Developing a battery management system (BMS) is an exciting but challenging task. It means to create and implement fast battery models, estimators and functions that ensure optimal operation of the battery – under all conditions and during the full lifetime of the system. All of that must run with limited computational power on cost-effective microcontrollers or in a more powerful backend in the cloud. This requires great expertise and deep know-how. Something that is missing when technology evolves fast – like in the battery business with novel chemistries that all have their own challenges.
The major problem is that fast, physical and accurate battery models are missing for BMS development. As an alternative, simple equivalent circuit-based models are used as software-in-the-loop plant models before testing but fail to describe the battery correctly. This causes major issues in validation testing when the BMS translates all model errors to BMS state or parameter errors: inaccurate predictions, additional battery aging and unsafe operation are the consequence.