Battery pack thermal management system based on nanofluid optimisation of thermal runaway model for single cell batteries

Li-ion batteries are used in a wide variety of applications, ranging from consumer electronics to electric vehicles (EVs) and large-scale energy storage. There are also ongoing efforts to electrify air transportation. The system level issues such as safety, thermal effects, and cell balancing need to be addressed as use of batteries become widespread in the transportation sector. These issues can be studied experimentally, however, extensive experimental testing at system level involving large battery packs is impractical. Additionally, experimental testing alone cannot provide insights into these issues. This makes experimental characterization studies necessary as well, which are not feasible beyond the lab scale. Appropriate use of modeling and simulation can provide an attractive alternative to gain insights into the system level issues. Presently, simplified equivalent circuit and empirical models are typically used at pack level. Since these models do not capture various physical phenomena and electrochemical processes, they cannot provide necessary insights into these issues. There are many simulation studies on thermal management of battery packs, but these studies are limited to studying heat transfer and fluid flow without capturing their effect on the life and performance of batteries. At the scale of a single li-ion cell, there are physics-based models incorporating various processes, including transport processes, reaction kinetics, thermal effect, and degradation mechanisms. However, these models are typically not used to study battery packs. One such attempt reported in literature involved the use of thermal single-particle battery model at the pack level, but this study considered simplified thermal boundary conditions representing natural convection type heat transfer, a rather simplistic treatment for the heat leaving the batteries1. There have been other similar studies as well2-4. Since thermal management systems presently used in EVs and new designs developed by researchers involve far more complex heat transfer processes, a model capturing heat transfer processes in these thermal management systems in an accurate manner is necessary. Using an accurate physics-based electrochemical-thermal model at the battery pack level and combing it with a heat transfer model for battery thermal management system can enable studying battery performance, aging, and safety characteristics at the pack level. However, this type of simulation would be computationally prohibitively expensive, especially for large battery packs, like the ones used in EVs.In the present work, we first develop volume averaged heat transfer models for two different battery pack designs, one involving prismatic/pouch cells, and other involving cylindrical cells, like the Tesla EV battery pack. These volume averaged models are informed by full-order steady-state computational fluid dynamics (CFD) simulations, and later validated against full-order transient CFD simulations for a wide variety of operating conditions. The simulations conducted using volume averaged heat transfer models are at least two orders of magnitude faster than conventional simulations while maintaining the same level of accuracy. Next, the volume averaged heat transfer model for one of these battery pack designs and the recently reported volume averaged thermal tank-in-series battery model are used to develop a modeling framework for multiple cells connected in series to form a module, and multiple such modules connected in parallel forming a battery pack. This modeling framework enables fast simulation of large battery packs while considering complex battery physics in each individual battery and heat transfer in the thermal management system. This proposed approach can be used for any battery pack design and configuration. Using this modeling framework, we perform detailed analysis on the battery pack, including studying electrochemical and thermal behavior of individual batteries in the pack as well as pack level characteristics under different operating conditions. Finally, we also study effect of cell-cell to variations due to possible manufacturing variations and variations in the state of charge (SOC) of batteries across the battery pack.

To enhance our understanding of the thermal characteristics of lithium-ion batteries and gain valuable insights into the thermal impacts of battery thermal management systems (BTMSs), it is crucial to develop precise thermal models for lithium-ion batteries that enable numerical simulations. The primary objective of creating a battery thermal model is to define equations related to heat generation, energy conservation, and boundary conditions. However, a standalone thermal model often lacks the necessary accuracy to effectively anticipate thermal behavior. Consequently, the thermal model is commonly integrated with an electrochemical model or an equivalent circuit model. This article provides a comprehensive review of the thermal behavior and modeling of lithium-ion batteries. It highlights the critical role of temperature in affecting battery performance, safety, and lifespan. The study explores the challenges posed by temperature variations, both too low and too high, and their impact on the battery’s electrical and thermal balance. Various thermal analysis approaches, including experimental measurements and simulation-based modeling, are described to comprehend the thermal characteristics of lithium-ion batteries under different operating conditions. The accurate modeling of batteries involves explaining the electrochemical model and the thermal model as well as methods for coupling electrochemical, electrical, and thermal aspects, along with an equivalent circuit model. Additionally, this review comprehensively outlines the advancements made in understanding the thermal behavior of lithium-ion batteries. In summary, there is a strong desire for a battery model that is efficient, highly accurate, and accompanied by an effective thermal management system. Furthermore, it is crucial to prioritize the enhancement of current thermal models to improve the overall performance and safety of lithium-ion batteries.

Mathematical model for thermal behavior of lithium-ion battery pack under overheating

Dynamic thermal behavior of micro heat pipe array-air cooling battery thermal management system based on thermal network model

Machine learning assisted multiscale modeling of composite phase change materials for Li-ion batteries’ thermal management

Thermofluidic modeling and temperature monitoring of Li-ion battery energy storage system

A lumped electro-thermal model for a battery module with a novel hybrid cooling system

Lithium ion (li-ion) batteries are gradually increasing their volumetric power and energy densities due to requirements imposed by electric vehicles and portable electronics applications. In consequence, modern lithium ion battery cells and battery packs are having much more compact design where a high amount of energy is encapsulated in a small volume. This imposes a need for an accurate thermal modeling of li-ion batteries in order to avoid battery cells overheating, which leads to safety concerns (e.g. thermal runaways) and accelerates battery cell's performance degradation. Conventional methods for two- and three-dimensional thermal modeling of lithium ion batteries, usually require a coupled electrochemical battery cell model and a lot of knowledge about battery cell internal composition which are not provided and often protected by the battery cell’s manufacturers. This paper proposes an alternative method for battery cell 2D modeling based on the extended concept of electrothermal impedance spectroscopy. Moreover, a verification of the accuracy of the obtained results will be performed. Electrothermal impedance spectroscopy and proposed approach Barsoukov et al. were the first ones presenting the concept of electrothermal impedance spectroscopy (ETIS) in [1]. Later the concept was further extended and improved by Schmidt et al., by introducing internal heat excitation and a more accurate frequency-based measurement method [2]. ETIS is a non-destructive, relatively easy to implement, ‘entropy-free’ and not requiring any a priori knowledge about cell internal composition method, which is used for determining battery cell’s heat capacity and heat conductivity. The ETIS method is based on applying a specific heat flow to the battery and measuring the amplitude and phase delay of resulting battery temperature response [2]. For the frequency-based method, this procedure is repeated for several heat excitation frequencies and thus the thermal impedance function is defined. So far, the ETIS method has been used for one point measurements. This work is extendig the ETIS concept to multi-point measurements and study the accuracy of the two-dimensional thermal model parameterized by the means of the multi-point ETIS measurement. Laboratory setup and description of experiments A laboratory setup was built based on a high-bandwidth Kepco galvanostat and several high-precision temperature sensors located at different points of the high-power LiMO2/Li4Ti5O12 battery cell (Fig.1). Frequency-based method with internal heat generation was applied and results for two spots, on the battery cell surface, are presented in Fig.2. The obtained results are demonstrating different ‘local’ thermal impedances of the battery cell and in consequence uneven battery cell heating (Fig.3 ad Fig.4). These spot dependent thermal impedance functions can be used later for two-dimensional thermal modeling of battery cell by means e.g. Cauer model [3]. Final version of the paper In the final version of the paper, the detailed results from multi-point ETIS will be presented and discussed. A two-dimensional equivalent thermal circuit based battery model will be developed and parametrized by means of multi-point ETIS. Finally, the accuracy of this two-dimensional battery thermal model [3], developed based on the multi-point ETIS, will be analyzed.

Lithium-ion batteries have emerged as a key driver in the commercialization of electric vehicles due to their high energy density, outstanding performance integrated with powertrain systems. Nonetheless, battery performance is greatly influenced by operating temperature which requires precise a thermal management for optimal performance, safety, cost, and longevity especially in high-capacity Li-ion battery. Essentially, investigation of battery thermal management system calls for different aspects of design ranging from configuration and geometry design depending on battery cell and pack layouts to the material selection or development for expected performance and safety level of thermal system. This review formulates heat generation and thermal models in the batteries along with thermal management systems. It explores the effects of abuse conditions in batteries such as thermal runaway and aging. Furthermore, fast charging technologies is discussed in safety design of battery thermal management systems which is rarely studied in similar studies to date. The study also deliberates different types of thermal management system for electric vehicle having Li-ion batteries, such as passive, active, and hybrid models, based on thermal, hydraulic performance and safety. Various heat transfer mediums such as different phase change material types, refrigerant fluid, and combination of them are discussed and categorized based on material characteristic. This review not only collects and reviews the latest battery thermal management system designs, by exploring their future trends and solutions in the performance and safety aspect, but also aims to paves the way for a comprehensive framework in future battery thermal management system research and development.

Review of thermal coupled battery models and parameter identification for lithium-ion battery heat generation in EV battery thermal management system

Electro-thermal characterization of Lithium Iron Phosphate cell with equivalent circuit modeling

Computationally efficient thermal network model and its application in optimization of battery thermal management system with phase change materials and long-term performance assessment

Modeling and control strategy optimization of battery pack thermal management system considering aging and temperature inconsistency for fast charging

Thermal modeling of secondary lithium batteries for electric vehicle/hybrid electric vehicle applications

Battery thermal management strategy for electric vehicles based on nonlinear model predictive control