**4. Thermal management at the modular level**

Crafting an effective thermal management system (TMS) capable of upholding lithium-ion battery (LIB) modules within designated safe temperature thresholds is imperative. Modern TMS implementations offer a means to mitigate the hazards linked to catastrophic thermal runaway (TR) incidents. Despite its straightforwardness, the efficacy of air-cooling mechanisms is hindered by air's low heat capacity and thermal conductivity. This diminishes heat transfer rate from the battery to the air medium. Given air's limited heat dissipation capabilities, achieving efficient air cooling necessitates substantial airflow volume and mixing rates to counterbalance these inherent limitations. Moreover, specific applications, such as those in space exploration, lack access to air altogether. Consequently, for larger LIB modules operating under high discharge rates, active liquid cooling emerges as a more efficient alternative. Liquid coolants circulate through a thermally conductive metal plate, typically equipped with micro- or macro-channels to augment heat transfer rates. In mitigating the potential hazards associated with liquid cooling, heat pipes are considered a safer option for extracting excess heat from the battery and directing it toward a heat sink [57–59]. Heat pipes are becoming widely adopted in electronic cooling applications owing to their small form factor and exceptional thermal conductivity. Similarly, phase change material (PCM) has surfaced as a novel solution within today's thermal management systems (TMSs) [60–62]. The greatest appeal for implementing PCM is that cell temperature is curbed within a safe, narrow temperature range, which is dictated by the PCM's melting point temperature. Despite this, the PCM system encounters challenges due to its limited thermal conductivity, hindering the efficient dissipation of stored heat. However, utilizing enhanced PCMs like graphene-infused PCM variants could offer a potential solution to overcome this obstacle [63, 64].

One good example of modeling thermal control is the research led by Basu et al. in which they used the capabilities of STAR-CCM+ [65]. By leveraging lateral water coolant channels and harnessing the exceptional heat conductivity of aluminum components, they not only achieved the requisite structural reinforcement but also ensured effective heat exchange between the coolant and water. As illustrated in

**Figure 6.**

*(a) Battery module along with its integrated cooling system, and (b) the mesh generated by STAR-CCM+ (b). (Printed with permission from [65]. Copyright 2016, Elsevier).*

**Figure 6**, their lithium-ion battery (LIB) module comprised 30 Li-NCA/C, 18650 sized cells (6S5P), with the initial row of parallel cells meshed using 400,000 polyhedral cells. Utilizing Battery Design Studio (BDS), they developed a model of the 18,650-sized cell, while the P2D DFN model was deployed for electrochemical aspects and current collector discretization. The CAD design of the cooling system, alongside the geometry generated by BDS, served as inputs for STAR-CCM+. This software facilitated the integration of the electrical mesh, electrochemical elements, and polyhedral mesh. Experimental validation was conducted to assess the model's accuracy in predicting cell temperature profiles, enabling an analysis of the effects of coolant flow rate, contact resistance between LIB cells and cooling elements, and discharge rate. Their compact thermal management system (TMS) successfully limited temperature elevation to within 7 K under high discharge and low coolant flow rates. This endeavor serves as a proof of concept for reliable simulation of a battery TMS, boasting an efficacy level exceeding 90%. Similar methodologies hold potential for streamlined onboard TMSs, promising reduced sensor reliance and simplified control systems.

**Table 2** provides a non-exhaustive list of the existing TR propagation simulation strategies. It is common practice to take advantage of Arrhenius type of equations to at least account for the four common reactions during a TR event. Advanced studies consider additional type of reactions and other additional terms such as the ones associated with the electrochemical heat source and joule heating. The higher the number of these additional reactions or terms, the higher the level of complexity and computational cost. This can be a significant barrier to their suitability for larger modular designs. Implementation of empirical heat source terms is seen as step toward simplification, which can be in the form of time- or temperature-dependent terms or some constants.
