Thermal management represents a critical challenge in battery systems, particularly for emerging solid-state battery architectures. Unlike conventional lithium-ion batteries with liquid electrolytes, solid-state batteries exhibit distinct thermal characteristics that complicate modeling efforts. Three primary factors contribute to these challenges: interfacial resistances between dissimilar materials, anisotropic thermal properties of ceramic electrolytes, and the absence of liquid-phase convection. These factors demand specialized modeling approaches to accurately predict thermal behavior under operational conditions.

Interfacial resistances between solid components create thermal bottlenecks that are absent in liquid electrolyte systems. In traditional batteries, liquid electrolytes provide continuous thermal pathways between electrodes and separators. Solid-state batteries instead contain multiple material interfaces, such as ceramic electrolyte to electrode contacts and grain boundaries within polycrystalline materials. Each interface introduces a thermal boundary resistance, often called Kapitza resistance, which reduces heat transfer efficiency. The magnitude of this resistance depends on the acoustic mismatch between materials, surface roughness, and interfacial bonding quality. For example, the thermal boundary resistance between lithium metal and common solid electrolytes can exceed 10^-7 m²·K/W, creating localized hotspots during operation. These microscopic discontinuities require mesoscale modeling techniques that bridge atomic-scale interactions with macroscopic heat flow.

The anisotropic thermal conductivity of ceramic electrolytes presents another modeling complication. Many promising solid electrolytes, such as LLZO (Li₇La₃Zr₂O₁₂), exhibit crystalline structures with directional heat transfer properties. Along certain crystallographic orientations, thermal conductivity may measure 2-3 W/m·K, while perpendicular directions show significantly lower values. Polycrystalline materials with random grain orientations average these directional effects, but textured or aligned microstructures preserve the anisotropy. This directional dependence necessitates tensor-based thermal conductivity models rather than the scalar approximations sufficient for isotropic liquid electrolytes. Experimental characterization of these properties remains challenging due to the difficulty in preparing single-crystal samples of sufficient size for traditional measurement techniques.

The absence of liquid electrolyte convection fundamentally alters heat dissipation mechanisms in solid-state batteries. Liquid electrolytes in conventional cells provide convective cooling by circulating between electrodes, distributing heat more evenly throughout the cell. Solid-state systems rely entirely on conductive heat transfer through rigid materials with limited thermal diffusivity. This results in steeper thermal gradients, particularly under high current operation where joule heating becomes significant. The problem compounds in multilayer stacked configurations common in pouch cell designs, where heat must traverse numerous interfaces before reaching external cooling surfaces. Thermal models must account for this purely conductive regime by incorporating detailed three-dimensional geometries of all solid components.

Multiphysics coupling introduces additional complexity to solid-state battery thermal modeling. Mechanical stresses from thermal expansion mismatch between materials can alter interfacial contact resistances during operation. For instance, lithium metal anodes exhibit a coefficient of thermal expansion nearly an order of magnitude greater than typical oxide electrolytes. Temperature variations induce interfacial gaps that further increase thermal resistance in a positive feedback loop. This thermomechanical coupling requires simultaneous solution of heat transfer and structural deformation equations, significantly increasing computational demands compared to isothermal mechanical models.

The temperature dependence of ionic conductivity in solid electrolytes creates another feedback mechanism that thermal models must capture. Unlike liquid electrolytes with relatively flat temperature-conductivity profiles, many solid electrolytes show strong Arrhenius-type behavior where conductivity drops exponentially with decreasing temperature. Localized cooling from poor heat dissipation can thus increase internal resistance, generating more joule heating in a self-reinforcing cycle. Accurate models require iterative solutions that update electrical and thermal properties based on local temperature calculations.

Experimental validation of thermal models faces unique hurdles for solid-state systems. Traditional battery calorimetry techniques designed for liquid electrolyte cells often fail to resolve the microscopic thermal gradients present in solid-state architectures. Infrared thermography encounters challenges from opaque casing materials and the small length scales of interfacial effects. Embedded microthermocouples risk altering the very thermal pathways they aim to measure. These limitations necessitate the development of specialized characterization techniques to provide reliable validation data for modeling efforts.

Scale effects further complicate thermal modeling across different battery form factors. Laboratory-scale coin cells may exhibit negligible thermal gradients due to their small dimensions, while large-format pouch cells or stacked configurations develop significant temperature variations. The transition from small-scale testing to commercial-scale designs requires models that can accurately extrapolate thermal behavior across orders of magnitude in size. This scaling challenge is particularly acute for solid-state batteries where interfacial effects dominate at all scales.

Manufacturing variability introduces another layer of uncertainty in thermal predictions. Sintering conditions, surface preparation techniques, and applied stack pressures all influence interfacial thermal resistances in ways that are difficult to quantify statistically. Probabilistic modeling approaches may be required to account for this production-induced variability, especially for quality control in mass production settings.

Emerging modeling techniques show promise for addressing these challenges. Phase-field methods can capture the evolution of interfacial contacts under thermal cycling. Peridynamics approaches offer advantages for modeling discontinuous thermal fields across material boundaries. Machine learning methods may help bridge the gap between atomistic simulations and continuum-scale models by identifying dominant heat transfer pathways in complex microstructures.

The development of accurate thermal models for solid-state batteries requires coordinated advances in computational methods, material characterization, and experimental validation techniques. Future progress will depend on establishing standardized testing protocols specifically designed for solid-state thermal properties, along with collaborative efforts between materials scientists and thermal engineers to develop unified modeling frameworks. These advancements will prove essential for enabling safe, high-performance solid-state battery designs across automotive, aerospace, and grid storage applications.