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2013年9月4日 by admin

SS904L steel

With the increment of urban vehicle ownership, vehicle handling stability and activesafety issues received extensive attention. Active safety control systems can improvethe handling stability of vehicle e?ectively and then avoid tra?c accidents. However,on the premise that we can access the vehicle running states accurately, which includethe longitudinal vehicle velocity, the lateral vehicle velocity, the sideslip angle, the yawrate and other states information, then the contSS904L steelrol logic of these vehicle active safetysystems can be work e?ectively. At present, the vehicle states that mentioned abovecan not be measured directly by the onboard sensors on the mass production vehicles.It has become bottleneck issues and limited the development of vehicle active safetycontrol systems because the lack of vehicle states information. With the developmentof the estimation theory, the vehicleSS904L steel states estimation become focus problems using themeasured information by the onboard sensors which has been equipped on the massproduction vehicle. Meanwhile, the vehicle states estimation is a challenging work becausethe environment change rapidly in the vehicle running and the road situation is extremelycomplex, in addition, there are calibration errors and temperature drift errors in theonboard sensors. The longitudinal vehicle velocity and lateral vehicle velocity are theessential information to be estimated among the numerous vehicle states for the activesafety systems. Therefore, the longitudinal vehicle velocity and lateral vehicle velocityhave important theoretical and practical significance.The objective of this paper is to present reliable and real-time nonlinear observermethod for vehicle velocity estimation for the longitudinal vehicle velocity and lateralSS904L steelvehicle velocity, which can not be measured directly in the active safety control problem.The experiments are carried out to validate the estimation results on the hardware-in-the-loop simulation platform, and then the hardware implementation scheme of nonlinearobserver is discussed.For the nonlinear dynamic characteristics shown in the vehicle running, A nonlinearfull-order observer with less measurement information is proposed for vehicle velocity es- timation based on the vehicle dynamic model and Uni-Tire model for longitudinal slipand lateral slip. The computed acceleration information using Uni-Tire model replace theonboard sensor information after identification the Uni-Tire model for longitudinal slipand lateral slip. The longitudinal velocity, lateral velocity and yaw rate of the vehicleare estimated by the observer using the information of vehicle states such as wheel ro-tational speed, the steering wheel angle and lateral acceleration which are measured byon-board sensors. The stability of the observer is analyzed using the theory of input-to-state stability(ISS), furthermore, the condition which the observer gain stratified is got.The nonlinear full-order observer has simple structure, good real time performance andcan be realized easily.For the complex structure, the state coupled with each other and the strong nonlinear-ity of vehicle systems, a nonlinear reduced-order observer method with less computationis presented for the longitudinal vehicle velocity and lateral vehicle velocity estimation,where the impact on vehicle dynamics is considered, which is caused by the changes ofCoG in the vehicle running. The yaw acceleration is chosen as the correction informationfor longitudinal vehicle velocity and lateral vehicle velocity estimation by analyzing thedynamic relationship between yaw rate and vehicle velocity. The condition of nonlinearobserver gain satisfied is obtained under the situation that the reduce-order observer isISS, and the condition is transform into LMIs using the Polytopic model description. Thesolving steps of reSS904L steelduce order observer is received by analyzing the relationship betweenobserver parameters, error decay rate and steady state error. The simulation study for es-timation results of reduced-order observer is carried out in the conventional condition andcritical condition, and the real-time experiments are carried out to validate the real-timeperformance.In order to avoid computational burden caused by complex tire model and improvethe calculation speed of the vehicle velocities observer, the tire model is received whichis built using MAP and the mechanism model description. The nonlinear cascaded ob-server method is presented for vehicle longitudinal velocity and lateral velocity estimationconsidering coriolis acceleration as disturbance of longitudinal vehicle velocity observer.we first used wheel rotational speed build longitudinal vehicle velocity observer, and thenthe estimated longitudinal vehicle velocity is used as input to estimated lateral vehiclevelocity. The longitudinal vehicle velocity observer and lateral vehicle velocity observercomposed of cascade structure. The ISS theory is used to analyse the stability of the ob-server and the condition which observer gain satisfied is got. Finally, in order to determinethe range of the observer gain and parameters, the performance function for nonlinearcascade observSS904L steeler is proposed, and the randomized algorithms is employed to discuss the range of the observer gain and parameters using Monte Carlo experiments.In order to validate the effectiveness of the nonlinear vehicle velocity observer method,the experiment must be carried out. The nonlinear vehicle velocity observer is validatedon the HiL platform which is builded based on xPC-Target real-time structure and vehi-cle dynamics software by operating the external steering wheel angle, acceleration pedaland brake pedal. Based on this, the FPGA/SOPC scheme is proposed for the hard-ware implementation of nonlinear veSS904L steelhicle velocity observer to satisfy the requirement ofminiaturization, real-time performance. The experimental validation is carried out for theeffectiveness and real-time performance base on dSPACE real time platform and FPGAexploited board and better experiment result is obtained.The formulation processes and the proof of mentioned approaches are presented indetail in this thesis. Moreover, in order to validate the efficiency of the proposed ap-proaches, we give simulation results for each approach, which is discussed from systemmodeling, vehicle velocity observer design, observer parameter choosing, simulation andexperiments. The simulation and experiments results indicate that estimation methodeffects with the proposed approaches are satisfactory.Deeper research work neSS904L steeleds to be done since some problems are still remain to besolved, for example, the roll motion and aerodynamic are omitted during the vehiclemodeling, so there exist some modeling errors, It requires improving the accuracy ofvehicle dynamics model constantly in future work. As the wheel speed can be measureddirectly by onboard sensors and it can be modeled by the drive torque and brake torque, wecan try to use the 7 degrees of freedom vehicle dynamics model to design the reduce-orderobserver. We can design some hardware accelerators to increase the computation speedin the research of FPGA/SOPC hardware implementation of nonlinear vehicle velocityobserver. In the hardware platform, only the hardware of driver manoeuvre is embeddedat present, how to embed more external sensor information which is useful for vehiclestates estimation, it is need to be further researchSS904L steel

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