The small leaf springs designed in this paper use the blades shown, and the processing is simple, and each blade adopts the same size. Since the springs of a few sheets of steel need to have more parameters to be determined, there are many factors influencing the factors. The factory often uses the trial and error method. According to the experience, the size parameters are first selected and then substituted into the formula for verification. After several rounds of such repetition, until the strength and stiffness All of them meet the requirements. This design method is not easy to obtain the best design results, and it takes time and labor to solve the above shortcomings. The computer uses the optimization method to solve the design. This often requires the designer to understand the optimization design theory and choose reasonable optimization. Solving methods, compiling and debugging correct computer programs is difficult to implement. The optimization toolbox can solve a variety of optimization problems. This paper discusses the feasibility of using MATLAB to solve the optimal solution of small-section variable-section leaf springs. The results show that the MATLAB optimization design of small-section variable-section leaf springs is simple, easy, fast and accurate. Optimized design model 1.1 Design variables For trapezoidal thickened sections, there are few leaf springs whose design parameters include length dimensions L, L1, L3; thickness dimension parameters h1, h2; blade width b and number of blades n. Where L3 is made by spring on the car The setting of the clamping is determined in advance and is regarded as a constant; the width b depends on the overall vehicle layout and the size specifications of the spring flat steel, and is also selected in advance, and the number of blades n is interactively controlled as discrete constants in the design. Therefore, when designing a few pieces of variable-section leaf springs using the optimization method, there are four design variables in centimeters.
Using MATLAB to optimize the calculation Using the Fmincon function of the MATLAB513 software optimization toolbox to solve the above mathematical model, first need to establish two function files, one is the function file of the objective function, named fun.m; one is the constraint function file, Name it confu.m. Then create an original file that is responsible for the original input, the function call, and the output of the result. Raw data is assigned to global variables to implement data transfer between functions and files. In this way, the original data is only input in the original file, which makes the target function file and the constraint function file common, which increases the versatility of the program.
In order to verify the feasibility and correctness of the algorithm, the front suspension of a certain type of truck is taken as an example, and the design of the small-section variable-section leaf spring is carried out, and compared with the solution result of the composite shape.
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