| Wheel Six-component Force is an important basic data for the development and verification of vehicle and chassis fatigue reliability.At present,the acquisition of Wheel Six-component Force load is mainly through real vehicle acquisition and simulation extraction.Collecting the Wheel Six-component Force through the real vehicle,the sensor is expensive and the technology is monopolized by foreign countries,which will consume a lot of manpower,material resources,and time costs;there are two ways to extract the Wheel Six-component Force through simulation,the reverse solution and the virtual test field technology.The vehicle collects the load and the accuracy is low;the use of the virtual test field technology can obtain the design load spectrum in the early stage of product development,which greatly improves the product development efficiency,and has been popularized in load extraction to a certain extent.There are few studies on the virtual test field,and there are still problems such as difficult 3D road modeling and inaccurate extraction.Therefore,this paper establishes a 3D road surface model through the measured load spectrum,extracts the Wheel Six-component Force based on the virtual test field technology,and establishes a Wheel Six-component Force extraction method based on the virtual test field,which has important engineering application value.First,in order to obtain the real vehicle response data for road modeling and model verification,a load spectrum synchronous acquisition and test system was established by using Wheel Six-component Force sensors,acceleration sensors,displacement sensors,logic switches and GPS sensors.The acquisition plan completes the collection of the actual vehicle load spectrum,uses the Butterworth filter to remove the trend items and interference,and uses the standard deviation method to remove the singular values.The preprocessed data is analyzed in the time-frequency domain.,wheel speed and logic switch signals are intercepted to the required load spectrum data.Secondly,according to the principle of 3D road reconstruction,a 3D road reconstruction method based on measured load spectrum and BP neural network is proposed.On the basis of establishing the input vibration model of the vehicle’s 7-DOF road surface,a two-dimensional road spectrum inverse model based on BP neural network is established.Taking the standard grade road as the input and the vehicle’s 7-DOF vibration model response as the output,the two-dimensional road spectrum inverse model is trained and verified.Taking the measured wheel center,the vertical acceleration of the vehicle body and its integral data as the model input,the two-dimensional road spectrum is obtained by inverse calculation.Using the 2D road spectrum data,the triangular mesh method is used to complete the 3D road reconstruction,and three kinds of curvilinear regular grid pavement models of the high-speed ring road,the comprehensive road and the abnormal noise road are established.Then,based on the system dynamics modeling theory,the system dynamics model of the whole vehicle is established,and the suspension model and parameters are verified;the driving control file is compiled using the vehicle state information measured on the proving ground,and the driving model is established;combined with the established three-dimensional The road surface model has completed the establishment of the "people-vehicle-road" virtual test field system.Finally,in the "people-vehicle-road" virtual test field system,three virtual tests under the road surface were carried out,the Wheel Six-component Force was extracted,and the measured Wheel Six-component Force data was used for time-frequency domain verification.Proving ground method for extracting the Wheel Six-component Force.On this basis,the main influencing factors of the Wheel Six-component Force are analyzed,and the influence of structural parameters such as curb weight,center of mass position and wheelbase on the Wheel Six-component Force is studied. |
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