Search Results (2,464)

The performance degradation of Permanent Magnet Synchronous Motors (PMSMs) is caused by nonlinear friction torque during low-speed operation, a phenomenon known as low-speed crawling. To address this issue, a composite compensation strategy based on a piecewise modeling approach is proposed in this paper. To accurately characterize the friction behavior, a dynamic learning rate neural network (DLRNN) is utilized for the ultra-low-speed region, while an optimal 5th-order polynomial model is established for the low-speed region. Building on this piecewise modeling, a composite control strategy with friction compensation is studied. This strategy employs a friction compensator for the feedforward compensation of the deterministic friction torque components. Furthermore, a reduced-order extended state observer (RESO) is designed to estimate and compensate for residual friction errors and random disturbance torques, thereby achieving high-precision motor control. Finally, experimental results on a surface-mounted PMSM validate that the proposed strategy effectively improves tracking accuracy and suppresses torque ripple near zero-speed, all while remaining within the computational constraints of standard industrial control hardware. Full article

This paper proposes a low-complexity residual-corrected loss-minimization current-reference generation method for permanent magnet synchronous motor (PMSM) drives. Existing loss-minimization control (LMC) methods often rely on lookup tables, numerical optimization, high-order algebraic equations, or explicit approximations based on maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) references. While effective, these simplified approximations often introduce residual errors relative to the true loss-optimal conditions. To address this, this paper adopts a more consistent iron-loss equivalent-circuit objective and analytically eliminates the torque equality constraint, reducing the LMC problem to a one-dimensional scalar minimization problem of the d-axis current. This paper demonstrates that this reduced objective is strictly convex over the admissible scalar domain, allowing for an exact benchmark solution via a scalar convex solver. The proposed method constructs a resistance-aware initial reference from explicit MTPA and MTPV approximations and then applies a one-step scalar Newton-type residual correction using the gradient and Hessian of the reduced loss objective. The initial reference reproduces the known exact surface-mounted PMSM (SPMSM) LMC solution in the SPMSM limit. The correction direction is proved to be a strict descent direction, and a safeguarded step-size ensures loss reduction compared to the initial approximation. The main novelty is the use of the scalar LMC optimality residual as a fixed-cost correction layer for explicit LMC references. The numerical validation is interpreted as steady-state current-reference mapping accuracy and model-based controllable loss-objective verification against the exact scalar optimum, not as hardware drive-efficiency validation. Tests including the no-MTPV case show reduced current-reference and loss-objective gaps while retaining a fixed-cost structure that may support future embedded implementation after validation; hardware transient and efficiency validation under inverter nonlinearity, temperature variation, saturation, and PWM effects remains for future work. Full article

The two-speed transmission system significantly enhances the powertrain matching performance of heavy-duty electric military armored vehicles by optimizing high-torque output at low speed and energy efficiency at high speed. However, most existing electric vehicles do not incorporate driving styles or real-time driving condition prediction into their shift control strategies, resulting in suboptimal gear shift timing and smoothness that fail to align with driver expectations and operational requirements. To address these limitations, this study focuses on the two-speed automated manual transmission (AMT) system in heavy-duty electric military armored vehicles. Firstly, a comprehensive shift control model is established, integrating key components such as the drive motor and power battery. Furthermore, a shift control strategy based on vehicle speed prediction and driving style recognition is proposed. The operational logic of this strategy is systematically analyzed under various driving cycles. Simulation and hardware-in-the-loop (HIL) results confirm the performance gains. Simulation and hardware-in-the-loop (HIL) results indicate that the proposed approach improves vehicle power performance by 21.36%, increases energy efficiency by 3.94%, and reduces powertrain shock by 31.81% compared to the conventional vehicle-speed-based gear shifting method. Compared to the adaptive shift schedule design method, the proposed approach reduces shifting frequency by 21.43% and improves ride comfort by at least 19.17% while maintaining comparable dynamic performance and energy efficiency. Full article

High-efficiency industrial motors are increasingly important for reducing energy consumption, operating costs, and indirect carbon emissions. This study presents a comparative evaluation of IE2 and IE4 efficiency class induction motors with the same rated power and frame size through finite element analysis and prototype testing. Two-dimensional transient electromagnetic models were developed in ANSYS Maxwell to investigate magnetic flux distribution, torque behavior, losses, and steady-state performance, and the numerical results were experimentally validated according to IEC 60034-2-1 procedures. The results show that the IE4 motor provides a more balanced magnetic flux distribution, lower local saturation tendency, reduced torque ripple, and lower total losses than the IE2 motor. Experimental measurements confirmed the numerical predictions with good agreement, particularly at the rated operating point. In addition to higher efficiency, the IE4 motor exhibited stronger starting and breakdown torque characteristics, indicating superior load-handling capability. An economic assessment based on a representative duty cycle showed that the relative additional cost of the IE4 motor can be recovered within approximately 0.81 years, while lower annual electricity consumption also reduces indirect CO₂ emissions. Furthermore, the IE4 prototype operated at a lower thermal steady-state temperature, supporting longer insulation life and improved long-term reliability. Overall, the findings demonstrate that replacing conventional IE2 motors with IE4 alternatives is not merely an efficiency upgrade, but also a technically robust, economically justified, and environmentally effective strategy for sustainable industrial systems. Full article

The growing demand for compact and high-performance motors in industrial robotic joints has intensified interest in axial flux permanent magnet motors (AFPMs), which inherently offer high torque density and a thin form factor compared with conventional radial flux permanent magnet motors (RFPMs). Among various AFPM structures, printed circuit board (PCB) Stator motors have gained significant attention due to their slotless configuration, reduced cogging torque, low vibration and acoustic noise, and enhanced geometric thinness enabled by PCB-etched conductors. This study proposes a conductor arrangement strategy that mitigates back-EMF imbalance in concentrated-winding single-rotor PCB AFPM for robotic joints. Several conductor configurations are analyzed and compared through electromagnetic finite-element evaluation, and an optimized arrangement is identified that effectively improves phase EMF symmetry while maintaining structural thinness. The results provide design guidelines for high-performance PCB AFPMs suitable for next-generation robotic actuators. Full article

To address the degradation of speed regulation performance in the permanent magnet synchronous motor (PMSM) transmission system caused by the gearbox broken tooth fault and disturbances, a fault model-assisted active disturbance rejection control (FMA-ADRC) algorithm is proposed in this paper. First, an electromechanical coupling model of the motor–gearbox transmission system is established based on the dynamic model of the tooth fault. Secondly, a fault model-assisted extended state observer (ESO) in the active disturbance rejection controller is designed, where the periodic torque disturbances caused by the fault are compensated to reduce the estimation burden on the observer. In addition, the observer is nonlinearized to improve the accuracy of tracking disturbances. The observer error of the nonlinear ESO (NESO) is proven to converge to a bounded region within finite time by using the Lyapunov stability proof theory. Finally, the speed regulation performance of the proposed FMA-ADRC controller is verified under different degrees of fault using an experimental platform based on DSP28335 and MATLAB/SIMULINK R2023b. The reliability and superiority of the proposed controller are verified by the experiment results. Full article

This work presents a nonlinear dynamic model and an energy-based control strategy for a coaxial vertical take-off and landing Unmanned Aerial Vehicle (UAV) equipped with independently tilting propulsion units. The proposed model captures the full six-degree-of-freedom motion of the vehicle and explicitly incorporates the forces and moments produced by the coaxial thrust-vectoring propulsion system, as well as the additional force components induced by the two-degree-of-freedom thrust vectoring mechanism. To regulate the vehicle during hover, cruise, and transition maneuvers, a passivity-based control framework formulated in terms of unit quaternions is developed. The control law simultaneously stabilizes the translational and rotational subsystems without relying on model linearization. In order to map the virtual control forces and torques into physically realizable actuator commands, a nonlinear control allocation procedure is introduced. This allocation scheme enables independent angular positioning of the propulsion units while computing the corresponding motor angular velocities. The effectiveness of the proposed modeling and control framework is assessed through three-dimensional dynamic simulations and numerical experiments, demonstrating accurate trajectory tracking, autonomous UAV landing capabilities, and smooth transitions between flight regimes for thrust-vectored UAV platforms. Full article

Slotless permanent magnet synchronous motors (PMSMs) have recently attracted significant attention for robotic and high-speed machine applications because they eliminate cogging torque and reduce iron loss through the absence of stator teeth. However, removing the stator teeth increases the effective airgap, resulting in extremely low synchronous inductance and introducing electrical challenges such as reduced control stability and increased current harmonics during pulse-width modulation (PWM) operation in inverter drive systems. In this paper, the current harmonic characteristics of a slotless PMSM are investigated with respect to switching frequency. Based on the mathematical model, the effects of switching frequency on a slotless PMSM drive system employing a MOSFET inverter are analyzed. In addition, an experimental setup, including a 700 W slotless PMSM and a MOSFET inverter, is implemented to evaluate the current harmonic characteristics under different switching frequencies of 25 kHz, 50 kHz, and 99 kHz. The total harmonic distortion of current at 99 kHz is reduced by approximately 6.73%p and 3.57%p compared with operation at 25 kHz and 50 kHz, respectively. The experimental results demonstrate the influence of PWM operation on the current characteristics of the slotless PMSM and verify the importance of high switching frequency operation for improving current performance. Full article

The capability of recovering a portion of braking energy during vehicle deceleration is one of the distinctive advantages of new energy vehicles (EVs) over Conventional Internal Combustion Engine Vehicles (ICEVs). In existing production vehicles, regenerative braking control is commonly implemented using rule-based lookup table methods. Although such approaches are simple, reliable, and easy to implement, they lack the ability to adaptively adjust the braking force allocation according to varying driving conditions, thereby limiting the potential for high efficiency energy recovery. To improve regenerative energy recovery while simultaneously maintaining braking stability, this study introduces an ANFIS-optimized Sliding Mode–Fuzzy Joint Hierarchical Control Strategy (S-FJHCS) for regenerative braking systems. In the upper control layer, an improved tire road friction coefficient estimation algorithm is integrated with a sliding mode controller to ensure consistent slip ratio regulation between the front and rear wheels. In the lower control layer, a fuzzy control algorithm is employed to coordinate the distribution of braking torque between the hydraulic braking system and the hub motors. Furthermore, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized to perform offline optimization of the fuzzy controller, enabling the adaptive adjustment of fuzzy rules and membership functions based on historical operating conditions. Simulation and experimental results demonstrate that the proposed regenerative braking control strategy can improve regenerative energy recovery efficiency by approximately 5–10% compared with a conventional rule based regenerative braking strategy, while maintaining satisfactory braking performance and vehicle stability under various driving conditions. Full article

Theswitched reluctance motor (SRM) suffers from torque ripple and speed fluctuations because of its doubly salient structure, magnetic saturation, and discrete commutation. To improve commutation performance and disturbance rejection, this paper proposes a progressive torque ripple suppression strategy. First, a multimodal magnetic co-energy model is developed to describe position-dependent saturation and generate the reference current through model inversion. Then, envelope extraction and frequency identification reveal the commutation-related periodic torque-error characteristic. Based on this feature, an angle-domain binned compensation method combining cycle averaging and linear interpolation is proposed to correct the reference current. A score-based finite-set PI hysteresis current controller is further designed to optimize magnetizing, freewheeling, and demagnetizing states, while a linear active disturbance rejection control (LADRC) speed loop improves load-disturbance rejection. Ablation studies verify the synergistic effect between angle-domain compensation and finite-set current execution. Robustness tests confirm low sensitivity to parameter variations, and theoretical analysis proves ultimate boundedness. Simulation results show that torque ripple is reduced to 2.00%, 2.03%, and 2.18% at 250, 500, and 1000 r/min, respectively. Under load-disturbance conditions, speed fluctuation is reduced by 59.92% and 57.20%, and all normalized parameter sensitivities remain below 0.35. Full article

This paper investigates the impact of segmented permanent magnet (PM) configurations on torque production, eddy current loss, and demagnetization in spoke-type flux-intensifying interior permanent magnet (FI-IPM) motors. While PM segmentation has been explored in conventional interior permanent magnet synchronous motors (IPMSMs) for reducing losses, its effect in flux-intensifying (FI) motors, characterized by reverse saliency, remains underexplored. To address this, five rotor designs with segmented PMs are analyzed against a baseline model using finite element analysis, maintaining identical stator and PM volume. Results show that segmentation increases reluctance torque, compensating for reduced PM torque, while simultaneously lowering eddy current loss and enhancing demagnetization resistance. These improvements validate segmented PMs as a viable strategy to enhance the durability and efficiency of FI-IPM motors for electric vehicle applications. 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

This study presents the design and development of a wearable lower-limb exoskeleton system aimed at supporting motion assistance in monoplegia-related conditions. The proposed approach integrates a simplified sensing configuration with a data-driven neuro-fuzzy control framework based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). Motion data are acquired from the healthy limb using bend flex sensors and are used to generate control signals for the actuation of the impaired limb through an Arduino-based embedded platform. The mechanical structure is developed using a lightweight 3D-printed design combined with high-torque DC motors and gear transmission mechanisms. Experimental evaluation conducted under controlled conditions demonstrates that the system is capable of capturing and reproducing fundamental motion patterns, with the ANFIS model providing a consistent mapping between sensor inputs and actuator responses. The obtained results indicate a satisfactory level of performance for motion pattern reproduction, particularly in terms of temporal behavior and transition between movement states. The presented system emphasizes low-cost implementation, computational efficiency, and practical implementation, making it suitable as a proof-of-concept framework for wearable assistive technologies. While the results demonstrate the feasibility of the proposed approach for motion reproduction, further studies involving extended testing and user-specific adaptation are required to assess its potential applicability in real-world scenarios. Full article

Electric Vehicle drive systems must provide fast torque response, low or minimal torque ripple, robustness to both parameter variations and external disturbances. Permanent Magnet Synchronous Motors (PMSMs) are commonly found in electric vehicle propulsion applications due to their high power density, high efficiency, and excellent dynamic performance. However, performance degradation in torque control of PMSMs under time-varying conditions arises from the nonlinear characteristics of motors and their high sensitivity to changes in system parameters. This paper presents a torque-control method with high dynamic bandwidth that combines three techniques: (1) Nonlinear Sliding Mode Torque Control; (2) Predictive Current Control; and (3) Disturbance Estimation. The sliding mode controller provides improved robustness against uncertainties about the system. In addition, the predictive current control provides improved accuracy in current tracking and significantly reduces the time required to achieve a steady state. A disturbance observer is used to compensate for load disturbances and model errors in the motor model. The integrated control architecture is simulated and modeled in MATLAB/Simulink for a typical EV driving environment. The simulation framework produced faster and more accurate torque tracking than conventional PI-type vector controllers, as well as reduced torque ripple and improved disturbance rejection under similar operating conditions. The results demonstrate that the proposed method is a viable candidate for high-performance EV propulsion systems while acknowledging practical limitations such as chattering, tuning complexity, sampling time sensitivity, and the need for further experimental validation. Full article

A novel method for controlling the speed of interior permanent magnet synchronous motors (IPMSMs), known as the current-sensing-based dynamic direct voltage control method under the maximum torque per ampere (MTPA) concept, is introduced. This technique achieves precise tracking of machine velocity by determining the optimal combination of voltage amplitude and angle for each specific motor velocity and current/load condition. Unlike previous studies, this approach takes into account the transient model of the machine, resulting in improved accuracy during dynamic operating conditions compared with existing methods in the literature. Moreover, a comparative analysis is conducted involving different direct voltage MTPA speed drive approaches: the current-sensing dynamic direct voltage control (CS-DDVC) methodology, the simplified DDVC technique, and the static direct voltage MTPA control strategy. The well-known field-oriented control method is also included in the analysis. The dynamic methodology employs two tuning parameters to achieve the same MTPA objective while eliminating transient effects. Experimental results and quantitative assessment demonstrate that the proposed MTPA control methodology is a highly effective strategy, offering a respectable alternative to existing MTPA methods for driving IPMSMs. It enables the operation of IPMSMs under MTPA working conditions with high efficiency, making it suitable for a wide range of industrial applications. Experimental results demonstrate a reduction in speed dip from 120 rpm to 50 rpm at full load application and a 128% improvement in IAE compared to conventional DVC. From an engineering design perspective, the proposed control framework simplifies the drive-system architecture by eliminating cascaded current-control loops while maintaining effective transient dynamic performance suitable for embedded electric vehicle applications. Full article