A Novel Multiple Correction Approach for Fast Open Circuit Voltage Prediction of Lithium-Ion Battery

Jinhao Meng, Daniel Ioan Stroe, Mattia Ricco, Guangzhao Luo, Maciej Swierczynski, Remus Teodorescu

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO 4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).

Original languageEnglish
Article number8528545
Pages (from-to)1115-1123
Number of pages9
JournalIEEE Transactions on Energy Conversion
Volume34
Issue number2
DOIs
StatePublished - Jun 2019

Keywords

  • Fast prediction
  • Lithium-ion battery
  • multiple correction approach
  • open circuit voltage

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