학술논문
ANC를 통한 전기자동차 인휠 모터 소음 개발
Development of In-Wheel Motor Noise Reduction for Electric Vehicles Using Active Noise Control (ANC)
Development of In-Wheel Motor Noise Reduction for Electric Vehicles Using Active Noise Control (ANC)
Document Type
Article
Source
한국소음진동공학회논문집, 34(1), 276, pp.12-18 Feb, 2024
Subject
Language
한국어
ISSN
2287-5476
1598-2785
1598-2785
Abstract
온실가스 배출과 이산화탄소로 인한 지구 온난화를 극복하기 위해 자동차 산업은 전기차 개발에 대응하여 시장 변화에 대응하고 있다. 다양한 종류의 전기차 중에서 In-Wheel Motor (IWM)은 간단한 구조, 높은 효율성 및 좋은 공간 활용성으로 인해 미래의 주행 기술 구조로 적합한 솔루션으로 간주된다. IWM의 다양한 소음 원인을 분석한 결과, 250 Hz 미만인 8차와 16차가 ANC (액티브 노이즈 캔슬링) 응용 기술을 사용하여 감소시키기에 적합하다고 판단되었다. 다중 상관관계, 최적 필터 및 2차 노이즈 경로 분석이 수행되었고 시간 주파수 필터링된 최소 제곱 알고리즘이 적용되었다. ANC 기술을 적용함으로써, 8차와 16차 소음이 각각 20 dBA로 감소되었고, 전체적인 소음은 6~8 dBA로 성공적으로 감소되었다.
To overcome global warming caused by air pollution and carbon dioxide, the automotive industry is responding to changes in the market by developing electric vehicles. Among the various types of electric vehicles, an in-wheel motor (IWM) is regarded as a suitable solution for future drive train architecture owing to its simple structure, high efficiency, and good space availability. Through the analysis of various IWM noise sources, the 8th and 16th orders, which are less than 250Hz are selected as the subjects to reduce using the ANC application technology. A multi-correlation, optimal filter, and secondary noise path analysis are conducted. Moreover, a time frequency-filtered least mean square algorithm is adapted. Four accelerometers and six speaker positions are chosen through the optimization of ANC. With ANC technology, the 8th and 16th noise are reduced by 20dBA and the overall noise is successfully reduced by 6 to 8dBA, respectively.
To overcome global warming caused by air pollution and carbon dioxide, the automotive industry is responding to changes in the market by developing electric vehicles. Among the various types of electric vehicles, an in-wheel motor (IWM) is regarded as a suitable solution for future drive train architecture owing to its simple structure, high efficiency, and good space availability. Through the analysis of various IWM noise sources, the 8th and 16th orders, which are less than 250Hz are selected as the subjects to reduce using the ANC application technology. A multi-correlation, optimal filter, and secondary noise path analysis are conducted. Moreover, a time frequency-filtered least mean square algorithm is adapted. Four accelerometers and six speaker positions are chosen through the optimization of ANC. With ANC technology, the 8th and 16th noise are reduced by 20dBA and the overall noise is successfully reduced by 6 to 8dBA, respectively.