Application of statistical approaches in IC engine calibration to enhance the performance and emission Characteristics: A methodological review. (15th September 2022)

• Record Type: Journal Article
• Authors: Sathish Kumar, T.; Vignesh, R.; Ashok, B.; Saiteja, Pajarla; Jacob, Ashwin; Karthick, C.; Jeevanantham, A.K.; Senthilkumar, M.; Muhammad Usman, Kaisan
• Is Part Of: Fuel. Volume 324:Part B(2022)
• Publication Date: 2022-09-15
• Subjects: 2D Two-dimensional -- AI Artificial intelligence -- ANN Artificial neural network -- ANOVA Analysis of variance -- AVGAS Aviation gasoline -- BMEP Brake mean effective pressure -- BP Brake power -- BSCO Brake specific carbon monoxide -- BSCO2 Brake specific carbon dioxide -- BSFC Brake specific fuel consumption -- BSHC Brake specific hydrocarbons -- BSNOx Brake specific oxides of nitrogen -- BSTHC Brake specific total hydrocarbons -- BTDC Before top dead center -- BTE Brake thermal efficiency -- CCD Central composite design -- CCRD Central composite rotatable design -- CI Compression ignition -- CIME Calophyllum inophyllum methyl ester -- CNG Compressed natural gas -- CO Carbon monoxide -- CO2 Carbon dioxide -- CR Compression ratio -- CRDi Common rail direct injection -- DEE Diethyl ether -- DGM Diglyme -- DMC Dimethyl carbonate -- DoE Design of experiments -- DPF Diesel particle filter -- EGR Exhaust gas recirculation -- FS/N Signal-to-noise ratio -- GA Genetic algorithm -- GDI Gasoline direct injection -- HC Hydrocarbon -- IC Internal combustion -- ID Injection duration -- IP Injection pressure -- ISCO Indicated specific carbon monoxide -- ISNOx Indicated specific oxides of nitrogen -- IS-Smoke Indicated specific smoke -- IT Injection timing -- MAPE Mean absolute percentage error -- MIMO Multiple-input multiple-output -- MISO Mixed-integer surrogate optimization -- MLP Multi-layer perceptron -- MPFI Multi-point fuel injection -- MRSN Multi-response signal-to-noise -- MSE Mean squared error -- NOx Oxides of nitrogen -- OICA International Organization of Motor Vehicle Manufacturers -- OFAT One factor at a time -- PM Particulate matter -- PMII Pilot-main injection intervals -- PN Particulate number -- RSM Response surface methodology -- SCR Selective catalytic converter -- SFC Specific fuel consumption -- SI Spark ignition -- SOI Start of injection -- SVM Support vector machine -- TDC Top dead center -- THC Total hydrocarbons -- UHC Unburned hydrocarbons -- VCR Variable compression ratio; Engine parameter Screening -- Engine optimization -- Taguchi -- RSM -- ANN -- GA; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2022.124607
• Languages: English
• ISSNs: 0016-2361

Abstract

Graphical abstract: Highlights: An overview of statistical tools for Engine optimization are briefed. Assessment of Engine parameter screening, optimization and prediction techniques are examined. Application of numerous statistical tools on engine design and calibration are investigated. An incisive procedure of calibration and optimization for engines are highlighted. Abstract: It is a well-known fact that the automotive industries have predominantly ruled the global industrial and commercial sectors. However, an increase in the demand for fossil fuels and stringent emission norms have paved a way for alternative fuels to power IC engines. To adapt the alternative fuels in IC engines, certain optimization protocols are followed by the automotive industry to save the time and cost involved in production, design and engine operating conditions. However, due to the broad nature of this subject in automotive applications, the optimization of engine operating conditions and their respective parameters are deeply delved into in this article. In order to guide the novice engine researchers, this article intents to critically elucidate the optimization techniques used by researchers for improving the performance of spark ignition and compression ignition engines systems and its various sub-systems. Initially, this article begins with experimental design plan approach for screening and optimization. Then elucidate about the single point optimization of Taguchi approach and multi-objective optimization of RSM approach. Further, provides the information of predictive optimization approach of Genetic algorithm in engine optimization and artificial neural networks for recognize the engine behaviour pattern. Moreover, this article also explains the certain methods to analyze the accuracy and model-fit significance for certain methodologies using an experimental case study dedicated solely for this article. From the review, it can be concluded that the statistical technique efficiently assists in exploring the in-depth engine function relation between the input variables.