State-of-Charge Estimation Using an EKF-Based Adaptive Observer
| العنوان: | State-of-Charge Estimation Using an EKF-Based Adaptive Observer |
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| المؤلفون: | Sepideh Afshar, Kirsten Morris, Amir Khajepour |
| المصدر: | IEEE Transactions on Control Systems Technology. 27:1907-1923 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Battery (electricity), Computer science, 020209 energy, Lithium iron phosphate, Estimator, 02 engineering and technology, Solid modeling, 021001 nanoscience & nanotechnology, Thermal diffusivity, Energy storage, Extended Kalman filter, chemistry.chemical_compound, State of charge, chemistry, Control and Systems Engineering, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, 0210 nano-technology |
| الوصف: | Lithium-ion batteries are used to store energy in electric vehicles. State of charge (SOC) is an important quantity of the battery cells that need to be estimated using limited measurements. In this paper, SOC estimation via an electrochemical model, a physics-based model, is considered. For lithium iron phosphate cells, a variable solid-state diffusivity model provides significantly more accuracy, but this complicates the model further. A previously obtained, simplified but still a physics-based model is used in this paper. An extended Kalman filter (KF)-based adaptive observer is designed via a low-order approximation of this electrochemical model. The predictions of the estimator are compared with the experimental data in simulations. The simulations are efficient and more accurate than a standard KF. |
| تدمد: | 2374-0159 1063-6536 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::e08901aea282b85e231fe7f9b82b0399 https://doi.org/10.1109/tcst.2018.2842038 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........e08901aea282b85e231fe7f9b82b0399 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23740159 10636536 |
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