A New Strategy Optimization Method for Vehicle Active Noise Control Based on the Genetic Algorithm Gissing Tech. Company, Limited

Format:

Conference/Event

Author/Creator:

Li, Li, author.

Contributor:

Care, Melvyn

Chen, Xiaojun

Huang, Wei

Ruan, Hailin

Tian, Xiujie

Wentzel, Richard

Zheng, Changwei

Zhu, Keda

Conference Name:

Noise and Vibration Conference and Exhibition (2017-06-12 : Grand Rapids, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2017

Summary:

AbstractThe control strategy design of vehicle active noise control (ANC) relies too much on experiment experience, which costs a lot to gather mass data and the experimental results lack representation. To solve these problems, a new control strategy optimization method based on the genetic algorithm is proposed. First, a vehicle cabin sound field simulation model is built by sound transfer function. Based on the filtered-X Least Mean Squares (FX-LMS) algorithm and the vehicle cabin sound field simulation model, a vehicle ANC simulation model is proposed and verified by a vehicle field test. Furthermore, the genetic algorithm is used as a strategy optimization tool to optimize an ANC control strategy parameter set based on the vehicle ANC simulation model. The optimized results provide a reference for the ANC control strategy design of the vehicle

Notes:

Vendor supplied data

Publisher Number:

2017-01-1831

Access Restriction:

Restricted for use by site license