Search

The flux switching permanent magnet (FSPM) motor is a stator permanent magnet motor. The typical FSPM motor is doubly salient, which generates torque ripple and affects the rotation smoothness. In this paper, the influence of salient pole geometric sizes on motor torque performance is studied to reduce motor torque ripple and improve motor torque density. First, three indicators are defined to present the motor torque characters, including the average torque, torque ripple, and the volume of permanent magnet material usage. Then, the model of salient pole geometric sizes function to the three indicators is created. With this model, the optimal solution is obtained by the multi-objective numerical optimization. Based on the optimized results, the rotor shape is refined and analyzed as the supplementary to reduce the torque ripple further. Finally, the results show that the optimization procedure in this paper can effectively weaken the torque ripple, reduce the permanent magnet material usage, and improve the average output torque of the motor. Based on the optimized data, the prototype machine is built to verify the analysis results and prove the feasibility of this research. [ABSTRACT FROM AUTHOR]

When magnetic saturation occurs during the operation of a permanent magnet (PM) slotless brushless DC motor, the material permeability will no longer be a constant value, and the neglected magnetic saturation model used for motor optimization will no longer be applicable. And considering that the increase in motor torque will lead to a high temperature rise of the winding, therefore, an electromagnetic heat coupling model applicable to the occurrence of magnetic saturation in the motor is established, and the model is utilized in combination with the particle swarm algorithm to enhance the maximum output torque of the motor. Firstly, a 100 W, 16,400 r/min high-speed PM slotless DC brushless motor is taken as the object of study, and its electromagnetic–thermal coupling model is established to derive the analytical equations for the electromagnetic torque with respect to the split ratio, the thickness of the stator yoke, the PM thickness, and the copper loss. Secondly, based on the modeling, the motor was optimized using a particle swarm algorithm to maximize the output torque and minimize the copper loss. Finally, a prototype was fabricated and verified with the prototype through no-load and load experiments. The difference between the theoretical maximum output torque and the experimental maximum output torque is less than 8%. The results show that this method can effectively predict the maximum output torque of the motor in the case of magnetic saturation, and the model is suitable for increasing the maximum output torque of slotless brushless DC motors under space constraints. [ABSTRACT FROM AUTHOR]

The flux switching permanent magnet (FSPM) motor is a stator permanent magnet motor. The typical FSPM motor is doubly salient, which generates torque ripple and affects the rotation smoothness. In this paper, the influence of salient pole geometric sizes on motor torque performance is studied to reduce motor torque ripple and improve motor torque density. First, three indicators are defined to present the motor torque characters, including the average torque, torque ripple, and the volume of permanent magnet material usage. Then, the model of salient pole geometric sizes function to the three indicators is created. With this model, the optimal solution is obtained by the multi-objective numerical optimization. Based on the optimized results, the rotor shape is refined and analyzed as the supplementary to reduce the torque ripple further. Finally, the results show that the optimization procedure in this paper can effectively weaken the torque ripple, reduce the permanent magnet material usage, and improve the average output torque of the motor. Based on the optimized data, the prototype machine is built to verify the analysis results and prove the feasibility of this research.

This paper presents a comprehensive investigation of the optimal design of an interior permanent magnet synchronous motor (IPMSM) for electric vehicles (EVs), utilizing the hybrid artificial bee colony algorithm–support vector machine (HAS) algorithm. The performance of the drive motor is a crucial determinant of the overall vehicle performance, particularly in EVs that rely solely on a motor for propulsion. In this context, interior permanent magnet synchronous motors (IPMSMs) offer a compelling choice due to their high torque density, wide speed range, superior efficiency, and robustness. However, accurate analysis of the nonlinear characteristics of IPMSMs necessitates finite element analysis, which can be time-consuming. Therefore, research into methods for deriving an optimal model with minimal computation is of significant importance. The HAS is a powerful multimodal optimization technique that is capable of exploring several optimal solutions. It enhances the navigation capability by combining the artificial bee colony algorithm (ABC) with the kernel support vector machine (KSVM). Specifically, the algorithm improves the search ability by optimizing the movement of bees in each region generated by the KSVM. Furthermore, hybridization with the Nelder–Mead method ensures accurate and quick convergence at pointers discovered in the ABC. To demonstrate the effectiveness of the proposed algorithm, this study compared its performance with a conventional algorithm in two mathematical test functions, verifying its remarkable performance. Finally, the HAS algorithm was applied to the optimal design of the IPMSM for EVs. Overall, this paper provides a thorough investigation of the application of the HAS algorithm to the design of IPMSMs for electric vehicles, and its application is expected to benefit from the combination of machine-learning techniques with various other optimization algorithms. [ABSTRACT FROM AUTHOR]

The application of new soft magnetic materials in permanent magnet motor can effectively reduce the loss of motor and improve the efficiency of motor. Taguchi method is a local multivariable and multi-objective optimization method widely used in various engineering problems, which can effectively improve the efficiency of engineering optimization. In this paper, based on a 25kW, 1700r/min three-phase permanent magnet motor, the relevant motor model is established in the finite element simulation software, and the relevant simulation analysis is carried out. Combined with Taguchi method optimization, the local optimal structure scheme is obtained. Through optimization, the motor can maintain high efficiency, reduce the cogging torque of the motor by 53.45%, reduce the torque ripple by 36.79%, and increase the torque generated by the permanent magnet per unit mass by 21.42%. Through this optimization, the overall performance of the motor has been significantly improved. The research content of this paper verifies the feasibility of the application of Taguchi method in the optimization of new soft magnetic material motor, provides a new idea for the optimization design of new soft magnetic material motor, and also provides a certain reference for the local multi-objective optimization of the electromagnetic structure of other similar motors.

To help the reverse Brayton cycle cool the refrigerant from 100 K to 50 K, an auxiliary generator, with a housed stator, is studied and optimized, and the influences of weights in the cost- function on the results are discussed. The power demand and adiabatic characteristics of reverse Brayton cycle expansion are analyzed, after which the optimization indexes, including output rated power, efficiency, the air gap between rotor and stator, loss, and volume, are decided. The initial model of the auxiliary generator is then constructed and the parameters to be optimized are also determined. Taking the low loss and sinusoidal back-EMF as the evaluation indexes, the single parameter optimizations of the auxiliary generator are carried out. The co-simulation of the generator and its corresponding driving circuit is investigated, with which the power generation efficiency is calculated. The global optimizations of the generator parameters are carried out using a genetic algorithm. A suitable analytic hierarchy process (AHP) model is proposed, with which a three-order judgment matrix is constructed, and the effects of different weight combinations, in the cost-function, on generator performance are compared. The experimental results show that the output back-EMF amplitude is 28.2 V, which is about 10% smaller than the simulation results; the output power of the auxiliary generator under load is about 3.7 W, meeting the rated demand. [ABSTRACT FROM AUTHOR]

This paper is focused on the design, optimisation and control of a permanent magnet assisted synchronous reluctance machine (PMaSynRel) for low cost high efficiency household appliances, in particular a motor for washing machine. The design and optimisation of the motor aims at maximising the torque produced and power factor, while minimise torque oscillations and the losses, thus improving the efficiency. A campaign of tests has been carried out on the prototype of the optimised machine, comparing finite element results and experimental measurements as a validation of the proposed design. In addition, torque ripple measurements are confirming that the solution proposed is meeting the optimisation design targets. The outcomes of this project are demonstrating that PMaSynRel drives are a suitable candidate for white goods sector, and that the proposed design is able to boost the performance and efficiency class with respect to the state-of-the-art solutions. [ABSTRACT FROM AUTHOR]

The equipment cost of pumping unit is one of the main investment costs of No. 2 oil production plant. Its annual power consumption is 41 million kwh, accounting for 10.8% of the energy consumption cost of the whole plant. The existing pumping units mainly include 14 and 16 beam walking units and 900 and 1 000 vertical units. According to the electrical parameter test and calculation, the average system efficiency is only 18.8%, far lower than the domestic average of 27%. Therefore, the management should be strengthened to improve the energy saving of the system. In this paper, the main reason of energy consumption loss of pumping unit in our plant is pointed out through the research and field practice of pumping unit energy saving, and the method of reducing cost and energy saving that is suitable for the second plant is found, which provides a guiding method for the later energy saving of pumping unit, and has great significance for comprehensive promotion. [ABSTRACT FROM AUTHOR]

The segmented-stator dual-rotor axial flux permanent magnet motor (AFPMM) in this article adopts two-segment Halbach permanent magnets (PMs) in the rotor and soft magnetic composite materials in the stator core, so it has the advantages of high torque density and high efficiency. This article proposes an optimization method for AFPMMs combining analytical optimization and nonlinear optimization, based on the analytical calculation of the magnetic field and electromagnetic performance. To realize analytical calculations, the AFPMM is regarded as the superposition of equivalent linear PM motor slices at different radii. The magnetic field is calculated using the slotless 2-D equivalent model and the slotted air gap relative permeability. Compared with finite-element analysis (FEA), the analytical calculation of the electromagnetic characteristics has acceptable accuracy and faster speed. The multiobjective optimization program for the AFPMM aims at lighter motor mass and lower loss. In analytical optimization, the expression of the optimal axial magnetization coefficient of the two-segment Halbach array and the expression of the minimum rotor core thickness is deduced to improve the optimization speed and results. Then, the nonlinear optimization algorithm is used to solve the multiobjective optimization problem. [ABSTRACT FROM AUTHOR]

As well known, enhancing pump system efficiency and reducing energy consumption have a great significance to develop low-carbon economy. Therefore, power matching research of motor-pump system based on genetic algorithm was carried out in this paper. Firstly, constructing test platform of motor and centrifugal pump to obtain model data. Secondly, the simulation model of motor-pump system was established based on centrifugal pump impeller angular velocity equal to motor angular velocity. Thirdly, asynchronous motor is optimized by genetic algorithm to reduce capacity and save energy. Finally, comparing and analysing the matching situation of optimized asynchronous motor and original prototype with centrifugal pump, the total power consumption of optimized motor is lower 214.3 W than original prototype, save power reached 15.58 %. The optimized machine pump system efficiency increased at least 1.32% under all condition and increased by 2.24 % on average. It proves the method of motor-pump system power matching effectiveness and practicability. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of electric drive systems are crucial in electric vehicles. Based on the dynamic finite element method and previous studies, this study proposes and analyzes a new mathematical model for a motor longitudinally mounted on a centralized electric drive system of a pure electric vehicle. First, we analyze the largest torque ripple of a fractional slot concentrated winding inner-mounted permanent magnet synchronous motor designed for commercial electric vehicles. This torque ripple is identified as one of the excitations influencing the dynamic performance of the electric drive system. Second, a new dynamic mathematical model for the electric drive system is established. Third, we investigate the linear vibration responses of the system subject to torque ripple and transmission error. Finally, the relationships between critical motor parameters and dynamic mesh force are revealed. The results demonstrate that the proposed theoretical method can effectively determine the dynamic characteristics of the electric drive system, thereby providing valuable theoretical guidance for the design and optimization of the motor and electric drive system.

A linear oscillating motor is an electromagnetic actuator that can achieve short-stroke reciprocating movement directly without auxiliary transmission mechanisms. It has been widely used in linear pump applications as the source of power and motion. However, because of the demand of high power density in a linear actuation system, the performance of linear oscillating motors has been the focus of studies and deserves further research for high power density. In this paper, a general framework of linear oscillating motor design and optimization is addressed in detail, including the electromagnetic, dynamics, and thermal aspects. First, the electromagnetic and dynamics characteristics are modeled to reveal the principle for optimization. Then, optimization and analysis on magnetic structure, resonant system, and thermal features are conducted, which provide the foundation for prototype development. Finally, experimental results are provided for validation. As a whole, this process offers complete guidance for high power density linear oscillating motors in linear pump applications. [ABSTRACT FROM AUTHOR]

Highlights: [•] This paper proposes a new method to optimize a Switched Reluctance Motor (SRM). [•] A combination of SOA and GA with Finite Element Method (FEM) analysis is employed to solve the SRM design optimization. [•] The results show that optimized SRM obtains higher average torque and higher efficiency. [Copyright &y& Elsevier]