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This paper proposes a monolayer Halbach array based permanent magnet spherical motor (PMSpM) using cubic permanent magnets (PM). The research aims to provide a fast computing model to calculate the magnetic field for this PMSpM, which helps for future PMSpM optimization and control study. Three thickness equivalence principles are provided and compared for cubic PMs. The magnetic scalar potential is introduced, and the spherical harmonics expansion is implemented for rotor magnetic field analysis. Engineering revision is used to reduce the Legendre function deviation in polar angle direction. Torques and forces are deduced using the Lorentz force law, and relatively simple models of this PMSpM for both magnetic fields and torques are acquired. In addition, a prototype motor has been developed, and the analytic results of air-gap flux density and torque are compared with their finite element simulation and experimental results, which are proved consistent. It is concluded that the fundamental component of the spherical harmonics can be used to present the magnetic field model, which uses fewer integrals than the Biot-Savart law based solution, and the modeling results of the magnetic field flux density, forces and torques are in line with the expectations. The analytic models are proved correct. [ABSTRACT FROM AUTHOR]

For the optimal speed–torque control of asynchronous motors for the electric cars in the field-weakening region, a random forest regression (RFR) algorithm is introduced in this article, to solve the problem of stator d-axis (isd) and the q-axis current (isq) matching. First, a vector control system for the asynchronous motors is built on the basis of the current distribution output model. Second, according to the limiting conditions of maximum voltage (Usmax) and current (Ismax), an analytical model of the maximum torque output is established, and the current distribution law is analyzed. Third, based on the variation laws of isd and isq, a closed-loop voltage vector analytical model is designed and embedded in the vector control system to analyze the simulation results. Fourth, an AVL dynamometer experimental platform is built to collect the measured sample data under a constant temperature of 85 °C and maximum power output. The working condition parameters serve as the input of the RFR model, whereas isd and isq are the outputs. The validity of the current distribution is verified. Finally, the regression model is embedded in the vector control system to determine isd and isq under different working conditions. Results verify the correctness and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the modeling methods for the structural design optimization of permanent magnet synchronous linear motors (PMSLMs), which are applied to linear motion machines. First, an initial PMSLM model is established by finite element analysis (FEA), and the data space is obtained for subsequent rapid regression modeling. Second, a powerful regression machine learning method, that is, distance-weighted K-nearest neighbor algorithm (DW-KNNA), is introduced to establish a calculation model by grasping the nonlinear relationships between input structural parameters and output motor performances. Model comparison experiments among analytical method, response surface method, K-nearest neighbor algorithm, and DW-KNNA demonstrate the superiority of the DW-KNNA. Finally, the differential evolution algorithm is used to determine the best combination of structural parameters and performances. The FEA and prototype motor experiments proved the validity and advantages of the proposed method. [ABSTRACT FROM AUTHOR]