Energy Management Strategy For Hybrid Vehicles Based On Adaptive Simplified ECMS

Since the birth of the automobile,the automobile has brought great convenience to people’s travel,but the development of the automobile industry has also had a negative impact,the increase in the number of traditional diesel locomotives has accelerated the consumption of oil energy,resulting in a shortage of oil energy,so it is urgent to find a suitable way to solve the problem of energy shortage.Hybrid vehicles are a model of transition to pure electric vehicles,because the current pure electric vehicles have battery range anxiety,fast charging technology to be improved,safety performance is relatively poor,the weight of the vehicle is relatively heavy,and the battery is difficult to adapt to the cold environment,so it cannot be popularized in the northern region in the short term.Hybrid vehicles combine the advantages of internal combustion engines and pure electric vehicles,equipped with two power sources,can better adapt to complex environments,and have good development prospects in the future.The energy management strategy is related to the economics of hybrid vehicles and is one of the core technologies developed by them.Good energy management strategies can meet vehicle dynamics while reducing fuel consumption,which one of great research significance.In this context,this thesis studies energy management strategies for the purpose of improving the fuel economy of hybrid vehicles,and the main research contents are as follows:First,rule-based energy management strategy was studied.Through the analysis of the type of hybrid vehicle,a plug-in parallel hybrid vehicle was selected as the research object,its working mode is studied and analyzed,and the basic parameters of the whole vehicle were determined,and the selection and parameter matching of key components were completed according to the configuration of the whole vehicle.In the MATLAB/Simuink simulation platform,each part of the vehicle was modeled,the rule-based energy management strategy of the model was formulated,the feasibility of the vehicle model was verified by simulation,and the conclusion that the rule-based control strategy had poor adaptability to working conditions and poor control effect.Secondly,the equivalent fuel consumption minimum strategy was studied.After studying the theory of equivalent minimum fuel consumption strategy(ECMS),the ECMS strategy was formulated for the vehicle model,the rule-based control strategy was replaced,and the relationship between the equivalent factor and the initial SOC and mileage of the battery was studied.Then,a simplified ECMS strategy was developed.In order to further reduce the calculation amount of ECMS,this thesis establishes a simplified ECMS strategy by segmented function fitting of the characteristic curves of the engine and motor,and the simulation verifies that the simplified strategy was significantly smaller than the ECMS control strategy in terms of simulation time,and the fuel consumption results were close to ECMS,which could better realize real-time control.Finally,an adaptive simplified ECMS strategy was formulated.The initial function of the equivalent factor was established,the search for the best equivalent factor was converted into the best correction coefficient,and the correction coefficient was optimized by using the DSGSO algorithm,and the MAP plot of the correction coefficient under different driving modes,driving distance and initial SOC was obtained.Based on the MAP diagram of correction coefficient and recognition algorithm,an adaptive simplified ECMS strategy was proposed.The test results showed that the adaptive simplified ECMS strategy can effectively distribute the torque of the engine and motor,and the fuel economy was significantly improved compared with the rule-based strategy.