지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2012.12
- 수록면
- 136 - 140 (5page)
이용수
초록· 키워드
오류제보하기
Air pollution became an issue due to the rapid industrialization and the development of car industry. Emissions form automobile cause destroying ozone layer, global warming, photochemical smog to environment and cause cancer, declined nerve center, respiratory diseases to humankind. From 1960s, society has concerned about the environment problem, and since established California Air Resources Boar(CARB-1967) and Environmental Protection Agency(EPA-1970), they tighten regulation at exhaust gases.
Since 1980s, three-way catalyst has been used to purify the car exhaust fumes. Characteristics of three-way catalyst are oxidize CO and HC when the air fuel ration is rich, deoxidize NOx when the air fuel ratio is lean. When air fuel ratio is nearly to stoichiometric value, the efficiency of catalyst is almost 100%. It is desirable to adjust air fuel ratio nearly stoichiometric value to reduce harmful gases. As TWC have the different characteristics and parameter changed by reason of durability, temperature and environment, the model has to corrected accurately. Gradient descent method is widely used to estimate parameters, but in this thesis we used nonlinear Kalman filter such as the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to estimate parameters and oxygen storage state. While EKF uses first order of Taylor expansion to approximate nonlinear system, UKF performs a stochastic linearization by using a weighted statistical linear regression process based on the unscented transform. The advantage of Kalman filter is it can estimate well instead of noise in system or sensor measurement. Bias compensator using polynomial regression function is also proposed to reduce bias error that occurs due to nonequilibrium effect. Finally, proposed estimation method is verified by simulations.
Since 1980s, three-way catalyst has been used to purify the car exhaust fumes. Characteristics of three-way catalyst are oxidize CO and HC when the air fuel ration is rich, deoxidize NOx when the air fuel ratio is lean. When air fuel ratio is nearly to stoichiometric value, the efficiency of catalyst is almost 100%. It is desirable to adjust air fuel ratio nearly stoichiometric value to reduce harmful gases. As TWC have the different characteristics and parameter changed by reason of durability, temperature and environment, the model has to corrected accurately. Gradient descent method is widely used to estimate parameters, but in this thesis we used nonlinear Kalman filter such as the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to estimate parameters and oxygen storage state. While EKF uses first order of Taylor expansion to approximate nonlinear system, UKF performs a stochastic linearization by using a weighted statistical linear regression process based on the unscented transform. The advantage of Kalman filter is it can estimate well instead of noise in system or sensor measurement. Bias compensator using polynomial regression function is also proposed to reduce bias error that occurs due to nonequilibrium effect. Finally, proposed estimation method is verified by simulations.
목차
Abstract
Ⅰ. 서론
Ⅱ. 삼원촉매 및 공연비 센서 모델링
Ⅲ. 비선형 칼만필터
Ⅳ. 바이어스 보상기
Ⅴ. 시뮬레이션
Ⅵ. 결론
참고문헌
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UCI(KEPA) : I410-ECN-0101-2017-003-000682422