Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries
State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered t...
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| Format: | Article |
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MDPI AG
2018-03-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/4/795 |
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| author | Ana-Irina Stroe Jinhao Meng Daniel-Ioan Stroe Maciej Świerczyński Remus Teodorescu Søren Knudsen Kær |
| author_facet | Ana-Irina Stroe Jinhao Meng Daniel-Ioan Stroe Maciej Świerczyński Remus Teodorescu Søren Knudsen Kær |
| author_sort | Ana-Irina Stroe |
| collection | DOAJ |
| description | State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed SOC estimation algorithm was successfully verified for a step discharge profile at five different temperatures and considering various initial SOC initialization values, showing a maximum SOC estimation error of 1.16% and a maximum voltage estimation error of 44 mV. Furthermore, by carrying out a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC. |
| first_indexed | 2024-04-14T06:51:34Z |
| format | Article |
| id | doaj.art-99e2405d56d8403e88da1328786208b1 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T06:51:34Z |
| publishDate | 2018-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-99e2405d56d8403e88da1328786208b12022-12-22T02:07:01ZengMDPI AGEnergies1996-10732018-03-0111479510.3390/en11040795en11040795Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based BatteriesAna-Irina Stroe0Jinhao Meng1Daniel-Ioan Stroe2Maciej Świerczyński3Remus Teodorescu4Søren Knudsen Kær5Department of Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Energy, Aalborg University, 9220 Aalborg, DenmarkDepartment of Energy, Aalborg University, 9220 Aalborg, DenmarkState of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed SOC estimation algorithm was successfully verified for a step discharge profile at five different temperatures and considering various initial SOC initialization values, showing a maximum SOC estimation error of 1.16% and a maximum voltage estimation error of 44 mV. Furthermore, by carrying out a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC.http://www.mdpi.com/1996-1073/11/4/795lithium-ion batterieslithium titanate oxide (LTO) batterieshybrid pulse power characterization testmodel parameterizationequivalent electrical circuitstate of charge (SOC)extended Kalman filter |
| spellingShingle | Ana-Irina Stroe Jinhao Meng Daniel-Ioan Stroe Maciej Świerczyński Remus Teodorescu Søren Knudsen Kær Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries Energies lithium-ion batteries lithium titanate oxide (LTO) batteries hybrid pulse power characterization test model parameterization equivalent electrical circuit state of charge (SOC) extended Kalman filter |
| title | Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries |
| title_full | Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries |
| title_fullStr | Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries |
| title_full_unstemmed | Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries |
| title_short | Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries |
| title_sort | influence of battery parametric uncertainties on the state of charge estimation of lithium titanate oxide based batteries |
| topic | lithium-ion batteries lithium titanate oxide (LTO) batteries hybrid pulse power characterization test model parameterization equivalent electrical circuit state of charge (SOC) extended Kalman filter |
| url | http://www.mdpi.com/1996-1073/11/4/795 |
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