Search Results (157)

Conventional flux-reversal permanent magnet motors have problems such as excessive torque ripple and rich harmonic content in direct drive applications such as oil exploration, which restrict their application in high-precision scenarios. To address this issue, this paper presents a hybrid excitation topology that integrates double-armature windings, stator Halbach hybrid permanent magnet arrays, rotor-staggered unequal-tooth and rotor-hybrid permanent magnets. Two-dimensional finite element analysis was conducted using ANSYS Maxwell 2023 R1 to evaluate electromagnetic performance under rated steady-state conditions, rated power 300 kW, rated speed 83 rpm, rated voltage 660 V, rated phase current 307 A, and axial core length 200 mm. The simulation results show that the proposed topology has an average output torque of 34.5 kN·m at rated conditions compared with the traditional flux-to-reverse permanent magnet motor of the same size, and the torque ripple rate is reduced from 27.5% to 17.4%, a relative reduction of 36.8%. The results are based only on numerical simulation and have not been verified by physical prototype experiments. Dynamic control strategies, multi-load transient responses and experimental verification will be carried out in subsequent work. Full article

Off-highway vehicle electrification requires traction motors combining high torque density with reliable performance across demanding duty cycles, yet finite-element-based optimization remains computationally demanding for broad design-space exploration. This study addresses the gap with a sensitivity-analysis-based, surrogate-assisted multi-objective optimization framework for a 12-pole/72-slot, 120 kW Interior Permanent-Magnet Synchronous Motor (IPMSM) for a compact wheel-loader drivetrain, coupling Ansys Motor-CAD with Ansys OptiSLang. A Latin Hypercube sensitivity study of thirteen geometric parameters identifies the dominant design drivers, and an evolutionary algorithm operating on the validated surrogate produces a Pareto-optimal set, from which the final design is selected using the CRITIC–TOPSIS method applied to finite-element-validated feasible designs. Relative to the baseline, the validated performance shows a 7.4% increase in continuous torque, a 4.0% increase in peak torque, a 4.0% increase in efficiency, and a 53.5% reduction in torque ripple, with mass essentially unchanged, while also revealing that surrogate predictions were markedly optimistic relative to the finite-element results. These findings demonstrate an efficient, reliable route to high-performance IPMSM design for off-highway applications. Full article

Manufacturing tolerances and winding-layout variations can introduce phase-to-phase mismatches in stator resistance and leakage inductance. Under such unbalanced phase impedances, conventional field-oriented control (FOC), typically designed under balanced-parameter assumptions, may produce unequal phase currents, distorted airgap MMF, reduced efficiency, increased torque ripple, and undesired vibro-acoustic behavior. This paper investigates an open-end winding (OEW) induction machine (IM) drive, in which each phase is independently driven by an H-bridge inverter fed by the same DC source. To mitigate phase–current imbalance without parameter estimation, an RMS-based phase–current-balancing controller is proposed. The controller continuously calculates the RMS value of each phase current and adaptively scales the corresponding reference-phase voltage in a low-bandwidth outer loop, while preserving the classical FOC structure. The balancing law is derived directly from the phase-impedance imbalance model; convergence of the three coupled per-phase loops is proven via a Lyapunov argument, and stability of the cascaded structure is established through an analytical bandwidth-separation analysis shown to be robust to ±30% machine-parameter variation and across the 500–1500 rev/min speed range. Simulation and experimental results across multiple operating points demonstrate effective phase–current equalization. Full article

This study proposes a linear active disturbance rejection control and load-adaptive multi-harmonic repetitive control (LADRC–LAMHRC)-based direct instantaneous torque control strategy to improve the dynamic performance of a three-phase 6/4 switched reluctance motor. Although conventional proportional–integral-based direct instantaneous torque control (PI-DITC) provides satisfactory speed tracking, its performance is limited by pronounced torque ripple and reduced robustness under sudden load variations. In the proposed scheme, the LADRC estimates and compensates for lumped disturbances and model uncertainties, whereas the LAMHRC attenuates the periodic speed-error components associated with the torque ripple and generates an auxiliary torque-compensation command. The effectiveness of the proposed method was evaluated through comparative MATLAB/Simulink simulations with the conventional PI-DITC scheme. At reference speeds of 500 and 1000 r/min, the proposed controller reduced the torque-ripple coefficient from 11.11% to 2.96% and from 11.76% to 2.55%, corresponding to reductions of 73.4% and 78.3%, respectively. When the load torque was increased from 5 to 7 N·m, the maximum speed deviation decreased from 0.45 to 0.05 r/min, corresponding to an 88.9% reduction in maximum speed deviation. For a load reduction from 7 to 5 N·m, the speed deviation decreased from 0.5 to 0.1 r/min, corresponding to an 80.0% reduction. Under the investigated simulation conditions, the proposed scheme achieved a lower torque ripple and improved load disturbance rejection compared with the conventional PI-DITC scheme. Full article

This paper presents a self-tuning minimal-rule fuzzy logic controller for high-performance induction motor drives operating under field-oriented control. Unlike conventional full-rule fuzzy controllers and reduced-rule designs with fixed post-design scaling, the proposed method combines a fixed nine-rule Mamdani inference structure with a bounded online output gain adaptation mechanism. The nominal gain and adaptation sensitivity are determined offline using Particle Swarm Optimization, thereby retaining operating-condition responsiveness without requiring online optimization, rule reconstruction, or membership-function retuning. The closed-loop behavior is analyzed using a discrete-time Lyapunov framework derived from the induction motor mechanical dynamics under bounded disturbances. The controller is evaluated through fixed-step simulations incorporating measurement noise, 12-bit signal quantization, and a one-sample computational delay. Comparative results against a conventional PI controller and a classical 49-rule fuzzy controller show that the proposed scheme achieves a rise time of 0.15 s, a settling time of 0.26 s, a post-transient mean absolute tracking error of 4 RPM, negligible overshoot, and a torque ripple of approximately 0.44 Nm. Relative to the classical 49-rule FLC, the proposed design reduces the maximum number of fuzzy-rule evaluations per control update from 49 to 9, corresponding to an 81.6% reduction in structural fuzzy-inference complexity. The results indicate a favorable simulation-level trade-off between dynamic performance, disturbance rejection, and structural algorithmic simplicity. Generated-code SIL, Hardware-in-the-Loop testing, target-processor timing measurements, and experimental implementation remain necessary to establish practical embedded feasibility. Full article

Permanent magnet synchronous motors (PMSMs) are widely employed in electric vehicles owing to their high efficiency, high power density, and wide speed regulation capability. However, electromagnetic vibration is aggravated by the non-sinusoidal air gap magnetic field distribution and cogging torque. To suppress vibration, this paper proposes an optimized asymmetric rotor design. Through sensitivity analysis of rotor parameters on motor performance, a high-precision Metamodel of Optimal Prognosis (MOP) is developed for the surrogate-based motor model. Subsequently, rotor parameters are comprehensively optimized using a genetic algorithm. The results demonstrate that, compared with the reference motor under identical operating conditions, the optimized motor maintains equivalent output torque while achieving significant reductions in vibration-related performance indicators: torque ripple is reduced by 17.9%, and cogging torque is reduced by 82.8%, the amplitude of the 48th-order electromagnetic force decreases from 2.60 N to 1.28 N (representing a 50.7% reduction), and the peak vibration response decreases from 109.7 dB to 107.2 dB. This study provides an effective design approach for electromagnetic vibration suppression in PMSMs. Full article

Electric power steering (EPS) systems have become the dominant steering solution in modern vehicles due to their advantages in energy efficiency and driving convenience. Among EPS configurations, rack-type EPS(R-EPS) is widely adopted in mid-to-large vehicles for its direct and responsive steering characteristics. However, conventional slotted motors used in R-EPS suffer from cogging torque and torque ripple caused by periodic reluctance variation in the stator tooth structure, resulting in vibration and noise directly perceived by the driver. This article proposes a slotless Surface Permanent Magnet Synchronous Motor (SPMSM) employing a Bar-Type magnet with a double-bridge rotor structure for R-EPS applications. By eliminating stator teeth, the proposed design achieves a uniform reluctance distribution during rotor rotation, theoretically reducing cogging torque to zero. The absence of stator tooth magnetic saturation further enables the use of high-remanence permanent magnets, improving gravimetric power density and enabling motor miniaturization. The proposed motor was designed and verified through finite element analysis (FEA). Compared to the conventional Arc-Type motor, the optimized design achieves a torque ripple reduction of 64.7% (from 5.07% to 1.79%) through Bar-Type magnet shaping combined with a 5 mm edge filet. The optimized design achieved an output power of 359.9 W, a gravimetric power density of 276.85 W/kg based on an active part weight of 1.30 kg, and a structural safety factor of 1146, demonstrating the effectiveness of the proposed double-bridge slotless motor for R-EPS applications. Full article

To address the degraded prediction accuracy, increased torque ripple, and weakened dynamic response of conventional finite-control-set model predictive control (FCS-MPC) under magnetic saturation, parameter mismatch, and load disturbances in permanent magnet synchronous motors (PMSMs), this paper proposes a hierarchical FCS-MPC framework based on PINN-RLS and virtual-voltage-vector extension, termed HRPV-MPC. Built upon a unified nonlinear motor model, the proposed method integrates PINN-RLS-based online parameter correction, virtual-voltage-vector extension, disturbance-observer-based feedforward compensation, maximum-torque-per-ampere (MTPA) and quadratic-programming (QP) reference reconstruction, and deep-neural-network (DNN)-based torque-ripple compensation into the same closed-loop control framework. Unlike existing studies that usually optimize parameter identification, disturbance compensation, or ripple suppression separately, the proposed method emphasizes their coordinated interaction within the predictive control chain so as to simultaneously improve steady-state precision, disturbance rejection, and dynamic recovery performance. Simulation results show that the proposed HRPV-MPC achieves coordinated improvements in steady-state precision, dynamic response, and disturbance rejection under various operating conditions; compared with baseline FCS-MPC, it exhibits clear advantages in torque-ripple suppression, torque-error reduction, load-disturbance recovery, and speed-tracking performance, thereby validating the effectiveness and superiority of the constructed hierarchical collaborative framework. Full article

Electric power steering (EPS) motors require low torque ripple, low cogging torque, and smooth torque output to ensure precise control and driving comfort. However, consequent pole permanent magnet synchronous motors (CP-PMSMs), although advantageous in reducing permanent magnet usage, exhibit an imbalanced magnetic flux distribution due to the iron poles, resulting in even-order harmonic components in the back electromotive force (BEMF) and significant torque ripple. In this paper, a rotor pole arrangement for CP-PMSMs is proposed to improve torque characteristics for EPS applications. Symmetric and asymmetric pole arrangements are introduced to modify the magnetic flux distribution and suppress harmonic components generated by the iron poles. In addition, the iron pole arc ratio is selected as a key design variable and analyzed for each model to achieve low torque ripple while maintaining torque performance. The electromagnetic characteristics of the proposed structures are evaluated using finite element analysis under identical operating conditions. The results show that the torque ripple of the proposed models is reduced by approximately 33.3%p and 34.1%p compared with the conventional CP-PMSM, and the cogging torque is also significantly reduced. Although average torque decreases, overall torque characteristics improve due to reduced torque ripple and harmonic components. These results demonstrate that the proposed rotor pole arrangement effectively enhances torque quality in CP-PMSMs without increasing axial length or requiring three-dimensional analysis. Full article

This paper proposes an adaptive-confidence-window-modulated model predictive controller (ACW-M2PC) for induction motor drives. The method combines angle-guided local sector selection with a confidence-triggered bounded expansion toward adjacent sectors, so that the online search remains local whenever the local solution is reliable and expands only when necessary. This decision structure reduces unnecessary candidate evaluations while preserving low computational burden and improving the quality of the selected voltage action. The proposed controller was implemented and validated through real-time hardware-in-the-loop experiments on a dSPACE DS1202 platform. Compared with a baseline full-search-modulated model predictive controller (M2PC), ACW-M2PC reduced the average number of evaluated sectors by 79.7% while maintaining zero-overrun real-time execution. At the same time, it improved torque quality, reducing torque ripple peak-to-peak by 70.2% and torque ripple RMS by 62.0%, with a slight reduction in speed integral absolute error. An ablation study further showed that angle-guided local reduction already captures a large part of the computational benefit, whereas the confidence-triggered bounded expansion provides the additional corrective action required when the local solution becomes insufficient. Overall, these results show that ACW-M2PC improves the performance–complexity trade-off while remaining suitable for real-time induction motor drive control. Full article

In high-performance applications of interior permanent magnet synchronous machines, critical emphasis is laid on torque characteristics of the design, especially average output torque and torque ripple. Consequently, various techniques of rotor step-skewing have been widely proposed and applied to enhance these performance metrics. This paper investigates the effects of conventional and novel pseudo-rotor step-skewing techniques on the torque characteristics of an interior permanent magnet synchronous machine. Using both 2D and 3D finite element analysis, the study provides a comprehensive performance comparison of these two methods. As the results demonstrate, while both techniques achieve significant reductions in torque ripple under normal load conditions with only a marginal decrease in average output torque, their effectiveness is compromised under increased load as a consequence of magnetic saturation. However, the proposed pseudo-step-skewing technique yields a marginal gain in average torque over its conventional counterpart, attributable to the suppression of axial inter-step flux leakage. The findings are experimentally validated, underpinning that the proposed method can be an effective alternative to the conventional one, primarily due to its ease of rotor assembly. Full article

Permanent magnet synchronous motors (PMSMs) suffer performance degradation under parameter uncertainties and external load disturbances, reducing the effectiveness of conventional proportional-integral and field-oriented control (FOC) schemes. This paper presents an artificial intelligence (AI) enhanced hybrid controller that combines finite-control-set model predictive control (FCS-MPC) and active disturbance rejection control (ADRC). The FCS-MPC optimizes inverter switching states by minimizing a cost function through predicted current trajectories. Additionally, the ADRC employs an extended state observer to estimate and compensate for aggregated disturbances. A lightweight radial basis function neural network is utilized, whose centers and widths are initialized offline based on k-means clustering on representative data, while its output weights are updated online via a Lyapunov-based adaptive law. This network dynamically adjusts the MPC cost function weights and ADRC observer bandwidth according to real-time operating conditions, while enabling online identification of key motor parameters. MATLAB/Simulink R2024a simulations under step load torque conditions verify that the proposed method achieves a speed deviation within 3% of the rated value, an over 90% reduction in torque ripple compared to FOC, and a settling time of less than 5 ms. Although it incurs a moderate computational cost, the proposed controller exhibits improved tracking accuracy and enhanced robustness under simulated conditions. Consequently, the AI-enhanced MPC-ADRC strategy shows strong potential for high-performance applications, subject to future experimental validation. 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 paper aims to improve the energy autonomy and the mechanical performances of an on-board drive chain for robotics. The energy autonomy improvement is performed by reducing electrical losses in the inverter. Electrical losses are reduced by decreasing the number of switching cycles per period of the inverter’s power semiconductor switches, while maintaining a low Total Harmonic Distortion (THD). These improvements are expected thanks to a new control strategy called Pre-Calculated Pulse Width Modulation (PC PWM). The principle of this new control strategy is that all the symmetries of an ideal three-phase voltage system are assigned to the real output voltage of the inverter. Then the switching instants of the inverter’s switches are determined off line, by means of Fourier’s analysis, so that the maximum number of successive harmonics is zeroed. This allows the optimal switching sequence to be predefined, thereby reducing unnecessary commutations of the power switches. The performance of the new method (PC PWM) is evaluated through detailed simulation studies and compared with the conventional method called Sinusoidal Pulse Width Modulation (SPWM). The simulation results show that despite the reduction in the number of commutations per period, the performance of the actuation chain has been significantly improved with PC-PWM (new technique). Indeed, for the same mechanical load, the PC-PWM method allows for a lower current, a shorter transient response time and a lower torque ripple than the SPWM method. Full article

Outer rotor permanent magnet synchronous motors (ORPMSMs) are widely used in drone and aircraft propulsion due to their high power density. However, conventional arc-shaped designs involve an inherent trade-off between efficiency and torque ripple. Increasing the arc curvature improves the sinusoidal air gap flux density and reduces torque ripple, but it also increases rotor eddy current loss due to larger flux variations, thereby degrading efficiency. This paper investigates the effects of stator and rotor geometries on rotor eddy current loss and torque ripple in ORPMSMs. To address this trade-off, arc- and rectangular-shaped rotor and stator pole shoes are combined to form four design candidates. Their electromagnetic performance is evaluated using finite element analysis. Based on this comparison, a configuration with rectangular rotor and stator pole shoes is selected as the initial design and further optimized using a multi-objective genetic algorithm to simultaneously improve efficiency and torque ripple. The optimized design demonstrates significant improvements, achieving reductions of 56.67% in peak-to-peak torque ripple and 46.89% in rotor eddy current loss compared to the initial design. Full article