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Title
Japanese: 
English:Knocking Detection in Gasoline Engines Based on Probability Density Functions: A Mixed Gaussian Distribution Approach 
Author
Japanese: 伊吹 竜也, 粟井 康裕, 坂柳 佳宏, 三平 満司, 加古 純一.  
English: Tatsuya Ibuki, Yasuhiro Awai, Yoshihiro Sakayanagi, Mitsuji Sampei, Junichi Kako.  
Language English 
Journal/Book name
Japanese: 
English:Proceedings of 54th IEEE Conference on Decision and Control 
Volume, Number, Page         pp. 191-196
Published date Dec. 15, 2015 
Publisher
Japanese: 
English:IEEE 
Conference name
Japanese: 
English:54th IEEE Conference on Decision and Control 
Conference site
Japanese: 
English:Osaka 
DOI https://doi.org/10.1109/CDC.2015.7402107
Abstract This paper proposes an engine knocking detection approach based on probability density functions (PDFs). In this work, we suppose that the PDF of knocking intensity distribution can be approximated by a mixture of two Gaussian functions due to normal combustion and abnormal one. We first apply EM (Expectation-Maximization) algorithm to actual engine data to show that the knocking intensity probability distribution can be successfully estimated by the mixed Gaussian distribution. We next try to apply the existing online EM algorithm in view of the actual implementation by an engine control unit. However, since the existing algorithm is built for the estimation of a fixed PDF, the effect of new input data is gradually attenuated and vanishes after long time. We thus newly propose a modified online EM algorithm so that the effect of the new input data is not attenuated. Finally, we perform simulations and an actual engine bench test for the validity of the present approach.

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