Bridging Models at Different Scales To Design New Generation Fuel Cells for Electrified Mobility (BLESSED)

桥接不同规模的模型来设计新一代电动汽车燃料电池 (BLESSED)

• 批准号: EP/X032264/1
• 负责人: Rune Lindstedt
• 金额: $ 50.7万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX032264%2F1
• 关键词: Bridging; Models; Different; Scales; Design

To achieve the goals of the European Green Deal on climate neutrality, a 90% reduction in transport emissions is needed by 2050. The automotive industry urgently needs to accelerate the introduction of alternative powertrains for electrified vehicles. Hydrogenpowered Proton Exchange Membrane Fuel Cells (PEMFCs) are carbon-free power devices that meet these goals in both mobile and stationary applications. BLESSED aims at revolutionising the design process of next generation PEMFCs, to improve efficiency, durability and affordability for widespread use, with direct implications in clean energy and sustainable industry/mobility. BLESSED will train 15 Doctoral Candidates (DCs) to solve Multi-Scale (MS) engineering challenges, from the electrons up to the device level, through a unique combination of multi-disciplinary computational methods with Machine Learning (ML) to bridge each length scale's highly accurate model to adjacent scales. Then, a top-down length scale approach will be followed to optimise PEMFC and its components. To this end, the 15 DCs will synergistically develop a unique MS computational framework for the all-scale PEMFC analysis/design, assisted by ML tools. This will allow the simultaneous consideration of complex physico-chemical phenomena occurring at all length scales, such as catalytically-assisted chemical reactions, contact of rough surfaces, mechanical/chemicaldegradation of membranes, fluid flows in porous media etc., at affordable computational cost. The proposed ID-network brings together world-class academic expertise on numerical modelling and simulation in electrochemistry, reacting flows, fluid mechanics, materials, optimisation methods and ML, with industrial developers. With a strong focus on industrial applications, BLESSED will develop methodologies and tools to exceed state-of-the-art in PEMFCs by minimising the Platinum group metal content and corrosion while maximising mass transport and electrical conductivity.

为了实现欧洲绿色协议关于气候中立的目标，到2050年需要减少90%的交通排放。汽车行业迫切需要加快为电动汽车引入替代动力系统。氢动力质子交换膜燃料电池（PEMFC）是无碳动力装置，满足这些目标在移动的和固定的应用。BLESSED旨在彻底改变下一代PEMFC的设计过程，以提高效率，耐用性和广泛使用的可负担性，直接影响清洁能源和可持续工业/移动性。BLESSED将培训15名博士候选人（DC），以解决多尺度（MS）工程挑战，从电子到器件级，通过多学科计算方法与机器学习（ML）的独特组合，将每个长度尺度的高精度模型与相邻尺度连接起来。然后，将遵循自上而下的长度尺度方法来优化PEMFC及其组件。为此，15个DC将协同开发一个独特的MS计算框架，用于所有规模的PEMFC分析/设计，并辅以ML工具。这将允许同时考虑在所有长度尺度上发生的复杂物理化学现象，例如催化辅助化学反应、粗糙表面的接触、膜的机械/化学降解、多孔介质中的流体流动等，以可承受的计算成本。拟议的ID网络将电化学、反应流、流体力学、材料、优化方法和ML的数值建模和模拟方面的世界级学术专业知识与工业开发人员汇集在一起。BLESSED专注于工业应用，将开发方法和工具，通过最大限度地减少铂族金属含量和腐蚀，同时最大限度地提高质量传输和电导率，超越PEMFC的最新技术水平。