A Cell Screening Algorithm Integrating Genetic and Numerical Differentiation

© 2024 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )

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Abstract

The consistency of the cell has a significant impact on battery capacity, endurance, overall performance, safety, and service life extension. However, it is challenging to identify cells with high consistency and no loss of battery energy. This paper presents a cell screening algorithm that integrates genetic and numerical differentiation techniques. Initially, a mathematical model for battery consistency is established, and a multi-step charging strategy is proposed to satisfy the demands of fast charging technology. Subsequently, the genetic algorithm simulates biological evolution to efficiently search for superior cell combinations within a short time while evaluating capacity, voltage consistency, and charge/discharge efficiency. Finally, through experimental validation and comparative analysis with similar algorithms, our proposed method demonstrates notable advantages in terms of both search efficiency and performance.

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