Objective
The RESiLiTE project (Robust, Economical, Silicon-rich, Lightweight, and Thermally Efficient battery packs) aims at increasing the energy density, energy efficiency, operative temperature range, fire safety and sustainability of upcoming battery packs for automotive vehicles and, subsequently, aircrafts. To achieve the project goals, cylindrical cells in the format 4695 will be tightly packed via a Cell To Pack (C2P) approach within a lightweight housing. The housing will be made of recycled fiber-reinforced thermoplastic materials. A cell-holder structurally integrated in the housing will allow the complete removal of potting materials. With the proposed concept, 230 Wh/kg energy density at pack level is aimed. This is more than 19% higher than the present SotA. Charging/discharging C-rates higher than 4.5C will be achieved thanks to the combined indirect cooling solutions integrated within the housing's cell-holder. Fire safety will be improved via a soft-venting concept, coupled with fire-retardant naomaterials integrated in the cell-holder. In order to achieve a high degree of redundance for safety measures, advanced diagnostics software will be accompanied by the implementation of Electrochemical Impedance Spectroscopy (EIS) sensors. Model-based SoX estimation algorithms will be implemented on the BMS to improve the diagnostic capability of the system. Thermal management control will be designed via a scenario-based algorithm with the help of Neural Networks (NN). This will increase the pack's energy efficiency. The employment of thermoplastic materials for the housing will also thermally insulate the pack, resulting in longer stand-time in cold environments before the need for active heating solutions. The proposed measures and materials help drive down the overall cost of ownership throughout the lifetime of the battery pack, offering a more resilient system with respect to the SotA.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencessoftware
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringaircraft
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- social scienceseconomics and businessbusiness and managementemployment
- natural sciencesphysical sciencesopticsspectroscopy
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Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
53229 Bonn
Germany