An Electrifying Idea For Roads
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.
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on new scientific theories and progress to give you a therapeutic dose of inspiration headed into the weekend.
Listen on Apple | Listen on Spotify | Listen on Stitcher | Listen on Amazon | Listen on Google
Here are the stories covered this week:
- The eyes are the windows to the soul - and biological aging?
- What bean genes mean for health and the planet
- This breathing practice could lower levels of tau proteins
- AI beats humans at assessing heart health
- Should you get a nature prescription?
Two-and-a-half year-old Huckleberry, a blue merle Australian shepherd, pulls hard at her leash; her yelps can be heard by skiers and boarders high above on the chairlift that carries them over the ski patrol hut to the top of the mountain. Huckleberry is an avalanche rescue dog — or avy dog, for short. She lives and works with her owner and handler, a ski patroller at Breckenridge Ski Resort in Colorado. As she watches the trainer play a game of hide-and-seek with six-month-old Lume, a golden retriever and avy dog-in-training, Huckleberry continues to strain on her leash; she loves the game. Hide-and-seek is one of the key training methods for teaching avy dogs the rescue skills they need to find someone caught in an avalanche — skier, snowmobiler, hiker, climber.
Lume’s owner waves a T-shirt in front of the puppy. While another patroller holds him back, Lume’s owner runs away and hides. About a minute later — after a lot of barking — Lume is released and commanded to “search.” He springs free, running around the hut to find his owner who reacts with a great amount of excitement and fanfare. Lume’s scent training will continue for the rest of the ski season (Breckenridge plans operating through May or as long as weather permits) and through the off-season. “We make this game progressively harder by not allowing the dog watch the victim run away,” explains Dave Leffler, Breckenridge's ski patroller and head of the avy dog program, who has owned, trained and raised many of them. Eventually, the trainers “dig an open hole in the snow to duck out of sight and gradually turn the hole into a cave where the dog has to dig to get the victim,” explains Leffler.
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”