SBIR/STTR Research Award

Contextual Predictions & Eco Services for EVs & PHEVs

Award identifier 4528621ba5bd6aac374a02aba6941549381a4e7a9b295057ed056751f1efd052Awarding agency Department of Energy

Award amount

$198,158

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
AV-CONNECT, INC.
Proposal award date
2020-06-29
Contract end date
2021-03-28
UEI
T8HJQ22FBKD3
Solicitation number
DEFOA0002146
Topic code
12c

Research abstract

Agencies, researchers and companies recognize that today’s abundance of sensor and other data offers a great opportunity for better use of energy resources by introducing energy-awareness into algorithms for vehicle control and decision-making. AV-Connect has identified a gap between the broad availability of maps, traffic forecasts, and large streams of vehicle sensor telematics, and the need for energy-aware algorithms that use real-time data to optimize vehicle behavior that can reduce vehicle energy consumption. AV-Connect will combine machine learning algorithms and decision-making algorithms to process real- time data streams from vehicles’ telematics, traffic and weather forecasts, and deliver tailored route and charging recommendations for electrified vehicles. It will target range anxiety by accurately predicting vehicle energy performance and by selecting routes and charging options that minimize energy usage. AV-Connect’s proposed platform addresses the target set by topic 12.C, as it uses real-time data to identify and leverage opportunities for better energy usage, while alleviating a big obstacle to rapid adoption of electrified mobility. In Phase I we focus on EVs and PHEVs for personal transportation; in that space, we identified a technology gap due to the lack of integration between vehicle telematics data, traffic and routing maps. If successful, our platform can also increase the value of electric fleets of light vehicles and delivery robots. In Phase I, AV-Connect will deploy and quantify the impact of a learning-based eco-routing platform for Electric Vehicles (EVs) and Plug-in Hybrid EVs (PHEVs). The platform will consist of IoT software, machine learning algorithms, and decision-making algorithms. It will leverage real-time data streams from vehicles’ telematics, traffic and weather forecasts, and deliver tailored route and charging recommendations. It will target route energy reduction and range anxiety by accurately predicting vehicle behavior and by selecting routes and charging options that minimize energy usage. AV-Connect will use head-to-head road tests to validate the variation of energy consumption and travel time. AV-Connect’s WideSense Eco-Services platform will deliver numerous cloud services to electrified vehicles from high-precision range prediction, eco-routing, eco-cruise control among others. This would enable a more rapid adoption of EVs and improve their energy performance, resulting in dramatic reductions in fuel emissions and GHG through the replacement of gasoline vehicles.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2020–2023). Reported award amounts total $3,750,648. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Energy, National Science Foundation

Agency intelligence

Department of Energy

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