“You can look at the state of charge (SoC) and the state of health (SoH) to see how that is performing given the current and voltage, and you can zoom in to diagnose issues. This is really useful for error identification and battery diagnostics. One customer has 4000 systems in India and they can go inside the system and see all the batteries on the road,” said Aryan.
However the battery management system has more intelligence than just the digital twin. “We don’t always follow the model – so if the data deviates that triggers the machine learning to look at the recommend over the air changes in the usage parameters that can change the trajectory to a potential trajectory with a recovery point so that instead of being a diagnostics you can have predictive data,” said Aryan.