Next generation battery management system based on data rich digital twin

Project Objectives

Energetic seeks to develop a next generation BMS using a hybrid of multiple AI and physics-basedĀ models to optimizeĀ battery utilization in the first (transportation) and second life (stationary). TheĀ project will use enhanced sensingĀ technologies,Ā cloudĀ and edge control integration, and investigateĀ explainable AI models as methods to achieve this.ā€‹

The developed models will be integrated into a hybrid (AI and physics-based) digital twin-based BMSĀ model, which will be later deployed on BMS hardware and tested with a real battery stack. TheĀ developed BMS should be able to cover at least 60% of use cases locally, and 90% of desired useĀ cases via connected computation (Edge/Cloud).

Typhoon’s role as a project partner

Typhoon HIL is leading real-time testing activities of the developed Smart Digital Twin BMS software prior to andĀ after its subsequentĀ integration in the BMS hardware. These tests will be connected between a BMS testbed andĀ BMS hardware (the BMS “edge”) hosted at Typhoon HIL’s R&D headquarters and the cloud-based BMS softwareĀ where more complex AI-driven calculations can be performed. By validating performance in the C-HIL testbed, theĀ battery should be ready for stack level demonstration testing at the end of the project.ā€‹