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
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- social sciences social geography transport electric vehicles
- social sciences economics and business business and management business models
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-1 - SME instrument phase 1
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
10823 BERLIN
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.