General Decoupling and Sampling Technique for Reduced-Sensor Battery Management Systems in Modular Reconfigurable Batteries

Abstract

The capacity and voltage rating of battery packs for electric vehicles or stationary energy storages are increasing, which challenge battery management and monitoring. Breaking the larger pack into smaller modules and using power electronics to achieve dynamic reconfiguration can be a solution. Reconfigurable batteries come with their own set of problems, including many sensors and complex monitoring systems, high-bandwidth communication interfaces, and additional costs. Online parameter estimation methods can simplify or omit many of these problems and reduce the cost and footprint of the system. However, most methods require many sensors or can only estimate a subset of the elements in the module’s equivalent circuit model (ECM). This paper proposes a simple decoupling technique to derive individual modules’ voltage and current profiles from the output measurements without direct measurement at the modules. The determined profiles can achieve a high sampling rate with minimum communication between the battery management system (BMS) and the modules. With accurate profiles, an estimation technique can easily determine the parameters of the modules. Provided simulations and experiments confirm this claim by estimating the parameters of a first-order ECM with a parallel capacitor. The proposed technique reduces the number of sensors from 2N + 2 to only two at the pack’s output terminals.

Keywords

• parameter estimation
• equivalent circuit model (ECM)
• battery management system (BMS)
• sensor reduction
• battery monitoring
• reconfigurable battery