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The dynamic properties of disc rotor play important role in the NVH performance of a disc brake system. Disc rotor in general is a centrosymmetric structure. It has many repeated-root modes within the interested frequency range and they may have significant influence on squeal occurrence. A pair of repeated-root modes is in nature one vibration mode. However, in current complex eigenvalue analysis model and relevant analysis methods, repeated-root modes are processed separately. This may lead to contradictory result. This paper presents methods to deal with repeated-root modes in substructure modal composition (SMC) analysis to avoid the contradiction. Through curve-fitting technique, the modal shape coefficients of repeated-root modes are expressed in an identical formula. This formula is used in SMC analysis to obtain an integrated SMC value to represent the total influence of two repeated-root modes.

In order to reduce the vibration energy transferred from engine to the chassis of a vehicle and improve the riding comfortability of the vehicle, a new semi-active controlled hydraulic mount is developed which could adjust the vibration isolating effect at wide frequency range. The dynamic characteristic of the new mount could be changed through adjusting the cross-sectional area of its inertia channel. The control strategy of the mount is based on a great deal of engine tests. Test results of the semi-active mount on an engine test bench show that it could optimize the isolation effect according to engine''s working condition.

This paper first discusses the principles of how to identify whether a time series has chaotic characteristics, and explores a method of finding out the embedding dimension of a time series. Then Grassberger-Procaccia (G-P) algorithm is adopted to calculate correlative dimension. After the validity of G-P algorithm is confirmed using several traditional strange attractors, it is applied to calculate the fractal dimension of some vibration signals of an automotive transmission. This article presents how to apply chaos and fractal theories to diagnose the wearing of ball bearings in automotive transmissions based on the analysis of the transmission acceleration vibration signals. The results show that the vibration signals of automotive transmissions have fractal nature. There are certain correlations between a bearing's condition and the fractal dimension of its vibration signal.

A coupled vibro-acoustic of a compressor modeling process was demonstrated for predicting the acoustic radiation from a vibrating compressor structure based on dynamic response data. FEM based modal analysis of the compressor was performed and the result was compared with experimental data, for the purpose of validating the FE model. Modal based force response analysis was conducted to calculate the compressor's surface vibration velocity on radiating structure, using the load which caused by mechanical excitation as input data. In addition, due to the coolant had oscillating gas pressure, the gas pulsed load was also considered during the dynamic response analysis. The surface vibration velocity solution of the compressor provided the necessary boundary condition input into a finite element/boundary element acoustic code for predicting acoustic radiation.

This paper presents a road classifier based on the system response with consideration of the tire enveloping. The aim is to provide an easily applicable yet accurate road classification approach for automotive engineers. For this purpose, tire enveloping effect is firstly modeled based on the flexible roller contact (FRC) theory, then transfer functions between road input and commonly used suspension responses i.e. the sprung mass acceleration, unsprung mass acceleration, and rattle space, are calculated for a quarter vehicle model. The influence of parameter variations, vehicle velocity, and measurement noise on transfer functions are comprehensively analyzed to derive the most suitable system response thereafter. In addition, this paper proposes a vehicle speed correction mechanism to further improve the classification accuracy under complex driving conditions.

This paper provides an investigation to improve vehicle powertrain NVH performance via modification of excitation and radiation system of powertrain. First of all, considering different excitation mechanisms of the powertrain, the excitation forces are analyzed. The FEM/BEM coupled analysis and the acoustic transfer vector (ATV) calculation as well as panel contribution analysis are applied to investigating the acoustic characteristics of the powertrain. Then a hybrid approach which couples the transmission gear profile modification for attenuating gear system excitation and the transmission housing modification for reducing transmission housing noise radiation is proposed to improve powertrain NVH performance. Experiment validation is conducted in order to assess the modified results. The assessment shows that this hybrid approach can effectively predict and reduce powertrain noise and vibration.

This research examined the focused design, elastic design, energy decoupling, and torque roll axis (TRA) decoupling methods for mount optimization design. Requiring some assumptions, these methods are invalid for some load conditions and constraints. The linearity assumption is advantageous and simplifies both design and optimization analysis, facilitating engineering applications. However, the linearity is rarely seen in real-world applications, and there is no practical method to directly measure the reaction forces in the three locally orthogonal directions, preventing validation of existing methods by experimental results. For nonlinear system identification, there are additional challenges such as unobservable internal variables and the uncertainty of measured data.

Flash boiling has drawn much attention recently for its ability to enhance spray atomization and vaporization, while providing better fuel/air mixing for gasoline direct injection engines. However, the behaviors of flash boiling spray with multi-component fuels have not been fully discovered. In this study, isooctane, ethanol and the mixtures of the two with three blend ratios were chosen as the fuels. Measurements were performed with constant fuel temperature while ambient pressures were varied to adjust the superheated degree. Macroscopic and microscopic characteristics of flash boiling spray were investigated using Diffused Back-Illumination (DBI) imaging and Phase Doppler Anemometry (PDA). Comparisons between flash boiling sprays with single component and binary fuel mixtures were performed to study the effect of fuel properties on spray structure as well as atomization and vaporization processes.

The spray structure and vaporization processes of flash-boiling sprays in a constant volume chamber under a wide range of superheated conditions were experimentally investigated by a high speed imaging technique. The Engine Combustion Network’s Spray G injector was used. Four fuels including gasoline, ethanol, and gasoline-ethanol blends E30 and E50 were investigated. Spray penetration length and spray width were correlated to the degree of the superheated degree, which is the ratio of the ambient pressure to saturated vapor pressure (pa/ps). It is found that parameter pa/ps is critical in describing the spray transformation under flash-boiling conditions. Three distinct stages namely the slight flash-boiling, the transition flash-boiling, and the flare flash-boiling are identified to describe the transformation of spray structures.

Gear rattle noise is one of the important characteristics of manual and dual-clutch transmission，it is generated by the impact of unloaded meshing gear pairs in the transmission due to engine torsional vibration. Based on a front-drive manual transmission and a five dynos drivetrain NVH test bench with high-speed sine wave generator function, this paper designs an experimental program suitable for transmission rattle noise. By driving dynamometer to simulate the torque fluctuation of real engine, the main research is to study the characteristics of the transmission rattle noise under different excitation amplitudes and different excitation frequencies, and the sensitivity of rattle noise under different gears, different oil temperatures, different excitation amplitudes and excitation frequencies is analyzed. Finally, the transmission maps of rattle noise in different gears can be obtained.

Wiper noise generated in the wiping process is one of the main influence factors affecting the driving comfort. Since the dynamic contact pressure of the contact between a blade and a windshield glass is difficult to be measured, it is also difficult to predict the degree of the wiper noise. In this paper, in the view of the reversal noise problem of a passenger-vehicle windscreen wiper system, the system dynamic models of the both wipers on the sides of the driver and copilot were built as considering the blade deformation and the elastic contact between the blades and the windscreen glass, including the crank pivot, the four linkage mechanism, the wiper blades, the wiper arms and the windscreen glass. The motion of the wiper system and the pressure distributions between the blades and the windscreen glass were analyzed under the half-dry condition.

HTL is a kind of biodiesel converted from wet biowaste via hydrothermal liquefaction (HTL), which has drawn increasing attention in recent years due to its wide range of raw materials (algae, swine manure, and food processing waste). However, from the previous experiments done in a constant volume chamber, it was observed that the presence of 20% of HTL in the blend produced as much soot as pure diesel at in chamber environment oxygen ratio of 21%, and even more soot at low oxygen ratios. It was also observed that n-butanol addition could reduce the soot emission of diesel significantly under all tested conditions. In this work, the spray and combustion characteristics of HTL and diesel blends with n-butanol added were investigated in a constant volume chamber. The in-chamber temperature and oxygen ranged from 800 to 1200 K and 21% to 13%, respectively, covering both conventional and low-temperature combustion (LTC) regimes.

The fusion of multi-modal perception in autonomous driving plays a pivotal role in vehicle behavior decision-making. However, much of the previous research has predominantly focused on the fusion of Lidar and cameras. Although Lidar offers an ample supply of point cloud data, its high cost and the substantial volume of point cloud data can lead to computational delays. Consequently, investigating perception fusion under the context of 4D millimeter-wave radar is of paramount importance for cost reduction and enhanced safety. Nevertheless, 4D millimeter-wave radar faces challenges including sparse point clouds, limited information content, and a lack of fusion strategies. In this paper, we introduce, for the first time, an approach that leverages Graph Neural Networks to assist in expressing features from 4D millimeter-wave radar point clouds. This approach effectively extracts unstructured point cloud features, addressing the loss of object detection due to sparsity.