Objetivo
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
Ámbito científico
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEInst-2018-2020-1
Régimen de financiación
SME-1 - SME instrument phase 1Coordinador
10823 BERLIN
Alemania
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.