Geo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EV

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2019_IECON_Geofence__.pdf (3.51 MB)
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ISBN: 978-1-7281-4879-3
ISBN: 978-1-7281-4878-6
ISBN: 9781728148786
DOI: 10.1109/IECON.2019.8927769
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2019-10
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IEEE
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Abstract
Nowadays, the shortage of energy and environmental pollution are considered as relevant problems due to the high amount of traditional automotive vehicles with internal combustion engines (ICEs). Electric vehicle (EV) is one of the solutions to localize the energy source and the best choice for saving energy and provide zero emission vehicles. However, their main drawback when compared to conventional vehicles is their limited energy storage capacity, resulting in poor driving ranges. In order to mitigate this issue, the scientific community is extensively researching on energy optimization and prediction strategies to extend the autonomy of 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 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, Driver in the Loop (DiL) test and experimental tests.
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Publisher Copyright: © 2019 IEEE.
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BEV , PHEV , Energy consumption estimation , Optimization , Tracking diagnosis , BEV , PHEV , Energy consumption estimation , Optimization , Tracking diagnosis , Control and Systems Engineering , Electrical and Electronic Engineering , SDG 7 - Affordable and Clean Energy , SDG 13 - Climate Action , Project ID , info:eu-repo/grantAgreement/EC/H2020/769944/EU/Smart-Taylored L-category Electric Vehicle demonstration in hEtherogeneous urbanuse-cases/STEVE , info:eu-repo/grantAgreement/EC/H2020/824311/EU/Advanced Architectures Chassis/Traction concept for Future Electric vehicles/ACHILES , info:eu-repo/grantAgreement/EC/H2020/769902/EU/Design OptiMisation for efficient electric vehicles based on a USer-centric approach/DOMUS , info:eu-repo/grantAgreement/EC/H2020/769944/EU/Smart-Taylored L-category Electric Vehicle demonstration in hEtherogeneous urbanuse-cases/STEVE , info:eu-repo/grantAgreement/EC/H2020/824311/EU/Advanced Architectures Chassis/Traction concept for Future Electric vehicles/ACHILES , info:eu-repo/grantAgreement/EC/H2020/769902/EU/Design OptiMisation for efficient electric vehicles based on a USer-centric approach/DOMUS , Funding Info , 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 Government 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. , 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 Government 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.
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conference output
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Prieto , P , Trancho , E , Arteta , B , Parra , A , Coupeau , A , Cagigas , D & Ibarra , E 2019 , Geo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EV . in unknown : IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society . 2019-October , IEEE , pp. 2694-2700 , 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 , Lisbon , Portugal , 14/10/19 . https://doi.org/10.1109/IECON.2019.8927769
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