直接甲醇燃料电池关键参数多层协同建模与优化设计理论研究

项目名称： 直接甲醇燃料电池关键参数多层协同建模与优化设计理论研究

项目编号： No.51505136

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 杨钦文

作者单位： 湖南大学

项目金额： 21万元

中文摘要： 直接甲醇燃料电池（DMFC）具有原料成本低、排放少和噪声小等优点，是目前最具潜质的便携设备电源之一。然而，当前不考虑非同类参数间交互作用的相对独立设计处理方式是当前DMFC系统设计效率相对低下、能量转化性能难于突破性提升的主要原因。本项目面向DMFC系统运行参数和阴、阳极板各自几何参数等非同类参数对电池能量转化性能的优化设计，提出基于数值模拟与自适应元模型的多层协同元模型建模理论，构建包含关键参数的DMFC能量转化性能分析模型。并基于该模型研究多层协同优化设计方法，以指导优化设计。本项目将开发并利用多参数可调式试验系统对所研究理论进行试验验证。本研究的开展对于解决当前DMFC系统综合特性的分析具有理论支撑作用，所构建多层协同优化设计方法为提升DMFC能量转化性能提供支持。该项目研究对于突破借助经验的试验测试模式，改进传统研发机制，提升DMFC开发效率，降低开发成本具有积极意义。

中文关键词： 直接甲醇燃料电池；多层协同；建模；优化设计

英文摘要： Direct Methanol Fuel Cells (DMFCs) possess quite beneficial characteristics, such as low cost, low emission, and low noise, thus being popularly considered as one of the most promising portable power sources. However, ordinary optimal design without considering the coupling relationship between different types of key parameters make the rate of energy conversion of the DMFC hardly be high and the design efficiency is relatively low. This project focuses on different types of DMFC geometric parameters and the operation parameters, to propose an adaptive sampling-based multi-level collaborative metamodeling theory on the basis of numerical simulation and adaptive metamodeling. The project is going to build the multi-parameter involved energy conversion performance analysis model, then develop the multi-level collaborate optimal design method to guide the optimal design of DMFC system. This project will use experiments based on multi-level parameter adjustable DMFC system to carry out the theory validation. The theoretical research in this project will support the integrated characteristics analysis of the DMFC system, while the collaborative optimization design method will serve the energy conversion rate-oriented DMFC performance optimization. This research will significantly improve the R&D efficiency, stepping out the experience-based test to modify development mode, reduce the cost of R&D and usage.

英文关键词： DMFC;Multi-level Collaborative;Modeling;Optimal design