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Parameter Matching And Control Strategy Research Of Powertrain System For Range-extended Electric Vehicle

Posted on:2015-07-05Degree:MasterType:Thesis
Country:ChinaCandidate:J L ZhaoFull Text:PDF
GTID:2272330422972340Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
Energy crisis would require new energy resources for automotive industry. Electricenergy is considered by automotive industry as a kind of clean, extensive-source energy.But currently, with the restraint on energy density and durability, pure electric vehiclecould hardly achieve large scale manufacture. Range-extended electric vehicles(R-EEV)as the transition models between internal combustion engine vehicles and pure electricvehicles can effectively increase the energy alternatives to fossil fuels, on condition thatdriving range and durability of batteries are ensured. Based on the above, this thesisdeveloped parameters for the powertrain system, and did some research on the energymanagement.The main details in this paper are as follows:â—‹1The structure features and working principle of R-EEV are introduced indetails,and difference among R-EEV, pure electric vehicle, hybrid electric vehicle andplug-in electric vehicle are summarized. At the same time, working mode of R-EEV isintroduced in details.â—‹2The powertrain system and energy source type of R-EEV are selected, andparameter matching have done including driving motor, transmission, air condition,power battery, and auxiliary power unit system.â—‹3Energy management strategy of R-EEV is developed, including pure electricdriving mode control strategy, range-extended mode control strategy, engine start&&stop control strategy, regenerative braking control strategy and battery control strategy.â—‹4The simulation models of R-EEV are building based on Matlab/Simulink,including battery model, driving motor model, transmission model, control strategymodel, and air condition model.Dynamic performance, economic performance andenergy control strategy of R-EEV are simulated in the vehicle model.â—‹5Control parameters of R-EEV are optimized by particle swarm optimization(PSO) algorithm. Nonlinear programming model of control parameters is build based onMatlab, and optimization goal is driving range maximum.
Keywords/Search Tags:R-EEV, powertrain system, electric air-condition, energy controlstrategy, PSO optimization
PDF Full Text Request
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