By cell-to-cell parameter comparison, short circuits are identified using the outlier current mismatch estimates and thus accurately estimating the leakage current and short circuit resistance. Real-time implementation of the coupled SoC–SoH estimation approach is presented using gradient parameter update law.
Abusive lithium-ion battery operations can induce micro-short circuits, which can develop into severe short circuits and eventually thermal runaway events, a significant safety concern in lithium-ion battery packs. This paper aims to detect and quantify micro-short circuits before they become a safety issue.
Micro short detection framework in lithium-ion battery pack is presented. Offline least square-based and real-time gradient-based SoH estimators are proposed. SoH estimators accurately estimate cell capacity, resistances, and current mismatch. Micro short circuits are identified by cell-to-cell comparison of current mismatch.
Battery parameters are physically coupled with SoC, so a coupled estimation of SoC and battery parameters can use sigma point KF , Unscented KF (UKF), dual EKF, , and non-linear observers.
Abusive lithium-ion battery operations can induce micro-short circuits, which can develop into severe short circuits and eventually thermal runaway events, a significant safety concern in
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