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

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 submodule (SM), 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 article presents a technique based on Kalman filtering for estimating the capacitor voltage at each SM 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 SM, and filtering the electromagnetic interference from voltage and current sensors. Experiments conducted in a three-phase MMC with 24 SMs confirm the effectiveness of the proposed approach during transients and steady-state operation.

Automated summary

This article presents a technique based on Kalman filtering for estimating the capacitor voltage and converter current of modular multilevel converters (MMCs). The proposed approach operates in both open and closed-loop and eliminates the need for voltage sensors per submodule, reducing complexity and costs.