Model predictive control of a dual fuel engine integrated with waste heat recovery used for electric power in buildings
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Waste heat recovery (WHR) system uses the thermal energy from the exhaust gases of an internal combustion engine (ICE) to assist in the electricity generated by the ICE generator in buildings. This paper presents a model predictive control (MPC) framework to minimize the fuel consumption of an ICE by integrating it with a WHR system. To this end, a control oriented model of a WHR system is developed and then integrated to a control oriented model of a turbocharged dual fuel diesel‐natural gas ICE. The ICE model is derived based on experimental data collected from a 6.7 L Cummins ISB engine modified for dual fuel operation. The designed MPC framework optimizes the ICE combustion, turbocharger, and organic Rankine cycle (ORC) system in the WHR to minimize fuel consumption of the ICE. The designed control framework also allows to meet time‐varying exhaust gas temperature requirements of the ICE to meet exhaust emission constraints. The results show that the optimal operation of the WHR and the ICE reduces the fuel consumption of the ICE by 6.7%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it