AI Plays Key Role in EV Charger Deployment and More

AI and EV are working together to help the USA.

AI, of course, stands for artificial intelligence and you know EV as our favorite little acronym for electric vehicles.

But, how is AI helping with EVs in the United States of America (and other countries)?

In many ways, actually.

Charger Deployment

The state of Michigan, for example, is using AI to help transportation planners decide where to put EV charging stations.

The AI software bases its recommendations on current EV adoption in those areas, EV demand and expected charger utilization. Michigan state officials have said the software has already recommended that eight new chargers be installed at several Kroger grocery store locations.

There are also myriad scientific studies that discuss how AI and machine learning can be used to help planners decide where to locate EV chargers and what type of chargers to install.

Over in the United Kingdom, various local governments have partnered with AI firms to help them figure out where they need to put EV charging stations to bolster EV adoption and benefit the entire community.

Oxfordshire City Council, for example, is working with Mind Foundry to use geospatial modeling and a variety of data sources to figure out where the city requires Level 2 and Level 3 EV charging units.

In a techUK case study about the project, Mind Foundry said: “The workflows are powered by scalable probabilistic machine learning and connect to both live and historic data sources, providing sophisticated scenario modeling and rollout planning capabilities.”

An extremely simplified version of what’s happening with the project is that Mind Foundry is taking all sorts of data; like population density, current EV charging infrastructure, forecasted EV adoption rates, and a whole lot more; and using AI to pinpoint where the city should add EV charging stations and what type of stations those should be.

For a much more detailed look at exactly how artificial intelligence is created and used in this capacity, you can check out this article in Towards Data Science by Obed Sims, which discusses the development of a computer model that indicates optimal locations for EV charging stations in Manchester.

Planning tools

There are some great new tools to help transportation planners when it comes to deploying EV chargers.

StreetLight Data, for example, has developed a new data-driven dashboard that planners can use to help them decide where to place new EV charging stations in their location.


To support inter-city travel via EV, researchers at Oak Ridge National Laboratory have developed an open-source modeling tool, called the ​​Regional Electric Vehicle Infrastructure Strategic Evolution (REVISE), to help regional infrastructure planners decide where to place charging stations along interstate highways.

AI isn’t just being used for deciding the best places to install EV charging stations, though.

Grid Management

In addition to charging station deployment, AI is also being used for electricity grid management. Up north in Ottawa, Ontario, the Ontario Energy Board (OEB) has partnered with BluWave-ai and Hydro Ottawa to use AI to manage EV charging during peak demand periods.

The expected increase in electricity demand as EVs become more common in Ontario is 20% annually. To help with this yearly increase, a pilot project, called EV Everywhere, will use AI to create an online service for EV owners. This service will pool the storage and charging capabilities of EV batteries in an effort to smooth out the various peaks in electricity demand and help drivers take advantage of lower cost energy during off-peak hours (generally in the evenings, overnight and on weekends).

“With input from customers, optimized charging times and strategic placement of battery storage, the platform aims to reduce the strain on the local grid, as well as allow EVs to provide services to the broader provincial electricity market,” the OEB said in a news release.

Trip Planning

In January 2021, Google introduced a then-new AI tool that helped drivers plan out routes based on the available public chargers between their starting points and their destinations.

Part of the native Android Automotive operating system available in some EVs, the AI algorithm suggests charging stops along a driver’s route based on their current location, the amount of juice still left in their battery and the type of plug their vehicle uses.

In a blog post introducing the AI algorithm, Google said:

“Now when you enter a destination that requires two or more recharge stops, algorithms in Maps will search and filter through tens to thousands of public charging stations to find the most efficient route — all in less than 10 seconds. You can see how long each charge will take and your updated total trip time, so your final ETA will never again be a mystery.”

Fast Charging Battery Development

Researchers from the Idaho National Laboratory are using AI and machine learning to speed up EV battery charging without damaging the vehicle’s battery.

With today’s current charging technology, trying to make a lithium-ion battery charge faster can cause lithium metal to build up on the battery, shortening its lifespan and range, or it can even cause the battery’s cathode to wear and crack.

To avoid this, researchers are trying to come up with new charging protocols for EV batteries that can fully charge a vehicle’s battery in as little as 10 minutes by feeding data from all kinds of lithium-ion batteries into a machine learning algorithm.

“We’ve significantly increased the amount of energy that can go into a battery cell in a short amount of time,” researcher Dr. Eric Dufek said. “Currently, we’re seeing batteries charge to over 90 percent in 10 minutes without lithium plating or cathode cracking.”

The hope is that the team can use what they’ve learned about super fast charging in existing batteries to help design newer batteries that can all be charged within just a few minutes, making EV charging nearly as quick as filling up a vehicle with liquid fuel like gasoline or diesel.

The ultimate goal of the researchers is to develop EV batteries that are able to “tell” the EV charging station they are using how best to charge them to do it quickly while avoiding damage.

Whether you’re using AI to help you designate the best spots to put EV chargers in your region or you are a business owner who wants to help facilitate the transition to a cleaner, greener future, Blink Charging can help you choose the best EV charging options to suit your needs.

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