Knock Threshold Detection in Turbocharged Gasoline Engine Using EEMD and Bispectrum

Knock threshold detection is the key of closed loop control of ignition in gasoline engine, and it is also the difficult point in knock measurement. In this paper, an investigation of knock detection in turbocharged gasoline engine using bispectrum slice and ensemble empirical mode decomposition (EEMD) based on the engine cylinder head vibration signals is presented. By adding some finite amplitude Gaussian white noises to the signal, EEMD keeps the signal continuous in different time span, and therefore the mode mixing inhering in the classical empirical mode decomposition (EMD) method is alleviated. Power spectrum density (PSD) estimation is used to determine the band range of the resonance frequency generated by knock component. EEMD is used to decompose the original signals, the time-frequency characteristics of the Intrinsic Mode Functions (IMF) are analyzed using Continues Wavelet Transform (CWT) due to its excellent time-frequency resolution. Then bispectrum as a post processing method is adopted to process IMF which contains knock feature information. The diagonal slice of bispectrum is computed to extract the non-linear feature deriving from the quadratic phase coupling, as well as the knock characteristic frequencies. This method is endowed with characteristics of avoiding model mixing, suppressing Gaussian white noise, detecting the nonlinear coupling feature. And knock characteristic information, especially for light knock detonation can be successfully extracted. Derived from the above method, a novel knock intensity factor has been developed and the relevance of the proposed criterion for characterizing different levels of knock has been investigated.