RT Conference Proceedings
T1 Route tracking diagnosis algorithm for EV energy prediction strategies
A1 Prieto, P.
A1 Trancho, Elena
A1 Arteta, B.
A1 Parra, A.
A1 Coupeau, A.
A1 Cagigas, D.
A1 Ibarra, E.
AB Current pollution issues generated by internal com bustion engine (ICE) based vehicles have lead to their progressive introduction of electrified transport systems. However, their main drawback is their poor autonomy when compared to conventional vehicles. In order to mitigate this issue, the scientific community is extensively researching on energy optimization and prediction strategies to extend the autonomy of electric vehicles (EV). In general, such strategies require the knowledge of the route profile, being of capital importance to identify whether the vehicle is on route or not. Considering this, in this paper, a geo-fence based route tracking diagnosis strategy is proposed and tested. The proposed strategy relies on the information provided by the Google Maps API (Application Programming Interface) to calculate the vehicles reference route. Additionally, a Global Positioning System (GPS) device is used to monitor the real vehicle position. The proposed strategy is validated throughout simulation and experimental tests.
SN 978-84-17171-50-6
YR 2019
FD 2019
LK http://hdl.handle.net/11556/1274
UL http://hdl.handle.net/11556/1274
LA eng
NO This work was supported in part by the H2020 European Commission under Grant 769944 (STEVE Project), Grant 824311 (ACHILES Project) and Grant 769902 (DOMUS Project) and in part by the research projects GANICS (KK 2017/00050), SICSOL (KK-2018/00064) and ENSOL (KK- 2018/00040), within the ELKARTEK program of the Gov ernment of the Basque Country. Finally, this work has been supported by the Department of Education, Linguistic Policy and Culture of the Basque Government within the fund for research groups of the Basque university system IT978-16.
DS TECNALIA Publications
RD 1 jul 2024