18 research outputs found
An alternative close-proximity test to evaluate sound power level emitted by a rolling tyre
The noise emission of a rolling tyre is produced by different physical mechanisms generated during the
tyre-road interaction, being the main noise source of a vehicle when driving at high speeds. Diverse measurement
methods can be found in the literature to assess the rolling noise emission. In that sense, the
close-proximity (CPX) method allows to evaluate tyre/road sound level with at least two microphones
operating in the close field of the test tyre. This paper presents a new methodology, based on the CPX
method, which allows assessing the sound power level of the rolling tyre by introducing some changes
in the traditional close-proximity test. The methodology (named A-CPX) has been analytically and experimentally
validated, and is finally used to obtain the total tyre/road sound power level emitted by the
whole set of tyres of a vehicle
Inverse transfer path analysis, a different approach to shorten time in NVH assessments
This paper presents the design and implementation of a simplified method, based on the transmissibility
concept, for a noise path assessment, which allows a rapid and accurate analysis. The Inverse Transfer
Path Analysis aims to assess, and determine, the contribution of the critical paths, which are transmitting
structure-borne noises and vibrations, from the vehicle’s vibration sources to the driver’s ear.
The cabin noise transfer function, from the involved attachment points and directions, can be simultaneously
obtained by applying an impulsive noise source inside the cabin. This approach avoids the use of
other time consuming classic procedures.
The proposed methodology includes two types of tests, static condition tests in a semi-anechoic chamber
and operational tests on a roller bench. The results assessment comprises the analysis of the noise
contribution of each path, depending on the frequency and the vehicle speed range.
This publication introduces a novel NVH method proposed to study and identify noise transfer paths in
a car structure. The theoretical approach of the methodology, practical implementation, and obtained
results, are described in this work, as well as a methodology validation, to evidence the suitability of
the proposed method
A methodology for the extrapolation of coast-by noise of tyres from sound power level measurements
Traffic noise is one of the most predominant noise sources that affect citizens’ quality of life in urban
areas. The increasing presence of alternative powered vehicles, such as electric or hybrid vehicles, could
provide an improvement of such a situation due to the absence of internal combustion engines. However,
tyre/road noise is independent of the vehicle type and still exists in alternative powered vehicles. Hence,
efforts should focus also on reducing noise emission by means of new tyre designs. The tyre/road noise
emission of newly produced tyres is currently evaluated by the Coast-By method, and as a result the rolling
sound pressure level at the measuring distance, located 7.5 m away from the test vehicle is obtained.
Such an acoustic index provides a very representative data of the annoyance that a pedestrian located at
such distance could suffer. However, this value could be affected by external factors, such as environmental
conditions. For that reason, this paper presents a methodology for extrapolating the sound pressure
levels that are obtained in a Coast-By test, by means of the sound power level emitted by the specific
tyre/road combination evaluated. This methodology could serve as the basis for defining a universal
model to evaluate a tyre when rolling on a road, by using its sound power emission and predicting the
Coast-By sound pressure level
Gear sound model for an approach of a Mechanical Acoustic Vehicle Alerting System (MAVAS) to increase EV’s detectability
Hybrid-electric and electric vehicles significantly reduce noise road emissions. This noise mitigation also
causes a reduction in the sound detectability and therefore it increases the potential of causing accidents.
A suitable solution arises with the Acoustic Vehicle Alerting Systems (AVAS) emitting a warning sound to
alert pedestrians about the presence of a silent vehicle. This paper details an acoustic prediction model
capable of simulating the sound produced by a pair of spur dry gears used as a Mechanical Acoustic
Vehicle Alerting System (MAVAS). This proposal that tries to reproduce a sound closer to the mechanical
sound of a conventional vehicle would be used as an alternative to existing systems. The prediction
model developed is validated and consists in two consecutive parts: first, a dynamic model studies the
rattle of the gears, then, an analytical model reproduces the sound of each impact of the gear teeth.
This sound model makes it possible to characterize a proposed gear combination of the MAVAS, verifying
its compliance with the European legislation
Numerical sound prediction model to study tyre impact noise
Impact noise is one of the mechanisms of vibratory origin that constitutes tyre/road interaction noise.
When assessing a vehicle as a noise source, the impact sound mechanism is especially significant when
obstacles are present on the driving surface. This document aims to enhance understanding of the impact
noise phenomenon by presenting a two-step numerical model for studying the sound propagation of an
accelerated tyre impacting a flat, rigid, and reflective surface: Firstly, a dynamic analysis of the contact is
performed using the Finite Element Method. Then, the Boundary Element Method is used to perform an
acoustic analysis with the vibration of the tyre surface as the sound source. The model has been successfully
validated through a drop-test, where a tyre/rim assembly is dropped onto a ground surface. The validation
was determined by comparing the predicted Sound Pressure Level measurements to those
obtained from a circular microphone structure at various points during the drop-test
Assessing the Impact of Attendance Modality on the Learning Performance of a Course on Machines and Mechanisms Theory
University education approaches related to the field of science, technology, engineering
and mathematics (STEM), have generally particularized on teaching activity and learning programs
which are commonly understood as reoriented lessons that fuse theoretic concepts interweaved with
practical activities. In this context, team work has been widely acknowledged as a means to conduct
practical and hands-on lessons, and has been revealed to be successful in the achievement of exercise
resolution and design tasks. Besides this, methodologies sustained by ICT resources such as online
or blended approaches, have also reported numerous benefits for students’ active learning. However,
such benefits have to be fully validated within the particular teaching context, which may facilitate
student achievement to a greater or lesser extent. In this work, we analyze the impact of attendance
modalities on the learning performance of a STEM-related course on “Machines and Mechanisms
Theory”, in which practical lessons are tackled through a team work approach. The validity of the
results is reinforced by group testing and statistical tests with a sample of 128 participants. Students
were arranged in a test group (online attendance) and in a control group (face-to-face attendance)
to proceed with team work during the practical lessons. Thus, the efficacy of distance and in situ
methodologies is compared. Moreover, additional variables have also been compared according to
the historical record of the course, in regards to previous academic years. Finally, students’ insights
about the collaborative side of this program, self-knowledge and satisfaction with the proposal have
also been reported by a custom questionnaire. The results demonstrate greater performance and
satisfaction amongst participants in the face-to-face modality. Such a modality is prooven to be
statistically significant for the final achievement of students in detriment to online attendance
Acoustic Directivity and Detectability of Electric Powered Two-Wheelers
Since motorcycles are one of the main sources of noise in urban environments, the use of electric powered two-wheelers may contribute to the improvement of soundscapes in Smart Cities. However, quiet vehicles can lead to an increased risk of accident for pedestrians and other drivers. In order to assess the noise generated by powered two-wheelers and their detectability, five different low capacity motorcycles were measured in a pass-by noise test. The measurements were performed at different speeds using a linear microphone array and a dummy head. The sound directivity radiated by the moving sources was studied with a microphone array. To establish the detectability of powered two-wheelers, thirty-seven subjects participated in an auditory test consisting on a virtual road-crossing scenario. The subjects had to detect the approaching of a vehicle at 20 km/h. The results showed a significant reduction in the sound pressure level emitted by electric motorcycles at low-speed, as well as a notable increase in sound directivity with velocity. The reaction time obtained for the detection of electric powered two-wheelers was higher compared to the traditional propulsion ones. The results highlighted the risk posed by this kind of electric vehicles for pedestrians