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    • Optimization Design of the Interference Connection Structure for Turbocharger Turbine Rotors Based on Back Propagation Neural Network
    DOI：10.13949/j.cnki.nrjgc.2024.01.002
    Key Words:titanium–aluminum alloy  turbine  interference connection  structural optimization
    Author NameAffiliationPostcode
    CHEN Sheng School of Mechanical Engineering， Hebei University of Technology， Tianjin 300130， China
    Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles， Tianjin 300130， China     		300130
    LIU Ye China North Engine Research Institute， Tianjin 300400， China 300400
    JING Guoxi School of Mechanical Engineering， Hebei University of Technology， Tianjin 300130， China
    Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles， Tianjin 300130， China     		300130
    CHEN Guang School of Mechanical Engineering， Hebei University of Technology， Tianjin 300130， China
    Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles， Tianjin 300130， China     		300130
    PENG Qianliang School of Mechanical Engineering， Hebei University of Technology， Tianjin 300130， China
    Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles， Tianjin 300130， China     		300130
    SUN Xiuxiu School of Mechanical Engineering， Hebei University of Technology， Tianjin 300130， China
    Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles， Tianjin 300130， China     		300130
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    Abstract:To solve the stress problems existing in the interference connection structure of the titanium-aluminum alloy turbine and the K418 alloy sleeve， the turbine rotor interference connection structure was taken as the research object. A profile and a stress prediction model of the interference connection structure were designed and established. And the influences of different profiles on the stress distribution state were analyzed based on the stress prediction model of the interference connection structure. The research results show that the prediction error of the interference connection structure stress prediction model for average contact stress is 0.67%， and the prediction error for the maximum Mises stress is 8.25%， which has high accuracy. The optimized design scheme of the profile obtained by using the interference connection structure stress prediction model reduces the maximum Mises stress of the turbine shaft by 42.01%， while the average contact stress only decreases by 10.22%. The reliability of the interference connection structure of the turbocharger turbine rotor is significantly improved.
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