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Optimal Design of Experiment for Parameter Estimation of a Single Particle Model for Lithiumion Batteries

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2018

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Pozzi, Andrea
Gopalakrishnan, Krishnakumar
Raimondo, Davide M.

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2018 IEEE Conference on Decision and Control (CDC). Hoboken, New Jersey, USA: IEEE, 2018, pp. 6482-6487. ISSN 0743-1546. eISSN 2576-2370. ISBN 978-1-5386-1396-2. Available under: doi: 10.1109/CDC.2018.8619340

Zusammenfassung

Advanced battery management systems rely on dynamical models in order to provide safe and profitable battery operations. Such models need to be suitable for control and estimation purposes while, at the same time, as accurate as possible. This feature can be satisfied only if model parameters are accurately estimated. In this work we investigate the design of optimal experiments in order to minimize the uncertainty of the parameters of the Single Particle Model, in the context of Lithium-ion battery. Simulation results show the effectiveness of the proposed methodology when compared with standard current profiles (e.g. constant current).

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510 Mathematik

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IEEE Conference on Decision and Control (CDC), 17. Dez. 2018 - 19. Dez. 2018, Florida, USA
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ISO 690POZZI, Andrea, Gabriele CIARAMELLA, Krishnakumar GOPALAKRISHNAN, Stefan VOLKWEIN, Davide M. RAIMONDO, 2018. Optimal Design of Experiment for Parameter Estimation of a Single Particle Model for Lithiumion Batteries. IEEE Conference on Decision and Control (CDC). Florida, USA, 17. Dez. 2018 - 19. Dez. 2018. In: 2018 IEEE Conference on Decision and Control (CDC). Hoboken, New Jersey, USA: IEEE, 2018, pp. 6482-6487. ISSN 0743-1546. eISSN 2576-2370. ISBN 978-1-5386-1396-2. Available under: doi: 10.1109/CDC.2018.8619340
BibTex
@inproceedings{Pozzi2018-12Optim-45226,
  year={2018},
  doi={10.1109/CDC.2018.8619340},
  title={Optimal Design of Experiment for Parameter Estimation of a Single Particle Model for Lithiumion Batteries},
  isbn={978-1-5386-1396-2},
  issn={0743-1546},
  publisher={IEEE},
  address={Hoboken, New Jersey, USA},
  booktitle={2018 IEEE Conference on Decision and Control (CDC)},
  pages={6482--6487},
  author={Pozzi, Andrea and Ciaramella, Gabriele and Gopalakrishnan, Krishnakumar and Volkwein, Stefan and Raimondo, Davide M.}
}
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