The large current ripple caused by the limited switching frequency significantly degrades the control performance of the high-speed permanent magnet motor drive system. To mitigate the current ripple, the switching frequency of the inverter should be high enough. The purpose of this paper is to reduce the current ripple of the HSPMSM drive system. Firstly, a Silicon-Carbide/Silicon(SiC/Si) hybrid inverter is designed. The designed hybrid inverter consists of two SiC-MOSFETs and six Si-IGBTs, and the circuit modals of the SiC/Si hybrid inverter is analyzed. Secondly, based on the SiC/Si hybrid inverter, three improved space-vector-modulation(SVM) strategies are proposed. The core principle of the proposed SVM strategies is that most of the switching actions are transferred from the Si-IGBTs to the SiC-MOSFETs. Benefit from the low switching loss of the SiC device, the total power loss can be significantly reduced. Besides, the SiC-MOSFETs can create the zero-voltage-switch(ZVS) condition for the Si-IGBTs, and then the switching loss of the Si-IGBTs can be almost eliminated. Finally, to verify the effectiveness of the proposed methods, sufficient simulations and experiments are implemented.

Winding configurations which are applicable to a novel bearingless flux-switching permanent magnet motor with stacked structure are investigated, and one method to evaluate these winding configurations is also proposed in this paper. Firstly, the motor structure and the influence of coil connections on torque and radial force are illustrated, and the fundamental radial force expressions of two diametrically opposite coils are derived. Afterwards, two kinds of torque windings and four kinds of radial force windings for the motor are studied and the radial force models are derived accordingly. Following this, the radial force models are verified and the transient radial force and torque characteristics are investigated by finite element analysis. More importantly, an evaluation factor related to the winding copper losses is defined to evaluate the winding configurations. Finally, an optimal winding configuration is determined theoretically and a prototype motor is built to validate the effectiveness of the motor structure and the optimal winding configuration.

Loss characteristics and loss separation methods of ultrahigh-speed permanent magnet motors (UHSPMSM) are comprehensively studied in this article. In view of the influence of stator structure, material, winding type, control method, and fluid dynamics, the ac copper loss equivalent calculation model, fluid dynamic model, and finite element simulation model are established, respectively, to calculate and analyze the loss of each part of UHSPMSM. Moreover, a set of loss separation methods in dynamic is designed, which can separate stator core loss, dc copper loss, eddy copper loss, rotor eddy current loss, and mechanical friction loss of UHSPMSM one by one under the condition of considering the high-frequency electromagnetic field and fluid dynamic. A 550 000 r/min prototype and back-to-back loss separation setup is built to complete the experiment. Finally, loss distribution of the motor is obtained, which provides a certain reference for the loss research of an ultrahigh speed motor.

Given the urgent challenges posed by global climate change and the ongoing energy crisis, fuel cell electric vehicles (FCEVs) have emerged as a promising solution. Incorporating sophisticated energy management strategies (EMSs) into FCEVs can significantly enhance the efficiency of the complex powertrain under diverse driving conditions. In this paper, a dual-model predictive control energy management strategy based on long short-term memory (LSTM)-based driving condition recognition is proposed to enhance the economic performance of FCEVs and robustness across diverse driving conditions. Firstly, to improve the generalization capability and adaptability of the LSTM model and to enhance the accuracy of driving condition recognition, wavelet transform (WT) is introduced into both the offline training and online application of LSTM. Secondly, to enhance the real-time performance and control effectiveness of the EMS, model predictive control (MPC) and explicit model predictive control (eMPC) are established based on a unified optimization objective and constraints. Thirdly, a dual MPC switching logic is developed using the information of driving condition prediction, ensuring the coordination of dual MPCs in practical applications and enhancing their adaptability to various conditions. Finally, an evaluation of the simulations demonstrates that the proposed dual-model predictive control energy management strategy based on wavelet transform LSTM driving condition recognition (WTL-DMPC EMS) can improve economic performance. Compared with other baselines, the energy-saving capability is remarkable, showcasing its promising performance.

For the purpose to solve the problem of poor anti-disturbance performance and large voltage fluctuations of the high-speed permanent magnet synchronous generator (HSPMSG), this paper proposes a compound control method. The method combines the super-twisting (STW) voltage outer loop controller with the super-twisting disturbance observer (STWO). First, in order to overcome the problem of poor anti-disturbance performance under the conventional PI control method, a voltage outer loop controller based on the STW is designed. Second, a load disturbance observer based on the STW is developed for further improving the anti-load disturbance capability of HSPMSG. The estimated value of the disturbance observer is feedforward into the STW controller as a compensation term. Finally, both simulations and experiments are performed on a HSPMSG to verify the effectiveness of the proposed control strategy.