A New State of Charge Estimation Method for LiFePO4 Battery Packs Used in Robots
Journal
Energies
Journal Volume
6
Journal Issue
4
Pages
2007-2030
Date Issued
2013
Author(s)
Abstract
The accurate state of charge (SOC) estimation of the LiFePO4 battery packs used in robot applications is required for better battery life cycle, performance, reliability, and economic issues. In this paper, a new SOC estimation method, "Modified ECE + EKF", is proposed. The method is the combination of the modified Equivalent Coulombic Efficiency (ECE) method and the Extended Kalman Filter (EKF) method. It is based on the zero-state hysteresis battery model, and adopts the EKF method to correct the initial value used in the Ah counting method. Experimental results show that the proposed technique is superior to the traditional techniques, such as ECE + EKF and ECE + Unscented Kalman Filter (UKF), and the accuracy of estimation is within 1%. © 2013 by the authors; licensee MDPI, Basel, Switzerland.
Other Subjects
Battery management systems; Charging (batteries); Efficiency; Electric batteries; Extended Kalman filters; Kalman filters; Life cycle; Lithium-ion batteries; Robot applications; Battery modeling; Coulombic efficiency; LiFePO4; SOC estimations; State of charge; State-of-charge estimation; Traditional techniques; Unscented Kalman Filter; Secondary batteries
Type
journal article