Research On Plug-in Hybrid Electric Vehicle Control System Based On Operating Condition Analysis

Based on a new hybrid transmission,this paper takes a domestic car as a reference model and converts the original vehicle into a plug-in hybrid electric vehicle.With the goal of improving its fuel economy,the research is carried out around the equivalent fuel consumption.minimum control strategy?The main research contents include: Based on the new hybrid power system,the vehicle power performance matching is completed,and the parameters of motor,engine and battery are determined;The ADVISIOR software is used to complete the modeling of the new hybrid power system.Sixteen standard cycle conditions were selected,and the typical cycle conditions were classified by principal component analysis(PCA)and K-means clustering method,and the corresponding cycle recognition method was proposed.For the five characteristic conditions selected,the equivalent fuel consumption minimum(ECMS)strategy was used to obtain the corresponding charge-discharge equivalent coefficient and the change of electric quantity and equivalent fuel consumption,and the charge-discharge equivalent coefficient corresponding to different discharge specifications under the five characteristic conditions was determined.the adaptive equivalent fuel consumption minimum control strategy(A-ECMS)based on Driving Condition Recognition with four operating modes is implemented,which are charge holding mode,shallow charge and shallow discharge mode,deep discharge mode and electric mode.A-ECMS control strategy was applied to simulate the performance of the hybrid power system under the combination of NEDC and PH Driving cycles.The results of NEDC simulation show that the fuel consumption per 100 km of the new hybrid power system is5.53 liters in the power holding mode,which meets the economic requirements of the national new energy dual integral policy.Compared with traditional vehicles,fuel economy improved by 25.6%.Compared with the motor assisted control strategy fuel economy increased by 15%.Compared with the equivalent fuel consumption minimum control strategy with fixed equivalent coefficient of charge and discharge,the fuel economy increased by1.7%.Compared with DP algorithm,the difference is 3.8%.The simulation results under CLTC-P condition show that the fuel consumption per 100 km of A-ECMS control strategy is 5.3 liters in the power holding mode.Compared with the traditional fuel vehicle fuel saving 29.3%;Compared with the motor assisted control strategy,the fuel saving is 16%;Compared with A-ECMS,DP algorithm saves 1.1% fuel.The simulation results under p H condition show that the equivalent fuel consumption per 100 km in the power-holding mode is 6.53 liters,which improves the fuel economy by 24.07% compared with the traditional vehicle.13% higher fuel economy compared to the motor assisted control strategy;Compared with the fixed-parameter ECMS control strategy,the fuel economy is significantly improved by 6%,which indicates the necessity of combining the condition identification with ECMS.0.31% difference compared to DP power holding mode.The equivalent fuel consumption per 100 km of shallow charging and discharging mode is 6.59 litres,which is23.37% higher than the fuel economy of traditional vehicles.12% better fuel economy compared to the motor assisted strategy;Compared with DP algorithm,the fuel economy is1.2% worse.In the deep discharge mode,the actual fuel consumption per 100 km is 5.53 liters,which is 35.7% higher than that of the traditional vehicle.Compared with the motor assisted strategy,it increased by 26.3%;Compared with the DP algorithm,the fuel economy of the deep discharge mode is 1.8% worse.