Experimental temperature distributions in a prismatic lithium-ion battery at varying conditions

Panchal, Satyam; Dinçer, İbrahim; Agelin‐Chaab, Martin; Fraser, Roydon; Fowler, Michael

doi:10.1016/j.icheatmasstransfer.2015.12.004

Cited by 75 publications

(24 citation statements)

References 21 publications

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“…The temperature distribution gradient followed the line from the top to the bottom. These thermal profiles are in accordance with the literature, however, the battery dimensions reported are not the same and they were tested separately instead of in a pack of batteries [3,19,27].…”

Section: Discharge At 07 Csupporting

confidence: 85%

“…Lithium polymer batteries (LiPBs) are extensively used as rechargeable energy storage systems for a wide range of electronic devices such as smartphones and laptops due to their high specific energy, power densities, nominal voltage, and low self-discharge rates [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…The ability to quantify and evaluate the mechanism of thermal runaway generated during the electrochemical processes that can occur, will create beneficial information regarding their behavior as well as an active tool to promote their safety. The thermal sensing of LiPBs is typically performed using different types of thermocouples in strategic locations [3,[14][15][16][17][18][19][20][21][22][23][24], micro-electro-mechanical systems [25], mathematical models [26,27], and resistance temperature sensors [28,29]. Generally, for commercialized battery packs, most of the existing methods use single-point temperature monitoring on the cell surface to represent the overall state of the cell [19].…”

Section: Introductionmentioning

confidence: 99%

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Thermal Mapping of a Lithium Polymer Batteries Pack with FBGs Network

et al. 2018

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In this paper, a network of 37 fiber Bragg grating (FBG) sensors is proposed for real-time, in situ, and operando multipoint monitoring of the surface temperature distribution on a pack of three prismatic lithium polymer batteries (LiPBs). Using the network, a spatial and temporal thermal mapping of all pack interfaces was performed. In each interface, nine strategic locations were monitored by considering a three-by-three matrix, corresponding to the LiPBs top, middle and bottom zones. The batteries were subjected to charge and discharge cycles, where the charge was carried out at 1.0 C, whereas the discharge rates were 0.7 C and 1.4 C. The results show that in general, a thermal gradient is recognized from the top to the bottom, but is less prominent in the end-of-charge steps. The results also indicate the presence of hot spots between two of the three batteries, which were located near the positive tab collector. This occurs due to the higher current density of the lithium ions in this area. The presented FBG sensing network can be used to improve the thermal management of batteries by performing a spatiotemporal thermal mapping, as well as by identifying the zones which are more conducive to the possibility of the existence of hot spots, thereby preventing severe consequences such as thermal runaway and promoting their safety. To our knowledge, this is the first time that a spatial and temporal thermal mapping is reported for this specific application using a network of FBG sensors.

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Section: Discharge At 07 Csupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Thermal Mapping of a Lithium Polymer Batteries Pack with FBGs Network

et al. 2018

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“…However, none of these studies for prismatic automotive cells take special care of experimental influences and high-resolution validation. Experimental investigations show equal temperature gradients of large-format cells [21,22] and, therefore, the necessity of spatially resolved temperature measurement and validation. Panchal et al [21] show a temperature gradient on the casing of up to 4 K at the end of constant current discharge with a 20 Ah cell.…”

Section: Introductionmentioning

confidence: 99%

“…Experimental investigations show equal temperature gradients of large-format cells [21,22] and, therefore, the necessity of spatially resolved temperature measurement and validation. Panchal et al [21] show a temperature gradient on the casing of up to 4 K at the end of constant current discharge with a 20 Ah cell. Christen et al [22] reveal a temperature gradient of 6.5 K at the casing of their 60 Ah prismatic cell after constant current cycling with cooling at the cell's bottom at a temperature of 25 • C. As a result of temperature gradients on the casing, neither a single temperature sensor in experiment nor an average temperature value for validation is conclusive enough.…”

Section: Introductionmentioning

confidence: 99%

Thermal Modelling of a Prismatic Lithium-Ion Cell in a Battery Electric Vehicle Environment: Influences of the Experimental Validation Setup

et al. 2019

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In electric vehicles with lithium-ion battery systems, the temperature of the battery cells has a great impact on performance, safety, and lifetime. Therefore, developing thermal models of lithium-ion batteries to predict and investigate the temperature development and its impact is crucial. Commonly, models are validated with experimental data to ensure correct model behaviour. However, influences of experimental setups or comprehensive validation concepts are often not considered, especially for the use case of prismatic cells in a battery electric vehicle. In this work, a 3D electro-thermal model is developed and experimentally validated to predict the cell's temperature behaviour for a single prismatic cell under battery electric vehicle (BEV) boundary conditions. One focus is on the development of a single cell's experimental setup and the investigation of the commonly neglected influences of an experimental setup on the cell's thermal behaviour. Furthermore, a detailed validation is performed for the laboratory BEV scenario for spatially resolved temperatures and heat generation. For validation, static and dynamic loads are considered as well as the detected experimental influences. The validated model is used to predict the temperature within the cell in the BEV application for constant current and Worldwide harmonized Light vehicles Test Procedure (WLTP) load profile.

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Thermal behavior of lithium‐ion battery in microgrid application: Impact and management system

Hasani

Mansor

Kumaran

et al. 2020

Intl J of Energy Research

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Summary Safe and reliable operation is among the considerations when integrating lithium‐ion batteries as the energy storage system in microgrids. A lithium‐ion battery is very sensitive to temperature in which it is one of the critical factors affecting the performance and limiting the practical application of the battery. Furthermore, the adverse effects differ according to the temperature. The susceptibility of lithium‐ion battery to temperature imposes the need to deploy an efficient battery thermal management system to ensure the safe operation of the battery while at the same time maximizing its performance and life cycle. To design a good thermal management system, accurate temperature measurement is vital to assist the battery thermal management system in managing relevant states such as the stage‐of‐charge and state‐of‐health of the battery. This article outlines the effects of low and high temperatures on the performance of Li‐ion batteries. Next, a review of currently available internal temperature monitoring approaches is presented based on their feasibility and complexity. Then, an overview of battery thermal management systems based on different cooling mediums is presented. This includes air cooling, liquid cooling, phase change material (PCM) cooling, heat pipe cooling, boiling‐based cooling, and solid‐state cooling. The final section of this article discusses the practical implementation of the internal temperature measurement approach and battery thermal management system for microgrids. From the review, a suitable candidate is the flexible, low maintenance, and long lifetime hybrid battery thermal management system that combines heat pipe cooling and solid‐state cooling. It is capable of maintaining the maximum operating temperature of the battery within 45°C at up to 3C discharge rate while being a relatively simple system. Additionally, passive PCM with thermally conductive filler can also be employed to assist the hybrid battery thermal management system in improving the temperature uniformity well within 5°C.

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Experimental temperature distributions in a prismatic lithium-ion battery at varying conditions

Cited by 75 publications

References 21 publications

Thermal Mapping of a Lithium Polymer Batteries Pack with FBGs Network

Thermal Mapping of a Lithium Polymer Batteries Pack with FBGs Network

Thermal Modelling of a Prismatic Lithium-Ion Cell in a Battery Electric Vehicle Environment: Influences of the Experimental Validation Setup

Thermal behavior of lithium‐ion battery in microgrid application: Impact and management system

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