Estimation of electric vehicle turning radius through machine learning for roundabout cornering
This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred us...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/34918/1/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning%20.pdf http://umpir.ump.edu.my/id/eprint/34918/2/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning_FULL.pdf |
| _version_ | 1825824126613323776 |
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| author | Ashaa, Supramaniam Muhammad Aizzat, Zakaria Kunjunni, Baarath Mohamad Heerwan, Peeie Ahmad Fakhri, Ab. Nasir Muhammad Izhar, Ishak |
| author_facet | Ashaa, Supramaniam Muhammad Aizzat, Zakaria Kunjunni, Baarath Mohamad Heerwan, Peeie Ahmad Fakhri, Ab. Nasir Muhammad Izhar, Ishak |
| author_sort | Ashaa, Supramaniam |
| collection | UMP |
| description | This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. A compact electric vehicle model is used to obtain data and measurements of the vehicle states for different sets of road radius. The augmented basic measurements is fed to an Extra Tree Regression to predict the turning radius of the vehicle. The feasibility of the developed algorithm was tested and validated using performance metrics. The results show that the regression accuracy for the turning radius is 99% and can be obtained with sufficient vehicle dynamics information. |
| first_indexed | 2024-03-06T12:59:25Z |
| format | Conference or Workshop Item |
| id | UMPir34918 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T12:59:25Z |
| publishDate | 2021 |
| publisher | IEEE |
| record_format | dspace |
| spelling | UMPir349182022-08-15T01:30:19Z http://umpir.ump.edu.my/id/eprint/34918/ Estimation of electric vehicle turning radius through machine learning for roundabout cornering Ashaa, Supramaniam Muhammad Aizzat, Zakaria Kunjunni, Baarath Mohamad Heerwan, Peeie Ahmad Fakhri, Ab. Nasir Muhammad Izhar, Ishak TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. A compact electric vehicle model is used to obtain data and measurements of the vehicle states for different sets of road radius. The augmented basic measurements is fed to an Extra Tree Regression to predict the turning radius of the vehicle. The feasibility of the developed algorithm was tested and validated using performance metrics. The results show that the regression accuracy for the turning radius is 99% and can be obtained with sufficient vehicle dynamics information. IEEE 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/34918/1/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning%20.pdf pdf en http://umpir.ump.edu.my/id/eprint/34918/2/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning_FULL.pdf Ashaa, Supramaniam and Muhammad Aizzat, Zakaria and Kunjunni, Baarath and Mohamad Heerwan, Peeie and Ahmad Fakhri, Ab. Nasir and Muhammad Izhar, Ishak (2021) Estimation of electric vehicle turning radius through machine learning for roundabout cornering. In: 19th IEEE Student Conference on Research and Development: Sustainable Engineering and Technology towards Industry Revolution, SCOReD 2021 , 23-25 November 2021 , Kota Kinabalu, Sabah. 329 -332.. ISSN 2643-2447 ISBN 978-1-6654-0193-7 (Published) https://doi.org/10.1109/SCOReD53546.2021.9652676 |
| spellingShingle | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics Ashaa, Supramaniam Muhammad Aizzat, Zakaria Kunjunni, Baarath Mohamad Heerwan, Peeie Ahmad Fakhri, Ab. Nasir Muhammad Izhar, Ishak Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title | Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title_full | Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title_fullStr | Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title_full_unstemmed | Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title_short | Estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| title_sort | estimation of electric vehicle turning radius through machine learning for roundabout cornering |
| topic | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics |
| url | http://umpir.ump.edu.my/id/eprint/34918/1/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning%20.pdf http://umpir.ump.edu.my/id/eprint/34918/2/Estimation%20of%20electric%20vehicle%20turning%20radius%20through%20machine%20learning_FULL.pdf |
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