uct.v29i127.971
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
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article

Fuzzy Control and Rule-Based Control for Energy Management in Hybrid Vehicles

Jose Efren Barbosa Galarza, Obaidullah Yadgar, Jose Efren Barbosa Costales, Pedro Alejandro Vejarano Jara
Universidad Ciencia y Tecnología
Electric and Hybrid Vehicle Technologies
article

Fuzzy Control and Rule-Based Control for Energy Management in Hybrid Vehicles

Jose Efren Barbosa Galarza, Obaidullah Yadgar, Jose Efren Barbosa Costales, Pedro Alejandro Vejarano Jara
article en

Abstract

This paper presents the design and simulation of fuzzy control and rule-based control for energy management in a parallel mild hybrid electric vehicle. The management system must minimize fuel consumption while ensuring load maintenance and ensuring component limitations. Equivalent fuel consumption is used to evaluate control performance, which penalizes the battery's use of electrical energy and fuel consumption but does not reward the storage of electrical energy in the battery. The presented model was tested in two different driving cycles, Europe: NEDC and USA: FTP-75 with an efficiency of 17.6% and 18.3% respectively. However, this result could be improved with more in-depth testing and error estimation, as well as more advanced simulations. In addition, more rules can be added to the proposed model, giving this approach scalable functionality.

Universidad Ciencia y TecnologíaVol. 29(127)
University of Kaiserslautern (DE), Universidad Técnica de Cotopaxi (EC), University of Applied Sciences Kaiserslautern (DE)
Openalex Percentile: Top 85%
Electric and Hybrid Vehicle Technologies
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Fuzzy Control and Rule-Based Control for Energy Management in Hybrid Vehicles — Jose Efren Barbosa Galarza, Obaidullah Yadgar, et al. · Universidad Ciencia y Tecnología (2025) | TGRS Research Map | TGRS