A Model for Crank-Angle-Resolved Engine Cylinder Pressure Estimation

2018 ◽  
Author(s):  
Jing Wu ◽  
Andres Jacoby ◽  
Daniel Llamocca ◽  
Brian Sangeorzan
Keyword(s):  
Cylinder Pressure ◽  
Engine Cylinder ◽  
Crank Angle ◽  
Pressure Estimation

scholarly journals A crank-kinematics-based engine cylinder pressure reconstruction model

2019 ◽  
Vol 21 (7) ◽  
pp. 1147-1161
Author(s):  
Julian F Dunne ◽  
Colin Bennett
Keyword(s):  
Chebyshev Polynomial ◽  
Peak Pressure ◽  
Pressure Sensors ◽  
Spark Ignition Engine ◽  
Least Square ◽  
Cylinder Pressure ◽  
Nonlinear Functions ◽  
Engine Cylinder ◽  
Crank Angle ◽  
Unseen Data

A new inverse model is proposed for reconstructing steady-state and transient engine cylinder pressure using measured crank kinematics. An adaptive nonlinear time-dependent relationship is assumed between windowed-subsections of cylinder pressure and measured crank kinematics in a time-domain format (rather than in crank-angle domain). This relationship comprises a linear sum of four separate nonlinear functions of crank jerk, acceleration, velocity and crank angle. Each of these four nonlinear functions is obtained at each time instant by fitting separate m-term Chebyshev polynomial expansions, where the total 4 m instantaneous expansion coefficients are found using a standard (overdetermined) linear least-square solution method. A convergence check on the calibration accuracy shows that this initially improves as more Chebyshev polynomial terms are used, but with further increase, the overdetermined system becomes singular. Optimal accuracy Chebyshev expansions are found to be of degree m = 4, using 90 or more cycles of engine data to fit the model. To confirm the model accuracy in predictive mode, a defined measure is used, namely the ‘ calibration peak pressure error’. This measure allows effective a priori exclusion of occasionally unacceptable predictions. The method is tested using varying speed data taken from a three-cylinder direct-injection spark ignition engine fitted with cylinder pressure sensors and a high-resolution shaft encoder. Using appropriately filtered crank kinematics (plus the ‘calibration peak pressure error’), the model produces fast and accurate predictions for previously unseen data. Peak pressure predictions are consistently within 6.5% of target, whereas locations of peak pressure are consistently within ±2.7 °CA. The computational efficiency makes it very suitable for real-time implementation.

Analysis of Incylinder Pressure and Temperature Variation in a Four-Stroke S. I. Engine Using Wiebe’s Combustion Model

2014 ◽  
Vol 984-985 ◽  
pp. 957-961
Author(s):  
Vijayashree ◽  
P. Tamil Porai ◽  
N.V. Mahalakshmi ◽  
V. Ganesan
Keyword(s):  
Heat Release ◽  
Combustion Process ◽  
Pressure Variation ◽  
Spark Ignition Engine ◽  
Working Fluid ◽  
Combustion Model ◽  
Cylinder Pressure ◽  
Crank Angle ◽  
Experimental Values ◽  
Release Model

This paper presents the modeling of in-cylinder pressure variation of a four-stroke single cylinder spark ignition engine. It uses instantaneous properties of working fluid, viz., gasoline to calculate heat release rates, needed to quantify combustion development. Cylinder pressure variation with respect to either volume or crank angle gives valuable information about the combustion process. The analysis of the pressure – volume or pressure-theta data of a engine cycle is a classical tool for engine studies. This paper aims at demonstrating the modeling of pressure variation as a function of crank angle as well as volume with the help of MATLAB program developed for this purpose. Towards this end, Woschni heat release model is used for the combustion process. The important parameter, viz., peak pressure for different compression ratios are used in the analysis. Predicted results are compared with experimental values obtained for a typical compression ratio of 8.3.

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