| Issue |
E3S Web Conf.
Volume 360, 2022
2022 8th International Symposium on Vehicle Emission Supervision and Environment Protection (VESEP2022)
|
|
|---|---|---|
| Article Number | 01038 | |
| Number of page(s) | 19 | |
| DOI | https://doi.org/10.1051/e3sconf/202236001038 | |
| Published online | 23 November 2022 | |
Parameter Identification of DOC Model Based on Variable Forgetting Factor Least Squares
Jilin University, State Key Laboratory of Automobile Simulation and Control, Changchun, 130025
* Corresponding author: gaoying@jlu.edu.cn
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.
Key words: Diesel oxidation catalyst / Parameter identification / Nonlinear least squares / Variable forgetting factor least squares
© The Authors, published by EDP Sciences, 2022
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