| With the improvement of living quality and the rapid growth of travel demands,there are more and more vehicles driving on the ground causing urban traffic congestion,energy consumption,and traffic accidents.The studies on preventing traffic congestion,reducing energy consumption,and improving driving safety increasingly attract people's attention.Ground vehicle plays an important role showing great responsibility to reduce the serious energy consumption,decrease congestion and remedy safety problems in the transportation system.Therefore,improving the sustainability of vehicles at the technical level is the top priority to address the above issues.On this background,it is of great significance to continuously promote the development of intelligent ecological mobility technology with safety,energy-saving and high efficiency.The development of 5G communication and V2 X technology,as a result,the control technology of multi-vehicle platooning has been highly appreciated by researchers.Ecological cooperative adaptive cruise control(ECACC)for the connected automated vehicle(CAV)platoon based on V2 X communication is taken as one of the key technologies,can effectively achieve energy-saving of vehicle groups,enhance the safety of vehicle following and improve road traffic efficiency.ECACC plays a key role in promoting the sustainable intelligent transportation system application.ECACC obtains the information resources by receiving the current traffic environment status,vehicle platoon state and future road information using V2 X communication.Optimal control problem design for vehicle platoon takes driving economy as the main goal,at the same time,achieving the stable and safe effect of car-following in the platoon.The energy-oriented behavior decisions of the leading vehicle are optimized,which are also treated as the control inputs for the following vehicles in the platoon to conduct the powertrain optimization.Hence,the vehicle platoon drives in a variety of intelligent transportation scenarios with the achievements of energy-saving and safe car-following.Compared with the traditional single-vehicle control,cooperative multi-vehicle control can further improve the performance of energy efficiency by 10-20%.Moreover,cooperative control for vehicle platoon can increase the safety of car-following,shorten the intervehicle distance,thus improving the capacity and efficiency of road traffic,and reducing the extra energy consumption caused by traffic congestion,achieving the purpose of ecological mobility in both vehicular and microscopic traffic levels.In this paper,the connected homogeneous platoon consisted of fully electric vehicles is taken as the research target.Based on V2 X communication,the ECACC strategy for the vehicle platoon was investigated in typical urban and highway scenarios at both theoretical and experimental levels,where the energy consumption is taken as the main optimization objective and the car-following performance of the platoon is taken as the basic guarantee.The verification procedure was carried out through the simulation analysis,hardware-in-theloop(Hi L)tests and vehicle experiments.Specific research contents are as follows:(1)According to the driving modes and driving constraints of vehicle platoons in different scenarios,ECACC strategies can be classified into two types,referring to passive following based and active planning based.Car-following performance and energy-saving performance as two main evaluation properties of ECACC were simulated and analyzed.In terms of bottom-level car-following control,the CACC controller is the technical cornerstone of platoon driving.The car-following controller using the feedforwardfeedback structure and fully feedback structure were modeled,analyzed and verified in simulation with consideration of string stability.Moreover,in terms of energy consumption,it is established based on the motor Map and battery dynamic parameters while the proposed grey box model of energy consumption for the fully electric vehicle is compared and verified with mature commercial software.As a result,the verification of the car-following controller and energy consumption model provide favorable research foundations for the following ECACC strategy.(2)A predictive optimization ECACC strategy is proposed based on nonlinear model predictive control to minimize the energy consumption of an electrified CAV platoon considering V2 V topological communication structure of leader predecessor follower.The cost function for NMPC includes the following velocity,range deviation and energy consumption.Through the simulation analysis under various drive cycles,the advantage of the proposed scheme emerges that the platoon consisted of three vehicles that possess nice string stability,excellent following performance and significant energy-saving potential at the same time.Moreover,the acceleration of the following vehicles is in a small range,improving the drive comfort.By the comparison with the existed Eco ACC controller,the simulation results demonstrate the proposed controller owns better following performance and energy-saving behavior of 16.1%,6.2% and 11.7% under full UDDS,HWFET and NEDC drive cycle,respectively.(3)Developing a novel hierarchical ECACC strategy with energy-saving achievements by conducting the ecological velocity trajectory planning of the leading vehicle based on dynamic programming and car-following driving of the rest of the vehicles in the platoon based on feedforward-feedback control.The main purpose is to reduce the energy consumption of multiple vehicles in intelligent transportation systems with consideration of trip time and car-following performance.The optimal velocity planning uses an innovative integrated longitudinal and lateral vehicle dynamics approach where both the lateral stability and energy efficiency in continuous curved roads are guaranteed at the same time.Moreover,the connected automated vehicle platoon presents better carfollowing performance with string stability as opposed to the Cooperative Adaptive Cruise Control based on feedback control and model predictive control.The results indicate the great potential of the proposed ECACC strategy to further improve the sustainability of intelligent transportation systems.(4)Based on V2 X communication,the ECACC is proposed combing the advantages of ecodriving and car-following to minimize the energy consumption of the connected automated vehicles platoon.Herein,the vehicle platoon behaviors in the scenario of driving through continuous signalized intersections show great impacts on sustainability,including energy and travel time saving of the transportation system.Fuel economy is improved along corridors with more traffic lights.In the velocity trajectory planning process,a modified dynamic programming algorithm is formulated with the switching logic gate of two types of optimal control problems to increase the computational speed.By testing in the real-world scenario,the results of the proposed Eco-CACC exhibit excellent energy performance which improves 8.02% compared to manual driving with a constant acceleration policy.Moreover,energy even can be further improved by 2.02%and 1.55% when the car-following strategy is selected with MPC and IDM algorithm.(5)The verification framework including simulation,Hi L tests and vehicle experiments was established.Based on RSU and OBU communication,Hi L tests focusing on the vehicle powertrain performance were carried out in dynamic e Horizon with a real HD urban road Map.Based on Virtual Platoon methodology,real vehicle experiments were conducted to evaluate the car-following performance under different desired acceleration inputs.A series of verifications show that the ECACC strategy can effectively improve the energysaving and car-following performance of the CAV platoon.Based on the systematic research from theory to application,ECACC was proved its huge energy saving potential and driving safety advantages for CAV platoon application,which also reflects the flexibility and applicability of ECACC strategy in different scenarios.This strategy shows significant practical application prospect in the future intelligent transportation system as well as providing the technical foundation for ecological mobility application with the goals of vehicle safety,energy-saving,traffic efficiency. |
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