The acceleration saltation of the traditional S-type acceleration model in the speed planning of the NURBS curve will result in the vibration and flexible impact of the machine tool.It will affect the surface quality ...The acceleration saltation of the traditional S-type acceleration model in the speed planning of the NURBS curve will result in the vibration and flexible impact of the machine tool.It will affect the surface quality of the components.The high speed smooth S-type acceleration and deceleration model deals with flexible impact,but the calculation is tedious.Aimed at the above problems,the traditional S-type acceleration and deceleration model is improved to make the jerk change linearly at a certain slope to reduce the flexible impact.Before the speed planning,it is needed to find the arc length and curvature of each point on the NURBS curve with a tiny step,and to determine the speed sensitivity point on the curve accordingly.According to the speed sensitive point,the NURBS curve is segmented.The attribute parameters of each section are determined by adaptive speed planning.Then,the speed planning can be performed on the NURBS curve according to the speed characteristics classification.The simulation results show that the algorithm can effectively reduce the flexible impact,improve the machining precision and efficiency,and simplify the classification of speed characteristics.展开更多
The development of intelligent connected technology has brought opportunities and challenges to the design of energy management strategies for hybrid electric vehicles.First,to achieve car-following in a connected env...The development of intelligent connected technology has brought opportunities and challenges to the design of energy management strategies for hybrid electric vehicles.First,to achieve car-following in a connected environment while reducing vehicle fuel consumption,a power split hybrid electric vehicle was used as the research object,and a mathematical model including engine,motor,generator,battery and vehicle longitudinal dynamics is established.Second,with the goal of vehicle energy saving,a layered optimization framework for hybrid electric vehicles in a networked environment is proposed.The speed planning problem is established in the upper-level controller,and the optimized speed of the vehicle is obtained and input to the lower-level controller.Furthermore,after the lower-level controller reaches the optimized speed,it distributes the torque among the energy sources of the hybrid electric vehicle based on the equivalent consumption minimum strategy.The simulation results show that the proposed layered control framework can achieve good car-following performance and obtain good fuel economy.展开更多
In this study, vehicle queuing was investigated at intersections to propose an eco-driving strategy to improve vehicle energy consumption and traffic efficiency in urban traffic environments. The proposed design appro...In this study, vehicle queuing was investigated at intersections to propose an eco-driving strategy to improve vehicle energy consumption and traffic efficiency in urban traffic environments. The proposed design approach can be applied to electric vehicles, and the control framework is categorized into two layers. In the upper layer, the speed of the host vehicle is planned offline, and in the lower layer, the required control variable acceleration is determined. First, the energy optimization problem of electric vehicles passing through an intersection was constructed, and the planning vehicle speed was obtained based on the genetic algorithm(GA). Next, the speed tracking controller and distance tracking controller were designed using sliding mode control(SMC) to ensure that the vehicle can track the planning speed with safe vehicle spacing. Finally, combined with specific cases, the energy-saving effect of the proposed method in the single-vehicle scenario, and the presence of manual driving vehicles in front-and multi-vehicle driving scenarios were studied. The results revealed that the GA-based single-vehicle speed planning method reduced energy consumption by up to 16% compared with the rule-based speed planning method. Furthermore,compared with the intelligent driver model(IDM) and adaptive cruise control(ACC) methods, the GA fleet speed planning method based on V2X communication can reduce average fleet energy consumption by 26% and 24%, respectively, and improve intersection traffic efficiency. The results of the sensitivity analysis of factors affecting planned speed revealed that vehicles passing through intersections at a steady speed exhibited superior economic performance. Finally, hardware-in-the-loop(HIL)testing was performed to verify the effectiveness of the controller under real-time conditions.展开更多
With the help of traffic information of the connected environment,an energy management strategy(EMS)is proposed based on preceding vehicle speed prediction,host vehicle speed planning,and dynamic programming(DP)with P...With the help of traffic information of the connected environment,an energy management strategy(EMS)is proposed based on preceding vehicle speed prediction,host vehicle speed planning,and dynamic programming(DP)with PI correction to improve the fuel economy of connected hybrid electric vehicles(HEVs).A conditional linear Gaussian(CLG)model for estimating the future speed of the preceding vehicle is established and trained by utilizing historical data.Based on the predicted information of the preceding vehicle and traffic light status,the speed curve of the host vehicle can ensure that the vehicle follows safety and complies with traffic rules simultaneously as planned.The real-time power allocation is composed of offline optimization results of DP and the real-time PI correction items according to the actual operation of the engine.The effectiveness of the control strategy is verified by the simulation system of HEVs in the interconnected environment established by E-COSM 2021 on the MATLAB/Simulink and CarMaker platforms.展开更多
A novel five-axis real-time interpolation algorithm for 3[PP]S-XY hybrid mechanism is proposed in this paper. In the algorithm, the five-axis tool path for controlling this hybrid mechanism is separated into two sub-p...A novel five-axis real-time interpolation algorithm for 3[PP]S-XY hybrid mechanism is proposed in this paper. In the algorithm, the five-axis tool path for controlling this hybrid mechanism is separated into two sub-paths. One sub-path describes the movement of 3[PP]S parallel kinematic mechanism module, and the other one describes the movement of XY platform. A pair of cubic Bezier curves is employed to smooth the corners in those two sub-paths. Based on the homogenous Jacobian matrix of 3[PP]S mechanism, a relationship between the position errors of every driving joint in hybrid mechanism and the position deviation of the tool tip center point at the moving platform is established. This relationship is used to estimate the approximation error for the corners smoothing according to the accuracy requirement of tool tip center in interpolation. Due to the high computational efficiency of this corner smoothing method, it is integrated into the look-ahead module of computer numerical control(CNC) system to perform online tool path smoothing. By performing the speed planning based on a floating window scheme, a jerk limited S-shape speed profile can be generated efficiently. On this basis, a realtime look-ahead scheme, which is comprised of path-smoothing and feedrate scheduling, is developed to acquire a speed profile with smooth acceleration. A monotonic cubic spline is employed for synchronization between those two smoothed sub-paths in tool path interpolation. This interpolation algorithm has been integrated into our own developed CNC system to control a 3PRS-XY experimental instrument(P, R and S standing for prismatic,revolute and spherical, respectively). A club shaped trajectory is adopted to verify the smoothness and efficiency of the five-axis interpolator for hybrid mechanism control.展开更多
Predictive cruise control(PCC)is an intelligence-assisted control technology that can significantly improve the overall performance of a vehicle by using road and traffic information in advance.With the continuous dev...Predictive cruise control(PCC)is an intelligence-assisted control technology that can significantly improve the overall performance of a vehicle by using road and traffic information in advance.With the continuous development of cloud control platforms(CCPs)and telematics boxes(T-boxes),cloud-based predictive cruise control(CPCC)systems are considered an effective solution to the problems of map update difficulties and insufficient computing power on the vehicle side.In this study,a vehicle-cloud hierarchical control architecture for PCC is designed based on a CCP and T-box.This architecture utilizes waypoint structures for hierarchical and dynamic cooperative inter-triggering,enabling rolling optimization of the system and commending parsing at the vehicle end.This approach significantly improves the anti-interference capability and resolution efficiency of the system.On the CCP side,a predictive fuel-saving speed-planning(PFSP)algorithm that considers the throttle input,speed variations,and time efficiency based on the waypoint structure is proposed.It features a forward optimization search without requiring weight adjustments,demonstrating robust applicability to various road conditions and vehicles equiped with constant cruise(CC)system.On the vehicle-side T-box,based on the reference control sequence with the global navigation satellite system position,the recommended speed is analyzed and controlled using the acute angle principle.Through analyzing the differences of the PFSP algorithm compared to dynamic programming(DP)and Model predictive control(MPC)algorithms under uphill and downhill conditions,the results show that the PFSP achieves good energy-saving performance compared to CC without exhibiting significant speed fluctuations,demonstrating strong adaptability to the CC system.Finally,by building an experimental platform and running field tests over a total of 2000 km,we verified the effectiveness and stability of the CPCC system and proved the fuel-saving performance of the proposed PFSP algorithm.The results showed that the CPCC system equipped with the PFSP algorithm achieved an average fuel-saving rate of 2.05%-4.39%compared to CC.展开更多
The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by o...The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT.A state-space model is constructed by connecting the vehicle dynamics and battery state of charge,and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption.The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle.A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic,where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved.Simulation results show that for the single-vehicle controller,the battery degradation and energy consumption are,respectively,reduced by up to 25.7%and 3.2%compared with the cruise control strategy.Based on the non-cooperative controller,the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further,respectively,reduced by 2%–5%and 9%–10%compared with those of the single-vehicle controller.展开更多
基金the National Key Basic Research Program of China(973 Program)(No.2014CB046501)。
文摘The acceleration saltation of the traditional S-type acceleration model in the speed planning of the NURBS curve will result in the vibration and flexible impact of the machine tool.It will affect the surface quality of the components.The high speed smooth S-type acceleration and deceleration model deals with flexible impact,but the calculation is tedious.Aimed at the above problems,the traditional S-type acceleration and deceleration model is improved to make the jerk change linearly at a certain slope to reduce the flexible impact.Before the speed planning,it is needed to find the arc length and curvature of each point on the NURBS curve with a tiny step,and to determine the speed sensitivity point on the curve accordingly.According to the speed sensitive point,the NURBS curve is segmented.The attribute parameters of each section are determined by adaptive speed planning.Then,the speed planning can be performed on the NURBS curve according to the speed characteristics classification.The simulation results show that the algorithm can effectively reduce the flexible impact,improve the machining precision and efficiency,and simplify the classification of speed characteristics.
基金supported by the National Natural Science Foundation of China(Grant No.62111530196)and the Technology Development Program of Jilin Province(Grant No.20200501010G X).
文摘The development of intelligent connected technology has brought opportunities and challenges to the design of energy management strategies for hybrid electric vehicles.First,to achieve car-following in a connected environment while reducing vehicle fuel consumption,a power split hybrid electric vehicle was used as the research object,and a mathematical model including engine,motor,generator,battery and vehicle longitudinal dynamics is established.Second,with the goal of vehicle energy saving,a layered optimization framework for hybrid electric vehicles in a networked environment is proposed.The speed planning problem is established in the upper-level controller,and the optimized speed of the vehicle is obtained and input to the lower-level controller.Furthermore,after the lower-level controller reaches the optimized speed,it distributes the torque among the energy sources of the hybrid electric vehicle based on the equivalent consumption minimum strategy.The simulation results show that the proposed layered control framework can achieve good car-following performance and obtain good fuel economy.
基金supported by the National Natural Science Foundation of China (Grant No.52272367)。
文摘In this study, vehicle queuing was investigated at intersections to propose an eco-driving strategy to improve vehicle energy consumption and traffic efficiency in urban traffic environments. The proposed design approach can be applied to electric vehicles, and the control framework is categorized into two layers. In the upper layer, the speed of the host vehicle is planned offline, and in the lower layer, the required control variable acceleration is determined. First, the energy optimization problem of electric vehicles passing through an intersection was constructed, and the planning vehicle speed was obtained based on the genetic algorithm(GA). Next, the speed tracking controller and distance tracking controller were designed using sliding mode control(SMC) to ensure that the vehicle can track the planning speed with safe vehicle spacing. Finally, combined with specific cases, the energy-saving effect of the proposed method in the single-vehicle scenario, and the presence of manual driving vehicles in front-and multi-vehicle driving scenarios were studied. The results revealed that the GA-based single-vehicle speed planning method reduced energy consumption by up to 16% compared with the rule-based speed planning method. Furthermore,compared with the intelligent driver model(IDM) and adaptive cruise control(ACC) methods, the GA fleet speed planning method based on V2X communication can reduce average fleet energy consumption by 26% and 24%, respectively, and improve intersection traffic efficiency. The results of the sensitivity analysis of factors affecting planned speed revealed that vehicles passing through intersections at a steady speed exhibited superior economic performance. Finally, hardware-in-the-loop(HIL)testing was performed to verify the effectiveness of the controller under real-time conditions.
基金supported by the National Natural Science Foundation of China(No.61973265)the Natural Science Foundation of Hebei Province(No.E2021203079)the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Hebei Province(No.C20210323).
文摘With the help of traffic information of the connected environment,an energy management strategy(EMS)is proposed based on preceding vehicle speed prediction,host vehicle speed planning,and dynamic programming(DP)with PI correction to improve the fuel economy of connected hybrid electric vehicles(HEVs).A conditional linear Gaussian(CLG)model for estimating the future speed of the preceding vehicle is established and trained by utilizing historical data.Based on the predicted information of the preceding vehicle and traffic light status,the speed curve of the host vehicle can ensure that the vehicle follows safety and complies with traffic rules simultaneously as planned.The real-time power allocation is composed of offline optimization results of DP and the real-time PI correction items according to the actual operation of the engine.The effectiveness of the control strategy is verified by the simulation system of HEVs in the interconnected environment established by E-COSM 2021 on the MATLAB/Simulink and CarMaker platforms.
基金the CNC Equipment Development for Key Structure Integrated Manufacturing by LAW(No.ZB-ZBYZ-03-11-2190)the Shanghai Aerospace Fund(No.HTJ10-20)
文摘A novel five-axis real-time interpolation algorithm for 3[PP]S-XY hybrid mechanism is proposed in this paper. In the algorithm, the five-axis tool path for controlling this hybrid mechanism is separated into two sub-paths. One sub-path describes the movement of 3[PP]S parallel kinematic mechanism module, and the other one describes the movement of XY platform. A pair of cubic Bezier curves is employed to smooth the corners in those two sub-paths. Based on the homogenous Jacobian matrix of 3[PP]S mechanism, a relationship between the position errors of every driving joint in hybrid mechanism and the position deviation of the tool tip center point at the moving platform is established. This relationship is used to estimate the approximation error for the corners smoothing according to the accuracy requirement of tool tip center in interpolation. Due to the high computational efficiency of this corner smoothing method, it is integrated into the look-ahead module of computer numerical control(CNC) system to perform online tool path smoothing. By performing the speed planning based on a floating window scheme, a jerk limited S-shape speed profile can be generated efficiently. On this basis, a realtime look-ahead scheme, which is comprised of path-smoothing and feedrate scheduling, is developed to acquire a speed profile with smooth acceleration. A monotonic cubic spline is employed for synchronization between those two smoothed sub-paths in tool path interpolation. This interpolation algorithm has been integrated into our own developed CNC system to control a 3PRS-XY experimental instrument(P, R and S standing for prismatic,revolute and spherical, respectively). A club shaped trajectory is adopted to verify the smoothness and efficiency of the five-axis interpolator for hybrid mechanism control.
基金Supported by National Key Research and Development Program of China(Grant No.2021YFB2501000).
文摘Predictive cruise control(PCC)is an intelligence-assisted control technology that can significantly improve the overall performance of a vehicle by using road and traffic information in advance.With the continuous development of cloud control platforms(CCPs)and telematics boxes(T-boxes),cloud-based predictive cruise control(CPCC)systems are considered an effective solution to the problems of map update difficulties and insufficient computing power on the vehicle side.In this study,a vehicle-cloud hierarchical control architecture for PCC is designed based on a CCP and T-box.This architecture utilizes waypoint structures for hierarchical and dynamic cooperative inter-triggering,enabling rolling optimization of the system and commending parsing at the vehicle end.This approach significantly improves the anti-interference capability and resolution efficiency of the system.On the CCP side,a predictive fuel-saving speed-planning(PFSP)algorithm that considers the throttle input,speed variations,and time efficiency based on the waypoint structure is proposed.It features a forward optimization search without requiring weight adjustments,demonstrating robust applicability to various road conditions and vehicles equiped with constant cruise(CC)system.On the vehicle-side T-box,based on the reference control sequence with the global navigation satellite system position,the recommended speed is analyzed and controlled using the acute angle principle.Through analyzing the differences of the PFSP algorithm compared to dynamic programming(DP)and Model predictive control(MPC)algorithms under uphill and downhill conditions,the results show that the PFSP achieves good energy-saving performance compared to CC without exhibiting significant speed fluctuations,demonstrating strong adaptability to the CC system.Finally,by building an experimental platform and running field tests over a total of 2000 km,we verified the effectiveness and stability of the CPCC system and proved the fuel-saving performance of the proposed PFSP algorithm.The results showed that the CPCC system equipped with the PFSP algorithm achieved an average fuel-saving rate of 2.05%-4.39%compared to CC.
基金funded by the Research Start-Up Funding of Chongqing University(Grant No.02090011044160)the National Natural Science Foundation of China(Grant No.51907136)。
文摘The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT.A state-space model is constructed by connecting the vehicle dynamics and battery state of charge,and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption.The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle.A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic,where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved.Simulation results show that for the single-vehicle controller,the battery degradation and energy consumption are,respectively,reduced by up to 25.7%and 3.2%compared with the cruise control strategy.Based on the non-cooperative controller,the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further,respectively,reduced by 2%–5%and 9%–10%compared with those of the single-vehicle controller.
