Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> In this paper we discuss the generation of models for emissions of a Diesel engine, produced by genetic programming based evolutionary system identification: Models for the formation of NO x and particulate matter emissions are identified and analyzed. We compare these models to models designed by experts applying variables section and the identification of local polynomial models; analyzing the results summarized in the empirical part of this paper we see that the use of enhanced genetic programming yields models for emissions that are valid not only in certain parts of the parameter space but can be used as global virtual sensors. <s> BIB001 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> A four-cylinder diesel engine model is established using Pro/Engineer 3D modeling software. The model is loaded by ANSYS software. Grids meshes are imposed to the model with contact-settings and boundary conditions. Finite element analysis is performed on the contact-state of the diesel engine body. According to the minimum-zone principle for the flatness error analysis, Particle Swarm Optimization algorithm (PSO) is applied, and the mathematical model and method of the engine body top-surface-flatness error analysis is established. Based on the established method, the engine body top-surface-flatness errors can be obtained under the maximum preload working conditions, providing an accurate and effective way for further improvement of the engine tightness and body design. <s> BIB002 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> This paper concerns measurement and modeling of cylinder pressure in diesel engines. The aim of this paper is to build the empirical-analytical model of engine working cycle. The experiments on engine test bench were conducted. The new genetic-fuzzy system GFSm was proposed. By means of GFSm, the engine working cycle model was built. This model allows simulation of cylinder pressure for each allowable crankshaft speed, and loads and also for several biofuels. The model can be used to evaluate the quality of working cycles of piston engine with an accuracy required in practical technical applications. <s> BIB003 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> The aim of this work was to build an empirical–analytical model for diesel engine operation and control. The engine that was used was fueled by biofuels or diesel oil and the measurements of cylinder pressure were conducted on a test bench. The engine model was built by means of a proposed genetic-fuzzy system. This model allows simulation of cylinder pressure for each allowable crankshaft speed with accuracy required in practical technical applications. <s> BIB004 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> This paper presents a novel control-oriented model of the raw emissions of diesel engines. An extended quasistationary approach is developed where some engine process variables, such as combustion or cylinder charge characteristics, are used as inputs. These inputs are chosen by a selection algorithm that is based on genetic-programming techniques. Based on the selected inputs, a hybrid symbolic regression algorithm generates the adequate nonlinear structure of the emission model. With this approach, the model identification efforts can be reduced significantly. Although this symbolic regression model requires fewer than eight parameters to be identified, it provides results comparable to those obtained with artificial neural networks. The symbolic regression model is capable of predicting the behavior of the engine in operating points not used for the model parametrization, and it can be adapted easily to other engine classes. Results from experiments under steady-state and transient operating conditions are used to show the accuracy of the presented model. Possible applications of this model are the optimization of the engine system operation strategy and the derivation of virtual sensor designs. <s> BIB005 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Engine Models: <s> The computer simulation technology of the work process of internal-combustion engine is the important measure to study the internal-combustion engine, but generally, because of the uncertainty of input parameters, the precision of the simulation model of the engine work process, which largely limits the application of the simulation model, so the parameters of the simulation model needs to be calibrated. Taking the work process of the certain one type turbocharging diesel engine as the example, and combining the genetic algorithm with the ant colony algorithm, the parameter combination which can satisfy the requirements of precision, is selected in this article to effectively reduce the simulation experiment times of parameter calibration, and realize the automatic calibration of the simulation model parameters. By comparing and analyzing the practical result of the experiment and the result of the simulation computation, the effectiveness of the algorithm has been validated in the article. <s> BIB006
Computer simulations of internal combustion engines are very important in studying the engines; however, because of the uncertainty of input parameters, the models are not very precise and thus the model parameters should be calibrated. Calibrating the parameters of the model of a diesel engine was studied in BIB006 , and a hybrid genetic algorithm and ant colony optimization algorithm were employed. The aim of the research was to reduce the time of calibration process and improve the precision of the model. In order to develop a four-cylinder diesel engine model, the ANSYS software was used BIB002 . Then grid meshes were imposed to the model with contact-setting and boundary conditions and PSO was employed for the flatness error analysis. 2) Cylinder Pressure: Concerning the measurement and modeling cylinder pressure in a diesel engine, an analyticalempirical model of the engine was built in  - BIB003 . A genetic-fuzzy algorithm was used in this papers to model the system. In BIB004 , an empirical-analytical model for diesel engine operation and control was built using a genetic-fuzzy system. The system was used to simulate the cylinder pressure of a diesel engine fueled by bio-fuels or diesel oil, for each allowable crankshaft speed. 3) Emissions: A genetic programming-based evolutionary system identification algorithm was proposed in BIB001 , to model the formation of NO x and particulate matter emissions in a diesel engine. The model was then compared to other models designed by experts. The authors showed that genetic programming modeling approaches were capable of generating models which can be used as global virtual sensors. In BIB005 , a novel control-oriented model of raw emissions of diesel engines was presented. The inputs of the model were chosen by a selection algorithm which was based on geneticprogramming. Then based on the selected inputs, a hybrid symbolic regression algorithm generated the nonlinear structure of the model. Experimental results suggested that while the proposed model had a smaller number of inputs, it provided comparable results to those obtained with neural networks.