To comprehensively suppress the current harmonics in both the torque plane and the zero-sequence dimension of the open-end winding permanent magnet synchronous motor (OW-PMSM) drive with a common dc bus, this paper proposes a novel three-dimensional space vector pulse width modulation (3D-SVPWM) strategy based on the ABC coordinate system. The proposed 3D-SVPWM strategy constructs a three-dimensional modulation space and uses adjacent voltage vectors in this space as synthetic vectors, enabling precise collaborative control of the torque plane and zero-sequence dimension. The proposed strategy utilizes the inherent regularity of voltage vector distribution in the ABC coordinate system to avoid complex 3D space partitioning and simplify the modulation process. Furthermore, the average switching frequency is reduced by one-third, which significantly decreases switching losses. Finally, experimental results are presented to verify the effectiveness and superiority of the proposed strategy.
Torque ripple suppression is critical for high-performance permanent magnet synchronous machine drives, where non-sinusoidal back-EMF and cogging torque introduce position-dependent disturbances. To address this issue, this paper proposes a one-step angle-based three-vector model predictive torque-flux-current control for surface-mounted permanent magnet synchronous machine drives, in which disturbance compensation is incorporated into both duty-ratio calculation and candidate vector-combination evaluation. Torque, stator-flux, and dq-axis current objectives are reformulated into load- and current-angle tracking, yielding a normalized two-angle cost function with a reduced weighting factor tuning burden. In the three-vector synthesis, the reconstructed back-EMF harmonic voltage is included in the compensated current-slope calculation used for the deadbeat duty-ratio calculation and state prediction. Meanwhile, the cogging-torque profile is introduced through the compensated torque reference and the resulting load-angle reference. Consequently, both disturbance profiles are reflected in the candidate evaluation before the final vector combination is selected. A spatial-adjacency-based candidate-set construction is further employed to reduce the implementation complexity. Experimental results show that the proposed method can achieve significant torque ripple reduction and competitive current quality compared with representative single-vector and three-vector model predictive control schemes, while maintaining real-time feasibility.
Harmonic distortion and non-ideal grid conditions pose significant challenges to LCL-Type grid-following inverters (GFLIs) interfacing distributed renewable energy resources with utility grids. However, existing ancillary harmonic-control loops have mainly focused on harmonic attenuation, while their impacts on output-admittance passivity and grid-interactive stability under non-ideal grid conditions have not been sufficiently addressed. This article develops a passivity-based design method for flexible harmonic compensation and rejection of LCL-Type GFLIs based on a voltage-feedback control structure. A unified admittance model is established by separating the fundamental and harmonic components, enabling the compensation and rejection modes to be analyzed within the same framework. Based on this model, the resonator compensation angles are derived from output-admittance passivity requirements, while the resonator gains are designed according to the inner-loop stability margin. In this way, the proposed method links harmonic-control design to both external and internal stability. Moreover, the studied control structure enables flexible harmonic compensation/rejection without additional harmonic extraction sensors or algorithms. Experimental results under complex distorted-grid conditions validate the effectiveness of the proposed method.
Multi-grid-forming (GFM) converters systems have shown broad application potential in fields with high penetration of renewable energy integration. Transient stability enhancement of multi-GFM converters systems is urgent under large disturbances. Even though modified methods have been proposed, the interactions of frequency dynamics among the converters are not fully utilized. Besides, methods based on center of inertia (COI) frequency show good control effectiveness but require high-bandwidth global communication and centralized controller, which limits their further extension. In this paper, a transient damping control method with distributed COI frequency estimation is proposed to enhance the transient synchronization stability of the multi-GFM converters system. The COI frequency estimation is realized through a well-designed predefined-time consensus (PTC) observer. By setting a reasonable predefined time, the PTC observer can realize fast and accurate COI frequency estimation when large disturbances occur, which significantly improves the system’s transient synchronization stability. Theoretical analysis and experimental results verify the feasibility of the proposed method.
Magnetic shunt integrated inductor-transformer is an effective solution to integrate a large resonant inductor in wide gain range LLC converter. However, existing works lacked a quantitative analysis of the effective turns ratio variation in these structures. Meanwhile, non-interleaved windings resulted in increased winding loss in designs. This paper quantitatively analyzed the leakage inductance locations and reasons of effective turns ratio variation in the magnetic shunt integrated structure. Based on the analysis, this paper proposed a magnetic shunt integrated transformer structure with arbitrary turns ratio. By controlling the reluctances of the two core air gaps independently, the proposed structure enables decoupled control of the leakage inductance, magnetizing inductance, and effective turns ratio, effectively decreased turns number in non-integer turns ratio designs. This paper then proposed an optimized magnetic shunt structure. By replacing the conventional shunt reluctance with a series combination of an air gap reluctance and a ferrite reluctance, optimized shunt structure enables the realization of an arbitrary equivalent permeability, preventing saturation and enhancing the practical feasibility. A 1.2 MHz, 40–60 V input and 12 V 80 W output LLC resonant converter is built to verify the proposed theories. The converter achieved precise control of the effective turns ratio, delivering a peak efficiency of 95.1% and a full-load efficiency of 94.85%.
To address the strong coupling problem among zero-sequence current (ZSC), common-mode voltage (CMV), and switching frequency in the control system of open-winding permanent magnet synchronous motors (OW-PMSMs) with a common DC bus, a novel reference voltage vector redistribution strategy is proposed in this paper. By designing two complementary voltage vector combinations and constructing a dual independent weighting factor redistribution mechanism, the proposed strategy breaks the binding constraint of a single weighting factor on reference voltage vector redistribution in traditional methods, while decoupling the mutual restrictions among ZSC suppression, CMV reduction, and switching frequency optimization. Specifically, the proposed method can adaptively switch between the two voltage vector combinations and accurately redistribute the duration time of voltage vectors via weighting factors. It not only ensures that the zero-sequence voltage (ZSV) real-time cancels the third-harmonic back electromotive force (EMF) to achieve ZSC suppression but also synchronously reducing CMV and switching frequency through optimized selection. Finally, comparative experiments on a 1.25 kW OW-PMSM platform demonstrate that the strategy significantly reduces CMV and switching frequency with maintained ZSC suppression and acceptable THD over the traditional methods.
Sampling current dc bias, inverter nonlinearity, and other non-ideal factors cause harmonic distortion of the estimated back electromotive force (EMF) in permanent magnet synchronous motor (PMSM) drives, which degrades the position estimation accuracy of sensorless control. To address this problem, a harmonic suppression method based on a minimum-order complex vector observer (MOCVO) is proposed for sensorless PMSM drives in this article. First, based on the conventional full-order observer, a MOCVO structure is constructed to alleviate the contradiction between observer stability and harmonic suppression performance. On this basis, with the help of the frequency domain characteristic analysis of harmonics, an adaptive harmonic elimination controller is designed to achieve the suppression of dc bias and mid-frequency harmonics. Meanwhile, the system phase tuning is achieved by introducing an imaginary gain. Then, the stability of the studied observer is ensured by the pole placement. Finally, the effectiveness of the proposed scheme is verified by comparative experiments on a test prototype.
The input-series-output-parallel (ISOP) dual active bridge (DAB) converter is widely used in renewable energy systems and direct current (DC) distribution networks. Direct phase-shift ratio control inevitably introduces second-order nonlinear coupling terms. These coupling terms cause inter-submodule coupling and degrade both the effectiveness of decoupling and the input voltage sharing (IVS) of traditional control strategies. To eliminate these coupling terms, this paper proposes a decoupled input-voltage-sharing control strategy for the ISOP DAB converter based on the linear power regulation factor (LPRF). First, the nonlinear system is linearized by introducing the LPRF. This eliminates the cross-coupling terms and simplifies the decoupling control design. Next, an LPRF-based decoupling framework is proposed to diagonalize the small-signal model matrix and resolve coupling issues between control loops. Subsequently, the decoupling structure incorporates an input voltage regulation loop with a power capacitor voltage balancing mechanism to improve IVS control accuracy. Furthermore, a decoupling IVS control approach is proposed by reshaping the converter's input impedance to enhance the system's dynamic and steady-state performance. Compared with existing control methods, the proposed strategy achieves a smaller steady-state error, lower voltage overshoot, and a faster dynamic response. Experimental results are provided to validate the performance of the proposed control strategy.
Electrothermal coupling has a critical impact on the steady-state losses and virtual junction temperature of power MOSFETs due to their strong thermal dependent on-resistance. Existing analytical loss calculation methods for power MOSFETs, which are based on an assumed operating temperature, are not accurate, whereas iterative electrothermal simulations offer high accuracy. However, in automatic design of converters based on artificial intelligence (AI), where circuit parameters and heat sink structural configurations vary dynamically, obtaining MOSFET losses through iterative simulations is very time costing. To address this challenge, the article proposes a high efficient design method for electrothermal coupling performance of power MOSFETs based on iterative multiple artificial neural networks (ANN). Two ANN surrogate models are respectively developed for the power losses and thermal distribution based on LTspice and COMSOL with limited number of simulations. Further, an iterative calculation is performed based on these two ANN models which significantly reduce the calculation time compared to the traditional iterative electrothermal simulations. The proposed method is validated in three-phase LLC converter in this article. Compared with iterative simulations, the proposed method achieves a 93.8-fold acceleration in data collection and over a 107-fold speedup in evaluation. Experimental validation at multiple power ratings shows high accuracy, underscoring the method’s engineering applicability.
Junction temperature and its fluctuations affect the reliability and lifetime of insulated gate bipolar transistor (IGBT) modules. Thermal management systems (TMSs) must achieve both low thermal resistance and high heat capacitance, which are often difficult to balance. To address the limitations, this work proposes a dual-path TMS design, in which heatsink provides continuous convective heat dissipation while graphene-enhanced phase change material (G-PCM) module enables thermal buffering. A micro heat pipe array (MHPA) effectively decouples the two paths, allowing each to operate independently for steady and transient cooling. A CFD model, incorporating the thermophysical properties of the G-PCM module, is established and validated experimentally. Compared with a conventional TMS, the dual-path TMS reduces thermal resistance by 11.0% and increases the effective sensible heat capacity by 60.7%. In addition, the proposed TMS more effectively suppresses junction temperature fluctuations, with a thermal response time 2.1 times longer than that of the conventional TMS due to the latent heat utilization of the G-PCM module. Experimental results agree well with the simulations. Dynamic power-cycling tests further demonstrate a 31.3% reduction in junction temperature fluctuation. These results indicate that the proposed dual-path TMS can improve dynamic thermal regulation of IGBT modules, which offering a promising pathway for reliability enhancement.
In underwater inductive power transfer (UIPT) systems, parameter identification and magnetic coupler (MC) optimization are often computationally intensive and time-consuming. This paper proposes a physics-data hybrid-driven approach for rapid parameter identification and a generative inverse design model for high-efficiency MC optimization. Firstly, an analytical electromagnetic model is established to provide physical priors. Then, a light gradient boosting machine based (LightGBM-based) residual network is introduced to compensate the nonlinear deviations. This strategy achieves a maximum mean absolute percentage error (MAPE) of less than 3% with a small-sample training dataset. The single prediction time is approximately 60 ms. Secondly, a physics-informed conditional denoising diffusion probabilistic model (cDDPM) is proposed. It integrates a multi-layer perceptron (MLP) proxy model to generate an optimal MC. Compared to conventional optimization algorithms, this approach reduces the design time by three orders of magnitude while achieving largely consistent optimization results in terms of efficiency and power. Finally, a 1 kW/85 kHz experimental setup is built to validate the proposed methodology. Experimental results demonstrate a system efficiency of 93.23%. Compared with the experimental results, the maximum errors of the parameter identification predictions and the inverse design optimization objectives are 7.7% and 4.39%, respectively.
Three-level neutral-point-clamped(3L-NPC) inverters are widely used in various industrial applications. However, compared with two-level inverters, the increased number of power switches leads to more open-circuit fault modes and higher fault localization complexity. This article proposes an online open-circuit fault diagnosis method based on the covariance ellipse of normalized currents. The proposed method first normalizes the three-phase currents to suppress the influence of current magnitude variations under dynamic operating conditions. The normalized currents are then transformed into the α-β frame, where a covariance matrix is constructed within a sliding window. According to the geometric characteristics of the covariance ellipse, the eccentricity is used for fault detection, the minor-axis direction is used for fault phase determination, the center-offset direction is used for fault arm localization, and the polarity-dependent sample-count ratio is used for inner/outer switch discrimination. The proposed method has a low computational burden and is easy to implement online. Moreover, it uses only three-phase current signals and requires no additional signals or sensors. Finally, experiments are carried out to verify the robustness and effectiveness of the proposed method.
Wireless power transfer (WPT) has become an important power supply solution for automated material handling systems in precision manufacturing, enabling contactless, contamination-free, and reliable energy delivery. However, during long-term operation of multi-segment wireless power transfer systems, drift in receiver-side resonant parameters can easily cause detuning, thereby disrupting the designed resonant condition and leading to reduced transmission efficiency and degraded output stability. To address this issue, this paper proposes an active-resonance receiver for multi-segment WPT systems. Compared with conventional receiver-side designs, the proposed system integrates resonance support, rectification, and output regulation into a unified active structure, enabling reactive power compensation and improving receiver-side compactness. The active-resonance control strategy dynamically regulates the phase of the receiver current according to the voltage phase, maintaining near-zero-phase-angle (ZPA) operation even under parameter drift conditions. As a result, the system achieves stable and efficient power transfer with enhanced detuning tolerance. A 1.5 kW prototype was developed to validate the theoretical analysis and control design. Experimental results show that the system maintains over 88% transmission efficiency with receiver-side inductance deviation up to 120 μH, while the output voltage fluctuation remains within 2% under various disturbance conditions.1.
In 48V voltage regulator modules (VRMs), single-stage current-doubler rectifier (CDR) is a promising candidate due to its inherent high step-down ratio and buck-like fast transient response. However, a fundamental incompatibility exists between conventional magnetic-integrated (MI) fractional-turn (FT) transformer and the CDR topology. During the freewheeling state, the simultaneous conduction of synchronous rectifiers (SRs) in an MIFT-CDR leads to catastrophic flux cancellation and magnetic short-circuits. Besides, there is extra issue of circulating current because of asymmetric MMF during turn-on state. To solve this problem, this paper proposes a novel circulating-current-suppressed magnetic-integrated fractional-turn (CCS-MIFT) transformer. First, a dedicated magnetic shunt path based on the fifth frustum-shaped center leg (FSCL) is introduced to decouple secondary fluxes, enabling the seamless integration of MIFT benefits within the CDR framework. Second, based on an improved magnetic reluctance model, an asymmetric air-gap distribution strategy is implemented—confining gaps strictly to the main center legs while maintaining a gap-free shunt path—which is analytically proven to minimize circulating currents. Third, a triangular leg arrangement is introduced to optimize the primary figure-eight winding geometry, ensuring a constant trace width and minimized mean magnetic path length to further reduce conduction and core losses. A 400-kHz, 48V-to-1.8V, 280W half-bridge CDR prototype was developed to verify the design. Experimental results demonstrate a peak efficiency of 95.55% and a power density of 882 W/in³, validating the effectiveness of the proposed magnetic design.
In wireless power transfer (WPT)-fed permanent magnet synchronous motor (PMSM) drives, coil misalignment and dynamic load transitions alter mutual inductance and resonance conditions, degrading system efficiency and voltage stability. This paper develops an adaptive estimation and coordinated control framework for a double-sided LCL-compensated WPT system driving a PMSM. By modeling the dynamic PMSM as a nonlinear DC-link load, the control objective shifts to direct DC-link voltage regulation. Based on relative gain array (RGA) analysis, a quasi-decentralized architecture is established to coordinate primary-side voltage regulation, secondary-side power matching, and active-rectifier synchronization. An adaptive moment estimation-optimized back-propagation neural network (Adam-BPNN) predicts the mutual inductance in real time, while the equivalent drive load is updated online. Furthermore, a hybrid sliding-mode-controlled synchronous rectification (HSMC-SR) strategy is used to track the resonant-current phase and maintain stable zero-voltage switching (ZVS). Hardware experiments on a WPT-fed 750-Wrated PMSM drive prototype show that the proposed method achieves a mutual-inductance mean absolute percentage error (MAPE) of 0.074% with R2=0.976, a 3-ms phase-tracking time, and a peak WPT-to-DC-link efficiency of 95.7%.
Reliable detection of stator inter-turn short-circuit (ITSC) faults is critical for the safe and efficient operation of six-phase induction motor drives. However, early ITSC signatures are weak and strongly affected by operating conditions, making fixed-threshold methods prone to missed detections or false alarms. This article proposes a confidence-aware adaptive thresholding scheme based on Gaussian process regression (GPR) trained using only healthy operating data for early fault detection. The fault indicator is defined as the magnitude of the current vector in the xy harmonic subspace. A GPR model captures the nonlinear dependence of this indicator on speed and torque while providing predictive uncertainty. During online monitoring, the residual between the measured and predicted indicators is compared with a variance-dependent dynamic threshold, enabling uncertainty-aware fault detection under varying operating conditions. The proposed method requires no faulty training data, additional sensors, or high-fidelity machine models. Experimental results demonstrate that the GPR model achieves lower prediction error than linear regression and artificial neural network (ANN) models, thereby improving the reliability of the proposed detector for low-severity ITSC faults. The method is validated in real time and achieves over 97% detection accuracy, demonstrating an effective trade-off between detection performance and computational complexity.
In permanent magnet synchronous motors (PMSMs) with harmonic back-EMF, back-EMF harmonics may degrade the accuracy of fundamental parameter identification. When the motor inductance is relatively small or the switching frequency is low, the discretization method of the identification model also affects the accuracy of parameter identification. This paper proposes a comprehensive online parameter identification method for PMSMs with harmonic back-EMF based on high-frequency injection (HFI). By incorporating a periodic midrange operation into the signal-processing procedure, the extracted amplitude and phase information is freed from harmonic interference. Additionally, the application of a low-pass filter ensures that the resistance and flux linkage identified by recursive least squares (RLS) are no longer affected by high-frequency components. Various factors affecting parameter identification accuracy, including inverter nonlinearities, position-angle errors and model discretization, are analyzed and compensated for. Subsequently, harmonic flux linkage identification is performed based on the identified fundamental parameters. Finally, an improved robust deadbeat predictive current control (DPCC) strategy is developed using the identified parameters. By incorporating an uncertainty and disturbance estimator (UDE) and harmonic back-EMF injection (HBEMFI), the proposed strategy effectively suppresses disturbances in current control over a wide frequency range while maintaining good dynamic performance with a modest computational burden. Simulations and experimental results validate the effectiveness of the proposed method, demonstrating accurate parameter identification and excellent current tracking performance.
State-of-charge (SOC) imbalance of battery clusters degrades usable capacity and accelerates aging in large-scale Battery Energy Storage Systems (BESS). This paper proposes an Inter-Battery-Cluster Equalization Power Converter (IBCEPC) and new modulation method based on Four-Switch Buck-Boost (FSBB). First, the converter’s topology and a new modulation method are analyzed, enabling flexible energy transfer among battery clusters. Then, the conditions and mechanisms for achieving zero-voltage switching (ZVS) without high-bandwidth and high-precision sampling circuits are analyzed across a wide voltage range. The strategy also incorporates inter-battery-cluster equalization to improve conversion efficiency. Furthermore, a smooth transition among constant current (CC), constant power (CP), and constant voltage (CV) modes is developed to ensure stable battery cluster operation without current or voltage overshoot. Finally, experimental results show that the proposed scheme achieves high efficiency, fast response, and smooth switching in inter-battery-cluster equalization applications.
This paper proposes a low-voltage source powered wireless mains-voltage-level DC motor with bidirectional rotation capability. The mains-voltage-level DC motor under full load can be wirelessly driven by a low-voltage source, with fully primary-controlled speed and rotational direction. A novel secondary-side polarity-reversible voltage multiplier (PRVM) is proposed to simultaneously achieve voltage step-up and voltage polarity reversal for the mains-voltage-level DC motor, without requiring secondary-side signal coils, transformers, high-frequency isolated gate drivers, isolated auxiliary power supplies, or microcontroller units (MCUs). Furthermore, it is demonstrated that among all basic compensations, the series-parallel (SP) compensation is best suited for the wireless power transfer (WPT) module in this work considering PRVM characteristics. Among existing wireless DC motor examples, this system offers superior experimental records of 254.22-V motor terminal voltage and 10.6 voltage gain, with an efficiency of 84.43%. The efficiency of proposed PRVM reaches 95.80%, coupled with zero isolation complexity and a power density of 1.2112 W/cm3.
High-performance control of high-speed Permanent Magnet Synchronous Motors (PMSMs) requires precise rotor position feedback. The Embedded Magnetic Encoder (EME) based on linear Hall sensors offers a cost-effective, compact, and mechanically decoupled solution. However, non-ideal flux distributions inside the motor induce severe multi-frequency harmonic distortion in the Hall output signals. The Multiple Complex-Coefficient Filter (MCCF), serving as a pre-filter for the synchronous reference frame phase-locked loop (SRF-PLL), can effectively suppress these harmonics to improve angle estimation accuracy. Nevertheless, its digital implementation over a wide-speed range remains unclear, limiting its application in high-speed drives. This paper bridges this gap through a systematic investigation with two contributions. First, a comprehensive multi-dimensional comparison of discretization methods is conducted for wide-frequency MCCF, identifying Tustin with Pre-warping (TP) as the optimal scheme to minimize frequency warping and ensure zero steady-state phase error. Second, to overcome the instability caused by the inherent one-beat feedback delay in the digital loop at high speeds, a regularized complex-ratio compensation method is proposed. This strategy effectively compensates the delay-induced phase lag without relying on external model parameters. Experimental results demonstrate that the combined approach of TP discretization and delay compensation significantly outperforms conventional methods, effectively eliminating harmonic distortion and substantially improving both position estimation accuracy and system stability under high-speed conditions.
