Evaluation of electric vehicle sounds and new concepts regarding speed-dependency

Steinbach, Lisa; Altınsoy, M. Ercan; Atamer, Serkan; Rosenkranz, Robert

doi:10.1121/1.4988673

Cited by 2 publications

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“…The environmental noise impact of additive sounds for EVs (Weinandy et al, 2019) is also a topic of considerable discussion. Steinbach et al (2017) used artificial neural network (ANN) detectors to model listener responses to show that the change of the speed-scaling of additive sounds greatly influences the detection time. The authors also conclude that the use of ANN provides a model that can predict the annoyance or the warning effectiveness of future electric vehicle sounds.…”

Section: Introductionmentioning

confidence: 99%

Probability of detection of electric vehicles with and without added warning sounds

Roan

Neurauter

Song

et al. 2021

The Journal of the Acoustical Society of America

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Detection performance as a function of distance was measured for 16 subjects who pressed a button upon aurally detecting the approach of an electric vehicle. The vehicle was equipped with loudspeakers that broadcast one of four additive warning sounds. Other test conditions included two vehicle approach speeds [10 and 20 km/h (kph)] and two background noise conditions (55 and 60 dBA). All of the test warning sounds were designed to be compliant with FMVSS 141 proposed regulations in regard to the overall sound pressure levels around the vehicle and in 1/3 octave band levels. Previous work has provided detection results as average vehicle detection distance. This work provides the results as probability of detection (Pd) as a function of distance. The curves provide insight into the false alarm rate when the vehicle is far away from the listeners as well and the Pd at the mean detection distance. Results suggest that, although the test sounds provide an average detection distance that exceeds the National Highway Traffic Safety Administration minimum at the two test speeds, Pd is not always 100% at those distances, particularly at the 10 kph. At the higher speed of 20 kph, the tire-road interaction noise becomes dominant, and the detection range is greatly extended. V

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Section: Introductionmentioning

confidence: 99%

Probability of detection of electric vehicles with and without added warning sounds

Roan

Neurauter

Song

et al. 2021

The Journal of the Acoustical Society of America

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The Evaluation of Conventional, Electric and Hybrid Electric Passenger Car Pass-By Noise Annoyance Using Psychoacoustical Properties

Altınsoy

2022

Applied Sciences

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Road traffic noise is one of the most prominent sources of urban noise pollution. Recently, as a result of the electrification of vehicles, lower noise levels are expected in urban areas at speeds below 50 km/h. The commonly used physical descriptor, the A-weighted sound pressure level, does not sufficiently characterize the perceived annoyance of either combustion engine or electric passenger car pass-by noises. Psychoacoustical descriptors are advantageous for characterization purposes. The objective of this study was to evaluate the perceived annoyance caused by the noise from internal combustion engine, electric, and hybrid passenger cars using psychoacoustical properties. To achieve this objective, the following steps were conducted. First, the binaurally recorded sounds of 40 cars from different brands with different motorization were presented to the subjects who indicated the intensity of their perceived annoyance on a quasi-continuous scale. Second, the signal and psychoacoustical properties of the recorded sounds were analyzed. Third, a new annoyance index was developed, based on annoyance judgments and signal and psychoacoustical properties, to characterize the annoyance caused by pass-by noises. One of the novel aspects of this study is the consideration of not only the pass-by sounds of the internal combustion engine passenger cars, but also the pass-by sounds of hybrid and electric passenger cars. An acceleration from idle to a target speed of 50 km/h was selected as a traffic pass-by situation, which differs from those considered in previous studies. The results of the study show that psychoacoustical properties, such as loudness, tonality, roughness, and fluctuation strength, are very useful to characterize the annoyance perception, which is caused by single passenger car pass-by sounds in the above mentioned traffic situation. The developed index, which is a weighted combination of chosen psychoacoustical properties, can be very useful for traffic planning and traffic noise prevention measures.

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Evaluation of electric vehicle sounds and new concepts regarding speed-dependency

Cited by 2 publications

References 0 publications

Probability of detection of electric vehicles with and without added warning sounds

Probability of detection of electric vehicles with and without added warning sounds

The Evaluation of Conventional, Electric and Hybrid Electric Passenger Car Pass-By Noise Annoyance Using Psychoacoustical Properties

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