An extended Kalman filter for input estimations in diesel-engine selective catalytic reduction applications

作者：Jiang, Kai; Geng, Peng; Meng, Fei; Zhang, Hui^*

来源：Neurocomputing, 2016, 171: 569-575.

DOI：10.1016/j.neucom.2015.06.072

• Selective Catalytic Reduction (SCR) system
• Input estimation
• Extended Kalman filter
• Diesel-engine

Nowadays the legislative regulation on emissions of Diesel engines is stringent such that an after-treatment system is necessary. To reduce vehicle NO emission, a selective catalytic reduction (SCR) system is widely used for Diesel-engine applications. In the SCR system, the gaseous ammonia plays a significant role which is utilized as the reduction to eliminate the NOx emission. To facilitate the NOx reduction, a NOx sensor and an ammonia sensor placed before the SCR catalyst are a good strategy. However, physical sensors would increase the system cost and diagnosis challenge. To reduce the number of physical sensors, in this paper, observers are designed with the assist of extended Kalman filter (EKF) to estimate the NOx or ammonia concentrations before the SCR catalyst. Simulation results show that the designed observers based on EKF can achieve the prescribed objectives quite well.

• 出版日期2016-1-1
• 单位上海海事大学