Combustion control using spiking neural networks
Abstract
A system that controls a combustion engine stores network vectors in a memory that represent diverse and distinct spiking neural networks. The system decodes the network vectors and trains and evaluates the spiking neural networks. The system duplicates selected network vectors and crosses-over the duplicated network vectors that represent modified spiking neural networks. The system mutates the crossed-over duplicated network vectors by randomly modifying one or more portions of the crossing-over duplicated network vectors. The system meter exhaust gas into an intake manifold when an engine temperature exceeds a threshold, an engine load exceeds a threshold, an engine's rotation-per-minute rate exceeds a threshold, and a fuel flow exceeds a threshold. The system modifies fuel flow into an engine's combustion chamber on a cycle-to-cycle basis by the trained spiking neural network.
- Inventors:
- Issue Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1998404
- Patent Number(s):
- 11655775
- Application Number:
- 17/888,047
- Assignee:
- UT-Battelle, LLC (Oak Ridge, TN)
- DOE Contract Number:
- AC05-00OR22725
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 08/15/2022
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Puente, Brian P. Maldonado, Kaul, Brian C., Schuman, Catherine D., Mitchell, John Parker, and Young, Steven R. Combustion control using spiking neural networks. United States: N. p., 2023.
Web.
Puente, Brian P. Maldonado, Kaul, Brian C., Schuman, Catherine D., Mitchell, John Parker, & Young, Steven R. Combustion control using spiking neural networks. United States.
Puente, Brian P. Maldonado, Kaul, Brian C., Schuman, Catherine D., Mitchell, John Parker, and Young, Steven R. Tue .
"Combustion control using spiking neural networks". United States. https://www.osti.gov/servlets/purl/1998404.
@article{osti_1998404,
title = {Combustion control using spiking neural networks},
author = {Puente, Brian P. Maldonado and Kaul, Brian C. and Schuman, Catherine D. and Mitchell, John Parker and Young, Steven R.},
abstractNote = {A system that controls a combustion engine stores network vectors in a memory that represent diverse and distinct spiking neural networks. The system decodes the network vectors and trains and evaluates the spiking neural networks. The system duplicates selected network vectors and crosses-over the duplicated network vectors that represent modified spiking neural networks. The system mutates the crossed-over duplicated network vectors by randomly modifying one or more portions of the crossing-over duplicated network vectors. The system meter exhaust gas into an intake manifold when an engine temperature exceeds a threshold, an engine load exceeds a threshold, an engine's rotation-per-minute rate exceeds a threshold, and a fuel flow exceeds a threshold. The system modifies fuel flow into an engine's combustion chamber on a cycle-to-cycle basis by the trained spiking neural network.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue May 23 00:00:00 EDT 2023},
month = {Tue May 23 00:00:00 EDT 2023}
}
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