Bus Ride air suspension and damping simulation optimization

With the development of society, people are increasingly demanding automotive comfort. The ride comfort of the car is the biggest suspension system, so the suspension is of great significance. Ride in a traditional study, tend to simplify the linear vehicle suspension system, in fact, has a strong non-linear suspension system.Therefore, the establishment of a relatively simple and accurate nonlinear mathematical model of vehicle suspension and used to ride the study has important theoretical and practical significance. An overview of the process of numerical analysis algorithms, detailed description of Runge - Kutta method and the average acceleration method, and discussed the compatibility of the average acceleration method, convergence and stability, as lay a theoretical foundation for further study. Carried out on the air spring stiffness analysis derived mechanical model of the air spring and shock absorber according to the test data were fitted damping force, thereby establishing a 1 / 2 car nonlinear model. Average acceleration method is derived using a 1 / 2 car model of the solution, in the Matlab / Simulink S-function to call and set up a 1 / 2 car simulation model. In order to verify the accuracy of the model test carried out smoothly; the same time through the comparison of linear and nonlinear nonlinear model proved more realistic than the linear model case. To the vertical center of mass weighted rms acceleration and body pitch angle weighted acceleration rms value as the vehicle ride comfort optimization goals, before the rear suspension damping coefficient for the design variables, suspension damping ratio, dynamic travel and wheel dynamic load as constraint conditions, the use of genetic algorithm, a series of optimal damping coefficient. From the optimization results, the optimized ride comfort of passenger cars has been improved to some extent. And through the optimization of damping for the suspension damping to provide a range of reference values for further damping provide the basis for the regulation and control. 

Key words: nonlinear, air suspension, Matlab, optimal design, the average acceleration method