Analysis of Driving Behavior's Impact on Battery Discharge Rate for Electric Vehicles

Abstract

A robust battery management system (BMS) is important for electric vehicle (EV) to preserve the battery health. As EV is gaining popularity as a mode of public transport, the fleet operator should be concerned of optimizing the usage of a fully charged battery, this boils down to the driving behavior. This paper investigates the relation of driving parameters to the battery discharge rate. The driving behavior is associated with vehicle speed, motor speed, throttle position and brake pressure. The data is collected from experiment where the EV is operated through urban roads in Singapore. Principal Component Analysis (PCA) is used to reduce dimensionality of data. We identified an interesting feature in the data distribution, which can be quantified by centroid. Using this feature, we conduct the regression analysis and find out that the centroid has a linear relationship with the duration of battery retaining its state of charge (SOC), which is supported by Pearson correlation coefficient of 0.89 obtained in the analysis.