Development and Analysis of a New Cylindrical Lithium-Ion Battery Thermal Management System

With the development of modern technology and economy,environmental protection and sustainable development have become the focus of global attention.The promotion and development of electric vehicles(EVs)have bright prospects.However,many challenges need to be faced seriously.Under diferent operating conditions,various safety problems of electric vehicles emerge one after another,especially the hidden danger of battery overheating which threatens the performance of electric vehicles.This paper aims to design and optimize a new indirect liquid cooling system for cylindrical lithium-ion batteries.Various design schemes for diferent cooling channel structures and cooling liquid inlet directions are proposed,and the corresponding solid-fuid coupling model is established.COMSOL Multiphysics simulation software is adopted to simulate and analyze the cooling systems.An approximate model is constructed using the Kriging method,which is considered to optimize the battery cooling system and improve the optimization results.Sensitivity parameter analysis and the optimization design of system structure are performed through a set of infuencing factors in the battery thermal management.The results indicate that the method used in this paper can efectively reduce the maximum core temperature and balance the temperature diferences of the battery pack.Compared with the original design,the optimized design,which is based on the non-dominated sorting genetic algorithm(NSGA-II),has an excellent ability in the optimized thermal management system to dissipate thermal energy and keep the overall cooling uniformity of the battery and thermal management system.Furthermore,the optimized system can also prevent thermal runaway propagation under thermal abuse conditions.In summary,this research can provide some practical suggestions and ideas for the engineering and production applications and structural optimization design carried by electric vehicles.

EFFICIENT METHOD FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION BY CONSIDERING UNCERTAINTY

A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. The Kriging approximate model with updating is introduced to reduce the computational cost of MDF caused by the complex structure. The computational efficiency is remarkably improved as the lack of iterative process during reliability analysis. Special attention is paid to a turbine blade design optimization by adopting the proposed method. Results show that the method is much more efficient than the commonly used double-loop based RBMDO method. It is feasible and efficient to apply the method to the engineering design.