Skip to main navigation Skip to search Skip to main content

Battery voltage and state of power prediction based on an improved novel polarization voltage model

  • Peng Lin
  • , Peng Jin
  • , Jichao Hong*
  • , Zhenpo Wang*
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • North China University of Technology
  • University of Science and Technology Beijing

Research output: Contribution to journalArticlepeer-review

Abstract

A reliable and accurate battery model is the basis of accurate prediction of battery voltage and state of power (SOP). Based on the electrochemical model of a battery, an improved novel polarization voltage (NPV) model based on current and time is developed in this study. The parameters of the NPV model can be identified with only small-batch primary data, and the accurate prediction of voltage and SOP at t-second (t > 0) under constant current (I ≠ 0) can be easily realized. The simulation results show that when 3C is used to charge the battery directly from state of charge = 0 to the cut-off voltage, the errors of terminal voltage and polarization voltage at the cut-off voltage are only 1.4% and 4.9%, respectively, and the average errors of them in the whole process are only 1.14% and 4%, respectively. The SOP prediction at t-second = 10 s with an overall error of around 5% can be realized by the NPV model. The NPV model is simple in structure and it is easy to identify model parameters. It is also very suitable for voltage simulation and SOP prediction, which can provide reliable support for charge and discharge safety control and energy management.

Original languageEnglish
Pages (from-to)2299-2308
Number of pages10
JournalEnergy Reports
Volume6
DOIs
Publication statusPublished - Nov 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Energy storage system
  • Lithium ion battery
  • Novel polarization voltage model
  • Polarization overpotential
  • State of power
  • Voltage prediction

Fingerprint

Dive into the research topics of 'Battery voltage and state of power prediction based on an improved novel polarization voltage model'. Together they form a unique fingerprint.

Cite this