Parameter Identification of DOC Model Based on Variable Forgetting Factor Least Squares

Abstract

In diesel engine after-treatment control technology, the accurate real-time control of Diesel Oxidation Catalyst (DOC) outlet temperature is an important topic. To find a high-precision parameter identification algorithm for the DOC system, this paper establishes zero-dimensional (0D) and one-dimensional (1D) mathematical models of DOC, introduces Variable Forgetting Factor Least Squares(VFFRLS) and Nonlinear Least Squares parameter identification for comparison and analysis. The results show that the 0D determination coefficient R-square of Nonlinear Least Squares parameter identification results is around 0.9, the root mean square error (RSME) mean is 23.682, the R-square of 1D is mostly less than 0.9, and the mean value of RSME is 32.649; The R-square of VFFRLS algorithm is 1, and the RSME is below 0.02. Therefore, the VFFRLS algorithm is more suitable for the parameter identification of the DOC temperature model.

Keywords

• diesel oxidation catalyst
• parameter identification
• nonlinear least squares
• variable forgetting factor least squares