Battery failure analysis relies on accelerated life testing (ALT) to predict field failure modes within compressed timeframes. The correlation between ALT results and real-world failures is critical for validating battery designs, yet the validity of these models depends on understanding the limits of acceleration techniques, particularly the Arrhenius equation. This analysis focuses on how ALT maps to field failures while addressing constraints in thermal acceleration models.

ALT employs elevated stress conditions to induce failure mechanisms that would otherwise manifest over extended periods under normal operation. Common stressors include temperature, charge-discharge cycling rates, and state of charge (SOC) windows. Thermal acceleration via the Arrhenius model is widely adopted due to its simplicity, but its applicability is bounded by electrochemical and material-specific constraints. The model assumes a single activation energy for degradation, which oversimplifies multi-mechanism degradation in batteries.

Field failure modes in lithium-ion batteries include capacity fade, impedance rise, internal short circuits, and thermal runaway. Capacity fade often results from solid electrolyte interface (SEI) growth, lithium plating, or active material loss. Impedance rise is linked to electrolyte decomposition or contact loss within electrodes. ALT aims to replicate these mechanisms by accelerating their underlying chemical kinetics. For SEI growth, elevated temperatures increase the rate of electrolyte reduction at the anode, but excessive temperatures may introduce unrealistic side reactions not observed in field conditions.

The Arrhenius equation estimates the acceleration factor (AF) as AF = exp[(Ea/k)(1/T_use - 1/T_stress)], where Ea is activation energy, k is Boltzmann’s constant, and T_use and T_stress are operational and test temperatures, respectively. However, this assumes Ea remains constant across temperatures, which is invalid when degradation mechanisms shift. For example, SEI growth typically has an Ea of 0.4–0.7 eV, but above 60°C, parasitic reactions with higher Ea may dominate, skewing predictions. Similarly, lithium plating accelerates at low temperatures and high charging rates, a scenario poorly captured by Arrhenius.

Mechanical degradation, such as electrode particle cracking or separator shrinkage, is another field failure mode with non-Arrhenius behavior. These mechanisms are driven by cyclic mechanical stress rather than thermal activation, rendering Arrhenius ineffective. ALT for mechanical wear requires alternative acceleration methods, such as increased C-rates or depth of discharge (DOD), though these may alter failure modes compared to field conditions.

Gas evolution and electrolyte depletion are additional field failures tied to oxidation at the cathode or solvent breakdown. ALT using high voltages or temperatures accelerates these processes, but the correlation to field data is nonlinear. For instance, cathode electrolyte interphase (CEI) formation accelerates at high SOC but may follow different kinetics than under moderate SOC cycling. Over-acceleration can also deplete electrolyte prematurely, masking long-term interfacial stability issues.

To address these limits, multi-stress ALT protocols combine thermal, electrical, and mechanical stressors. A representative approach might cycle cells at elevated temperature (45–55°C), high C-rate (1–2C), and 80–100% DOD while monitoring impedance and gas generation. This better replicates field conditions but requires careful calibration to avoid mechanism crossover. For example, simultaneous high temperature and high C-rate may induce lithium plating unrelated to field usage patterns.

Validation of ALT results against field data is essential. A study comparing 12-month field-aged cells with 3-month ALT cells showed good agreement for capacity fade when ALT temperatures stayed below 50°C. Beyond this, divergence occurred due to parasitic copper dissolution. Such findings underscore the need for mechanism-specific acceleration limits.

Non-Arrhenius behaviors also arise in solid-state batteries, where interfacial degradation dominates. Here, mechanical delamination and lithium dendrite growth are poorly accelerated by temperature alone. Pressure and current density become critical stressors, necessitating hybrid ALT models.

In summary, ALT provides valuable failure mode insights but requires disciplined application. The Arrhenius model is effective for thermally driven mechanisms within validated temperature bounds. For non-thermal failures, multi-stress approaches or alternative models are needed. Robust ALT design must prioritize failure mode alignment over acceleration speed, ensuring predictive accuracy for field reliability.