Abstract:

Electric vehicles with connectivity and autonomy (C/AEVs) have the potential to offer reliable, effective, and low-emission transportation options. To ensure that all advantages associated with C/AEVs are realised, it is imperative to manage the C/AEV lithium-ion battery (LIB) system effectively. This necessitates that the operation of the C/AEV system inform the design and control of LIBs. In order to accurately characterise and simulate their LIBs, application-specific testing methodologies must first be developed. This article first shows how C/AEV operation differs from human-driven electric vehicle operation. In order to create designs of experiments that represent a variety of C/AEV driving modes and LIB system sizes, laboratory-prone synthetic duty cycles are generated from C/AEV driving data. The authors provide data gathered from 31 LIB cells that were used in the synthetic cycling tests. An application-specific C/AEV LIB dataset for the construction and calibration of data-driven battery models for real-time control and operation is made available to the academic community in this study.