Analysis of Heat-Spreading Thermal Management Solutions for Lithium-Ion Batteries

Khasawneh, Hussam J.; Neal, John A.; Canova, Marcello; Guezennec, Yann; Wayne, Ryan; Taylor, Jonathan; Smalc, Martin; Norley, Julian

doi:10.1115/imece2011-63662

Cited by 11 publications

(4 citation statements)

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“…[49], 0.69 Wm -1 K -1 in Ref. [50], and 0.75 Wm -1 K -1 in Ref. [51], which are estimated based on the thickness of each electrode.…”

Section: Estimation Of Core Temperature and Thermal Swellingmentioning

confidence: 99%

A novel thermal swelling model for a rechargeable lithium-ion battery cell

Epureanu

2016

Journal of Power Sources

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The thermal swelling of rechargeable lithium-ion battery cells is investigated as a function of the charge state and the charge/discharge rate. The thermal swelling shows significant dependency on the state of charge and the charge rate. The thermal swelling follows a quadratic form at low temperatures, and shows linear characteristics with respect to temperature at high temperatures in free-swelling conditions. Moreover, the equivalent coefficient of thermal expansion is much larger than that of each electrode and host materials, suggesting that the separator and the complex shape of the cell play a critical role in thermal expansion. Based on the experimental characterization, a novel thermal swelling model is proposed. The model introduces an equivalent coefficient of thermal expansion for the cell and also considers the temperature distribution throughout the battery by using heat transfer theory. The comparison between the proposed model and experiments demonstrates that the model accurately predicts thermal swelling at a variety of charge/discharge rates during operation and relaxation periods. The © 2015. This manuscript version is made available under the Elsevier user license http://www.elsevier.com/open-access/userlicense/1.0/ model is relatively simple yet very accurate. Hence, it can be useful for battery management applied to prolong the cycle life of cells and packs. Keywords Lithium-ion battery; phase transition; swelling; thermal expansion; the coefficient of thermal expansion 1. Introduction Concerns for energy security, instability in world oil markets, and limitations of carbon emissions have accelerated the development of eco-friendly, high-efficiency automobiles. This drives automobile industries toward the development of vehicle electrification technology.Electrified vehicles currently use lithium-ion (Li-ion) batteries as the reversible power source.Li-ion batteries have advantages such as high power/energy density, high potential, and low selfdischarge rate. They are also environmentally friendly and have a long life cycle [1][2][3].While vehicle electrification with the advent of the Li-ion batteries [4] enhances fuel efficiency and reduces CO 2 emissions, many challenges still exist when using Li-ion batteries such as their limited performance at low temperatures [5] and their thermal runaway [6]. Especially, extensive research on vehicle electrification has been driven by stringent safety standards for air and ground applications. Therefore, recent research focuses on the thermal distribution and the heat dissipation of Li-ion battery packs [7,8] as elevated temperatures not only can cause thermal runaway but can also degrade battery life. A variety of heat transfer models have been created

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“…[49], 0.69 Wm -1 K -1 in Ref. [50], and 0.75 Wm -1 K -1 in Ref. [51], which are estimated based on the thickness of each electrode.…”

Section: Estimation Of Core Temperature and Thermal Swellingmentioning

confidence: 99%

A novel thermal swelling model for a rechargeable lithium-ion battery cell

Epureanu

2016

Journal of Power Sources

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“…The preset parameters are shown in Table 3, and these structure parameters have been identified and validated in the previous work [18,37]. To verify the effectiveness of the DEKF-based coestimation method, we made several estimation comparisons of the performance of the DEKF and baseline EKF algorithms whereby the same parameters are provided in Table 3.…”

Section: Validationmentioning

confidence: 99%

Sensorless Coestimation of Temperature and State-of-Charge for Lithium-Ion Batteries Based on a Coupled Electrothermal Model

Bai

Zhang

Gao

et al. 2023

International Journal of Energy Research

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Accurate estimations of the temperature and the state-of-charge (SOC) are of extreme importance for the safety of lithium-ion battery operation. Traditional battery temperature and SOC estimation methods often omit the relation between battery temperature and SOC, which may lead to significant errors in the estimations. This study presents a coupled electrothermal battery model and a coestimation method for simultaneously estimating the temperature and SOC of lithium-ion batteries. The coestimation method is performed by a coupled model-based dual extended Kalman filter (DEKF). The coupled estimators utilizing electrochemical impedance spectroscopy (EIS) measurements, rather than utilizing direct battery surface measurements, are adopted to estimate the battery temperature and SOC, respectively. The information being exchanged between the temperature estimator and the SOC estimator effectively improves the estimation accuracy. Extensive experiments show that, in contrast with the EKF-based separate estimation method, the DEKF-based coestimation method is more favorable in reducing errors for estimating both the temperature and SOC even if the battery core temperature has increased by 17°C or more during the process of test.

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“…Each of the Li-ion battery packs made use of A123 ANR26650M1A cells [38]. This battery was modeled in MATLAB/Simulink using the Randle equivalent-circuit phenomenological model [39]. It was built as a control-oriented model incorporating both the thermal and electrical properties as well as parameter estimation, as displayed by the block diagram in Figure 8(b).…”

Section: Modeling and Simulationmentioning

confidence: 99%

Flexible Distribution of Energy and Storage Resources: Integrating These Resources into a Microgrid

Illindala

Khasawneh

Renjit

2015

IEEE Ind. Appl. Mag.

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NDUSTRIAL POWER SYSTEMS IN the mining and metal industries typically comprise several large and fluctuating loads, such as crushers, excavators, shovels, and steel mills. Flexible distribution of energy and storage resources (FDERS) is a proposed new framework for reliably regulating the quickly varying loads supplied by a network of multiple smaller-rated distributed energy resources (DERs), especially when power from the main grid is not available. It was inspired by the cooperative V-shape formation of flocks of birds and the peloton/echelon formation of cycling racing teams for extending their IEEE Industry ApplIcAtIons MAgAzInE • sEpt|oct 2015 • www.IEEE.org/IAs 32 IEEE Industry ApplIcAtIons MAgAzInE • sEpt|oct 2015 • www.IEEE.org/IAs 33 endurance limits. Similar ideas applied to integrating DERs can extend sustainability through increased resource lifetime, optimal energy storage deployment, enhanced controllability, and improved system robustness.FDERS is a cooperative framework among multiple interconnected DERs to achieve these goals through in situ reconfiguration, variable interface reactances, virtual inertia, and/or adaptive controls. The decisions can be based on various factors, such as energy resource availability, response characteristics, and the life-cycle costs of participating DERs. This article explains the basic concept of FDERS and its benefits supported by case studies focusing on battery-lifetime analyses. DERs and Their IntegrationLarge and fluctuating loads, such as crushers, excavators, and steel rolling mills, are typical at any mining or metal industrial site. Their industrial power-system design invariably requires precise and painstaking planning in the early stages. The key motivation for this article was to address a basic question: What is the best way of integrating multiple smaller-rated DERs to enable them as a whole to reliably supply a large and fluctuating load, especially when power from the main grid is not available?DERs include combined heat and power (CHP), microturbines (MTs), fuel cells (FCs), microhydro power, solar/ photovoltaic (PV) systems, and wind power [1]-[4]. Energy production from smaller-rated and dispatchable DERs on a low-voltage distribution system may have a slow response time. On the other hand, renewables, such as solar and wind power, are nondispatchable resources. Under islanded conditions, it is essential to complement them with energy storage for reliable operation of the DERs [4]- [8]. A higher penetration of DERs has become inevitable for meeting ever-growing energy demands [9], [10], and coordinating them is essential to achieve sustainable and reliable distribution. In the recent past, concepts such as microgrids [2], [8] and virtual power plants [3] have been presented to tackle DER coordination issues. Illindala [11] introduced the concept of FDERS, where multiple DERs operate as a network, teaming up in a formation that secures energy stability through optimal resource utilizations.FDERS was inspired by the V-shape formation of flocks of...

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Analysis of Heat-Spreading Thermal Management Solutions for Lithium-Ion Batteries

Cited by 11 publications

References 54 publications

A novel thermal swelling model for a rechargeable lithium-ion battery cell

A novel thermal swelling model for a rechargeable lithium-ion battery cell

Sensorless Coestimation of Temperature and State-of-Charge for Lithium-Ion Batteries Based on a Coupled Electrothermal Model

Flexible Distribution of Energy and Storage Resources: Integrating These Resources into a Microgrid

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