Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the grid are required for effective Vehicle-to-Grid (V2G) implementation. As such, a cloud-based big data platform is proposed in this presentation to exploit these data. Additionally, this study aims to develop smart algorithms, which optimise different factors, including BEV cost of ownership and battery degradation. Dashboards are developed to provide key information to different V2G stakeholders.
Florent Grée is a data science engineer in the CAE and Data Science Team. He has 7 years’ experience within AVL UK and has taken a leading role in key projects including data analysis, system modelling & simulation and system engineering. He has worked on internal AVL R&D project as well as commercial projects working in partnership with Ford, Jaguar Land Rover. The last 3 years, he has been mainly involved in data science projects. He has a master’s degree in electrical engineering.