The electromagnetic vibration level of the powertrain seriously affects the NVH performance of electric vehicles. Due to the non-ideal structure of the drive motor and the non-linear characteristics of the inverter，the output torque of the motor fluctuates greatly. At a certain speed，the frequency of the torque harmonics will be consistent with the torsional modal frequency of the powertrain，resulting in resonance of the powertrain. In order to study the problem of electromagnetic vibration caused by torque ripple，an 8-pole 48-slot permanent magnet synchronous motor is analyzed by electromagnetic simulation. Taking the influence of speed and magnetic saturation on the parameters of the motor during operation into account，the electromagnetic model and control circuit of the motor are established to analyze the electromagnetic excitation. Additionally，a vibration test is conducted and it is considered that the 48-order vibration in the speed range of 500~1500 r/min is caused by torque ripple. In order to suppress the output torque ripple，the harmonic current injection method is adopted to offset the harmonic torque，and the RBF neural network and genetic algorithm are combined to optimize the current harmonics. The accuracy of the analysis is verified by vibration tests. The results show that the method of minimizing torque ripple by harmonic injection can effectively suppress the electromagnetic vibration of the powertrain.