An easy-to-parameterise physics-informed battery model and its application towards lithium-ion battery cell design, diagnosis, and degradation

Abstract

Accurate diagnosis of lithium ion battery state-of-health (SOH) is of significant value for many applications, to improve performance, extend life and increase safety. However, in-situ or in-operando diagnosis of SOH often requires robust models. There are many models available however these often require expensive-to-measure ex-situ parameters and/or contain unmeasurable parameters that were fitted/assumed. In this work, we have developed a new empirically parameterised physics-informed equivalent circuit model. Its modular construction and low-cost parametrisation requirements allow end users to parameterise cells quickly and easily. The model is accurate to 19.6 mV for dynamic loads without any global fitting/optimisation, only that of the individual elements. The consequences of various degradation mechanisms are simulated, and the impact of a degraded cell on pack performance is explored, validated by comparison with experiment. Results show that an aged cell in a parallel pack does not have a noticeable effect on the available capacity of other cells in the pack. The model shows that cells perform better when electrodes are more porous towards the separator and have a uniform particle size distribution, validated by comparison with published data. The model is provided with this publication for readers to use.