Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29419
Title: Improving the Efficiency of Electric Vehicles: Advancements in Hybrid Energy Storage Systems
Authors: Farrag, M
Lai, CS
Darwish, M
Taylor, G
Keywords: electric vehicles;hybrid energy storage system;proportional-integral controller;model predictive control and radial basis function
Issue Date: 28-Jun-2024
Publisher: MDPI
Citation: Farrag, M.R. et al. (2024) 'Improving the Efficiency of Electric Vehicles: Advancements in Hybrid Energy Storage Systems', Vehicles, 6 (3), pp. 1089 - 1113. doi: 10.3390/vehicles6030052.
Abstract: Electric vehicles (EVs) encounter substantial obstacles in effectively managing energy, particularly when faced with varied driving circumstances and surrounding factors. This study aims to evaluate the performance of three different control systems in a fully operational hybrid energy storage system (HESS) installed in the Nissan Leaf. The objective is to improve the performance of EVs by focusing on optimising energy management in response to different global environmental and driving circumstances. This study utilises an analytical strategy by developing a distinct energy management system model using MATLAB/Simulink. This model is specifically designed for optimising the integration and control of batteries and supercapacitors (SCs) in a fully active HESS. This model mimics the performance of the controllers under three different driving cycles—Artemis rural, Artemis motorway, and US06. The findings demonstrate notable progress in managing the battery state of charge (SOC) and the system’s responsiveness, especially when employing the radial basis function (RBF) controller. This study emphasises the capacity of HESSs to enhance the effectiveness and durability of EVs, therefore promoting wider acceptance and progress in electric transportation technology.
Description: Data Availability Statement: The data that support the findings of this study are available from the corresponding authors upon reasonable request.
URI: https://bura.brunel.ac.uk/handle/2438/29419
DOI: https://doi.org/10.3390/vehicles6030052
Other Identifiers: ORCiD: Chun Sing Lai https://orcid.org/0000-0002-4169-4438
ORCiD: Mohamed Darwish https://orcid.org/0000-0002-9495-861X
ORCiD: Gareth A. Taylor https://orcid.org/0000-0003-0867-2365
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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