Research On Smart Tire Information Estimation Algorithms Based On Multi-Acceleration Measurement

The contact between tire and ground plays an important role in the acceleration,deceleration and steering of vehicles,as well as for the safety and stability of vehicles.However,in some cases of sudden changes in road conditions,the driver's ability to control vehicles will be significantly reduced.Therefore,in the field of vehicle active safety,a variety of chassis control systems have emerged to enhance the active safety performance of the vehicle.Obviously,the design of vehicle control system requires accurate tire status information.At present,indirect estimation methods is widely used in tire information acquiring,which relys on a variety of sensors and complex calculations.With the help of the research of "intelligent tire" technology,we can obtain accurate,direct and fast tire status information,and then improve the performance of chassis control system.Supported by the Nation Natural Science Foundation of China,this paper carries out the research on smart tire information estimation algorithms based on multi-accelerometer measurement.Firstly,a smart tire platform for multi-acceleration measurement is built,which provides the support for the research of smart tire information estimation algorithm.Secondly,based on the smart tire platform,bench test and vehicle test are carried out.Finally,the tire force information,tire pressure status information and tire-road adhesion condition estimation algorithm are studied.The research contents are as follows:1.The establishment of the smart tire platformThe type of accelerometer and the layout scheme of multi-acceleration are determined.A smart tire platform for multi-acceleration measurement is built,and the bench test and vehicle test of smart tire are designed and completed.The tire acceleration information under various working conditions is acquired.The noise in the original acceleration signal is processed,which provides a basis for the subsequent algorithm research.2.Tire force estimation based multi-acceleration measurementThe response mechanism of multi-acceleration of smart tire is analyzed,and the estimation method of tire-ground contact length is proposed,and the characteristics of three-direction acceleration signal are extracted.The tire longitudinal force,lateral force and vertical force are estimated by using neural network algorithm and linear regression model.3.Tire pressure estimation based smart tireThe response mechanism of vibration acceleration signals under different tire pressures is studied.The characteristics of acceleration signals are analyzed and extracted in both time and frequency domains.Based on the time-domain and frequency-domain characteristics of intelligent tire acceleration signal combining with other factors such as wheel speed and load,the corresponding relationship between smart tire acceleration signal and tire pressure state is established by using neural network algorithm,and the tire pressure status is estimated.4.Coefficient estimation based smart tireThe brush tire model is selected,and the road adhesion coefficient is taken as the parameter to be identified.The genetic algorithm is used to identify the parameters.Based on the fuzzy logic,the road adhesion conditions are classified,and the corresponding frequency domain features are selected as the input of the fuzzy logic classifier,and the road type as the output,which achieves a goodr classification effect.