Spatio-temporal analysis of state-of-charge streams for electric vehicles

Abstract

This paper collects the SoC (State-of-Charge) changes of electric vehicles and analyzes the battery consumption behavior. For multiple SoC streams generated on the same road, a Hadoop Pig script filters essential information fields out of the vast amount of SoC records, while its user-defined function adds the distance and the time taken from the start point. Next, neural networks are built to trace the SoC dynamics according to both spatial and temporal aspects of SoC records using the R statistics package. A time-combined model reduces the fitting error by 50 %, compared with the distance-only model. The ongoing project keeps accumulating SoC streams and our model will investigate the effect of other parameters and correlate different streams. An accurate model for major roads taken by most trips, will lead to a more efficient estimation of battery consumption for any point-to-point routes.