Based on multiple reference frames (MRF), this article investigates high-precision harmonic current extraction for permanent magnet synchronous motor, while taking the disturbance of speed harmonics into account. First, the extraction error in MRF caused by speed harmonics is deduced and analyzed, showing that the error is nonignorable and detrimental. Second, a novel preprocessing of fundamental current reconstruction and elimination in MRF is proposed, which effectively suppresses the extraction error. Third, a variable forgetting factor recursive least squares algorithm is proposed for the fundamental current amplitude identification, which guarantees fast and accurate preprocessing. Furthermore, the above method parallelly resolves the conflict between rapid extracting and low steady-state fluctuation in MRF, which significantly enhances harmonic current extraction performance. The superiority and accuracy of the proposed algorithms are proved by experiments.

The conventional finite-control-set model predictive control (FCS-MPC) approach for controlling three-phase three-level inverters is plagued by significant current ripple. To minimize the root mean square error (RMSE) of the current control, this paper proposes a more straightforward and efficient solution using dual vectors. Firstly, a dual-vectors algebraic preselection method is presented to reduce computational complexity. Secondly, the continuous current reference is adopted for the first time instead of the discretized value to improve the accuracy of the current control error calculation, which leads to a more precise RMSE calculation. Thirdly, the impact of the sequence and duty cycles of the vectors on the RMSE is quantified for the first time, and the optimal solution is proposed to minimize RMSE. Compared to existing dual-vectors optimization algorithms, the proposed algorithm reduces the RMSE and total harmonic distortion of output current by more than 25% and 10%, respectively. Experimental results are presented to validate the advantages of the proposed algorithm.

The computational complexity of the three-level space vector pulse width modulation (SVPWM) limits its application in high-switching-frequency converters. To address this issue, this paper proposes a simplified SVPWM algorithm based on virtual chopping. Firstly, the reference voltage vector (VV) is adjusted to avoid excessive line-to-line voltage jumps. Secondly, boundary VVs in the space vector diagram, with simple switching sequences, are chosen as standards. Thirdly, the switching sequence of the reference VV is determined by virtual chopping the corresponding standard VV’s. Furthermore, to generate it in the microcontroller, the corresponding modulation waves are obtained. Finally, a method to balance DC side capacitor voltages is proposed. Consequently, the proposed algorithm simplifies the process, requiring only four equations. The sector determination, dwell time calculation and allocation are bypassed. Compared with the existing algorithms, the execution time and design complexity of the proposed algorithm in the microcontroller is reduced. Experimental results are presented to verify its effectiveness.

For three-level three-phase inverters, a novel finite-state machine-based model predictive control (FSM-MPC) is proposed. The state transition diagram of FSM is regarded as the operation guideline to avoid excessive voltage jumps (Δ V ). No more than five voltage vectors (VVs) are selected as FSM-MPC's candidates VVs, based on the VV reference and the previous optimal VV. And the cost function is simplified in terms of time duration. Thus, evaluating a candidate VV requires a very low computation cost. Without losing control performance, the proposed FSM-MPC's execution time is decreased to 50% of the MPC algorithm, which enumerates all basic VVs to get global optimal VV and performance. Compared with the existing simplified algorithms, the proposed FSM-MPC makes current harmonics lower, and its average switching frequency is 33% less, which means much less switching loss. Furthermore, the proposed algorithm is robust when the electric-circuit parameters are mismatched in the control system. Experimental results are provided to validate the advantages of the proposed algorithm.

For high-power paralleled three-phase three-level inverters with low switching frequency requirements, a novel cell-by-cell-based (CBCB) finite control set model predictive control algorithm is proposed in this article. First, the CBCB framework involves two individual inverters with staggered control timings, differing by half a period. Second, within the CBCB framework, a delay compensation solution with smaller estimation errors is expounded. Furthermore, a novel cost function for each individual inverter is designed, resulting in a doubling of the equivalent control frequency. Third, to improve the computational efficiency, candidate voltage vectors are preselected under the constraint of phase voltage jump and the requirement for low phase circulating current (PCC). Compared to the conventional decentralized FCS-MPC algorithm and the existing optimization algorithms, the proposed algorithm significantly reduces current harmonics and has a faster dynamic response rate at low average switching frequencies. Meanwhile, PCC is well suppressed. Besides, the above advantages are robust when the electric-circuit parameters are mismatched in the control system. Experimental results are provided to validate the advantages of the proposed algorithm.

This article proposes a robust dual-vector model predictive control (RDVMPC) strategy for high-power three-level inverters, specifically designed to optimize current harmonics. By extending the concept of total harmonic distortion (THD) to the entire time domain, the current deviation is redefined, and a novel cost function is formulated. The proposed strategy incorporates dual-vector control to maintain a fixed switching frequency while optimizing the sequences and duty cycles of the vectors to further mitigate THD. A novel ultra-local model is employed to eliminate dependency on precise system parameters, with unknown components accurately estimated through an extended state observer (ESO) equipped with an adaptive bandwidth gain mechanism. This mechanism dynamically adjusts to enhance disturbance rejection under parameter variations and suppress noise under steady-state conditions. The efficacy of the proposed method is substantiated through simulations and experimental validation on a 10 kW T-type inverter, demonstrating significant improvements in harmonic reduction and overall system performance.