Optimization of encapsulation for electric drive units: An experimental approach to predict insertion loss

Abstract

Considering from the environment stand point and usage, the trend of electric ve hicles has been on the rise and is certainly developing as the future of automotive industry. With the increasing customer expectations on the comfort and driving experience, the noise, vibration and harshness (NVH) play an important role in the design and launch of a vehicle. With the advent of electric vehicles, the challenges are different when compared to a conventional internal combustion (IC) engine. The use of Electric Drive Units (EDU) makes the operation less noisy as compared to an IC engine, but it leads to other high frequency noises which are picked up by the human ears inside the cabin of the car. This makes the encapsulation of the EDU, an important part of the electric vehicle’s NVH package. The aim of this thesis is to investigate if, an empirical model can be built to predict the insertion loss by systematic variation of certain control parameters. The parameters considered are sound absorption coefficient (α), sound transmission loss (dB) and percentage (%) of coverage of the encapsulation. In the first phase, certain configurations of foam layer, mass layer and carrier layer are built and are called as samples (35 samples). These samples are tested on the impedance tube and characterized for absorption coefficient and transmission loss values. In the second phase, five different encapsulations are built and tested on the EDU for insertion loss (IL) values along with percentage (%) coverage variation. The selection of samples for building the encapsulations from impedance tube results is based on variation of the values (good/average/poor) considering the end goal of model building. A high frequency driver with a hose is used as the noise source which is fed into the EDU exciting it internally. White noise is used to excite all frequency components with equal intensity. As it is an experimental approach, there are measurement uncertainties present and this has been addressed by performing repeatability study in order to achieve confidence and reliability on the results. The results obtained from the EDU measurements lay the foundation to form an empirical equation through linear regression analysis. This equation will finally be used to predict the insertion loss of the encapsulations. In the future, this work will help to give a prior idea of the encapsulation performance and ensure that the end product is a cost effective and acoustically efficient EDU encapsulation.