Search Results (29)

This study introduces a paradigm shift in permanent magnet synchronous motor (PMSM) control through the development of hybrid dual fractional-order sliding mode control (HDFOSMC) architecture integrated with evolutionary parameter learning (EPL). Conventional PMSM control frameworks face critical limitations in ultra-precision applications due to their inability to reconcile dynamic agility with steady-state precision under time-varying parameters and compound disturbances. The proposed HDFOSMC framework addresses these challenges via two synergistic innovations: (1) a dual fractional-order sliding manifold that fuses the rapid transient response of non-integer-order differentiation with the small steady-state error capability of dual-integral compensation, and (2) an EPL mechanism enabling real-time adaptation to thermal drift, load mutations, and unmodeled nonlinearities. Validation can be obtained through the comparison of the results on PMSM testbenches, which demonstrate superior performance over traditional fractional-order sliding mode control (FOSMC). By integrating fractional-order theory, sliding mode control theory, and parameter self-tuning theory, this study proposes a novel control framework for PMSM. The developed system achieves high-precision performance under extreme operational uncertainties through this innovative theoretical synthesis and comparative results. Full article

The traditional deadbeat predictive current control (DPCC) strategies for a permanent magnet synchronous motor (PMSM), such as those based on an extended state observer (ESO) and quasi-resonant extended state observer (QRESO), usually require large observer bandwidth, rendering the system sensitive to noise. To address this issue, this paper proposes a cascaded quasi-resonant extended state observer-based DPCC (CQRESO-based DPCC) strategy. Specifically, the CQRESO is utilized to estimate the predicted values of d-axis and q-axis currents, as well as the system total disturbance caused by the deterministic and uncertain factors at time instant k + 1. Subsequently, the required control command voltage at time instant k + 1 is then calculated according to the deadbeat control principle. Finally, the comparative simulation results with ESO-based DPCC and QRESO-based DPCC strategies demonstrate that the proposed strategy can achieve dynamic and robust performance comparable to the ESO-based and QRESO-based DPCC strategies while utilizing a smaller observer bandwidth. Additionally, it exhibits superior steady-state performance and 5th and 7th harmonic current suppression capabilities (in the abc reference frame). 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

Efficient heat dissipation remains a critical challenge in the research and development of automotive permanent magnet synchronous motors. In this study, a Tesla valve cooling channel is innovatively designed, and a corresponding flow model is established using computational fluid dynamics (CFD) simulations. The effects of the spacing between adjacent Tesla valves, the number of stages, and inlet velocities on motor temperature rise and pressure drop within the channel are analyzed under varying flow directions. A comprehensive evaluation of 25 simulation samples reveals that the reverse flow Tesla valve-type channel, with an inlet velocity of 1 m/s, 90 mm spacing, and 16 stages, achieves an optimal balance between cooling performance and energy consumption. Compared to the conventional spiral waterway design, this configuration reduces the maximum temperature and temperature difference by 1.5% and 2.2%, respectively, while maintaining a relatively low pressure drop. Additionally, the structure enhances the coolant’s heat exchange capacity, effectively lowering the peak temperature of the motor. These findings provide valuable insights for advancing motor cooling technologies. Full article

Fuel cells (FCs) offer several operational advantages when integrated as a power source in electric vehicles (EVs). Since the voltage of these cells is typically low, usually less than 1 V, the power conversion system requires a DC–DC converter capable of providing a high voltage conversion ratio to match the input voltage of the motor propulsion system, which can exceed 400 V and reach up to 800 V. The modular DC–DC boost converter proposed in this paper is designed to achieve a high voltage step-up ratio for the input FC voltages through the use of isolated series-connecting boosting submodules connected. The power electronic topology employed in the submodules (SMs) is designed to provide a flexible output voltage while maintaining a continuous input current from the fuel cells with minimal current ripple to improve the FC’s performance. The proposed step-up modular converter provides several benefits including scalability, better controllability, and improved reliability, especially in the presence of partial faults. Computer simulations using MATLAB/SIMULINK^® software (R2024a) have been used to study the feasibility of the proposed converter when connected to a permanent magnet synchronous motor (PMSM). Also, experimental results using a 1 kW prototype composed of four SMs have been obtained to validate the performance of the proposed converter. Full article

The aviation industry is undergoing electrification due to the increased global focus on reducing emissions in air traffic. Regarding the volatility of raw material prices, one main objective is the increase in the specific power of the motor. This matches the ambitious targets of the CoE project (Center of Excellence) in Finland on high-speed electric motors. The targeted specific power is 20 kW/kg. In this work, motors are designed and optimized for a fully electric regional aircraft. motors with different slot/pole configurations and rotational speed values are studied to determine the advantage of increasing speed in terms of weight reduction. As increasing speed requires the use of a gearbox, the overall weight of the motor and the gearbox is evaluated in post-processing, which allows for determining the impact of high speed on the overall weight. An optimization tool coupled with an electromagnetic and mechanical analysis is used to optimize 1 MW surface mounted permanent magnet synchronous motors (S-PMSMs) for given specifications of regional electric aircraft. Optimization results indicate that there is considerable gain in terms of overall weight only when increasing the speed to the range of 10,000–15,000 rpm. Full article

For an electric locomotive traction motor, it is necessary to maintain relatively low vibration and noise due to the higher design standards. By using effective motor control strategies and implementing current harmonic suppression schemes, motor efficiency and vibration and noise suppression can be effectively improved. This study investigates the current harmonic suppression strategy for permanent magnet synchronous motors by (1) constructing a mathematical model of the permanent magnet motor to explore the sources of low-order harmonics currents such as fifth and seventh harmonics, as well as high-order harmonics at switch frequencies and their multiples, and analyzing the electromagnetic force characteristics generated by the current, and (2) establishing a vector control system for the permanent magnet motor. To suppress the fifth and seventh harmonic components in the current, a resonance controller is constructed, which utilizes the parallel connection of a resonator and PI controller to achieve low-order harmonic suppression. The factors affecting the effectiveness of the resonance controller’s suppression are also analyzed. The experiments are conducted, and the current harmonic suppression scheme constructed in this study can effectively reduce the harmonics in the current, thereby reducing motor vibration and noise. Full article

This paper designs a safe, low-cost, and efficient permanent magnet synchronous motor (PMSM) booster pump system. The aim is to enhance the pump’s safety and reduce the incidence of electric shock accidents, while also achieving cost reduction and efficiency improvement. The pump components are made of a plastic material, and a safe voltage of 36 V is used as the operating voltage. Additionally, the PMSM is chosen to replace the induction motor (IM) as the pump’s driving device, utilizing sensorless control and field-weakening control strategies. The study results show that when the flow rate is 1.51 m³/h, the efficiency of the PMSM low-voltage pump can reach up to 20.86%. At the same flow rate of 1 m³/h, compared to other pumps, the PMSM low-voltage pump exhibits higher head, energy savings, and efficiency. The proposed PMSM low-voltage pump offers advantages such as high efficiency, energy savings, safety, and low cost. This study provides a reference for the domestic PMSM pump industry. Full article

Addressing the issue of significant speed fluctuations in permanent magnet synchronous motors (PMSM) under load, this paper proposes an active disturbance rejection control strategy based on an improved particle swarm optimization (PSO) algorithm. Initially, the speed of the PMSM is considered as the comprehensive optimization objective, and an active disturbance rejection control (ADRC) model for the PMSM is established by integrating the ADRC with vector control. Subsequently, an adaptive PSO algorithm incorporating genetic algorithms is proposed. This algorithm uses chaotic initialization for uniform particle distribution, introduces adaptive inertia weight and dynamic cognitive factors to enhance search efficiency, and integrates the crossover and mutation modules from genetic algorithms, optimizing mutations using a Gaussian probability function. Simulation results demonstrated that: (1) under identical external load conditions, the proposed ADRC strategy ensured smaller speed fluctuations and a smoother waveform for the PMSM, and (2) compared to the traditional PSO algorithm, the proposed method reduced the speed fluctuation after external load by approximately 26%. Full article

Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit fault diagnosis system faces challenges in precisely detecting specific faulty switches. The proposed work presents a neural network-based open-circuit fault diagnosis system for identifying faulty power switches in inverter-driven motor systems. The system leverages trained phase-to-phase voltage data from the motor to recognize the type and location of faults in each phase with high accuracy. Employing separate neural networks for each of the three phases in a three-phase permanent magnet synchronous motor, the system achieves an outstanding overall fault detection accuracy of approximately 99.8%, with CNN and CNN-LSTM architectures demonstrating superior performance. This work makes two key contributions: (1) implementing neural networks to significantly improve the accuracy of locating faulty switches in open-circuit fault scenarios, and (2) identifying the optimal neural network architecture for effective fault diagnosis within the proposed system. Full article

This paper proposes a NCPM (Nano-composite coated permanent magnets)-based IPMSM (Interior Permanent Magnet Synchronous Motor) electric drive system, especially applicable for electric vehicles (EV). For an EV, an increase in the “T/A (torque per ampere)” condition is highly recommended, as it directly affects the maximum distance run by EV on a single charge. Due to NCPM, a substantial increase in magnetic flux intensity, resistance to corrosion and Curie temperature are observed. As a result, the proposed drive clearly exhibits a higher power to weight ratio. Also, it is capable of delivering higher T/A to the drive system without any considerable change in two important factors of EV: (1) mass and volume of the drive system (2) battery capacity of the drive system. Moreover, NCPM performance is less susceptible to temperature variation, which makes it an appropriate candidate for vehicular applications, where temperature inconsistency could be a common issue during working conditions. Also, NCPM-based IPMSM offers a quicker speed response than conventional IPMSM, thus providing higher acceleration, which is one of the important performance factors for vehicular applications. A vector controlled mathematical model of IPMSM and NCPM-based IPMSM is tested for various speed commands. Also, the NCPM-based IPMSM, in the proposed configuration, is fed from a three-level DCMLI (diode clamped multi-level inverter), as the drive system is considered for medium to high power applications. A comparative performance analysis is carried out between the proposed drive system and a conventional IPMSM-based drive system using MATLAB/SIMULINK to indicate the efficacy of the proposed configuration. Full article

In rail transit traction, synchronous reluctance machines (SynRMs) are potential alternatives to traditional AC motors due to their energy-saving and low-cost characteristics. However, the nonlinearities of SynRMs are more severe than permanent magnet synchronous motors (PMSM) and induction motors (IM), which means the characteristics of SynRMs are challenging to model accurately. The parameter identification directly influences the modeling of nonlinearity, while the existing algorithms tend to converge prematurely. To overcome this problem, in this paper, a hybrid optimizer combining the SCA with the SSO algorithm is proposed to obtain the parameters of SynRMs, and the proposed Sine-Cosine self-adaptive synergistic optimization (SCSSO) algorithm preserves the self-adaptive characteristic of SSO and the exploration ability of SCA. Comprehensive numerical simulation and experimental tests have fully demonstrated that the proposed method has obviously improved parameter identification accuracy and robustness. In the dq-axis flux linkage, the mismatch between reference and estimated data of proposed algorithm is below 1% and 6%, respectively. Moreover, the best d-axis RMSE of SCSSO is 50% of the well-known algorithm CLPSO and 25% of BLPSO and its performance has improved by two orders of magnitude compared to traditional simple algorithms. In the q-axis, the best RMSE is 10% of CLPSO and 50% of Rao-3 and Jaya. Moreover, the performance of the proposed algorithm has improved nearly 90 times compared to traditional simple algorithms. Full article

Nowadays, energy shortages and environmental pollution have received a lot of attention, which makes the electrification of transportation systems an inevitable trend. As the core part of an electrical driving system, the electrical machine faces the extreme challenge of keeping high power density and high efficiency output under complex workin g conditions. The development and research of new soft magnetic materials has an important impact to solve the current bottleneck problems of electrical machines. In this paper, the variation trend of magnetic properties of ultra-thin grain-oriented silicon steel electrical steel (GOES) under thermal-mechanical-electric-magnetic fields is studied, and the possibility of its application in motors is explored. The magnetic properties of grain-oriented silicon steel samples under different conditions were measured by the Epstein frame method and self-built multi-physical field device. It is verified that the magnetic properties of grain-oriented silicon steel selected within 30° magnetization deviation angle are better than non-grain-oriented silicon steel. The magnetic properties of the same ultra-thin grain-oriented silicon steel as ordinary non-oriented silicon steel deteriorate with the increase in frequency. Different from conventional non-grain-oriented silicon steel, its magnetic properties will deteriorate with the increase in temperature. Under the stress of 30 Mpa, the magnetic properties of the grain-oriented silicon steel are the best; under the coupling of multiple physical fields, the change trend of magnetic properties of grain-oriented silicon steel is similar to that of single physical field, but the specific quantitative values are different. Furthermore, the application of grain-oriented silicon steel in interior permanent magnet synchronous motor (IPM) for electric vehicles is explored. Through a precise oriented silicon steel motor model, it is proved that the magnetic flux density of stator teeth increases by 2.2%, the electromagnetic torque of motor increases by 2.18%, and the peak efficiency increases by 1% after using grain-oriented silicon steel. In this paper, through the investigation of the characteristics of grain-oriented silicon steel, it is preliminarily verified that grain-oriented silicon steel has a great application prospect in the drive motor (IPM) of electric vehicles, and it is an effective means to break the bottleneck of current motor design. Full article

This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an $abc$ frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, four structured residuals are designed based on the acquired redundant sub-models to detect measurement faults in the encoder and ITSC faults, which are applied in different levels of each phase winding. The effectiveness of the proposed detection method is validated by an in-house test setup of an inverter-fed PMSM, where ITSC and encoder faults are applied to the system in different time intervals using controllable relays. Finally, a statistical detector, namely a generalized likelihood ratio test algorithm, is implemented in the decision-making diagnostic system resulting in the ability to detect ITSC faults as small as one single short-circuited turn out of 102, i.e., when less than 1% of the PMSM phase winding is short-circuited. Full article

In this paper, the rotor position estimation performance of the sensorless scheme for permanent magnet synchronous motors (PMSMs) implemented through the injection of high-frequency square-wave voltage according to the frequency of the square-wave voltage is presented through HILS (Hardware In the Loop Simulation) experiments. An inverter using an IGBT device usually has a switching frequency of around 15 kHz. On the other hand, GaN devices that can be switched on and off at frequencies higher than 100 kHz have been recently developed, and research is being actively conducted to apply GaNs to a variable speed system. The purpose of this study is to conduct HILS experiments to analysis the rotor position estimation ability of the sensorless technique in cases where a high switching frequency was applied, such as GaN devices, with that of a system having a usual switching frequency, such as IGBT. In the HILS system used in this study, an inverter and motor model implemented with Simulink are located in a real-time simulator. A sensorless motor control method was implemented with an FPGA control board, which includes a PWM interrupt service routine of 100 kHz frequency and a harmonic injection and position detection algorithm. The HILS experiments show rotor position detection errors according to the various frequency of the harmonic voltage injected for estimating the rotor position with a PWM frequency of 100 kHz cases. According to the experimental results, good position estimation was possible not only when the harmonic of 10 kHz corresponding to 1/10 of the PWM frequency was injected, but also when the harmonic of 1 kHz corresponding to 1/100 of the PWM frequency was injected. The experiments suggest that position estimation errors decrease as the frequency of the harmonic voltage increases, and, based on the foregoing, it is thought that the application of a GaN device capable of realizing a high switching frequency in a variable speed drive system can be another advantage. Full article