Vehicle Throttle Position Signal Denoising Based on Wavelet Transform
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摘要: 传统的汽车节气门位置信号(throttle position sensor,TPS)处理方法不易消除发动机舱内电磁信号及周边环境的干扰。根据TPS的特征,在MATLAB中选用Daubechies五阶正交小波(dB5)对TPS噪声信号进行4层小波分解,再对分解后得到的各层系数用软阈值法量化处理,最后利用小波重构,实现对信号去噪。最后将获得的去噪信号用于发动机控制,并将控制结果与采用未去噪信号的发动机进行实车对比试验。试验表明:发动机采用去噪的TPS信号运行更平稳,小波变换后的去噪TPS信号对发动机控制具有良好的效果。Abstract: In engine compartment, it is difficult to eliminate the effect of interfering signals on vehicle throttle position sensor (TPS) by the traditional signal processing method.In this article, according to the characteristic ofTPS, the wavelet theory was applied to decompose the noise signal for 4 levels by selecting Daubechies (dB5)wavelet in MATLAB.After decomposing, the soft-threshold de-noising method was employed to eliminate noise，then the inverse wavelet transform was used to reconstruct signals for signal de-noising and rebuilding.Finally, thede-noised signal was compared with the un-denoised signal by real vehicle tests.The tests show that the engine runmore stable when using the de-noised TPS signal and the de-noised TPS signal after wavelet transforming can improve the engine control more effectively.
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Key words:
- vehicle /
- throttle position sensor /
- wavelet transforms /
- threshold de-noising
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