Ai-driven bioinspired cooling plate design for enhanced lithium-ion battery thermal management: integrating topology optimization and deep learning

Liquid cooling plates are pivotal in lithium-ion battery thermal management systems (BTMS), yet traditional designs struggle to balance thermal uniformity, pressure drop, and structural efficiency. This paper harnesses artificial intelligence (AI) to propose new cooling plate design through a synergistic integration of bioinspired topology optimization (TO) and deep learning. We propose a herringbone-inspired cooling plate optimized via a variational autoencoder (VAE)-based TO framework, which accelerates generative design while enhancing thermal performance. Firstly, this work explored the potential of improving the performance of cooling plates by evaluating three different designs: topology optimized herringbone single outlet design, traditional topology optimized single outlet design and traditional straight through design. All processes are carried out under the same boundary conditions, and the performance comparison comes from a comprehensive three-dimensional computational fluid dynamics (CFD) analysis. This study further investigated the influence of fluid inlet conditions (including velocity and temperature) on thermal and fluid behavior. In addition, the advanced machine learning approach, variable autoencoder (VAE) was incorporated into the optimization framework to explore the generative design capability. The results shows that the herringbone single outlet design is superior to other structures. When the Reynolds number is 231.52, compared with the single outlet topology optimization and the straight channel design, the maximum temperature is reduced by 1.02 k and 0.305 k, the average temperature is reduced by 0.403 k and 0.666 k, and the pressure drop is reduced by 20.43% and 45.41% respectively. In addition, the VAE generated cooling plate shows a more uniform temperature distribution than the traditional design, highlighting the potential of deep learning in developing heat balance and efficient cooling solutions.