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A New Strategy Optimization Method for Vehicle Active Noise Control Based on the Genetic Algorithm
ISSN: 0148-7191, e-ISSN: 2688-3627
Published June 05, 2017 by SAE International in United States
Annotation ability available
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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- Longchen Li - Gissing Tech. Co., Ltd.
- Wei Huang - Gissing Tech. Co., Ltd.
- Hailin Ruan - Gissing Tech. Co., Ltd.
- Xiujie Tian - Gissing Tech. Co., Ltd.
- Keda Zhu - Gissing Tech. Co., Ltd.
- Melvyn Care - Gissing Tech. Co., Ltd.
- Richard Wentzel - Gissing Tech. Co., Ltd.
- Xiaojun Chen - Gissing Tech. Co., Ltd.
- Changwei Zheng - Gissing Tech. Co., Ltd.
CitationLi, 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, https://doi.org/10.4271/2017-01-1831.
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