| After China's WTO entry, the design and production of auto parts must meet the requirements of international community. Lightweight which is one of the mainstreams of the development of automobile industry, as well as the chief method of economizing energy and materials? Automobile manufacturers, mainly through reducing the weight of vehicles to save material, reduce energy consumption and reduce pollution. Lightweight vehicles make spring design tend to lightweight. Optimization algorithm has been widely applied to the automotive components design. Genetic Algorithms (GA) is a new-style optimizing technique, it imitates the selection and evolution of biology in the nature and it is a random search algorithm, which can make up the deficiencies of conventional optimization algorithms, especially deal with the complex problem and non-linear problem which can not be settled by conventional algorithms. Compared with the conventional optimization algorithms, it has the good commonality and robustness. It presents the algorithm is a common framework, which is not dependent on the type, which is more robust, especially for large complex nonlinear systems. Due to these advantages, engineering optimization problems has been widely distributed applications.The purpose of this paper is to apply floating-point genetic algorithm in optimal design of the main auto springs. It including the theory study of the floating-point Genetic algorithms, the contrast of floating-point algorithms with the traditional genetic algorithm, the use of Floating-point Genetic Algorithm in cylindrical spiral spring, taper-leaf spring and the pull-type diaphragm spring. Specific tasks: (1) Describe the genetic algorithm on the whole, analyze the biological basis and the binary description of GA, and make basic tenets study and review of floating-point Genetic algorithm. Program optimization procedure of floating-point genetic algorithm, finally, by optimizing a sick function through genetic algorithm and floating-point genetic algorithm, and get the conclusion that floating-point Genetic Algorithm is more efficient and more practical. (2) A cylindrical spiral spring optimal design is taken as an example, through the analysis and stability calculation of the spring, build the cylindrical spiral spring mathematical model based on the establishment of a floating-point genetic algorithm optimization, prepare the relevant simulation and optimization procedures, and an example of this optimization algorithm has been tested, proved that the cylindrical spiral spring design optimization model is reasonably practicable, has practical value and significance of the promotion.(3) As small-leaf spring can save material to reduce weight, easy to layout and lower vehicle height, good ride comfort, therefore, Bearing in volume is not large vehicles, small-leaf springs are increasingly being used to eliminate multi-unit leaf spring flaws. On the foundation of analysis of the parabola-shaped and linear taper-leaf springs, a mathematical model was built based on the floating-point genetic algorithm optimization, program the optimal procedure. The optimized results contrast with the original results showed that the work ensure the strength of the leaf spring intensity; effectively reduce the weight of the leaf spring. (4) The pull-type diaphragm spring's structure and characteristics was presented and analyzed, Based on the calculation of diaphragm spring Principle (AL), the flexibility and strength of pull-type diaphragm spring is calculated, mathematical model based on the floating-point genetic algorithms is built, program the simulation and optimal procedure. Genetic algorithm to a vehicle pull-type diaphragm spring optimization design is applied, Based on the structure of the same size under the conditions of the push-diaphragm and pull-type diaphragm spring, results of the optimization are analyzed and compared. Feasibility and superiority of the floating-point genetic algorithm in optimizing complex issues is proved.
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