Modeling of 0-D heat release rate of heavy-duty diesel engine based on classification algorithm

Abstract

With the shortage of fossil fuel and the strengthening of emission regulations, the control strategy using in-cylinder pressure signals has caused extensive concern. Modeling the combustion heat release rate is an indispensable work along with the in development of the diesel combustion control hardware-in-loop system. Based on the analysis of experimental data, four combustion modes are proposed in this paper. The Wiebe-based functions developed for each combustion mode are given. According to experimental launch data, the combustion mode is classified automatically using the multi-classification support vector machine algorithm. The LM-Chaos algorithm based on function parameter identification is proposed. The results show that HRR shape is mainly related to the rate of premixed combustion and diffusion combustion under different operating conditions, and the variation of HRR directly affects the structure of Wiebe-based function. Different combustion modes can be simulated by selecting the starting time of combustion, the duration of combustion phases and the co-existence time of combustion phases. This method can simulate the heat release curves of various working conditions and improve the fitting of heat release curves of long combustion time by adding error function.

Keywords

0-D model heavy-duty diesel engine combustion mode classification multi-Wiebe function LM-Chaos optimal algorithm

Get full access to this article

View all access options for this article.

References

Loganathan

Leenus Jesu Martin

Nagalingam

Prabhu

. Heat release rate and performance simulation of DME fuelled diesel engine using oxygenate correction factor and load correction factor in double Wiebe function. Energy 2018; 150: 77–91.

Bai

Tunestål

Tunér

. Combustion characteristics of gasoline DICI engine in the transition from HCCI to PPC: experiment and numerical analysis. Energy 2019; 185: 922–937.

Wang

Yang

Wang

. Burnt fraction sensitivity analysis and 0-D modelling of common rail diesel engine using Wiebe function. Appl Therm Eng 2017; 115: 170–177.

Abbaszadehmosayebi

Ganippa

. Characterising Wiebe equation for heat release analysis based on Combustion Burn Factor (CI). Fuel 2014; 119: 301–307.

Maroteaux

Saad

Aubertin

. Development and validation of double and single Wiebe function for multi-injection mode diesel engine combustion modelling for hardware-in-the-loop applications. Energy Convers Manag 2015; 105(10): 630–641.

Maroteaux

Saad

. Diesel engine combustion modeling for hardware in the loop applications: effects of ignition delay time model. Energy 2013; 57: 641–652.

Yasar

Soyhan

Walmsley

Head

Sorusbay

. Double-Wiebe function: an approach for single-zone HCCI engine modeling. Appl Therm Eng 2008; 28(11–12): 1284–1290.

Galindo

Climent

Plá

Jiménez

. Correlations for Wiebe function parameters for combustion simulation in two-stroke small engines. Appl Therm Eng 2011; 31(6–7): 1190–1199.

Csallner

Gernard

Woschni

. Calculation of off design combustion process of gasoline engine[J]. Small Inter Combust Engine and Vehicle Technique 1987; 1987(2): 42–51.

10.

Yıldız

Albayrak Çeper

. Zero-dimensional single zone engine modeling of an SI engine fuelled with methane and methane-hydrogen blend using single and double Wiebe function: a comparative study. Int J Hydrogen Energy 2017; 42(40): 25756–25765.

11.

Sun

Song

Yang

Wang

. Calculation method of Weber parameters in SACI combustion process. J Huazhong Univ Sci Technol 2017; 45(06): 91–96.

12.

Zhu

Zhang

, et al. Zero dimensional predictive combustion model and modeling method based on neural network. J Inter Combust Engines 2015; 33(02): 163–170.

13.

Ghojel

. Review of the development and applications of the Wiebe function: A tribute to the contribution of Ivan Wiebe to engine research. Int J Engine Res 2010; 11(4): 297–312.

14.

Song

Wang

H-C

Wang

Y-Y

, et al. Control-oriented modeling approach for multiple injection diesel engine simulation model. J Intern Combust Engines 2020; 38(05): 392–400.

15.

Yeliana

Cooney

Worm

Michalek

Naber

. Estimation of double-Wiebe function parameters using least square method for burn durations of ethanol-gasoline blends in spark ignition engine over variable compression ratios and EGR levels. Appl Therm Eng 2011; 31(14–15): 2213–2220.

16.

Hellström

Stefanopoulou

Jiang

. A linear least-squares algorithm for double-Wiebe functions applied to spark-assisted compression ignition. J Eng Gas Turbine Power 2014; 136(9): 091514.

17.

Liu

Dumitrescu

. Single and double Wiebe function combustion model for a heavy-duty diesel engine retrofitted to natural-gas spark-ignition. Appl Energy 2019; 248: 95–103.

18.

Wang

Niu

Wang

. Automatic calibration algorithm of 0-D combustion model applied to DICI diesel engine. Appl Therm Eng 2018; 130(130): 331–342.

19.

Nagaosa

Miyagi

Yamazaki

Iwase

. Combustion process estimation in cylinders based on an integrated engine model of the Wiebe function and a piston-crank mechanism. In: 2015 54th Annual conference of the Society of Instrument and Control Engineers of Japan (SICE), 28–30 July 2015, pp.393–399. New York, NY: IEEE.

20.

Huang

Hao

. Prediction of dynamic indicated torque of turbocharged diesel engine based on combustion model. J Intern Combust Engines 2016; 34(04): 357–364.

21.

Yin

Turesson

Johansson

Tunestål

. Nonlinear estimation of variables for heat release calculation using a gradient method. J Dyn Syst Meas Control 2019; 141(6): 061011.

22.

Sun

Wang

Yang

Wang

. Development and validation of a marine sequential turbocharging diesel engine combustion model based on double Wiebe function and partial least squares method. Energy Convers Manag 2017; 151: 481–495.

23.

Ghojel

. Investigation of cycle processes of direct injection diesel engines with cylindrical piston bowl. PhD Thesis, Moscow Automobile and Road Institute (MADI)Moscow, 1974.

24.

Platt

. Sequential minimal optimization: a fast algorithm for training support vector machines. 1998. Microsoft Research

25.

Canova

Garcin

Midlam-Mohler

, et al. A control-oriented model of combustion process in a HCCI diesel engine. In: American control conference, Portland, OR, 8–10 June 2005. New York, NY: IEEE.