Innovative Calibration Method for System Level Simulation Models of Internal Combustion Engines

The paper outlines a procedure for the computer-controlled calibration of the combined zero-dimensional (0D) and one-dimensional (1D) thermodynamic simulation model of a turbocharged internal combustion engine (ICE). The main purpose of the calibration is to determine input parameters of the simulation model in such a way as to achieve the smallest difference between the results of the measurements and the results of the numerical simulations with minimum consumption of the computing time. An innovative calibration methodology is based on a novel interaction between optimization methods and physically based methods of the selected ICE sub-systems. Therein physically based methods were used for steering the division of the integral ICE to several sub-models and for determining parameters of selected components considering their governing equations. Innovative multistage interaction between optimization methods and physically based methods allows, unlike the use of well-established methods that rely only on the optimization techniques, for successful calibration of a large number of input parameters with low time consumption. Therefore, the proposed method is suitable for efficient calibration of simulation models of advanced ICEs.

[1]  K. Kobe The properties of gases and liquids , 1959 .

[2]  Xlj Xander Seykens,et al.  Automated Model Fit Method for Diesel Engine Control Development , 2014 .

[3]  C. S. Daw,et al.  A proposed methodology for estimating transient engine-out temperature and emissions from steady-state maps , 2010 .

[4]  Soliman Abdel-hady Soliman,et al.  Modern Optimization Techniques with Applications in Electric Power Systems , 2011 .

[5]  Haiyan Miao,et al.  Genetic Algorithms Optimization of Diesel Engine Emissions and Fuel Efficiency with Air Swirl, EGR,Injection Timing and Multiple Injections , 2003 .

[6]  Johann C. Wurzenberger,et al.  Assessment of engine thermal management through advanced system engineering modeling , 2014, Adv. Eng. Softw..

[7]  D. P. Sekulic,et al.  Fundamentals of Heat Exchanger Design , 2003 .

[8]  Karl A. Zinner Aufladung von Verbrennungsmotoren , 1975 .

[9]  Mark J. Anderson,et al.  DOE Simplified: Practical Tools for Effective Experimentation , 2000 .

[10]  He Ma,et al.  Model-Based Multiobjective Evolutionary Algorithm Optimization for HCCI Engines , 2015, IEEE Transactions on Vehicular Technology.

[11]  Zoran Filipi,et al.  Cam-phasing Optimization Using Artificial Neural Networks as Surrogate Models-Fuel Consumption and NOx Emissions , 2006 .

[12]  Kangyao Deng,et al.  Thermodynamic model and optimization of a miller cycle applied on a turbocharged diesel engine , 2014 .

[13]  A. Maria,et al.  Simulation Optimization: Methods And Applications , 1997, Winter Simulation Conference Proceedings,.

[14]  Li-ming Di,et al.  Study on simulation and optimization of engine valve timing , 2010, 2010 International Conference on Mechanic Automation and Control Engineering.

[15]  John B. Heywood,et al.  Internal combustion engine fundamentals , 1988 .

[16]  Tomaž Katrašnik,et al.  Transient Momentum Balance—A Method for Improving the Performance of Mean-Value Engine Plant Models , 2013 .

[17]  Michele Messina,et al.  The Evaluation of Gross Heat Release in Internal Combustion Engines by Means of Genetic Algorithms , 2006 .

[18]  Ali Jamali,et al.  Modelling and multi-objective optimization of a variable valve-timing spark-ignition engine using polynomial neural networks and evolutionary algorithms , 2007 .

[19]  Yu Cai Dong,et al.  Research on the Parameter Calibration of the Internal-Combustion Engine Work Process Simulation Model , 2011 .

[20]  Z Win,et al.  Parameter optimization of a diesel engine to reduce noise, fuel consumption, and exhaust emissions using response surface methodology , 2005 .

[21]  Tomaž Katrašnik,et al.  Application of Optimization Techniques to Determine Parameters of the Vibe Combustion Model , 2009 .

[22]  Tomoyuki Hiroyasu,et al.  Multi-Objective Optimization of Diesel Engine Emissions and Fuel Economy using Genetic Algorithms and Phenomenological Model , 2002 .

[23]  Siuli Mukhopadhyay,et al.  Response surface methodology , 2010 .

[24]  Xiaodong Li,et al.  Benchmark Functions for the CEC'2010 Special Session and Competition on Large-Scale , 2009 .

[25]  Johann C. Wurzenberger,et al.  A Comprehensive Study on Different System Level Engine Simulation Models , 2013 .