Affiliations 

  • 1 Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical & Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
  • 2 Department of Mechanical Engineering, P. A. College of Engineering (Affiliated To Visvesvaraya Technological University, Belagavi), Mangalore, 574153 India
  • 3 Department of Mechanical Engineering, Glocal University, Delhi-Yamunotri Marg, SH-57, Mirzapur Pole, Saharanpur District, Uttar Pradesh 247121 India
  • 4 Department of Mechanical Engineering, Mirpur University of Science and Technology (MUST), Mirpur, 10250 (AJK) Pakistan
  • 5 Center for Energy Science, Department of Mechanical Engineering, University of Malaya, Kuala Lumpur, 50603 Malaysia
  • 6 Department of Mechanical Engineering, Lovely Professional University, Phagwara, Punjab 144411 India
  • 7 School of Chemical Engineering, The University of Queensland, Brisbane, QLD 4072 Australia
  • 8 Düzce University, Mechanical Engineering Department, Faculty of Engineering, Düzce, 81620 Turkey
  • 9 Department of Mechanical Engineering, College of Engineering, King Khalid University, PO Box 394, Abha, 61421 Saudi Arabia
PMID: 33935484 DOI: 10.1007/s11831-021-09571-0

Abstract

Covid-19 has given one positive perspective to look at our planet earth in terms of reducing the air and noise pollution thus improving the environmental conditions globally. This positive outcome of pandemic has given the indication that the future of energy belong to green energy and one of the emerging source of green energy is Lithium-ion batteries (LIBs). LIBs are the backbone of the electric vehicles but there are some major issues faced by the them like poor thermal performance, thermal runaway, fire hazards and faster rate of discharge under low and high temperature environment,. Therefore to overcome these problems most of the researchers have come up with new methods of controlling and maintaining the overall thermal performance of the LIBs. The present review paper mainly is focused on optimization of thermal and structural design parameters of the LIBs under different BTMSs. The optimized BTMS generally demonstrated in this paper are maximum temperature of battery cell, battery pack or battery module, temperature uniformity, maximum or average temperature difference, inlet temperature of coolant, flow velocity, and pressure drop. Whereas the major structural design optimization parameters highlighted in this paper are type of flow channel, number of channels, length of channel, diameter of channel, cell to cell spacing, inlet and outlet plenum angle and arrangement of channels. These optimized parameters investigated under different BTMS heads such as air, PCM (phase change material), mini-channel, heat pipe, and water cooling are reported profoundly in this review article. The data are categorized and the results of the recent studies are summarized for each method. Critical review on use of various optimization algorithms (like ant colony, genetic, particle swarm, response surface, NSGA-II, etc.) for design parameter optimization are presented and categorized for different BTMS to boost their objectives. The single objective optimization techniques helps in obtaining the optimal value of important design parameters related to the thermal performance of battery cooling systems. Finally, multi-objective optimization technique is also discussed to get an idea of how to get the trade-off between the various conflicting parameters of interest such as energy, cost, pressure drop, size, arrangement, etc. which is related to minimization and thermal efficiency/performance of the battery system related to maximization. This review will be very helpful for researchers working with an objective of improving the thermal performance and life span of the LIBs.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.