On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles
<p dir="ltr">The State-of-Charge (SoC) of Lithium-Ion Batteries (LIBs) is a crucial parameter for Battery Management Systems (BMSs) used in Electric Vehicles (EVs). This paper presents a comprehensive study on the SoC estimation of LIBs using advanced model-based methods. The practic...
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| مؤلفون آخرون: | , |
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2025
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| _version_ | 1864513534585470976 |
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| author | Fatma Ahmed (11084787) |
| author2 | Khalid Abualsaud (16888701) Ahmed M. Massoud (16896417) |
| author2_role | author author |
| author_facet | Fatma Ahmed (11084787) Khalid Abualsaud (16888701) Ahmed M. Massoud (16896417) |
| author_role | author |
| dc.creator.none.fl_str_mv | Fatma Ahmed (11084787) Khalid Abualsaud (16888701) Ahmed M. Massoud (16896417) |
| dc.date.none.fl_str_mv | 2025-04-14T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2025.3560065 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/On_Equivalent_Circuit_Model-Based_State-of-Charge_Estimation_for_Lithium-Ion_Batteries_in_Electric_Vehicles/30405577 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Automotive engineering Electrical engineering Electronics, sensors and digital hardware Equivalent circuit model (ECM) state-of-charge (SoC) extended Kalman filter (EKF) unscented Kalman filter (UKF) electric vehicles (EVs) Estimation Kalman filters Accuracy Integrated circuit modeling Noise Adaptation models Robustness Real-time systems Parameter estimation |
| dc.title.none.fl_str_mv | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The State-of-Charge (SoC) of Lithium-Ion Batteries (LIBs) is a crucial parameter for Battery Management Systems (BMSs) used in Electric Vehicles (EVs). This paper presents a comprehensive study on the SoC estimation of LIBs using advanced model-based methods. The practical implications of this research are significant, as they provide a reliable and efficient approach to SoC estimation, enhancing the performance and lifespan of LIBs in real-world applications, particularly EVs. A third-order equivalent circuit model is employed for the LIB based on electrochemical impedance spectra test results, with model parameters identified using a particle swarm optimization algorithm. Two real-time model-based estimation algorithms, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), are compared for SoC estimation. A hybrid approach based on UKF and EKF is presented. The results demonstrate that the UKF outperforms the EKF in SoC estimation, with the root mean squared error (RMSE) and maximum error for SoC estimation being 1.06% and 1.15%, respectively. The hybrid EKF-UKF approach provides the best performance for SoC estimation, achieving the lowest root mean squared error (RMSE) of 0.2% and a maximum error of 0.5% for SoC estimation. This approach leverages the strengths of EKF and UKF, offering superior accuracy and robustness in real-time battery monitoring in EV applications.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3560065" target="_blank">https://dx.doi.org/10.1109/access.2025.3560065</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_2828204df34e27a5cab672f858149bee |
| identifier_str_mv | 10.1109/access.2025.3560065 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30405577 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric VehiclesFatma Ahmed (11084787)Khalid Abualsaud (16888701)Ahmed M. Massoud (16896417)EngineeringAutomotive engineeringElectrical engineeringElectronics, sensors and digital hardwareEquivalent circuit model (ECM)state-of-charge (SoC)extended Kalman filter (EKF)unscented Kalman filter (UKF)electric vehicles (EVs)EstimationKalman filtersAccuracyIntegrated circuit modelingNoiseAdaptation modelsRobustnessReal-time systemsParameter estimation<p dir="ltr">The State-of-Charge (SoC) of Lithium-Ion Batteries (LIBs) is a crucial parameter for Battery Management Systems (BMSs) used in Electric Vehicles (EVs). This paper presents a comprehensive study on the SoC estimation of LIBs using advanced model-based methods. The practical implications of this research are significant, as they provide a reliable and efficient approach to SoC estimation, enhancing the performance and lifespan of LIBs in real-world applications, particularly EVs. A third-order equivalent circuit model is employed for the LIB based on electrochemical impedance spectra test results, with model parameters identified using a particle swarm optimization algorithm. Two real-time model-based estimation algorithms, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), are compared for SoC estimation. A hybrid approach based on UKF and EKF is presented. The results demonstrate that the UKF outperforms the EKF in SoC estimation, with the root mean squared error (RMSE) and maximum error for SoC estimation being 1.06% and 1.15%, respectively. The hybrid EKF-UKF approach provides the best performance for SoC estimation, achieving the lowest root mean squared error (RMSE) of 0.2% and a maximum error of 0.5% for SoC estimation. This approach leverages the strengths of EKF and UKF, offering superior accuracy and robustness in real-time battery monitoring in EV applications.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3560065" target="_blank">https://dx.doi.org/10.1109/access.2025.3560065</a></p>2025-04-14T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2025.3560065https://figshare.com/articles/journal_contribution/On_Equivalent_Circuit_Model-Based_State-of-Charge_Estimation_for_Lithium-Ion_Batteries_in_Electric_Vehicles/30405577CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/304055772025-04-14T09:00:00Z |
| spellingShingle | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles Fatma Ahmed (11084787) Engineering Automotive engineering Electrical engineering Electronics, sensors and digital hardware Equivalent circuit model (ECM) state-of-charge (SoC) extended Kalman filter (EKF) unscented Kalman filter (UKF) electric vehicles (EVs) Estimation Kalman filters Accuracy Integrated circuit modeling Noise Adaptation models Robustness Real-time systems Parameter estimation |
| status_str | publishedVersion |
| title | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| title_full | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| title_fullStr | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| title_full_unstemmed | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| title_short | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| title_sort | On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles |
| topic | Engineering Automotive engineering Electrical engineering Electronics, sensors and digital hardware Equivalent circuit model (ECM) state-of-charge (SoC) extended Kalman filter (EKF) unscented Kalman filter (UKF) electric vehicles (EVs) Estimation Kalman filters Accuracy Integrated circuit modeling Noise Adaptation models Robustness Real-time systems Parameter estimation |