4 research outputs found
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
Assessment of warning sound detectability for electric vehicles by outdoor tests
Electric Vehicles (EV) are characterized by a high reduction of the acoustic emission. The absence of warning sounds entails a risk situation for pedestrians. The previous research is focused on detectability of warning sounds in different noise environments. These experiments are performed indoors, where a pedestrian’s conditions are not similar to real road crossing. Drivers’ behaviour study demonstrated that different environments and workload have influence on reaction time. Consequently, this paper proposes a methodology for the analysis of detectability of real warning sound using a dynamic subject. The sample was composed by 65 participants walking around a pedestrian area. Participants had to react when they detected a vehicle approaching. The subject’s response was affected by background noise, therefore, this parameter was measured. The results establish that power levels have influence on the detectability. There is an optimum power level which improves efficiency of vehicle detection. Besides, warning sound features and learning effect, based on previous experience, have influence on subject response
Tecnicas experimentales para el analisis sonoro y vibratorio de vehiculos electricos e hibridos
El uso de tecnicas experimentales para el analisis de ruido y vibraciones (en ingles Noise Vibration and Harshness, NVH) en vehiculos convencionales de combustion interna (ICEV) ha propiciado avances tecnicos asociados a las caracteristicas mecanicas y aerodinamicas de los mismos, asi como una mejora
significativa en sus condiciones de confort interior. Asi mismo, la creciente demanda social de vehiculos hibridos-electricos (HEV) y electricos (EV), unido a sus caracteristicas peculiares en materia de ruido y vibraciones, promueven la necesidad de estudiar y desarrollar tecnicas experimentales para la correcta evaluacion sonora de sus
fuentes, el estudio de su transmisibilidad estructural y su radiacion sonora al exterior. El presente articulo realiza un analisis de diferentes tecnicas experimentales adaptadas y
puestas en marcha para el estudio NVH en el interior de vehiculos electricos, nuevas tecnicas de ensayo para materiales ligeros empleados en cabina, asi como sistemas de
medicion para la evaluacion de los niveles exteriores de radicacion de esta tipologia de vehiculos
Assessment of warning sound detectability for electric vehicles by outdoor tests
Electric Vehicles (EV) are characterized by a high reduction of the acoustic emission. The absence of warning sounds entails a risk situation for pedestrians. The previous research is focused on detectability of warning sounds in different noise environments. These experiments are performed indoors, where a pedestrian’s conditions are not similar to real road crossing. Drivers’ behaviour study demonstrated that different environments and workload have influence on reaction time. Consequently, this paper proposes a methodology for the analysis of detectability of real warning sound using a dynamic subject. The sample was composed by 65 participants walking around a pedestrian area. Participants had to react when they detected a vehicle approaching. The subject’s response was affected by background noise, therefore, this parameter was measured. The results establish that power levels have influence on the detectability. There is an optimum power level which improves efficiency of vehicle detection. Besides, warning sound features and learning effect, based on previous experience, have influence on subject response