Research Article
Multiobjective Optimization of Diesel Particulate Filter Regeneration Conditions Based on Machine Learning Combined with Intelligent Algorithms
Table 7
Comparison of parameters and responses before and after optimization.
| | Parameter | Before optimization | After optimization | Percentage change |
| | Preinjection quantity (mg) | 1.90 | 1.80 | −5.23% | | Rear injection 1 quantity (mg) | 3.84 | 4.36 | 20.5% | | Rear injection 2 quantity (mg) | 8.88 | 7.00 | −21.1% | | Rear injection 2 timing (°CA) | −42.47 | −43.88 | −1.41 | | Main injection timing (°CA) | 9.25 | 8.92 | −3.5% | | Preinjection timing (°CA) | 18.06 | 13.60 | −20.7% | | T4 (°C) | 433.06 | 474.32 | 9.5% | | T5 (°C) | 592.56 | 600.19 | 1.3% | | O2 (%) | 4.44 | 5.24 | 18.5% | | NOx (ppm) | 428.57 | 347.75 | −18.8% | | Smoke (FSN) | 1.17 | 0.86 | −26.5% | | BSFC (g/kW·h) | 326.00 | 353.00 | 8.3% |
|
|
