Calibration of 0-D combustion model applied to dual-fuel engine. (15th December 2022)
- Record Type:
- Journal Article
- Title:
- Calibration of 0-D combustion model applied to dual-fuel engine. (15th December 2022)
- Main Title:
- Calibration of 0-D combustion model applied to dual-fuel engine
- Authors:
- Hu, Deng
Wang, Hechun
Wang, Binbin
Shi, Mingwei
Duan, Baoyin
Wang, Yinyan
Yang, Chuanlei - Abstract:
- Abstract: To acquire a highly accurate 0-D combustion model of the Wiebe function, a genetic algorithm (GA) based on algebraic analysis is developed. By analyzing the in-cylinder combustion process of biodiesel and diesel, a new method is proposed for determining the number of Wiebe functions and the transition angle between premixed and diffusive combustion in dual-fuel engine. First, for different operating conditions, the number of required Wiebe functions and the initial value of Wiebe parameters are determined by algebraic analysis method. Then, genetic algorithm is applied to obtain the further optimized Wiebe parameters and finally compared with Levenberg-Marquardt (LM) algorithm on fitting precision. The algorithm is applied to a dual-fuel engine under the conditions of propeller performance. The results show that, based on the initial value of Wiebe parameters, the fitting process of both LM algorithm and genetic algorithm converges rapidly, the R 2 of x b are all at a high level (larger than 0.997), but the RMSE values of genetic algorithm are all in a low range (smaller than 0.013). The fitting effect of genetic algorithm is obviously better than that of LM algorithm. Therefore, genetic algorithm based on algebraic analysis is an incredibly precise algorithm for structuring a 0-D combustion model. Highlights: An identification algorithm was proposed to determine required Wiebe function number. A geometric algorithm was proposed to calculate combustion phaseAbstract: To acquire a highly accurate 0-D combustion model of the Wiebe function, a genetic algorithm (GA) based on algebraic analysis is developed. By analyzing the in-cylinder combustion process of biodiesel and diesel, a new method is proposed for determining the number of Wiebe functions and the transition angle between premixed and diffusive combustion in dual-fuel engine. First, for different operating conditions, the number of required Wiebe functions and the initial value of Wiebe parameters are determined by algebraic analysis method. Then, genetic algorithm is applied to obtain the further optimized Wiebe parameters and finally compared with Levenberg-Marquardt (LM) algorithm on fitting precision. The algorithm is applied to a dual-fuel engine under the conditions of propeller performance. The results show that, based on the initial value of Wiebe parameters, the fitting process of both LM algorithm and genetic algorithm converges rapidly, the R 2 of x b are all at a high level (larger than 0.997), but the RMSE values of genetic algorithm are all in a low range (smaller than 0.013). The fitting effect of genetic algorithm is obviously better than that of LM algorithm. Therefore, genetic algorithm based on algebraic analysis is an incredibly precise algorithm for structuring a 0-D combustion model. Highlights: An identification algorithm was proposed to determine required Wiebe function number. A geometric algorithm was proposed to calculate combustion phase transition angle. A new method for determining the combustion phase transition angle was proposed. The advantages of algebraic analysis and genetic algorithms were combined. Algebraic analysis-genetic algorithm is reliable and accurate. … (more)
- Is Part Of:
- Energy. Volume 261:Part B(2022)
- Journal:
- Energy
- Issue:
- Volume 261:Part B(2022)
- Issue Display:
- Volume 261, Issue b (2022)
- Year:
- 2022
- Volume:
- 261
- Issue:
- b
- Issue Sort Value:
- 2022-0261-NaN-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-12-15
- Subjects:
- Diesel engine -- Wiebe function -- Biodiesel -- Genetic algorithm
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2022.125251 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24199.xml