Cyber-Physical Co-Simulation Framework for Smart Cells in Scalable Battery Packs

This article introduces a Cyber-physical Co-Simulation Framework (CPCSF) for design and analysis of smart cells that enable scalable battery pack and Battery Management System (BMS) architectures. In contrast to conventional cells in battery packs, where all cells are monitored and controlled centrally, each smart cell is equipped with its own electronics in the form of a Cell Management Unit (CMU). The CMU maintains the cell in a safe and healthy operating state, while system-level battery management functions are performed by cooperation of the smart cells via communication. Here, the smart cells collaborate in a self-organizing fashion without a central controller instance. This enables maximum scalability and modularity, significantly simplifying integration of battery packs. However, for this emerging architecture, system-level design methodologies and tools have not been investigated yet. By contrast, components are developed individually and then manually tested in a hardware development platform. Consequently, the systematic design of the hardware/software architecture of smart cells requires a cyber-physical multi-level co-simulation of the network of smart cells that has to include all the components from the software, electronic, electric, and electrochemical domains. This comprises distributed BMS algorithms running on the CMUs, the communication network, control circuitry, cell balancing hardware, and battery cell behavior. For this purpose, we introduce a CPCSF that enables rapid design and analysis of smart cell hardware/software architectures. Our framework is then applied to investigate request-driven active cell balancing strategies that make use of the decentralized system architecture. In an exhaustive analysis on a realistic 21.6kW h Electric Vehicle (EV) battery pack containing 96 smart cells in series, the CPCSF is able to simulate hundreds of balancing runs together with all system characteristics, using the proposed request-driven balancing strategies at highest accuracy within an overall time frame of several hours. Consequently, the presented CPCSF for the first time allows us to quantitatively and qualitatively analyze the behavior of smart cell architectures for real-world applications.