Toyota to Use Artificial Intelligence to Hunt for New Battery, Fuel Cell Materials
Electric cars and hydrogen fuel-cell cars could drastically reduce emissions if they ever truly take off, but that will require finding better batteries and fuel cells. Toyota thinks artificial intelligence might be the key to that. Over the next four years, Toyota will invest $35 million into AI research related to materials science.
The work will be conducted through the automaker’s Toyota Research Institute, an R&D group started in 2015 that previously focused on AI development for autonomous cars. Now, Toyota hopes to use AI to find new materials faster. The carmaker is specifically interested in materials that can improve the performance of batteries and fuel cells.
Toyota is one of the main proponents of hydrogen fuel cell cars, and until recently, criticized battery-electric cars as impractical. But now, the carmaker plans to launch a mass-market electric car alongside the current Mirai fuel cell car. That model is expected to appear before the end of the decade.
Toyota’s researchers will collaborate with Stanford University, MIT, the University of Michigan, and the University of Buffalo, the University of Connecticut, and U.K.-based materials-science company Ilika on various projects. The carmaker says it is open to research projects with other entities, as well.
Developing new materials can take decades, Toyota notes. It hopes applying AI to the computational models currently used in materials science could significantly reduce that. Toyota hopes to reduce global average carbon-dioxide emissions from its cars 90 percent by 2050, and anything that can improve battery-electric and fuel-cell cars will be an important step toward that goal.
Toyota has become a major booster of AI in recent years. In 2015, it announced a $50 million research project with Stanford and MIT to develop the technology for use in future autonomous cars. That possible future was previewed at CES earlier this year by the Concept-i, a concept car designed to show how AI could be integrated with future vehicles.