Search Results (112)

Tidal energy, as a stable and predictable renewable energy source, is garnering increasing attention. However, tidal energy generation faces challenges such as low energy conversion efficiency and high mechanical losses in low-velocity environments. To address these issues, this paper proposes a novel design for a tidal energy generator based on an axial field coreless structure. This design significantly reduces mechanical losses and enhances energy conversion efficiency by employing a direct-drive structure and a coreless stator. Additionally, the introduction of a Halbach array permanent magnet and soft magnetic composite further optimizes the generator’s electromagnetic performance, thereby increasing power output. Simulation results demonstrate that the designed generator can achieve a power output of 300 W at a tidal velocity of 1.8 m/s, with an average generation efficiency of 90.6%. This design exhibits excellent performance in low-velocity tidal environments and provides valuable technical support for the design of tidal energy generators. Full article

Thanks to the magnetic field modulation effect, the magnetic field modulation motor (MFMM) significantly improves torque density and magnetic field harmonic utilization by breaking the constraints of traditional motor excitation and armature pole number matching. This advantage enhances its development potential in fields such as new energy vehicles, aerospace, power generation, and the military. This article first starts with the basic principle of magnetic field modulation, and adopts the excitation unit position classification method to systematically summarize the evolution laws of major MFMM topology structures such as the permanent magnet synchronous motor, switch magnetic flux motor, and flux reversal motor in recent years. It also analyzes the research progress of key performance such as the torque characteristics and power factor of these motors. Research has pointed out that the MFMM still faces core challenges such as high torque ripple, complex structure, low power factor, and multiple losses. Based on a review of the main achievements in the field, the future development direction of MFMMs is proposed to promote its development in the fields of precision drive and efficient energy conversion. Full article

Direct-drive permanent magnet synchronous machines (DDPMSMs) have recently become an ideal candidate for applications such as military, robotics, electric vehicles, etc. These machines eliminate the need for a transmission mechanism and excitation coil circuits, which enhances the system’s overall efficiency and decreases the likelihood of failures. However, it may incur demagnetization faults. Due to the characteristic of having a large number of pole pairs, this type of machine exhibits numerous demagnetization fault modes, which poses a challenge in locating demagnetization faults. This paper proposed a probabilistic neural network (PNN)-based diagnostic system to detect and locate demagnetization faults in DDPMSMs, using information obtained through three toroidal-yoke-type search coils arranged at the bottom of the stator slot. A rotor partition method is proposed to solve the problem of demagnetization fault location difficulty caused by various fault modes. Demagnetization fault location is achieved by sequentially diagnosing the condition of each partition of permanent magnets. Three demagnetization fault identified signals (DFISs) are constructed by the voltage of the three toroidal-yoke coils, which are used as inputs of PNNs. Three PNNs have been designed to map the extracted features and their corresponding types of demagnetization faults. The database for training and testing the PNNs is generated from a DDPMSM with different demagnetization conditions and different operating conditions, which are established through an experimentally validated mathematical model, an FEM model, and experiments. The simulation and experimental test results showed that the accuracy in diagnosing the location of the demagnetization fault is 99.2% when the demagnetization severity is 10%, which demonstrates the effectiveness of the proposed three PNN-based diagnostic approach. Full article

The drive system of an electric car must meet road requirements related to overcoming obstacles and driving dynamics depending on the class and purpose of the vehicle. The driving dynamics of modern cars as well as size and weight limitations mean that wheel hub motors operate with relatively high current density and high power supply frequency, which may generate significant power losses in the windings and permanent magnets and increase their operating temperature. Designers of this type of motor often face the need to minimize the motor’s weight, as it constitutes the unsprung mass of the vehicle. Another limitation for motor designers is the motor dimensions, which are limited by the dimensions of the rim, the arrangement of suspension elements and the braking system. The article presents two directions in the design of wheel hub motors. The first one involves minimizing the length of the stator magnetic core, which allows for shortening of the axial dimension and mass of the motor but involves increasing the thermal load and the need for deeper de-excitation. The second one involves increasing the number of pairs of magnetic poles, which reduces the mass, increases the internal diameter of the motor and shortens the construction of the fronts, but is associated with an increase in the motor operating frequency and increased power losses. Additionally, increasing the number of pairs of magnetic poles is often associated with reducing the number of slots per pole and the phase for technological reasons, which in turn leads to a greater share of spatial harmonics of the magnetomotive force in the air gap and may lead to the generation of higher power losses and higher operating temperatures of permanent magnets. The analysis is based on a simulation of the motor operation, modeled on the basis of laboratory tests of the prototype, while the car is driving in various driving cycles. Full article

Cold energy generation is an important part of liquefied natural gas (LNG) cold energy cascade utilization, and existing studies lack a specific descriptive model for LNG cold energy transmission to the AC subgrid. Therefore, this paper proposes a descriptive model for the grid-connected process of cold energy generation at LNG stations. First, the expansion kinetic energy transfer of the intermediate work mass is derived and analyzed in the LNG unipolar Rankine cycle structure, the mathematical relationship between the turbine output mechanical power and the variation in the work mass flow rate and pressure is established, and the variations in the LNG heat exchanger temperature difference, seawater flow rate, and the turbine temperature difference in the cycle system are investigated. Secondly, based on the fifth-order equation of state of the synchronous generator, the expressions of its electromagnetic power, output AC frequency, and voltage were analyzed. Finally, the average equivalent models of the machine-side and grid-side converters are established using a direct-fed grid-connected structure, thus forming a descriptive model of the overall drive process. The ORC model is built in Aspen HYSIS to obtain the time series expression of the torque output of the turbine; based on the ORC output torque, the permanent magnet synchronous generator (PMGSG) as well as the direct-fed grid-connected structure are built in MATLAB/Simulink, and the active power and current outputs of the grid-following-type voltage vector control method and the grid-forming-type power-angle synchronous control method are also verified. Full article

When wind turbines contribute to system frequency support using virtual synchronous generator (VSG) control, conventional VSG methods often fall short of meeting operational demands, particularly in terms of inertia and frequency support. In this study, considering both the frequency regulation and dynamic performance of VSG, a novel parameter design method that enhances frequency modulation capabilities is proposed in this paper. Initially, VSG control is integrated into the grid-side converter of a direct-drive permanent magnet synchronous generator (D-DPMSG) wind turbine. A small-signal model of the D-DPMSG-VSG active power is then formulated to analyze how the moment of inertia and damping coefficient impact system stability. Subsequently, ensuring that system parameter constraints are met, the key parameters of VSG are adaptively designed to dynamically adjust the system’s frequency and output power during transient responses. Finally, simulation results based on D-DPMSG-VSG in MATLAB/Simulink validated the feasibility, effectiveness, and advantages of the proposed parameter-adaptive VSG control strategy for enhancing the frequency modulation (FM) performance of wind turbines. Full article

Dual-port direct drive wave energy power generation systems (DP-DDWEPGS) have received widespread attention due to their smooth and zero-free output power, compared to single-port direct drive wave energy power generation systems (SP-DDWEPGS) which have the disadvantage of large out-put power fluctuations. To further enhance the performance of the DP-DDWEPGS, optimal power capture control is proposed to achieve maximum power point tracking. Meanwhile, a multiport converter is applied to the DP-DDWEPGS to solve the problem caused by an excessive number of switching devices in the overall system converter. The multiport converter fulfills all the functional requirements of the DP-DDWEPGS while reducing the number of switching devices. However, switch multiplexing of the multiport converter also introduces coupling relationships between each port and the wave force exhibits time-varying characteristics, necessitating advanced control methods with superior fast-tracking capability. Therefore, in this paper, a decoupling duty cycle optimization model predictive control for DP-DDWEPGS is proposed. Based on the characteristics of switching multiplexing, NSC finite control set model predictive control (FCS-MPC) decouples the current prediction and the cost function, reduces the number of candidate voltage vectors in each operation, and shortens the operation time by 70%. To address the issues of high ripple value and increased error due to decoupling in FCS-MPC, duty cycle optimization control is added, greatly reducing the fluctuations in electromagnetic force and power of the permanent magnet linear generator (PMLG). Based on the established simulation model, the feasibility and superiority of the multiport converter and decoupling duty cycle optimization model predictive current control method are verified. Full article

An integrated structural optimization strategy was produced in this study for direct-drive electrical generator structures of offshore wind turbines, implementing a design for an additive manufacturing approach, and using generative design techniques. Direct-drive configurations are widely implemented on offshore wind energy systems due to their high efficiency, reliability, and structural simplicity. However, the greatest challenge associated with these types of machines is the structural optimization of the electrical generator due to the demanding operating conditions. An integrated structural optimization strategy was developed to assess a 100-kW permanent magnet direct-drive generator structure. Generated topologies were evaluated by performing finite element analyses and a metal additive manufacturing process simulation. This novel approach assembles a vast amount of structural information to produce a fit-for-purpose, adaptative, optimization strategy, combining data from static structural analyses, modal analyses, and manufacturing analyses to automatically generate an efficient model through a generative iterative process. The results obtained in this study demonstrate the importance of developing an integrated structural optimization strategy at an early phase of a large-scale project. By considering the typical working condition loads and the machine’s dynamic behavior through the structure’s natural frequencies during the optimization process coupled with a design for an additive manufacturing approach, the operational range of the wind turbine was maximized, the overall costs were reduced, and production times were significantly diminished. Integrating the constraints associated with the additive manufacturing process into the design stage produced high-efficiency results with over 23% in weight reduction when compared with conventional structural optimization techniques. Full article

The design optimization of a direct-drive permanent magnet synchronous generator (DDPMSG) is of great significance for wind turbines because of its unique advantages. This paper proposes a two-stage model to realize multi-objective design optimization for a 6 MW DDPMSG. In the first stage, a surrogate optimized response surface model based on an improved sparrow search algorithm (ISSA) was established for modeling the cogging torque and generator efficiency. In the second-stage model, a multi-objective optimization model is proposed to optimize the cogging torque and generator efficiency of the DDPMSG. Finally, the proposed two-stage model was used for a 6 MW DDPMSG design optimization, and the simulation results demonstrated the superiority and rationality of the proposed model. In the first-stage model, the proposed surrogate model based on the ISSA had a better modeling accuracy and lower errors. Compared with traditional response surface models and correlation analysis models, the proposed optimized surrogate model reduced errors in the cogging torque by 34.63% and 42.97%, respectively, while the errors in the efficiency models were reduced by 12.92% and 60.78%, respectively, which indicates the superiority of the first-stage model. In the second stage, compared with the single-objective optimization model, the multi-objective optimization model achieved a trade-off optimization between the cogging torque and the efficiency. Compared with the cogging torque optimization model, the proposed model optimized the efficiency by 101.41%. Compared with the efficiency optimization model, the proposed model reduced the cogging torque by 16.67%. These results verified the superiority and rationality of the second-stage model. Full article

Magnetic microgrippers, with their miniaturized size, flexible movement, untethered actuation, and programmable deformation, can perform tasks such as cell manipulation, targeted drug delivery, biopsy, and minimally invasive surgery in hard-to-reach regions. However, common external magnetic-field-driving devices suffer from low efficiency and utilization due to the significant size disparity with magnetic microgrippers. Here, we introduce a microgripper robot (MGR) driven by end electromagnetic and permanent magnet collaboration. The magnetic field generated by the microcoils can be amplified by the permanent magnets and the direction can be controlled by changing the current, allowing for precise control over the opening and closing of the magnetic microgripper and enhancing its operational range. Experimental results demonstrate that the MGR can be flexibly controlled in complex constrained environments and is highly adaptable for manipulating objects. Furthermore, the MGR can achieve planar and antigravity object grasping and transportation within complex simulated human cavity pathways. The MGR’s grasping capabilities can also be extended to specialized tasks, such as circuit connection in confined spaces. The MGR combines the required safety and controllability for in vivo operations, making it suitable for potential clinical applications such as tumor or abnormal tissue sampling and surgical assistance. Full article

Renewable energy resources are playing a crucial role in minimizing fossil fuel emissions. Integrating machine learning techniques with tidal power forecasting could greatly enhance the accuracy and reliability of predictions, which is crucial for efficient energy production and management. A hybrid approach combining different methods often yields better results than relying on individual techniques. The accuracy of tidal current power is very important, especially for smart grid applications. This work proposes hybrid adaptive neuro-fuzzy inference system (ANFIS) with the Kalman filter (KF) and a neuro-wavelet (WNN) for tidal current speed, direction, and power forecasting. The turbine used in this study is driven by a direct drive permanent magnet synchronous generator (DDPMSG). The predictions of individual and hybrid models including the ANFIS, the Kalman filter, and the WNN for tidal current speed and the power it generates are compared with another dataset as a way of validation which is the tidal currents direction. Also, other published work results in the literature are compared to the proposed work. Different hybrid models are proposed for smart grid integration. The results of this work indicate that the hybrid model of the WNN and the ANFIS for tidal current power or speed forecasting has the highest performance compared to all other models. Full article

The grid interconnections for direct-drive wind farms have triggered multiple new sub-synchronous oscillation events, which can prevent the power system from operating safely and stably. However, the excessively high order of the detailed model for large-scale wind farms with multiple direct-drive permanent magnet synchronous generators (PMSGs) connected to power systems poses a challenge when investigating small disturbance stability and instability mechanisms. This study establishes a model of the grid-connected PMSG system based on the voltage/power excitation–response relationship to describe the dynamic characteristics of the port of the PMSG, and the analysis of active and reactive response characteristics of PMSG lays the foundation for model simplification. Based on the unit model, a direct-drive wind farm aggregation equivalence method based on the excitation–response relationship is proposed. The equivalent model obtained by this method is suitable for the small disturbance stability analysis of direct-drive wind farms grid connected system, with good accuracy. The simulation verified the effectiveness of the aggregation model. Full article

Interior permanent magnet synchronous machines (IPMSMs) driven with a square-wave control (i.e., six-step, block, or 120° control), known commonly as brushless direct current (BLDC) drives, are used widely due to their high power density and control simplicity. The advance firing (AF) angle is employed to achieve improved operation characteristics of the drive. The AF angle is, in general, applied to compensate for the commutation effects. In the case of an IPMSM, the AF angle can also be adjusted to exploit reluctance torque. In this paper, a detailed study was performed to understand its effect on the drive’s performance in regard to reluctance torque. Furthermore, a multi-objective optimization of the machine’s cross-section using neural network models was conducted to enhance performance at a constant AF angle. The reference and improved machine designs were evaluated in a system-level simulation, where the impact was considered of the commutation of currents. A significant improvement in the machine performance was achieved after optimizing the geometry and implementing a fixed AF angle of 10°. Full article

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability. Full article

The article presents the issues related to load-power sharing in direct-current grid and a novel control method has advantages over known solutions. Unlike many similar-sounding papers, this article shows an attempt at creating fully controllable non-isolated system that allows for load-power sharing between a permanent magnet alternator equipped with machine-side converter (MSC) and a dual active bridge (DAB) tied to batteries or supercapacitor. The current-based load-power sharing is an essential feature of parallel-connected direct-current generators, and all types of voltage sources, in this way are contributing power to the system. To keep the optimal efficiency of the alternator, the rotational speed changes rely on proper mapping of the driving combustion engine. System components include a self-excited synchronous generator (SESG), operating at variable shaft speed, as well as batteries and supercapacitors that provide electricity for sudden electrical-load changes on the distribution grid. The core of the presented system is in a power-distribution method that consists of a programmed-controller structure allowing precise current distribution. A novelty of the proposed method is the use of a cascaded system of current and DC voltage regulators that allows for precise power-distribution control. In contrast with previously presented solutions, the proposed system allows for fast and accurate control of currents, loading parallel-connected DC voltage sources for wide-range generator speed changes. In the presented solution, both converters have been equipped with Schottky diodes, preventing the flow of equalizing currents between closed transistors in the parallel mode of operation. An experimental test-stand of the described system is presented with its theoretical basis and experimental results. Full article