Multi-objective optimization design of thermal management system for lithium-ion battery pack based on Non-dominated Sorting Genetic Algorithm II

• Published in: Applied thermal engineering Vol. 164; p. 114394
• Main Authors: Deng, Tao, Ran, Yan, Yin, Yanli, Liu, Ping
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 05.01.2020; Elsevier BV
• Subjects: Batteries; Battery thermal management system (BTMS); Bifurcations; Classification; Coefficient of friction; Computer simulation; Computing time; Convective heat transfer; Cooling systems; Design optimization; Genetic algorithms; Heat conductivity; Heat transfer; Heat transfer coefficients; Hypercubes; Latin hypercube sampling; Liquid cooling; Lithium-ion batteries; Lithium-ion battery pack; Low flow; Multi-objective optimization; Multiple objective analysis; Non-dominated Sorting Genetic Algorithm II (NSGA-II); Optimization; Rechargeable batteries; Response surface approximation (RSA); Response surface methodology; Skin friction; Sorting algorithms; Temperature gradients; Thermal management; Lithium-ion battery pack; Non-dominated Sorting Genetic Algorithm II (NSGA-II); Battery thermal management system (BTMS); Multi-objective optimization; Response surface approximation (RSA)
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2019.114394

•A novel liquid cooling system is proposed for lithium-ion battery pack.•Multi-objective optimization of the cooling system is performed based on NSGA-II.•Small hydraulic diameter enhances heat transfer coefficient at large friction factor.•The cooling system achieves the desired thermal performance at a small pressure drop. The thermal management of batteries was a significant issue considering the safety and efficiency. Optimal design of a novel liquid cooling system with symmetrical double-layer reverting bifurcation channel was performed by combining experimental, numerical simulation and multi-objective optimization techniques. The thermophysical parameters and heat production rate of the battery for numerical simulation were obtained by experiments. The convective heat transfer coefficient and the surface friction coefficient were chosen as objective functions to visually reflect the heat transfer process. Furthermore, batteries were confined to work at the optimal temperature (25–40 °C) and the optimal temperature difference between cells (less than 5 °C). The performance values of design points obtained by Latin hypercube sampling were calculated numerically. Response surface approximation was adopted to approximate the objective function and the constraint function to reduce computing time. The Pareto-optimal front between −h and f was obtained using Non-dominated Sorting Genetic Algorithm II. 17.19% change in heat transfer coefficient was accomplished by 85.53% change in skin friction coefficient. The results reported that the cooling system with optimized thermal performance can be obtained at low flow loss.