Data Is Required to Solve EV Charging Challenges

By Hubert Yoshida posted 08-23-2021 19:40

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Recently the Wall Street Journal published an article by Christopher  Mims, What’s Missing in the Electric-Vehicle Revolution: Enough Places to Plug In. In this article he described the experience of a driver of a 2017 Chevrolet Volt, who drove from Tampa, Fla. to Fort Carson, Colo., who spent about 58 hours on the road, a journey of 1,900 miles which would have only taken 30 hours In a gasoline-powered vehicle. This time difference was due to his need to regularly power up the Bolt’s battery at a “fast” charger—so called because they’re many times faster than typical home chargers. (Fast charging stations provide 50kw, compared to home charging stations which top out at 7.2kw)

In addition to the extra time, the inconveniences that he suffered included too few charging stations, too much demand at the stations that are available, broken chargers, confusing payment systems, exorbitant electricity rates, and uncertainty over how long his car needed to charge.

To Tesla’s credit, they addressed this problem early on by building a nationwide fast-charging infrastructure for its vehicles even before its cars were widely adopted. During the development and rollout of Tesla’s car-and-charger platform, the company offered to allow other companies to use the patents on its charging standards and equipment, but none took it up on the offer. While Tesla offered “open source” charging technology, using it, meant signing off on Tesla’s terms which the world’s automakers were unwilling to accept. Instead, they collectively adopted a competing standard in the U.S., making their vehicles incompatible with Tesla’s. The reverse isn’t true: With an adapter, Teslas can charge at nearly all fast-charging stations.

In the early days of the automobile, there were similar concerns about gas stations. However, today, there are more than 128,000 retail gas stations, compared to less than 5000 fast charging stations in the U.S. according to the Department of Energy. The Biden administration has proposed building a network of 500,000 chargers in the next five years, which would cost billions. The fact that many believe such a government investment is required shows just how little faith many industry insiders have in the ability of private enterprise to solve this problem. One issue: Building out the nation’s charging infrastructure might not be profitable.

Other problems not mentioned in the WSJ article was the impact on the electrical grid and the cost of prime-time usage. What happens when every EV owner comes home at 6pm and plugs in his home charger at the same time to get ready for the next day’s commute? What happens to a fleet user like a metro bus who needs to be ready for peak usage in the morning and in the evening hours, or an Uber driver who never knows when his next peak will be? How does a fleet user choose the optimum time to charge when the utility rates are the lowest? In order to answer these question, to optimize the maxim use of electrical grid capacity and minimize cost, requires data. Before spending billions of dollars on charging stations, we need to have data to understand usage and demand, and the effect of using smart charging technology that optimizes usage with demand.

Where will people need chargers? What is the best time to charge them up? Can our electricity grid provide enough power in the right places? These are all questions which need to be answered, and quickly. Currently, Hitachi is working with companies in London and the South East, UK, in playing host to the world’s largest commercial EV trial. Optimise Prime is using IoT technology to track the charging activity of up to 3,000 commercial vehicles. It is endeavoring to unearth all of the potential issues surrounding the large-scale uptake of EVs and developing solutions for smart depot and home charging.

The Optimes Prime project is a collaborative effort. With the backing of UK energy regulator Ofgem, Hitachi, UK Power Networks, Royal Mail, Centrica, Uber and Scottish and Southern Electricity Networks are working together to collect and analyze data from EV vehicles. Hitachi Vantara is designing, building and operating the project’s IoT platform. The platform manages all the data from the vehicles and helps develop the results. Hitachi is also coordinating the project workstreams and developing solutions to optimise the "smart" charging of fleets of EVs at depots, allowing more vehicles to charge within the network’s existing capacity.

The result will be the world’s largest commercial electric vehicle dataset, which will help the project partners devise practical ways of overcoming the up-front costs that are currently preventing widespread commercial EV deployment, while reducing the cost of the EV transition for electricity bill payers. The dataset will be publicly available, allowing urban planners, power grid engineers and, of course, vehicle operators, to prepare for EVs.

Hopefully the Biden administration will review this data before spending billions of dollars on charging stations.