ORNL launches Motor Decide platform to rank EV motor technologies by supply chain risk
Summary
Oak Ridge National Laboratory has developed Motor Decide, a platform that evaluates electric motor technologies against critical material availability, supply chain stability and long-term resilience. The tool pairs scenario modeling with ORNL's super intelligence approach to help manufacturers make data-driven motor decisions amid uncertain mineral prices.
Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) have developed Motor Decide, a platform designed to help manufacturers evaluate electric motor technologies when critical material supplies and prices are uncertain.
Motor Decide evaluates motor technologies on performance, critical material availability, supply chain stability, technology maturity and long-term resilience. The platform doesn’t design a motor, but evaluates which motor technology may be the best fit for a specific application.
Many electric motors depend on critical minerals such as copper and rare earth elements. The system combines what ORNL calls super intelligence (SI) with modeling and large-scale scenario analysis to evaluate how motor technologies could perform under fluctuating material costs and supply chain disruptions. Researchers can model what happens if copper prices increase sharply or if a newer technology later becomes commercially viable. The result is a ranked set of motor technology options with information on cost, performance, critical material use, manufacturability and long-term risk.
Motor Decide is designed to work alongside Motor AI, another ORNL-developed platform that uses SI-assisted engineering tools to accelerate detailed motor design. Once a company selects a motor approach, researchers can transfer the results into Motor AI to generate detailed design configurations and engineering specifications.
“Many companies make technology decisions based largely on market momentum or competitor activity,” said Praveen Kumar, lead researcher on the project. “We wanted to create a tool that helps organizations make more informed, data-driven decisions for the long term. We are trying to quantify uncertainty and incorporate it into the decision-making process.”
Source: Oak Ridge National Laboratory
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