A New Strategy Optimization Method for Vehicle Active Noise Control Based on the Genetic Algorithm

Paper #:
  • 2017-01-1831

Published:
  • 2017-06-05
DOI:
  • 10.4271/2017-01-1831
Citation:
Li, L., Huang, W., Ruan, H., Tian, X. et al., "A New Strategy Optimization Method for Vehicle Active Noise Control Based on the Genetic Algorithm," SAE Technical Paper 2017-01-1831, 2017.
Pages:
6
Abstract:
The 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.
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