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Mutual information of cylinder pressure and combustion phase estimation in spark ignition engines

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Abstract

For the study of internal combustion engines, combustion control is an important method to achieve high efficiency and low emissions. Currently, in-cylinder pressure sensor-based closed-loop control strategies have become the preferred solution. However, their productional application in automotive industries is limited due to the cost of intensive pressure acquisition for a whole cycle and the calculation load of combustion phase indicators. This paper proposes a method of combustion phase estimation for spark ignition (SI) engines. In this method, the combustion phase is estimated only based on pressure measurements at several crank angles. Information entropy and mutual information are introduced to analyze the feasibility and accuracy of the combustion phase estimation, which shows that the pressure measurements at selected points contain most of the information for the estimation. As a result, only pressure measurements at 3 points and ELM estimation models are required to obtain the combustion phase, instead of intensive data acquisition and calculation.

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Acknowledgements

The authors would like to thank the Toyota Motor Corporation for its financial and technical support of this research.

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Authors and Affiliations

  1. Department of Engineering and Applied Sciences, Sophia University, Tokyo, 102-8554, Japan

    Huanyu Di & Tielong Shen

Authors
  1. Huanyu Di
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  2. Tielong Shen
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Correspondence to Huanyu Di.

Additional information

This work was supported by the Toyota Motor Corporation.

Huanyu DI received his B.Eng. and M.Sc. degrees in Mechanical Engineering from the Department of Mechanical Engineering, Tsinghua University, Beijing, China, in 2013 and 2016, respectively. He is currently working toward the Ph.D. degree in Mechanical Engineering with the Department of Engineering and Applied Sciences, Sophia University, Tokyo, Japan. His current research interests include stochastic systems, chaos dynamics, machine learning, and control applications in the automotive engines and hybrid electric vehicles.

Tielong SHEN is a Full Professor in control engineering at Sophia University. He received his Ph.D. degree in Mechanical Engineering from Sophia University in 1992 and joined Sophia University as an Assistant Professor with Tenure in April 1992, where he is currently chairing the Shen Laboratory. His research interests include control theory and applications in automotive systems, power systems, and mechanical systems. In 2005, his laboratory founded a transient control engine test bench and began academicindustrial long-term collaborative research on advanced engine control technology with the Toyota Motor Corporation. Recently, his publication “Transient Control of Gasoline Engines” (CRC Press, 2015) has focused much attention in the research field of automotive control. Dr. Shen has authored/coauthored eleven text books in Japanese, English and Chinese and has published more than 150 research papers in major peer-reviewed journals.

He is currently a member of the IEEE Technical Committee on Automotive Control and the IFAC Technical Committee on Automotive System Control. He has served as general chair of CCC-SICE 2015 and IPC chair for the IFAC Symposium on Advances in Automotive Control and is serving IPC vice-chair of the 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling (E-CoSM 2018), Changchun, 2018, and as the general chair of the 6th IFAC E-CoSM, Tokyo.

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Di, H., Shen, T. Mutual information of cylinder pressure and combustion phase estimation in spark ignition engines. Control Theory Technol. 18, 34–42 (2020). https://doi.org/10.1007/s11768-020-9047-z

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  • DOI: https://doi.org/10.1007/s11768-020-9047-z

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