A Framework for a Connected Electric Vehicle Cloud to Learn Drivers' Behaviors

A common question around the development of electric vehicles (EVs) is associated with the power, performance and reliability of their battery-powered systems in real world driving situations. The aim of this research work is to evaluate and characterize an EV battery power under real-world driving conditions in order to inform the design of the next generation systems. Also, we develop a framework of Connected Electric Vehicle Cloud (also known as connected EV cloud, or EV-cloud) to collect energy patterns and analyze driving behaviors for EV energy management. In this work we used a machine learning method based on Google's TensorFlow framework (TensorSOM) as our kernel analytic tool. Additionally, we utilized the SOM Toolbox on the Matlab platform to confirm the TensorSOM clustered results. The experimental result demonstrated that our proposed approach is a sensible solution for learning EV drivers' behaviors.