Study On Control Strategy Of Hybrid Electric Vehicle Based On Working Condition Recognition

Control strategy is the key to energy saving and emission reduction of hybrid electric vehicle.In order to improve the adaptability and fuel economy of the control strategy,a single axle parallel hybrid electric vehicle was used as the research object.Through the condition identification and dynamic programming algorithm,an instantaneous optimization control strategy based on double weight factors was developed.The main research work was as follows:1.Establishment of typical working condition database.The typical working condition was the basis of the control strategy and the condition of obtaining the optimal control sequence database.In order to improve the adaptability of the strategy,rational planning was made and the actual driving conditions was obtained.Through the principal component analysis of the characteristic parameters,the K-means algorithm was used to cluster the kinematics fragments.On the basis of verifying the rationality of the clustering results,a typical working condition database was established,which was the base of the optimal control sequence database.2.Establishment of optimal control sequence database.The optimal control sequence database based on global optimization was the reference of the instantaneous optimal control strategy.The MATLAB function was used to realize the dynamic programming algorithm and the global optimization controller model was established.The physical model of the target vehicle was constructed,and the simulation model was compared with the logic threshold control strategy.On the basis of verifying the effectiveness of the global optimization control strategy,the optimal control sequence database was established by using the global optimization in the typical working condition database.3.Research on energy management strategy for hybrid electric vehicle based on working condition recognition.Based on the optimal control sequence database,the instantaneous optimal control strategy of hybrid electric vehicle was designed based on the double weight factors.Firstly,the overall weight factor and Instantaneous weight factor were defined.The overall weight factor represents the road characteristics of the current working conditions,such as urban conditions,suburban conditions,etc.The instantaneous weight factor represents the current state of the vehicle,such as acceleration,deceleration and uniform.Two kinds of weighting factors and optimal control sequence database were used to calculate the real time weighting factor.At last,the validity of the proposed control strategy was verified by comparing the simulation results with the logic threshold control strategy and the global optimization control strategy.The results show that the double weight factors control strategy can achieve the vehicle speed tracking and battery SOC maintenance.The difference of oil consumption between the double weight factors control strategy and the global optimization control strategy is 3.8%,which is decreased by 8.5%than the logic threshold control strategy.So,the the double weight factors control strategy achieves the design goal.