Battery Week is coming — five days, five webinars, one mission!

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We've been building something for a while now, and Battery Week is our chance to show it properly.

Over five consecutive days in May, our experts will be walking through the tools, models, and processes we use to make battery development faster and more reliable — from how we structure test data all the way to AI models that simulate a cell's full lifetime from just a handful of early cycles. No pre-recorded content, no polished pitch decks. Live sessions, real demos, and time at the end of each one for questions.

Each session tackles a different layer of the development stack, so whether you're deep in cell testing, working on simulation models, or thinking about how AI fits into your validation process, there's a session built for you. We'd love to see you there.

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BATTERY WEEK PROGRAM:

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04.05 - 10 am CET

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Day 1: AI-driven battery development — the perfect use case

The V-model has defined battery validation for decades — rigorous, reliable, and painfully slow. We show how replacing its linear gates with an AI-driven loop cuts validation effort by 30% without compromising confidence.

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➤ REGISTER

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05.05 - 10 am CET

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Day 2: Managing battery data efficiently is the key to China speed!

Great battery engineering starts with clean data — yet teams often face noisy, fragmented results from siloed labs. We show how Sphere’s Battery Testing Center solves this and how raw cell data is then streamlined into a unified, real-time view for seamless engineering.

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06.05 - 10 am CET

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Day 3: Automatic ECM and P2D parametrisation — 10x faster battery modelling

Calibrating ECM and P2D simulation models from test data has always taken months. We show how APEX-Physics does it automatically, cutting parametrisation time by up to 10x and unlocking simulation far earlier in development.

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07.05 - 10 am CET

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Day 4: Simulating performance along battery lifetime from just a couple of cycles

Full cell validation across temperatures, C-rates, and usage profiles takes 12–18 months. APEX-Battery Intelligence simulates aging and end-of-life performance from as few as 50 early cycles — a fraction of the time and cost.

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08.05 - 10 am CET

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Day 5: Trust in data-driven AI battery engineering

AI that engineers can't understand is AI they won't use. Our experts tackle the hardest questions in applied battery AI: explainability, transparency, and what it actually takes to trust a model with a critical engineering decision.

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