Modeling and Simulation of Battery Systems

Mukherjee, Partha P.; Pannala, Sreekanth; Turner, John A.

doi:10.1002/9783527637188.ch25

Cited by 14 publications

(30 citation statements)

References 98 publications

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“…The heat generated and the change in reacting species content during this reaction is given as Q ne = H ne W c R ne [16] dt sei dt = R ne [17] dc ne dt = −R ne [18] where Q ne (W m −3 ) is the volumetric heat generation, and H ne (J kg −1 ) is the specific heat release.…”

Section: Methodsmentioning

confidence: 99%

“…13,14 The thermal behavior of lithium-ion batteries under normal operation has been studied extensively and can be modeled using a coupled thermal-electrochemical model. [15][16][17] A different approach that captures the side-reactions that occur at elevated temperatures is required to capture abuse behavior and determine safe practices. Many researchers have studied the mechanisms of thermal runaway in an attempt to determine methods of improving LIB safety.…”

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confidence: 99%

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Characterization of Lithium-Ion Battery Thermal Abuse Behavior Using Experimental and Computational Analysis

López

Jeevarajan

Mukherjee

2015

J. Electrochem. Soc.

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175

126

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While the popularity of lithium-ion batteries (LIBs) has increased significantly in recent years, safety concerns due to the high thermal instability of LIBs limit their use in applications with zero tolerance for a catastrophic failure. Industries such as aerospace and automotive must be very stringent in their selection and design of lithium-ion cells and modules to meet safety requirements. A safety issue of particular interest is a scenario called thermal runaway in which one or more exothermic side-reactions occur, leading to elevated temperature ranges that in turn lead to an uncontrollable and excessive release of heat. This work aims to characterize the effect of these reactions by utilizing a thermal abuse model that predicts single-cell behavior when subjected to an elevatedtemperature. The experimental test of the thermal safety behavior includes a constant-power heating element to trigger a thermal runaway event. This study takes an existing thermal abuse model and modifies it to emulate the conditions during a constant-power heating test. The result is found to be in agreement with the experimental data for different cell configurations. The influence of convection condition, cell physical configuration, and electrolyte combustion on the cell thermal behavior is also investigated.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Characterization of Lithium-Ion Battery Thermal Abuse Behavior Using Experimental and Computational Analysis

López

Jeevarajan

Mukherjee

2015

J. Electrochem. Soc.

Self Cite

175

126

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“…Lithiation and delithiation causes volume expansion and contraction of particles which may cause particles to lose contact with each other, thereby changing thermal pathways (or diffusive pathways) and reducing effective conductivity. 19,4 Relevance to exponents used in electrochemical model equations.-The results presented above may be used to evaluate the correctness of effective properties widely used in volume averaged electrochemical models. As explained in section Volume averaged charge and species transport equations, the effective transport properties used in species and charge transport are given by Eqs.…”

Section: Bruggeman's Exponents For Effective Thermal Conductivity-eqmentioning

confidence: 99%

“…3 Realistic modeling of batteries across these disparate physics and scales is critical for their effective and safe commercialization. 4 Research in lithium-ion batteries has been primarily driven by the need to develop cathode, anode and electrolyte materials that deliver high potential and capacity. 5,6 On the cell level, the battery consists of a porous composite anode and cathode filled with an electrolyte and separated by a separator.…”

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confidence: 99%

“…This is being made possible with the advent of instruments like micro-computed tomography (μCT ) scanners and focused ion beam-scanning electron microscopes (FIB-SEM) in conjunction with advanced image processing techniques. 14 Unlike volume averaging, performing transport simulations on geometries explicitly partitioned into various constituent phases can be termed as fully resolved pore-scale or particle-scale simulations (some authors 4 also use the term direct numerical simulation (DNS)). A few papers have been published using pore-scale simulations, employing simple synthetic geometries and other simplifications.…”

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confidence: 99%

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Bruggeman's Exponents for Effective Thermal Conductivity of Lithium-Ion Battery Electrodes

Vadakkepatt

Trembacki

Mathur

et al. 2015

J. Electrochem. Soc.

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Simulations of lithium-ion battery cells are usually performed with volume averaging methods that employ effective transport properties. Bruggeman's model, which is widely used to determine these effective properties, is primarily based on the volume fraction of porous electrodes. It does not consider actual particle shape, size or the topology of constituent phases; these play a crucial role in determining effective transport. In this paper, a general derivation of the effective thermal conductivity of multiphase materials, which can be correlated with these factors, is derived using the volume averaging technique. Three-dimensional finite volume meshes of fully-resolved lithium-ion battery cathode microstructures are reconstructed from scanned images. Effective volume averaged thermal conductivity is then determined from numerical analysis of thermal transport on these meshes. It is shown that the Bruggeman model for effective thermal conductivity must be recalibrated to fit the effective thermal conductivity computed from these detailed simulations. The relevance of these results to effective transport properties typically employed in electrochemical simulations is presented. Commonly used theories for effective thermal transport in composites are evaluated for comparison. Furthermore, it is shown that Bruggeman's exponents yield an important quantitative measure, the connectivity, to characterize the physical path for transport through the underlying phases. The importance of lithium-ion batteries is now well recognized in light of the global energy crisis, global warming and the need for efficient and inexpensive energy storage options.1,2 Battery physics encompass thermodynamics, electrochemistry, material science, transport phenomena and solid mechanics, and span multiple length and time scales.3 Realistic modeling of batteries across these disparate physics and scales is critical for their effective and safe commercialization. 4 Research in lithium-ion batteries has been primarily driven by the need to develop cathode, anode and electrolyte materials that deliver high potential and capacity. 5,6 On the cell level, the battery consists of a porous composite anode and cathode filled with an electrolyte and separated by a separator. Typically, the thickness of such a sandwich is hundreds of microns, while lateral dimensions are of the order of centimeters. Lithium ions shuttle between cathode and anode during charge and discharge. Active cathode particles (for e.g. LiCoO 2 , LiMn 2 O 4 , LiFePO 4 ), which form the key constituent of batteries, are lithium insertion compounds and have high lithium ion conductivity. These active particles are spatially dispersed and held together by binder (such as polyvinylidene fluoride [PVDF]), while the electrolyte resides in the pores, wetting the active particles, and facilitating transport of lithium ions. The electronic conductivity of these active materials is generally low compared to lithium ion conductivity. Therefore additives like carbon particles are dispersed ...

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