Chaos embedded particle swarm optimization algorithm-based solar optimal ReflexTM frequency charge

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Jui-Ho Chen
Her-Terng Yau
Jin-Han Lu

Abstract

The battery temperature rise and charge efficiency during the long-term charge in the sun are a very important topic. The traditional common constant current and constant voltage result in quick temperature rise and influence the charge efficiency indirectly. Therefore, the ReflexTM charge is adopted, the chemical reaction of electrolyte is buffered during discharge, so that the battery temperature rises slightly during charge. However, there is no optimum frequency for switching loss and charge efficiency during ReflexTM charge. Therefore, this paper proposes using chaos embedded particle swarm optimization algorithm (CPOS) to minimize the switching loss of battery in charge and discharge conditions. The battery module in Matlab/Simulink environment is used for solar charge, multiple charge modes are compared with traditional common methods. The simulation results show that the ReflexTM method has improved the battery temperature in Matlab/Simulink, and the State of Charge (SOC) is equivalent to other charge modes. It is proved that the method proposed in this paper has significant effect on switching loss and oscillation, and its charge efficiency is equivalent to traditional quick charge. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.

 

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How to Cite
Chen, J.-H., Yau, H.-T., & Lu, J.-H. (2015). Chaos embedded particle swarm optimization algorithm-based solar optimal ReflexTM frequency charge. Journal of Applied Research and Technology, 13(2). https://doi.org/10.1016/j.jart.2015.06.011