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Safe and lightweight battery enclosure design for zero-emission vehicles

CORDIS · observation · Publication date unknown

ensure the optimized designs are buildable and industrially viable. To overcome computational bottlenecks, SALVE will implement advanced acceleration strategies, combining Reduced Order Models (ROM), Machine Learning (ML) surrogates, and High-Performance Computing (HPC) on multi-core CPUs and GPUs, significantly reducing design iteration time for complex, large-scale models. Developed at the Centre International de Mètodes Numèrics en Enginyeria (CIMNE) using the in-house Julia-based Swan code, the methodology will undergo rigorous validation against commercial software and real-world scenarios. By achieving significant weight reduction (projected 10%) and enhanced safety (up to 3%), SALVE directly contributes to the EU's zero-emission targets, fostering sustainable transportation, improved energy efficiency, and increased EV market penetration. This interdisciplinary effort brings together expertise from engineering, computer science, applied mathematics, and materials science to drive innovation in EV component design. Computational mechanics, topology optimization, finite element

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recordType

award

status

SIGNED

region

EU

value

209914.56

unit

EUR