Bayesian calibration for electrochemical thermal model of lithium-ion cells
| Autor: | Duk-Jin Oh, Piyush Tagade, Krishnan S. Hariharan, Seok-Gwang Doo, Subramanya Mayya Kolake, Suman Basu, M. K. S. Verma, Tae-won Song, Taejung Yeo |
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| Rok vydání: | 2016 |
| Předmět: |
Engineering
Calibration (statistics) 020209 energy Energy Engineering and Power Technology chemistry.chemical_element 02 engineering and technology symbols.namesake 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Physical and Theoretical Chemistry Representation (mathematics) Gaussian process Simulation Renewable Energy Sustainability and the Environment business.industry Estimation theory Markov chain Monte Carlo 021001 nanoscience & nanotechnology Random variate chemistry symbols Lithium Transient (oscillation) 0210 nano-technology Biological system business |
| Zdroj: | Journal of Power Sources. 320:296-309 |
| ISSN: | 0378-7753 |
| Popis: | Pseudo-two dimensional electrochemical thermal (P2D-ECT) model contains many parameters that are difficult to evaluate experimentally. Estimation of these model parameters is challenging due to computational cost and the transient model. Due to lack of complete physical understanding, this issue gets aggravated at extreme conditions like low temperature (LT) operations. This paper presents a Bayesian calibration framework for estimation of the P2D-ECT model parameters. The framework uses a matrix variate Gaussian process representation to obtain a computationally tractable formulation for calibration of the transient model. Performance of the framework is investigated for calibration of the P2D-ECT model across a range of temperatures (333 K 263 K) and operating protocols. In the absence of complete physical understanding, the framework also quantifies structural uncertainty in the calibrated model. This information is used by the framework to test validity of the new physical phenomena before incorporation in the model. This capability is demonstrated by introducing temperature dependence on Bruggeman's coefficient and lithium plating formation at LT. With the incorporation of new physics, the calibrated P2D-ECT model accurately predicts the cell voltage with high confidence. The accurate predictions are used to obtain new insights into the low temperature lithium ion cell behavior. |
| Databáze: | OpenAIRE |
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