Reduce fabrication and development costs

Challenge: The performance, cost and safety of batteries determine the successful development of electric vehicles (EVs). Further research of battery chemistries will result in more complicated battery dynamics, where safety and efficiency will become a concern. Therefore, an advanced battery management system (BMS) that can optimize and monitor safety is crucial for the electrification of vehicles.

Solution: Machine learning to design the cathode, anode, and electrolyte and predictive models for battery management systems to alleviate range anxiety. Alchemite’s predictive models standardize processes and reduce costs both in terms of the number of experiments that need to be performed and optimizing experiments to minimize the need for expensive components or processes.

Outcome: Our deep learning technology ran virtual experiments to focus the search for new materials. Alchemite predicted remaining useful life, state of health and state of charge while reducing fabrication and development costs and improving key battery metrics for process parameter prediction.