Research On Energy Management Strategy Of Plug-in Hybrid Electric Vehicle Based On Hardware In Loop Simulation

The plug-in hybrid electric vehicles(PHEV)have broader market prospects because of combining the advantages of both hybrid electric vehicles(HEV)and pure electric vehicles(EV).The potential for PHEV energy-saving mainly depends on the energy management strategy.Currently,most energy management strategies studied neither can be applied to real-time control because they are too computationally intensive nor can adapt to the driving conditions properly,leading to good optimization difficult to be achieved.Focusing on a single-axis parallel PHEV layout,and by using a model-based design approach,this paper investigates the development of system modeling,control strategy design,and hardware-in-the-loop tests.First,the parameters and their matching of the vehicle powertrain are investigated,thus the system mathematical models are built accordingly.Then the real-time energy consumption optimization control strategy for practical application is developed.Taking the improvement of energy economy as target,the battery power observer is adopted to calculate the switching thresholds between charge-depleting(CD)mode and chargesustaining(CS)mode.In CD mode,the motor provides the main power supported by an engine.A logic threshold control strategy based on engineoptimal rules and a map-based equivalent fuel consumption minimization strategy(ECMS)are developed for CS mode.Taking the logic threshold control strategy based on engine optimal rules as reference,a map-based equivalent consumption minimization strategy is developed for the real-time control of the PHEV.By using a basic principle of the minimum equivalent fuel consumption strategy,the optimal rules are calculated off-line and stored as 4-dimentional maps for real-time control.The proposed map-based approach simplifies the complexity of control strategy design,which thus can be more effective in practice.Also,an equivalent fuel consumption penalty factor is adjusted in real time by using a proportional-integral(PI)controller based on battery state-of-charge(SOC)feedback and fuzzy logic controller respectively.Finally,a hardware-in-the-loop(HIL)simulation platform based on LabCar is developed to conduct experimental analysis and model verification of the proposed control strategies.HIL simulation results show that the proposed control strategies can effectively coordinate the vehicle powertrain,optimize vehicle fuel economy,and meanwhile maintain the battery SOC satisfactorily.The logic threshold control strategy based on engine optimal rules is effective and easy to be implemented in practice.The map-based ECMS adjusting equivalent minimum fuel consumption strategy penalty factor through the PI control can improve the fuel economy of the vehicle;The map-based ECMS adjusting the penalty factor by fuzzy logic control can further consider battery SOC change rates,hence it can achieve the best energy-saving and battery SOC changes more smoothly which is more beneficial to battery health meanwhile.