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Drivetrain noise from heavy off-road vehicles mainly includes engine noise, drive shaft noise, wheel-side gear noise, tire pattern noise etc. They are the main noise sources for such vehicles as they greatly influence the ride comfort of the passengers inside. This paper solved the drivetrain noise problems of a heavy off-road vehicle using the method of active noise control (ANC). Firstly, the vehicle is benchmarked and the noise problems are analyzed, while the noise sources are identified by analyzing the transmission principles of the drivetrain. Secondly, ANC strategies are made for the vehicle based on the noise profiles under various operating conditions. Thirdly, the multiple parameters for ANC are computed from simulations modeling the vehicle in idle, constant speed and acceleration respectively. Lastly, road tests are conducted using the multiple parameters from the simulations and a noise reduction of 2-4 dB can be achieved in the whole vehicle.

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.