Browsing by Subject "Battery thermal management system"

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    A review on soft computing and nanofluid applications for battery thermal management
    (Elsevier Ltd, 2022) Can A.; Selimefendigil F.; Öztop H.F.
    This study is about applications of nanofluids and various soft computing algorithms on designs of battery thermal management systems and their potential performance enhancement in cooling. Brief information on Li-ion batteries, energy storage process and cooling techniques such as passive, active and hybrid cooling techniques are presented. Basic knowledge on nanofluids and soft computing methods are explained to deep understanding the following chapters. Potential of using nanofluids on thermal management of battery packs and effect on their life cycles and performance improvements are discussed. Application of the most common soft computing methods in battery thermal management systems is presented. Li-ion batteries are a promising solution to energy storage issue with appropriate thermal management designs such as presented in this review. When different active and hybrid cooling battery thermal management systems are operated with nanofluids, their performances are increased. Different machine learning methods have been successfully used in battery thermal management systems and outputs from the modeling have been considered for further performance enhancement and optimization studies. Even though, they are excellent tools assisting in high fidelity simulations or expensive experimental testing of systems, deep learning and other advanced machine learning methods may be considered for future studies. Exergetic performance analysis of nano enhanced thermal management along with the cost of using nanofluids is needed as the extension of the current studies. © 2022 Elsevier Ltd
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    THERMAL MANAGEMENT OF LITHIUM-ION BATTERY PACKS BY USING CORRUGATED CHANNELS WITH NANO-ENHANCED COOLING
    (Begell House Inc., 2024) Selimefendigil F.; Can A.; Öztop H.F.
    In this study, a cooling system using corrugated cooling channels and Al2O3–Cu/water hybrid nanofluid is offered as the battery thermal management system (BTMS) for prismatic Li-ion batteries. A computational model built based on the finite element approach uses hybrid nanofluid at solid volume fractions ranging from 0 to 2% at various Reynolds numbers. The cold plates are corrugated and have a variety of square grooves positioned between prismatic Li-ion battery cells. The maximum temperature decreases as the volume fraction of solid nanoparticles and the number of corrugated cooling channels increases. When cases of using lowest and highest number of cooling channels are compared, maximum temperature reduction is found as 3.07 K when using water and 1.86 K when using Al2O3–Cu/ water hybrid nanofluid (at the largest solid volume fraction). The number of square grooves in the cooling channels does not have any significant impact on the temperature drop when using nanofluid at the highest solid volume fraction. © 2024 by Begell House, Inc.