Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire
With increasing concerns about urban air quality and carbon emissions, electric vehicles (EVs) have gained popularity in megacities, especially in Europe and Asia. The energy consumption of EVs has subsequently caught researchers’ attention. However, the exploration of energy consumption of EVs has...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/1074817 |
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| _version_ | 1832564027356610560 |
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| author | Kezhen Hu Jianping Wu Mingyu Liu |
| author_facet | Kezhen Hu Jianping Wu Mingyu Liu |
| author_sort | Kezhen Hu |
| collection | DOAJ |
| description | With increasing concerns about urban air quality and carbon emissions, electric vehicles (EVs) have gained popularity in megacities, especially in Europe and Asia. The energy consumption of EVs has subsequently caught researchers’ attention. However, the exploration of energy consumption of EVs has largely focused on people’s revealed driving behavior and rarely touched on their self-perception of driving styles. In this paper, we developed a more human-centric approach, aiming to investigate how the energy efficiency of EVs is shaped by the driving behavior and driving style in the urban scenario from field test data and driving style questionnaires (DSQs). Field tests were carried out on a designated route for a total of 13 drivers in the city of Beijing, where vehicle operation parameters were recorded under both congested and smooth traffic conditions. DSQs were collected from a larger pool of drivers including the field test drivers to be applied to driving style factor analysis. The results of a correlation analysis demonstrate the dynamic interaction between drivers’ revealed behavior and stated driving style under different traffic conditions. We also proposed an energy consumption prediction model with the fusion of collected driving parameters and DSQ data and the result is promising. We hope that this study would draw inspiration for future research on people’s transitioning driving behavior in an electric-mobility era. |
| format | Article |
| id | doaj-art-fe15fab934f04d65865e7ea55eabdbeb |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-fe15fab934f04d65865e7ea55eabdbeb2025-02-03T01:12:02ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/10748171074817Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and QuestionnaireKezhen Hu0Jianping Wu1Mingyu Liu2Department of Civil Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Civil Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Civil Engineering, Tsinghua University, Beijing 100084, ChinaWith increasing concerns about urban air quality and carbon emissions, electric vehicles (EVs) have gained popularity in megacities, especially in Europe and Asia. The energy consumption of EVs has subsequently caught researchers’ attention. However, the exploration of energy consumption of EVs has largely focused on people’s revealed driving behavior and rarely touched on their self-perception of driving styles. In this paper, we developed a more human-centric approach, aiming to investigate how the energy efficiency of EVs is shaped by the driving behavior and driving style in the urban scenario from field test data and driving style questionnaires (DSQs). Field tests were carried out on a designated route for a total of 13 drivers in the city of Beijing, where vehicle operation parameters were recorded under both congested and smooth traffic conditions. DSQs were collected from a larger pool of drivers including the field test drivers to be applied to driving style factor analysis. The results of a correlation analysis demonstrate the dynamic interaction between drivers’ revealed behavior and stated driving style under different traffic conditions. We also proposed an energy consumption prediction model with the fusion of collected driving parameters and DSQ data and the result is promising. We hope that this study would draw inspiration for future research on people’s transitioning driving behavior in an electric-mobility era.http://dx.doi.org/10.1155/2018/1074817 |
| spellingShingle | Kezhen Hu Jianping Wu Mingyu Liu Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire Journal of Advanced Transportation |
| title | Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire |
| title_full | Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire |
| title_fullStr | Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire |
| title_full_unstemmed | Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire |
| title_short | Exploring the Energy Efficiency of Electric Vehicles with Driving Behavioral Data from a Field Test and Questionnaire |
| title_sort | exploring the energy efficiency of electric vehicles with driving behavioral data from a field test and questionnaire |
| url | http://dx.doi.org/10.1155/2018/1074817 |
| work_keys_str_mv | AT kezhenhu exploringtheenergyefficiencyofelectricvehicleswithdrivingbehavioraldatafromafieldtestandquestionnaire AT jianpingwu exploringtheenergyefficiencyofelectricvehicleswithdrivingbehavioraldatafromafieldtestandquestionnaire AT mingyuliu exploringtheenergyefficiencyofelectricvehicleswithdrivingbehavioraldatafromafieldtestandquestionnaire |