A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles
It is of great significance to improve the driving range prediction accuracy to provide battery electric vehicle users with reliable information. A model built by the conventional multiple linear regression method is feasible to predict the driving range, but the residual errors between -3.6975 km a...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/4109148 |
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| _version_ | 1850208317005103104 |
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| author | Shuai Sun Jun Zhang Jun Bi Yongxing Wang |
| author_facet | Shuai Sun Jun Zhang Jun Bi Yongxing Wang |
| author_sort | Shuai Sun |
| collection | DOAJ |
| description | It is of great significance to improve the driving range prediction accuracy to provide battery electric vehicle users with reliable information. A model built by the conventional multiple linear regression method is feasible to predict the driving range, but the residual errors between -3.6975 km and 3.3865 km are relatively unfaithful for real-world driving. The study is innovative in its application of machine learning method, the gradient boosting decision tree algorithm, on the driving range prediction which includes a very large number of factors that cannot be considered by conventional regression methods. The result of the machine learning method shows that the maximum prediction error is 1.58 km, the minimum prediction error is -1.41 km, and the average prediction error is about 0.7 km. The predictive accuracy of the gradient boosting decision tree is compared against that of the conventional approaches. |
| format | Article |
| id | doaj-art-990b938b0b7e4e61a16b614d2582015f |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-990b938b0b7e4e61a16b614d2582015f2025-08-20T02:10:16ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/41091484109148A Machine Learning Method for Predicting Driving Range of Battery Electric VehiclesShuai Sun0Jun Zhang1Jun Bi2Yongxing Wang3School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaYunnan Travelsky Airport Technology Co. Ltd., Kunming 650200, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaIt is of great significance to improve the driving range prediction accuracy to provide battery electric vehicle users with reliable information. A model built by the conventional multiple linear regression method is feasible to predict the driving range, but the residual errors between -3.6975 km and 3.3865 km are relatively unfaithful for real-world driving. The study is innovative in its application of machine learning method, the gradient boosting decision tree algorithm, on the driving range prediction which includes a very large number of factors that cannot be considered by conventional regression methods. The result of the machine learning method shows that the maximum prediction error is 1.58 km, the minimum prediction error is -1.41 km, and the average prediction error is about 0.7 km. The predictive accuracy of the gradient boosting decision tree is compared against that of the conventional approaches.http://dx.doi.org/10.1155/2019/4109148 |
| spellingShingle | Shuai Sun Jun Zhang Jun Bi Yongxing Wang A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles Journal of Advanced Transportation |
| title | A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles |
| title_full | A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles |
| title_fullStr | A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles |
| title_full_unstemmed | A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles |
| title_short | A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles |
| title_sort | machine learning method for predicting driving range of battery electric vehicles |
| url | http://dx.doi.org/10.1155/2019/4109148 |
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