Research On Speed Planning And Energy Management Strategy For Hybrid Electric Vehicle Platoon

With the tendency that energy shortages,urban traffic congestion,frequent road accidents and other problems becoming more and more serious,countries all over the world are looking for effective solutions.New energy vehicle technology has significant advantages in improving fuel economy,in the meantime,vehicle platoon control can improve the driving safety of vehicles.Therefore,how to combine traffic and vehicle status information to achieve energysaving and safe speed planning and energy management is a problem that must be considered in the design of vehicle platoon control strategies.In this paper,select the hybrid vehicle platoon as the research object,the road model established with real road information as the scene,carried out research on speed planning and energy management strategies,and the specific research contents are as follows:Firstly,builded a hybrid vehicle model and a road model.Builded mathematical models of important power and transmission components of the vehicle based on MATLAB,developed a gear shift strategy that considers braking energy recovery.Through vehicles and inertial navigation equipment,data information such as the slope,road speed limit,signal lamp position,signal lamp phase of two roads in Chongqing was collected,and a road model oriented to speed planning was established in MATLAB.Secondly,a comparative study of energy management strategies for parallel hybrid power systems.Explains the basic theory of Pontryagin minimum Principle(PMP)and equivalent fuel consumption minimum strategy(ECMS).The detailed process of solving energy management problems with PMP and ECMS is given,and it is proved that ECMS is an approximate realization of PMP in energy management problems.The connotation of the equivalent factor is analyzed and the adjustment rule of the equivalent factor is given.The optimization performance of non-adaptive ECMS,optimal ECMS,continuous adaptive ECMS(C-AECMS),discrete adaptive ECMS(D-AECMS)and PMP strategy are compared.Results show that DAECMS has better working condition adaptability and fuel economy.Thirdly,based on Model Predictive Control(MPC)and D-AECMS algorithm,the multiobjective optimization problem integrating comfort and fuel economy is studied.Established a hierarchical optimization strategy,the upper layer has developed an MPC control strategy that integrates SPAT(Signal Phase and Timing)information,enables vehicles to pass through signal intersections without stopping,improving the ride comfort of vehicles.The lower layer developed the D-AECMS strategy to optimize the power distribution of the hybrid power system,improve the fuel economy of the vehicle,and maintain the battery SOC within the desired range.Results show that compared to the fusion optimization strategy,the hierarchical optimization strategy can effectively improve the comfort and fuel economy of the vehicle.Finally,based on the MPC and D-AECMS algorithms,the speed planning and energy management issues incorporating the CTH(Constant Time Headway)safety spacing strategy are studied.Established a control-oriented hybrid vehicle platoon model and a hierarchical optimization strategy.The upper layer realizes the safe driving of the vehicle platoon through the MPC algorithm,and the lower layer realizes the optimization of the fuel economy of the hybrid vehicle platoon through the D-AECMS strategy.The results show that the adjacent vehicles in the fleet have achieved a better tracking effect on the expected distance,and achieved a fuel economy close to the PMP strategy.hierarchical optimization strategy can realize the coordinated control of the fleet and improve the safety and fuel economy of the hybrid vehicle platoon.