Modular battery management software for satellite applications: Kalman filter-based state of charge estimation and SoC-driven balancing on an 8-bit microcontroller

This work presents a modular battery management system (BMS) for space applications. Based on commercial off-the-shelf (COTS) components, the system provides state of charge (SoC) data for battery power budgeting and lifetime management. While intelligent BMS are common on Earth, space applications are constrained by severe computational limits. Therefore, the novelty of this work lies in embedding a linear Kalman filter (KF) for SoC estimation and an SoC-driven cell balancing algorithm entirely on a standard space-grade 8-bit microcontroller. This reliable on-board solution prevents faults and reduces the reliance on high-bandwidth Earth telemetry. The KF-based SoC estimation and balancing approach is validated in an electrical test campaign. The battery system is charged and discharged in more than 100 cycles representative of a space mission profile to evaluate the software. During the measurements, the SoC is determined by the algorithm implemented on the microcontroller and compared to a reference. A root-mean-square error (RMSE) of less than 1 % is obtained for the on-board SoC estimation across long-term tests with varying depths of discharge (DOD). Furthermore, the method proves its drift stability and correction capabilities in a long-term test with faulty sensor data. Balancing is achieved during all test cycles.

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Publication Details

Journal
Journal of Power Sources
Published
2026-06-29
DOI
https://doi.org/10.1016/j.jpowsour.2026.240836
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Modular battery management software for satellite applications: Kalman filter-based state of charge estimation and SoC-driven balancing on an 8-bit microcontroller

Jakob Technau, Daniel Gómez Toro, Cornelie Bänsch, Marius Eilenberger et al.
Journal of Power Sources
Advanced Battery Technologies Research
article

Modular battery management software for satellite applications: Kalman filter-based state of charge estimation and SoC-driven balancing on an 8-bit microcontroller

Jakob Technau, Daniel Gómez Toro, Cornelie Bänsch, Marius Eilenberger, Johannes Spleiß, Luc Rajer
article en

Abstract

This work presents a modular battery management system (BMS) for space applications. Based on commercial off-the-shelf (COTS) components, the system provides state of charge (SoC) data for battery power budgeting and lifetime management. While intelligent BMS are common on Earth, space applications are constrained by severe computational limits. Therefore, the novelty of this work lies in embedding a linear Kalman filter (KF) for SoC estimation and an SoC-driven cell balancing algorithm entirely on a standard space-grade 8-bit microcontroller. This reliable on-board solution prevents faults and reduces the reliance on high-bandwidth Earth telemetry. The KF-based SoC estimation and balancing approach is validated in an electrical test campaign. The battery system is charged and discharged in more than 100 cycles representative of a space mission profile to evaluate the software. During the measurements, the SoC is determined by the algorithm implemented on the microcontroller and compared to a reference. A root-mean-square error (RMSE) of less than 1 % is obtained for the on-board SoC estimation across long-term tests with varying depths of discharge (DOD). Furthermore, the method proves its drift stability and correction capabilities in a long-term test with faulty sensor data. Balancing is achieved during all test cycles.

Journal of Power SourcesVol. 690
University of Stuttgart (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Deutsches Zentrum für Luft- und Raumfahrt
Openalex Percentile: Top 11%
Advanced Battery Technologies Research
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