Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Chemical Kinetic Model: <s> Abstract The auto-ignition predictions of the Shell hydrocarbon fuel ignition model have been improved for initial conditions similar to those in diesel engine environments. A series of modifications were made to the model, including a more accurate calculation of the heat release of the fuel, a new mass balance for the products of the termination reactions, and the enthalpies of the Shell model species, R∗, B and Q were revised. In addition the twenty-six kinetic parameters of the revised model were determined using a genetic algorithm optimization methodology guided by auto-ignition results obtained from a detailed chemical kinetic mechanism. The optimization was performed for a broad range of conditions that is representative of the operating conditions in diesel engines at the start-of-injection (SOI). This range includes: equivalence ratios from 0.5–4.0, initial pressures from 40–120 bar, initial temperatures from 650 K to 1175 K and EGR percentages from 0–75%. The model constants were optimized for two single component hydrocarbons species, n-heptane and tetradecane, that are representative of diesel fuel. Finally, the model was implemented into the KIVA-3V CFD code and a series of engine simulations was performed in order to assess its agreement with experimental data for engine applications. The results were found to be promising in both cases of short and long ignition delays. <s> BIB001 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Chemical Kinetic Model: <s> This research is focused on the fuel economy benefit issues for gasoline engines under emission performance constraints. New technologies are to be implemented on a PFI engine throughout physical operating ranges of the testing vehicle. The objective is to create a complementary scheme that offers an optimal fuel consumption performance. Fuel economy is to be optimized in a city drive cycle. The values from speed-load regions in city drive cycles with no VVT and VCR are used as the baseline. Then, variable valve timing (VVT) and variable compression ratio (VCR) techniques can be applied on 1.8 L four-cylinder engine for fuel economy improvement. The inter-cooled engine is supercharged to achieve efficiency benefits so that a smaller boosted engine can reach similar performance to that of a larger replacement regular engine. The influences of both VVT and VCR on various operating regions are studied to identify the actual outcome of fuel economy improvement by the integration of compression ratio and valve timing technologies so as to optimize the engine operation at a part load region and to prevent engine knock at a full load region. The results show that the two technologies can be collaborated to achieve an overall fuel economy benefit at some typical operating regions despite of overlapping. The speed-load points for potential maximal and minimal fuel economy benefit via technology synergy are determined by genetic algorithm optimization. <s> BIB002 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Chemical Kinetic Model: <s> Abstract A new reduced chemical kinetic model for the Homogeneous Charge Compression Ignition (HCCI) combustion of n -heptane in an engine has been developed. The new model is based on two previous reduced kinetic models for alkane oxidation, from which some reactions have been eliminated and with enhanced treatment of the oxidization of CO and CH 3 O. The kinetic parameters of the key reactions in the new model were adjusted by using a genetic algorithm optimization methodology to improve ignition timings predictions over the range of equivalence ratios from 0.2 to 1.2, temperature from 300 to 3000 K. The final model contains 40 species and 62 reactions and was validated under HCCI engine conditions. The results showed the well-known two-stage ignition characteristics of n -heptane, which involve low and high temperature regimes followed by a branched chain explosion. The optimized reduced model generally agrees well with those of the detailed chemical kinetic model (544 species and 2446 reactions); the computational time of using the former is less 1/1000 that of the latter. <s> BIB003 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Chemical Kinetic Model: <s> The micro-genetic algorithm (μGA) as a highly effective optimization method, is applied to calibrate to a newly developed reduced chemical kinetic model (40 species and 62 reactions) for the homogeneous charge compression ignition (HCCI) combustion of n-heptane to improve its autoignition predictions for different engine operating conditions. The seven kinetic parameters of the calibrated model are determined using a combination of the Micro-Genetic Algorithm and the SENKIN program of CHEMKIN chemical kinetics software package. Simulation results show that the autoignition predictions of the calibrated model agree better with those of the detailed chemical kinetic model (544 species and 2 446 reactions) than the original model over the range of equivalence ratios from 0.1–1.3 and temperature from 300–3 000 K. The results of this study have demonstrated that the μGA is an effective tool to facilitate the calibration of a large number of kinetic parameters in a reduced kinetic model. <s> BIB004 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> 1) Chemical Kinetic Model: <s> New automotive engine combustion concepts, such as the Homogeneous Charge Compression Ignition (HCCI) or the Controlled Autoignition (CAI), have been developed in the last years in order to fulfil the very stringent European regulations limiting pollutant emissions (mainly nitrogen oxides and particulate matter). These combustion modes are not controlled by the physical phenomena prior to combustion, as usual in traditional Compression Ignition (CI) and Spark Ignition (SI) engines, but by the fuel chemical kinetics leading to autoignition, which is described by the corresponding reaction mechanism. Since the detailed reaction mechanism of surrogate fuels (which are used instead of the original fuels in order to simulate their oxidation process) consists of hundreds of species and thousands of reactions, it cannot be used for engine simulation purposes due to the very excessive computational time requirements. Thus, reduced reaction mechanisms, which simulate properly some characteristics of the detailed one (autoignition time, combustion temperature, etc.), are used instead. Among the typical reduction techniques (Quasi-Steady-State Assumption (QSSA), Reaction Analysis, etc.), Genetic Algorithms (GA) allow for both an efficient reduction of small/medium size reaction mechanisms and, when combined with other techniques, a more effective reduction of large reaction mechanisms. In this work, a general and innovative GA methodology for the reduction of kinetic mechanisms describing the hydrocarbon oxidation processes has been proposed, and its application to the reduction of two different mechanism sizes (a medium one describing the methane autoignition and a larger one derived from the oxidation of a diesel fuel surrogate) has provided better results when compared to other GA methodologies or reduction techniques. The reduced mechanisms provide very similar autoignition time and combustion temperature values to those obtained from the detailed mechanism under different engine operating conditions (intake pressure and temperature, equivalence fuel/air ratio and exhaust gas recirculation rate). <s> BIB005
In order to fulfil the new stringent regulations on limiting pollutant emissions new concepts like the homogeneous charge compression ignition (HCCI) have emerged BIB004 . Unlike in traditional compression ignition and SI engines, these combustion modes are controlled by the fuel chemical kinetics leading to autoignition. The combustion process in HCCI engines does not involve flame propagation as in SI engines or flame diffusion as in diesel engine. Thus, the combustion in HCCI engines is dominated by fuel/air chemical kinetics BIB004 . In this respect, a detailed model of the fuel oxidation chemistry is essential in modeling the engines. One example of applications of genetic algorithm in this area is BIB003 and BIB004 , where a new reduced chemical kinetic model of n-heptane was developed. After developing a model for the problem, a micro-genetic algorithm was employed to adjust the parameters of the model. In BIB001 , the Shell hydrocarbon fuel ignition model was improved, where the 26 kinetic parameters of the model were optimized using a genetic algorithm guided by results obtained from a detailed kinetic mechanism. The optimizations were performed for a wide range of conditions representing the operating conditions in diesel engines. In HCCI engines, the detailed reaction mechanism of surrogate fuels cannot be used for engine simulation purposes, due to very expensive computational time requirements BIB005 . Therefore, some algorithms were used to reduce the reaction mechanisms, among which were genetic algorithms that offered an efficient reduction of reaction mechanisms. In BIB005 , a genetic methodology for the reduction of kinetic mechanisms was proposed which provided very similar results to those obtained from the detailed mechanism. 2) Fuel Economy in Gasoline Engines: In order to optimize the fuel economy of a gasoline engine under emission constraints, in BIB002 the variable valve timing and variable compression ratio techniques under various operating regions were applied to a 1.8 L four-cylinder engine. The authors use a genetic algorithm for the speed-load points for potential maximal and minimal fuel economy benefit via technology synergy. In  , a neural network was developed to model a gasoline engine. Then a PSO and a derivative-based method were used to minimize the fuel consumption of the engine with respect to the constraint of emission.