Search Results (79)

The increasing complexity of modern control systems highlights the need for reliable and robust fault detection, isolation, and identification (FDII) methods, particularly in safety-critical and industrial applications. The study focuses on the FDII of multiplicative faults in a DC motor and its electronic amplifier. To simulate such scenarios, a complete laboratory platform was developed for real-time FDII, using relay-based switching and custom LabVIEW software 2009. This platform enables real-time experimentation and represents an important component of the study. Two estimation-based fault detection (FD) algorithms were implemented: the Sliding Window Algorithm (SWA) for discrete-time models and a modified Sliding Integral Algorithm (SIA) for continuous-time models. The modification introduced to the SIA limits the data length used in least squares estimation, thereby reducing the impact of transient effects on parameter accuracy. Both algorithms achieved high model output-to-measured signal agreement, up to 98.6% under nominal conditions and above 95% during almost all fault scenarios. Moreover, the proposed fault isolation and identification methods, including a decision algorithm and an indirect estimation approach, successfully isolated and identified faults in key components such as amplifier resistors (R₁, R₉, R₁₂), capacitor (C₈), and motor parameters, including armature resistance (R_a), inertia (J), and friction coefficient (B). The decision algorithm, based on continuous-time model coefficients, demonstrated reliable fault isolation and identification, while the reduced Jacobian-based approach in the discrete model enhanced fault magnitude estimation, with deviations typically below 10%. Additionally, the platform supports remote experimentation, offering a valuable resource for advancing model-based FDII research and engineering education. Full article

This paper proposes a vibration reduction method for fractional slot concentrated winding (FSCW) permanent magnet synchronous motors (PMSMs) by applying a four-layer winding configuration. The radial electromagnetic force (REF), particularly its low space-harmonics, causes significant vibration in PMSMs. These low-order REF components are influenced by sub-harmonics in the airgap magnetic flux density (MFD), which occur at frequencies lower than the fundamental component generated by the armature magnetomotive force (MMF) in FSCW PMSMs. To mitigate these sub-harmonics in the MFD, the four-layer winding is applied to the FSCW PMSM. As a result, the overall vibration of the motor is reduced. To verify the effectiveness of the four-layer winding, both electrical and mechanical characteristics are compared among motors with conventional one-, two-, and, proposed, four-layer windings. Finally, the three motors are fabricated and tested, and their vibration levels are experimentally evaluated. 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

This work focuses on the small Bearingless Brushless DC Motor (BL-BLDCM), to solve the problems, such as larger commutation torque ripple and difficult solution of air-gap magnetic field, a novel BL-BLDCM structure with like-tangential parallel-magnetization interpolar magnetic poles (LTPMIMPs) is proposed, which is abbreviated as BL-BLDCM-LTPMIMP in this work, and the analytical calculation model of its air-gap magnetic field has been investigated. First, inserting a like-tangential parallel magnetizing auxiliary magnetic pole between every two adjacent single-radial-magnetizing main poles, and forming several combination magnetic poles, each of which is composed of a radial-magnetizing main magnetic pole and two semi-auxiliary-magnetic-poles (with different magnetization directions) located on both sides. Then, by solving the Laplace equation and Poisson equation in every subdomain, and combining the relative permeability function, the analytical expressions of the air-gap magnetic fields for the BL-BLDCM-LTPMIMP was obtained. The armature reaction magnetic fields of the torque windings and suspension windings are also analyzed. Finally, through the finite element method (FEM), the correctness and computational accuracy of the analytical calculation model for the air-gap magnetic field is proven. Additionally, the comparison of electromagnetic characteristics with ordinary BL-BLDCM shows that the BL-BLDCM-LTPMIMP can not only effectively improve the amplitude and stability of electromagnetic torque on the basis of obtaining a shoulder-shrugged trapezoidal wave air-gap magnetic field but also has stable radial magnetic levitation force control characteristics. Full article

The electro-hydraulic servo valve is a critical component that transforms electrical signals into hydraulic signals, thereby controlling the hydraulic system. It finds extensive application in precision control systems. The stability of the electro-hydraulic servo valve is primarily influenced by the armature assembly. Unlike integral armature assembly, the separated armature assembly, comprising the armature, spring tube, flapper, and feedback spring, is joined through an interference fit, which introduces prestress within the assembly. The existence of prestress may affect the operational mode of the armature assembly. Consequently, this paper investigates the vibration characteristics of the separated armature assembly under interference fit conditions. Comparative analysis reveals that interference fit indeed generates prestress, which cannot be overlooked. To further validate the reliability of the simulation results, the natural frequency of the separated armature assembly is determined by applying a sweeping frequency signal to the torque motor using an electric drive, thereby verifying the feasibility of the simulation analysis. Additionally, the impact of interference on the vibration characteristics of the separated armature assembly is examined, confirming the accuracy of the simulation analysis method based on the interference fit. The research on vibration characteristics of a separated armature assembly provides technical support for the structural optimization design of the electro-hydraulic servo valve, thereby enhancing its performance. Full article

There is a need to address challenges faced in detecting and segmenting defects in micro-vibration motor armatures, which are crucial components used in digital devices. Due to their complex structure and tiny size, quality control during assembly is difficult. In this paper, an adaptive segmentation quantization (ASQ) system based on YOLO 11 and SAM is proposed to address the issue above. The system consists of a target detection (TD) unit, shape segmentation (SS) unit, and quantitative assessment (AS) unit, and introduces a practical combination of YOLO11 for defect detection and SAM for segmentation, integrating this with a novel quantitative assessment framework to measure defect severity and occurrence. This approach is efficient and cost-effective, supporting real-time industrial applications by allowing for automated, rapid analysis and improvement identification. Finally, a quantitative evaluation standard with more than 90% accuracy was achieved. Additionally, a hardware system was developed to implement this framework in industrial settings. The proposed framework adopts a strategy of intelligent morphological feature extraction and computation, focusing on pixel-level segmentation and quantitative assessment. This research makes a significant step forward in automating quality control processes for micro-scale components, providing a robust and adaptive solution for the enhancement of manufacturing efficiency and product quality. Full article

The moving-magnet linear motor has received considerable attention in the development of logistic and factory automation in recent years. A reliable position detection system is the key to achieving the precise position and control of the motor. At present, the magnetic grid-scale and grating-scale are the most widely used traditional detection methods. However, these are not suitable for position detection with moving-magnet linear motors. They have the disadvantages of being easy to disturb, having a high cost, and exhibiting a limited measurement range. In this work, a moving-magnet linear motor position detection system based on an array of magnetoresistive sensors is used. The array is configured by arranging the magnetoresistive sensors at equal intervals along a line parallel to the trajectory of the armature. Then, the permanent magnet is fixed on the rotor and detected by sensors. When the rotor crosses the sensors in a parallel line, the changes in the magnetic field cause the magnetoresistive sensors to output two voltage signals directly proportional to the corresponding position changes. The signals are collected by the AD7606 and transmitted to the FPGA and STM32 controller for data processing, and the actual position of the rotor is calculated. This method has no length limitation and can be used for long-distance position detection. The experimental results show that the position detection system has a higher linear correlation coefficient compared with the magnetic grid ruler, in addition to a capability of ±9 μm accuracy, which verifies the validity of the position detection method for the moving-magnet linear motor. Full article

The fundamental idea underlying the research presented in this paper was the desire to use less magnetically charged areas of the general construction of induction machines by increasing the active working surface by interposing a new internal stator armature. This results in a new air gap and foreshadows the advantage of increasing the torques developed by the motor considered, compared to the equivalent standard motor, at the same volume of iron. The following research-validation methods were followed: theoretical studies (analytical simulation and FEM), an experimental model (prototype), and testing on the experimental platform. We recall obtaining solid conclusions on the technological construction, functional and energy characteristics, as well as superior performances of over 50% regarding electromagnetic torques compared to the equivalent classic version. The prototype of this type of machine was surprising due to the ease with which the rotor can be rotated, highlighting the reduced inertia. In conclusion, concerning the problem addressed and the objectives pursued, the research had, in essence, an applied and experimental nature. The recent development of permanent-magnet synchronous motor constructions has led to the concept of creating such motors in the constructive configuration specified in the paper (two stators and two radial air gaps). Full article

In this article, the linear non-equilibrium thermodynamic approach is used to mathematically describe the energy regularities of an interior permanent magnet synchronous motor (IPMSM), taking into account iron loss. The IPMSM is considered a linear power converter (PC) that is multiple-linearized at operating points with a given angular velocity and load torque. A universal description of such a PC by a system of dimensionless parameters and characteristics made it possible to analyze the perfection of energy conversion in the object. For IPMSM, taking into account iron loss, a mathematical model of the corresponding PC has been built, and an algorithm and research program have been developed, which is valid in a wide range of machine speed regulations. This allows you to choose the optimal points of PC operation according to the maximum efficiency criteria and obtain the efficiency maps for IPMSM in different speed regions. The results of the studies demonstrate the effectiveness of the proposed method for determining the references of the d and q components of the armature current for both the loss-minimization strategy at the constant torque range of motor speed and the flux-weakening strategy in the constant power range. Full article

In this study, a stepper driver, which is suitable for use in the automotive industry, designed for general use, capable of adaptive learning in the systems in which it is used, and with CAN and universal asynchronous receiver–transmitter (UART) communication options, was designed. This design was made with a PIC18F25K22 microcontroller unit (MCU). Rotor speed, armature current, and terminal voltage can be measured on the proposed brushed DC motor drive system. It gives the desired response by evaluating obstacles and other situations in which high currents are drawn from the source. The speed measurement of the vehicle and the open and closed status of an automatic door can be monitored. The main contribution of the designed PCB is an adaptive learning algorithm (ALA) that uses the pulses of the encoder, estimates the position of the step, and manages the operation process to prevent mechanical damage at the final point of the motor. Furthermore, unexpected hitting and pinching which are defined as obstacles to the driver can be controlled by monitoring the current value drawn from the driver. The benefit of this method is that the life of the mechanical step is increased due to the management of the forward and backward step operation, preventing potential accidents. Full article

The optimal performance of direct current (DC) motors is intrinsically linked to their mathematical models’ precision and their controllers’ effectiveness. However, the limited availability of motor characteristic information poses significant challenges to achieving accurate modeling and robust control. This study introduces an approach employing artificial neural networks (ANNs) to estimate critical DC motor parameters by defining practical constraints that simplify the estimation process. A mathematical model was introduced for optimal parameter estimation, and two advanced learning algorithms were proposed to efficiently train the ANN. The performance of the algorithms was thoroughly analyzed using metrics such as the mean squared error, epoch count, and execution time to ensure the reliability of dynamic priority arbitration and data integrity. Dynamic priority arbitration involves automatically assigning tasks in real-time depending on their relevance for smooth operations, whereas data integrity ensures that information remains accurate, consistent, and reliable throughout the entire process. The ANN-based estimator successfully predicts electromechanical and electrical characteristics, such as back-EMF, moment of inertia, viscous friction coefficient, armature inductance, and armature resistance. Compared to conventional methods, which are often resource-intensive and time-consuming, the proposed solution offers superior accuracy, significantly reduced estimation time, and lower computational costs. The simulation results validated the effectiveness of the proposed ANN under diverse real-world operating conditions, making it a powerful tool for enhancing DC motor performance with practical applications in industrial automation and control systems. Full article

Brushed DC motors and generators (DCMs) are extensively used in various industrial applications, including the automotive industry, where they are critical for electric vehicles (EVs) due to their high torque, power, and efficiency. Despite their advantages, DCMs are prone to premature failure due to sparking between brushes and commutators, which can lead to significant economic losses. This study proposes two approaches for determining the temporal and frequency evolution of Shannon entropy in armature current and stray flux signals. One approach indirectly achieves this through prior analysis using the Short-Time Fourier Transform (STFT), while the other applies the Stockwell Transform (S-Transform) directly. Experimental results show that increased sparking activity generates significant low-frequency harmonics, which are more pronounced compared to mid and high-frequency ranges, leading to a substantial rise in system entropy. This finding enables the introduction of fault-severity indicators or Key Performance Indicators (KPIs) that relate the current condition of commutation quality to a baseline established under healthy conditions. The proposed technique can be used as a predictive maintenance tool to detect and assess sparking phenomena in DCMs, providing early warnings of component failure and performance degradation, thereby enhancing the reliability and availability of these machines. Full article

This paper presents the detailed design, construction and tests of a protype iron-free MRI-compatible electromagnetic actuator. The originality of this proposal lies in the use of the homogeneous static magnetic field B₀, present in the MRI bore, to ensure the electromechanical energy conversion. The armature is composed of three rectangular coils in a three-phase arrangement, which makes the actuator very light-weight and compact. The operating principle is that of an AC synchronous motor with a rotating armature. In order to design the actuator, a 3D analytical electromagnetic model is developed to predict the magnetic field produced by the armature winding. Then, a 3D finite element (FE) computation is performed to validate the analytically calculated magnetic field. The developed analytical model is then inserted into an optimization routine based on Genetic Algorithms (GAs) to obtain the prototype dimensions to be realized. Finally, the prototype is constructed and tested inside an MRI research scanner. The results indicate that the reduction in the Signal-to-Noise Ratio (SNR) and the geometrical distortion are less than 5% when the actuator is powered with a current of 10 times the rated one and when it is located very close to the subject to be imaged. Full article

The automotive industry is increasingly focused on waste management, elimination, and reduction to achieve sustainability and cost reduction. This focus drives the industry towards resource-efficient operations that minimize environmental impact while exceeding customer expectations. Meeting these demands necessitates the adoption of more efficient production methodologies, such as the PDCA cycle. This work presents a case study that illustrates the application of the PDCA methodology to minimize scrap generation due to process variability in a multinational company that manufactures electric motors for the automotive industry. The aim was to demonstrate how the PDCA methodology can improve quality standards by minimizing scrap generated during the manufacture of electrical armatures. Notably, the organization in this case study set a waste target of 0.7%, which was significantly exceeded. Finally, the implementation of this methodology can deliver significant economic benefits, with a total annual cost reduction of approximately USD 135,000. Full article

Axial flux permanent magnet motors have attracted increasing attention due to their compact topology and high torque density. Many topological variations have arisen over time; however, limited research has directly compared the differences in magnetic performance of these topologies. This paper carries out a comprehensive investigation, employing both analytical and 3D finite element analyses, to compare the magnetic performance of three topologies: yokeless and segmented armature (YASA), axial flux internal rotor (AFIR), and offset AFIR. The findings reveal that each topology offers specific advantages for different applications. The YASA topology excels in minimizing core losses; the AFIR configuration achieves the highest torque density; and the offset AFIR topology shows the highest efficiency. The offset AFIR topology appears to offer advantages for a wide array of applications due to its higher power factor and lower permanent magnet loss, leading to reduced costs for converter design and cooling system design. Full article