Range anxiety is an obstacle to the acceptance of electric vehicles (EVs), caused by drivers' uncertainty regarding their vehicle's state of charge (SoC) and the energy required to reach their destination. Most estimation methods for these variables use simplified models with many assumptions that can result in significant error, particularly if dynamic and environmental conditions are not considered. For example, the combined efficiency of the inverter drive and electric motor varies throughout the route and is not constant as assumed in most range estimation methods. This study proposes an improved method for SoC and range estimation by taking into account location-dependent environmental conditions and time-varying drive system losses. To validate the method, an EV was driven along a selected route and the measured EV battery SoC at the destination was compared with that predicted by the algorithm. The results demonstrated excellent accuracy in the SoC and range estimation, which should help alleviate range anxiety.