“For instance, in a 16-cell battery pack, wiring can be reduced from more than 20 meters to just 80 centimetres, lowering material costs, weight, and assembly complexity, while enhancing overall efficiency,” remarked the press release.
Furthermore, data from the BMS and iSCM is fed into a digital twin. This system uses machine learning to provide predictive analytics on the battery’s remaining life, state of charge, and overall health.
This real-time information is crucial for accurately planning second-life applications for the battery components once they are no longer suitable for automotive use.