Multi-objective optimization of a liquid cooled battery module with collaborative heat dissipation in both axial and radial directions. (July 2020)

• Record Type: Journal Article
• Authors: Zhu, Zehua; Wu, Xiaoyu; Zhang, Hengyun; Guo, Yun; Wu, Guoping
• Is Part Of: International journal of heat and mass transfer. Volume 155(2020)
• Publication Date: 2020-07
• Subjects: Collaborative heat dissipation -- Multi-objective optimization -- Sensitivity analysis -- Heat spreader plate -- Thermal column -- Liquid cooling; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2020.119701
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: Tmax for the present battery module with conjugated structure is about 13 °C lower than the conventional design. Single-factor analysis and sensitivity analysis are conducted to identify the effects of influence parameters. Sensitivity analysis shows that thermal column diameter has the highest impact on optimization objectives. Multi-objective optimization is conducted in two steps to obtain lower ΔT while minimizing Tmax and pressure drop. The optimal configuration could operate under lower flow rate with reduced pressure drop within the design requirements. Abstract: In this paper, numerical investigation and multi-objective optimization of a liquid cooled battery module with collaborative heat dissipation in both axial and radial directions are presented. In the battery module, 11×10 cylindrical batteries are arranged in square array on the cold plate, allowing axially downward heat dissipation. Besides, the upper parts of the batteries are connected radially with a common heat spreader plate, which is then connected to the bottom cold plate through thermal columns adjacent to the batteries, forming the thermal path in radial direction. Comparing with the conventional design configuration without heat dissipation structure, the maximum temperature of the present configuration (Baseline) is reduced by 42.10%, whereas the temperature difference is unfavorably increased by about 11.37%. Single-factor analysis is first conducted to identify the major influence variables. Then, the multi-objective optimizations are conducted in two steps to optimize the structure by minimizing the optimization objectives such as the maximum temperature, temperature difference and the pressure drop. After Step 2 optimization, the temperature difference of the battery module is reduced to 4.28 °C, providing good fitting agreement with the numerical simulation within 1.52%. The numerical simulations are also compared with the experiment and the discrepancy in battery is about 0.94 °C, which authenticates the present numerical model. Graphical abstract: Image, graphical abstract