Fast charging is considered a key aspect for increasing the usage of Li-ion batteries, especially within applications where it is
fundamental to reduce the downtown of the equipment due to charge (Electric Vehicles, Drones, Power and Gardening Tools, etc.).
Most of the current commercial battery management systems (BMSs) available in the market make use of fast-charging options based on
logic-based protocols without awareness of the battery dynamics that can dramatically reduce the lifespan of the battery in the
long term.

After more than 10 years of experience in the field, this spin-off project, funded by Innoviris and led by Alejandro, aims at
improving the current commercially-available fast charging solutions with scientific findings in the area of model-based constrained
control strategies. Thus, we develop, test, and validate low-complexity, optimization-free, and close-loop estimation and
charging algorithms that reduce the charging time while diminishing the likelihood of an accelerated electrochemical and thermal
degradation of Li-ion batteries. Our offer is built upon 4 pillars:

1. An accurate but simple characterization of the electrochemical and thermal dynamics of the battery (either a cell or a pack);

2. An estimation layer able to track the dynamics of the battery;

3. Charging-control algorithms that charger the battery as fast as possible according to the battery dynamics and considering
the environmental conditions;

4. Extensive validations campaigns, using commercial batteries (Sony, Samsung, Panasonic, LG, etc):

Such pillars are operative supported by more than 60 testing channels and covered by the patent WO2022189454 A1 (Fast-charge of
a Li-ion Battery based on a state feedback on a reduced order electrochemical model).