Cloud BMS

The project will develop dedicated hardware and software for cloud-based BMS demonstrations and future commercialization. The general advantages of the cloud-based BMS will be demonstrated on different battery applications including forklifts, robots and stationary BES system utilizing both new (1^st life) and used (2^nd life) batteries.

In the project, a large number of battery systems will be connected to the internet (Internet of Things) and real-life data stored in the ‘cloud’. Adaptive battery diagnostics and lifetime estimation models will be established from the could data by using artificial intelligence algorithms. By processing a large amount of real-life harvested battery data, a detailed and quantitative picture showing how different parameters contribute to the degradation of the individual battery will be established. In this way the following unique advantages are realized:

• Battery lifetime is extended by optimizing the utilization patterns in order to reduce degradation;
• Battery pack capacity and hence cost can be optimized to match the desired lifetime for known operational parameters;
• The Remaining Useful Lifetime of the battery can be predicted

This project will contribute to the wider use of renewable energy in the energy system as both longer and precisely known battery lifetimes will help the introduction of batteries in both stationary and mobile systems.