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https://doi.org/10.1109/TAES.2019.2958161
Title: | Battery Management System With State-of-Charge and Opportunistic State-of-Health for a Miniaturized Satellite | Authors: | Aung, Htet Soon, Jing Jun Goh, Shu Ting Lew, Jia Min Low, Kay-Soon |
Keywords: | Science & Technology Technology Engineering, Aerospace Engineering, Electrical & Electronic Telecommunications Engineering Batteries State of charge Estimation Satellites Kalman filters Integrated circuit modeling Mathematical model Battery management system (BMS) equivalent circuit model lithium-ion batteries nanosatellite state-of-charge (SOC) state-of-health (SOH) unscented Kalman filter (UKF) EXTENDED KALMAN FILTER LITHIUM-ION BATTERIES POWER-SYSTEM POLYMER BATTERY NANO-SATELLITE DESIGN CUBESAT TECHNOLOGY ESTIMATOR |
Issue Date: | 1-Aug-2020 | Publisher: | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Citation: | Aung, Htet, Soon, Jing Jun, Goh, Shu Ting, Lew, Jia Min, Low, Kay-Soon (2020-08-01). Battery Management System With State-of-Charge and Opportunistic State-of-Health for a Miniaturized Satellite. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 56 (4) : 2978-2989. ScholarBank@NUS Repository. https://doi.org/10.1109/TAES.2019.2958161 | Abstract: | The lifespan of a satellite is primarily dependent on its battery performance. Thus, proper management and monitoring of the battery is important. Most miniaturized satellites of cubeSat and nanosatellite primarily rely on battery voltage readings for monitoring and seldom provide battery health status in a satellite. As the voltage readings can be affected by satellite operating conditions such as temperature and battery lifespan, it can give unreliable readings that might jeopardize satellite operation. The availability of the battery health status can prevent unexpected battery failures and provide useful insights into the planning of satellite operations. In this article, the battery management system of a satellite with state-of-charge (SOC) and state-of-health (SOH) monitoring is presented. For SOC estimation, a scaled unscented Kalman filter (UKF) is proposed. When compared to the existing UKF approach, it requires fewer sigma points and the positive weights used in the scaled unscented transform ensure the positive semidefiniteness of the covariance matrix leading to the improved numerical stability of the filter. Conversely, SOH monitoring is achieved by taking advantage of the opportunity arising from the satellite operations. The battery parameters are extracted without artificially injecting charge and discharge pulses. To validate the performance of the BMS, the experimental prelaunch tests and the actual in-flight data of the VELOX-II satellite is used as an example. From the results, the SOC estimation error is approximately 1% and the SOH estimation is consistent with the manufacturer's datasheet. | Source Title: | IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | URI: | https://scholarbank.nus.edu.sg/handle/10635/231043 | ISSN: | 0018-9251 1557-9603 |
DOI: | 10.1109/TAES.2019.2958161 |
Appears in Collections: | Staff Publications Elements |
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