Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles
The eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently their usage is not related to the autonomy required by the driver. For this reason, in thi...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/7893968 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850168008232665088 |
|---|---|
| author | Y. Bello T. Azib C. Larouci M. Boukhnifer N. Rizoug D. Patino F. Ruiz |
| author_facet | Y. Bello T. Azib C. Larouci M. Boukhnifer N. Rizoug D. Patino F. Ruiz |
| author_sort | Y. Bello |
| collection | DOAJ |
| description | The eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently their usage is not related to the autonomy required by the driver. For this reason, in this paper, the eco-driving challenge is translated into two-layer optimal controller designed for pure electric vehicles. This controller is oriented to ensure that the energy available is enough to complete a demanded trip, adding speed limits to control the energy consumption rate. The mechanical and electrical models required are exposed and analyzed. The cost function is optimized to correspond to the needs of each trip according to driver behavior, vehicle, and traject information. The optimal controller proposed in this paper is a nonlinear model predictive controller (NMPC) associated with a nonlinear unidimensional optimization. The combination of both algorithms allows increasing around 50% the autonomy with a limitation of the 30% of the speed and acceleration capabilities. Also, the algorithm is able to ensure a final autonomy with a 1.25% of error in the presence of sensor and actuator noise. |
| format | Article |
| id | doaj-art-e6bcbf8a4c324348968c5e41c067cdfb |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-e6bcbf8a4c324348968c5e41c067cdfb2025-08-20T02:21:04ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/78939687893968Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric VehiclesY. Bello0T. Azib1C. Larouci2M. Boukhnifer3N. Rizoug4D. Patino5F. Ruiz6Department of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá, DC, ColombiaEnergy and Embedded Systems for Transportation Research Department, ESTACA-LAB, Montigny-Le-Bretonneux, FranceEnergy and Embedded Systems for Transportation Research Department, ESTACA-LAB, Montigny-Le-Bretonneux, FranceLorraine University, Lcoms, Metz, FranceEnergy and Embedded Systems for Transportation Research Department, ESTACA-LAB, Montigny-Le-Bretonneux, FranceDepartment of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá, DC, ColombiaDepartment of Electronics Engineering, Pontificia Universidad Javeriana, Bogotá, DC, ColombiaThe eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently their usage is not related to the autonomy required by the driver. For this reason, in this paper, the eco-driving challenge is translated into two-layer optimal controller designed for pure electric vehicles. This controller is oriented to ensure that the energy available is enough to complete a demanded trip, adding speed limits to control the energy consumption rate. The mechanical and electrical models required are exposed and analyzed. The cost function is optimized to correspond to the needs of each trip according to driver behavior, vehicle, and traject information. The optimal controller proposed in this paper is a nonlinear model predictive controller (NMPC) associated with a nonlinear unidimensional optimization. The combination of both algorithms allows increasing around 50% the autonomy with a limitation of the 30% of the speed and acceleration capabilities. Also, the algorithm is able to ensure a final autonomy with a 1.25% of error in the presence of sensor and actuator noise.http://dx.doi.org/10.1155/2020/7893968 |
| spellingShingle | Y. Bello T. Azib C. Larouci M. Boukhnifer N. Rizoug D. Patino F. Ruiz Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles Journal of Advanced Transportation |
| title | Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles |
| title_full | Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles |
| title_fullStr | Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles |
| title_full_unstemmed | Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles |
| title_short | Eco-Driving Optimal Controller for Autonomy Tracking of Two-Wheel Electric Vehicles |
| title_sort | eco driving optimal controller for autonomy tracking of two wheel electric vehicles |
| url | http://dx.doi.org/10.1155/2020/7893968 |
| work_keys_str_mv | AT ybello ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT tazib ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT clarouci ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT mboukhnifer ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT nrizoug ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT dpatino ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles AT fruiz ecodrivingoptimalcontrollerforautonomytrackingoftwowheelelectricvehicles |