To improve the electromagnetic performance of the machine for flywheel energy storage system (FESS), in this paper, a five-phase bearingless flux-switching permanent magnet (BFSPM) machine with E-core stator is presented. The topology and struc-ture are introduced and the operation principle of the generation of torque and suspension force is also explained. Based on the simple variable method and overall trial and error method, the influence of the machine parameters on machine performance is investigated by using finite element analysis (FEA). And then the parameters are optimized. The results show the improvement of the torque and suspension force with increased amplitude and smaller fluctuation.

Electrically excited synchronous motor (EESM) has the characteristics of high order, nonlinear and strong coupling, so it is difficult to be controlled. However, it has the advantages of adjustable power factor, high efficiency, and high precision torque control, so it is widely used in high-power applications. The accuracy of a flux observer influences the speed control system of EESM. Based on state observer in modern control theory and electrical excitation synchronous machine state equation, a reduced-order flux observer is designed. Using the first-order difference method and forward bilinear transformation method, the reduced-order flux observer is discrete, and the stability of the motor system is analyzed. The analysis shows that the stability of the system using the bilinear transformation method is better than that using the first order forward difference method. In motor operation, motor parameters will be affected by the factors of temperature, magnetic saturation, and motor frequency. In this paper, the influence of parameter variation on the motor system is studied by using the variation of the pole distribution. Finally, the speed regulation system using the reduced-order observer is simulated, which verifies the accuracy of the reduced-order flux observer observation.

This article proposes a novel physics-informed neural network (PINN) controller for five-phase permanent magnet synchronous motors (PMSMs) that addresses the limitations of existing dual-plane current control methods. The notable constraints of existing machine learning controllers for PMSMs, particularly with respect to interpretability and stability, are examined to enable offline interpretability and online deployability. A neural network (NN) control model is derived for dual-plane operation of five-phase PMSMs by extending the NN control frameworks of three-phase PMSMs. The motor’s prior physical information is deeply integrated into the training process to enhance generalization. A hybrid optimization strategy is proposed to improve the fit between the predicted and actual operating voltages and to suppress prediction fluctuations, thereby better aligning the predicted values with the exact operational requirements. Experimental results validate the excellent steady-state performance and robust antiinterference performance of the proposed controller.

Electrically excited synchronous motor (EESM) is widely used in many large equipment drives because of its strong overload capacity, high efficiency, and adjustable power factor. The research and development of a high-performance EESM control system can realize the high combination of energy-saving speed regulation and green environmental protection and has a high social effect and economic value. In this paper, the signal injection method is used to obtain the initial rotor position information of EESM. Sliding Fourier transform is used to improve the initial position angle detection method based on the rotor signal injection method, and the improved method is compared with the traditional voltage integration method. Rotor high-frequency signal injection method was used to detect the rotor position information of the motor during operation, and the influence of the damping winding on the rotor signal injection method was analyzed. On the premise that the damping winding had no influence on the method, a method of obtaining the rotor position information of EESM without a speed sensor was designed. Finally, the speed sensorless regulation system using the initial rotor position detection method is simulated, which verifies the accuracy of the proposed speed sensorless control scheme.

Considering that the excitation method of an electric excitation synchronous motor has the disadvantages of the brush and slip ring, this article proposes a new brushless excitation system, which includes two parts: a wireless charging system and a motor. To meet the requirements of maximum transmission efficiency and constant voltage output of the system, a bilateral cooperation control strategy is proposed. For the strategy, the buck converter in the receiving side of the system can maintain maximum transmission efficiency through impedance matching, while the inverter in the transmitting side can keep the output voltage constant through phase shift modulation. In the control process, considering that the offset of coupling coils will affect the control results, a grey wolf optimization–particle swarm optimization algorithm is proposed to identify mutual inductance. Simulation and experimental results show that this identification algorithm can improve the identification accuracy and maximize the avoidance of falling into local optima. The final experimental result shows that the bilateral cooperation control strategy can maintain the output voltage around 48 V and the transmission efficiency around 84.5%, which meets the expected requirements.

In recent years, electric vehicles have developed rapidly. However, many electric cars are equipped with permanent magnet synchronous motors. Permanent magnet synchronous motors have several disadvantages: For example, permanent magnets tend to demagnetize at high temperatures. Electrically excited synchronous motors have several excellent properties. First, they are cheaper because the stator and rotor of the motor only need to be wound, which is more affordable than permanent magnets for speed regulation. When the armature current reaches the maximum value, the excitation current can also be adjusted for speed regulation, which makes the speed regulation more flexible. In the case of a short circuit, the corresponding direct-axis current is smaller than the quadrature-axis current, so the fault tolerance is better. Since the traditional electric excitation motor has brushes and slips rings, sparks will be generated during commutation. Therefore, a new excitation method is adopted to make non-contact motor excitation, and the motor operation is safer and more environmentally friendly. At the same time, to ensure that the output power of the non-contact electric excitation motor remains stable, a step-down circuit and power-type fast discrete terminal sliding mode control are added after the full-bridge rectifier circuit to make the excitation current and voltage output of the motor more stable. That is, the output power reaches a steady production. In this paper, an improved sliding mode control algorithm is used to stabilize the output voltage of the non-contact excitation motor, which can still ensure the stable output of the voltage when the equivalent load changes. It is confirmed that the non-contact excitation motor can be applied to various complex situations, and the proposed algorithm is simulated and experimentally verified to verify the accuracy of the proposed algorithm.