Pack Level Design Optimization for Electric Vehicle Thermal Management Systems Minimizing Standard Deviation of Temperature Distribution
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Green technologies have recently gained interest for many reasons. Economic factors in conjunction with an increased social desire to reduce our environmental impact on the Earth have created a desire for more environmentally friendly technologies, especially automotive technologies such as the electric car. While public interest in electric vehicles is growing, there are a number of challenges which must first be addressed before their widespread adoption is possible. Cost, longevity, and range are all important factors which need to be addressed for electric vehicles to compete directly with their gasoline counterparts. By more efficiently using the energy stored within the battery pack, some of these issues can be addressed. This study focuses on the thermal management systems for electric vehicles and the application of design optimization in the early design phase considering the pack in its entirety. A liquid cooling system is considered for a current generation electric vehicle, with time dependent heat generation rates within the battery cells based on vehicle operating conditions. Identifying the most efficient distribution of cooling within the battery pack to achieve uniform temperature is the objective of optimization. Simulations were performed on a complete battery pack model, featuring 288 battery cells and 144 cooling plates. Anisotropic material properties and non-uniform heat generation rates are included as well as energy demands based on a representative vehicle drive cycle. Results have shown that through design optimization, the standard deviation of temperature within the battery cells can be improved by as much as 80% when compared to a conventional design. The standard deviation of temperature saw improvement from an average of 0.2828 K for a conventional design to 0.05318 K after optimization. These results are specific to the given battery pack construction, battery cell, and cooling type. The method of modeling and analysis can be extended to many battery geometries and cooling technologies in the future. Application of design optimization to the problem of thermal iii management system design can yield significant improvements to battery pack thermal management, and thereby incrementally improve the efficiency of electrified vehicles.