GNSS-Based Estimation of Average Instantaneous Power Consumption in Electric Vehicles

Abstract

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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 1.5$</tex-math></inline-formula> m –as best case– and 73.6% accuracy for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm 8.6$</tex-math></inline-formula> 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.