Abstract: When a car is running at high speeds, the signal-to-noise ratio from the wheel speed sensors is reduced, and the data calculated by the wheel speed signal are emanative, which is the problem for the safety and effective control of a car. The wheel speed sensor signals are transformed into the frequency domain using fast Fourier transform(FFT), and the characteristics of the waveforms of the true signal and noise are studied in the frequency domain. The frequency range of true signals is very narrow and its energy is very strong, but the noise spectral range is very width and its energy is very weak. According to this difference, a new method is given to process wheel speed signals using FFT and IFFT. Wheel speed sensor signals are transformed into frequency domain with inverse fast Fourier transform(FFT). In frequency domain the energy of signals keeps unchanged, and that of noise is reduced with the method of polynomial fitting. After so “filtering” processing, the curve of spectrum wave is transformed back into time domain with IFFT to obtain real signals. The S/N of signals is significantly improved with this FFT/IFFT processing. In tire pressure monitoring system(TPMS)test in road, the effects of three filtering methods are compared which are electronic current filter, Karman filter and FFT/IFFT filter. The test indicates that the method of FFT/IFFT filter can get rid of noise efficiently, and its effect is best.

Key words: wheel speed signal;fast Fourier transform(FFT);frequency domain filtering;signal-to-noise ratio