Analysis of the Best Driving Decision of Electric Vehicles Based onDynamic Programming
The internet of vehicles enables electric vehicles to access more front-road and traffic information, helping the vehicle control system to more accurately plan the speed trajectory and improving the driving efficiency and ecology. In this paper, the optimal economic driving strategy and its influen...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2019-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2019.06.600 |
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| Summary: | The internet of vehicles enables electric vehicles to access more front-road and traffic information, helping the vehicle control system to more accurately plan the speed trajectory and improving the driving efficiency and ecology. In this paper, the optimal economic driving strategy and its influencing factors of an electric vehicle with completely known front road information were studied. The optimal speed control problem is constructed with the shortest time and the lowest energy consumption. And a location-based dynamic programming algorithm was adoped to solve the problem. The effects of objective function weighting factor, rolling resistance coefficient spatial distribution, road gradient spatial distribution and regional speed limit on the optimal economic driving strategy were analyzed. The results show that the optimal driving strategy is not affected by above mentioned factors when the shortest time is taken as the goal, and the motor basically works on its external characteristic curve; when the lowest energy consumption is taken as the goal, the optimal driving strategy is to dynamically adjust the throttle pedal opening according to the road load and the speed limit of the road section, so as to maintain the motor working near its maximum efficiency area all the time. |
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| ISSN: | 2096-5427 |