期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 70, 期 9, 页码 9281-9290出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2022.3206748
关键词
Electric vehicles (EVs); instantaneous; power consumption (IPC); power estimation
Several countries are leading the effort of replacing internal combustion engines (ICE) in vehicles with electric ones in order to reduce dependence on oil and carbon emissions. However, the range of electric vehicles (EVs) is still lower compared to ICE vehicles, depending on the energy stored and its utilization rate. In this study, the authors propose a method to estimate the average power consumption of EVs using only localization information, achieving high accuracy without the need for extra sensors.
Several countries are currently leading the challenge of replacing internal combustion engines (ICE) in vehicles by electrically powered ones, mainly motivated by the goal of reducing the dependence on oil and the carbon footprint. However, the autonomy of electric vehicles (EVs) remains significantly lower than their ICE counterpart: it depends on the amount of energy stored and its rate of utilization, characterized by the instantaneous power consumption (IPC). Although IPC can be measured from on-board voltage and current sensors, in route planning applications it is of paramount importance to generate prior estimates from other sources of information, such as the mass of the vehicle, its velocity, acceleration, aerodynamic, and rolling resistances (among other vehicle and terrain parameters). In this work, we propose the estimation of average IPC for a given path, using only localization information provided by a global navigation satellite system antenna, at different levels of errors. Our work is experimentally validated with an EV on the road, achieving on average a 99.7% of power estimation accuracy for a localization error of +/- 1.5 m-as best case-and 73.6% accuracy for +/- 8.6 m of localization error-as worst case. These results encourages us to use only position data to estimate average IPC of EVs, avoiding the need of placing extra sensors into the vehicles.
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