LAUSR

Most of the commercially available range indicator systems for electric vehicles (EVs) do not provide a sufficiently accurate range to destination, as the environmental factors and driver's behavior are generally not taken into account. In this paper, a real-time range indicator system is developed and implemented using online environmental data from various internet resources to estimate accurately the real-time state of charge and the remaining range for the EV while it is on the road. The estimation considers 1) the dynamic wind speed and wind direction with respect to vehicle position, 2) the probability of rain and ambient temperature, 3) the dynamic effective rolling resistance and terrain adhesion coefficient (based on the condition of the road surface), 4) the time-domain efficiency analysis of the propulsion system, 5) the online traffic conditions and auxiliary loads, and 6) the braking force distribution used in commercially available EVs. The real-time range indicator system is validated using measured data from a 2012 Nissan Leaf driven along a selected route in Australia with the maximum error of 8% for the entire route and less than 1% error at the destination.