CATL has received the World Economic Forum’s 2026 MINDS (Meaningful, Intelligent, Novel, Deployable Solutions) Award for its project “Augmented Intelligence Leading Next-Generation Lithium-ion Battery Design.” The WEF selected only 15 organizations worldwide for this recognition.
Highlights
- CATL’s AI-driven design platform draws on more than 50 million data records and 600TB of test data to generate virtual cell designs in minutes
- Prediction accuracy reaches 95 percent by combining physics-based electrochemical models with machine learning
- The platform shifts battery development from trial-and-error prototyping to forward design and prediction before production
- WEF’s MINDS programme evaluates applicants across strategy, talent, data, technology, and governance dimensions
Platform Architecture and Capabilities
The Centre for AI Excellence at the World Economic Forum manages the MINDS programme, which focuses on accelerating responsible AI adoption across industries. In its official report, the WEF noted that CATL “turned a deep reservoir of proprietary, multimodal data into a sustained AI advantage.”
The Intelligent Cell Design platform runs on an on-premises private cloud. It combines physics-based electrochemical models with machine learning to deliver predictions and accelerate key steps in cell design.
Core technical capabilities include:
- Physics-informed machine learning that functions as a “digital engineer”
- Automatic generation, evaluation, and refinement of design options
- Training data from more than 100,000 battery design cases
- Aftermarket data drawn from a broad range of new energy vehicles
Addressing Industry Challenges
Traditional lithium-ion cell design has relied on individual engineers’ experience and extensive manual testing. This approach creates prolonged evaluation cycles, high prototyping costs, and repeated trial-and-error iterations.
With NEV market penetration now exceeding 50 percent and EV development cycles compressed to 18 months, automakers face pressure to secure batteries with superior performance and enhanced safety.
The platform accommodates customized performance requirements and dynamically adjusts design priorities. It evaluates designs against electrochemical constraints and generates design recommendations in seconds.
Company Perspective
Ni Jun, Chief Manufacturing Officer and Co-President of Engineering Manufacturing System at CATL, commented on the distinction between artificial and augmented intelligence.
“In complex industrial scenarios like battery production, relying solely on ‘Artificial Intelligence’ can’t solve core problems,” Ni said. “By integrating our intelligent design system with engineers’ in-depth understanding of material properties, process principles and system engineering, we can strengthen the human–AI partnership.”
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