CAREER: Optimizing Power Processing for Heterogeneous Energy Storage Systems

这一NSF职业项目旨在通过可持续的能源储存，使人们能够广泛和公平地获得可持续的电力和能源。在全球范围内，废旧电动汽车电池的数量正在指数级增长，同时对固定储能的需求也在增加，这是一个对可持续性的担忧。该项目将为将电动汽车(EV)的退役电池用于电网和电动汽车快速充电应用的固定电池储能(BESS)的技术经济可行性带来革命性的变化。这将通过大幅降低二次使用电池储能系统(2-BESS)内的电力处理成本来实现，目前这一成本在总成本中占很大比例。该项目的智能优势包括为在由二次使用(2U)电动汽车电池组成的电池能量存储系统中使用和优化功率处理的新方法建立了理论、算法和硬件基础。该项目的更广泛影响包括：广泛普及可再生能源，同时保持更强大的电网并通过可负担性、可用性和可持续性降低能源成本、公平获取和能源正义；通过缓冲能源和降低电网升级和高峰需求收费的潜在成本来降低快速充电的成本，从而加快电动汽车的普及；尽管二次使用(2U)电动汽车电池有大约80%的剩余容量，但其经济高效使用的挑战在于其特性的多样性，包括电动汽车中不同的驱动和温度循环，以及潜在的不同化学成分。这导致它们的能量和功率能力以及它们的降解率有显著的差异或异质性。目前处理异构性的技术状态是在每个电池的输出端使用一个功率转换器，从而导致更高的成本和功率损耗。该项目的研究将致力于：(1)功率处理的设计和优化框架，在较低的功率额定值下使用较少的不同转换器；(2)在新的功率处理架构中的2-BESS的最佳控制。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This NSF CAREER project aims to enable widespread and equitable access to sustainable power and energy through sustainable energy storage. Globally, the number of used EV batteries is rising exponentially together with the need for stationary energy storage, which is a concern for sustainability. The project will bring transformative change to the techno-economic feasibility of using retired batteries from electric vehicles (EV) for stationary battery energy storage (BESS) for grid and EV fast charging applications. This will be achieved by dramatically reducing the cost of power processing within a second-use battery energy storage system (2-BESS), which is currently a significant portion of the total cost. The intellectual merits of the project include building the foundation of theory, algorithms, and hardware for a new method for using and optimizing power processing in battery energy storage systems consisting of second-use (2U) EV batteries. The broader impacts of the project include widespread penetration of renewable energy sources while maintaining a more robust grid and reducing the cost of energy, equitable access and energy justice through affordability, availability, and sustainability; faster proliferation of EVs by reducing the cost of fast charging by buffering the energy and reducing the potential cost of grid upgrades and peak demand charges; and providing high-quality and effective, remote/distance learning to a workforce that may be vulnerable to changing technology and manufacturing landscapes, global crises (like pandemics), and shifting socio-economics.Although second-use (2U) EV batteries contain approximately 80% remaining capacity, the challenge in their cost-effective use is the diversity in their characteristics that include different drive and temperature cycles while in the EV and potentially different chemistries. This results in a significant variation or heterogeneity in their energy and power capabilities, and their degradation rates. The current state of the art in handling the heterogeneity is to use one power converter at the output of every battery, leading to higher cost and power losses. The research in this project will address: (1) a design and optimization framework for power processing with few dissimilar converters at lower power ratings; (2) optimal control of 2-BESS in a new power processing architecture.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.