A multi-objective optimization method for active control of loudness and sharpness of wiper windshield systems

SUN Yijia; WANG Yansong; LIU Ningning; YUAN Tao; XIE Xiaolong; GUO Hui

doi:10.12299/jsues.24-0080

Volume 39 Issue 2

Jun. 2025

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Article Navigation > Journal of Shanghai University of Engineering Science > 2025 > 39(2): 119-124, 222

SUN Yijia, WANG Yansong, LIU Ningning, YUAN Tao, XIE Xiaolong, GUO Hui. A multi-objective optimization method for active control of loudness and sharpness of wiper windshield systems[J]. Journal of Shanghai University of Engineering Science, 2025, 39(2): 119-124, 222. doi: 10.12299/jsues.24-0080

Citation:

SUN Yijia, WANG Yansong, LIU Ningning, YUAN Tao, XIE Xiaolong, GUO Hui. A multi-objective optimization method for active control of loudness and sharpness of wiper windshield systems[J]. Journal of Shanghai University of Engineering Science, 2025, 39(2): 119-124, 222. doi: 10.12299/jsues.24-0080

Citation:

SUN Yijia, WANG Yansong, LIU Ningning, YUAN Tao, XIE Xiaolong, GUO Hui. A multi-objective optimization method for active control of loudness and sharpness of wiper windshield systems[J]. Journal of Shanghai University of Engineering Science, 2025, 39(2): 119-124, 222. doi: 10.12299/jsues.24-0080

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A multi-objective optimization method for active control of loudness and sharpness of wiper windshield systems

doi: 10.12299/jsues.24-0080

1.
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
2.
Shenda (Shanghai) Technology Co., Ltd., Shanghai 201814, China

Received Date: 2024-03-21
Available Online: 2025-09-30
Publish Date: 2025-06-30

Abstract

Abstract

The reduction of noise in the power system of electric vehicles has accentuated the contradictory issues between loudness and sharpness caused by wiper reversal. Multi-objective optimization methods can help guide multi-band collaborative active control and improve the sound quality of the wiper windshield system. Noise data during wiper operation were collected through actual vehicle test. A multi-objective optimization formulation was constructed based on the direct mapping relationships between the amplitude of characteristic frequency bands and loudness and sharpness. Sensitivity analysis identified a set of sensitive frequency bands that most significantly affect changes in loudness and sharpness. The multi-objective genetic algorithm NSGA-Ⅱ was employed to obtain the amplitude values of these sensitive bands yielding the best compromise between loudness and sharpness. Active control of loudness and sharpness was simulated using an active noise equalization (ANE) algorithm based on a filtered-error least mean square algorithm (FELMS) adaptive filter, verifying the feasibility of the optimal solution. The results show that the loudness is reduced by 15.4%, sharpness by 18%, achieving 94% of the optimal loudness reduction and 87% of the optimal sharpness reduction, demonstrating improved sound quality.
- interior noise,
- wiper windshield system,
- sound quality,
- multi-objective optimization,
- active control

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References(17)

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