The persistence of engine knock poses a significant obstacle to advancing the efficiency of Spark Ignited (SI) engines. This irregular combustion occurrence, resulting from the auto-ignition of unburned mixtures in the end-gas, can lead to detrimental pressure fluctuations within the cylinder and potential damage to engine components.
Knock is quantified by the octane number, defining the anti-knock quality of the fuel.
Engine knock is particularly challenging at high loads, while at low loads, maintaining combustion stability becomes a concern.
Refineries invest substantial efforts in producing high anti-knock or high-octane market gasoline through methods like splash blending. However, high-octane gasoline is only essential for specific operating conditions to counteract knock.
Refineries also produce low octane fuels, which may not address knock but prove beneficial for combustion stability at low loads.
To address the challenges of knock at high loads and ensure combustion stability at low loads for future engines, a promising strategy involves using multiple fuels. This includes combining low octane fuels with high octane fuels, where the latter is only required at high loads. By employing low octane fuels at low loads, refineries can significantly reduce emissions associated with high-octane gasoline production.
The goal is to use artificial intelligence methods to alleviate knock, enhance fuel economy, and concurrently decrease emissions for future Spark-Ignited (SI) engines in heavy-duty applications. This overarching strategy aligns with the industry's increasing emphasis on sustainable solutions and cleaner technologies.
The central objective is to create a Spark-Ignited (SI) fuel map capable of achieving peak efficiency comparable to diesel engines, which traditionally exhibit higher efficiency than SI engines.
This research collection invites contributions in artificial intelligence methods, focusing on fundamental and applied research related to fuel combinations with different octane levels.
This includes exploring non-carbon alternatives such as hydrogen and ammonia, as well as low carbon fuels.
We welcome Research articles, Review articles, Mini Review and Perspectives aiming to provide the recent advancements, mainly focused on:
• Different artificial intelligence (AI) methods to predict the fuel blends for SI engines that can offer comparable efficiency benefit to diesel engines on different regions of the fuel map.
Discussions can include emission reductions and fuel blends chemistry including the blending ratios that can help to alleviate knock at high loads and provide combustion stability at low loads.
• Cost comparison of deploying artificial intelligence (AI) methods vs experimental/computational work for future benefits.
Keywords:
Low to Zero carbon fuels, Spark Ignition, Knock, Combustion stability, Artificial intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The persistence of engine knock poses a significant obstacle to advancing the efficiency of Spark Ignited (SI) engines. This irregular combustion occurrence, resulting from the auto-ignition of unburned mixtures in the end-gas, can lead to detrimental pressure fluctuations within the cylinder and potential damage to engine components.
Knock is quantified by the octane number, defining the anti-knock quality of the fuel.
Engine knock is particularly challenging at high loads, while at low loads, maintaining combustion stability becomes a concern.
Refineries invest substantial efforts in producing high anti-knock or high-octane market gasoline through methods like splash blending. However, high-octane gasoline is only essential for specific operating conditions to counteract knock.
Refineries also produce low octane fuels, which may not address knock but prove beneficial for combustion stability at low loads.
To address the challenges of knock at high loads and ensure combustion stability at low loads for future engines, a promising strategy involves using multiple fuels. This includes combining low octane fuels with high octane fuels, where the latter is only required at high loads. By employing low octane fuels at low loads, refineries can significantly reduce emissions associated with high-octane gasoline production.
The goal is to use artificial intelligence methods to alleviate knock, enhance fuel economy, and concurrently decrease emissions for future Spark-Ignited (SI) engines in heavy-duty applications. This overarching strategy aligns with the industry's increasing emphasis on sustainable solutions and cleaner technologies.
The central objective is to create a Spark-Ignited (SI) fuel map capable of achieving peak efficiency comparable to diesel engines, which traditionally exhibit higher efficiency than SI engines.
This research collection invites contributions in artificial intelligence methods, focusing on fundamental and applied research related to fuel combinations with different octane levels.
This includes exploring non-carbon alternatives such as hydrogen and ammonia, as well as low carbon fuels.
We welcome Research articles, Review articles, Mini Review and Perspectives aiming to provide the recent advancements, mainly focused on:
• Different artificial intelligence (AI) methods to predict the fuel blends for SI engines that can offer comparable efficiency benefit to diesel engines on different regions of the fuel map.
Discussions can include emission reductions and fuel blends chemistry including the blending ratios that can help to alleviate knock at high loads and provide combustion stability at low loads.
• Cost comparison of deploying artificial intelligence (AI) methods vs experimental/computational work for future benefits.
Keywords:
Low to Zero carbon fuels, Spark Ignition, Knock, Combustion stability, Artificial intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.