Model predictive and SoC balancing control of a CHB inverter in battery energy storage application using reward functions

Abstract

SummaryThis article presents an improved model predictive current control algorithm combined with a novel state of charge (SoC) balancing approach for a three‐phase cascaded H‐bridge inverter in battery energy storage applications. Based on the model predictive control with elimination of redundant voltage vectors, neighboring vectors of the last voltage vectors are used to find the optimal ones in only one control cycle, which solves the problems of high computational burden and slow dynamic response. To overcome the unsuitability of the conventional cost function in SoC balancing, the reward functions that effectively balance the inter‐phase SoCs, inner‐phase SoCs, and inner‐phase dc voltages are presented respectively. Simulation and hardware‐in‐the‐loop‐based experimental results validate the effectiveness of the proposed strategy.