Name
Title | ||
|---|---|---|
Probabilistic Guaranteed Gradient Learning-Based Spark Advance Self-Optimizing Control for Spark-Ignited Engines. |
Abstract | ||
|---|---|---|
In spark-ignited (SI) engines, the spark advance (SA) controls the combustion phase that has a significant impact on the efficiency. Online self-optimizing control (SOC) of SA to maximize the indicated fuel conversion efficiency (IFCE) forms a stochastic optimization problem for a static map due to the stochasticity of combustion. Gradient-based optimization algorithms using periodic dithers are e... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2017.2767293 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Engines,Combustion,Optimization,Fuels,Silicon,Probabilistic logic,Statistical distributions | Convergence (routing),Gradient descent,Stochastic optimization,Spark (mathematics),Test bench,Computer science,Control theory,Probability distribution,Artificial intelligence,Probabilistic logic,Machine learning,Sample size determination | Journal |
Volume | Issue | ISSN |
29 | 10 | 2162-237X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yahui Zhang | 1 | 1 | 2.46 |
| Jinwu Gao | 2 | 337 | 31.61 |
| Tielong Shen | 3 | 243 | 40.52 |