Search Results

To reduce dependence on petroleum resources and pollution to the natural environment, electric vehicles as new energy vehicles have become the focus of various original equipment manufacturers and component companies. At the same time, the NVH performance of electric vehicles is the focus of attention of automobile companies, and higher requirements are placed on sound-proof packaging, which is an important part of reducing automobile noise. Compared with traditional internal combustion engine vehicles, the biggest difference between electric vehicles (EV) is their electric drive system. High-frequency noise is generated when the electric motor is used as a power device. When there is no engine noise, the problem of electric drive noise is more obvious. Generally, an sound package is used to block the transmission path of noise. Therefore, an sound package is selected to cover the electric motor to reduce the impact of noise on the interior of the vehicle.

In the early stages of a vehicle program, sound package design is significantly complicated by numerous competing requirements including cost, weight, acoustical targets and packaging space. The problem is further convoluted due to a limited definition of the vehicle at this time. In this article, a Statistical Energy Analysis (SEA) model of the vehicle is created based on a gross description of the vehicle architecture. A large material database of commonly used sound package configurations is then linked to the SEA model. Genetic Algorithms (GA) are finally applied to optimize the sound package design to satisfy cost, weight, acoustical targets and packaging requirements in the vehicle design.