Nonlinear Disturbance Observer design for estimation of ammonia storage ratio in selected catalytic reduction systems
Bibliographic record
Abstract
Urea based selected catalytic reduction (SCR) system is a promising devise to achieve high NOx reduction and widely used in diesel engine after-treatment systems. The ammonia storage ratio is critical in SCR feedback control for high NOx reduction and low ammonia slip. However, it cannot be directly measured by production sensors. To effectively estimate the ammonia storage ratio on line and reduce the cost by using exhaust gas sensors, a cost-effective Nonlinear Disturbance Observer (NDO) was designed based on part of the three-state SCR model by using NOx sensors only. In this approach, the ammonia storage ratio is treated as an external disturbance and estimated. The stability of the estimation was also analyzed in the paper. The simulation results based on the full-vehicle simulation of FTP-75 test show that the NDO can effectively estimate the ammonia storage ratio when NOx sensor with/without measurement noise or ammonia cross-sensitivity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".