New Approach for Road Induced Noise Prediction in Battery Electric Vehicles

Abstract

<div class="section abstract"><div class="htmlview paragraph">In general, in-cabin booming noise is low frequency (20 Hz∼300 Hz) phenomenon which excites the cabin structure mainly due to excitations from the powertrain, exhaust system, road loads, etc. When a vehicle drives over road seams or a bumpy surface, low-frequency drumming noise is generated, causing driver discomfort. The generation of drumming noise is due to road irregularities, transferred and amplified through the vibration characteristics of the suspension, body frame, and body panels, as well as the acoustic characteristics of the vehicle interior. It is therefore difficult to take measures to get rid of drumming, after the basic vehicle construction has been finalized. The regular practice in vehicle development is finite element method (FEM) to obtain acoustical transfer functions of the body, and multi body simulation to get suspension load characteristics. The full vehicle simulation needs more time for analysis and extracting data. So traditional computational aided engineering (CAE) will not support development timeline. Market has become very dynamic, benchmark changes very often, so getting complete data is difficult for very accurate analysis in ‘early to market’ project timeline. Most of the automotive companies are using computational tools for predicting road noise in simulation phase. But with the help of method, we developed can predict road noise at early design stage itself. It is a novel hybrid tool which can give strong directional results in comparatively lesser time.</div><div class="htmlview paragraph">This user-friendly hybrid tool is developed for predicting and improving road noise at early stage with limited data, especially for new age battery electric vehicle. The inputs used during the initial stage of the program are vibration data of benchmark vehicle at body attachment points, targets, or simulation data (DPDS, NTF), etc. By the proposed methodology, overall trend of road noise can be predicted. In addition to that critical paths can be identified by using transfer path analysis. Once the project/program matures, we can use physically measured data (DPDS &amp; NTF) of the trimmed body and perform the robust root cause analysis to identify the critical paths. Based upon the analysis, modifications to be made on actual body structure for effective drumming reduction. Hence new hybrid approach is proposed, which consists of mathematical model and design philosophy for better in cabin noise. It is worth to note that there are some limitations in the tool and results from the calculations such as granularity of benchmark test data availability, accurate trimmed body level test or simulation data.</div></div>