Toyota Looks To Artificial Intelligence For Next-Generation Battery Technology
It turns out that Toyota will begin employing artificial intelligence (AI) related to electric cars. However, not in the way most might think.
Now that Toyota is moving forward in its development of longer-range EVs, instead of fuel-cell vehicles (FCV), the company is eager to be the first to discover some “hidden” battery range secrets.
Toyota will invest $35 million into its Toyota Research Institute (TRI), over the course of the next four years, specifically to use AI to search for the answers to increasing battery range. CEO of TRI, Eric Krotkov, shared:
“We want to accelerate the rate at which we can design or discover new materials for fuel cells and batteries.”
The AI will be put to the task of searching for new materials that can better power EVs and FCVs. Toyota believes that using technology to find the answers could put them years ahead of the competition. The company is also set to begin a multi-faceted partnership with a U.K.-based “accelerated materials innovation” firm (Ilika Plc), along with Stanford University, and the Massachusetts Institute of Technology. Toyota is also willing to expand this partnership to multiple other contributors.
TRI is also working toward autonomous vehicles. However, the company was specific about its intention to market toward the elderly, creating vehicles that will allow older people to “age in place,” instead of having to rely on others, or be confined to an elderly care facility. Retired U.S. military robotics expert, Gill Pratt, was brought on board Toyota’s team to head up this venture.
Toyota hopes that with this major step, it can reach its goal of having a carbon footprint that decreases by 90 percent by 2050. Though Toyota is still pursuing FCVs as a substantial part of this role, company president, Akio Toyoda, admitted that the automaker is now shifting immediate focus to battery electric vehicles.
You can read Toyota’s official press release below:
$35 Million to Accelerate Materials Science Discovery
Projects will apply artificial intelligence and machine learning to speed development of materials for next-generation energy
March 30, 2017
Palo Alto, Calif., March 30, 2017 — The Toyota Research Institute (TRI) will collaborate with research entities, universities and companies on materials science research, investing approximately $35 million over the next four years in research that uses artificial intelligence to help accelerate the design and discovery of advanced materials. Initially, the program will aim to help revolutionize materials science and identify new advanced battery materials and fuel cell catalysts that can power future zero-emissions and carbon-neutral vehicles.
“Toyota recognizes that artificial intelligence is a vital basic technology that can be leveraged across a range of industries, and we are proud to use it to expand the boundaries of materials science,” said TRI Chief Science Officer Eric Krotkov. “Accelerating the pace of materials discovery will help lay the groundwork for the future of clean energy and bring us even closer to achieving Toyota’s vision of reducing global average new-vehicle CO2 emissions by 90 percent by 2050.”
Initial research projects include collaborations with Stanford University, the Massachusetts Institute of Technology, the University of Michigan, the University at Buffalo, the University of Connecticut, , and the U.K.-based materials science company Ilika. TRI is also in ongoing discussions with additional research partners.
“This represents a fantastic opportunity to drastically advance the use of databases and machine learning methods in materials discovery,” said Jens Norskov, Professor at Stanford University and director of the SUNCAT center. “The partnership combines theory, computation and experiment in an unprecedented, concerted effort. We are particularly excited by prospects for an avant-garde approach to catalyst development for fuel cells.”
Research will merge advanced computational materials modeling, new sources of experimental data, machine learning and artificial intelligence in an effort to reduce the time scale for new materials development from a period that has historically been measured in decades. Research programs will follow parallel paths, working to identify new materials for use in future energy systems as well as to develop tools and processes that can accelerate the design and development of new materials more broadly.
In support of these goals, TRI will partner on projects focused on areas including:
- The development of new models and materials for batteries and fuel cells;
- Broader programs to pursue novel uses of machine learning, artificial intelligence and materials informatics approaches for the design and development new materials; and,
- New automated materials discovery systems that integrate simulation, machine learning, artificial intelligence and/or robotics.
Accelerating materials science discovery represents one of four core focus areas for TRI, which was launched in 2015 with mandates to also enhance auto safety with automated technologies, increase access to mobility for those who otherwise cannot drive and help translate outdoor mobility technology into products for indoor mobility.