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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.05255 |
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| _version_ | 1866912750772420608 |
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| author | Bolay, Linda Mendoza-Hernandez, Omar Hosono, Eiji Asakura, Daisuke Shironita, Sayoko Umeda, Minoru Sone, Yoshitsugu Latz, Arnulf Horstmann, Birger |
| author_facet | Bolay, Linda Mendoza-Hernandez, Omar Hosono, Eiji Asakura, Daisuke Shironita, Sayoko Umeda, Minoru Sone, Yoshitsugu Latz, Arnulf Horstmann, Birger |
| contents | Li-ion batteries are essential for the energy supply of satellites. The accurate estimation of their states is important for
the reliable and safe operation in space. This paper introduces a new algorithm for the estimation of SOC and SOH.
The multi-timescale algorithm combines Kalman filters and physics-based models for batteries. We use a P2D model
combined with a degradation model that describes capacity fading due to SEI growth. The state estimation algorithm
combines two extended Kalman filters for the two states evolving on different timescales, with one filter nested within
the other one. We test the algorithm with synthetic data as well as with in-flight data from Japanese satellite REIMEI.
The algorithm adequately estimates the SOC and SOH in both cases. Furthermore it gives insight into the reliability of
the chosen model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_05255 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nested State and Degradation Estimation of a Satellite Battery with In-flight Data Bolay, Linda Mendoza-Hernandez, Omar Hosono, Eiji Asakura, Daisuke Shironita, Sayoko Umeda, Minoru Sone, Yoshitsugu Latz, Arnulf Horstmann, Birger Chemical Physics Li-ion batteries are essential for the energy supply of satellites. The accurate estimation of their states is important for the reliable and safe operation in space. This paper introduces a new algorithm for the estimation of SOC and SOH. The multi-timescale algorithm combines Kalman filters and physics-based models for batteries. We use a P2D model combined with a degradation model that describes capacity fading due to SEI growth. The state estimation algorithm combines two extended Kalman filters for the two states evolving on different timescales, with one filter nested within the other one. We test the algorithm with synthetic data as well as with in-flight data from Japanese satellite REIMEI. The algorithm adequately estimates the SOC and SOH in both cases. Furthermore it gives insight into the reliability of the chosen model. |
| title | Nested State and Degradation Estimation of a Satellite Battery with In-flight Data |
| topic | Chemical Physics |
| url | https://arxiv.org/abs/2512.05255 |