This paper investigates the significance of internal losses of high voltage lithium-ion batteries on the range estimation algorithms of Electric Vehicles (EV) and proposes a method to predict the internal battery losses in close cooperation with the vehicle's control strategy. The method combines a vehicle consumption model taking into account trip based information containing speed limits, live traffic and elevation data within a modular battery prediction model. The battery model calculates future losses of the internal battery resistance based on the control strategy's predicted energy consumption. The battery model takes into account the Temperature, State of Charge (SOC) and State of Health (SOH) parameters of the battery. Simulation results show that internal battery losses vary significantly depending on intensity and form of discharge as well as the State of Charge and Temperature. It is demonstrated that varying internal battery losses can be responsible for inaccuracies in current range estimation algorithms. The proposed method aims at reducing these inaccuracies.