Edet David Kokoette, Onuh Spencer
This thesis investigates the optimization of battery management systems (BMS) for nano satellites, aiming to enhance energy efficiency and operational longevity. The objective is to develop a robust BMS that can effectively manage and monitor the state of charge, depth of discharge, and overall health of the battery systems used in small satellite applications. Employing a combination of simulation techniques and algorithmic optimization methods, including Genetic Algorithms and Particle Swarm Optimization, the thesis establishes a model that integrates real-time data for improved decision-making in battery management. Results demonstrate significant improvements in battery performance parameters, showcasing a decrease in energy loss and extending battery life through optimized charging and discharging strategies. The research contributes to the field of satellite engineering by providing a scalable framework applicable to various nano satellite missions, thereby supporting future advancements in space technology and sustainability. The findings indicate that effectively optimizing a BMS is crucial for the operational success and longevity of nano satellites in orbit.
@article{637f3959-6e78-42ff-ada2-63d5777be4e8,
title={OPTIMIZATION OF BATTTERY},
author={Edet David Kokoette and Onuh Spencer},
year={2021},
language={English}
}TY - JOUR TI - OPTIMIZATION OF BATTTERY AU - Edet David Kokoette AU - Onuh Spencer PY - 2021 LA - English ER -
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