Advanced diagnostics to evaluate heterogeneity in lithium-ion battery modules

Battery packs for electric and stationary applications experience varied operating conditions, including abuse-e.g., fast charging, overcharging, thermal, vibration, shock, etc.-throughout their lifetimes. Innovative diagnostic tools and algorithms that go beyond single cells and deal with modules and packs are essential for early detection of off-normal issues. High-resolution tools with known detection limits are key to developing appropriate mitigation strategies. With the advent of rapid impedance spectroscopy that can generate a broadband impedance spectrum in similar to 10 s, the case for impedance-based diagnostics that can be readily aligned with other methods, such as incremental capacity or dQ.dV(-1), has become promising. This study used the aforementioned diagnostic methods to identify realistic in-vehicle battery abnormalities (e.g., localized self-discharge and non-uniform aging), in series (up to 10S) and parallel (4P) strings, using 16 Ah graphite/NMC cells. The impedance-based diagnostic is found to be sensitive to the string size and state. Depending on the type of abnormality, detection frequency varied. The dQ.dV(-1) method showed the potential to detect long-term aging-related heterogeneity in modules. In general, both the impedance and dQ.dV(-1) methods were able to detect series strings' abnormalities, but struggled to find those issues within parallel modules. (C) 2020 Elsevier B.V. All rights reserved.