Lithium-ion battery limits and how predictive software can help

January 10, 2020

The increased use of battery technology in the transportation and energy industries has put unique demands on the lithium-ion battery. For electric cars, it needs to charge more quickly. For energy storage, it needs to retain a charge for a longer duration. In order for batteries to meet these and other challenges, you need next-generation solutions that are built on an understanding of how to optimize battery charging and use.

Significant advances in the past few years have made it possible to increase the number of charge and discharge cycles within a 24-hour period. In a normal discharge cycle, the ions migrate between a lithium-based intercalation compound, such as LiCoO2, to the negative electrode made of carbon. Unfortunately, a natural part of this process results in some of the ions reacting with the electrode and becoming bonded to the material, thereby degrading the battery life. Frequent charging can stress the electrodes and cause microfractures that decrease longevity. Given that transportation and energy storage batteries will increasingly fall under leasing regimes, anything that threatens the residual value of the assets (such as accelerated degradation) is likely to hamper adoption.

Managing charge/discharge cycles with increased precision is an industry requirement to ensure that battery assets are utilized to their fullest revenue potential. As it stands, the margins for overcharging are incredibly small — around 1%. Exceeding the limit by that small margin can damage the battery permanently. On the other hand, undercharging by only 100mV can result in a 10% loss in capacity. Newer integrated circuits continuously monitor the input voltage, current and battery voltage, and can disable the charging circuit instantly if it detects an overcharge. Continued research in this area will allow lithium-ion batteries to charge even more quickly. The key here will be lifecycle management of batteries and precision monitoring of large scale deployments (down to each individual battery) across both transportation and grid deployments. The more precision you can bring to a charge/discharge cycle (including the insertion of rest cycles), the less likely you are to damage the battery.

Peaxy Lifecycle Intelligence (PLI) for Batteries is a complete predictive battery analytics and machine learning software platform that delivers dramatic performance improvements across R&D, manufacturing and field operations to drive significant return on investment and new revenue streams.

As one of the first cloud-based battery analytics software platforms, PLI for Batteries takes a completely holistic approach to your data by delivering a unified data vision for battery development, manufacturing and deployment. Our enterprise-grade solution securely captures and stores the entire data value chain (using a proprietary process) to create a single source of truth for serialized battery data down to the asset level, laying the foundation for machine learning insights and high fidelity digital twins.

Features include:

  • Degradation curves for each serial number in real-time
  • Optimization of charge / discharge regimes
  • Tracking of ambient profiling and operating profiles to help tune optimal charge / discharge cycles
  • Helping operators work within the boundaries of a complex battery warranty regime.
  • Helping lessors make sure they protect the long-term residual value of battery assets.

Find out more about Peaxy Lifecycle Intelligence for Batteries here.