Performance Analysis of Coulomb Counting Approach for State of Charge Estimation
Authors:
- 1 October 2019
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
Abstract
In this paper, we consider the problem of the state of charge estimation for rechargeable batteries. Coulomb counting is one of the traditional approaches to SOC estimation and it is considered one of the reliable approaches to SOC estimation as long as the battery capacity and initial SOC is known. However, the Coulomb counting method is susceptible to errors and the extent of these errors are not studied in the literature. In this paper, we formally derive and quantify the SOC estimation error due to the following four types of error sources: (i) current measurement error; (ii) error due to the approximation of current integration with respect to time; (iii) uncertainty in the knowledge of battery capacity; and the (iv) error (drift) in timing oscillator. We analyze the individual effect of these four types of errors on the estimated SOC. Further, We show numerical simulations to illustrate the effect of these errors on the estimated SOC.Keywords
This publication has 12 references indexed in Scilit:
- Performance analysis results of a battery fuel gauge algorithm at multiple temperaturesJournal of Power Sources, 2015
- A robust approach to battery fuel gauging, part II: Real time capacity estimationJournal of Power Sources, 2014
- Open circuit voltage characterization of lithium-ion batteriesJournal of Power Sources, 2014
- A review on lithium-ion battery ageing mechanisms and estimations for automotive applicationsJournal of Power Sources, 2013
- On-line estimation of lithium-ion battery impedance parameters using a novel varied-parameters approachJournal of Power Sources, 2013
- State of Charge Estimation Using the Extended Kalman Filter for Battery Management Systems Based on the ARX Battery ModelEnergies, 2013
- Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteriesApplied Energy, 2009
- Combined state of charge estimator for electric vehicle battery packControl Engineering Practice, 2007
- Extended Kalman filtering for battery management systems of LiPB-based HEV battery packsJournal of Power Sources, 2004
- Simulation of capacity fade in lithium-ion batteriesJournal of Power Sources, 2003