Towards an Information System for Evidence-Based Analysis of Charging Behavior, Charging Demand, and Battery Degradation of Electric Vehicles

Abstract

Batteries in Electric Vehicles (EV) are subject to a degradation process that has many, yet not fully understood, influential factors. Typically, the battery is continuously monitored by a proprietary Battery Management System (BMS) which records and analyzes various key figures of the battery. Because the BMS is proprietary, the data collected throughout the lifetime of an EV and its battery cannot simply be looked into by the owner but only by the EV manufacturer and licensed service providers. Hence, the EV owner is dependent on the manufacturer to retrieve accurate data regarding the State of Health (SOH) of the battery, e.g. when selling the vehicle or when the battery needs replacement. An in-depth understanding of charging behavior and the degradation process of an EV's battery requires a vast amount of data, which is a crucial factor limiting current research. This paper proposes an information system that blends into the EV charging infrastructure and utilizes a crowdsourcing approach to collect charging transaction data. In order to identify concealed dependencies with regards to battery degradation and to identify patterns in the charging behavior, an enrichment of the raw transaction data is motivated and different information providers are discussed. This augmentation integrates environmental information from various sources such as weather and location data. On a macroscopic view, analyses could point out the correlation between weather, public events, location, and charging demand. On an individual basis, the effect of environmental impacts, charging behavior, and driving profile on battery degradation can be investigated and compared.