Towards in-situ detection of nascent short circuits and accurate estimation of state of short in Lithium-Ion Batteries

Early detection of internal short circuits (ISC) in Lithium-Ion Batteries (LIBs) is crucial for avoiding potential catastrophes. State-of-the art health monitoring methods fall short in terms of their ability to detect early-stage short circuits and in terms of ease of implementation. We report a unique internal-short circuit detection method, capable of detecting early-stage short circuits. A set of electrochemically curated pulse current probes, activated at predetermined states of charge (SOC), accurately determine the short-induced leakage current by comparing with an on-board physics based electrochemical-thermal reduced order model, that considers characteristic non-linear behaviour of LIBs. These specially designed diagnostic probes act as a ‘treadmill’ test, which detect soft short and estimates the soft short resistance accurately. Importantly, we demonstrate its ability to detect, estimate both internal short and ageing-related battery degradation, even when both are present. Proof-of-concept experiments on commercial batteries show our method's ability to detect soft short (up to 200Ω) and ageing extents (>90%) with >98% accuracy. Anchored in underlying electrochemical processes of the battery, we provide a detailed analysis on how and why this method is uniquely positioned as an accurate, practically implementable health and safety monitoring algorithm on a battery management system. [Display omitted] •Soft short detection with an electrochemically defined pulse probe technique.•Differentiation between short and degradation signatures.•Accurate estimation of state of short & health (SOS & SOH) with just 5 data points.•Experimental validation shows ≥98% accuracy for SOS ≤200Ω & SOH ≥90%.•Highly robust Battery Management System (BMS) algorithm for commercial applications.