Browsing by Keyword "Energy consumption estimation"

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    Geo-Fence Based Route Tracking Diagnosis Strategy for Energy Prediction Strategies Applied to EV
    (IEEE, 2019-10) Prieto, P.; Trancho, E.; Arteta, B.; Parra, A.; Coupeau, A.; Cagigas, D.; Ibarra, E.; POWERTRAIN; Tecnalia Research & Innovation
    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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    Route tracking diagnosis algorithm for EV energy prediction strategies
    (2019) Prieto, P.; Trancho, Elena; Arteta, B.; Parra, A.; Coupeau, A.; Cagigas, D.; Ibarra, E.; POWERTRAIN; Tecnalia Research & Innovation
    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.