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Research On Lateral Stability Control For Large Bus Based On Intelligence Tire System

Posted on:2021-05-17Degree:MasterType:Thesis
Country:ChinaCandidate:F YangFull Text:PDF
GTID:2392330620972029Subject:Vehicle engineering
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The rapid development of China’s transportation industry has driven the production and sales of commercial vehicles.However,commercial vehicles themselves have the characteristics of large quality and large load.They are more prone to dangerous accidents such as vehicle instability than passenger vehicles.The harm caused by an accident from commercial vehicles is also greater.Therefore,as people prefer to travel by large bus,safety issues have received widely attention.In this paper,the UniTire tire model is firstly studied,relevant knowledge of the UniTire model are introduced,then the steady-state complex characteristics of tires are modeled,and the Least Squares is used to identify the parameters of tire model formula.On the basis of summarizing the domestic and foreign research achievements on intelligent tires,an intelligent tire monitoring system is designed and optimized to detect the tire force in real time.The vehicle characteristics is modeled using the parameters of the reference vehicle by Trucksim,and the parameters of the ideal reference model are optimized using the intelligent tire detection system.Base on that,the lateral stability control algorithm for large bus involving online tire force estimation is studied.Finally,the hardware-in-the-loop test bench is used to verify the control strategy.The main contents of this article are as follows:(1)According to the simulation data of similar tires in Trucksim,the identification of the UniTire model parameters is carried out,and the simulation results are compared with the virtual experimental data.UniTire model is established by S-Function in Simulink,and the vehicle model is established in Trucksim based on reference vehicle parameters,both models are used for joint simulation.(2)The tire intelligent collection equipment is designed and optimized,and a high frame rate camera is installed on the rim surface.The camera can be uese to capture video of the marking array of the tire’s internal tread,and the data is prosessed through Matlab software to extract the relative position of the marking point array,then the tire force is estimated according to the relationship between the tire force and deformation.Finally,through this test,the system can monitor the tire force in real time.According to the comparison,the difference between the estimated tire force and the actual tire force under each working condition is small.(3)On the basis of the intelligent tire detect system,to ensure the yaw stability of large bus,the vehicle lateral stability control strategy involving the intelligent tire monitoring system is developed,and the reference model parameters are optimized.It elaborated how to choose the control quantity and the setting method of the instability judgment module.At the same time,the sliding mode variable structure controller is established,and the torque calculation is optimized considering the influence of the tire force.The tire longitudinal force collected through the intelligent tire monitoring system is used as a feedback input to adjust the braking force distribution of ESP.(4)Finally,this paper simplified the EBS system equipped on the advanced configuration of the large bus,and the valve devices from WABCO company is selected to built the pneumatic brake bench for hardware in the loop test.The control strategy is verified on the pneumatic electronic control test bench.The simulation results show that the lateral stability control method developed in this paper can maintain lateral stability of large bus under the specified working conditions,and the driver can easily manipulate the vehicle to travel along the designated path,and this ESP system has the ability to maintain the vehicle’s lateral stability.
Keywords/Search Tags:UniTire tire model, Intelligent tire, Yaw control, Pneumatic braking, Hardware in the loop
PDF Full Text Request
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