Abstract
In the frame of the research project "Hybrid DRIVE" aimed at investigating the impact of hybrid power trains on vibroacoustic comfort, dedicated test campaigns were carried out on different models of hybrid vehicles. A first experiment involving a Toyota Prius revealed how the peculiarity of such a design concept requires special attention both for the execution of NVH tests and the analysis of results. Multiple rotating engines introduce rpm dependent excitations whose interaction may lead to acoustic discomfort for some operating conditions. The electronic control system mastering the power delivery improves power train performance in terms of efficiency and fuel consumption, but it causes that continuous variations of rotating speeds occur - a swept-multi-sine type of excitation - that excite the acoustic cavity modes.
This observation led to the application of a recently developed algorithm for output only Modal Analysis (i.e. the Operational PolyMAX) as an advanced tool for fast identification of vehicle cavity resonances occurring in operating conditions. Operational Modal Analysis is a technique that allows estimating the modal parameters of a system under unknown excitation. In theory the unknown excitation must approximate white noise but a large industrial practice has shown that a flat excitation spectrum suffices, and that Operational Modal Analysis can also be applied to vibroacoustic responses generated by sine sweep excitation.
In order to successfully apply the Operational PolyMAX, an accurate and fast order tracking algorithm is required that provides the relevant information on the operational excitation. In this respect, a novel algorithm was developed that allows automatic order tracking from noise signals recorded in the vehicle cavity. The resulting analysis method is implemented as threestep process. First, an automatic order detection algorithm is used to identify the significant engine orders in the measured data. These orders are then accurately tracked in both amplitude and phase by using an advanced time-varying DFT Order Tracking method. The result of this operation is the derivation of a set of sweeping loads that are actually applied to the vehicle in operating conditions. Finally, the PolyMAX modal parameter estimation algorithm is applied to the tracked engine orders to identify the system resonances.
The method is illustrated and discussed using measured in-vehicle sound data and tacho pulse signal recorded on several 4-cylinder cars, including hybrid ones, during run-up conditions. Were available, CAN bus data directly recorded from the vehicle CAN network are used to validate the RPM automatic extraction tool. The obtained resonance identification results are compared with those coming out of the traditional spectrum-based method for Operational Modal Analysis. While the spectrum-based method suffers from "end-of-order" artefacts showing up in the frequency spectrum as additional non-physical peaks, the new order-based approach shows better performances and allows identifying system´s operating resonances from multi-sine sweep excitation.
Finally, JTFA analysis is used to assess transient phenomena causing relevant comfort issue in quieter hybrid power trains. The combination of the described tools paves the way to a faster and more accurate assessment of vehicle vibroacoustic comfort.
Keywords:Hybrid power train, noise feature extraction, operational modal analysis