Traditional automated guided vehicle(AGV)primarily relies on scheduling systems to manage warehouse locations and execute picking or placing tasks on fixedheight pallets.However,these conventional systems are illsuite...Traditional automated guided vehicle(AGV)primarily relies on scheduling systems to manage warehouse locations and execute picking or placing tasks on fixedheight pallets.However,these conventional systems are illsuited for scenarios involving variable heights,such as vehicle loading and unloading or the complex stacking of soft packages.To address the challenges of AGV endeffector operations in nonfixed height scenarios,this paper proposes an innovative solution leveraging lowcost depth camera sensors.By capturing image and depth data,and integrating deep learning,image processing,and spatial attitude calculation techniques,the method accurately determines the position of the endeffector center point relative to the upper plane of the fork.The approach effectively resolves a key issue in AGV operations within intelligent logistics scenarios that lack fixed heights.The proposed algorithm is deployed on a domestic embedded,lowcost ARM chip controller,and extensive experiments are conducted on a real AGV equipped with multiple stacked vehicles and nonstandard vehicles.The experimental results demonstrate that for diverse vehicles with different heights,the measurement error can be maintained within±10 mm,satisfying the requirements for highprecision measurement.The height measurement method developed in the paper not only enhances the AGV’s adaptability in nonfixed height scenarios but also significantly broadens its application potential across various industries.展开更多
The implementation of the standard is expected to help electric vehicle battery swap stations to adapt to diversified needs and vehicle models,promoting the industry’s orderly and healthy development.
The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 n...The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 new models on display-85 percent of them new energy vehicles-this year’s show spotlighted how the global auto industry is pivoting rapidly towards an era of software-defined and AI-powered mobility.展开更多
The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on e...The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.展开更多
This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining ...This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining the internal and external factors of the formation about the Chinese EV industry business ecosystem,such as industrial structure transformation,technology transfer,government policies,and corporate competition,with the platform theory,I analyze the growth strategies and competitiveness of Chinese companies,particularly BYD Co.,Ltd.(BYD),which has risen to the top of the world in EV completed vehicles,and Contemporary Amperex Technology Co.,Ltd.(CATL),which has risen to the top of the world in electric vehicle batteries(EVB)2.BYD and CATL have gained competitive advantages by utilizing the distinctive management resources,which have accumulated over the years to build platforms for EVBs and EVs in response to changes in the external environment,and have actively developed their platform strategies.展开更多
Flapping-Wing Air Vehicles(FWAVs)have been developed to pursue the efficient,agile,and quiet flight of flying animals.However,unlike lightweight FWAVs capable of vertical takeoff,relatively heavy FWAVs face challenges...Flapping-Wing Air Vehicles(FWAVs)have been developed to pursue the efficient,agile,and quiet flight of flying animals.However,unlike lightweight FWAVs capable of vertical takeoff,relatively heavy FWAVs face challenges in self-takeoff,which refers to taking off without both external device and energy input.In this study,a cliff-drop method is implemented for an independent takeoff of a heavy FWAV,relying solely on gravity.In the takeoff process using the cliff-drop method,the FWAV moves on the ground to a cliff edge using a wheel-driving motor and then descends from the cliff to achieve the necessary speed for flight.To demonstrate the cliff-drop method,the KAIST Robotic Hawk(KRoHawk)with a mass of 740 g and a wingspan of 120 cm is developed.The takeoff tests demonstrate that the KRoHawk,significantly heavier than the vertical-takeoff capable FWAVs,can successfully take off using the gravity-assisted takeoff method.The scalability of cliff-drop method is analyzed through simulations.When drop constraints are absent,the wheel-driving motor mass fraction for cliff-drop method remains negligible even as the vehicle's weight increases.When drop constraints are set to 4 m,FWAVs heavier than KRoHawk,weighing up to 4.4 kg,can perform the cliff-drop takeoffs with a wheel-driving motor mass fraction of less than 8%.展开更多
The pressure wave generated by an urban-rail vehicle when passing through a tunnel affects the comfort of passengersand may even cause damage to the train and related tunnel structures.Therefore,controlling the trains...The pressure wave generated by an urban-rail vehicle when passing through a tunnel affects the comfort of passengersand may even cause damage to the train and related tunnel structures.Therefore,controlling the trainspeed in the tunnel is extremely important.In this study,this problem is investigated numerically in the frameworkof the standard k-εtwo-equation turbulence model.In particular,an eight-car urban rail train passingthrough a tunnel at different speeds(140,160,180 and 200 km/h)is considered.The results show that the maximumaerodynamic drag of the head and tail cars is most affected by the running speed.The pressure at selectedmeasuring points on the windward side of the head car is very high,and the negative pressure at the side windowof the driver’s cab of the tail car is also very large.From the head car to the tail car,the pressure at the same heightgradually decreases.The positive pressure peak at the head car and the negative pressure peak at the tail car aregreatly affected by the speed.展开更多
Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated ...Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use.First,considering the range loss characteristics,dynamic time-sharing tariff mechanism,and user incentive policy in the lowtemperature environment of northern winter,a differentiated charging model is constructed for four types of vehicles:family cars,official cars,buses,and cabs.Then,we innovatively introduce the urgency parameter of charging demand for multiple types of vehicles and dynamically divide the emergency and non-emergency charging modes according to the difference between the regular charging capacity and the user’s minimum power demand.When the conventional charging capacity is less than the minimum power demand of the vehicle within the specified time,it is the emergency vehicle demand,and this type of vehicle is immediately charged in fast charging mode after connecting to the grid.On the contrary,it is a non-emergency demand,and the vehicle is connected to the grid to choose the appropriate time to charge in conventional charging mode.Finally,by optimizing the objective function to minimize the peakto-valley difference between the grid and the vehicle owner’s charging cost,and designing the charging continuity constraints to avoid battery damage,it ensures that the vehicle is efficiently dispatched under the premise of meeting the minimum power demand.Simulation results show that the proposed charging strategy can reduce the charging cost of vehicle owners by 26.33%,reduce the peak-to-valley difference rate of the grid by 29.8%,and significantly alleviate the congestion problem during peak load hours,compared with the disordered charging mode,while ensuring that the electric vehicles are not overcharged and meet the electricity demand of vehicle owners.This paper solves the problems of the existing research on the singularity of vehicle models and the lack of environmental adaptability and provides both economic and practical solutions for the cooperative optimization of electric vehicles and power grids in multiple scenarios.展开更多
The design of wide-range high-efficiency aerodynamic configurations is one of the most important key technologies in the research of near-space hypersonic vehicles.A double-sided intake configuration with different in...The design of wide-range high-efficiency aerodynamic configurations is one of the most important key technologies in the research of near-space hypersonic vehicles.A double-sided intake configuration with different inlets on the upper and lower surfaces is proposed to adapt to widerange flight.Firstly,the double-sided intake configuration’s design method and flight profile are delineated.Secondly,Computational Fluid Dynamics(CFD)numerical simulation based on multi-Graphics Processing Unit(GPU)parallel computing is adopted to evaluate the vehicle’s performance comprehensively,aiming to verify the feasibility of the proposed scheme.This evaluation encompasses a wide-range basic aerodynamic characteristics,inlet performance,and heat flux at critical locations.The results show that the inlets of the designed integration configuration can start up across Mach number 3.5 to 8.The vehicle possesses multi-point cruising capability by flipping the fuselage.Simultaneously,a 180°rotation of the fuselage can significantly decrease the heat accumulation on the lower surface of the vehicle,particularly at the inlet lip,further decreasing the temperature gradient across the vehicle structure.This study has some engineering value for the aerodynamic configuration design of wide-range vehicles.However,further study reveals that the flow phenomena at the intersection of two inlets are complex,posing potential adverse impacts on propulsion efficiency.Therefore,it is imperative to conduct additional research to delve into this matter comprehensively.展开更多
In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide ef...In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide efficient and privacypreserving collaborative learning.However,in Io V environment,federated learning faces the challenges introduced by high mobility of vehicles and nonIndependently Identically Distribution(non-IID)of data.High mobility causes FL clients quit and the communication offline.The non-IID data leads to slow and unstable convergence of global model and single global model's weak adaptability to clients with different localization characteristics.Accordingly,this paper proposes a personalized aggregation strategy for hierarchical Federated Learning in Io V environment,including Fed SA(Special Asynchronous Federated Learning with Self-adaptive Aggregation)for low-level FL between a Road Side Unit(RSU)and the vehicles within its coverage,and Fed Att(Federated Learning with Attention Mechanism)for high-level FL between a cloud server and multiple RSUs.Agents self-adaptively obtain model aggregation weight based on Advantage Actor-Critic(A2C)algorithm.Experiments show the proposed strategy encourages vehicles to participate in global aggregation,and outperforms existing methods in training performance.展开更多
Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessi...Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessive suppression of real targets,which ultimately cause accuracy degradation.At the same time,to facilitate the subsequent positioning of vehicles in the factory,this paper proposes an improved YOLOv8 algorithm.Firstly,the RFCAConv module is combined to improve the original YOLOv8 backbone.Pay attention to the different features in the receptive field,and give priority to the spatial features of the receptive field to capture more vehicle feature information and solve the problem that the vehicle is partially occluded and difficult to detect.Secondly,the SFE module is added to the neck of v8,which improves the saliency of the target in the reasoning process and reduces the influence of background interference on vehicle detection.Finally,the head of the RT-DETR algorithm is used to replace the head in the original YOLOv8 algorithm,which avoids the excessive suppression of the real target while combining the context information.The experimental results show that compared with the original YOLOv8 algorithm,the detection accuracy of the improved YOLOv8 algorithm is improved by 4.6%on the self-made smart factory data set,and the detection speed also meets the real-time requirements of smart factory vehicle detection and subsequent vehicle positioning.展开更多
Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-ma...Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict.This paper introduces a novel multi-mode evasion assistance control(MEAC)method for intelligent distributed-drive electric vehicles.A reference safety area is established considering the vehicle safety and stability requirements,which serves as a guiding principle for evading obstacles.The proposed method includes two control modes:Shared-EAC(S-EAC)and Emergency-EAC(E-EAC).In S-EAC,an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance.The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance.Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions.In addition,it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.展开更多
As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational ...As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.展开更多
With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total co...With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total costs of fuel cell systems are still too high,thus limiting the further development of fuel cell hybrid electric vehicles.This paper presents an energy management strategy(EMS)based on deep reinforcement learning for the energy management of fuel cell hybrid electric vehicles.The energy management model of a fuel cell hybrid electric bus and its main components are established.Considering the power response characteristics of the fuel cell system,the power change rate of the fuel cell system is reasonably limited and introduced as action variables into the network of Double Deep Q-Learning(DDQL),and a novel DDQL-based EMS is developed for the fuel cell hybrid electric bus.Subsequently,a comparative test is conducted with the DP-based and the Rule-based EMS to analyze the performance of the DDQL-based EMS.The results indicate that the proposed EMS achieves good fuel economy performance,with an improvement of 15.4%compared to the Rule-based EMS under the training scenarios.In terms of generalization performance,the proposed EMS also achieves good fuel economy performance,which improves by 13.3%compared to the Rule-based energy management strategy under the testing scenario.展开更多
Aerodynamic and dynamic interference from trains is a key issue of concern for the safety of road vehicles travelling on single-level rail-cum road bridges.Based on the wind-road vehicle-train-bridge(WRTB)coupled vibr...Aerodynamic and dynamic interference from trains is a key issue of concern for the safety of road vehicles travelling on single-level rail-cum road bridges.Based on the wind-road vehicle-train-bridge(WRTB)coupled vibration system developed herein,this study examines the dynamic characteristics when road vehicles meet trains in this situation.The influence of load combination,vehicle type and vehicle location is analyzed.A method to obtain the aerodynamic load of road vehicles encountering the train at an arbitrary wind speed is proposed.The results show that due to the windproof facilities and the large line distance between the railway and highway,the aerodynamic and dynamic influence of trains on road vehicles is slight,and the vibration of road vehicles depends on the road roughness.Among the road vehicles discussed,the bus is the easiest to rollover,and the truck-trailer is the easiest to sideslip.Compared with the aerodynamic impact of trains,the crosswind has a more significant influence on road vehicles.The first peak/valley value of aerodynamic loads determines the maximum dynamic response,and the quick method is optimized based on this conclusion.Test cases show that the optimized method can produce conservative results and can be used for relevant research or engineering applications.展开更多
Flapping-Wing Micro Air Vehicles(FMAVs)are compact and agile,capable of accessing narrow spaces that conventional vehicles struggle to reach,such as ruins,caves,or the interiors of complex structures,making them ideal...Flapping-Wing Micro Air Vehicles(FMAVs)are compact and agile,capable of accessing narrow spaces that conventional vehicles struggle to reach,such as ruins,caves,or the interiors of complex structures,making them ideal tools for reconnaissance and rescue missions.1 However,the operation of FMAVs relies on coordinating multiple forces with different scaling effects,posing challenges to miniaturization design.展开更多
Railway bridges are continuously loaded by railway trains;therefore, it is important to understand the nonlinear seismic response of the Vehicle-Bridge Interaction (VBI) system under strong earthquakes. For this purpo...Railway bridges are continuously loaded by railway trains;therefore, it is important to understand the nonlinear seismic response of the Vehicle-Bridge Interaction (VBI) system under strong earthquakes. For this purpose, the nonlinear behavior of the pier was introduced into the in-house VBI solvers. The nonlinear the seismic response of the VBI system was comprehensively evaluated using this model, and the effect of the vehicle dynamics on seismic performance of the bridge was identified. It was found that the seismic responses of most simply-supported bridges were reduced in the presence of railway trains due to the out-of-phase motion of the vehicle-bridge system. Meanwhile, the nonlinear behavior of the pier can reduce the vehicle’s seismic responses. Therefore, ignoring the nonlinear behavior of the pier during strong earthquakes can significantly overestimate the seismic response of the vehicle.展开更多
The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relativel...The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relatively lacking.Therefore,this paper proposes a method for modeling the charging load of electric vehicles based on the influence of multiple factors.First,an in-depth analysis of the factors affecting the charging load of electric vehicles was conducted.Then,a model of electric vehicle electricity consumption per unit kilometer was constructed based on the influencing factors.Next,the electric vehicle,the charging station,the traffic network and the grid are modeled separately.In addition,a unified model of vehicle-station-road-network was constructed through the interaction and coupling of information between the models.Finally,the spatial-temporal distribution of electric vehicle charging loads was simulated using real data from a region.The study shows that the model is able to simulate the charging load of electric vehicles more accurately.Different traffic flows and areas have a significant impact on the charging load distribution.展开更多
Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,parti...Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,particularly regarding their complex load transfer mechanisms.This paper develops an enhanced model of a multi-axle heavy-duty vehicle(MHV)coupled with the uneven and flexible pavement.An advanced coupling iterative method is proposed to solve the highly dimensional equations of the MHV-pavement coupled system.The proposed method was validated through experimental tests,with characteristic parameters of vertical accelerations showing relative errors between 0.42%and 11.80%.The coupling effect and influence mechanism of the braking process are investigated by characteristic parameters of the dynamic responses.Additionally,the influences of braking conditions and pavement parameters are analyzed in time and frequency domains in order to reveal the vibration mechanisms of the coupled system.Moreover,this study establishes a theoretical foundation for monitoring pavement health via vehicle-mounted acceleration signals,which is necessary in military transportation.展开更多
This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing opti...This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.展开更多
基金Supported by the Key Research and Development Program of Anhui Province(No.201904a05020035)the Postdoctoral Research Initiative of Anhui Province(No.2024B804)the Hefei City Key Technology Research and Development‘Ranking’(No.2023SGJ017).
文摘Traditional automated guided vehicle(AGV)primarily relies on scheduling systems to manage warehouse locations and execute picking or placing tasks on fixedheight pallets.However,these conventional systems are illsuited for scenarios involving variable heights,such as vehicle loading and unloading or the complex stacking of soft packages.To address the challenges of AGV endeffector operations in nonfixed height scenarios,this paper proposes an innovative solution leveraging lowcost depth camera sensors.By capturing image and depth data,and integrating deep learning,image processing,and spatial attitude calculation techniques,the method accurately determines the position of the endeffector center point relative to the upper plane of the fork.The approach effectively resolves a key issue in AGV operations within intelligent logistics scenarios that lack fixed heights.The proposed algorithm is deployed on a domestic embedded,lowcost ARM chip controller,and extensive experiments are conducted on a real AGV equipped with multiple stacked vehicles and nonstandard vehicles.The experimental results demonstrate that for diverse vehicles with different heights,the measurement error can be maintained within±10 mm,satisfying the requirements for highprecision measurement.The height measurement method developed in the paper not only enhances the AGV’s adaptability in nonfixed height scenarios but also significantly broadens its application potential across various industries.
文摘The implementation of the standard is expected to help electric vehicle battery swap stations to adapt to diversified needs and vehicle models,promoting the industry’s orderly and healthy development.
文摘The 2025 Shanghai Auto Show reaffirmed its role as one of the world’s most influential automotive industry events,offering a panoramic view of the future shaped by intelligent and electrified vehicles.With over 200 new models on display-85 percent of them new energy vehicles-this year’s show spotlighted how the global auto industry is pivoting rapidly towards an era of software-defined and AI-powered mobility.
文摘The usage of electric vehicles holds a crucial role in lowering the diminishing of the ozone layer because electric vehicles are not dependent on fossil fuels.With more research,evaluation,and its characteristics on electric vehicles,the infrastructure of charging points,production of electric vehicles,and network modelling,this paper provides a comprehensive overview of electric vehicles,and hybrid vehicles,including an analysis of their market growth,as well as different types of optimization used in the current scenario.In developing countries like India,the biggest barrier is their unfulfilled facility over the charging.Without renewable energy sources,vehicle-to-grid technology facilitates the enhancement of additional power requirements.The mobility factor has been considered an important and special characteristic of electric vehicles.
文摘This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining the internal and external factors of the formation about the Chinese EV industry business ecosystem,such as industrial structure transformation,technology transfer,government policies,and corporate competition,with the platform theory,I analyze the growth strategies and competitiveness of Chinese companies,particularly BYD Co.,Ltd.(BYD),which has risen to the top of the world in EV completed vehicles,and Contemporary Amperex Technology Co.,Ltd.(CATL),which has risen to the top of the world in electric vehicle batteries(EVB)2.BYD and CATL have gained competitive advantages by utilizing the distinctive management resources,which have accumulated over the years to build platforms for EVBs and EVs in response to changes in the external environment,and have actively developed their platform strategies.
基金supported by Unmanned Vehicles Core Technology Research and Development Program through the National Research Foundation of Korea(NRF)Unmanned Vehicle Advanced Research Center(UVARC)funded by the Ministry of Science and ICT,the Republic of Korea(2020M3C1C1A01083415).
文摘Flapping-Wing Air Vehicles(FWAVs)have been developed to pursue the efficient,agile,and quiet flight of flying animals.However,unlike lightweight FWAVs capable of vertical takeoff,relatively heavy FWAVs face challenges in self-takeoff,which refers to taking off without both external device and energy input.In this study,a cliff-drop method is implemented for an independent takeoff of a heavy FWAV,relying solely on gravity.In the takeoff process using the cliff-drop method,the FWAV moves on the ground to a cliff edge using a wheel-driving motor and then descends from the cliff to achieve the necessary speed for flight.To demonstrate the cliff-drop method,the KAIST Robotic Hawk(KRoHawk)with a mass of 740 g and a wingspan of 120 cm is developed.The takeoff tests demonstrate that the KRoHawk,significantly heavier than the vertical-takeoff capable FWAVs,can successfully take off using the gravity-assisted takeoff method.The scalability of cliff-drop method is analyzed through simulations.When drop constraints are absent,the wheel-driving motor mass fraction for cliff-drop method remains negligible even as the vehicle's weight increases.When drop constraints are set to 4 m,FWAVs heavier than KRoHawk,weighing up to 4.4 kg,can perform the cliff-drop takeoffs with a wheel-driving motor mass fraction of less than 8%.
基金supported by the Beijing Postdoctoral Research Foundation(No.2023-ZZ-133)Scientific Research Foundation of Beijing Infrastructure Investment Co.,Ltd.(No.2023-ZB-03)Fundamental Research Funds for the Central Universities(No.2682023ZTPY036).
文摘The pressure wave generated by an urban-rail vehicle when passing through a tunnel affects the comfort of passengersand may even cause damage to the train and related tunnel structures.Therefore,controlling the trainspeed in the tunnel is extremely important.In this study,this problem is investigated numerically in the frameworkof the standard k-εtwo-equation turbulence model.In particular,an eight-car urban rail train passingthrough a tunnel at different speeds(140,160,180 and 200 km/h)is considered.The results show that the maximumaerodynamic drag of the head and tail cars is most affected by the running speed.The pressure at selectedmeasuring points on the windward side of the head car is very high,and the negative pressure at the side windowof the driver’s cab of the tail car is also very large.From the head car to the tail car,the pressure at the same heightgradually decreases.The positive pressure peak at the head car and the negative pressure peak at the tail car aregreatly affected by the speed.
基金funded by Science and Technology Project of SGCC(SGJLCC00KJJS2203595).
文摘Aiming at the problem of increasing the peak-to-valley difference of grid load and the rising cost of user charging caused by the disorderly charging of large-scale electric vehicles,this paper proposes a coordinated charging scheduling strategy for multiple types of electric vehicles based on the degree of urgency of vehicle use.First,considering the range loss characteristics,dynamic time-sharing tariff mechanism,and user incentive policy in the lowtemperature environment of northern winter,a differentiated charging model is constructed for four types of vehicles:family cars,official cars,buses,and cabs.Then,we innovatively introduce the urgency parameter of charging demand for multiple types of vehicles and dynamically divide the emergency and non-emergency charging modes according to the difference between the regular charging capacity and the user’s minimum power demand.When the conventional charging capacity is less than the minimum power demand of the vehicle within the specified time,it is the emergency vehicle demand,and this type of vehicle is immediately charged in fast charging mode after connecting to the grid.On the contrary,it is a non-emergency demand,and the vehicle is connected to the grid to choose the appropriate time to charge in conventional charging mode.Finally,by optimizing the objective function to minimize the peakto-valley difference between the grid and the vehicle owner’s charging cost,and designing the charging continuity constraints to avoid battery damage,it ensures that the vehicle is efficiently dispatched under the premise of meeting the minimum power demand.Simulation results show that the proposed charging strategy can reduce the charging cost of vehicle owners by 26.33%,reduce the peak-to-valley difference rate of the grid by 29.8%,and significantly alleviate the congestion problem during peak load hours,compared with the disordered charging mode,while ensuring that the electric vehicles are not overcharged and meet the electricity demand of vehicle owners.This paper solves the problems of the existing research on the singularity of vehicle models and the lack of environmental adaptability and provides both economic and practical solutions for the cooperative optimization of electric vehicles and power grids in multiple scenarios.
基金co-supported by the Foundation of National Key Laboratory of Science and Technology on Aerodynamic Design and Research,China(No.614220121020114)the Key R&D Projects of Hunan Province,China(No.2023GK2022)。
文摘The design of wide-range high-efficiency aerodynamic configurations is one of the most important key technologies in the research of near-space hypersonic vehicles.A double-sided intake configuration with different inlets on the upper and lower surfaces is proposed to adapt to widerange flight.Firstly,the double-sided intake configuration’s design method and flight profile are delineated.Secondly,Computational Fluid Dynamics(CFD)numerical simulation based on multi-Graphics Processing Unit(GPU)parallel computing is adopted to evaluate the vehicle’s performance comprehensively,aiming to verify the feasibility of the proposed scheme.This evaluation encompasses a wide-range basic aerodynamic characteristics,inlet performance,and heat flux at critical locations.The results show that the inlets of the designed integration configuration can start up across Mach number 3.5 to 8.The vehicle possesses multi-point cruising capability by flipping the fuselage.Simultaneously,a 180°rotation of the fuselage can significantly decrease the heat accumulation on the lower surface of the vehicle,particularly at the inlet lip,further decreasing the temperature gradient across the vehicle structure.This study has some engineering value for the aerodynamic configuration design of wide-range vehicles.However,further study reveals that the flow phenomena at the intersection of two inlets are complex,posing potential adverse impacts on propulsion efficiency.Therefore,it is imperative to conduct additional research to delve into this matter comprehensively.
基金supported by the National Natural Science Foundation of China under Grant 61931005Beijing Natural Science Foundation under Grant L202018the Key Laboratory of Internet of Vehicle Technical Innovation and Testing(CAICT),Ministry of Industry and Information Technology under Grant No.KL-2023-001。
文摘In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide efficient and privacypreserving collaborative learning.However,in Io V environment,federated learning faces the challenges introduced by high mobility of vehicles and nonIndependently Identically Distribution(non-IID)of data.High mobility causes FL clients quit and the communication offline.The non-IID data leads to slow and unstable convergence of global model and single global model's weak adaptability to clients with different localization characteristics.Accordingly,this paper proposes a personalized aggregation strategy for hierarchical Federated Learning in Io V environment,including Fed SA(Special Asynchronous Federated Learning with Self-adaptive Aggregation)for low-level FL between a Road Side Unit(RSU)and the vehicles within its coverage,and Fed Att(Federated Learning with Attention Mechanism)for high-level FL between a cloud server and multiple RSUs.Agents self-adaptively obtain model aggregation weight based on Advantage Actor-Critic(A2C)algorithm.Experiments show the proposed strategy encourages vehicles to participate in global aggregation,and outperforms existing methods in training performance.
基金funded by Changzhou Science and Technology Project(No.CZ20230025)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.XSJCX23_36).
文摘Aiming at the problem that the existing algorithms for vehicle detection in smart factories are difficult to detect partial occlusion of vehicles,vulnerable to background interference,lack of global vision,and excessive suppression of real targets,which ultimately cause accuracy degradation.At the same time,to facilitate the subsequent positioning of vehicles in the factory,this paper proposes an improved YOLOv8 algorithm.Firstly,the RFCAConv module is combined to improve the original YOLOv8 backbone.Pay attention to the different features in the receptive field,and give priority to the spatial features of the receptive field to capture more vehicle feature information and solve the problem that the vehicle is partially occluded and difficult to detect.Secondly,the SFE module is added to the neck of v8,which improves the saliency of the target in the reasoning process and reduces the influence of background interference on vehicle detection.Finally,the head of the RT-DETR algorithm is used to replace the head in the original YOLOv8 algorithm,which avoids the excessive suppression of the real target while combining the context information.The experimental results show that compared with the original YOLOv8 algorithm,the detection accuracy of the improved YOLOv8 algorithm is improved by 4.6%on the self-made smart factory data set,and the detection speed also meets the real-time requirements of smart factory vehicle detection and subsequent vehicle positioning.
基金Supported by National Key Research and Development Program of China(Grant Nos.2022YFE0117100 and 2021YFB250120101)National Natural Science Foundation of China(Grant No.52325212)+1 种基金Shanghai Municipal Automotive Industry Science,Technology Development Foundation(Grant No.2203)the SAIC Motor Corporation Limited(Grant No.2023023).
文摘Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict.This paper introduces a novel multi-mode evasion assistance control(MEAC)method for intelligent distributed-drive electric vehicles.A reference safety area is established considering the vehicle safety and stability requirements,which serves as a guiding principle for evading obstacles.The proposed method includes two control modes:Shared-EAC(S-EAC)and Emergency-EAC(E-EAC).In S-EAC,an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance.The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance.Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions.In addition,it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.
基金in part by the National Natural Science Foundation of China(NSFC)under Grant 62371012in part by the Beijing Natural Science Foundation under Grant 4252001.
文摘As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.
基金Supported by National Natural Science Foundation of China(Grant Nos.U1864205,Grant No.52172377).
文摘With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total costs of fuel cell systems are still too high,thus limiting the further development of fuel cell hybrid electric vehicles.This paper presents an energy management strategy(EMS)based on deep reinforcement learning for the energy management of fuel cell hybrid electric vehicles.The energy management model of a fuel cell hybrid electric bus and its main components are established.Considering the power response characteristics of the fuel cell system,the power change rate of the fuel cell system is reasonably limited and introduced as action variables into the network of Double Deep Q-Learning(DDQL),and a novel DDQL-based EMS is developed for the fuel cell hybrid electric bus.Subsequently,a comparative test is conducted with the DP-based and the Rule-based EMS to analyze the performance of the DDQL-based EMS.The results indicate that the proposed EMS achieves good fuel economy performance,with an improvement of 15.4%compared to the Rule-based EMS under the training scenarios.In terms of generalization performance,the proposed EMS also achieves good fuel economy performance,which improves by 13.3%compared to the Rule-based energy management strategy under the testing scenario.
基金The Research Project of Southwest Municipal Design&Research Institute of China under Grant No.2023KY-KT-02-I。
文摘Aerodynamic and dynamic interference from trains is a key issue of concern for the safety of road vehicles travelling on single-level rail-cum road bridges.Based on the wind-road vehicle-train-bridge(WRTB)coupled vibration system developed herein,this study examines the dynamic characteristics when road vehicles meet trains in this situation.The influence of load combination,vehicle type and vehicle location is analyzed.A method to obtain the aerodynamic load of road vehicles encountering the train at an arbitrary wind speed is proposed.The results show that due to the windproof facilities and the large line distance between the railway and highway,the aerodynamic and dynamic influence of trains on road vehicles is slight,and the vibration of road vehicles depends on the road roughness.Among the road vehicles discussed,the bus is the easiest to rollover,and the truck-trailer is the easiest to sideslip.Compared with the aerodynamic impact of trains,the crosswind has a more significant influence on road vehicles.The first peak/valley value of aerodynamic loads determines the maximum dynamic response,and the quick method is optimized based on this conclusion.Test cases show that the optimized method can produce conservative results and can be used for relevant research or engineering applications.
基金supported by the Scientific Research Innovation Capability Support Project for Young Faculty,China(No.ZYGXQNJSKYCXNLZCXM-D1)the National Natural Science Foundation of China(No.52272384).
文摘Flapping-Wing Micro Air Vehicles(FMAVs)are compact and agile,capable of accessing narrow spaces that conventional vehicles struggle to reach,such as ruins,caves,or the interiors of complex structures,making them ideal tools for reconnaissance and rescue missions.1 However,the operation of FMAVs relies on coordinating multiple forces with different scaling effects,posing challenges to miniaturization design.
基金supported by the National Natural Science Foundation of China(Grant No.51678490)the Natural Science Foundation of Sichuan Province(Grant No.2024NSFSC0161).
文摘Railway bridges are continuously loaded by railway trains;therefore, it is important to understand the nonlinear seismic response of the Vehicle-Bridge Interaction (VBI) system under strong earthquakes. For this purpose, the nonlinear behavior of the pier was introduced into the in-house VBI solvers. The nonlinear the seismic response of the VBI system was comprehensively evaluated using this model, and the effect of the vehicle dynamics on seismic performance of the bridge was identified. It was found that the seismic responses of most simply-supported bridges were reduced in the presence of railway trains due to the out-of-phase motion of the vehicle-bridge system. Meanwhile, the nonlinear behavior of the pier can reduce the vehicle’s seismic responses. Therefore, ignoring the nonlinear behavior of the pier during strong earthquakes can significantly overestimate the seismic response of the vehicle.
基金the National Key Research and Development Program of China(No.2021YFB2501602)the National Natural Science Foundation of China(No.52077208)。
文摘The spatial-temporal distribution of charging loads for electric vehicles is influenced by multiple factors,Nowadays,the accuracy of the forecasts needs to be improved and the completeness of the modeling is relatively lacking.Therefore,this paper proposes a method for modeling the charging load of electric vehicles based on the influence of multiple factors.First,an in-depth analysis of the factors affecting the charging load of electric vehicles was conducted.Then,a model of electric vehicle electricity consumption per unit kilometer was constructed based on the influencing factors.Next,the electric vehicle,the charging station,the traffic network and the grid are modeled separately.In addition,a unified model of vehicle-station-road-network was constructed through the interaction and coupling of information between the models.Finally,the spatial-temporal distribution of electric vehicle charging loads was simulated using real data from a region.The study shows that the model is able to simulate the charging load of electric vehicles more accurately.Different traffic flows and areas have a significant impact on the charging load distribution.
基金National Defense Basic Scientific Research Program of China(Grant No.JCKY2021602B030).
文摘Multi-axle heavy-duty vehicles(MHVs)are essential for military equipment transport due to their safety and stability.However,braking dynamic responses between MHVs and pavement systems still remain underexplored,particularly regarding their complex load transfer mechanisms.This paper develops an enhanced model of a multi-axle heavy-duty vehicle(MHV)coupled with the uneven and flexible pavement.An advanced coupling iterative method is proposed to solve the highly dimensional equations of the MHV-pavement coupled system.The proposed method was validated through experimental tests,with characteristic parameters of vertical accelerations showing relative errors between 0.42%and 11.80%.The coupling effect and influence mechanism of the braking process are investigated by characteristic parameters of the dynamic responses.Additionally,the influences of braking conditions and pavement parameters are analyzed in time and frequency domains in order to reveal the vibration mechanisms of the coupled system.Moreover,this study establishes a theoretical foundation for monitoring pavement health via vehicle-mounted acceleration signals,which is necessary in military transportation.
文摘This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.
