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Application of PID optimization control strategy based on particle swarm optimization (PSO) for battery charging system

Author

Listed:
  • Tiezhou Wu
  • Cuicui Zhou
  • Zhe Yan
  • Huigang Peng
  • Linzhang Wu

Abstract

The battery charging process has nonlinear and hysteresis properties. PID (Proportion Integration Differentiation) control is a conventional control method used in the battery charging process. The control effect is determined by the PID control parameters ${K}_p$, ${K}_i$ and ${K}_d$. The traditional PID parameter setting method is difficult to give the appropriate parameters, which affects the battery charging efficiency. In this paper, the particle swarm optimization (PSO) is used to optimize the PID parameters. Aiming at the defects of basic PSO, such as slow convergence speed, low convergence precision and easy to be premature, a modified particle swarm optimization algorithm is proposed, and the optimized PID parameters are applied to the battery charging control system. Also, the experimental results show that the battery charging process possesses better dynamic performance and the charging efficiency of the battery has increased from 86.44% to 91.47%, and the charging temperature rise has dropped by 1°C.

Suggested Citation

  • Tiezhou Wu & Cuicui Zhou & Zhe Yan & Huigang Peng & Linzhang Wu, 0. "Application of PID optimization control strategy based on particle swarm optimization (PSO) for battery charging system," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 15(4), pages 528-535.
    • Handle: RePEc:oup:ijlctc:v:15:y::i:4:p:528-535.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctaa020
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