Fast Charging Batteries via Electrochemical Model-based Control

通过基于电化学模型的控制对电池进行快速充电

• 批准号: 1408107
• 负责人: Scott Moura
• 金额: $ 29.47万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1408107&HistoricalAwards=false
• 关键词: Fast; Charging; Batteries; via; Electrochemical

Title: Fast Charging Batteries via ElectroChemical Model-Based Control In telecommunications, there were 5.2B active mobile handsets and over 1.7B mobile phone sales worldwide for 2012. Mobile phones are also a powerful tool for solving poverty and financial inequity in third world countries. In electrified transportation, there were 53,000 were plug-in electric vehicles sold in the U.S. for 2012. Despite growing sales, range anxiety is considered the largest inhibitor of electrified transportation. Significant reduction in charge times, e.g. comparable to filling a gas tank, would eliminate this obstacle and consequently reduce emissions and oil dependence. It is clear that fast charging increases the practicality of mobile devices and electric vehicles. However, it can also decrease cycle life depending on the charging method used. Traditionally, batteries are charged via a constant current/constant voltage (CCCV) protocol. A typical mobile phone requires 47 minutes to charge from 0-50%. However, it is well-known within the academic and industrial communities that alternative protocols can reduce charge times. Such alternatives, however, are almost always heuristic, without any provably optimal properties or safe constraint satisfaction guarantees. This research project pursues a drastically different and potentially transformative approach. This research seeks to significantly reduce Li-ion battery charge times by developing control theoretic foundations for electrochemical model-based control. Mathematically, this is formulated as minimizing charge time subject to constraints on estimated electro-chemical variables associated with aging. This approach is termed Electro-chemical model-based Control (ECC). The development of this control strategy will provide a major breakthrough in the way batteries are operated, safely at their electrochemical limits. The PI is currently establishing collaborations to impact both sectors with this research. Collaborations with electrochemists in the BATT group at Lawrence Berkeley National Lab are also being pursued. At UC Berkeley, the PI has created a new course entitled Energy Systems and Control. This course studies energy systems in transportation and energy infrastructures as motivation for systems and control theory. Results from this research will directly influence course material. Finally, the PI has historically recruited students of underrepresented populations to facilitate higher educational access. The PI plans to coordinate with the UC Berkeley Center for STEM Innovation, Leadership, and Diversity to recruit undergraduate researchers.Ultimately, this research seeks to achieve a 10 minute 0-20% charge time and 25 minute 0-50% charge time over 500 charge/discharge cycles. The project is organized into three integrated research tasks. (i) First, it will analyze parameter sensitivity and develop a fast charging-oriented reduced model for estimator design. (ii) Second, it will derive provably stable state estimators and optimal fast charging algorithms. These designs will advance PDE estimation and reference governor theory, respectively, while translating these theories to battery systems. (iii) Finally, it will quantify the performance of an ECC approach vis-à-vis traditional CCCV protocols on a battery-in-the-loop experimental facility. This project is among the first to focus on control-theoretic methods for optimizing battery charge times via electro-chemical models. Mathematically, these models are multi-state coupled nonlinear partial differential equations (PDEs). Due to the model complexity, several fundamental tools in systems and control theory will be developed in the context of batteries. (i) The first is a systematic procedure for assessing parameter sensitivity in multi-state PDE models. (ii) The second is fast charging-relevant model reduction techniques for achieving observability. (iii) The third is advancements to state estimation theory for PDE-ODE models. (iv)The fourth is advancements to reference governor theory for PDE-ODE models. (v) The last is an experimental quantification of ECC fast charging performance versus traditional protocols.

职务名称：通过基于电化学模型的控制实现电池快速充电2012年，全球共有52亿部活跃的移动的手机和超过17亿部移动的手机销量。移动的电话也是解决第三世界国家贫困和金融不平等的有力工具。在电气化运输方面，2012年美国销售了53，000辆插电式电动汽车。尽管销售额不断增长，但里程焦虑被认为是电动交通的最大抑制因素。充注时间的显著减少（例如，与充注油箱相当）将消除这一障碍，从而减少排放和对石油的依赖。显然，快速充电提高了移动的设备和电动汽车的实用性。然而，它也会降低循环寿命，这取决于所使用的充电方法。传统上，电池通过恒流/恒压（CCCV）协议充电。一部典型的移动的手机需要47分钟才能从0充电到50%。然而，在学术界和工业界众所周知，替代方案可以减少充电时间。然而，这样的替代方案几乎总是启发式的，没有任何可证明的最优属性或安全的约束满足保证。这个研究项目追求一种完全不同的、具有潜在变革性的方法。本研究旨在通过开发基于电化学模型的控制的控制理论基础，显着减少锂离子电池充电时间。在数学上，这是制定为最小化充电时间受到与老化相关的估计电化学变量的约束。这种方法被称为基于电化学模型的控制（ECC）。这种控制策略的开发将为电池在其电化学极限下安全运行的方式提供重大突破。PI目前正在建立合作关系，以通过这项研究影响这两个部门。与劳伦斯伯克利国家实验室BATT小组的电化学家的合作也在进行中。在加州大学伯克利分校，PI创建了一个名为能源系统和控制的新课程。本课程研究交通和能源基础设施中的能源系统，作为系统和控制理论的动力。这项研究的结果将直接影响课程材料。最后，PI历来招收代表性不足的学生，以促进接受高等教育。PI计划与加州大学伯克利分校STEM创新，领导力和多样性中心合作招募本科研究人员。最终，这项研究旨在实现500次充电/放电循环的10分钟0-20%充电时间和25分钟0-50%充电时间。该项目分为三个综合研究任务。(i)首先，它将分析参数的敏感性，并开发一个面向快速充电的简化模型的估计器设计。(ii)其次，它将推导出可证明稳定的状态估计和最佳快速充电算法。这些设计将分别推进PDE估计和参考调速器理论，同时将这些理论转化为电池系统。(iii)最后，它将量化ECC方法维斯传统CCCV协议在电池在环实验设施上的性能。该项目是第一个专注于通过电化学模型优化电池充电时间的控制理论方法。数学上，这些模型是多状态耦合的非线性偏微分方程（PDE）。由于模型的复杂性，系统和控制理论中的几个基本工具将在电池的背景下开发。 (i)第一个是一个系统的程序，用于评估参数的敏感性，在多状态偏微分方程模型。(ii)第二个是快速充电相关的模型简化技术，实现可观测性。(iii)三是对PDE-ODE模型状态估计理论的改进。（iv）四是改进了PDE-ODE模型的参考调速器理论。(v)最后是ECC快速充电性能与传统协议的实验量化。