Electric vehicles have been promoted worldwide because of their high energy efficiency and low pollution. However, frequent charging safety accidents have to a certain extent restricted the development of electric vehicles. Therefore, it is extremely important to accurately evaluate the safety state of EV charging. The paper presents an integrated safety assessment method for electric vehicle charging safety based on fuzzy neural network. The integrated fault model was established by analyzing the correlation between truck–pile–grid. Then the integrated evaluation index was analyzed and sorted out, and the comprehensive fuzzy evaluation method used to evaluate. Following this, the improved GA_BP neural network algorithm was used to calculate the weight. Compared with the evaluation effect before and after the improvement, the simulation results show that the GA_BP neural network has higher accuracy and smaller error than the ordinary BP neural network. Finally, the feasibility and effectiveness of the evaluation method was verified by a case study.

In active magnetic bearing (AMB), the beat vibration will affect the flywheel rotary precision. A vibration model, which includes general dynamic stiffness and unbalance response different from the existing vibration research, is proposed to analyze the vibration characteristics, and the vibration model can express the actual system vibration features from the mechanism. In order to solve the vibration model, it is considered as a multi-degree-of-freedom vibration system. Both the free vibration and the forced vibration are analyzed according to the proposed model’s solution, and therefore the beating vibration is discovered when the two vibration frequencies are similar. The weakening measures of the unbalance vibration and the beat vibration are also discussed by analyzing the general dynamic stiffness changing. The simulation and experimental results demonstrate the validity of the theoretical analysis. The vibration analysis results can provide effective mechanism support for active magnetic bearings vibration characteristics research, and the vibration model can provide simulation platform for others applied Research.

According to the mobile storage characteristic of electric vehicles, an emergency power supply model about the electric vehicles is presented through analyzing its storage characteristic. The model can ensure important consumer loss minimization during power failure or emergency and can make electric vehicles cost minimization about running, scheduling, and vindicating. In view of the random dispersion feature in one area, an emergency power supply scheme using the electric vehicles is designed based on the K‐means algorithm. The purpose is to improve the electric vehicles initiative gathering ability and reduce the electric vehicles gathering time. The study can reduce the number of other emergency power supply equipment and improve the urban electricity reliability.

A bearingless switched reluctance motor (BSRM) has the combined characteristics of a switched reluctance motor (SRM) and a magnetic bearing. The hybrid-rotor BSRM (HBSRM) discussed in the paper has a twelve-pole stator and an eight-pole hybrid rotor, which is composed of a cylindrical rotor and a salient-pole rotor. Although the asymmetry of the hybrid rotor makes the structure and magnetic field of the HBSRM more complex, it can always produce a significant amount of magnetic pulling force to levitate a rotor shaft at all the rotor angular positions of each phase, which is not available in a traditional BSRM. The classical mathematical model for a conventional BSRM is valid only when its rotor rotates from the start of the overlap position to the aligned position, and the radial force and torque derived from this model are discontinuous at the aligned positon, which is harmful to the motor’s stable operation. In this paper, a full-period mathematical model on the assumption that the gap permeance is cut apart by straight lines or improved elliptical lines for a 12/8-pole HBSRM is provided. On the basis of this mathematical model, the continuity of the radial force and torque at all the rotor angular positions can be guaranteed, and the fine characteristics of this mathematical model have been verified by simulations.

In order to play the important role of electric vehicles to promote the realization of the 3060 double carbon target, electric vehicles have seen explosive growth. However, due to the tight symmetry between the number and distribution of electric vehicles and their corresponding charging facilities, the layout of charging facilities has higher requirements. This paper collects travel data in the form of a traffic travel questionnaire for electric vehicle users. Based on the vehicle parking demand model of the queuing theory and Monte Carlo simulation, the paper gives the number of stopping vehicles and the time of vehicles stopping in different places such as residential areas, workplaces, supermarket parking and roadside. In addition, based on the Bass prediction model, the main parameters are modeled in the model, and the price correction coefficient is introduced. The improved Bass model is used to predict the growth trend of electric vehicles in different regions in different years and in different incentive sites. By predicting the ownership of urban electric vehicles and accurately grasping the distribution and operation of electric vehicles, this paper can provide guidance and suggestions for the planning and construction of charging facilities in different regions, effectively reduce the investment cost of charging facilities and guide local governments to formulate reasonable planning schemes.