CAREER: Optimizing Power Processing for Heterogeneous Energy Storage Systems

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

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.