Thermal management of Li-ion battery packs is a critical technological challenge that directly impacts safety and performance. Removal of heat generated in individual Li-ion cells into the ambient is a considerably complicated problem involving multiple heat transfer modes. This paper develops an iterative analytical technique to model conjugate heat transfer in coolant-based thermal management of a Li-ion battery pack. Solutions for the governing energy conservation equations for thermal conduction and convection are derived and coupled with each other in an iterative fashion to determine the final temperature distribution. The analytical model is used to investigate the dependence of the temperature field on various geometrical and material parameters. This work shows that the coolant flowrate required for effective cooling can be reduced significantly by improving the thermal conductivity of individual Li-ion cells. Further, this work helps understand key thermal-electrochemical trade-offs in the design of thermal management for Li-ion battery packs, such as the trade-off between temperature rise and energy storage density in the battery pack.

Predicting temperature rise accurately during fast charge/discharge of a Li-ion cell is essential to avoid thermal runaway and extend battery life. While modeling the temperature rise, it is necessary to model the heat generation correctly. Heat of mixing, one of the four main sources of heat generation in a Li-ion battery, has often been considered insignificant and therefore excluded from modeling. When included, it is modeled using the expression from a Taylor expansion approximation. In this work, we have shown the conditions when including the heat of mixing becomes important and quantified the error associated with using the Taylor expansion, especially under high charge/discharge conditions. Consequently, we carry out the calculation of the rate of enthalpy change and the heat generation rate from the most fundamental equation for the rate of the total enthalpy change without simplifying assumptions or approximations. The heat generation rate calculated doing so naturally includes irreversible, reversible and mixing heat. We then exclusively separate out the heat of mixing by subtracting the rate of enthalpy change by reaction from the rate of the total enthalpy change. Results show that the contribution of heat of mixing in the total heat generated increases with the charge/discharge rate and is as large as 23% for a 6 C discharge. This result suggests that while modeling heat generation for fast charge/discharge, it is necessary to include the heat of mixing and avoid calculating it using the Taylor expansion approximation.

In the published paper, the details of the implementation of Newman's P2D model was incomplete. Additionally, the acknowledgement section failed to note the contributions of a collaborator who provided the P2D simulation code used in the original work.

Traditionally it has been assumed that battery thermal management systems should be designed to maintain the battery temperature around room temperature. That is not always true as lithium-ion battery (LIB) R&D is pivoting towards the development of high energy density and fast charging batteries. Therefore, it is necessary to have a comprehensive review of thermal considerations for LIBs targeted for high energy density and fast charging, i.e., the optimal thermal condition, thermal physics (heat transport and generation) inside the battery, and thermal management strategies. As the energy density and charge rate increases, the optimal battery temperature can shift to be higher than room temperature. In the first part of the review various sources of heat generation inside LIBs and various approaches to minimizing battery heat generation are summarized. The importance of heat of mixing due to ion diffusion during fast charging is also highlighted. To improve the temperature uniformity and avoid excessive internal temperature rise, heat transfer inside the battery needs to be enhanced, and reducing the thermal contact resistance between the electrodes and separator can significantly increase the effective thermal conductivity of batteries. In the second part of the review various challenges and latest developments related to thermal transport and properties of LIBs are discussed. Finally, a summary of latest advancement on smart control of internal temperature of LIBs is discussed as depending on the ambient temperature and the optimal temperature; the battery heat needs to be retained or dissipated to elevate or avoid temperature rise.

The 3ω method is a well-established thermal technique used to measure the thermal conductivity of materials and the thermal resistance of interfaces. It has significant advantages over other steady state and transient thermal techniques in its ability to provide spatially resolved thermal property measurements over a wide range of thermal conductivity. Despite its advantages, it has been restricted to lab-scale use because of the difficulty involved in sample preparation and sensor fabrication and is limited to non-metallic substrates. High-throughput 3ω measurements with reusable sensors have not been realized yet. In this work, we demonstrate a method of applying reusable 3ω sensors fabricated on flexible polyimide films to measure bulk and spatially resolved thermal properties. We establish the limits of thermal conductivity measurement with the method to be 1 to 200 W/mK, and within the measurement limit, we verify the method by comparing the measured thermal conductivities of standard samples with established values. From the 3ω measurements, we also determine the thermal resistance of an interlayer of thermal grease as a function of pressure and compare it against the resistance calculated from direct thickness measurements to demonstrate the ability of this method to provide spatially resolved subsurface information. The technique presented is general and applicable to both metallic and non-metallic substrates, providing a method for high-throughput 3ω measurements with reusable sensors and without considerable sample preparation.

Phase change materials are promising for thermal energy storage; however, one major bottleneck for their practical implementation is their unclear supercooling behaviors. In this work, we introduce a framework to predict the degree of supercooling for a phase change material subject to arbitrary geometrical and thermal conditions by analyzing the phase change material's intrinsic nucleation characteristics with a statistical model. The prediction capability of our framework is successfully validated with experiments using magnesium chloride hexahydrate as a phase change material. For a system with a uniform temperature distribution, our framework can predict the average degree of supercooling. For a general case such as phase change materials embedded in a heat sink, the framework can accurately predict the expected time, with less than 8% deviation, for nucleation under given conditions. This work provides important insights in understanding and predicting supercooling behavior, thereby providing guidelines for the optimal design of phase change material-based thermal energy storage applications.

The development of battery sensing techniques is crucial for safe, reliable, and fast operation of lithium-ion batteries (LIBs). There is a growing realization that the spatially averaged chemical information provided by existing battery diagnostic tools is insufficient for understanding degradation of LIBs. Here, we report the use of thermal waves for operando probing of the local lithium concentration as a function of depth inside battery electrodes. The dependence of the thermal conductivity of electrodes on lithiation is used for lithium detection for the first time. A proof-of-concept study of graphite anodes demonstrates that thermal-wave sensing provides spatial information of lithium concentration comparable with experimental results using synchrotron X-ray diffraction. Therefore, a valuable battery sensing technique based on thermal waves is developed for studying the lithium concentration and the degradation of electrodes during fast charge, which may lead to much cheaper and faster sensing techniques compared with synchrotron-based techniques.

The lithium metal-solid-state electrolyte interface plays a critical role in the performance of solid-state batteries. However, operando characterization of the buried interface morphology in solid-state cells is particularly difficult because of the lack of direct optical access. Destructive techniques that require isolating the interface inadvertently modify the interface and cannot be used for operando monitoring. In this work, we introduce the concept of thermal wave sensing using modified 3ω sensors that are attached to the outside of the lithium metal-solid-state cells to noninvasively probe the morphology of the lithium metal-electrolyte interface. We show that the thermal interface resistance measured by the 3ω sensors relates directly to the physical morphology of the interface and demonstrates that 3ω thermal wave sensing can be used for noninvasive operando monitoring the morphology evolution of the lithium metal-solid-state electrolyte interface.

Monitoring real-world battery degradation is crucial for the widespread application of batteries in different scenarios. However, acquiring quantitative degradation information in operating commercial cells is challenging due to the complex, embedded, and/or qualitative nature of most existing sensing techniques. This process is essentially limited by the type of signals used for detection. Here, we report the use of effective battery thermal conductivity (k_eff) as a quantitative indicator of battery degradation by leveraging the strong dependence of k_eff on battery-structure changes. A measurement scheme based on attachable thermal-wave sensors is developed for non-embedded detection and quantitative assessment. A proof-of-concept study of battery degradation during fast charging demonstrates that the amount of lithium plating and electrolyte consumption associated with the side reactions on the graphite anode and deposited lithium can be quantitatively distinguished using our method. Therefore, this work opens the door to the quantitative evaluation of battery degradation using simple non-embedded thermal-wave sensors.

The recent push for the "materials by design"paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (∼50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (∼3 μm) and scratched sample surfaces. This work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.