The model is fast enough to guide design only when its predictions still match cell behavior.
Battery Engineering needs timely guidance, while R&D needs evidence that a new data batch has not distorted the physics.
Who you’d be doing this for
“My planning review is Thursday, and I need assumptions that won’t unravel under questions.”
Filipa Gomes · Grid Resource Planner
Evaluates whether a multi-day storage project can provide dependable capacity during prolonged renewable shortfalls.
What is at stake
Twenty-two overnight predictions fall outside observed discharge bounds. You must weigh fast engineering guidance against using a model that no longer tracks test data.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- engineering speed vs validation confidence
- observed test bounds vs model generalization
- agent throughput vs reviewed changes
Why Form Energy, Inc.
Iron-air battery design decisions depend on physics-based models that remain aligned with R&D data.
Written with these in mind
Not your kind of problem? 20 more at Form Energy, Inc., or browse every organization.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.