An EV-Scale Demonstration of In-Situ Battery Electrochemical Impedance Spectroscopy and BMS-Limited Pack Performance Analysis

Abstract

State-of-Power (SOP) and State-of-Charge (SOC) estimation inaccuracy manifests throughout the EV battery lifetime due to the non-linear degradation trajectory that is unique to each use-case. The inaccuracy leads to premature termination of charge and discharge operations, which results in the virtual loss of battery performance. In-situ Electrochemical Impedance Spectroscopy (EIS) has been proposed to provide real-time battery impedance measurements, which can theoretically improve the SOP/SOC estimation accuracy. In this work, an EV-scale in-situ EIS system is demonstrated experimentally, from impedance measurement to Equivalent Circuit Model (ECM) extraction. The pack-level discharge energy versus SOP/SOC estimation errors is also simulated, which quantifies the virtual loss of battery performance. The measured-impedance error tolerance of three common ECM extraction techniques is then examined through a randomised set of simulated EIS tests with injected measurement noise. Finally, in-situ impedance measurement is performed on 20 battery sub-modules using an electric pickup truck EIS system. The ECM-predicted voltage output is compared against measured driving data. Experimental results indicate approximately 8-9% improvement in SOP estimation accuracy at 3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C and 10 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C between the in-situ extracted models and a representative baseline.