Companies such as Wave and Magment offer a variety of approaches for charging vehicles without plugs while they're being stored or even used, but costs stand in the way of broader adoption.
Starting this summer, the public buses in the Oberhaching suburb of Munich, Germany, won’t have to be plugged in to charge overnight anymore. Stefan Schelle, the mayor of Oberhaching, is taking advantage of the fact that an innovative startup has its offices in his community: Magment, short for “magnetizing cement,” will install its underground charging pad in the coming months. As soon as that happens, the buses will charge while they wait at the city’s main station or while stored at their overnight quarters.
In his light-filled office, Magment’s co-founder and CEO, Mauricio Esguerra, demonstrates how the new technology works: The lights on his black model car only flash when he puts the miniature Porsche directly atop the induction plate. “This works just like when you charge your iPhone on its charging pad or heat a pot on an induction range. People don’t have to be afraid of magnetic fields or anything like that,” says the 60-year-old Colombia-born entrepreneur. “The induction only gets activated when the storage battery is placed directly on top.
Patented by Esguerra, the “magnetizing concrete” is able to target the charge quite precisely. The batteries will be mounted in a box underneath the vehicles such as the retrofitted public buses. “Look, here’s one passing by,” says Esguerra, pointing out the window as a blue city bus rides past his office.
An invention finds its purpose
Esguerra grew up in Bogotá, studied physics at the Technical University Munich where he fell in love with a German woman, and started a family in her home country. For 15 years, he developed magnetic products, including the magnetizing cement, for Siemens, Europe’s largest industrial manufacturing company. The patent belonged to Siemens, of course. “But there were hardly any electric vehicles yet,” Esguerra says, “and Siemens didn’t quite know what to do with this invention.”
Esguerra changed companies a few times but, in 2015, he got an offer from Siemens. The patent for the magnetizing cement was expiring and Siemens wasn’t interested in keeping it. Would he, as the inventor, want it back? “I did not hesitate a second,” Esguerra remembers with a smile. “I’m a magnetician at heart.” That same year, he founded Magment to finally make use of the technology he created 20 years ago.
To demonstrate how his cement is made, he opens the lid of a plastic bucket filled with cement powder. Mixed in are fingernail-sized black pieces, so-called ferrites, mainly consisting of three ceramic oxides: iron, nickel and zinc. Conventionally, they are used in electronics such as cell phones, computers and cables. Molded in concrete, ferrites create a magnetic field that can transport charge to a vehicle, potentially eliminating range anxiety for EV drivers.
Molded in concrete, ferrites create a magnetic field that can transport charge to a vehicle, potentially eliminating range anxiety for EV drivers.
Magment
“Ferrites have extremely high rejection rates,” Esguerra adds. “It’s comparable to other ceramics: As soon as there is a small tear or crack, the material is rejected. We are talking about a rejection pile of 500,000 tons per year worldwide. There are mountains of unused materials.”
Exactly this fact was the starting point of his research at Siemens: “What can we do with this energy-intensive material? Back then, it was crushed up and mixed into the cement for building streets, without adding any function.” Today, too, the Magment material can simply be mixed with the conventional material and equipment of the cement industry. “We take advantage of the fact that we don’t have to build factories and don’t have high transportation costs."
In addition to saving resources, recycled ferrite also makes concrete more durable.
No plugs, no charging breaks
A young intern in the office next door winds cables around a new coil. These coils will later be lowered underground in a box, connected to the grid and encased in magnetizing concrete. The recipient box looks similar; it’s another coil but smaller, and it will be mounted underneath the carriage of the vehicle. For a car, the battery box would be 25 by 25 centimeters (about 10 inches), for a scooter five by five centimeters (about two inches).
Esguerra pushes an electric scooter into a cemented scooter rack next to his office. The charging pad is invisible. A faint beep is the only sign that it has started charging. “Childs play!” Esguerra says. “Even when someone puts in the scooter a little crooked, the charge still works. Our efficiency rate is up to 96 percent.” From this summer on, hotel chains in Munich will try out this system with their rental scooters, at a price of about 500 Euros per charging station.
Compared to plug-in charging, Magment’s benefits include smaller batteries that charge slower and, therefore, gentler, so they may last longer. Nobody needs to plug in the vehicles manually anymore. “Personally, I’ve had an EV for six years,” Esguerra says, “and how often does it happen that I forgot to plug it in overnight and then start out with a low charge in the morning? Once people get used to the invisible charging system, it will become the norm.“
There are also downsides: Most car companies aren’t ready for the new technology. Hyundai is the first carmaker that announced plans to equip some new models with inductive charging capability. “How many cars are electrified worldwide?” Esguerra asks and gives the answer himself: “One percent. And how many forklifts are electrified? More than 70 percent!” Therefore, Magment focuses on charging forklifts, e-scooters and buses.
Magment has focused most of its efforts on charging forklifts and other vehicle types that are entirely or predominantly electric, unlike cars.
Magment
On the morning of my visit to Esguerra’s office, a developer of the world’s third-biggest forklift manufacturer is there to inspect how the technology works on the ground. In the basement, a Magment engineer drives an electric forklift over a testbed with invisible charging coils, turning on the green charging light. Esguerra opens the interior of the forklift and points out the two batteries. “With our system, the forklift will only need one battery.” The savings, about 7,000 Euro per forklift, will pay for the installation of Magment’s charging system in warehouses, Esguerra calculates. “Less personnel and no unnecessary wait times for charging will lead to further savings,” he says.
To implement the new technology as efficiently as possible, Magment engineers began recording the transport routes of forklifts in warehouses. “It looks like spaghetti diagrams,” Esguerra explains. “Soon you get the areas where the forklifts pass or wait most frequently. This is where you install the chargers underground.” The forklifts will charge while in use, without having to pause for charging breaks. The method could also work for robots, for instance, in warehouses and distribution centers.
Roads of the future could be electric
Potential disadvantages might become apparent once the technology is more broadly in use. Therefore investors were initially reluctant, Esguerra admits. “Some are eager to be the first but most prefer to wait until the technology has been extensively used in real life.”
A clear hurdle today is that electrifying entire freeways with induction coils would cost at least 1 to 1.5 million Euros per kilometer. The German Department for Transportation even calculates overall costs of 14 to 47 million Euros per kilometer. So, the technology may only make sense for areas where vehicles pass or dwell the longest, like the Oberhaching train station or a busy interstate toll booth.
And yet, Magment is ramping up to compete with other companies that build larger inductive charging pads. The company just finished the first 20 meters of a testbed in Indiana, in partnership with the Purdue University and the Indiana Department of Transportation. Magment is poised to build “the world’s first contactless wireless-charging concrete pavement highway segment,” Purdue University announced.
The project, part of Purdue’s ASPIRE (Advancing Sustainability through Powered Infrastructure for Roadway Electrification) program, is financed by the National Science Foundation. “Indiana is known as the Crossroads of America, and we’re committed to fortifying our position as a transportation leader by innovating to support the emerging vehicle technology,” Governor Eric J. Holcomb said. If testing is successful, including the concrete’s capacity to charge heavy trucks operating at higher power (200 kilowatts and above), Indiana plans to identify a highway segment to install Magment’s charging pads. The earliest would be 2023 at best.
In the meantime, buses in the Californian Antelope Valley, trams at Hollywood's Universal Studios and transit buses in Tampa, Florida, are already charging with inductive technology developed by Wave, a company spun out of Utah State University. In Michigan, Governor Gretchen Whitmer announced plans to build a test route for vehicles to charge while driving, in collaboration with the Israel-based company Electreon, and this year contracted to build the first road-based charging system in the U.S. The state is providing support through an innovative grant program.
Costs remain one of the biggest obstacles, but Esguerra’s vision includes the potential that toll roads could charge a premium for inductive charging capabilities. “And in reverse, a driver who has too much energy could feed his surplus into the grid while driving,” Esguerra dreams.
Meanwhile, Wave’s upcoming big projects are moving trucks along a route in Southern California and running a UPS route between Seattle and Portland. Wave CTO Michael Masquelier describes the inductive power transfer his company champions as “similar to a tuning fork. By vibrating that fork, you sent energy through the air and it is received by another tuning fork across the room. So it’s similar to that, but it’s magnetic energy versus sound energy.”
He hopes to partner with Magment, saying that “the magnetizing cement makes installation easier and improves the energy efficiency.” More research is needed to evaluate which company’s technology will prove to be the most efficient, practical, and cost-effective.
Esguerra’s vision includes the potential that toll roads could charge a premium for inductive charging capabilities. “And in reverse, a driver who has too much energy could feed his surplus into the grid while driving,” Esguerra dreams.
The future will soon arrive in the idyllic town of Bad Staffelstein, a quaint tourist destination in the Upper Franconia region of Germany. Visitors will be taken to and from the main station and the popular thermal bath by driverless shuttles. Together with the University of Wuppertal, the regional government of Upper Franconia wants to turn its district into “the center of autonomous driving.” Magment is about to install inductive charging pads at the shuttle stations and the thermal bath, eliminating the need for the shuttles to stop for charging times. No more drivers, no cable, no range anxiety. Masquelier believes that “wireless and autonomous driving go hand in hand.” Science fiction? It will become science reality in spring 2023.
CORRECTION: An earlier version of the story erroneously mentioned that Electreon required overhead cables.
Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
