Synthesize battery degradation modes via a diagnostic and prognostic model

Abstract Batteries are being used in increasingly complicated configurations with very demanding duty schedules. Such usage makes the use of batteries in multi-cell configurations to meet voltage, power, and energy demands in a very stressful manner. Thus, effective management and control of a battery system to allow efficient, reliable, and safe operation becomes vital, and diagnostic and prognostic tools are essential. Yet, developing these tools in practical applications is new to the industry, difficult and challenging. Here we present a novel mechanistic model that can enable battery diagnosis and prognosis. The model can simulate various “what-if” scenarios of battery degradation modes via a synthetic approach based on specific electrode behavior with proper adjustment of the loading ratio and the extent of degradation in and between the two electrodes. This approach is very different from the conventional empirical ones that correlate the cell parameters (such as impedance increases) with degradation in capacity or power fade to predict performance and life. This approach, with mechanistic understanding of battery degradation processes and failure mechanisms, offers unique high-fidelity simulation to address path dependence of the battery degradation.