Extended Kalman Filtering for Full State Estimation and Sensor Reduction in Modular Multilevel Converters

Abstract

Modular multilevel converters (MMCs) have become one of the most popular power converters for medium/high power applications, from transmission systems to motor drives. However, to operate the MMC, typical control schemes use a voltage measurement per sub-module, which increases dramatically the number of sensors required to build an MMC, adding complexity in terms of communications and increasing costs, hence limiting its applicability. As an effort to overcome these issues, this work presents a technique based on Kalman filtering for estimating the capacitor voltage at each sub-module and the converter current. The proposed approach operates both in open and closed-loop, during transients and steady-state, enabling the use of estimator-based state feedback control without the need of a voltage sensor per sub-module, and filtering the EMI from voltage and current sensors. Experiments conducted in a three-phase MMC with 24 sub-modules confirm the effectiveness of the proposed approach during transients and steady-state operation.