Ride Comfort Analysis And Optimization Design Of A Off - Road Vehicle

With the development of economic society and the improvement of living standards, the car is no more a simple means of traffic, people have a higher demand for the comfort of its driving. People constantly pay more attention to the requirement for vehicle ride comfort under the condition of economy and power performance indicators improving. On the off-road vehicle, people pay more and more attention to its ride comfort. In this paper, taking a light off-road vehicle as the research object, which based on automobile ride comfort evaluation method, from two aspects of theory and experiment of the SUV comfort are analyzed, and design experiments to study the effect of system parameters on the ride comfort, parameters optimization design, improve the ride comfort SUV. The concrete research content of this article is as follows:(1) To summarize the current evaluation methods, such as Average Absorbed Power, BS 6841-1987, VDI 2057,IOS 2631-1 and so on. By contrast, it reveals the traditional evaluation method of limitations. Finally, we make sure that the ride comfort evaluation index used in the research work is based on GB/T 4970-2009.(2) The random road inputs were generated by the harmonic superposition method. Then, according to the needs of the research on ride comfort, set up 2 dof 1/4 vehicle vibration numerical model,4 dof 1/2 vehicle vibration numerical model and 7 dof vehicle vibration numerical model. The dynamic equations were obtained by the Lagrange method. For ride comfort, random input simulations were carried out at different speeds. The evaluation for ride comfort was carried out on class B road. Beside, we discuss the influence of the nonlinear factors in the analysis of the comfort.(3) Have a road test by the national standard and Evaluation of a suv for comfort. The accuracy of the model was verified by the test.(4) The optimal Latin hypercube method was used to do the DOE, analyzing and the influence of suspension stiffness, damping and tire stiffness on the response output. According to the DOE results, the design variables and the suspension system output’s approximation model were built by response surface, RBF neural network and Kriging respectively. Coefficient of determination was used to test fitting accuracy, and Kriging approximation model fitted the best.Make simulation and optimization of ride comfort on off-road vehicles, which can effectively improve the riding comfort of off-road vehicles, shorten the development cycle and save cost. It is important to improve the sport development in our country, design is of and has great significance.