February 2020 - 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 ∼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.