Assessment of Residual Range of an Electric Vehicle: Experimental Validation using Real World Driving Cycles

The displayed range in Electric Vehicles (EVs) doesn’t match the value given in specifications, mostly during steeper road gradients and extreme thermal comfort settings. Though extensively researched, an accurate residual range estimation algorithm for addressing range anxiety remains unresolved. The main objective of this research is to assess the residual range of EVs through experimental validation using real-world driving cycles. The Video VBOX device records vehicle location, speed, acceleration, and route elevation data, while environmental data such as ambient temperature and wind speed are collected from OpenWeatherMap using API. The proposed range estimation algorithm then uses the data to calculate a dynamically changing residual range. The estimated results are then compared with odometer readings for real-time experimental verification of the model. For a 66 km trip with elevation changes between 20 m and 115 m, the energy consumption was 6.9 kWh over 16.3% energy regeneration with a specific energy consumption of 153 Wh/km. The proposed model was benchmarked against FASTSim results for the Urban Dynamometer Driving Schedule (UDDS) drive cycle, and the results obtained show an inaccuracy of 0.122%.