Sound Package Optimization of Passenger Bus Using Hybrid Statistical Energy Analysis Mahindra Truck and Bus Limited

Format:

Book

Conference/Event

Author/Creator:

Bhangale, Rajesh, author.

Contributor:

Chavan, Pruthviraj

shinde, Nikhil

SOUNDATTE, Nitin

Conference Name:

Symposium on International Automotive Technology (2021-09-29 : Pune, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

Increasing Demands for high fuel efficiency requires imperative light weighting of automotive structure, but this adversely affects the NVH performance since transfer path of noise sources like engine, road, wind to vehicle interior through the panels weakens. Also increasing customer centric approach drives the urge to provide world-class comfort that is cost-effective too. Sound Packaging helps us to optimize these transfer paths through the panel, and can effectively complement efforts of Testing Team, by reducing the redundant iterations required to conclude to most effective trims to be put on. Statistical Energy Analysis Based Simulations is employed for carrying out these iterations at the Virtual Validation Gateway itself. Baseline Vehicle is fully modeled as per the criterion required by inherent SEA theory and simulated within frequency range of 200Hz-10KHz. Trims application areas are identified and layered Trims are applied at these locations to compare its effectiveness, in terms of Transmission Loss or Sound Pressure Level at Driver Ear Cavity. Evaluating performance of trims in terms of Noise attenuation at the test validation stage by varying the Material grade in terms of biot parameters of flow resistivity, tortuosity, density, along with the thickness is a repetitive monotonous task involving does not justify crucial cost and time exhaustion in product development. Statistical Energy Analysis is the dedicated simulation methodology that upfront aids validation by ranking, trims in consideration, positively impacting first time right approach. Hybrid SEA further builds the confidence in SEA Model Building by availing the deterministic results from FEA to predict the model behavior in higher frequency range

Notes:

Vendor supplied data

Publisher Number:

2021-26-0268

Access Restriction:

Restricted for use by site license