Effects analysis on energy density optimization and thermal efficiency enhancement of the air-cooled Li-ion battery modules

摘要

In this study, a fractional-order electro-thermal model of an NMC/C 43Ah battery is initially built, that can accurately derive the cell's terminal voltage and surface temperature at various loadings (1C, 1.5C, 2C) and ambient conditions (10 degrees C, 25 degrees C, 45 degrees C), and with an average heat dissipation of 15 W being measured at a 2C discharge rate and 25 degrees C. To meet an electric vehicle's demands, a 12S1P air-cooled modular topology with the 43Ah cell is further proposed. For evaluating and optimizing its battery thermal management (BTMS) efficiency and volume, a multi-objective algorithm is linked to a multiphysics 3D model. The proposed design optimization framework can converge towards the global optimal parameters (cell-to-cell interspace, inlet/outlet orientations and length, and among nine U-and Z-type solutions) to achieve the best thermal and volumetric performances. To do so, the BTMS is geometrically redefined at each optimization step according to the algorithm's optimal decisions, and it calculates the new costs based on finite element method. Eventually, the suggested process evaluates over 250 BTMSs with different designs at a 2C-rate and 25 degrees C, where significant variations on their performances are observed. Up to 9 degrees C on the maximum temperature rise and more than twice required volume to be needed for the same thermal efficiency of the various BTMSs, are recorded. As a result, the presented framework is proven capable of enhancing the cooling efficiency and reducing the BTMS's volume at the same time. Indicatively, a 15, 70 and 40, improvement on the maximum temperature, cell uniformity and cell-level heat distribution, is achieved respectively on the optimal-derived BTMS, offering simultaneously a 5 volume reduction compared to its baseline design. Lastly, the proposed methodology's robustness is verified with a numerical investigation on the optimal BTMS performance, by rearranging certain fluid and electrical controlled variables.