Multi-objective optimization of a mini channeled cold plate for using thermal management of a Li-Ion battery

KALKAN O., CELEN A., BAKIRCI K.

ENERGY, cilt.251, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 251
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.energy.2022.123949
  • Dergi Adı: ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Computer & Applied Sciences, Environment Index, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Anahtar Kelimeler: Battery thermal management, Optimization, Mini channel, Li-ion battery, Cold plate, SYSTEMS
  • Atatürk Üniversitesi Adresli: Evet

Özet

Mini channeled cold plates (MCCP) are an impressive choice for electric vehicles with a liquid-based thermal management system to keep the battery temperature within the desired range and to achieve a homogeneous temperature distribution. This paper came up with an optimum solution for maximum battery temperature (MBT), maximum temperature difference on the battery surface (MTD) and pressure drops in the channels (DP), which are vital parameters. Multi-objective optimization of geometric pa-rameters and coolant flow rate of a designed MCCP which is experimentally investigated is carried out using the Desirability Function Approach. Firstly, the design of experiments (DoE) is generated using response surface method after determining the input variables and their levels. Then, each sample of DoE are modeled and analyzed numerically. Furthermore, the regression equations of the objective functions (MBT, MTD and DP) depending on the design parameters are developed and their variance analyzes are performed. Prediction accuracies of model equations developed for MBT, MTD and DP are 97.75%, 95.49% and 97.15%, respectively. As a result, optimum values of design variables, namely channel width (mm), distance between branches (mm), channel depth (mm), number of crossovers in branches and coolant flow rate (l/min) are 5, 5, 10, 13 and 0.7061, respectively.(c) 2022 Published by Elsevier Ltd.