Research On Comfort Evaluation Of Car Seat Based On B-Spline Interpolation And Particle Swarm Optimization

With the continuous improvement of economic level and material life,automobiles have become the main means of transportation for daily travel and cargo transportation,and their driving comfort has been upgraded to the third focus of traditional safety and handling.As the main component of the car interior,the seat's comfort performance directly determines the driver's experience of the whole car.The high-comfort car seat not only relates to driving safety and the health of the occupants,but also potentially increases the consumer's desire to purchase.How to evaluate the comfort of car seats,how to establish a scientific standard evaluation system,has become the focus of scholars.In the main and objective evaluation,the objective pressure distribution is the main data resource for predicting the comfort of car seats.A large number of studies focus on finding appropriate mathematical methods to establish the quantitative relationship between subjective scores and objective pressure data,so as to achieve smaller predictions error.In this paper,the original pressure matrix collected by objective evaluation is studied.The interpolation method is used to expand the information volume of the original data.From the aspects of enhancing the pressure matrix simulation degree and improving the objective experimental conditions,the objective pressure data quality is improved to improve the seat comfort.The prediction accuracy of the model is evaluated;and the reference standard is provided for the evaluation of the comfort of the car seat by means of optimization.Firstly,unlike the traditional method of extracting the characteristic parameters directly from the measured pressure matrix,the method of fitting the surface using B-spline interpolation is used to expand the pressure matrix,which solves the problem that the density of the sensor test points is limited and cannot be measured.The problem of pressure matrix,and the validity of B-spline interpolation application is verified by cloud image comparison and quantitative analysis,which provides a powerful data foundation for the subsequent establishment of a high prediction accuracy comfort evaluation model;Secondly,the experimental process of subjective and objective evaluation was further improved,and the broadly representative subjects were selected.The BMI(Body Mass Index)index was distributed between 17.0-28.4,and the height covered 90 th and 95 th..Select the seat to be tested,use the driving seat of 10 different grades of cars,and build a simulated driving test bench in full accordance with the driving environment of the car,ensuring the quality of objective pressure data collection;Finally,the optimization problem of comfort prediction model is designed.Based on the response surface theory,the quantitative relationship between objective pressure data and subjective score is established to predict the comfort score of car seat.Then the particle swarm optimization algorithm is used to optimize the design.The results show that the model can provide a reference standard for better evaluation of car seat comfort.Using the B-spline interpolation to expand the pressure data,a comfort prediction model was established,and the average absolute error was reduced by 1.33% compared to the prediction model established using the original pressure data collected directly;Based on the response surface theory,a comfort evaluation prediction model with high fitting accuracy is established,and the particle swarm optimization algorithm is used to optimize the prediction model.Three kinds of(slim,medium,and fat)different body groups are optimized.In the comfortable state,that is,the comfort score is 14.99 minutes(out of 15 points),the reference standard of each pressure characteristic parameter value;Comparing the optimization results,it is found that the three body types have similar maximum pressure values of ischial tuberosity under high comfort state,and the maximum pressure of ischial tuberosity can be used as the main index to evaluate the comfort of car seat,simplifying the evaluation process.