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DC Field | Value | Language |
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dc.contributor.author | Farrag, M | - |
dc.contributor.author | Lai, CS | - |
dc.contributor.author | Darwish, M | - |
dc.contributor.author | Taylor, G | - |
dc.date.accessioned | 2024-07-26T10:08:27Z | - |
dc.date.available | 2024-07-26T10:08:27Z | - |
dc.date.issued | 2024-06-28 | - |
dc.identifier | ORCiD: Chun Sing Lai https://orcid.org/0000-0002-4169-4438 | - |
dc.identifier | ORCiD: Mohamed Darwish https://orcid.org/0000-0002-9495-861X | - |
dc.identifier | ORCiD: Gareth A. Taylor https://orcid.org/0000-0003-0867-2365 | - |
dc.identifier.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. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29419 | - |
dc.description | Data Availability Statement: The data that support the findings of this study are available from the corresponding authors upon reasonable request. | en_US |
dc.description.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. | en_US |
dc.description.sponsorship | This research is funded by the National Natural Science Foundation of China (62206062) and the EPSRC Doctoral Training Programme. | en_US |
dc.format.extent | 1089 - 1113 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Copyright © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | electric vehicles | en_US |
dc.subject | hybrid energy storage system | en_US |
dc.subject | proportional-integral controller | en_US |
dc.subject | model predictive control and radial basis function | en_US |
dc.title | Improving the Efficiency of Electric Vehicles: Advancements in Hybrid Energy Storage Systems | en_US |
dc.type | Article | en_US |
dc.date.dateAccepted | 2024-06-26 | - |
dc.identifier.doi | https://doi.org/10.3390/vehicles6030052 | - |
dc.relation.isPartOf | Vehicles | - |
pubs.issue | 3 | - |
pubs.publication-status | Published online | - |
pubs.volume | 6 | - |
dc.identifier.eissn | 2624-8921 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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FullText.pdf | Copyright © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | 4.55 MB | Adobe PDF | View/Open |
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