The powertrain mount is an important component, which reduces the vibrations generated from the powertrain. Vibration isolation is achieved with help of modal separation by predicting the kinetic energy fraction (KEF) and natural frequency (NF) at each mode. The soft mounts reduce vibrations transferred from the engine to the chassis, but if stiffness is very low, the displacement of the mount will be high, and hence, the lifetime of the mount will be less. Vibration isolation using a powertrain mount is a compromise between the displacement of the mount, displacement of the center of gravity of the powertrain, KEF, and NF. In this paper knowledge-based engineering (KBE) application methodology is explained to initially find out the optimum values of mount parameters using permutation and the combination of mount stiffness, mount angle, and mount locations. Using these permutations and combinations, KEFs, NF, and the displacement of the center of gravity of the powertrain are found. At different loading conditions of the powertrain, results are sorted out based on the highest KEFs and lowest displacement of the center of gravity of the powertrain. Using this approach, the best mount stiffness, mount angle, and mount locations are decided, which ultimately gives a good vibration isolation. Integration of the calculated results with computer-aided design (CAD) software provides the engine envelope with calculated displacement which is used for packaging the engine compartment. All of the above features are verified with a test result and modifications with case studies are proposed to improve the noise, vibration, and harshness (NVH). The objective of this paper is to apply a KBE approach in powertrain mounting system (PMS) design to improve the productivity of the PMS design engineer and accelerate the design and development process. A KBE approach helps to increase the productivity and accuracy of mount designing parameters during the early design stage without the need for computer-aided engineering (CAE) software.


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    Titel :

    Knowledge-Based Approach for Optimized Powertrain Mounting Layout


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    Automotive Technical Papers ; 2022



    Erscheinungsdatum :

    2022-11-25




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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