Research On The Identification Of Mass For Heavy Vehicle And The Estimation Of Road Gradient

By the gradual increase in the volume of the heavy vehicle, there are more andmore studies which can improve the performance of the heavy vehicle. Improving theperformance of heavy vehicle is often achieved by developing the controls that areapplied to each implementation through the vehicle electronic control units. Get someimportant input parameters and use various algorithms to solve these control problems.For the characteristics that heavy vehicle mass changes range and heavy vehicle oftenwork on mountainous area, heavy vehicle mass and road grade are two importantparameters which influence vehicle performance. If the two amounts are used as inputparameters of control problems which can improve the performance of heavy vehicle,will be able to greatly develop the performance of vehicle power, economy andmanipulation stability and so on. Accurately real-time online getting the twoparameters lay a solid foundation for the studies of heavy vehicle performance controlproblem.This paper using the vehicle information provided by the heavy vehicles CAN bus,develops an economic-real-time identification of mass for heavy vehicle andestimation of road grade,and gets an accurate result in real time. The main contentsare divided into the following aspects:Firstly, by using modern control theory, analysis on the nature of slow-varyingvehicle mass and rapid-varying road grade have been taken. The result that the vehiclemass is a system parameter and the road grade is a state parameter is determined.Thus vehicle mass and road grade joint estimation model is designed.Secondly, based on the vehicle's longitudinal dynamics formula, the vehiclemass identification model and the road grade state estimation model are establishedrespectively by the use of recursive least squares with forgetting and Luenberger stateobserver state estimation method. Then the vehicle mass and road grade jointestimation model is built. By the use of MATLAB/Simulink toolbox, the programcode is written to the model of the vehicle mass and road grade joint estimation. Thirdly, taking the real vehicle coasting test, the vehicle air-drag coefficient,rolling resistance coefficient and the engine braking torque can be obtained. Measurethe gradient of the mountain road which is selected as test section. Besides, thevehicle acceleration test, the vehicle slope-climbing test and the mountain road testare carried out. Based on the above test data, the vehicle and road parameter databasecan be designed and be established to facilitate the subsequent verification andanalysis.Finally, the vehicle mass identification and the road grade state estimation modelcan be verified and analyzed using the above experimental data. The vehicleacceleration test data can be evidence to the feasibility and accuracy of the massidentification model. The vehicle slope-climbing test data can be evidence to thefeasibility and accuracy of the road grade state estimation model. By using themountain road test data, vehicle mass and road grade joint estimation model is furthervalidated to get the result that the model has good accuracy and stability.