Batteries are one of the most critical enabling technologies for achieving clean, efficient and sustainable energy development in the transportation and power sectors. Advanced vehicle and power grid battery systems consist of networked battery modules of diverse types and characteristics. System-level performance can be interrupted or completely disabled by subsystem abnormality. Beyond typical battery management systems (BMS) for individual battery modules, this project will develop a novel resilient battery management system (RBMS) for reliable operations of networked battery systems. This RBMS will be capable of detecting and locating abnormality, prevent them from propagating, and of reconfiguring the battery system for sustained operation. This critical and transformative technology will support electric vehicles for extended battery life, sustain military missions under limited energy resources, and maintain smart electricity grids without interruption. Beyond its direct technological advance in battery characterization, control and management, this project will have significant educational, societal, and economic impact. It will also help advance technology and workforce development in these energy storage and the many associated fields of application. Within this project, the team will integrate findings into battery technology curricula in the existing Electrical-Drive Vehicle Engineering programs at the undergraduate and graduate levels at Wayne State University. Courses and training seminars on advanced battery management systems will be developed for students, engineers, and technicians to enhance workforce training in vehicle electrification, sustainable energy development, and smart grids. The success of this project will help achieve cleaner, more efficient, and more reliable transportation, power grids, and beyond.
Battery abnormality conditions include potential health deterioration indicated by drifting of characterizing variables into unacceptable regions, faults that must be cleared by timely remedy actions, and failures that are not recoverable. Networked battery systems introduce unique and daunting challenges, including sensing limitations for prompt fault diagnosis and localization, fast and accurate joint estimation of state of charge and characterizing parameters, and advanced power electronics for system reconfiguration. Current battery systems and their management do not include such functions. Employing methodologies from discrete event systems, system identification and state estimation, stochastic analysis, and advanced power electronics control, this project will introduce a new RBMS framework for integrated control, active diagnosis, and sustained operation of networked battery systems. Collaborating with industry leaders in battery technology, electric vehicles, and smart grids, the team will develop a new theory of active network observers, real-time active diagnosis and localization of abnormal conditions, reconfiguration, and adaptive BMS strategies. The proposed methods represent a transformative technology for managing different types of batteries and structures, including new or old batteries, for vehicle and grid applications. The main approaches of this project have some distinctive and novel features: (1) Discrete event system (DES)-based diagnosis strategies and control decisions. By using systematic DES strategies, fast diagnosis and localization of abnormal conditions can be achieved; (2) Real-time battery characterization for module-level diagnosis. A battery's states and parameters will be jointly estimated for characterizing batteries in real time; and (3) Active system reconfiguration to accommodate resilient operation and adaptive battery management systems. Hardware reconfiguration will prevent local abnormality from spreading to other parts of battery systems. The battery management systems then self-adjust to sustain operation under the new configuration.
