Charging Station Site Selection Solutions

INCEPTS is a patent-pending technology for simulating real-world electric vehicle performance by using high-fidelity battery and vehicle dynamics that incorporate local conditions. We’re currently using INCEPTS to guide policy and investments for cost-effective and equitable charger placement.

By simulating thousands of cars in an area, INCEPTS can predict charger demand and suggest charger locations to meet that demand. Unlike other approaches, which assume a constant range, INCEPTS directly simulates vehicles producing a richer picture of where chargers are needed.

For more information visit the INCEPT website.

Mobilyze.ai was founded in 2019 by a team of MIT researchers passionate about making widespread adoption of electric vehicles (EVs) a reality. 

The company’s goal is to solve the problem of access to EV charging using location analytics so that infrastructure investors can profit, and EV drivers have an ownership experience that is even better than filling up a gasoline vehicle today. Mobilyze.ai provides EV location intelligence globally, helping firms to make the promise of EVs a reality.

Mobilyze.ai’s machine learning analytics solution is designed for charging network operators, site hosts, utilities, cities and state governments, automakers, and ride-hailing companies, and commercial fleet operators. The companies software solution offers enables organizations to:

• Forecast utilization at existing stations to optimize revenues.
• Identify new sites that have the greatest market potential.
• Quantify the impact of EV rate case deployments. 
• Target environmental justice communities, households without dedicated off-street parking, ride-hail drivers and public fleets.
• Identify individual households most likely to purchase EVs.
• Determine optimum DC fast-charging locations to minimize time spent charging mid-shift for ride-hailing and fleet drivers.

For more information, visit the Mobilyze.ai website.

Otonomo’s EV Intelligence solution is based on mobility patterns and combined with with battery level data, enables charge point operators to pinpoint high demand corridor site locations for EV charging stations. The EV Intelligence solution empowers strategic, data-driven decisions by transforming vast amounts of anonymized data and activity signals into actionable, impactful, and monetizable intelligence and insights, including:

• EV driver and point of interest:
  
  • Latitude/Longitude area insights
  • Seasonality / Day / Night
• Charger type Analysis
  
  • • kWh potential usage
    • AC/DC charging station recommendations

For more information, visit the Otonomo website.

The Foundry eMobility solution is an out-of-the-box offering by Palantir to expand, maintain, and future-proof electric vehicle charging networks. It can be deployed by EV charging station manufacturers, charge point network operators (CPOs), utility companies, and automakers who are expanding charging access for their customers.

Intelligently plan network expansion by forecasting charging demand with Foundry’s ML model management suite. Then, quickly integrate IOT systems as they are installed in the field, ensuring seamless integration into the network.

For more information, visit the Palantir website.

Stable was founded by former MIT researchers Rohan Puri and Jamie Schiel to accelerate investments in EV infrastructure by making them predictable and effective, paving the way for EV adoption in every corner of the globe. 

The Stable enterprise software platform is powered by comprehensive datasets and precision machine learning and is designed to predict site EV charging station performance and help companies improve performance by optimizing energy rates, equipment size, and location. 

Stable is currently working with major utilities, charging networks, banks, and infrastructure developers across the U.S. with investments from Trucks, MIT E14, Ubiquity Ventures, Upside, and more.

For more information, visit the Stable website.

StreetLight’s Mobility Metrics solution helps organizations maximize the benefits of electric vehicle (EV) infrastructure for a targeted market. From highlighting gaps in existing charging infrastructure to accessing key mobility metrics for EV infrastructure rollout to predicting future demand patterns.

Identify prime EV charging locations along any corridor or highway exit by blending StreetLight’s Mobility Metrics — including volume, trip distance, peak time, dwell time, and visitor versus resident demographics — with data such as vehicle registration information and electric grid data. Analyze and evaluate your EV infrastructure portfolio by merging your EV site location data with insights to conduct traffic impact studies.

StreetLight’s Mobility Metrics solution helps organizations:

• Identify the most optimal EV charging sites by accessing existing traffic demand metrics: Utilize multimodal traffic volume and activity patterns to compare and prioritize top EV sites.
• Determine aggregate demographic profiles of existing drivers at sites: Study the travel activity of visitors, workers, and residents at any location to understand who your groups of customers are.
• Identify the most frequent route to sites and understand how long travelers are staying: Analyze local travel patterns, including vehicle start, end, and dwell times to plan your network based on the region’s charging needs.

For more information, visit the Streetlight website.

Volta’s PredictEV® software product makes it easy to understand future EV adoption and EV charging demand in your area, so that you can build the network, incentives, and solutions to satisfy your customers’ needs. All backed by real charging network data and advanced AI. PredictEV® is designed for:

Utilities: Plan today to meet tomorrow’s demand for EV charging. Site stations where they’ll be used the most.

Public Agencies: Meet zero-carbon transportation goals with smart EV incentives, station locations and programs.

Consultants: Gain a data-driven view of EV adoption for your clients’ energy and transportation projects.

For more information, visit the Volta PredictEV®.