Blog
The latest news from Google AI
Academics and the Little Box Challenge
Tuesday, July 22, 2014
Posted by Maggie Johnson, Director of Education and University Relations
Think shrink! Min it to win it! Smaller is baller! That's what the
Little Box Challenge
is all about: developing a high power density inverter. It’s a competition presented by Google and the Institute of Electrical and Electronics Engineers Power Electronics Society (IEEE PELS) -- not only a grand engineering challenge, but your chance to make a big impact on the future of renewables and electricity.
With the rise of solar photovoltaic panels, electric vehicles (EV) and large format batteries, we’ve seen a resurgence in the
over-a-century-long feud
between Thomas Edison’s direct current (DC) and Nikola Tesla’s alternating current (AC). The electric grid and most higher power household and commercial devices use AC; batteries, photovoltaics, and electric vehicles work in DC. So the power electronics that convert between the two -- rectifiers (AC->DC), and inverters (DC->AC) -- are also gaining increased prominence, as well as the DC/DC and AC/AC converters that switch between different voltages or frequencies.
While different flavors of these devices have been around for well over a century, some of them are starting to show their age and limitations versus newer technologies. For example, conventional string inverters have power densities around 0.5-3 Watts/Inch
3
, and microinverters around 5 Watts/Inch
3
-- but lithium ion batteries can now get 4-10 Watt Hours/Inch
3
. So for a 1-2 hour battery pack, your inverter could end up being bigger than your battery -- a lot to carry around.
Some recent advances may change what’s possible in power electronics. For example,
Wide-bandgap
(WBG) semiconductors -- such as gallium-nitride (GaN) and silicon-carbide (SiC) -- not only enable higher power densities than conventional silicon-based devices do, but can also convert between DC and AC at higher temperatures, using higher switching frequencies, and with greater efficiency.
But even WBG materials and other new technologies for power electronics run into limits on the power density of inverters. Photovoltaic power and batteries suffer when they see oscillations on their power output and thus require some form of energy storage -- electrolytic capacitors store that energy and bridge the power differential between the DC input and the AC output, but that makes the devices much larger. Household and consumer devices also need to add filters to prevent electromagnetic interference, so that’s even more bulk.
When it comes to shrinking these devices, inverters may have the most potential. And because inverters are so common in household applications, we hope The Little Box Challenge may lead to improvements not only in power density, but also in reliability, efficiency, safety, and cost. Furthermore, it is our hope that some of these advances can also improve the other types of power electronics listed above. If these devices can be made very small, reliable and inexpensive, we could see all kinds of useful applications to the electric grid, consumer devices and beyond, maybe including some we have yet to imagine.
To recognize the role academics have played in pushing the forefront of new technologies, Google has taken a couple of special steps to help them participate:
Research at Google will provide unrestricted gifts to to academics pursuing the prize. This funding can be used for research equipment and to support students. Visit the
Little Box Challenge awards for academics
page for more info --
proposals are due September 30, 2014.
Academics often have trouble getting the latest technology from device manufacturers to tinker on. So Google has reached out to a number of WBG manufacturers who’ve put up dedicated pages detailing their devices. Check out the
Little Box Challenge
site to get started.
We hope you’ll consider entering, and please tell your colleagues, professors, students and dreamers -- you can print and post
these posters
on your campus to spread the word.
Labels
2018
accessibility
ACL
ACM
Acoustic Modeling
Adaptive Data Analysis
ads
adsense
adwords
Africa
AI
Algorithms
Android
Android Wear
API
App Engine
App Inventor
April Fools
Art
Audio
Augmented Reality
Australia
Automatic Speech Recognition
Awards
BigQuery
Cantonese
Chemistry
China
Chrome
Cloud Computing
Collaboration
Compression
Computational Imaging
Computational Photography
Computer Science
Computer Vision
conference
conferences
Conservation
correlate
Course Builder
crowd-sourcing
CVPR
Data Center
Data Discovery
data science
datasets
Deep Learning
DeepDream
DeepMind
distributed systems
Diversity
Earth Engine
economics
Education
Electronic Commerce and Algorithms
electronics
EMEA
EMNLP
Encryption
entities
Entity Salience
Environment
Europe
Exacycle
Expander
Faculty Institute
Faculty Summit
Flu Trends
Fusion Tables
gamification
Gboard
Gmail
Google Accelerated Science
Google Books
Google Brain
Google Cloud Platform
Google Docs
Google Drive
Google Genomics
Google Maps
Google Photos
Google Play Apps
Google Science Fair
Google Sheets
Google Translate
Google Trips
Google Voice Search
Google+
Government
grants
Graph
Graph Mining
Hardware
HCI
Health
High Dynamic Range Imaging
ICLR
ICML
ICSE
Image Annotation
Image Classification
Image Processing
Inbox
India
Information Retrieval
internationalization
Internet of Things
Interspeech
IPython
Journalism
jsm
jsm2011
K-12
KDD
Keyboard Input
Klingon
Korean
Labs
Linear Optimization
localization
Low-Light Photography
Machine Hearing
Machine Intelligence
Machine Learning
Machine Perception
Machine Translation
Magenta
MapReduce
market algorithms
Market Research
Mixed Reality
ML
ML Fairness
MOOC
Moore's Law
Multimodal Learning
NAACL
Natural Language Processing
Natural Language Understanding
Network Management
Networks
Neural Networks
NeurIPS
Nexus
Ngram
NIPS
NLP
On-device Learning
open source
operating systems
Optical Character Recognition
optimization
osdi
osdi10
patents
Peer Review
ph.d. fellowship
PhD Fellowship
PhotoScan
Physics
PiLab
Pixel
Policy
Professional Development
Proposals
Public Data Explorer
publication
Publications
Quantum AI
Quantum Computing
Reinforcement Learning
renewable energy
Research
Research Awards
resource optimization
Robotics
schema.org
Search
search ads
Security and Privacy
Semantic Models
Semi-supervised Learning
SIGCOMM
SIGMOD
Site Reliability Engineering
Social Networks
Software
Sound Search
Speech
Speech Recognition
statistics
Structured Data
Style Transfer
Supervised Learning
Systems
TensorBoard
TensorFlow
TPU
Translate
trends
TTS
TV
UI
University Relations
UNIX
User Experience
video
Video Analysis
Virtual Reality
Vision Research
Visiting Faculty
Visualization
VLDB
Voice Search
Wiki
wikipedia
WWW
Year in Review
YouTube
Archive
2019
Mar
Feb
Jan
2018
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Jul
May
Apr
Mar
Feb
2007
Oct
Sep
Aug
Jul
Jun
Feb
2006
Dec
Nov
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Feed
Follow @googleai
Give us feedback in our
Product Forums
.
