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Artificial Intelligence based Smart Charging Assistant for Electric Light Commercial Vehicle Fleets

Objective

Light Commercial vehicle fleets are important for the EV adoption A LCV is a business tool, so the utilisation rate and ensuring business continuity are key. Integrating and managing electric LCV is challenging due to the limited driving range and charging infrastructure.

In this project, our aim is to make a feasibility study of developing the first AI based charging assistant for Light Commercial Vehicle fleets. As part of the project aim is to research into the technical feasibility of analyzing vehicle charging data from the electric LCVs and combine that with consumption data from public, home and office chargers to ensure business continuity of eLCV fleets and save money on charging and reducing idle time.

According to the IEA, EV/HEVs stock is projected to reach 200 Million units by 2030. The total EV/HEV market is expected to grow up 233EUR bn by 2021 growing at a 40.65%

The project will allow us to facilitate the market spread of eLCVs with the first machine learning based smart charging assistant tool based on our unique algorithm that combines advanced energy management and telematics. This will imply to disrupt into the European and international market by saving significant money on eLCV charging and reducing downtimes for our client while generating 5,1 M€ profit until 2022 and a generation of 42 new direct jobs on the company level for Konetik.

Konetik is a telematics company focusing on products helping the widespread of electric vehicles. Konetik serves 300+ companies 3 energy utilities already engaged (NKM, ENGIE, EnBW) regarding a pilot program. Selected as one of the top 100 Berlin based startups

Field of science

  • /social sciences/economics and business/business and management/commerce
  • /social sciences/social and economic geography/transport/electric vehicles
  • /social sciences/economics and business
  • /natural sciences/computer and information sciences/artificial intelligence
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning

Call for proposal

H2020-SMEInst-2018-2020-1
See other projects for this call

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

KONETIK DEUTSCHLAND GMBH
Address
Akazienstrasse 3/A
10823 Berlin
Germany
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 50 000