Papers by Author: En Wei Chen

Abstract: To control the pure electric vehicle motors vibration and noise, the dynamic characteristics of the motor are analyzed. Dynamic characteristic include the natural frequency and response characteristics of different parts of the motors structural member. This paper uses three-dimensional software Pro/E modeling of the motor: By making appropriate assumptions and equivalent treatment of the motors stator, rotor core and coil winding, establish the finite element simulation model of the various components .Using the finite element analysis software Workbench analyzes the windings and motor model modal analysis, to get natural frequency of each mode. To make a modal analysis test, we can use hammering method done on the motor. By using real-time signal analyzer AWA6291 make spectral analysis of the motor online, comprehensive comparative analysis of the results and used to guide motor design.

Abstract: MR damper (magnetorheological damper) has broad application prospects, and equivalent damping coefficient is very important of its dynamic characteristic analysis. Based on the modified Bouc_Wen model, the performance of MR damper was analyzed and the equivalent linear damping coefficient of MR damper was calculated. Based on simulation date of the modified Bouc_Wen model, the relationships between the equivalent linear damping coefficient of MR damper and the parameters of control voltage and MR dampers movement amplitude were established by the curve fitting regression analysis method. Verification results prove that the equivalent linear damping coefficient model has higher accuracy. For the vibration systems using strongly nonlinear MR damper, new model can effectively improve the efficiency of calculating the vibration analysis and the stability of the system in a certain frequency. At the same time, the model provides a theoretical basis for the application of MR damper control.

Abstract: Time-varying parameters identification in linear system is considered, which can be changed into time-invariant coefficient polynomials after Taylor expansion. Using response data to establish the time-varying autoregressive moving average (TV-ARMA) model, then utilizing least-square algorithm to obtain time-invariant coefficients of time-varying parameters. According to error analysis, to reduce errors and improve accuracy, the estimation time is divided into small internals and the above method is used in each interval. Simulation shows that, under certain error condition, the time-varying parameters obtained by the method have good agreement with the theoretical values; the measures taken have strong anti-interference and high efficiency.

Abstract: A new technique is present in this paper that transforms the railway track irregularity power spectral density of left and right rails into the excitation power spectral density of wheelset of train, compared with the railway track irregularity spectrums of left and right rails which are not the direct inputs of simulation dynamic model of trail. A parameter model is chosen as the model of excitation spectrum and parameters fitting result shows that this model is suitable for the excitation spectrums of traversing, floating and head shaking, and the method present in this paper is effective.