TY - GEN
T1 - A predictive control method for automotive selective catalytic reduction systems
AU - Ma, Yao
AU - Wang, Junmin
N1 - Publisher Copyright:
© 2019 American Automatic Control Council.
PY - 2019/7
Y1 - 2019/7
N2 - This paper presents a predictive control method for automotive Selective Catalytic Reduction (SCR) systems to minimize vehicle tailpipe Nitrogen Oxides (NOx) and ammonia (NH3) emissions. SCR systems have been indispensable in Diesel-powered vehicles to reduce the toxic emissions. To balance the tradeoff between NOxand NH3, the ammonia storage level in an SCR needs to be critically controlled. The proposed control method consists of an ammonia coverage ratio tracking controller and a predictive reference ammonia coverage ratio generator. The reference generator will utilize the predictive information, enabled by growing vehicle connectivity and intelligence, to determine an optimal level of ammonia coverage ratio within the preview horizon. The tracking controller will then drive ammonia coverage ratio to a desired level. The effectiveness of the proposed design approach is demonstrated through simulation studies with experimentally acquired data.
AB - This paper presents a predictive control method for automotive Selective Catalytic Reduction (SCR) systems to minimize vehicle tailpipe Nitrogen Oxides (NOx) and ammonia (NH3) emissions. SCR systems have been indispensable in Diesel-powered vehicles to reduce the toxic emissions. To balance the tradeoff between NOxand NH3, the ammonia storage level in an SCR needs to be critically controlled. The proposed control method consists of an ammonia coverage ratio tracking controller and a predictive reference ammonia coverage ratio generator. The reference generator will utilize the predictive information, enabled by growing vehicle connectivity and intelligence, to determine an optimal level of ammonia coverage ratio within the preview horizon. The tracking controller will then drive ammonia coverage ratio to a desired level. The effectiveness of the proposed design approach is demonstrated through simulation studies with experimentally acquired data.
UR - http://www.scopus.com/inward/record.url?scp=85072294312&partnerID=8YFLogxK
U2 - 10.23919/acc.2019.8814808
DO - 10.23919/acc.2019.8814808
M3 - Conference contribution
AN - SCOPUS:85072294312
T3 - Proceedings of the American Control Conference
SP - 1593
EP - 1598
BT - 2019 American Control Conference, ACC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 American Control Conference, ACC 2019
Y2 - 10 July 2019 through 12 July 2019
ER -