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Brushless DC motor torque ripple reduction has been the main issue in servo driving systems in which the speeds of fluctuation, vibration, and acoustic noise should be minimized. Most methods for suppressing torque ripples usually require Fourier series, analysis, finite element analysis or least-mean-square minimization. These methods might lead to errors during complex Fourier series analysis and cost much calculation time. This paper presents a new method to improve torque ripple based on the Genetic Algorithm. The proposed method depends on Genetic Algorithms to search for the Fourier coefficients of three-phase stator currents for the given back-EMF waveforms. These Fourier coefficients can then be used to recompose three-phase optimum current commands for three-phase balanced brushless DC motor driving. The torque ripple must therefore be expected to improve in this way if stator currents are perfectly achieved. The validity and practical applications of the proposed method are verified from experiments using the TMS320F2812 DSP. In the experimental structure, the three-phase optimum current commands and the measured three-phase backEMFs are set up as the tables. They are obtained according to the rotor angle and speed information from the encoder. The experimental results can prove that the proposed method provides a simple and efficient way to obtain three-phase optimum stator currents for the given back-EMF waveforms and the minimum torque ripple will also be acquired.

Torque Ripple Reduction of Brushless DC Motor Using Genetic Algorithm