This paper presents a sensorless finite control set model predictive current control (FCS-MPCC) for surface-mounted permanent magnet synchronous motor drives based on an improved reduced-order generalized integrator-frequency-locked loop (IROGI-FLL). To simplify the structure of the sensorless FCS-MPCC and avoid control performance degradation caused by the rotor position estimation error, an instantaneous power theory-based given current calculation method is designed. Accordingly, the whole algorithm can be realized without using rotor position. IROGI-FLL is adopted for filtering the estimated back electromotive force and estimating motor speed. To enhance its dynamic speed tracking performance, a speed tracking deviation compensation term is designed for FLL. With the feedforward compensation term, speed static tracking deviation in acceleration and deceleration states can be eliminated. Moreover, to avoid the adverse effect of parameter mismatch on control performance, an incremental adjustable model-based model reference adaptive system (MRAS) is introduced to identify the resistance and inductance parameters. The incremental adjustable model can avoid identification error caused by the rank deficiency issue. Finally, the effectiveness of the proposed method is investigated by experiments.

The combination of a high-performance filter and phase-locked loop (PLL) has been presented as an effective alternative for the position estimation of a permanent magnet synchronous motor (PMSM) drive. However, the feedback delays existing in the practical implementation of the filter and PLL usually lead to position estimation deviation. To enhance the accuracy of position estimation, this paper proposes a sensorless control technology based on an improved adaptive vectorial filter (AVF) and PLL. First, the effect of feedback delay on the filtering performance of the AVF and the tracking performance of the PLL are analyzed. Then, corresponding delay compensation methods for the AVF and PLL are proposed. A compensation term based on the prediction of the filtered back electromotive force (EMF), which can repress the filtering performance degradation caused by feedback delays, is introduced and combined with the conventional AVF. As a result, the amplitude and phase shifts with the filtered back EMF can be effectively eliminated before applying it to the PLL. A differential calculation structure, which can ensure that the closed-loop transfer function of the equivalent ideal PLL is the same as the ideal PLL under the condition of feedback delay, is proposed to replace the cascade calculation structure of the conventional PLL. In addition, an open-loop deviation compensation method is integrated to eliminate the position estimation static deviation. The effectiveness of the proposed sensorless control technology is investigated by experimental tests.

Three-phase voltage source pulsewidth modulation rectifiers with deadbeat predictive direct power control (PDPC) have been extensively studied for their simple concept and satisfactory performance. However, conventional deadbeat PDPC strategies exhibit a slow dynamic response to load disturbances and demonstrate active power errors under steady-state conditions. To enhance the dynamic response, this paper proposes a linear active disturbance rejection control (LADRC) with an adaptive virtual capacitance method in the outer voltage loop. This enhancement provides a virtual active power component, that enables immediate power tracking under load disturbances. Additionally, a feedback correction method is implemented to predict the active power reference accurately and eliminate steady-state active power error. The design of parameters, disturbance rejection capabilities, and stability analysis of the proposed LADRC with adaptive virtual capacitance and feedback correction (LADRC-AVCFD) strategy are presented comprehensively. A 1.5 kW prototype was constructed, and experimental results indicate a complete elimination of steady-state active power errors, a 75% reduction in DC voltage fluctuations, and an 81% decrease in settling time under load disturbances.

In modern marine vessels equipped with electric propulsion systems, rectifiers are commonly used as part of the setup. However, the conventional deadbeat predictive direct power control strategy for three-phase voltage source pulse-width modulation (PWM) rectifiers tends to underperform when subjected to load variations and external disturbances. To address these limitations, this paper proposes an enhanced linear active disturbance rejection control (LADRC), incorporating virtual capacitance and an improved equivalent input disturbance strategy. The integration of virtual capacitance in the LADRC is specifically applied during load transitions. Virtual capacitance is a capacitor element simulated through the control strategy. It enhances voltage stability and dynamic response capability by compensating for voltage fluctuations and power deficits in the system. By providing a virtual active power, this approach substantially improves power tracking performance, reducing the DC voltage drop and settling time by 60% and 74%, respectively. In addition, the proposed strategy is easy to implement and does not add complexity to the LADRC. Moreover, the equivalent input disturbance is refined through virtual capacitance, enabling accurate disturbance estimation. As a result, the active power ripple and current total harmonic distortion under disturbances are reduced by 44% and 40%, respectively. The stability of the proposed strategy is comprehensively analyzed, and experimental results from a prototype system validate its effectiveness and accuracy.

In data center power systems, three-phase LLC resonant converters are widely adopted due to their advantages of electrical isolation and high power density. However, the conventional use of multiple discrete high-power transformers reduces both overall power density and efficiency. To address this issue, this paper proposes a novel three-phase magnetically integrated transformer design based on PQ cores. By optimizing the multi-layer winding structure, the proposed transformer ensures balanced current sharing among parallel windings under high-frequency conditions. Additionally, by sharing the side limbs between adjacent phases, the core volume and weight are further reduced. The feasibility of the proposed transformer is validated through magnetic circuit analysis, finite element simulation, and experimental testing. Compared with traditional magnetic integration methods, the proposed approach eliminates the need for custom magnetic cores, simplifying the manufacturing process. Furthermore, compared with the design using multiple discrete transformers, the proposed transformer achieves a 14.3% reduction in core volume and weight. To verify the performance of the proposed design, a two-stage 15 kW three-phase LLC resonant converter was built and tested.

Conventional model predictive current control (MPCC) bears high current fluctuations and the system parameter dependence problem. To address these issues, an improved dual-vector MPCC (DMPCC) with parameter identification is proposed in this paper. To reduce the number of alternative active voltage vectors, two adjacent active voltage vectors (AVVs) are first preselected by the reference weighting amplitude slope (WAS) of the stator current, and the action time of the two-vector combinations are calculated by WAS. Then, the cost function is used to determine the optimal dual-vector combination to improve the steady-state performance. Meanwhile, to solve the rank deficiency issue of multiple parameter identification, an improved MRAS parameter identification algorithm based on the incremental state equation is proposed. Finally, the feasibility and effectiveness of the proposed control algorithm are verified by experiments.