Data analytics for electric vehicle energy management

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In recent years, Electric Vehicle (EV) popularity has been rapidly growing: in 2020 global EV registration increased 41% despite overall car sales falling 16%. Canada will be banning new internal combustion engine vehicles after 2035 and many other countries are announcing similar plans. Moreover, interest in sustainability is growing and many consumers are willing to pay a premium for sustainability. Meeting such aggressive objectives imposes many challenges. First, new services are needed for EV owners to encourage EV adoption and support energy consumption and cost management. Expansive growth in EV adoption will put a strain on the existing electrical grid and services are needed for distribution companies to estimate future grid load, understand EV charging patterns, predict local grid loads, and support decision making.Consequently, the main objective of this project is to design and develop EV data analytics solution for EV owners and electricity distributors in order to promote EV adoption, reduce the cost of ownership, understand the EV charging impact of the grid, and reduce the impact on the environment. The two main components are: the EV owner-facing and distributor-facing solutions. The EV owner-facing solution will help EV owners manage their charging cost, provide them personalized suggestions and range estimates. The distributor-facing solution will provide large-scale grid impact analysis to support decision-making in respect to grid expansion, renewable integration, and optimizing large-scale EV charging. The project will help London Hydro adapt to changing grid characteristics, provide additional services for its customers, improve demand-response programs, and ultimately reduce the impact on the environment.