PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

 

e-ISSN 2231-8526
ISSN 0128-7680

Home / Regular Issue / JST Vol. 32 (2) Mar. 2024 / JST-4469-2023

 

Integrating Fuzzy Logic and Brute Force Algorithm in Optimizing Energy Management Systems for Battery Electric Vehicles

Abdulhadi Abdulsalam Abulifa, Azura Che Soh, Mohd Khair Hassan, Raja Kamil and Mohd Amran Mohd Radzi

Pertanika Journal of Science & Technology, Volume 32, Issue 2, March 2024

DOI: https://doi.org/10.47836/pjst.32.2.17

Keywords: Battery electric vehicle, brute-force algorithm, energy management system, fuzzy logic, satisfaction ratio, state of charge

Published on: 26 March 2024

The limited driving range of BEVs is the main challenge in developing zero-emission Battery Electric Vehicles (BEVs) to replace traditional fuel-based vehicles. This limitation necessitates an increase in battery energy while balancing the power supply and consumption requirements for the vehicle’s motor and auxiliaries, such as the Heating, Ventilation, and Air Conditioning (HVAC) system. This research proposes a solution to achieve more efficient control of HVAC consumption by integrating fuzzy logic techniques with brute-force algorithms to optimize the Energy Management System (EMS) in BEVs. The model was based on actual parameters, implemented using MATLAB-Simulink and ADVISOR software, and configured using a backward-facing design incorporating the technical specifications of a Malaysian electric car, the PROTON IRIZ. An optimal solution was proposed based on the Satisfaction Ratio (SR) and State of Charge (SoC) metrics to achieve the best system optimization. The results demonstrate that the optimized fuzzy EMS improved power consumption by 23.2% to 26.6% compared to a basic fuzzy EMS. The proposed solution significantly improves the driving range of BEVs.

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