📊 The quoted lifetime on a manufacturer's datasheet is usually a single cycle number, but this can be very misleading. The actual lifespan of a cell depends on various factors, including how extreme the use case is.

⚙️ Cells can last longer or degrade more quickly depending on their operating conditions. Designing and controlling battery packs to target specific usage windows can significantly enhance performance and extend battery life. To achieve these gains, high-quality data is necessary. Companies need to conduct in-house experiments for the following reasons:

📋 Data Provenance: A detailed description of how cells are tested, ensuring companies understand the conditions and methods used during testing.

🔗 Data Traceability: The ability to identify any issues or changes in test conditions or protocols, crucial for maintaining consistency and reliability in results.

📊 Data Fidelity: Usable Reference Performance Tests (RPTs) and trend maps that are essential for powering accurate models and predicting battery behaviour.

🚗 However, managing these in-house experiments is costly and resource-intensive. At About:Energy, we centralise this process, providing critical degradation data for the Molicel P45B (and now the P50B) to support new product development and help optimise battery performance. Our data-driven approach saves you time and resources.