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Research On Performance Optimization Of Electric Vehicle R1234yf Heat Pump Air Conditioning System Based On PSO

Posted on:2022-03-24Degree:MasterType:Thesis
Country:ChinaCandidate:K ZhangFull Text:PDF
GTID:2492306554467964Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
In the context of China’s"carbon peak"and"carbon neutralization"goals and the 14th Five-Year Plan,electric vehicles will gradually replace fuel cars as the first choice for future transportation.The range of electric vehicles has been constrained by the problem of winter heating.The heat pump air conditioning system for electric vehicles based on the environmentally friendly refrigerant R1234yf is a promising solution.In this paper,the performance of the electric vehicle heat pump air conditioning system based on R1234yf has been analyzed by numerical simulation plus experimental study under various operating conditions,and sensitivity analysis,particle swarm optimization and geographical analysis have been carried out for the system.(1)An electric vehicle heat pump air conditioning system experimental bench was built,and the performance analysis of the system under variable operating conditions was carried out,and a comparison analysis with the R134a refrigerant system was conducted.(2)The mathematical model of each component of the electric vehicle heat pump air conditioning system was established,and the overall system model was experimentally verified,and the difference between the cooling capacity and COP and the experimental results were within 10%;and the system cooling and heating performance and the system battery analysis were conducted through the mathematical model.(3)A sensitivity analysis based on the Sobol method was conducted for the R1234yf electric vehicle heat pump air conditioning system,and the results showed that for the cooling(heating)capacity,the most sensitive parameter is the outdoor(inner)side heat exchanger air surface area,the most sensitive for the COP is the compressor speed,and the outdoor side heat exchanger head-on air speed is the least sensitive parameter for both.(4)The particle swarm algorithm was optimized for the R1234yf electric vehicle heat pump air conditioning system,and the optimization results were as follows:in the cooling mode,when the compressor speed is 3745rpm,the indoor side heat exchanger inlet air volume is 423m3/h,the outdoor side heat exchanger head-on air speed is 6.6m/s,the outdoor side heat exchanger head-on air area is 1.2Rc and the indoor side heat exchanger head-on air area is 1.2Re The COP is 3.236 and the cooling capacity is 4459W.With the same COP,the optimized cooling capacity is 14%higher than that before optimization.In the heating mode,when the compressor speed is 3894rpm,the inlet air volume of indoor side heat exchanger is 468m3/h,the head-on air speed of outdoor side heat exchanger is5.3m/s,the head-on air area of outdoor side heat exchanger is 1.2Rc and the head-on air area of indoor side heat exchanger is 1.2Re,the COP is 2.554 and the heating capacity is4357W,under the same COP,the optimized The optimized heating capacity is 12%higher than that before optimization.(5)The geographical analysis of electric vehicle heat pump air conditioning system based on R1234yf in different climate regions,especially the winter heating problem,is discussed and analyzed,and it is concluded that:for the cold summer-free zone(Harbin)and the cold cool high-spoke zone(Lhasa),the CO2 heat pump air conditioning system is recommended;for the cold dry hot high-spoke zone(Urumqi)and the cold micro-heat zone(Beijing),the R1234yf-based electric vehicle heat pump air conditioning system with heat return and steam injector is recommended to enhance heat production;for mild hot and humid zone(Guangzhou),mild cool zone(Guiyang)and cold and humid hot zone(Hefei),R1234yf-based electric vehicle heat pump air conditioning system can fully meet the winter heating demand without any modification.
Keywords/Search Tags:Electric vehicle, heat pump, R1234yf, Sobol sensitivity analysis, PSO
PDF Full Text Request
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