A Real-Time Range Indicator for EVs Using Web-Based Environmental Data and Sensorless Estimation of Regenerative Braking Power

Most of the commercially available range indicator systems for electric vehicles (EVs) do not provide sufficiently accurate range to destination, as the environmental and driver's behavior (driving style of a particular driver) factors 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 (SoC) and the remaining range for the electric vehicle while it is on the road. The estimation considers: (i) the dynamic wind speed and wind direction with respect to vehicle position, (ii) the probability of rain and ambient temperature, (iii) the dynamic effective rolling resistance and terrain adhesion coefficient (based on the condition of the road surface), (iv) the time domain efficiency analysis of the propulsion system, (v) the online traffic conditions and auxiliary loads, and (vi) the braking force distribution used in commercially available electric vehicles. 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.