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A novel programmed hybrid spreading spectrum modulation method to mitigate electromagnetic interference (EMI) emission and bearing current in the context of miniaturised and lightweight synchronous machine drives is proposed. The proposed method adopts the combination of conventional pulsewidth modulation (PWM) and low common mode voltage PWM. The offline look‐up table for switching frequency is acquired by analysing the root mean square voltage values at different modulation indices and angles. By adjusting the switching frequency according to this table, the spectrum can be spread into the sidebands of the switching frequency, and the harmonic spike can be suppressed. To address the challenge of increased current ripple and harmonic distortion in high torque density motors under overload conditions, a motor model that considers the cross‐saturation and slotting effect is presented. This motor model is used to derive the switching frequency correction factors, aiming to mitigate the influence of saturation and slotting effect on harmonic amplification. The proposed method is well‐suited for controlling synchronous motors using three‐phase two‐level voltage source inverters. The simulation and experimental results validate the effectiveness of the proposed method, showcasing its advantages in terms of computational complexity reduction and significant attenuation of peak EMI currents. [ABSTRACT FROM AUTHOR]

In interior permanent magnet synchronous motor (IPMSM) position‐sensorless drives, the high‐frequency (HF) square‐wave voltage injection method is often used to estimate the rotor position and speed in low‐speed range by tracking the salient polarity of the motor. In order to reduce the torque ripple caused by HF signal injection, a strategy to update the magnitude of the injected signal online by back propagation neural network is proposed in this paper. With the proposed method, the neural network can update the magnitude of the injected signal online according to the d‐axis current and the position error information. It can not only ensure the accuracy of position extraction but also effectively reduce the current harmonics caused by the injected signal, and then the torque ripple can be reduced. In addition, the proposed method is easy to implement, resulting in low computation burden. Finally, the experiments are implemented on a 1‐kW IPMSM drive. The experimental results show that compared with the conventional fixed magnitude injection, the peak‐to‐peak value of the torque ripple is reduced by nearly half along with the decrease of the injected magnitude. [ABSTRACT FROM AUTHOR]

This study proposes an optimal control scheme for a permanent‐magnet linear synchronous generator (PMLSG) using the state feedback control (SFC) method plus the grey wolf optimisation (GWO) algorithm. First, A novel state‐space model of linear PMLSG is established in order to obtain desired dynamics and enough power when used for the smooth wave energy. Second, the GWO algorithm is adopted to acquire weighting matrices Q and R in the process of optimising linear quadratic regulator (LQR). What is more, a penalty term is brought into the fitness index to reduce the overstrike of output voltage and keep the rate of work more stable. Finally, optimal LQR‐based SFC with and without penalty term and proportional‐integral (PI) controllers are compared both in simulations and in experiments. Results clearly prove that the proposed optimal control strategy performs a better response when compared to other strategies. [ABSTRACT FROM AUTHOR]