Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Deep reinforcement learning for turbulent drag reduction in channel flows
We introduce a reinforcement learning (RL) environment to design and benchmark control
strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The …
strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The …
Applications of machine learning to the analysis of engine in-cylinder flow and thermal process: A review and outlook
F Zhao, DLS Hung - Applied Thermal Engineering, 2023 - Elsevier
To adequately elucidate the complex in-cylinder flow structures and its underlying effects on
the thermal processes inside an internal combustion engine (ICE) has long been a daunting …
the thermal processes inside an internal combustion engine (ICE) has long been a daunting …
Automated function development for emission control with deep reinforcement learning
The conventional automotive development process for embedded systems today is still time-
and data-inefficient, and requires highly experienced software developers and calibration …
and data-inefficient, and requires highly experienced software developers and calibration …
A component sizing prediction study for a series hybrid electric vehicle based on artificial neural network
SE Faghih, I Chitsaz… - International Journal of …, 2024 - journals.sagepub.com
In the present study, the predictive tool based on an artificial neural network is developed by
means of the experimental data of two series hybrid electric vehicles. The experiments have …
means of the experimental data of two series hybrid electric vehicles. The experiments have …
Adaptive phase shift control of thermoacoustic combustion instabilities using model-free reinforcement learning
K Alhazmi, SM Sarathy - Combustion and Flame, 2023 - Elsevier
Combustion instability is a significant risk in the development of new engines when using
novel zero-carbon fuels such as ammonia and hydrogen. These instabilities can be difficult …
novel zero-carbon fuels such as ammonia and hydrogen. These instabilities can be difficult …
Reinforcement learning applied to dilute combustion control for increased fuel efficiency
BP Maldonado, BC Kaul… - … Journal of Engine …, 2024 - journals.sagepub.com
To reduce the modeling burden for control of spark-ignition engines, reinforcement learning
(RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to …
(RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to …
Data-driven control of automotive diesel engines and after-treatment systems: State of the art and future challenges
Model-based approaches have played a significant role in automotive electronics for diesel
engines and aftertreatment systems, while they also have some drawbacks that cannot be …
engines and aftertreatment systems, while they also have some drawbacks that cannot be …
Transfer of Reinforcement Learning-Based Controllers from Model-to Hardware-in-the-Loop
The process of developing control functions for embedded systems is resource-, time-, and
data-intensive, often resulting in sub-optimal cost and solutions approaches. Reinforcement …
data-intensive, often resulting in sub-optimal cost and solutions approaches. Reinforcement …
Optimizing Fuel Injection Timing for Multiple Injection Using Reinforcement Learning and Functional Mock-up Unit for a Small-bore Diesel Engine
A Vaze, PS Mehta, A Krishnasamy - SAE International Journal of Engines, 2024 - sae.org
Reinforcement learning (RL) is a computational approach to understanding and automating
goaldirected learning and decision-making. The difference from other computational …
goaldirected learning and decision-making. The difference from other computational …