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.

题目：薄膜太阳能电池制造的多尺度建模和控制，以改进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，它们的转换效率有限，限制了它们的广泛应用。薄膜硅太阳能电池是目前最发达、应用最广泛的太阳能电池。薄膜硅太阳能电池的光学和电学建模研究表明，薄膜表面/界面的散射特性直接关系到它们的光捕获过程，从而影响它们的转换效率。界面的散射特性受表面形貌，特别是均方根粗糙度和均方根斜率的影响。本文的目的是通过同时调节与可见光波长范围相对应的空间长度尺度上的薄膜表面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。计算多尺度建模和基于实时模型的薄膜太阳能电池制造过程控制，以优化光捕获和整体转换，有可能导致太阳能电池技术的变革性进步。该研究的目标是开发一个系统的、计算上可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的制造，从而导致薄膜表面形态优化光捕获和太阳能的整体转换。本项目将设计适合于控制器设计和实时实现的此类系统多尺度模型的低阶随机建模近似的构建方法。这些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，非线性和预测控制理论将被开发并用于生产实际可实现的反馈控制系统，从而在闭环系统中获得所需的稳定性、性能（即，表面均方根斜率和粗糙度值可导致最佳的光捕获薄膜性能）和鲁棒性。此外，还将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构策略，以及使用多尺度模型和现实薄膜光捕获规格的薄膜生长过程的应用。这种对薄膜太阳能电池制造过程的实时控制有可能导致生产具有最佳太阳能转换效率的薄膜太阳能电池的变革性进步。开发用户友好的软件、短期课程和讲习班、将研究成果纳入课程以及编写一本关于“薄膜形态的动力学和控制：表面粗糙度、坡度和孔隙度”的新书，也在项目目标之内。培养在工业领域处于领先地位的高质量博士生，以及pi与工业的持续互动，将是将这项研究成果转移到工业部门的手段。通过参与加州大学洛杉矶分校的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，与波莫纳的加州州立理工大学（California State Polytechnic University）联系，让不同群体的本科生和研究生参与研究。