This conference paper was submitted for presentation at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

In today'™s competitive engineering landscape, organizations face immense pressure to deliver high-performing, energy-efficient products at an accelerated pace. This challenge is particularly prominent in the electric vehicle (EV) industry, where efficient battery thermal management systems are critical for both performance and longevity. Design teams must innovate rapidly, navigating complex trade-offs between performance and cost while simultaneously adhering to manufacturing constraints and stringent timelines. However, traditional design processes for battery cold plates often fall short, hindered by lengthy iteration cycles and limited automation. To address these challenges, engineering intelligence (EI) provides a transformative solution by combining generative design, real-time feedback, and historical data utilization to significantly reduce development times and enhance product quality. Neural Concept, in collaboration with MAHLE, has redefined this process by leveraging Neural Concept'™s advanced engineering intelligence platform. This workflow dramatically accelerates the design process, enabling swift response to evolving customer requirements (such as package or operating conditions) with optimized designs delivered in exceptionally short timeframes. Designers can now explore hundreds of potential configurations, identifying optimal trade-offs between performance and cost with a comprehensive 360° view of the design problem including live insights on manufacturing constraints, packaging, weight and performance. By integrating advanced automatic design optimization techniques, the solution ensures the designs reach the edge of achievable performance, clearing doubts and delivering designs that combine peak thermal efficiency and minimized pressure drop. In a case study with MAHLE, this workflow demonstrated remarkable outcomes. Despite MAHLE already utilizing a streamlined development tool chain to reduce friction between the design and the simulation tasks, the implementation of Neural Concept'™s new tool in a development project with a challenging timeline led to further improvements. It resulted in a 10% reduction in pressure drop without compromising thermal performance compared to a traditional design. In another design concept, Neural Concept'™s solution reduced the temperature delta in the battery pack by 10% while maintaining the same pressure drop as a conventional design. These outcomes highlight the transformative potential of Neural Concept'™s platform to enhance competitiveness in the EV industry, setting a new standard for battery cold plate design by eliminating inefficiencies and empowering teams with cutting-edge technology. This case study exemplifies how engineering intelligence empowers teams to overcome the limitations of conventional tools, enabling rapid iteration, improved performance, and enhanced competitiveness in the EV market. By fostering collaboration and integrating cutting-edge AI techniques, this partnership demonstrates the potential of next-generation workflows to redefine industry standards.