IEEJ Transactions on Electrical and Electronic Engineering最新文献

In view of the problem of large torque ripple and poor output performance of permanent magnet synchronous motor, a new topology of asymmetric magnetic pole permanent magnet synchronous motor is proposed, and the torque ripple of this motor structure and the suppression method are analyzed. First, the equivalent magnetic circuit method and Lorentz force law are used to derive the analytical formula of torque ripple of the motor. Then, based on the analytical formula, the parameters of permanent magnet of the asymmetric magnetic pole permanent magnet synchronous motor are optimized and verified by finite element software simulation; on this basis, the method of rotor eccentricity is used to further weaken the torque ripple of the motor, and the optimal eccentricity distance is analyzed. The research shows that when the parameters of the magnetic pole of the asymmetric magnetic pole permanent magnet synchronous motor is appropriate, the harmonic content of the air gap magnetic density of the optimized motor is greatly reduced, and the motor has good output characteristics, and the torque ripple is reduced to 5.4%. Finally, the prototype is trial-manufactured and tested. The results show that after optimization, the cogging torque of the motor is reduced, the torque output performance is improved, and the overall motor performance is improved. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

With access to many power electronic loads in a power network, the number of suspicious harmonic sources increases significantly, which makes it highly difficult to trace the position of such sources in the entire network. Starting from the engineering application of harmonic tracing and using power quality monitoring data, a harmonic zoning tracing scheme is proposed based on two-layer clustering. Based on the characteristics of harmonic measurement data, k-Shape, a time-series clustering algorithm based on waveform similarity is adopted. By calculating the morphological distance between the harmonic voltage sequences, the similarity of data fluctuation is measured, and the correlation information associated with harmonic pollution is mined. On this basis, adaptive density peak clustering is introduced to improve the k-Shape algorithm. It solves the local minimization problem caused by the random selection of initial clustering centers, and realizes the adaptive selection of the optimal number of clusters. The proposed method can effectively realize the regional positioning of multi-harmonic sources, reduce the suspected range of dominant harmonic sources, and is suitable for traceability analysis in the scenario of a large number of harmonic sources. The IEEE 123 node network and monitoring platform data confirm the practicality and effectiveness of the proposed method. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Various mainstream target tracking algorithms based on Siamese networks are gradually becoming a trend in the field of deep learning tracking due to their concurrent advantages of accuracy and speed. Most Siamese network-based trackers describe the tracking of a target object as a similar matching problem, and these trackers have achieved more advanced performance in several public tests. Most trackers often suffer from tracking drift or performance degradation owing to the non-updating of the template in the first frame and the target appearance encounters disturbing environments such as occlusion and drastic deformation. Therefore, to address this problem, this paper introduces a template updating mechanism and proposes a refine structure network based on the template updating of Siamese networks as well as the greater similarity of target features in two adjacent frames, which improves the tracking accuracy while limiting the amount of computation using an anchor-free method in order not to lose the tracking speed, and only needs to be trained by selecting the most suitable pre-training network, thus greatly reducing the amount of network computation. Meanwhile, in the application of the refine structure, with the aim of making the weight design of the target localisation module more reasonable, we propose a new Refine Head section and analyze and design the update threshold to optimize the overall network. This method is practiced in SiamFC++ algorithm, which firstly designs the template refine module, inputs the image that needs to be improved, and then outputs it to the Refine Head to complete the template update and applies it to the tracking of the subsequent frames, thereby constituting the SiamTRN (Template-Refine Network). According to the experiments, the improved structure of the method can effectively implement the refine module function and enhance the performance of the tracker on public datasets, such as OTB100, VOT2016, UAV123 and GOT-10 k. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Effective load current distribution is a fundamental aspect of ensuring a stable and efficient DC microgrid operation particularly when utilizing dual active bridge converters. In order to construct an improved piecewise setpoint, this research involves a thorough analysis of the statistical distribution of load profiles and the intrinsic properties of a two-segment piecewise droop controller. Furthermore, a thorough comparison analysis of linear and exponential droop-based approaches is carried out in this paper. To assess the proposed two-segment piecewise droop controller, several simulations and hardware-in-loop scenarios are carried out. Additionally, the conventional discrete piecewise droop control method is compared with the proposed method. Notably, with the proposed method, paralleling dual active bridge converters in a DC microgrid clearly demonstrates a significant improvement in current sharing within a specific operating range. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

With the development of high-voltage direct current (HVDC) engineering around the world, there has been increasing attention to the issue of selecting site for direct current (DC) grounding electrodes since the pollution coming from ground potential and electric field. As previous study result, the distance is closer to the grounding electrode, the influence is greater for ground potential and electric field, as well as vice versa. Through proposing the analysis approach of equivalent interfacial charge accumulating, the article goes beyond this previous general-conclusion and extracts the relative position conception from the mono-distance for further studying on weakening their impacts on the environment. In comparison with the previous results, the research finding shows that the movement of relative position is able to achieve the best distribution of ground potential or electric field corresponding to different soil-layered structure, furthermore, the specific mathematic formula about the best relative position has been derived by the accumulated charge model proposed. Finally, the results have been demonstrated by simulation calculation of the CDEGS software for a practical HVDC project in China, moreover, regarding soil resistivity variation related to the different seasons, the optimized relative position about 13 ~ 24 km has been adopted in the real HVDC grounding project as a suggested site. It reveals that the underlying relative position behind the mono-distance could be applied to selecting the site of grounding electrode as reference in the future. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

In order to reduce the torque ripple and the unbalanced electromagnetic force on the rotor of the dual-parallel rotor permanent magnet motor, a dynamic Kriging surrogate model is proposed to optimize its structural parameters. In the process of constructing the dynamic Kriging surrogate model, the concept of key sampling space is introduced, which solves the problems of low optimization efficiency and poor model accuracy of the traditional static surrogate model based on ‘one-time’ sampling. The topological structure of the dual-parallel rotor permanent magnet motor is introduced, and a prototype is used to verify the accuracy of the numerical model. The optimization parameters are determined, and the initial sampling space of each optimization parameter is determined according to the influence law of a single parameter on the optimization objectives. The initial sample database of the Kriging surrogate model is established, and a dynamic criterion for adding sample points is proposed. Combined with the NSGA-II algorithm, the surrogate model is constructed and solved. The optimal solution is substituted into the numerical model, which verifies the feasibility and correctness of the proposed optimization design method. The accuracy of the dynamic Kriging surrogate model is discussed and compared with the traditional static surrogate model. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

In monitoring transmission line external damage prevention, due to the limited memory computing power of the equipment, the image needs to be transmitted to the data center at regular intervals, resulting in a high false negative rate. Therefore, this paper proposes a target detection method based on lightweight YOLOv5s. First, DSConv and improved E-ELAN are used in Backbone to reduce the model's parameters. Then, GSConv and VoV-GSCSP are introduced in Neck to reduce the complexity of the model. Finally, the Mish activation function achieves more effective feature transfer. According to the experimental findings, the proposed model's parameters are about 37% smaller than the original model's, and the calculation amount is about 53% smaller. The detection accuracy on the self-built data set is the same, which proves that the proposed algorithm can reduce the model while maintaining high detection performance. It has specific practical significance for the terminal real-time detection of external mechanical damage targets. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

To further improve the operating efficiency of linear induction motor, this paper proposes a loss minimization model predictive current control method based on governable loss online calculation. First, the method derives the equivalent circuit of linear induction motor containing independent iron loss branches, and establishes the loss model containing iron loss. Second, the expressions of stator d-axis current with governable losses and secondary flux amplitude are derived from theoretical analysis, and then a given value of stator d-axis current is derived when the governable losses are minimal. Then, a chain observer is designed to observe the secondary flux and calculate the governable loss and stator d-axis current under the current operation. Finally, a method is proposed to introduce the stator d-axis current observation results into the model predictive current control, which ensures the loss suppression effect and improves the dynamic performance at the same time. In addition, this article also compares the loss minimization controllers with or without iron loss. The simulation results are consistent with the theory, and the optimal control of the secondary flux of the linear induction motor can be successfully realized, thus effectively reducing the energy loss of the motor in the dynamic operation process. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.