Yao Chen

To meet the dual requirements of selectivity and rapidity in fuse-based short-circuit protection for shipboard DC Integrated Power Systems (DC IPS), this paper proposes a novel coordination method. This approach employs an artificial neural network (ANN) to map the inherent time–current characteristic (TCC) curves of all fuses onto a unified time–current coordinate plane. Protection selectivity is then evaluated based on the relative positions of these curves, and by prioritizing fuses with shorter operating times, both selectivity and rapid fault clearance are achieved. Furthermore, through a mathematical analysis of the current relationships between faulted and non-faulted distribution circuits, the ANN is formulated to require only current and time data while maintaining robustness to moderate variations in short-circuit transition resistance. The effectiveness of the proposed method is validated using DC IPS cases of a hybrid passenger vessel and a pure electric sightseeing vessel. Compared with conventional coordination methods, the proposed method simultaneously accounts for the TCCs of protective devices and the influence of transition resistance on short-circuit current behavior. The case study results demonstrate that the proposed method achieves both selective and rapid protection, and shows strong potential for broader application in the coordination of multi-source DC power systems.

The magnetic flux distribution of 12/14 BSRM creates dynamic variations across the stator-rotor air gap during rotor rotation. Consequently, the electromagnetic suspension force depends not only on the control current and the displacement of rotor but also varies with the angular position of the rotor, manifesting distinct time-varying nature. The time-varying suspension system faces issues, such as lower suspension accuracy and reduced resistance to disturbance. This article proposes a control strategy based on a nominal feedback model (NFM) and an adaptive Kalman filter observer (AKFO). The core idea of the proposed control strategy is to equivalently convert the time-varying suspension system into a time-invariant suspension system. Specifically, a dual closed-loop control system is designed for the time-varying suspension force, incorporating NFM independent of rotor position and AKFO. The NFM facilitates the design of a double closed-loop, while the AKFO can compensate for the discrepancy between the NFM and the real time-varying suspension force model. The performances of the proposed strategy and traditional strategy are compared through simulations and experiments.

The harsh marine environment often leads to bearing erosion and damage to propulsion motors. The single-winding bearingless flux-switching permanent magnet motor (BFSPMM), which operates without mechanical bearings, provides notable advantages, including frictionless operation, long service life, high back-EMF sinusoidal quality, and superior efficiency. But the BFSPMM faces significant challenges due to the strong coupling between its torque and suspension controls, as well as the speed-frequency ripple in rotor radial displacement, which severely impacts mechanical transmission performance. This paper proposes a suspension flux control strategy based on a model-compensated repetitive controller. A mathematical flux linkage model incorporating rotor dynamic eccentricity is developed, establishing a linear relationship between rotor displacement and flux linkage. The control strategy accounts for controllable suspension forces, unbalanced magnetic pull, and speed-frequency ripple in the rotor dynamics model. It employs a repetitive controller that integrates a repetitive signal generator, a model compensator, and a least mean square notch filter to compute the desired suspension flux. To enhance accuracy, a flux observer leveraging orthogonal characteristics is designed to measure the actual suspension flux. The effectiveness of the proposed method is validated through simulations and experiments, demonstrating its superior performance in steady-state and dynamic conditions.

Single-winding bearingless flux switching permanent magnet motor (BFSPMM), characterized by its frictionless operation, maintenance-free nature, and high efficiency, holds the potential to fundamentally address the issues of bearing erosion and failure in marine propulsion motors caused by harsh oceanic environments. However, the torque and suspension forces are strongly coupled, and the radial forces are complex and variable, resulting in significant rotor displacement ripples that severely impact the performance of electric drive systems. Herein, a suspension internal model control strategy with active ripple suppression is proposed. Firstly, based on the magnetic field modulation theory, the mechanism of unbalanced magnetic pull is analyzed in detail, and the corresponding expressions are established. Then, a rotor dynamic model is derived from the differential equations of a whirl for the suspended rotor, which facilitates the construction of the BFSPMM internal model. A linear extended state observer is employed to obtain smoother displacement error signals, differential signals, and account for unmodeled dynamics. Subsequently, an inverse system model for the controllable suspension force is derived, and the internal model controller is formulated and analyzed in an innovative PD-based structure. This approach not only enhances the controller's performance but also simplifies the tuning process, requiring only two parameters to be adjusted. Finally, the performance of the proposed method is analyzed theoretically, and its effectiveness is validated through experimental verification.

The strong coupling of suspension force and torque in a single-winding bearingless flux-switching permanent magnet motor creates a complex dynamic model, complicating controller parameter tuning. The complexity and large data requirements of intelligent algorithms highlight the continued relevance of PID control, which remains dominant in high integration and low-cost applications. Consequently, research on tuning PID controllers is crucial. This paper proposes a controller parameter optimization strategy based on characteristic models. Initially, the principles governing the generation of controllable suspension force and unbalanced magnetic pull during motor operation are analyzed, leading to the development of corresponding mechanistic models. Notably, a spatially asymmetric rotor dynamic eccentricity modulation operator is introduced to accurately represent the establishment of unbalanced magnetic pull. The rotor dynamic model is then simplified, and a characteristic model for the system is established. To enhance controller parameter tuning, an online algorithm for optimization is proposed, which involves iteratively adjusting the controller parameters over a specified period, guided by the output error between the characteristic model and the actual system. This approach facilitates the determination of optimal controller parameters. Finally, experimental studies are conducted on the prototype, validating the effectiveness of the proposed method.

A suspension flux internal model control method is proposed to address the problem of the strong coupling of a single-winding bearingless flux-switching permanent magnet motor leading to a significant ripple of the rotor radial displacement. Firstly, based on air-gap magnetic field modulation theory, the stator flux equation considering rotor dynamic eccentricity is established to reveal the relationship between the eccentric rotor and the magnetic field. Secondly, according to the dynamic characteristics of the motor and the variation law of the air-gap magnetic field, the suspension-plane flux is substituted into the rotor dynamic model, and the suspension flux-dynamics internal model and corresponding output are constructed, respectively. Finally, a complete control strategy is established, and the rotor is stably suspended by PWM control. The simulation and experimental results show that the proposed method has better steady-state and dynamic performance than traditional PID control, and the maximum radial displacement ripples of the rotor are reduced by 53% and 50% in steady-state and dynamic operation.