Abstract
Identification of lithium-ion (Li-ion) battery models is essential for enhancing the operation of electrical vehicles. This paper develops a novel approach for estimating the equivalent circuit model (ECM) of Li-ion batteries and reconstructing the open-circuit voltage (OCV) and state of charge (SOC) relationship. We formulate the OCV-SOC relation as a piecewise affine (PWA) function and estimate its coefficients and the Markov parameters (impulse response) of the ECM via l1-regularized least squares. The state space model of the ECM is derived through the Ho-Kalman algorithm. Experiments with simulated and real-life battery data demonstrate the method's effectiveness and advantages with respect to the state of the art.
| Original language | English |
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| Title of host publication | Proceedings of the European Control Conference, ECC 2024 |
| Publisher | IEEE |
| Pages | 3551-3556 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-3-9071-4410-7 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 European Control Conference, ECC 2024 - Stockholm, Sweden Duration: 25 Jun 2024 → 28 Jun 2024 |
Conference
| Conference | 2024 European Control Conference, ECC 2024 |
|---|---|
| Country/Territory | Sweden |
| City | Stockholm |
| Period | 25/06/24 → 28/06/24 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.