Search Results (1,687)

PMSM-based flywheel energy storage systems require fast and robust speed regulation in the presence of parameter uncertainty, load disturbances, and measurement noise, while avoiding the cost and reliability limitations associated with mechanical encoders. This paper proposes a sensorless control framework that combines a fractional-order sliding-mode speed controller with a fractional-order sliding-mode observer. To improve dynamic performance, an improved hybrid Aquila Optimizer–African Vulture Optimization Algorithm (IHAOAVOA) is employed to tune the controller parameters, while the observer follows the proposed robust sensorless design. Simulation results show that at the 1000 rpm operating point under a 20 N·m load disturbance, the proposed method limits the startup overshoot to about 0.24%, compared with 8.02% for the PI control and 9.74% for the conventional sliding-mode control. After the disturbance is introduced at $\mathrm{t}=1.0$ s, the speed drop of the proposed method is limited to 2.80%, whereas those of the PI control and conventional sliding-mode control reach 7.20% and 5.60%, respectively. At the 8000 rpm operating point under an 80 N·m load disturbance, the proposed method maintains the same advantage, with an overshoot of about 0.04% and a speed drop of 1.88%, both lower than those of the two benchmark controllers. In sensorless operation, the sensorless scheme with the IHAOAVOA-tuned speed controller also improves transient estimation performance. At the 1000 rpm operating point, the maximum startup speed estimation error is reduced from 41.8 r/min to 34.8 r/min. At the 8000 rpm operating point, the estimation error enters the ±10 r/min band at 0.0671 s, compared with 0.0718 s for the PSO-tuned case. The electromagnetic torque responses further indicate that the proposed tuning strategy improves transient torque smoothness while maintaining comparable steady-state torque behavior. These results demonstrate that the proposed control framework provides an effective balance among fast dynamic response, disturbance rejection, sensorless estimation accuracy, and electromechanical transient smoothness for PMSM-based flywheel energy storage applications. Full article

This paper presents a temperature field analysis and a new water-cooling channel design for a 1000 kW, 72-slot/8-pole permanent magnet synchronous motor used in mining applications. To capture temperature rise data related to electromagnetic losses and fluid heat transfer, a multiphysics coupling model was established, and its accuracy was verified through temperature rise experiments on a prototype. To address the issues of poor temperature uniformity and excessive head loss in the original structure, a double-helix return cooling water channel structure was designed, effectively compensating for the heat exchange capacity at the motor ends and reducing fluid resistance. Comparative analysis shows that this structure significantly outperforms traditional cooling water channels in terms of heat dissipation efficiency, temperature uniformity, and pressure loss. Under optimal geometric parameters—10 spiral turns and a flow velocity of 1 m/s—the maximum winding temperature was suppressed to 67.7 °C, with a winding temperature difference of only 2.6 °C, while the pressure drop was maintained at a low level of 9580 Pa. This study provides a theoretical basis and an efficient engineering solution for the design of water-cooling structures in large mining motors. Full article

Traditional optimization methods for interior permanent magnet synchronous motors (IPMSMs) often treat the stator and rotor as independent design domains, which limits the potential for suppressing torque fluctuations due to the neglected electromagnetic coupling between these components. This paper proposes a synergistic optimization strategy for a 120 kW IPMSM, aiming to overcome the inherent limitations of conventional unilateral optimization in design space exploration and achieve global performance enhancement through cross-domain collaboration. By establishing a unified surrogate model incorporating both stator slot geometries and rotor pole topologies, the collaborative effect of seven high-sensitivity design variables is systematically analyzed. The NSGA-II algorithm, coupled with a Kriging surrogate model, is employed to navigate the complex trade-offs among average torque, torque ripple, and cogging torque. Results demonstrate that the synergistic approach achieves a 28.1% reduction in torque ripple while maintaining high average torque, demonstrating superior improvement over conventional stator-only or rotor-only optimization schemes. Analysis based on Maxwell stress tensors and air-gap permeance functions reveals that the proposed method achieves simultaneous suppression of cogging torque and torque ripple by effectively harmonizing the 24th and 48th spatial harmonics. This study provides an efficient synergistic design methodology for the comprehensive performance enhancement of traction motors, offering practical reference value for the engineering development of high-performance electric vehicles. Full article

This study details the modelling and simulation analyses performed on a mathematically modelled permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) driven by a field-oriented controlled (FOC) voltage source inverter (VSI) coupled with a half-bridge bidirectional buck-boost DC/DC converter for two-wheeler electric vehicle (EV) applications. The 5 kW, 1500 rpm PMa-SynRM employed here has a shorter response time and is also naturally lighter and cost-effective, making it suitable for two-wheeler EVs. Field-oriented control simplifies the control strategy for PMa-SynRM by decoupling torque and flux, effectively matching the behaviour of a DC motor. A half-bridge buck-boost converter is a DC-DC converter capable of bidirectional power flow, stepping up and down voltages. This makes it ideal for both motoring and regenerative braking in electric vehicles. The buck-boost converter with its controller effectively adjusts the inverter and battery voltage for efficient power flow during motoring and maximum power recovery during regenerating braking. The developed model aims at demonstrating forward and reverse motoring, as well as forward and reverse braking to validate the four-quadrant torque-speed characteristics of two-wheeler EVs. The proposed model attains less than 2% torque ripple and less than 1% speed ripple, respectively. Further, the current ripples are minimised to reduce losses and to improve efficiency. The work presented in this paper implements a PMa-SynRM-based drive system for EVs, a technology which is in the exploratory stage and not commercially widespread. This adds novelty to the proposed work. A MATLAB Simulink environment was used for modelling and simulation. Full article

To improve the speed regulation performance of permanent magnet synchronous motor (PMSM) drive systems, a composite control strategy consisting of an improved sliding mode controller (ISMC) and an adaptive Luenberger load torque observer (ALLTO) is proposed. The ISMC is constructed based on a novel sliding mode reaching law (NSMRL). The proposed NSMRL overcomes the slow convergence and chattering problems of conventional reaching laws by introducing system state variables and a nonlinear adaptive function, ensuring rapid convergence with reduced chattering. In parallel, the ALLTO is developed to estimate and compensate load disturbances in real time, where its bandwidth is adaptively adjusted according to the speed error to achieve fast response and high estimation accuracy without degrading steady-state performance. Experimental results demonstrate that the proposed control scheme significantly improves the dynamic response and disturbance rejection capability of PMSM drive systems. Full article

In this study, parameter estimation-assisted sensorless control methods are proposed for compressor motors. As sensorless control strategies, rotating high-frequency injection (RHFI), pulsating high-frequency injection (RHFI), and an adaptive-gain sliding mode observer (AG-SMO) are employed. During startup, HFI-based methods are utilized, whereas AG-SMO is activated under steady-state operating conditions. To mitigate parameter variations and inverter nonlinearities, Adaline Neural Network (ANN), Recursive Least Squares (RLS), and Extended Kalman Filter (EKF) algorithms are integrated for the real-time estimation of stator resistance and dead-time voltage. The proposed framework is validated through both simulation and experimental studies on a 30 W, 20 V interior permanent magnet motor commonly used in compressor applications. The results demonstrate that sensorless control algorithms alone provide robust operation, while the incorporation of parameter estimation effectively eliminates stability issues and ensures reliable transitions from low to high speeds. Comparative analysis reveals that ANN has a simple structure, RLS achieves faster convergence, and EKF provides smoother estimates under noisy conditions. Overall, the integration of sensorless control algorithms with ANN/RLS/EKF-based parameter estimation and dead-time compensation offers a cost-effective and reliable solution for high-performance compressor applications. Full article

Accurate demagnetization fault diagnosis is critical to ensuring the safety and reliability of permanent magnet synchronous motors (PMSMs). However, the number, location, and severity of demagnetized permanent magnets are mutually coupled, leading to a combinatorial explosion of fault patterns. Existing methods are largely limited to idealized assumptions involving single-magnet demagnetization or uniform demagnetization of multiple magnets, making it difficult to characterize the random nature of demagnetization in practical operation. Thus, this paper proposes a precise demagnetization fault diagnosis method based on a novel search coil (SC) configuration, in which only two toroidal-yoke-type search coils are installed in the stator slots. The proposed method partitions the rotor permanent magnets into several modules and categorizes the infinite demagnetization fault patterns into 26 representative patterns, effectively addressing the issue of fault mode explosion. Theoretical analysis and experimental results show that the voltage waveforms of the search coil over a single electrical period exhibit significant and stable differences across the identified patterns. By constructing feature vectors based on these differences, a physically interpretable mapping between the feature vectors and fault patterns is established. Combined with a corresponding pattern recognition algorithm, the proposed method enables fast and accurate differentiation of the 26 patterns without the need for complex machine learning models, thereby achieving precise localization of demagnetized permanent magnets. Simulation and experimental results verify the correctness and effectiveness of the proposed method. Full article

Interior permanent magnet synchronous motors (IPMSMs) offer performance advantages such as saliency effect, high mechanical strength, and a wide speed regulation range. The magnetic and mechanical properties of the core material significantly influence IPMSM performance. By investigating the effects of different core materials on IPMSM performance, an optimal material combination can be identified to enhance the overall motor performance. This paper takes a $\overline{\mathrm{V}}$-shaped IPMSM for use as a main drive motor in new energy vehicles as the research object. First, the influence of the iron loss characteristics of non-oriented silicon steel (NOSS) on IPMSM performance is analyzed, and the material selection principles for the stator and rotor cores under this condition are summarized. Subsequently, the influence of the magnetic flux density characteristics of NOSS on IPMSM performance is analyzed, and the corresponding material selection principles for the stator and rotor cores are summarized. Furthermore, ultra-high-yield-strength NOSS is applied as the motor core material to reduce the width of the rotor magnetic flux barrier, and the resulting performance advantages for the IPMSM are analyzed. Finally, prototypes of the IPMSM are manufactured and tested to validate the results of the analysis. Full article

Aiming to improve the robustness of two-phase buck converters powering DC bus of permanent magnet synchronous motor drives, this article presents a novel voltage regulation scheme. The proposed scheme comprises a three-switching-surface nonsingular fast terminal sliding mode controller (TSS-NFTSMC) for output voltage regulation and a current balancing controller to equalize the inductor currents. Due to the fast terminal sliding mode surface, the output voltage error converges more rapidly both when far from zero and when approaching zero. The phase plane is split into four regions by three independent switching surfaces. Based on the region where the sliding variable resides, the TSS-NFTSMC can directly decide the number of enabled high-side switches, which helps suppress internal disturbances effectively. The stability and convergence of the presented control system are verified via Lyapunov stability analysis. The convergence property of TSS-NFTSMC is independent of the current controller. Both simulation and experimental results demonstrate that the proposed control strategy achieves satisfactory dynamic response and strong disturbance rejection capability. Full article

Due to the widespread adoption of high-performance electric vehicles (EVs), Interior Permanent Magnet (IPM) machines have achieved significant advancement in the field of electric motors due to their high torque density and efficiency. However, research has been ongoing for many decades to suppress the rare-earth permanent magnet (PM) usage without sacrificing electromagnetic performance while still achieving the required torque, power, and efficiency. In this regard, various EV manufacturers, such as Honda, Toyota, Chevrolet, BMW, and Nissan, have developed different types of IPM topologies; however, the rare-earth PM usage is extensively high, and the torque density is lower. Thus, to reduce the PM consumption and improve the electromagnetic performance, especially torque density, this paper proposes a novel segmented delta-shaped IPM (SΔ-IPM) with a three-notched rotor pole shape having two different specifications and featuring embedded circular flux barriers and an intermediate flux bridge. Secondly, torque performance is analytically discussed, and electromagnetic performance has been evaluated using 2D finite element analysis (FEA). Due to its unique design featuring improved magnetic field shifting, an average torque of 393.7 Nm with torque ripples of 5.1% and a cogging torque of 0.57 Nm has been achieved. Finally, an extensive comparative analysis of the aforementioned ten state-of-the-art industry models has been conducted, which confirms the effectiveness of the proposed design for high torque density with minimum PM usage. Full article

The dual-inverter open-winding permanent magnet synchronous motor (OW-PMSM) drive system exhibits significant advantages for electric vehicles with dual energy sources, particularly in achieving coordinated energy management and efficient power allocation between the sources. Based on the dual-inverter OW-PMSM drive configuration, this paper proposes two stator current planning algorithms: one aims to minimize the electrical losses during motor operation and the other aims to maximize the power allocation range of the dual inverters, respectively. Building upon this, a geometric algorithm for stator voltage vector allocation is proposed to achieve smooth switching of the motor between the two algorithms. This enhances the tracking performance of the electromagnetic torque and d-axis current during motor operation, while ensuring that the motor operates within its steady-state range, thereby improving system stability. Finally, simulations and experiments are conducted on the proposed algorithm to verify its feasibility and advantages. Full article

Although model predictive control (MPC) has been successfully applied in permanent magnet synchronous motor (PMSM) speed control systems, its performance can degrade under high-dynamic operating conditions and uncertain load disturbances. To address these issues, a continuous-time model predictive control (CTMPC) framework is proposed to improve speed tracking accuracy and robustness. From a symmetry perspective, the proposed method leverages the orthogonal symmetry of Laguerre basis functions and the structural invariance of the continuous-time PMSM speed dynamics, enabling a compact and balanced representation of the control trajectory while preserving prediction accuracy. Specifically, a finite set of orthogonal Laguerre functions, combined with an adaptive smoothing factor and soft constraint mechanism, is employed to reduce computational complexity without compromising performance. In addition, a nonlinear disturbance observer is integrated to achieve real-time estimation and feedforward compensation of load torque variations, thereby enhancing disturbance rejection capability. Comprehensive simulation results demonstrate that the proposed approach significantly improves tracking precision, reduces overshoot, and shortens recovery time following load disturbances compared to conventional MPC methods. Full article

In order to improve the speed control performance of the permanent magnet synchronous motor, an improved self-coupling PID with NDO (nonlinear disturbance observer) compensation control strategy is proposed. To address the problems of the traditional self-coupling PID being inflexible and making it difficult to achieve an optimal response, a four-parameter self-coupling PID control strategy is proposed. This strategy not only solves the problems of dimensional conflict and a discordant control mechanism but also expands the selection range of closed-loop poles. On the other hand, a nonlinear disturbance observer is designed to improve the system’s anti-disturbance performance. The observed disturbance is transformed into a compensating current to enhance the system’s anti-disturbance ability. Simulations and experiments demonstrate that the control strategy proposed in this paper is effective: the maximum regulation time is less than 0.03 s, the maximum dynamic speed drop is less than 5 r/min, and the maximum recovery time is less than 0.002 s. Full article

To suppress AC-side oscillation and improve steady-state current quality in current-source-inverter-fed permanent magnet synchronous motor (CSI-PMSM) systems, this paper proposes a predictive current control method based on steady-state characteristics. An equivalent model of the CSI-PMSM system is developed in the synchronous rotating dq reference frame, and the steady-state characteristics of the filter capacitor current are analyzed. The analysis shows that the capacitor current is generally nonzero under steady-state operation, whereas its deviation from the steady-state reference component should converge to zero. Based on this property, a discrete predictive model is constructed, and the stator current tracking error and the capacitor current deviation are incorporated into the cost function to achieve coordinated current tracking and LC oscillation suppression. In addition, a deadbeat preselection and a local finite-candidate optimization scheme are adopted to reduce the online computational burden. Experimental results obtained from a 3.7 kW CSI-PMSM platform demonstrate that, compared with conventional multi-loop PI control, the proposed method significantly reduces dq-axis current ripples and DC-link current fluctuations, while decreasing the stator current total harmonic distortion from 9.87% to 2.25%. These results verify the effectiveness and engineering feasibility of the proposed steady-state-consistent predictive current control method. Full article

To improve the dynamic performance of position tracking in permanent magnet synchronous linear motors, a model predictive position control method based on disturbance observer is proposed. Firstly, a novel neural network enhanced model reference adaptive observer is designed to estimate the lumped disturbance of the system. Taking the estimated disturbance as a new state variable, it is explicitly embedded in the framework of model prediction, which realizes the online estimation and compensation of disturbance, and effectively solves the deterioration of control performance caused by inaccurate system parameters and unknown disturbance in model prediction method. The increment of the control input is used as the input of the prediction equation, which makes the control input smoother and avoids drastic changes. The adaptive gain of the observer is designed by Lyapunov theory and the stability of the system is analyzed. A large number of experiments and analysis are carried out on the tubular permanent magnet linear synchronous motor platform, which proves the effectiveness of the proposed method. Full article