Search Results

In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.

A comprehensive investigation was carried out in order to develop the idle sound quality for diesel V6 engine when the engine development process is applied to power-train system, which included new 8-speed automatic transmission for breaking down the noise contribution between the mechanical excitation and the combustion excitation. First of all, the improvement of dynamic characteristic can be achieved during the early stages of the engine development process using experimental modal analysis (EMA) & the robust design of each engine functional system. In addition, the engine structural attenuation (SA) is enhanced such that the radiated combustion noise of the engine can be maintained at a target level even with an increased combustion excitation. It was found that the engine system has better parts and worse parts in frequency range throughout the SA analysis. It is important that weak points in the system should be optimized.