Search Results (487)

This paper presents an electromechanical coupling model integrating an equivalent magnetic network (EMN) model of a dual three-phase permanent magnet synchronous motor (DTP-PMSM) with the dynamic model of a helical planetary gear transmission system. Using this model, this study analyzes the dynamic characteristics of an electric drive system, specifically motor phase current, electromagnetic torque, and gear meshing force, under self-fault-tolerant control strategies. Simulation and experimental results demonstrate that the self-fault-tolerant control strategy enables rapid fault tolerance during open-phase faults, significantly reducing system fault recovery time. Meanwhile, compared to the open-phase faults conditions, the self-fault-tolerant control effectively suppresses most harmonic components within the system; only the second harmonic amplitude of the electromagnetic torque exhibited an increase. This harmonic disturbance propagates to the gear system through electromechanical coupling, synchronously amplifying the second harmonic amplitude in the gear system’s vibration response. This study demonstrates that self-fault-tolerant control strategies significantly enhance the dynamic response performance of the electric drive system under open-phase faults conditions. Furthermore, this study also investigates the electromechanical coupling mechanism through which harmonics generated by this strategy affect the gear system’s dynamic response, providing theoretical support for co-optimization electromechanical coupling design and fault-tolerant control in high-reliability electric drive transmission systems. Full article

This paper presents an accurate analysis of the power losses of an interior permanent magnet synchronous motor fed by a cascaded H-bridge multilevel inverter. The main goal of this study is to investigate the impact of the cascaded h-bridge inverter, multicarrier PWM strategies, and inverter switching frequency on the synchronous motor power losses. With this aim in mind, a detailed frequency domain power analysis was carried out on motor power losses at different operating points in the frequency–torque plane. Motor power losses were further categorized into fundamental and harmonic power losses. This evaluation involved driving the power converter using six distinct multicarrier PWM strategies at four different switching frequencies. Additionally, a comparison was conducted with a conventional two-level PWM inverter to quantify the reduction in motor power losses. The experimental results show that the cascaded h-bridge inverter guarantees a notable increase in the motor efficiency, up to 7%, and losses in segregation at the fundamental frequency, if compared to the standard two-level PWM inverter, especially at low speed and with partial-load conditions. Such results mark out the cascaded H-bridge inverter as a valuable choice, also with regard to low-voltage drive applications. Full article

In recent years, the rapid spread of electric vehicles (EVs) has intensified the competition to develop power units for EVs. In particular, improving the driving range of EVs has become a major topic, and in order to achieve this, many studies have been conducted on improving the efficiency of EV power units. In this study, we propose a multiple-inverter-drive permanent magnet synchronous motor based on an 8-pole, 48-slot structure, which is commonly used as an EV motor. The proposed motor is composed of two completely independent parallel inverters and windings, and intermittent operation is possible; that is, only one inverter and one parallel winding is used depending on the situation. In the proposed motor, we compare losses including stator iron loss, rotor iron loss, and magnet eddy current loss by PWM voltage inputs for some stator winding topologies, we show that the one-side winding arrangement is the most efficient during intermittent operation, and that it is more efficient than normal operation especially in the low-speed, low-torque range. Finally, through a vehicle-driving simulation considering the efficiency map including motor loss and inverter loss, we show that the intentional use of intermittent operation can improve electrical energy consumption. Full article

This paper presents a simulation framework for evaluating power flow, energy efficiency, thermal behavior, and energy consumption in electric vehicles (EVs) under standardized driving conditions. A detailed Simulink model is developed, integrating a lithium-ion battery, inverter, permanent magnet synchronous motor (PMSM), gearbox, and a field-oriented control strategy with PI-based speed and current regulation. The framework is applied to four standard driving cycles—UDDS, HWFET, WLTP, and NEDC—to assess system performance under varied load conditions. The UDDS cycle imposes the highest thermal loads, with temperature rises of 76.5 °C (motor) and 52.0 °C (inverter). The HWFET cycle yields the highest energy efficiency, with PMSM efficiency reaching 92% and minimal SOC depletion (15%) due to its steady-speed profile. The WLTP cycle shows wide power fluctuations (−30–19.3 kW), and a motor temperature rise of 73.6 °C. The NEDC results indicate a thermal increase of 75.1 °C. Model results show good agreement with published benchmarks, with deviations generally below 5%, validating the framework’s accuracy. These findings underscore the importance of cycle-sensitive analysis in optimizing energy use and thermal management in EV powertrain design. Full article

This research presents a method for improving the regenerative efficiency of interior permanent magnet synchronous motors (IPMSMs) used in traction applications such as electric vehicles. In conventional powertrain control, the maximum torque per ampere (MTPA) strategy is commonly applied in the constant-torque region. However, this approach does not account for the combined losses of both the motor and inverter. In this study, overall system efficiency is investigated, and an improved current combination is proposed to minimize total losses. The single switching method is employed in the inverter due to its simplicity and its ability to reduce inverter losses. Simulations incorporating both motor and inverter losses were performed for two driving conditions around the MTPA current point. The results show that the optimal current combination slightly deviates from the MTPA point and leads to a slight improvement in efficiency. Experimental results under the two steady-state driving torque and angular velocity conditions confirm that the optimized current combination enhances system efficiency. Furthermore, simulations based on the Urban Dynamometer Driving Schedule predict an increase in recovered energy of approximately 1%. The proposed control strategy is simple, easy to implement, and enables the powertrain to operate with highly efficient current references. Full article

The lower-limb assistance exoskeleton is increasingly being utilized in various fields due to its excellent performance in human body assistance. As a crucial component of robots, the joint is expected to be designed with a high-output torque to support hip and knee movement, and lightweight to enhance user experience. Contrasted with the elastic actuation with harmonic drive and other flexible transmission, the non-elastic quasi-direct actuation is more promising to be applied in exoskeleton due to its advanced dynamic performance and lightweight feature. Moreover, robot joints are commonly driven electrically, especially by a permanent magnet synchronous motor which is rapidly developed because of its compact structure and powerful output. Based on different topological structures, numerous research focus on torque density, ripple torque suppression, efficiency improvement, and thermal management to improve motor performance. Furthermore, the elaborated joint with powerful motors should be controlled compliantly to improve flexibility and interaction, and therefore, popular complaint control algorithms like impedance and admittance controls are discussed in this paper. Through the review and analysis of the integrated design from mechanism structure to control algorithm, it is expected to indicate developmental prospects of lower-limb assistance exoskeleton joints with optimized performance. Full article

Elevators are a vital part of urban infrastructure, playing a key role in smart cities where increasing population density has driven the rise in taller buildings. As an essential means of vertical transportation, elevators have become an integral part of daily life, making their design, construction, and maintenance crucial to ensuring safety and compliance with evolving industry standards. The safety of elevator systems depends on the continuous monitoring and fault-free operation of Permanent Magnet Synchronous Motor (PMSM) drives, which are critical to their performance. Furthermore, the fault-free operation of PMSM drives reduces operating costs, increases service life, and improves reliability. The PMSM drive components may be susceptible to electrical, mechanical, and thermal faults that, if undetected, can lead to operational disruptions or safety risks. The integration of artificial intelligence and Internet of Things (IoT) technologies can enhance fault prediction, reducing downtime and improving efficiency. Ongoing challenges such as managing machine thermal load and developing more durable materials for PMSMs require the development of suitable models that are adapted to existing drive systems. The proposed framework for fault prediction is validated on a real residential elevator equipped with a PMSM drive. Multimodal signal data is processed through a Generative Adversarial Network (GAN)-enhanced Positive Unlabeled (PU) classifier and a Reinforcement Learning (RL)-based adaptive decision engine, enabling robust and scalable fault prediction in a non-intrusive fashion. Full article

Conventional model-free control (MFC) is widely used in motor drives due to its simplicity and model independence, yet its performance suffers from imperfect disturbance estimation and input gain mismatch. To address these issues, this paper proposes an adaptive enhanced model-free speed control (AEMFSC) scheme based on an ultra-local model for permanent magnet synchronous motor (PMSM) drives. First, by integrating a nonlinear disturbance observer (NDOB) and a PD control law into the generalized model-free controller, an enhanced model-free speed controller (EMFSC) was developed to ensure closed-loop stability. Compared with a conventional MFSC, the proposed method eliminated steady-state errors, reduced the speed overshoot, and achieved faster settling with improved disturbance rejection. Second, to address the performance degradation induced by input gain $\alpha$ mismatch during time-varying load conditions, we developed an online parameter identification method for real-time $\alpha$ estimation. This adaptive mechanism enabled automatic controller parameter adjustment, which significantly enhanced the transient tracking performance of the PMSM drive. Furthermore, an algebraic-framework-based high-precision identification technique is proposed to optimize the initial $\alpha$ selection, which effectively reduces the parameter tuning effort. Simulation and experimental results demonstrated that the proposed AEMFSC significantly enhanced the PMSM’s robustness against load torque variations and parameter uncertainties. Full article

To address the issue of reduced observer accuracy under low carrier–frequency ratio (CFR) conditions in the sensorless control of high-speed motors, which limits system performance, this paper proposes a discrete mathematical modeling method for surface-mounted permanent magnet synchronous motors (SPMSMs). Based on this established accurate discrete motor model, the influence of low CFR on the phase estimation error of back electromotive force (EMF) is analyzed. Building on this foundation, an accurate discrete Luenberger observer (ALO) is designed, and a corresponding phase compensation control method is proposed. A motor drive control system comprising hardware, software, and experimental test setups is constructed. The experimental results demonstrate that, compared to the Euler model, the discrete mathematical model established by this method significantly improves position observation accuracy under low CFR conditions. Furthermore, compared to the traditional Luenberger observer (TLO), the estimation error of the proposed observer under a low CFR is reduced by approximately 85%. This approach exhibits high application value in the sensorless control of high-speed and high-frequency motors. Full article

The mechanical connection between a transmission system and an electric motor gives rise to a strong interaction between their respective dynamics. In particular, the coupling between an electric motor and a nonlinear spur gear transmission significantly influences the overall dynamic behavior of the integrated system. This study presents a detailed investigation into the electromechanical coupling effects between a permanent magnet synchronous machine (PMSM) and a nonlinear spur gear transmission. To focus on these effects, three configurations are analyzed: (i) a standalone gear pair model without motor interaction, (ii) a combined gear–motor system without dynamic coupling, and (iii) a fully coupled electromechanical system where the mechanical feedback influences motor control. The dynamic interaction between the motor’s torsional vibrations and the gear transmission is captured using the derivative of the transmission error as a feedback signal, enabling a closed-loop electromechanical model. Numerical simulations highlight the critical role of this coupling in shaping system dynamics, offering insights into the stability and performance of electric drive–gear transmission systems under different operating conditions. It also underscores the limitations of traditional modeling approaches that neglect feedback effects from the mechanical subsystem. The findings contribute to a more accurate and comprehensive understanding of coupled motor–gear dynamics, which is essential for the design and control of advanced electromechanical transmission systems in high-performance applications. Full article

In response to the limitations of suboptimal control accuracy, compromised synchronization capability, and reduced stability inherent in PID control for conventional shaftless multi-permanent magnet synchronous motor drive systems, this article establishes a three-motor synchronous control system model for a shaftless printing system. On this basis, the speed loop adopts a sliding mode controller (NSMC) based on a new approach law, and the current loop adopts an improved super spiral structure. At the same time, the compensator of the deviation coupling control structure (NDCS) is optimized by weighted arithmetic mean. Finally, comparative simulation experiments were conducted on the system model using various algorithms. The results show that the deviation coupling control structure based on improved sliding mode control has better anti-interference ability, control accuracy, and synchronization in the synchronous control strategy of a multi-permanent magnet motor drive in a shaftless printing system, which is conducive to the safe and stable operation of shaftless printing systems under multiple working conditions. Full article

The application fields of high-speed submersible permanent magnet synchronous motors (PMSM) are constantly expanding. Especially in high-risk and complex environments such as oil exploration, offshore oil exploitation, and deep well operation, the reliability, stability, and efficiency of motor drive systems are more and more prominent. The submersible motor is greatly affected by load disturbance, pressure change, and external oil flow, and the traditional method may not perform well in complex disturbance problems. Therefore, a three-order adaptive nonlinear extended state observer is proposed to collect the input and output information of the system in real time, and estimate the motor speed, position, and total disturbance. A linear feedback control law is designed to eliminate the disturbance. The superiority of the proposed algorithm under complex operating conditions is verified by the Simulink model and experiments, which provide a theoretical basis for the control of submersible motors. Full article

The interior permanent magnet synchronous motors (IPMSMs) are extensively applied in the field of new energy vehicles due to their high-power density and excellent performance control. However, the iron loss has a significant impact on their performance. This study conducts an optimization analysis on the processing technology of silicon steel sheets and motor structure, targeting the reduction of iron loss and the improvement of the motor’s integrated efficiency. Firstly, the influences of two iron core processing technologies on iron loss, namely gluing and welding, are compared. Through experimental tests, it is found that the iron loss density of the gluing process is lower than that of the welding process, and as the magnetic flux density increases, the difference between the two is expanding. Therefore, the iron loss test data from the adhesive process are employed to develop a variable-coefficient iron loss model, enabling precise calculation of the motor’s iron loss. On this basis, aiming at the problem of excessive iron loss of the motor, a novel topological structure of the stator and rotor is proposed. With the optimization goal of reducing the motor iron loss and taking the connection port of the air magnetic isolation slot and the gap of the stator module as the optimization variables, the optimized design of the IPMSM with low iron loss is achieved based on the Taguchi method. After optimization, the stator iron loss decreases by 13.60%, the rotor iron loss decreases by 20.14%, and the total iron loss is reduced by 15.34%. The optimization scheme takes into account both the electromagnetic performance and the process feasibility, it offers technical backing for the high-efficiency operation of new energy vehicle drive motors. Full article

Parameter mismatch in model predictive control (MPC) strategies presents significant challenge in permanent magnet synchronous motor (PMSM) control, often leading to reduced tracking accuracy and compromised system stability under dynamic operating conditions. To address above issue, this article proposes a modified parameter robust FCS-MPC framework that integrates an online learning echo state network (ESN) for real-time compensation of parameter deviations. By leveraging the structural simplicity and application efficiency of ESNs during training, the proposed approach is well-suited to tackling complex parameter variation challenges via online learning. Initially, the ESN is trained offline using data derived from a PMSM-MPC control environment. Subsequently, the trained ESN replaces the predictive model of the MPC controller, enabling online learning under varying PMSM driving conditions. The incorporation of an online ESN allows the proposed controller to achieve real-time adjustments that mitigate the effects of parameter mismatch. Plenty of simulation studies are available and demonstrate that the proposed ESN-MPC controller exhibits enhanced robustness against parameter mismatch compared to the traditional FCS-MPC method. Full article

Wide-speed regulation control strategies for Interior Permanent Magnet Synchronous Motors (IPMSMs) are widely applied in industrial fields. However, traditional algorithms are prone to being affected by motor parameter mismatches, sensor sampling errors, and other disturbances under complex operating conditions, leading to insufficient robustness. In order to enhance dynamic performance while simultaneously ensuring robustness, we analyzed the limitations of traditional control strategies and, based on this, proposed an improved control framework. A Multi-Axis Coordinated Extended State Observer(MCESO)-based robust control framework was developed for full-speed domain operation, which enhances disturbance rejection capability against parameter uncertainties and abrupt load changes through hierarchical disturbance estimation. Subsequently, the effectiveness and stability of the proposed method were verified through theoretical analysis and simulation studies. Compared with traditional control strategies, this method can effectively observe and compensate for a series of complex issues such as nonlinear disturbances during operation without requiring additional hardware support. Finally, extensive experimental tests were carried out on a 500 W IPMSM dual-motor drive platform. The experimental results demonstrated that, even under harsh operating conditions, the proposed scheme can effectively suppress torque ripple and significantly reduce current harmonics. Full article