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
A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate...A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate flight pairs were selected from all international flights arriving at or departing from China in one day according to the requirement of the proposed method.Aircraft performance database Base of Aircraft Data(BADA)was employed in the trajectory computation.By assuming different fuel-saving percentages for the following aircraft,pre-flight plan trajectories of formation flight were optimized.The fuel consumption optimization effect under the influence of different trajectory optimization parameters was also analyzed.The results showed that the higher the fuel savings percentage,the longer the flight distance of formation flight,but the smaller the number of formation combinations that can be realized,which is limited by the aircraft performance.The following aircraft flying along the approximate actual flight trajectory can be benefited as well,and the optimal fuel-saving efficiency is related to the expected fuelsaving efficiency of formation flight.展开更多
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This work was supported by the National Natural Science Foundation of China(No.U1633109)the Fundamental Research Funds for the Central Universities(No.3122016C010).
文摘A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate flight pairs were selected from all international flights arriving at or departing from China in one day according to the requirement of the proposed method.Aircraft performance database Base of Aircraft Data(BADA)was employed in the trajectory computation.By assuming different fuel-saving percentages for the following aircraft,pre-flight plan trajectories of formation flight were optimized.The fuel consumption optimization effect under the influence of different trajectory optimization parameters was also analyzed.The results showed that the higher the fuel savings percentage,the longer the flight distance of formation flight,but the smaller the number of formation combinations that can be realized,which is limited by the aircraft performance.The following aircraft flying along the approximate actual flight trajectory can be benefited as well,and the optimal fuel-saving efficiency is related to the expected fuelsaving efficiency of formation flight.
