In failure analysis of battery systems, identifying the root cause of degradation or catastrophic events requires a multidisciplinary approach. Coupled electrochemical-thermal-mechanical models serve as critical tools in validating hypotheses by simulating real-world conditions and interactions between different failure mechanisms. These models integrate multiple physical domains to replicate the complex behavior of batteries under stress, abuse, or operational extremes, providing forensic investigators with a systematic way to test assumptions and narrow down probable causes.

Battery failures often result from interdependent factors rather than isolated events. For example, thermal runaway may originate from a combination of mechanical damage, localized overheating, and electrolyte decomposition. A coupled model allows investigators to assess how these factors interact by simulating scenarios where mechanical deformation triggers a short circuit, leading to joule heating and subsequent thermal propagation. By adjusting input parameters—such as indentation depth, state of charge, or cooling efficiency—the model can reproduce observed failure patterns, confirming or refuting suspected causes.

One key application is in analyzing internal short circuits. Mechanical abuse, such as penetration or crushing, can compromise separator integrity, leading to anode-cathode contact. A coupled model simulates the mechanical strain on the separator, the resulting electrical current spike, and the localized temperature rise. If the simulated thermal response matches post-failure infrared imaging or charring patterns in the actual cell, the hypothesis of mechanical breach as the root cause gains credibility. Conversely, if the model predicts a different thermal profile than observed, alternative causes, such as manufacturing defects or electrolyte impurities, may need investigation.

Another forensic use case involves dendrite-induced failures. Lithium plating and dendrite growth are electrochemically driven but are influenced by temperature and mechanical pressure on the electrodes. A coupled model can simulate how low-temperature charging accelerates plating, how mechanical stress from cycling affects dendrite penetration, and how these collectively lead to internal shorts. By comparing simulation results with microscopy data (e.g., SEM images of electrode cross-sections), analysts can determine whether dendrite growth was the primary failure mode or a secondary effect of other degradation processes.

Coupled models also play a role in investigating thermal runaway propagation in battery packs. Here, the interplay between cell-to-cell heat transfer, electrical interconnect failures, and gas venting dynamics must be considered. A model that integrates electrochemical heat generation with thermal conduction and mechanical deformation of pack structures can replicate the observed sequence of cell failures. For instance, if a pack exhibits sequential thermal runaway from one cell to adjacent units, the model can test whether the failure propagation was driven by thermal radiation, conductive heat transfer through busbars, or mechanical rupture of cooling channels. Matching the simulated propagation timeline and temperature gradients with experimental data validates the underlying hypothesis.

In cases of field failures, where operational history is incomplete, coupled models help reconstruct plausible scenarios. For example, a battery module that failed in an electric vehicle may show signs of both overcharge and mechanical vibration damage. A model can simulate the combined effects of repetitive mechanical stress on weld joints, leading to increased resistance, localized heating, and eventual thermal runaway. If the simulated degradation timeline aligns with the vehicle’s usage patterns and failure symptoms, the root cause can be attributed to mechanical fatigue exacerbated by electrical load cycles.

Validation of these models relies on cross-referencing with physical evidence. For instance, mechanical strain predictions from the model should correlate with deformation patterns in CT scans, while simulated temperature profiles should align with thermal marks on failed components. Discrepancies often reveal gaps in the hypothesis, prompting further investigation into overlooked factors such as material impurities or manufacturing tolerances.

The forensic application of coupled models extends beyond failure analysis to preventive design. By identifying critical interactions between electrochemical, thermal, and mechanical factors, engineers can develop more robust batteries. For example, if a model reveals that a specific electrode curvature increases susceptibility to mechanical strain, designers can adjust cell geometry or stacking pressure to mitigate the risk.

In summary, coupled electrochemical-thermal-mechanical models are indispensable for validating root cause hypotheses in battery failure analysis. By integrating multiple physical domains, these tools enable investigators to test complex interactions, match simulations with empirical evidence, and arrive at data-driven conclusions. The iterative process of modeling and validation not only clarifies failure mechanisms but also informs improvements in battery safety and reliability.