Imagine if your phone battery could think and adjust itself based on how you use it and the weather outside, rather than following a rigid set of rules. This technology does that for electric vehicles, acting like a smart brain that manages energy more efficiently. It removes heavy wiring and uses cloud data to make sure the battery lasts longer and charges smarter.
Current battery management systems use static rules that don't adapt to real-world changes, leading to inaccurate range predictions and shorter battery life. This forces manufacturers to use oversized, expensive batteries to compensate for inefficiency.
A wireless, scalable BMS hardware and software suite featuring cloud-informed strategies and hybrid physical/data-driven models for real-time battery optimization.
If you are an EV manufacturer dealing with high battery costs and short lifespans — this project developed a situational BMS that delivers a 33% longer battery lifetime and a 12% reduction in costs for passenger cars.
If you are a fleet operator dealing with unpredictable range and vehicle downtime — this project developed a predictive BMS that improves range predictions and enables a demonstrated battery lifetime of up to 15 years.
If you are a supplier dealing with bulky wiring and slow calibration times — this project developed a wireless, scalable BMS hardware that provides a 36% reduction in the time needed for calibrating algorithms.
The technology enables a cost reduction of 12% for passenger cars and 9.7% for light-duty vehicles.
The project aims for TRL6, demonstrating the system in real-world use cases including a Fiat Doblo Electric and an IVECO eDaily van.
Based on available project data, the project develops specific hard- and software solutions, including wireless hardware and cloud-informed strategies, though specific licensing terms are not listed.
It delivers a 12% higher effective battery pack volumetric density by reducing reliance on oversized batteries and removing traditional wiring.
The project period runs from 2024-01-01 to 2027-06-30.
The consortium is heavily industry-driven with a 77% industry ratio, comprising 10 industrial partners including 2 vehicle manufacturers and 2 Tier 1 suppliers. This strong commercial presence, supported by 2 universities and 1 research organization across 11 countries, suggests a high probability of commercial translation and practical application in the automotive supply chain.
Contact Vrije Universiteit Brussel for technical specifications and partnership inquiries.
Contact us to connect with the InnoBMS consortium for licensing and integration opportunities.
