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In ultra‐high speed (UHS) motor applications, full SIC two‐level (2L) inverters with high switching frequencies are generally used due to their lower cost. However, even with the usage of all WBG power devices, high‐frequency hard‐switched 2L inverters still do not achieve optimal efficiency characteristics. As a result, in order to simultaneously reduce the switching frequency and enhance overall efficiency, recently three‐level (3L) topologies have emerged as a promising solution. Nevertheless, to fully meet the requirements of UHS applications, the switching frequency of 3L inverters should be increased beyond 30 kHz, which necessitates the usage of all SIC power devices. This, in turn, leads to a potential drawback where the cost of the drive system may become prohibitively high due to the requirement of all SIC switches. To address this issue and reduce the cost of a full SIC 3L inverter, a new 3L simplified sparse NPC (SSNPC) topology is proposed in this work. The operational principle of this topology, its distinctive control features, and the advantages it offers specifically for UHS applications are presented. Additionally, to further increase the efficiency and reduce the influence of dead time at low speeds, a new switching sequence is introduced. Finally, the overall performance and efficiency characteristics of the high‐frequency SSNPC inverter were verified across all operational conditions of UHS motor drive system. [ABSTRACT FROM AUTHOR]

Deadbeat control calculates excitation by a differential equation model that takes measurements of state variables as initial values and instructions as terminal values. Ideally, this excitation can force state variables to track instructions in the succeeding control interval. However, in a practical system, noises in measured signals can mislead the control system and degrade its performance with increased ripples and harmonics. Therefore, some filters are often used in measurements, but their inherent delay can lead to inaccurate initial values and cause severe overshoots in dynamic cases. In this study, a new type filtering algorithm called predictive deviation filter is proposed for deadbeat control, which filters only the predicted deviation obtained by removing the expected values from measured ones, and then the real values of state variables are recovered. With this method, the influence of the filter delay can be limited only on the deviation which is a small part of the signal, significantly improving the accuracy of the initial values. Furthermore, a comprehensive frequency‐domain analysis of the predictive deviation filter is provided. Finally, the new filtering algorithm is applied to drive control of permanent magnet synchronous motor. The simulation and experimental results verify the effectiveness and performance of this approach. [ABSTRACT FROM AUTHOR]