State of Available Power: Sensitivity of Lithium-Ion Battery SoP Estimates

Prepared by Dr. Gregory L. Plett, University of Colorado,
and Dr. Gavin McVeigh, Senior Director of Systems Architecture, Dukosi.

Abstract

Accurate estimates of cell State of Power (SoP) are critical to maximize battery pack performance and safety. Since SoP is not directly measurable, algorithms having varying complexity are implemented to compute SoP estimates. Input to these algorithms are the cell’s measurable quantities, acquired with sensors whose characteristics are defined by precision, accuracy, and synchronicity. This paper provides an evaluation of the performance of SoP estimation algorithms versus the integrity of the measurements provided by the cell voltage, current, and temperature sensors. Overviews of state-of-charge and cell-resistance estimation, required by SoP, are also shown. We employ model-based simulation to compare the ideal case having zero sensor measurement error against real-life sensor performances which exhibit measurement offset, noise and non-synchronicity. We consider typical usage scenarios in electric vehicle and BESS applications, cell chemistry, estimation method, and sensor performance.