Enhanced OCV prediction mechanism for a stand-alone PV-lithium ion renewable energy system

Thomas Stockley*, Kary Thanapalan, Mark Bowkett, Jonathan Williams

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This paper aims to improve the estimation of state of charge (SoC) of the battery component for a small-scale photovoltaic stand-alone system through the use of a simple summing equation, at a set measurement interval. The system uses a predefined parameter to accurately predict the open-circuit voltage (OCV) of a cell at a much reduced measurement time of 5 minutes, while maintaining a maximum prediction error of less than 1%SoC. A simulation model has been provided that allows measurement of the cell voltage and current for prediction of the equilibrated OCV. The simulation can be used for single cell, modules and battery packs which use lithium-based technologies. Validation of the model has been performed using experimental data from tests conducted at the Centre for Automotive and Power System Engineering (CAPSE) laboratories, at the University of South Wales. An application has been proposed for this work, which includes a photovoltaic module for energy generation to power an illuminated advertizing sign. The energy is stored in a lithium-based battery model which uses a combination of a battery management system and remote monitoring for real-time data acquisition.

Original languageEnglish
Pages (from-to)524-534
Number of pages11
JournalSystems Science and Control Engineering
Issue number1
Publication statusPublished - 1 Jan 2015


  • BMS
  • module simulation
  • prediction mechanism
  • PV-lithium
  • smart monitoring


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