Automatic calibration algorithm of 0-D combustion model applied to DICI diesel engine. (5th February 2018)

• Record Type: Journal Article
• Authors: Hu, Song; Wang, Hechun; Niu, Xiaoxiao; Li, Xu; Wang, Yinyan
• Is Part Of: Applied thermal engineering. Volume 130(2018)
• Page Start: 331
• Page End: 342
• Publication Date: 2018-02-05
• Subjects: Diesel engine -- Combustion model -- Wiebe function -- DICI -- Burnt fraction; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.11.013
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: A identification algorithm of needed Wiebe function number was proposed. New confirmation method of combustion phase transition angle was proposed. Advantages of algebra method and Levenberg-Marquardt algorithm were combined. The automatic calibration algorithm is reliable, precise and less computing-time. The calibration algorithm is a promising tool to realize online diagnosing. Abstract: To automatically acquire high accuracy 0-D combustion model based on Wiebe function, in this work, an automatic calibration algorithm is developed to determine and then calibrate standard and double Wiebe function, which combines advantages of the algebra and Levenberg-Marquardt (LM) algorithm and avoids the two methods' disadvantages. Up to two combustion phases models have been analyzed. An innovative method is proposed to confirm the transition angle between premixed and diffusive combustion phases. The algebra method is used to provide the initial value of Wiebe parameters, then the LM algorithm is applied to obtain the further refined Wiebe parameters. The automatic calibration algorithm is applied to a turbocharging medium-speed diesel engine for a wide range of engine speeds and loads. The effectiveness of this algorithm is quantified by the accuracy for describing the burnt fraction ( x b ). The fitting results indicated that the algebra method is an effective measure to provide the initial values of Wiebe parameters. All the fitting results are convergent and the iterations of LM algorithm are all less than 8. The R 2 of x b are all at a high level (larger than 0.995), and RMSE are all at a low level (smaller than 0.015). The proposed automatic calibration algorithm presents high reliability and precision, moreover, its computation time is less than 70 ms. Therefore it is a promising algorithm to realize online fitting, diagnosing and controlling combustion process.