American Journal of Mechanical Engineering
ISSN (Print): 2328-4102 ISSN (Online): 2328-4110 Website: http://www.sciepub.com/journal/ajme Editor-in-chief: Kambiz Ebrahimi, Dr. SRINIVASA VENKATESHAPPA CHIKKOL
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American Journal of Mechanical Engineering. 2021, 9(1), 24-40
DOI: 10.12691/ajme-9-1-4
Open AccessArticle

A Model-based Method of Monitoring Combustion Pressure Measurement Chains for Closed-loop Combustion Control Applications

David R. Rogers1, , Antonios Pezouvanis2 and Nikolaos Kalantzis2

1Kistler Instrumente AG, Switzerland

2Aeronautical and Automotive Engineering, Loughborough University

Pub. Date: August 31, 2021

Cite this paper:
David R. Rogers, Antonios Pezouvanis and Nikolaos Kalantzis. A Model-based Method of Monitoring Combustion Pressure Measurement Chains for Closed-loop Combustion Control Applications. American Journal of Mechanical Engineering. 2021; 9(1):24-40. doi: 10.12691/ajme-9-1-4

Abstract

Significant research is ongoing into the use of carbon neutral fuels for combustion engines. In order to fully exploit these new fuel technologies, alongside existing carbon based fuel types, the engine requires a sophisticated level of control for the combustion event based upon a cyclic feedback loop (i.e., a preceding cycle provides the optimization data for the following cycle). This then allows the engine and combustion controller to have the capability to respond and optimise, normal and abnormal combustion phenomena, based on information gained during run-time (as opposed to inferred or indirectly derived parameters). An essential element is the in-cylinder pressure sensor and its measuring chain, that supplies the raw in-cylinder pressure curve for real time analysis within the control system. This paper describes a model-based method for monitoring such a dynamic system, in which the condition of the physical system is represented in a dynamic model consisting of the engine itself, plus the measuring chain, as coupled models. The intent is to mimic the condition of the complete physical system in the model, allowing comparison of model and physical systems to observe residuals and identify fault conditions with all, or part of the measuring chain components.

Keywords:
engine pressure in-cylinder closed-loop control emissions efficiency model-based real-time co-simulation robustness failure detection

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  P. Casoli et al., “Development and validation of a ‘crank-angle’ model of an automotive turbocharged engine for HiL applications,” in Energy Procedia, 2014, vol. 19, p. 146808741771333.
 
[2]  A. Al-Durra, L. Fiorentini, M. Canova, and S. Yurkovich, “A Model-Based Estimator of Engine Cylinder Pressure Imbalance for Combustion Feedback Control Applications,” 2011 Am. Control Conf., no. May, pp. 991-996, 2011.
 
[3]  M. Korres, “Cylinder Pressure Sensor based Engine Combustion and Fuel System Diagnostics,” 2016.
 
[4]  Minghui Kao and J. J. Moskwa, “Model-based engine fault detection using cylinder pressure estimates from nonlinear observers,” 2002.
 
[5]  D. Watzenig, M. S. Sommer, and G. Steiner, “Engine state monitoring and fault diagnosis of large marine diesel engines,” e i Elektrotechnik und Informationstechnik, vol. 126, no. 5, pp. 173-179, May 2009.
 
[6]  F. Liu, G. A. J. Amaratunga, N. Collings, and A. Soliman, “An Experimental Study on Engine Dynamics Model Based In-Cylinder Pressure Estimation,” 2012.
 
[7]  S. Kulah, A. Forrai, F. Rentmeester, T. Donkers, and F. Willems, “Robust cylinder pressure estimation in heavy-duty diesel engines,” Int. J. Engine Res., vol. 19, no. 2, pp. 179-188, Feb. 2018.
 
[8]  Z. Zhou, D. Liu, and X. Shi, “Research on combination of data-driven and probability-based prognostics techniques for equipments,” in Proceedings of 2014 Prognostics and System Health Management Conference, PHM 2014, 2014, pp. 323-326.
 
[9]  W. Haijun, “Research of Marine Diesel Engine Condition Detecting Base on BP Neural Network and Spectrometric Analysis,” Oct. 2010.
 
[10]  Q. Wang and H. S. Dai, “Engine condition monitoring based on grey AR combination model,” in International Conference on Challenges in Environmental Science and Computer Engineering, CESCE 2010, 2010, vol. 1, pp. 215-218.
 
[11]  D. Watzenig, G. Steiner, and M. S. Sommer, “Robust estimation of blow-by and compression ratio for large diesel engines based on cylinder pressure traces,” in Conference Record - IEEE Instrumentation and Measurement Technology Conference, 2008, pp. 974-978.
 
[12]  T. L. Fog et al., “ON CONDITION MONITORING OF EXHAUST VALVES IN MARINE DIESEL ENGINES,” 1999.
 
[13]  H. Wang, I. Kolmanovsky, and J. Sun, “Set-membership condition monitoring framework for dual fuel engines,” in Proceedings of the American Control Conference, 2016.
 
[14]  R. H. Badgley, “A Knowledge-Based System Approach to Improved Marine Diesel Engine Condition Assessment,” 1985.
 
[15]  D. Grill and S. Tacke, “System Architecture and Applications of Vehicle Condition Monitoring,” SAE Trans., no. 724, 2002.
 
[16]  A. R. Dandge, “Low Cost Engine Monitoring System for Commercial Vehicles,” SAE - Int., 2010.
 
[17]  C. Wallin, L. Gustavsson, and M. Donovan, “Engine Monitoring of a Formula 1 Racing Car Based on Direct Torque Measurement,” in Electronic Engine Controls 2002: Engine Control, Neural Networks and Non-Linear Systems, 2002.
 
[18]  A. Radwan, A. Soliman, and G. Rizzoni, “Model-Based Component Fault Detection and Isolation in the Air-Intake System of an SI Engine Using the Statistical Local Approach,” Repr. From Electron. Engine Control., 2003.
 
[19]  A. Schwarte and R. Isermann, “Model-Based Fault Detection of Diesel Intake with Common Production Sensors Printed in USA Model-Based Fault Detection of Diesel Intake with Common Production Sensors,” 2002.
 
[20]  M. B. and S. M. In Kwang Yoo, Kenneth Simpson, I. K. Yoo, K. Simpson, M. Bell, and S. Majkowski, “An Engine Coolant Temperature Model and Application for Cooling System Diagnosis,” SAE Tech. Pap., no. 724, Mar. 2000.
 
[21]  J. J. Gribble, “A model based approach to real-time aero - engine condition monitoring,” in IEE Seminar on Aircraft Airborne Condition Monitoring (Ref. No. 2003/10203), 2003, pp. 4/1-4/6.
 
[22]  Vanraj, D. Goyal, A. Saini, S. S. Dhami, and B. S. Pabla, “Intelligent predictive maintenance of dynamic systems using condition monitoring and signal processing techniques #x2014; A review,” in 2016 International Conference on Advances in Computing, Communication, Automation (ICACCA) (Spring), 2016, pp. 1-6.
 
[23]  T. R. Krogerus, M. P. Hyvönen, and K. J. Huhtala, “A Survey of Analysis, Modeling, and Diagnostics of Diesel Fuel Injection Systems,” J. Eng. Gas Turbines Power, vol. 138, no. 8, p. 081501, Dec. 2016.
 
[24]  Robert Keim, “Understanding and Modeling Piezoelectric Sensors,” 2018. [Online]. Available: https://www.allaboutcircuits.com/technical-articles/understanding-and-modeling-piezoelectric-sensors/.
 
[25]  Robert Keim, “Understanding and Implementing Charge Amplifiers for Piezoelectric Sensor Systems,” 2018. [Online]. Available: https://www.allaboutcircuits.com/technical-articles/understanding-and-implementing-charge-amplifiers-for-piezoelectric-sensor-s/.
 
[26]  D. R. Rogers, Engine Combustion: Pressure Measurement and Analysis. Warrendale, PA: SAE International, 2010.