Test Method for Thermal Characterization of Li-Ion Cells and Verification of Cooling Concepts

Christen, R.; Rizzo, Gerhard; Gadola, Alfred; Stöck, Max

doi:10.3390/batteries3010003

Cited by 29 publications

(22 citation statements)

References 16 publications

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“…Correspondingly, the method presented by Christen [39] is comprised of the contemporaneous acquisition of local heat flux density and temperature. Furthermore, this procedure allows both quantities to be controlled, which enables the reproduction of different packaging conditions.…”

Section: Thermal Conductivitymentioning

confidence: 99%

Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

2018

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This paper reviews different methods for determination of thermal parameters of lithium ion batteries. Lithium ion batteries are extensively employed for various applications owing to their low memory effect, high specific energy, and power density. One of the problems in the expansion of hybrid and electric vehicle technology is the management and control of operation temperatures and heat generation. Successful battery thermal management designs can lead to better reliability and performance of hybrid and electric vehicles. Thermal cycling and temperature gradients could have a considerable impact on the lifetime of lithium ion battery cells. Thermal management is critical in electric vehicles (EVs) and good thermal battery models are necessary to design proper heating and cooling systems. Consequently, it is necessary to determine thermal parameters of a single cell, such as internal resistance, specific heat capacity, entropic heat coefficient, and thermal conductivity in order to design suitable thermal management system.

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Section: Thermal Conductivitymentioning

confidence: 99%

Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

2018

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“…Variation reduction among cells can contribute significantly in boosting the overall performance of a large energy storage installation. While investigating the thermal imbalance between cells, Christen et al [42] mentioned that variation in resistance can significantly reduce the lifetime of a battery. in the manufacturing process [38].…”

Section: Problem Definitionmentioning

confidence: 99%

Further Cost Reduction of Battery Manufacturing

Asif

Singh

2017

Batteries

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Abstract:The demand for batteries for energy storage is growing with the rapid increase in photovoltaics (PV) and wind energy installation as well as electric vehicle (EV), hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle (PHEV). Electrochemical batteries have emerged as the preferred choice for most of the consumer product applications. Cost reduction of batteries will accelerate the growth in all of these sectors. Lithium-ion (Li-ion) and solid-state batteries are showing promise through their downward price and upward performance trends. We may achieve further performance improvement and cost reduction for Li-ion and solid-state batteries through reduction of the variation in physical and electrical properties. These properties can be improved and made uniform by considering the electrical model of batteries and adopting novel manufacturing approaches. Using quantum-photo effect, the incorporation of ultra-violet (UV) assisted photo-thermal processing can reduce metal surface roughness. Using in-situ measurements, advanced process control (APC) can help ensure uniformity among the constituent electrochemical cells. Industrial internet of things (IIoT) can streamline the production flow. In this article, we have examined the issue of electrochemical battery manufacturing of Li-ion and solid-state type from cell-level to battery-level process variability, and proposed potential areas where improvements in the manufacturing process can be made. By incorporating these practices in the manufacturing process we expect reduced cost of energy management system, improved reliability and yield gain with the net saving of manufacturing cost being at least 20%.

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“…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. Temperature gradients occur due to cooling conditions and thermal resistances inand outside the cell and need to be validated.…”

Section: Introductionmentioning

confidence: 99%

“…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%

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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Test Method for Thermal Characterization of Li-Ion Cells and Verification of Cooling Concepts

Cited by 29 publications

References 16 publications

Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

Review of Parameter Determination for Thermal Modeling of Lithium Ion Batteries

Further Cost Reduction of Battery Manufacturing

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

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