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Journal of Biosensors & Renewable sources

Review ArticleOpen Access

A novel improved PNGV model parameter identification of lithium battery based on double exponential fitting Volume 1 - Issue 2

Xiao Yanga, Shunli Wanga*, Wenhua Xua, Carlos Fernandezb, Chunmei Yua, Yongcun Fana, Wen Caoa

  • School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China
  • School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen AB10-7GJ, UK.

Received: September 08,2020   Published: September 30, 2020

Corresponding author: Shun-Li Wang, School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China

DOI: 10.32474/JBRS.2020.01.000110

 

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Abstract

In order to establish a more accurate battery equivalent model, the polarization circuit of the existing PNGV equivalent model is extended to characterize the polarization characteristics of the battery better. The double exponential fitting method is used in the parameter identification to improve the accuracy of parameter identification of battery equivalent model. With the results of hybrid pulse power characterization experiment, the parameters of improved model are identified. And obtain the functional relationship between parameters and state of charge through fitting. At last, a real-time simulation model is established. The simulation results show that the error value between the simulation model voltage and the actual voltage is less than 1.2%, the model accuracy is high. This lays the foundation for the estimation of the state of charge of the lithium battery in the follow-up work.

Keywords: Lithium Battery; Parameter Identification; improved PNGV model; double exponential fitting

Abstract| Introduction| Mathematical analysis| Experimental analysis| Conclusion| Acknowledgments| References|

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