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

 

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

 

Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung, Taiwan. *Corresponding author. E-mail addresses: pan1012@ms52.hinet.net; htyau@ncut.edu.tw

 

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 Reflex™ 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 Reflex™ 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 Reflex™ 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.

Keywords: CPSO; Reflex™; Charge; SOC.

 

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Acknowledgements

Financial support for this research is provided by the National Science Council of Taiwan, under the Project No. NSC-100-2628-E-167-002 -MY3 is greatly appreciated.

 

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