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In a hybrid-inverter open-winding permanent magnet synchronous motor (OW-PMSM) drive, the motor and the floating capacitor are controlled simultaneously. Besides, since the compensatory inverter barely provides active power under steady-state operation, the unity power factor control (UPFC) of the main inverter (MI) is also required. However, the conventional model-based predictive control of the hybrid-inverter OW-PMSM is highly sensitive to the accuracy of parameters, including the floating capacitance and stator inductance. Serious current distortions and system oscillations appear when the model parameters are mismatched with the actual ones. In addition, unmodeled parts such as power switch voltage drops and disturbances also degrade the system performance. Hence, a linear disturbance observer (LDO) based model-free predictive control (MFPC) is put forward. By using ultralocal models to substitute the mathematical models of the floating capacitor and OW-PMSM, the proposed scheme maintains satisfactory performance when system parameters are mismatched. Moreover, because system disturbances are obtained by LDO, the tracking errors can be eliminated even when parameters of ultralocal model are less appropriate. Thus, high precision of UPFC for the MI is guaranteed. Finally, experiments are carried out on a 500 W hybrid-inverter OW-PMSM drive, proving the superiority and effectiveness of the proposed MFPC strategy.

The precision of motor parameters directly affects the control performance of SynRMs drive system. Currently, high-frequency injection methods often generate noise and are unsuitable for high-power and low carrier wave ratio scenarios. Meanwhile, model-based methods can only identify the saturation characteristics of the Ld without calibration bench loading. This letter proposes an identification method based on a novel active flux observer orientation, which does not require high-frequency injection or calibration bench loading to identify the saturation characteristics of dq-axis inductance. During identification Ld, the active flux observer adopts d-axis orientation and identifies the saturation values of Ld by applying different id. When identifying the Lq, the active flux observer adopts negative q-axis orientation, and the output of the speed loop is used as the input for the d-axis current loop. By applying different iq, the saturation values of Lq are identified. Experimental results show the validity of the proposed method.

To achieve improved multinode temperature estimation with limited training data in permanent magnet synchronous motors, a novel approach of a lumped-parameter thermal network (LPTN) informed neural network is proposed in this article. First, the parameter and model uncertainties of third or higher order LPTNs with global parameter identification for temperature estimation are systematically stated based on numerical analysis. Then, a two-step parameter identification strategy for a third-order LPTN with simplified thermal transfer paths is proposed to resolve parameter uncertainty. This strategy uses only air-gap structure information to make all parameters converge to their unique solutions without the need for additional geometrical parameters or material features. In response to model uncertainty, an LPTN-informed long short-term memory (LSTM) framework is designed to compensate for model unaccounted errors and extend temperature estimation nodes that the highly abstract low-order LPTN does not consider. Experimental temperature estimation results validate the effectiveness of the proposed LPTN-informed LSTM framework under a limited 23.8 h of training data.

Accurate position observation in interior permanent magnet synchronous motors (IPMSMs) model-based sensorless drive relies on the precision of model parameters. This article first derives an analytical function that quantitatively relates position observation error to mismatches in multiple model parameters and the current lead angle in one unified equation. The position error mechanism highlights the potential limitations of relying solely on steady-state-based parameter estimation. It also emphasizes the importance of introducing current transient states for online multiparameter estimation. To reduce the position observation error caused by parameter mismatch, a multiparameter estimation method with extra small signal injection based on the dual extended Kalman filter with a position error prior prediction structure is proposed for the IPMSM sensorless drive. The method is built upon the misaligned synchronous frame model where the asymmetry in dq-axis magnetic path, flux coupling terms, and position observation error are well considered. This makes the proposed method effective for both steady and transient states within the rated speed. Additional experiments corroborate both the validity of the analysis and the effectiveness of the proposed technique.

This article proposes an improved hybrid desaturation detection circuit for switching devices, which aims to accelerate the short-circuit (SC) protection for the bridge leg in power converters. The proposed hybrid detection circuit not only retains the linear charging rate of the blanking capacitor voltage like the current source detection circuit, but also obtains the circuit parameters’ adjustment capability like the voltage source detection circuit. The mapping between the detected desaturation voltage and the terminal voltage of the semiconductor device can be modified by the proposed solution. Thus, for bridge leg phase SC with a slow current change rate, the proposed circuit can appropriately set the detection threshold to fit the maximum operating current, thereby shortening the peak value and duration of the SC current. Furthermore, the proposed circuit can decouple the detection speed configuration of fault-under-load (FUL) and hard-switching-fault (HSF) states without adding additional detection circuits. Thus, it can accelerate the detection of FUL without shortening the blanking time of HSF, and therefore the shoot-through SC fault of the entire bridge leg can be quickly cutoff. Experimental results verify that the proposed circuit can effectively accelerate the detection and protection process of bridge leg SC faults.

The article proposes a multiobjective optimization procedure for a dual active bridge (DAB) converter based on nondominated sorting genetic algorithm with back propagation (BP) neural network embedded in back propagation nondominated sorting genetic algorithm (BP-NSGA-II), where the BP neural network was used to predict the vibration of power electronic transformer (PET). Experimental results demonstrate the high accuracy of this neural network in vibration fitting of PET. Based on the offline trained neural network, the phase-shift angles corresponding to minimum vibration is found in the triple phase-shift mode of DAB. Compared with common phase-shift modes at the same transmission power level, the optimized method could effectively reduce the vibration amplitude of PET at the key frequency with more than 20 dB. Meanwhile, the vibration amplitude at the concerned frequency of the optimized method is smaller than that of all the training sets. Furthermore, in BP-NSGA-II, the current stress, reflow power, and vibration of PET are used as objective functions to optimize the operating state of DAB further. The experimental results show that the proposed multiobjective optimization method, based on BP-NSGA-II, can improve the performance of the DAB converter by reducing its current stress and reflow power while suppressing the vibration amplitude of PET.

To improve the reliability and continuous navigation of ship propulsion, a magnetic variable speed diesel–electric hybrid motor with auxiliary teeth for ship propulsion is proposed in this article. The inner rotor permanent magnet of the motor adopts an eccentric structure and is magnetized by the Halbach array. The auxiliary teeth are inserted into the stator, which not only has the function of magnetic regulation but also can realize phase-to-phase isolation. Moreover, it can increase the reliability of the motor. The working modes of the motor in the marine propulsion system mainly include diesel engine driving mode, electric propulsion mode, and hybrid propulsion mode. In this study, finite element software is employed to build the motor's parametric model. According to the results of comprehensive sensitivity analysis, the electromagnetic torque and torque ripple are optimized by combining evolutionary algorithm and response surface method. Finally, a prototype is manufactured and an experimental platform is built. The experimental results show that the motor exhibits excellent dynamic response performance, a small torque ripple, a good sinusoidal back electromotive force, and low loss.

Benefited from flux modulation effects, permanent magnet Vernier machines (PMVMs) have the advantage of high torque. Generally, the higher pole-pair ratio (PR), i.e., PM pole-pair to armature winding pole-pair, the stronger flux modulation effects, as well as the higher torque. However, PMVMs with high PR suffer from low power factor due to the parasitic large inductance. This article is devoted to propose a low PR integration design approach of PMVMs to achieve the high average torque and power factor simultaneously. According to exploit multiple working harmonics with low PRs, not only the high power factor and low inductance characteristic can be maintained, but also the average torque and flux modulation effects can be strengthened. Further, the stator flux barrier has been added to restrict the parasitic no-working harmonics with high PRs. Based on these, two PMVM design examples with different slot/pole combinations are constructed and analyzed to verify the effectiveness of the proposed design approach. Finally, a prototype is manufactured and experimented. It is showed that under electric loading 320 A/cm, the active volume torque density of proposed PMVM can be up to 33.4 N·m/L, which is comparable to regular PMVM with high PR 8, while power factor can be improved from 0.63 to 0.8.

As one type of flux modulation machines, flux-switching permanent magnet (FSPM) machines present high sensitivity to airgap structures. Therefore, both stator/rotor teeth and slot/pole combinations have significant influences on machine performance. However, the relationships between the optimal stator structure and maximum torque capability of the FSPM machine are barely investigated. Therefore, in this article, we are devoted to proposing a directional stator permeance design approach to achieve the maximum torque of the FSPM machines under a given rotor and reveal the corresponding stator structure. First, the relations between torque and air-gap permeance are presented based on a constructed torque contribution equation, where amplitudes and phase angles of the stator permeance harmonics are determined. Then, main permeance harmonics are directionally optimized to enlarge positive torque while negative contributions are inversed to be positive. Especially, two FSPMs with 6-slot/19-pole and 6-slot/13-pole are chosen as design examples, and their optimal design processes and torque performances have been deeply analyzed, which verifies the effectiveness of the proposed design approach.

Short-circuit faults in permanent magnet (PM) machines have consistently been a hindrance for safety-critical applications. However, short-circuit currents, especially turn-to-turn short-circuit currents, are difficult to detect and suppress in a timely manner. This article investigates the automatically variable impedance characteristics of the toroidal winding, which restricts the turn-to-turn short-circuit current to an allowable level without terminal short circuit. An analytical model considering the saturation effect of toroidal winding is proposed to reveal the fault tolerance mechanism as well as the mapping relationship between yoke-annular-leakage and fault-tolerant performance. It is found that variable impedance PM machines with toroidal winding have superior fault tolerance performance compared to conventional fractional-slot concentrated-winding and lap winding. Besides, there is a contradictory relationship between its fault tolerance and electromagnetic performance. Furthermore, the laws of phase belt angle and pole number on the electromagnetic and fault-tolerant performance of toroidal winding are first presented in this article. The design criteria and the feasible pole-slot combinations that have inherent fault-tolerant capability are given. Finally, the prototype is built and tested. The experimental results match well with the analytical ones.