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Safe and lightweight battery enclosure design for zero-emission vehicles

Project description

Driving the green transition with smarter battery designs

Battery efficiency is a critical challenge on the road to electric vehicles because current systems are often heavy and costly, relying on fragmented design methodologies that separate structural integrity from thermal management. Supported by the Marie Sklodowska-Curie Actions programme, the SALVE project aims to develop a 3D multiphysics topology optimisation framework using advanced machine learning and high-performance computing. It will optimise enclosures for mechanical strength and heat dissipation. This approach incorporates multi-material solutions and practical manufacturing constraints to ensure industrial viability. The project’s goal of a 10 % weight reduction and 3 % safety enhancement accelerates the adoption of sustainable transport. These breakthroughs support a more energy-efficient and competitive electric vehicle market.

Objective

The SALVE project aims to develop a Safe and Lightweight Battery Enclosure Design for Zero-Emission Vehicles (ZEVs) by addressing critical shortcomings in current design methodologies. Existing electric vehicle battery systems are heavy, costly, and require advanced thermal management for optimal performance and safety. Current design approaches often consider structural and thermal characteristics separately, lack multi-material integration and practical manufacturing constraints, and suffer from high computational costs.

SALVE proposes an innovative 3D thermo-structural multiphysics Topology Optimization (TO) framework. This methodology will concurrently optimize battery enclosures for mechanical integrity (stiffness, stress, vibration) and thermal performance (heat dissipation, uniform temperature distribution). It integrates multi-material formulation and manufacturing constraints to 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.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

CENTRE INTERNACIONAL DE METODES NUMERICS EN ENGINYERIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 209 914,56
Address
C GRAN CAPITAN, EDIFICI C1, CAMPUS NORD UPC SN
08034 Barcelona
Spain

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Region
Este Cataluña Barcelona
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Research Organisations
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Total cost

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