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Research On Parameter Matching And Energy Management Strategy Of Extended Engine Based On Small Engine

Posted on:2020-07-27Degree:MasterType:Thesis
Country:ChinaCandidate:S K ZhangFull Text:PDF
GTID:2392330599460603Subject:Engineering
Abstract/Summary:
With environmental pollution and energy shortages becoming more and more serious,national automobile emission regulations are becoming stricter.As a transitional product between traditional fuel vehicles and pure electric vehicles,the extended-range electric vehicle has the advantages of both,and is a new energy vehicle with more advantages and development prospects at this stage.The pros and cons of the vehicle energy management control strategy have a significant impact on the vehicle’s power,fuel economy and emissions.This paper takes the extended-program hybrid electric vehicle as the research object.The research contents of this paper are as follows:First of all,based on the current social development background and trends,the selection of the extended-range electric vehicle for the purpose of urban transportation is the research object,and a model of a traditional car is used as a reference prototype.According to the operation mode,structural composition,basic vehicle parameters and performance indicators of the extended-range electric vehicle,the power system component selection and parameter matching are carried out.Secondly,the operation mode and energy flow of the extended-range electric vehicle are elaborated and analyzed in detail.According to the characteristics of urban operation,the vehicle speed is low,the driving distance is short,and the working mode of the extended-range electric vehicle is established.The start-stop control strategy and energy recovery control strategy of the extended-range electric vehicle range extender are formulated.The vehicle simulation model is built based on MATLAB/Simulink platform,and the rationality of the parameter matching of the vehicle dynamic system and the correctness of the control strategy are verified.Finally,the power battery capacity is optimized to ensure the accuracy of the battery state of charge estimation.Taking 100 km of energy consumption and CO2 100 km emission as the optimization goal,the genetic algorithm is used to optimize the start and stop control strategy and control strategy parameters of the range extender.Under the conditions of NEDC and CLTC,the fuel economy and emissions were effectivelyimproved by the vehicle simulation model.
Keywords/Search Tags:extended-range electric vehicle, energy management, target travel, fuel economy, multi-objective optimization
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