Sensitivity of Lithium-Ion Battery SoC and SoH Estimates to Sensor Measurement Error and Latency
Prepared by Dr. Gregory L. Plett, Battery Control LLC, in association with Dukosi
Abstract
Highly accurate and highly confident estimates of state of charge (SoC) and state of health (SoH) are crucial prerequisites to maximizing the performance and safety achieved from a battery pack. Neither SoC nor SoH are directly measurable, so algorithms of varying complexity and computational cost are employed to provide estimates of the values.
Required inputs to the algorithms are the measurable quantities of the cell, whose performances are defined by precision, accuracy and synchronicity. This white paper provides an evaluation of the impact on the performance of SoC and SoH estimation based on the integrity of these inputs through execution of model-based simulation. It considers typical usage scenarios in electric-vehicle (xEV) and battery energy storage system (BESS) applications, cell chemistry, estimation method and measurement performance. The cell measurements under examination are: cell temperature, cell voltage and cell current. The cell-model derivation and methods used in SoC and SoH estimation are described.
Poster Presentation
In July 2025, at the Oxford Battery Modelling Symposium (OBMS), Dr. Plett presented a poster, co-authored by Gavin McVeigh, Sr. Director of Systems Architecture at Dukosi, outlining the white paper, along with additional research and commentary on the sensitivity of the State of Available Power (SoP).
About the author
Gavin McVeigh
Senior Director ASIC Systems Architecture