Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model
Parameter identification with the pseudo-two-dimensional (p2D) model has been an important research topic in battery engineering because some of the physicochemical parameters used in the model can be measured, while some can only be estimated or calculated based on the measurement data. Various met...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Batteries |
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| Online Access: | https://www.mdpi.com/2313-0105/8/11/222 |
| _version_ | 1827647241066643456 |
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| author | Yulong Zhao Andreas Jossen |
| author_facet | Yulong Zhao Andreas Jossen |
| author_sort | Yulong Zhao |
| collection | DOAJ |
| description | Parameter identification with the pseudo-two-dimensional (p2D) model has been an important research topic in battery engineering because some of the physicochemical parameters used in the model can be measured, while some can only be estimated or calculated based on the measurement data. Various methods, either in the time domain or frequency domain, have been proposed to identify the parameters of the p2D model. While the methods in each domain bring their advantages and disadvantages, a comprehensive comparison regarding parameter identifiability and accuracy is still missing. In this present work, some selected physicochemical parameters of the p2D model are identified in four different cases and with different methods, either only in the time domain or with a combined model. Which parameters are identified in the frequency domain is decided by a comprehensive analysis of the analytical expression for the DRT spectrum. Finally, the parameter identifiability results are analyzed and the validation results with two highly dynamic load profiles are shown and compared. The results indicate that the model with ohmic resistance and the combined method achieves the best performance and the average voltage error is at the level of 12 mV. |
| first_indexed | 2024-03-09T19:16:25Z |
| format | Article |
| id | doaj.art-ab85bfb46e594154977618beb8866025 |
| institution | Directory Open Access Journal |
| issn | 2313-0105 |
| language | English |
| last_indexed | 2024-03-09T19:16:25Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Batteries |
| spelling | doaj.art-ab85bfb46e594154977618beb88660252023-11-24T03:45:05ZengMDPI AGBatteries2313-01052022-11-0181122210.3390/batteries8110222Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery ModelYulong Zhao0Andreas Jossen1Chair of Electrical Energy Storage Technology, TUM School of Engineering and Design, Technical University of Munich, Karlstraße 45, 80333 Munich, GermanyChair of Electrical Energy Storage Technology, TUM School of Engineering and Design, Technical University of Munich, Karlstraße 45, 80333 Munich, GermanyParameter identification with the pseudo-two-dimensional (p2D) model has been an important research topic in battery engineering because some of the physicochemical parameters used in the model can be measured, while some can only be estimated or calculated based on the measurement data. Various methods, either in the time domain or frequency domain, have been proposed to identify the parameters of the p2D model. While the methods in each domain bring their advantages and disadvantages, a comprehensive comparison regarding parameter identifiability and accuracy is still missing. In this present work, some selected physicochemical parameters of the p2D model are identified in four different cases and with different methods, either only in the time domain or with a combined model. Which parameters are identified in the frequency domain is decided by a comprehensive analysis of the analytical expression for the DRT spectrum. Finally, the parameter identifiability results are analyzed and the validation results with two highly dynamic load profiles are shown and compared. The results indicate that the model with ohmic resistance and the combined method achieves the best performance and the average voltage error is at the level of 12 mV.https://www.mdpi.com/2313-0105/8/11/222electrochemical impedance spectroscopyphysics-based modeldistribution of relaxation timesMarkov chain Monte Carlo algorithm |
| spellingShingle | Yulong Zhao Andreas Jossen Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model Batteries electrochemical impedance spectroscopy physics-based model distribution of relaxation times Markov chain Monte Carlo algorithm |
| title | Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model |
| title_full | Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model |
| title_fullStr | Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model |
| title_full_unstemmed | Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model |
| title_short | Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model |
| title_sort | comparative study of parameter identification with frequency and time domain fitting using a physics based battery model |
| topic | electrochemical impedance spectroscopy physics-based model distribution of relaxation times Markov chain Monte Carlo algorithm |
| url | https://www.mdpi.com/2313-0105/8/11/222 |
| work_keys_str_mv | AT yulongzhao comparativestudyofparameteridentificationwithfrequencyandtimedomainfittingusingaphysicsbasedbatterymodel AT andreasjossen comparativestudyofparameteridentificationwithfrequencyandtimedomainfittingusingaphysicsbasedbatterymodel |