Efficient tuning of active sound design in electric vehicles - An interactive validation approach

The implementation of active sound design models in a target vehicle requires careful tuning of all synthetic sound elements with respect to existent vehicle interior noise, current driving conditions and general driving styles. Besides the creative aspects in sound design, this tuning process is highly time-consuming. It must be ensured that load feedback, speed feedback and general interactivity with the synthetic sound meet the driver's expectations and match the intended emotional expressions of the sound concept. Testing the tuning parameters in real vehicles requires access to the vehicle prototype and all involved system components, which is often not granted in early development stages. A key approach to overcome this difficulty is the application of acoustic driving simulator technology, directly linked to the main tuning parameters. Combining this methodology with an efficient procedure for perceptive assessment of the sound design model, an interactive approach to active sound design is established. This paper discusses current progress in the field of efficient tuning of active sound design models, presenting a case study for a high-performance electric vehicle.

Authors

Institutions

Publication Details

Journal
NOISE-CON proceedings
Published
2024-10-04
DOI
https://doi.org/10.3397/in_2024_2624
Primary Topic
Vehicle Noise and Vibration Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient tuning of active sound design in electric vehicles - An interactive validation approach

Thiago Henrique Gomes Lobato, Fabian Kamp, Stefan Hank, Lars HEINRICHS
1 links
NOISE-CON proceedings
Vehicle Noise and Vibration Control
article

Efficient tuning of active sound design in electric vehicles - An interactive validation approach

Thiago Henrique Gomes Lobato, Fabian Kamp, Stefan Hank, Lars HEINRICHS
article en

Abstract

The implementation of active sound design models in a target vehicle requires careful tuning of all synthetic sound elements with respect to existent vehicle interior noise, current driving conditions and general driving styles. Besides the creative aspects in sound design, this tuning process is highly time-consuming. It must be ensured that load feedback, speed feedback and general interactivity with the synthetic sound meet the driver's expectations and match the intended emotional expressions of the sound concept. Testing the tuning parameters in real vehicles requires access to the vehicle prototype and all involved system components, which is often not granted in early development stages. A key approach to overcome this difficulty is the application of acoustic driving simulator technology, directly linked to the main tuning parameters. Combining this methodology with an efficient procedure for perceptive assessment of the sound design model, an interactive approach to active sound design is established. This paper discusses current progress in the field of efficient tuning of active sound design models, presenting a case study for a high-performance electric vehicle.

NOISE-CON proceedingsVol. 270(11)
HEAD Acoustics (Germany) (DE), RWTH Aachen University (DE)
Sustainable cities and communities
Openalex Percentile: Top 82%
Vehicle Noise and Vibration Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Efficient tuning of active sound design in electric vehicles - An interactive validation approach — Thiago Henrique Gomes Lobato, Fabian Kamp, et al. · NOISE-CON proceedings (2024) | TGRS Research Map | TGRS