Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of th...Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.展开更多
The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the ...The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.展开更多
Uncertain environment on multi-lane highway,e.g.,the stochastic lane-change maneuver of surrounding vehicles,is a big challenge for achieving safe automated highway driving.To improve the driving safety,a heuristic re...Uncertain environment on multi-lane highway,e.g.,the stochastic lane-change maneuver of surrounding vehicles,is a big challenge for achieving safe automated highway driving.To improve the driving safety,a heuristic reinforcement learning decision-making framework with integrated risk assessment is proposed.First,the framework includes a long short-term memory model to predict the trajectory of surrounding vehicles and a future integrated risk assessment model to estimate the possible driving risk.Second,a heuristic decaying state entropy deep reinforcement learning algorithm is introduced to address the exploration and exploitation dilemma of reinforcement learning.Finally,the framework also includes a rule-based vehicle decision model for interaction decision problems with surrounding vehicles.The proposed framework is validated in both low-density and high-density traffic scenarios.The results show that the traffic efficiency and vehicle safety are both improved compared to the common dueling double deep Q-Network method and rule-based method.展开更多
Uniform crushed straw throwing and seed-sowing machines can achieve the processes of straw chopping,straw transport,sowing,fertilization,and straw mulching at the same time,which is widely used in many areas of China....Uniform crushed straw throwing and seed-sowing machines can achieve the processes of straw chopping,straw transport,sowing,fertilization,and straw mulching at the same time,which is widely used in many areas of China.Conveying device is one of the important components used to convey,elevate and throw straw.However,the problems of high power consumption and congestion affect the promotion of the machine.Therefore,the conveying device of uniform crushed straw throwing and seed-sowing machine was analyzed in order to determine its device operation mechanism.Kinematic and dynamic analyses of particles of crushed rice straw during lifting and dispersion are used to develop a flexible-body model of rod-shaped and agglomerate-shaped crushed straw and a coupling model including the mechanical structure of the device.By integrating computational fluid dynamics and the discrete element method,the gas-solid coupling theory in numerical simulations and motion analysis of crushed straw particles is used to determine how the flow field and motion characteristics affect the conveying performance.Besides,regression equations to describe the relationships between the factors and each assessment index were established by using the regression analysis and response surface analysis with the software Design-Expert.The effect of throwing blade speed X_(1),conveying volume of crushed straw X_(2),and pipeline diameter X_(3) on the throwing speed of crushed straw Y_(1) and specific power consumption Y2 were investigated.The highest throwing speed of crushed straw and lowest specific power consumption are the optimization goal.The results of optimization showed that the predict the best optimal parameters were 2000 r/min throwing blade rotational speed,1.4 kg/s conveying volume,and 220 mm pipeline diameter,the planter achieved a throwing speed of 12.2 m/s and specific power consumption of 9179 m^(2)/s^(2).And then a field test verification was conducted.The planter achieved a throwing speed 12.4 m/s and specific power consumption 9070 m^(2)/s^(2) while selecting the best optimal parameters.Thus,the optimal parameters can provide a high-performance operation and satisfy the actual operation requirements The results provide a theoretical basis and data support for seeding technology innovation and equipment optimization to ensure uniform crushed straw throwing in dense rice stubble fields.展开更多
基金Supported by National Natural Science Foundation of China (Grant No.11672127)Innovative Science and Technology Platform Project of Cooperation between Yangzhou City and Yangzhou University of China (Grant No.YZ2020266)+3 种基金Advance Research Special Technology Project of Army Equipment of China (Grant No.AGA19001)Innovation Fund Project of China Aerospace 1st Academy (Grant No.CHC20001)Fundamental Research Funds for the Central Universities of China (Grant No.NP2022408)Jiangsu Provincial Postgraduate Research&Practice Innovation Program of China (Grant No.SJCX23_1903)。
文摘Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.
基金Supported by National Natural Science Foundation of China(Grant Nos.51575103,11672127,U1664258)Fundamental Research Funds for the Central Universities of China(Grant No.NT2018002)+1 种基金China Postdoctoral Science Foundation(Grant Nos.2017T100365,2016M601799)the Fundation of Graduate Innovation Center in NUAA(Grant No.k j20180207)
文摘The current research of autonomous vehicle motion control mainly focuses on trajectory tracking and velocity tracking. However, numerous studies deal with trajectory tracking and velocity tracking separately, and the yaw stability is seldom considered during trajectory tracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectory tracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectory tracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectory tracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed control strategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle.
基金support of the National Engineering Laboratory of High Mobility antiriot vehicle technology under Grant B20210017the National Natural Science Foundation of China under Grant 11672127+2 种基金the Fundamental Research Funds for the Central Universities under Grant NP2022408the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX21_0188the Chinese Scholar Council under Grant 202106830118.
文摘Uncertain environment on multi-lane highway,e.g.,the stochastic lane-change maneuver of surrounding vehicles,is a big challenge for achieving safe automated highway driving.To improve the driving safety,a heuristic reinforcement learning decision-making framework with integrated risk assessment is proposed.First,the framework includes a long short-term memory model to predict the trajectory of surrounding vehicles and a future integrated risk assessment model to estimate the possible driving risk.Second,a heuristic decaying state entropy deep reinforcement learning algorithm is introduced to address the exploration and exploitation dilemma of reinforcement learning.Finally,the framework also includes a rule-based vehicle decision model for interaction decision problems with surrounding vehicles.The proposed framework is validated in both low-density and high-density traffic scenarios.The results show that the traffic efficiency and vehicle safety are both improved compared to the common dueling double deep Q-Network method and rule-based method.
基金supported by the earmarked fund for CARS-13Natural Science Foundation of Jiangsu Province (Grant No.BK20221187).
文摘Uniform crushed straw throwing and seed-sowing machines can achieve the processes of straw chopping,straw transport,sowing,fertilization,and straw mulching at the same time,which is widely used in many areas of China.Conveying device is one of the important components used to convey,elevate and throw straw.However,the problems of high power consumption and congestion affect the promotion of the machine.Therefore,the conveying device of uniform crushed straw throwing and seed-sowing machine was analyzed in order to determine its device operation mechanism.Kinematic and dynamic analyses of particles of crushed rice straw during lifting and dispersion are used to develop a flexible-body model of rod-shaped and agglomerate-shaped crushed straw and a coupling model including the mechanical structure of the device.By integrating computational fluid dynamics and the discrete element method,the gas-solid coupling theory in numerical simulations and motion analysis of crushed straw particles is used to determine how the flow field and motion characteristics affect the conveying performance.Besides,regression equations to describe the relationships between the factors and each assessment index were established by using the regression analysis and response surface analysis with the software Design-Expert.The effect of throwing blade speed X_(1),conveying volume of crushed straw X_(2),and pipeline diameter X_(3) on the throwing speed of crushed straw Y_(1) and specific power consumption Y2 were investigated.The highest throwing speed of crushed straw and lowest specific power consumption are the optimization goal.The results of optimization showed that the predict the best optimal parameters were 2000 r/min throwing blade rotational speed,1.4 kg/s conveying volume,and 220 mm pipeline diameter,the planter achieved a throwing speed of 12.2 m/s and specific power consumption of 9179 m^(2)/s^(2).And then a field test verification was conducted.The planter achieved a throwing speed 12.4 m/s and specific power consumption 9070 m^(2)/s^(2) while selecting the best optimal parameters.Thus,the optimal parameters can provide a high-performance operation and satisfy the actual operation requirements The results provide a theoretical basis and data support for seeding technology innovation and equipment optimization to ensure uniform crushed straw throwing in dense rice stubble fields.
