Mechanical Engineering

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https://hdl.handle.net/10323/11894

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Browsing Mechanical Engineering by Subject "Active noise control"

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    A Vibro-acoustic CAE Approach for Active Noise Control Prediction
    (2024-01-01) Abbas, Ahmad A; Mourelatos, Zissimos P; Latcha, Michael; Yang, Lianxiang; Drignei, Dorin; Sturla, Francisco
    This research focuses on a comprehensive analysis and prediction of Active Noise Cancellation (ANC) system performance in vehicles, with particular emphasis on the structural and acoustic aspects. While acknowledging the significance of electronic components and control algorithms in ANC systems, this study focuses on predicting the ANC performance using a full vibro-acoustic vehicle model. Additionally, the integration of noise management supplier control systems with CAE ANC models is explored. The development of a predictive CAE methodology is demonstrated using a road noise cancellation example. The process involves several steps including the structural behavior of the Trim Body in White (TBIW) structure, the development of a vehicle cavity model, the derivation of accurate speaker models, the assessment of speaker integration with vehicle doors, and the development of Transfer Paths (TP) from speakers to microphones. A novel methodology is presented to quantify the door stiffness requirements for optimal speaker ANC performance, incorporating substructuring methods and physical testing. The accuracy of the developed CAE models is validated using physical testing of circular and oval-shaped speakers integrated into vehicle doors and the calculation of transfer paths between each door speaker and microphone locations is demonstrated. The significance of microphone and speaker locations relative to driver or passenger ear positions highlights their influence on ANC performance. Finally, a controller is developed to test the CAE model and illustrate its functionality using a supplier’s controller for sound management. Overall, this research establishes a reliable vibro-acoustic CAE ANC model capable of predicting ANC system performance accurately by integrating a full vehicle vibro-acoustic model with an ANC controller. Such a predictive capability enables optimization and enhancement of vehicle performance for noise cancellation, unlocking its full potential in mitigating vehicle noise.