Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> C. Optimization of Mechanical Parts in Gasoline Engines <s> In this paper a method is described for determining the design unbalance of crankshafts and also the recommended procedure for a balanced design strategy. The use of a search tool for solutions is suggested based on Genetic Algorithms (GA). GAs have been used in different applications, one of them is the optimization of geometric shapes, a relatively recent area with high research potential. The interest towards this field is growing, and it is anticipated that in the future mechanical engineering will be an area where many applications of shape optimization will be widely applied. <s> BIB001 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> C. Optimization of Mechanical Parts in Gasoline Engines <s> In this study, computational fluid dynamics (CFD) analysis is utilized in order to determine the convective heat transfer coefficient of an engine air-cooling system in different air velocity conditions. Various models with different geometric configurations are considered. Based on the CFD results, two formulas are proposed to approximate the values of convective heat transfer coefficients in zero and non-zero air velocities. Finally, two conflicting objective functions including volume of the required material for construction of the finned cylinder and heat release per unit temperature difference are considered. Multi-objective optimization using genetic algorithm is utilized, which generates a multiple set of solutions, each of which is a trade-off between two objectives. The user can select each of the optimal geometric configurations based on the project's requirements. In other words, considering the desired thermal design, designer is able to find the minimum volume of the required material for co... <s> BIB002 </s> Meta-Heuristic Algorithms in Car Engine Design: A Literature Survey <s> C. Optimization of Mechanical Parts in Gasoline Engines <s> Currently only the bearing was usually taken as the studing object in the optimization of crankshaft bearing. However, there is the corresponding relationship between the main dimensions (the diameter and width of journal) of the crankshaft bearing and crankshaft in an internal combustion engine, and there is the interaction between the crankshaft bearing and crankshaft in operation. In this paper, the crankshaft-bearing system of a four-cylinder engine was taken as the studing object, and an integrated optimization design of crankshaft bearing based on the multi-object was carried out. The total average frictional power loss of crankshaft bearings and the crankshaft mass were chosen as the objective functions, and the algorithms of the Particle Swarm Optimization (PSO) with the idea of decreasing inertia weight based on exponential curve strategy and the simulated annealing (SA) were used in the intelligent optimization. The results of comparing the two algorithms with the ones of original design show that, 26.2% and 25.8% reduction in total average frictional power loss of crankshaft beatings and 5.3% reduction of the crankshaft mass were presented by the optimization design, which are more reasonable than the original design. By comparison, the PSO algorithm has higher precision than the SA algorithm, but the calculation time of the SA algorithm is less than that of the PSO algorithm. <s> BIB003
Designing mechanical structures is a complex optimization task with different and sometimes contradictory objectives. This is particularly true when designing different parts of a car engine. Many researchers thus employ meta-heuristic algorithms when designing mechanical parts of an engine. In this section, we review the applications of meta-heuristic algorithms in mechanical design of car engines. We start our review with applications of heuristic algorithms in designing mechanical parts of gasoline engines. 1) Air Cooling System: In order to optimize the air-cooling system of an engine, a multiobjective EA was employed in BIB002 . In this problem, there were two conflicting objectives, one was the volume of the required material for construction of the finned cylinder and the other was the heat release per unit temperature difference. The system they have designed generated a set of solutions, thus users can select the optimal geometric configurations based on their project requirements. 2) Crankshafts: In one of the first attempts in employing meta-heuristic algorithms in crankshaft design, a genetic algorithm was used in BIB001 to determine the design unbalance of crankshafts and also to optimize the geometric shape for balanced design of crankshafts. They then extended their study in  . The crankshaft-bearing system of a four-cylinder engine was designed in BIB003 , where a PSO algorithm was used to optimize the crankshaft mass and the total average frictional power loss of the crankshaft bearing. The results suggest 26.2% and 5.3% reduction in average frictional power loss and crankshaft mass, respectively. In order to optimize the crankshaft offset a genetic algorithm was used in  . The optimization process in this paper was defined to be the minimization of friction losses between piston and cylinder, and the difference between peak values of resultant force of the piston in the normal direction. The research showed that the performance of an engine can be improved by a careful offset of crankshaft. 3) Cylinder Fin Arrays: Genetic algorithms were used in cylinder fin arrays is the maximization of heat transfer through fin arrays of an engine cylinder  , where a binary coded genetic algorithm was employed. They also studied the effect of spacing between fins on various parameters.