Estimation of the residual energy in battery electric vehicles

Abstract

The driving range of battery electric vehicles (BEVs) has been fairly extended during recent years, as a consequence of little improvements in energy density of lithium-based batteries. Nonetheless, charging stations are not widespread installed in all geographical areas. For these reasons, range anxiety still acts as a barrier when considering to move from traditional fuel vehicles to BEVs. Most of the traditional range estimation methods are untrustworthy because they leverage upon the electric energy drawn by the motor. As a matter of fact, the estimates do not generally match the energy that is actually drawn from the battery, as they do not take into account the non-linearity of battery efficiency and its dependence from the state of charge. In this work, we propose and incorporate a state-dependent battery model, including the non-linear characteristics, into a range estimator that takes into account slope, speed limits as well as traffic information. Our simulation results show that the energy estimation is 10.19% more accurate with respect to the conventional estimation based on linear battery model.