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Hyundai Ioniq
Thrifty With Energy: The Hyundai Ioniq wrings more range out of a watt-hour than any other EV around.
Photo: Hyundai

RANGE

200 km

EV EFFICIENCY

136 mpge

HYBRID EFFICIENCY

58 mpg

The most energy-efficient car in America isn’t a Tesla, Toyota, or even the remarkable Chevrolet Bolt. It’s a Hyundai. With a range of 200 kilometers (124 miles), the all-electric Ioniq comes nowhere near the Bolt’s astounding 383 km (238 miles). But the Hyundai’s gasoline equivalent of 1.73 liters per 100 kilometers (136 mpge) tops all current EVs.

This Year’s
Winning Autos

Let’s do some quick math. Americans will pay about US $3.36 to charge the Ioniq’s 28 kilowatt-hour battery pack, at the average electricity rate of 12 cents per kilowatt hour. So, for less than the price of 1.5 gallons of unleaded, an Ioniq can cover 124 miles, the distance from Philadelphia to Washington, D.C.

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Video Friday: Humanoid Soccer

Your weekly selection of awesome robot videos

4 min read
Humans and human-sized humanoid robots stand together on an indoor soccer field at the beginning of a game

Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.

CoRL 2022: 14–18 December 2022, AUCKLAND, NEW ZEALAND
ICRA 2023: 29 May–2 June 2023, LONDON

Enjoy today’s videos!

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Array of devices on a chip

This analog electrochemical memory (ECRAM) array provides a prototype for artificial synapses in AI training.

IBM research

How far away could be an artificial brain? Perhaps a very long way still, but a working analogue to the essential element of the brain’s networks, the synapse, appears closer at hand now.

That’s because a device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is giving traditional transistor-based AI an unexpected run for its money—and is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse. Researchers recently reported a string of advances at this week’s IEEE International Electron Device Meeting (IEDM 2022) and elsewhere, including ECRAM devices that use less energy, hold memory longer, and take up less space.

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Solving Automotive Design Challenges With Simulation

Learn about low-frequency electromagnetic simulations and see a live demonstration of COMSOL Multiphysics software

1 min read

The development of new hybrid and battery electric vehicles introduces numerous design challenges. Many of these challenges are static or low-frequency electromagnetic by nature, as the devices involved in such designs are much smaller than the operating wavelength. Examples include sensors (such as MEMS sensors), transformers, and motors. Many of these challenges include multiple physics. For instance, sensors activated by acoustic energy as well as heat transfer in electric motors and power electronics combine low-frequency electromagnetic simulations with acoustic and heat transfer simulations, respectively.

Multiphysics simulation makes it possible to account for such phenomena in designs and can provide design engineers with the tools needed for developing products more effectively and optimizing device performance.

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