Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill
Compressed Natural Gas (CNG) is an affordable fuel with a higher octane number. However, older CNG kits without electronic controls have the potential to supply more fuel when driving downhill due to the vacuum in the intake manifold. Therefore, this article presents a development of a CNG control...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Muhammadiyah Magelang
2023-04-01
|
| Series: | Automotive Experiences |
| Subjects: | |
| Online Access: | http://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/8107 |
| _version_ | 1827957734436241408 |
|---|---|
| author | Suroto Munahar Muji Setiyo Ray Adhan Brieghtera Madihah Mohd Saudi Azuan Ahmad Dori Yuvenda |
| author_facet | Suroto Munahar Muji Setiyo Ray Adhan Brieghtera Madihah Mohd Saudi Azuan Ahmad Dori Yuvenda |
| author_sort | Suroto Munahar |
| collection | DOAJ |
| description |
Compressed Natural Gas (CNG) is an affordable fuel with a higher octane number. However, older CNG kits without electronic controls have the potential to supply more fuel when driving downhill due to the vacuum in the intake manifold. Therefore, this article presents a development of a CNG control system that accommodates road inclination angles to improve fuel efficiency. Machine learning is involved in this work to process engine speed, throttle valve position, and road slope angle. The control system is designed to ensure reduced fuel consumption when the vehicle is operating downhill. The results showed that the control system increases fuel consumption by 25.7% when driving downhill which an inclination of 5ᵒ. The AFR increased from 17.5 to 22 and the CNG flow rate decreased from 17.7 liters/min to 13.8 liters/min which is promising for applying to CNG vehicles.
|
| first_indexed | 2024-04-09T15:25:43Z |
| format | Article |
| id | doaj.art-4c45f24e81e24c8d9ced51d3472460ad |
| institution | Directory Open Access Journal |
| issn | 2615-6202 2615-6636 |
| language | English |
| last_indexed | 2024-04-09T15:25:43Z |
| publishDate | 2023-04-01 |
| publisher | Universitas Muhammadiyah Magelang |
| record_format | Article |
| series | Automotive Experiences |
| spelling | doaj.art-4c45f24e81e24c8d9ced51d3472460ad2023-04-28T18:12:17ZengUniversitas Muhammadiyah MagelangAutomotive Experiences2615-62022615-66362023-04-016110.31603/ae.8107Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the DownhillSuroto Munahar0Muji Setiyo1Ray Adhan Brieghtera2Madihah Mohd Saudi3Azuan Ahmad4Dori Yuvenda5Universitas Muhammadiyah Magelang, IndonesiaUniversitas Muhammadiyah Magelang, IndonesiaUniversitas Muhammadiyah Magelang, IndonesiaUniversiti Sains Islam Malaysia (USIM), MalaysiaUniversiti Sains Islam Malaysia (USIM), MalaysiaUniversitas Negeri Padang, Indonesia Compressed Natural Gas (CNG) is an affordable fuel with a higher octane number. However, older CNG kits without electronic controls have the potential to supply more fuel when driving downhill due to the vacuum in the intake manifold. Therefore, this article presents a development of a CNG control system that accommodates road inclination angles to improve fuel efficiency. Machine learning is involved in this work to process engine speed, throttle valve position, and road slope angle. The control system is designed to ensure reduced fuel consumption when the vehicle is operating downhill. The results showed that the control system increases fuel consumption by 25.7% when driving downhill which an inclination of 5ᵒ. The AFR increased from 17.5 to 22 and the CNG flow rate decreased from 17.7 liters/min to 13.8 liters/min which is promising for applying to CNG vehicles. http://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/8107CNGControl systemRoad inclining angleFuel savingsAFRMachine learning |
| spellingShingle | Suroto Munahar Muji Setiyo Ray Adhan Brieghtera Madihah Mohd Saudi Azuan Ahmad Dori Yuvenda Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill Automotive Experiences CNG Control system Road inclining angle Fuel savings AFR Machine learning |
| title | Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill |
| title_full | Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill |
| title_fullStr | Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill |
| title_full_unstemmed | Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill |
| title_short | Fuel Control System on CNG Fueled Vehicles using Machine Learning: A Case Study on the Downhill |
| title_sort | fuel control system on cng fueled vehicles using machine learning a case study on the downhill |
| topic | CNG Control system Road inclining angle Fuel savings AFR Machine learning |
| url | http://journal.unimma.ac.id/index.php/AutomotiveExperiences/article/view/8107 |
| work_keys_str_mv | AT surotomunahar fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill AT mujisetiyo fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill AT rayadhanbrieghtera fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill AT madihahmohdsaudi fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill AT azuanahmad fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill AT doriyuvenda fuelcontrolsystemoncngfueledvehiclesusingmachinelearningacasestudyonthedownhill |