Controllability, Observability, and Integrated State Estimation and Control of Networked Battery Systems

Abstract

This paper develops an integrated state estimation and control methodology of networked battery systems that require only terminal voltage and current measurements for reduced cost and complexity. Without direct internal voltage/current measurements and individual control on each battery pack in the system, a networked battery system is inherently uncontrollable and unobservable. By employing bypass power electronics, we show that the networked system can be made controllable and observable by switching control. To coordinate switching control for integrated state of charge (SOC) estimation and control, this paper introduces switching control algorithms that use time division, duty cycle control, and periodic switching. It is shown that under noisy terminal voltage and current measurements, state estimation algorithms are convergent, and the control algorithms can achieve balanced SOC control during operation. The proposed hardware and methodology framework is useful for networked battery systems that can accommodate battery packs of different types, ages, and power/capacity ratings. Case studies using production batteries demonstrate convergence behavior for both state estimation and SOC consensus control under time-varying charging current profiles. The approach will be especially useful for managing battery storage systems to support power grids with renewable energy sources where the battery systems are required to operate continuously.