It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently.However,it was rarely considered in intelligent vehicle motion planning.To improve rollover stability,a motion ...It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently.However,it was rarely considered in intelligent vehicle motion planning.To improve rollover stability,a motion planning strategy with autonomous anti rollover ability for an intelligent heavy truck is put forward in this paper.Considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability,a rollover dynamics model is built for the intelligent heavy truck.From the model,a novel rollover index is derived to evaluate vehicle rollover risk accurately,and a model predictive control algorithm is applicated to design the motion planning strategy for the intelligent heavy truck,which integrates the vehicle rollover stability,the artificial potential field for the obstacle avoidance,the path tracking and vehicle dynamics constrains.Then,the optimal path is obtained to meet the requirements that the intelligent heavy truck can avoid obstacles and drive stably without rollover.In addition,three typical scenarios are designed to numerically simulate the dynamic performance of the intelligent heavy truck.The results show that the proposed motion planning strategy can avoid collisions and improve vehicle rollover stability effectively even under the worst driving scenarios.展开更多
In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interi...In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interior noise of this vehicle are analyzed. According to the spectrum analysis of acquired noise signal, it is found out that the main frequencies of interior noise are less than 800Hz. Then the least squares lattice （LSL） algorithm is used as signal processing algorithm of the controller and a closed-loop control DSP system, based on TMS 320VC5416, is developed. The residual signal at driver＇s ear is used as feedback signal. Lastly, the developed ANC system is loaded into the heavy truck cab, and controlling the noise at driver＇ s ear for that truck at different driving speeds is attempted. The noise control test results indicate that the cab interior noise is reduced averagely by 0.9 dBA at different driving speeds.展开更多
Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototyp...Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver's seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.展开更多
This paper reports on the dynamic response of highway subgmde under moving heavy Wuck in cold regions. Numerical simulations are performed in two stages. In the first stage, the moving heavy truck vibration, induced b...This paper reports on the dynamic response of highway subgmde under moving heavy Wuck in cold regions. Numerical simulations are performed in two stages. In the first stage, the moving heavy truck vibration, induced by mad roughness, is calculated through a three-dimensional dynamic interaction model of heavy tmckavement-subgrade, and the lime-histories of nodal loads on the top of the base are calculated through this model. In the second stage, a two-dimensional dynamic finite element model of the bgrade-ground system is formulated, using the calculated nodal loads from the first stage as input. The dynamic resporkse of the subgrade is validated by field measurements, and the effects of mack type, axle loading, running speed, and road roughness on the vertical dynamic slress in the unfrozen period and the spring thawing period are analyzed and discussed.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51775269,U1964203,52072215)National Key R&D Program of China(Grant No.2020YFB1600303).
文摘It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently.However,it was rarely considered in intelligent vehicle motion planning.To improve rollover stability,a motion planning strategy with autonomous anti rollover ability for an intelligent heavy truck is put forward in this paper.Considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability,a rollover dynamics model is built for the intelligent heavy truck.From the model,a novel rollover index is derived to evaluate vehicle rollover risk accurately,and a model predictive control algorithm is applicated to design the motion planning strategy for the intelligent heavy truck,which integrates the vehicle rollover stability,the artificial potential field for the obstacle avoidance,the path tracking and vehicle dynamics constrains.Then,the optimal path is obtained to meet the requirements that the intelligent heavy truck can avoid obstacles and drive stably without rollover.In addition,three typical scenarios are designed to numerically simulate the dynamic performance of the intelligent heavy truck.The results show that the proposed motion planning strategy can avoid collisions and improve vehicle rollover stability effectively even under the worst driving scenarios.
基金Sponsored by the National Natural Science Foundation of China (50875022)Research Foundation of Beijing Institute of Technology(20070342012)
文摘In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interior noise of this vehicle are analyzed. According to the spectrum analysis of acquired noise signal, it is found out that the main frequencies of interior noise are less than 800Hz. Then the least squares lattice （LSL） algorithm is used as signal processing algorithm of the controller and a closed-loop control DSP system, based on TMS 320VC5416, is developed. The residual signal at driver＇s ear is used as feedback signal. Lastly, the developed ANC system is loaded into the heavy truck cab, and controlling the noise at driver＇ s ear for that truck at different driving speeds is attempted. The noise control test results indicate that the cab interior noise is reduced averagely by 0.9 dBA at different driving speeds.
基金Projects(51078087, 51178158) supported by the National Natural Science Foundation of ChinaProject(11040606Q39) supported by the Natural Science Foundation of Anhui Province, ChinaProjects(2012HGQC0015, 2011HGBZ0945) supported by the Fundamental Research Funds for the Central Universities
文摘Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver's seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.
基金supported by the National Key Basic Research Development Plan (No. 2012CB026104)the Natural Science Foundation of Heilongjiang Province (No. ZD201218)+1 种基金the China Postdoctoral Science Foundation Funded Project (No. 2012M520751)the Fundamental Research Funds for the Central University (No. HIT. NSRIF. 2014078)
文摘This paper reports on the dynamic response of highway subgmde under moving heavy Wuck in cold regions. Numerical simulations are performed in two stages. In the first stage, the moving heavy truck vibration, induced by mad roughness, is calculated through a three-dimensional dynamic interaction model of heavy tmckavement-subgrade, and the lime-histories of nodal loads on the top of the base are calculated through this model. In the second stage, a two-dimensional dynamic finite element model of the bgrade-ground system is formulated, using the calculated nodal loads from the first stage as input. The dynamic resporkse of the subgrade is validated by field measurements, and the effects of mack type, axle loading, running speed, and road roughness on the vertical dynamic slress in the unfrozen period and the spring thawing period are analyzed and discussed.
