A Modeling Method for Continuous Active Synthetic Sound During Dynamic Operating Condition Transitions in Electric Vehicles
- 1College of Mechanical:Engineering & Automation, Fuzhou University, Fuzhou 350108, China
- 2Zhejiang Geely Holding Group Co., Ltd., Hangzhou 310051, China
- 3School of Automotive and Transportation Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China
Abstract
With the increasing adoption of electric vehicles, the in-vehicle active sound generation (ASG) system has emerged as a key technology for shaping brand-specific acoustic characteristics and enhancing the driving and riding experience. However, during dynamic operational transitions such as vehicle acceleration and deceleration, existing systems are often affected by issues including discontinuous and distorted synthesized sounds, which lack coherence and significantly compromise sound quality and auditory comfort. In response to the aforementioned issues, this paper aims to enhance the coherence of synthesized sound in the ASG system by proposing an active sound control method for adaptive and variable operating conditions. Firstly, a synthesis acoustic coherence algorithm based on trigonometric periodic functions (SACA_TPF) is designed to enhance the smoothness of transitions in both the time and frequency domains of the synthesized sound. Subsequently, a simulation method for the variable operating conditions of the ASG system is proposed, along with a further developed optimization method for enhancing the coherence of the synthesized sounds. Simulation results indicate that the proposed method significantly enhances the coherence of the synthesized sound generated by the ASG system during dynamic condition transitions, effectively preventing sound discontinuities and ensuring smooth acoustic transitions. This research is of significant practical value in terms of enhancing brand acoustic recognition in electric vehicles and improving user auditory experience.
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BibTeX
@article{xie2026modeling,
title = {{A Modeling Method for Continuous Active Synthetic Sound During Dynamic Operating Condition Transitions in Electric Vehicles}},
author = {Liping Xie and Longcheng Liu and Yi Sun and Songchun Zou},
journal = {Mathematics},
year = {2026},
month = sep,
doi = {10.3390/math14193558},
url = {https://www.mdpi.com/2227-7390/14/19/3558},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A Modeling Method for Continuous Active Synthetic Sound During Dynamic Operating Condition Transitions in Electric Vehicles
AU - Liping Xie
AU - Longcheng Liu
AU - Yi Sun
AU - Songchun Zou
PY - 2026
DA - 2026/09/30
JO - Mathematics
DO - 10.3390/math14193558
UR - https://www.mdpi.com/2227-7390/14/19/3558
AB - With the increasing adoption of electric vehicles, the in-vehicle active sound generation (ASG) system has emerged as a key technology for shaping brand-specific acoustic characteristics and enhancing the driving and riding experience. However, during dynamic operational transitions such as vehicle acceleration and deceleration, existing systems are often affected by issues including discontinuous and distorted synthesized sounds, which lack coherence and significantly compromise sound quality and auditory comfort. In response to the aforementioned issues, this paper aims to enhance the coherence of synthesized sound in the ASG system by proposing an active sound control method for adaptive and variable operating conditions. Firstly, a synthesis acoustic coherence algorithm based on trigonometric periodic functions (SACA_TPF) is designed to enhance the smoothness of transitions in both the time and frequency domains of the synthesized sound. Subsequently, a simulation method for the variable operating conditions of the ASG system is proposed, along with a further developed optimization method for enhancing the coherence of the synthesized sounds. Simulation results indicate that the proposed method significantly enhances the coherence of the synthesized sound generated by the ASG system during dynamic condition transitions, effectively preventing sound discontinuities and ensuring smooth acoustic transitions. This research is of significant practical value in terms of enhancing brand acoustic recognition in electric vehicles and improving user auditory experience.
SN - 2227-7390
ER -