Multiscale Modeling and Control of Thin Film Solar Cell Manufacturing for Improved Light Trapping and Solar Power Conversion

薄膜太阳能电池制造的多尺度建模和控制，以改善光捕获和太阳能转换

• 批准号: 1262812
• 负责人: Panagiotis Christofides
• 金额: $ 22.17万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1262812&HistoricalAwards=false
• 关键词: Multiscale; Modeling; Control; Thin; Film

ABSTRACTPI: Christofides, PanagiotisInstitutions: UCLAProposal Number: 1262812Title: Multiscale Modeling and Control of Thin Film Solar Cell Manufacturing for Improved Light Trapping and Solar Power ConversionPhotovoltaic (solar) cells are an important source of sustainable energy. Currently, their limited conversion efficiency limits their wide applicability. Thin-film silicon solar cells are the most developed and widely used solar cells. Research on optical and electrical modeling of thin-film silicon solar cells indicates that the scattering properties of the thin film surfaces/interfaces are directly related to their light trapping processes and thus their conversion efficiency. The scattering properties of the interfaces are influenced by the surface morphology, in particular, the root-mean-square (RMS) roughness and RMS slope. The aim here is to improve the efficiency of thin-film solar cells by controlling the manufacturing process via simultaneous regulation of the thin film surface RMS slope and roughness at spatial length scales corresponding to the visible light wavelength range. Computational multiscale modeling and real-time model-based control of the thin film solar cell manufacturing process to optimize light trapping and overall conversion has the potential to lead to transformative advances in solar cell technology.Intellectual Merit The objective of the proposed research is to develop a systematic and computationally tractable multiscale modeling and control framework for real-time control of thin film solar cell manufacturing which leads to thin film surface morphology that optimizes light trapping and overall conversion of solar power. This project will devise methods for the construction of reduced-order stochastic modeling approximations of the multiscale models of such systems, which are suitable for controller design and real-time implementation. These should predict the effect of controllable process variables on key film surface morphology parameters. On the basis of these reduced-order stochastic models, nonlinear and predictive control theory will be developed and used to produce practically-implementable feedback control systems that lead to the desired stability, performance (i.e., surface RMS slope and roughness values that lead to optimal light trapping thin film properties) and robustness properties in the closed-loop system. In addition, the design of monitoring systems for assessing actuator/sensor/controller abnormal behavior and controller reconfiguration strategies for dealing with abnormal events, as well as applications to thin film growth processes using multiscale models and realistic thin film light trapping specifications, will be pursued.Broader Impact Such real-time control of the thin film solar cell manufacturing process has the potential to lead to transformative advances in producing thin film solar cells with optimal solar power conversion efficiencies. The development of user-friendly software, short courses and workshops, the incorporation of research results into the curriculum and the writing of a new book on "Dynamics and Control of Thin Film Morphology: Surface Roughness, Slope and Porosity," are also within the project objectives. The education of high-quality doctoral students who take on leading positions in industry and the on-going interaction of the PIs with industry will be the means for transferring the results of this research into the industrial sector. The involvement of a diverse group of undergraduate and graduate students in the research through participation in the Center for Engineering Education and Diversity (CEED) at UCLA and outreach to the California State Polytechnic University in Pomona by offering summer internships to highly-qualified students will also be pursued.

摘要PI：Christofides，Panagiotis 机构：加州大学洛杉矶分校提案编号：1262812 标题：薄膜太阳能电池制造的多尺度建模和控制，以改善光捕获和太阳能转换光伏（太阳能）电池是可持续能源的重要来源。目前，它们有限的转换效率限制了它们的广泛应用。薄膜硅太阳能电池是发展最快、应用最广泛的太阳能电池。对薄膜硅太阳能电池的光学和电学建模的研究表明，薄膜表面/界面的散射特性与其光捕获过程及其转换效率直接相关。 界面的散射特性受到表面形态的影响，特别是均方根（RMS）粗糙度和RMS斜率。这里的目的是通过在与可见光波长范围相对应的空间长度尺度上同时调节薄膜表面RMS斜率和粗糙度来控制制造过程，从而提高薄膜太阳能电池的效率。对薄膜太阳能电池制造过程进行计算多尺度建模和基于实时模型的控制，以优化光捕获和整体转换，有可能带来太阳能电池技术的变革性进步。 智力优势 本项研究的目标是开发一种系统且可计算处理的多尺度建模和控制框架，用于实时控制薄膜太阳能电池制造，从而产生优化光捕获和太阳能整体转换的薄膜表面形态。该项目将设计用于构建此类系统多尺度模型的降阶随机建模近似的方法，该方法适用于控制器设计和实时实现。 这些应该可以预测可控工艺变量对关键薄膜表面形貌参数的影响。在这些降阶随机模型的基础上，将开发非线性和预测控制理论，并用于产生可实际实施的反馈控制系统，从而实现所需的稳定性、性能（即，表面均方根斜率和粗糙度值，从而实现最佳光捕获薄膜特性）和闭环系统的鲁棒性特性。此外，还将致力于设计用于评估执行器/传感器/控制器异常行为的监测系统和用于处理异常事件的控制器重新配置策略，以及使用多尺度模型和现实薄膜光捕获规范在薄膜生长过程中的应用。更广泛的影响 这种对薄膜太阳能电池制造过程的实时控制有可能在生产具有最佳太阳能转换效率的薄膜太阳能电池方面带来革命性的进步。开发用户友好的软件、短期课程和研讨会、将研究成果纳入课程以及撰写一本关于“薄膜形态动力学和控制：表面粗糙度、斜率和孔隙率”的新书也在该项目的范围内。项目目标。培养在行业中处于领先地位的高素质博士生以及PI与行业的持续互动将是这项研究成果向工业部门转化的手段。通过参与加州大学洛杉矶分校工程教育和多样性中心 (CEED)，以及通过向高素质学生提供暑期实习机会，向位于波莫纳的加州州立理工大学进行推广，也将让不同的本科生和研究生群体参与研究。被追击。