Online Battery Monitoring for State-of-Charge and Power Capability Prediction

Abstract

This document presents an investigation of a proposed methodology that uses system identification techniques to implement a monitoring system for lead-acid batteries in an electric vehicle. Specifically, the information that the proposed methodology provides can help estimate the energy remained in the battery bank (Stateof- Charge (SOC)) and the power capability of the battery bank (State-of-Function (SOF)). A combination of analytical and experimental techniques has been devised to construct an equivalent circuit model that includes a diffusion voltage term for the OPTIMA D34M battery used in the WEMPEC Corbin Sparrow vehicle. In addition, the document analyzes a set of actual road trip data from the WEMPEC Corbin Sparrow to demonstrate the proposed model?s potential use for diagnosing the relative state-of-health (SOH) of individual batteries. Detailed discussions of the limitations and assumptions associated with the model, as well as other possible alternatives, are included in the document. The performance capabilities of the proposed method for estimating battery SOC and SOF are evaluated against experimental data with an emphasis on electric vehicle (EV) operations.