Periodic Reporting for period 1 - Predictive Battery Analytics (TWAICE predictive analytics and digital twin ecosystem to optimise and automate batteries second life and re-use)
Período documentado: 2022-10-01 hasta 2023-09-30
The mobility sector accounts for the largest share of demand for lithium-ion batteries and the major source of used batteries. By 2030, 75% (~1,525 GWh) of all produced lithium-ion batteries are forecasted to be used for electric mobility. Since most of the batteries are replaced after a service life of 10 years or 150,000 km, although 70-80% of the modules would still be usable, a waste of up to 1,220 GWh per year can be expected from 2040 onwards.
TWAICE creates a new value chain by enabling the recovery and upcycling of used batteries from electric vehicles and energy storages through battery analytics and providing it with a second life at the best suiting application, from mobility to energy storage systems. Today, batteries that reach the end of life are industrial waste, particularly Li-ion batteries that are extremely difficult to recycle.
TWAICE technology allows customers to access the battery state of health (SoH) down to the module level, determine best re-using scenario, and predicting the re-used batteries’ lifetime performance for the following 5 to 10 years period.
Our solution solves the major cost and safety problems posed by batteries. TWAICE’s predictive battery analytics platform can be implemented at all stages of the battery value chain, optimizing processes such as development, operation, and re-use (second life). There is a substantial lack of transparency in Li-ion batteries, a problem which can lead to overly high development and operation costs and pose safety risks. Our software addresses this problem by empowering customers to better understand their batteries. They can obtain precise diagnoses and prognoses on battery health and remaining lifetimes, using this information to inform their strategic operational decisions. Underpinned by digital twin technology, we combine battery knowledge with artificial intelligence and machine learning to solve the specific customer needs mainly in the energy and mobility sector. Wherever it is applied, our solution will make significant contributions to reducing CO2 and ensuring a greener future.
TWAICE creates a new value chain by enabling the recovery and upcycling of used batteries from electric vehicles and energy storages through battery analytics and providing it with a second life at the best suiting application, from mobility to energy storage systems. Today, batteries that reach the end of life are industrial waste, particularly Li-ion batteries that are extremely difficult to recycle.
TWAICE technology allows customers to access the battery state of health (SoH) down to the module level, determine best re-using scenario, and predicting the re-used batteries’ lifetime performance for the following 5 to 10 years period.
Our solution solves the major cost and safety problems posed by batteries. TWAICE’s predictive battery analytics platform can be implemented at all stages of the battery value chain, optimizing processes such as development, operation, and re-use (second life). There is a substantial lack of transparency in Li-ion batteries, a problem which can lead to overly high development and operation costs and pose safety risks. Our software addresses this problem by empowering customers to better understand their batteries. They can obtain precise diagnoses and prognoses on battery health and remaining lifetimes, using this information to inform their strategic operational decisions. Underpinned by digital twin technology, we combine battery knowledge with artificial intelligence and machine learning to solve the specific customer needs mainly in the energy and mobility sector. Wherever it is applied, our solution will make significant contributions to reducing CO2 and ensuring a greener future.
The first milestone of the project has been achieved, namely the collection of battery units and the development of a battery analytics platform as well as first functionalities to process large amounts of battery data to access key battery status metrics regarding the state of health of a battery. This is a key step to enable the development of predictive analytics tools.
In parallel, we have launched our battery management platform beta version and collected customers feedback to improve the platform.
In parallel, we have launched our battery management platform beta version and collected customers feedback to improve the platform.
Not applicable yet as project is still ongoing.