Material Sciences Industry Solution

R&D: Federated Machine Learning for Battery Innovations

With increasing demand for high-performance batteries, the need for next-level materials that allow for increased functionalities is imminent. Battery material suppliers have limited access to real-world usage data and cannot fully leverage predictive AI models for material optimization and discovery. The Apheris Platform for federated and privacy preserving data science allows battery material suppliers to leverage real-world battery usage data for the development of optimized materials.

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Situation

A battery material supplier develops materials to produce advanced batteries, which are assembled by a cell manufacturer. A vehicle OEM employs these advanced batteries in its electric vehicles at a large scale and can track battery behaviour continuously in relation to various parameters, such as usage and environmental conditions. Battery quality is one of the most important customer decision factors when buying an electrical vehicle, so the OEM wants to be a frontrunner in this aspect.

Problem

The battery material supplier and the cell manufacturer have insufficient amounts of real-world usage data to optimize the employed material/ the cell manufacturing and management to the actual needs. The vehicle OEM is highly interested in collaborating but is not able to share its valuable real-world data due to IP concerns and data privacy regulations, as the real-world usage data contains personally identifiable information of customers.

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Apheris solution

With the help of Apheris, vehicle OEMs can provide controlled access to their proprietary real-world data for model training, without disclosing any sensitive information. The other parties can train robust and advanced models on the real-world datasets that enable the next generation of battery materials, assembly setups and management systems. The data collaboration provides value for all participating parties and the end-customers, who benefit from superior products.

Advantages of using Apheris

Optimize battery materials, assembly setups and management systems

Secure data sharing enables high-performance battery solutions that lead to a larger use of electric vehicles and reduced air pollution

Increase vehicle value

Vehicle OEMs provide IP-preserving access to data and in turn receive high-quality batteries and added value to their products

Reduce R&D costs

The battery material supplier and cell manufacturer reduce their R&D development costs due to a lower need for in-house testing, saving millions of dollars and cutting down the development cycle time

Reduce risk of failure

The large and diverse training data includes edge cases and rare events, reducing the likelihood of critical failures in a real-world environment

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