IBM collaboration to boost fuel cell performance using GenAI

One of the world’s largest industrial research organisations, IBM, has announced a collaboration to enhance the performance of an American fuel cell company's technology leveraging the of the most topical technological advancements of the last year: generative AI.

Called Foundation Model, this specific iteration of GenAI will support both IBM and FuelCell Energy’s efforts to lead a global transition to renewable energy sources that emit little to no carbon.

How IBM will boost FuelCell Energy’s performance with Foundation Model GenAI

IBM’s Foundation Model will create device-level models using FuelCell Energy data, predicting technology performance and creating a digital twin of the fuel cell. As a result of this, the collaboration aims to extend fuel cell life through optimal control of operational parameters, cost-effectiveness and replacing traditional accelerated life testing processes. 

“We hope that IBM’s AI will help FuelCell Energy replace the traditional, time-intensive and expensive accelerated life testing process when it comes to electrochemical energy production to quickly and efficiently propel forward the world’s transition to clean energy,” said Alessandro Curioni, VP IBM Research Europe & Africa and Director of IBM Research Europe.

What are fuel cells?

Fuel cells are a source of clean energy that can be used solo or in conjunction with other types of renewable energy sources. The electrochemical devices then convert the chemical energy of a fuel, usually hydrogen, into electricity thanks to an electrochemical reaction between the fuel and an oxidising agent, like oxygen. Unlike traditional combustion processes, fuel cells generate electricity with higher efficiency and lower emissions and can be used in various fields, including transportation, stationary power generation and portable electronics, offering a clean and efficient alternative to traditional energy sources.

Through the collaboration, IBM will research ways that FuelCell Energy can extend the life of its fuel cells through an optimal control of operational parameters and their cost effectiveness for customers.

IBM’s GenAI will predict performance by learning FuelCell data

The Foundation Model will create device-level models using FuelCell Energy data and, in turn, predict the technology's performance. By this digital twin method, replicating the fuel cell, various data sources will be connected and streamlined to provide a greater insight into how various operating parameters impact the fuel cell's degradation and subsequently enable potential improvements.

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