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2019 | OriginalPaper | Buchkapitel

Strategy Research on Key Technologies of Misfire Detection on Gasoline Engine

verfasst von : Long Qin, Chunjiao Zhang, Yongyi Huang, Feng Xu, Xue Lei, Liuchun Yang, Kai Wang, Junpeng Wang, Fengmin Tian, Fanwu Zhang

Erschienen in: Proceedings of the 19th Asia Pacific Automotive Engineering Conference & SAE-China Congress 2017: Selected Papers

Verlag: Springer Singapore

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Abstract

Misfire seriously impacts on performance, emissions, engine life, etc. When the engine is running at different conditions, causing an unstable behavior of combustion, it will bring challenges to the accuracy and robustness of misfire detection. In this paper, an analysis of misfire detection algorithms based on instantaneous power and instantaneous torque is presented. The instantaneous crankshaft (engine speed) signal has been recorded. The optimal angular position and the selected final algorithm to detect misfire, within the engine cycle, for the combustion time evaluation, and its variation with the engine operating condition have been put forward. Some related factors affecting misfire algorithm detection are finally compensated. During the engine running, roughness threshold self-adapting is realized to improve the detection accuracy. Finally, the misfire detection algorithm is proved in the car, and the test result shows that misfire event and its corresponding misfire cylinder can be precisely detected.

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Metadaten
Titel
Strategy Research on Key Technologies of Misfire Detection on Gasoline Engine
verfasst von
Long Qin
Chunjiao Zhang
Yongyi Huang
Feng Xu
Xue Lei
Liuchun Yang
Kai Wang
Junpeng Wang
Fengmin Tian
Fanwu Zhang
Copyright-Jahr
2019
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-8506-2_35

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