LAST ADDED

In order to effectively improve the reliability level of the permanent magnet synchronous motor (PMSM) drive system of electric aircraft, a component importance analysis based on the GO method for the repairable systems is proposed. Firstly, the system reliability model GO diagram is established according to the hardware schematic diagram of the PMSM drive system. Secondly, the steady-state availability and failure importance of the components are calculated. In addition, the criteria importance through intercriteria correlation (CRITIC) is adopted to determine the objective weights of steady-state availability and failure importance. The combined weighting is employed to obtain the importance of key components. Meanwhile, a system redundancy design based on the importance of components is proposed to provide data support for the design of the system. Finally, the feasibility and effectiveness of the proposed method are evaluated by an example of an electric aircraft PMSM drive system. This method provides a supporting basis for the optimization design of the entire system.

The paper presents the possibility of neural network application in order to identify the most advantageous design variants of column energy absorbers in terms of the achieved energy absorption indicators. Design variants of the column energy absorber made of standard thin-walled square aluminium profile with triggers in the form of four identical cylindrical embossments on the lateral edges were considered. These variants differ in the diameter of the trigger, its depth and position. The geometrical parameters of the trigger are crucial for the energy absorption performance of the energy absorber. The following indicators are studied: PCF (Peak Crushing Force), MCF (Mean Crushing Force), CLE (Crash Load Efficiency), SE (Stroke Efficiency) and TE (Total Efficiency). On the basis of numerical studies validated by experimentation, a neural network has been created with the aim of predicting the above-mentioned indices with an acceptable error for an energy absorber with the trigger of specified geometrical parameters and position. The paper demonstrates that the use of an effective multilayer perceptron can successfully speed up the design process, saving time on multivariate time-consuming analyses.