Control of Reconfigurable Battery Energy Storage Systems

可重构电池储能系统的控制

• 批准号: 1763093
• 负责人: Huazhen Fang
• 金额: $ 29.52万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1763093&HistoricalAwards=false
• 关键词: Control; Reconfigurable; Battery; Energy; Storage

Rechargeable battery systems represent a key enabler for several technologies such as electrified transportation, smart grid, renewables, and green buildings. These systems are increasingly recognized as a driver for moving the world forward into a sustainable energy era. Despite their ever-growing presence, the performance and safety of these systems are fundamentally constrained by how the battery cells are connected inside. Typically, these cells are hardwired. As a result, there is no flexibility to overcome battery failures caused by defects in individual cells, whether created during manufacturing or through malfunction of a cell. This has led to greater interest in reconfigurable battery systems, which use rapid reconfigurable connections between cells to overcome these problems. While there is rapid growth of power electronics architecture and circuit design, the management algorithms to control these devices are not improving at the same pace. This project aims to develop a new control paradigm, through which the system's input control and connection topology adjustment are achieved concurrently. This research, if successful, will significantly improve the reconfigurable battery systems and accelerate their use across diverse sectors. The research-integrated education program will engage K-12, undergraduate, and graduate students through curriculum enhancement, community outreach, and research mentorship. The PI's collaboration with the industry through this project will lead to practical algorithms and tools. As battery systems are central to key devices and equipment used in all sectors this research will not only promote the progress of science in battery technology but help improve technologies used in national health, prosperity, and national defense. The scientific focus of this project is to develop a foundational mathematical framework for enabling simultaneous control and topology reconfiguration for reconfigurable battery systems from a network perspective and build a set of control algorithms that take the best advantage of reconfigurability. This research specifically includes: 1) creation of an algebraic graph-theoretic modeling methodology for reconfigurable battery systems, 2) synthesis of a predictive control framework that can optimize control input and reconfigure system-wide connections, and 3) application of the framework to key battery management tasks including optimal charging/discharging, thermal management and cell balancing. The models and algorithms will be subjected to principled evaluation through rigorous theoretical analysis, simulations and experiments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

可充电电池系统代表了电气化运输、智能电网、可再生能源和绿色建筑等多种技术的关键推动因素。这些系统越来越被认为是推动世界进入可持续能源时代的驱动力。尽管它们的存在不断增长，但这些系统的性能和安全性从根本上受到电池内部连接方式的限制。通常，这些细胞是硬连线的。因此，没有灵活性来克服由单个电池中的缺陷引起的电池故障，无论是在制造期间产生的还是通过电池故障产生的。这导致了对可重构电池系统的更大兴趣，可重构电池系统使用电池之间的快速可重构连接来克服这些问题。虽然电力电子架构和电路设计快速增长，但控制这些设备的管理算法并没有以相同的速度改进。本计画旨在发展一种新的控制模式，借由此模式可同时实现系统的输入控制与连接拓扑调整。这项研究如果成功，将显著改善可重构电池系统，并加速其在不同领域的应用。研究综合教育计划将通过课程改进，社区推广和研究导师制来吸引K-12，本科生和研究生。PI通过这个项目与业界的合作将带来实用的算法和工具。由于电池系统是所有部门使用的关键设备和设备的核心，因此这项研究不仅将促进电池技术的科学进步，而且有助于改善用于国家健康，繁荣和国防的技术。该项目的科学重点是开发一个基础数学框架，从网络的角度实现可重构电池系统的同时控制和拓扑重构，并建立一套控制算法，充分利用可重构性。该研究具体包括：1）创建可重构电池系统的代数图论建模方法，2）合成预测控制框架，可以优化控制输入并重新配置系统范围的连接，以及3）将框架应用于关键的电池管理任务，包括最佳充电/放电，热管理和电池平衡。模型和算法将通过严格的理论分析、模拟和实验进行原则性评估。该奖项反映了NSF的法定使命，并且通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Observer-based distributed leader-follower tracking control: a new perspective and results

• DOI: 10.1080/00207179.2019.1580770
• 发表时间: 2019-02
• 期刊: International Journal of Control
• 影响因子: 2.1
• 作者: Chuan Yan;H. Fang

A Novel Modular, Reconfigurable Battery Energy Storage System Design

• DOI: 10.1109/iecon48115.2021.9589321
• 发表时间: 2021-10
• 期刊: IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society
• 作者: Amir Farakhor;H. Fang

Implicit particle filtering via a bank of nonlinear Kalman filters

通过一组非线性卡尔曼滤波器进行隐式粒子滤波

• DOI: 10.1016/j.automatica.2022.110469
• 发表时间: 2022
• 期刊: Automatica
• 影响因子: 6.4
• 作者: Askari, Iman;Haile, Mulugeta A.;Tu, Xuemin;Fang, Huazhen
• 通讯作者: Fang, Huazhen

Real-Time Optimal Charging for Lithium-Ion Batteries via Explicit Model Predictive Control

• DOI: 10.1109/isie.2019.8781259
• 发表时间: 2019-06
• 期刊: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE)
• 作者: Ning Tian;H. Fang;Yebin Wang

High‐order leader‐follower tracking control under limited information availability

• DOI: 10.1002/rnc.6251
• 发表时间: 2022-07
• 期刊: International Journal of Robust and Nonlinear Control
• 影响因子: 3.9
• 作者: Chuan Yan;Tao Yang;H. Fang