A Study On Predictive Energy Management Strategy Of 48V Hybrid Electric Vehicle Based On V2X

With the increasingly stringent requirements of vehicles’ energy saving and fuel consumption regulations,the development of electric and intelligent new power systems has become an inevitable trend.As a cost-effective energy-saving solution,the 48 V hybrid power system has many advantages.At the same time,the application of the vehicle to everything(V2X)technology has been gradually promoted,and the use of real-time road traffic information provided by the V2 X provides further optimization space for the energy management strategy of hybrid electric vehicles(HEV).This paper uses the 48 V P2 HEV as the research platform,a detailed study was carried out around the torque distribution strategy based on real-time optimization and the engine start-stop control and coasting braking energy recovery strategy fused with road traffic information.First of all,according to the performance design goal and braking energy recovery capacity,the 48 V motor and battery matching parameters and modeling were carried out.The actual experimental data is used to identify and verify the parameters of the battery model,and perform the performance simulation verification of the 48 V HEV.The results show that the 48 V HEV simulation platform built by MATLAB/Simulink satisfies the design goals’ requirements,and lays a foundation for the research of control strategies in the following.Secondly,in order to explore the fuel-saving effect of the 48 V HEV based on the optimized energy management strategy,a rule-based strategy(RB)and equivalent consumption minimization strategy(ECMS)was established based on the 48 V HEV simulation platform.The accuracy of the strategy was verified through the driving speed following simulation.The characteristics of various types of strategies and the ability to improve fuel economy are analyzed.The results show that the fuel saving rate of the torque distribution strategy based on optimization is only about 1% higher than the strategy based on rules;the 48 V HEV mainly relies on regenerative brake and engine start-stop mode to save fuel.Thirdly,in order to make full use of deceleration and parking conditions to engine stop and save fuel,for vehicles encountering traffic signal intersections and traffic congestion conditions,a predictive start-stop strategy that integrates real-time road traffic information is proposed,which uses traffic signal timing and information from the preceding vehicle to recognize the intention to decelerate and stop and predict the total idle time.The Wiedemann car-following model is used to calibrate the parameters of the deceleration intention recognition strategy.And combined with the VISSIM traffic scene and MATLAB/Simulink vehicle model for simulation verification and analysis.The results show that the proposed predictive start-stop strategy can still achieve 0.8%～5.1% fuel saving rate compare with BOSCH coast-to-stop strategy,which is the most energy-efficient,under each working condition set in this paper,and it can avoid invalid start-stop.Finally,in order to achieve a better coasting regenerative brake recovery rate and better meet the driver’s desired coasting distance requirements.For urban road vehicles encountering traffic signal intersections,a predictive coasting braking energy recovery strategy that integrates real-time road traffic information is proposed.Through coasting braking intention recognition and expected coasting braking distance prediction,solving the motor braking torque that meets the demand in real time.Simulation verification and analysis are carried out based on the traffic scene and the vehicle platform established in the previous article.The results show that the proposed predictive coasting braking energy recovery strategy can better meet the driver’s coasting braking demand and has higher economic efficiency than the fixed-value coasting braking recovery strategy.