Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019)

The importance of energy storage in the sustainable energy chain has resulted in an increasing number ofx000D
battery technologies being introduced into the market. Utilizing each type of the battery to its full potentialx000D
requires charging and discharging methods that are specific to the battery chemistry and the battery's state ofx000D
the health. However, the technology behind the battery is not always known to the user. A method that enablesx000D
the fast identification of the battery chemistry can be achieved through measuring its response to electrical orx000D
other perturbations. This approach could enable identification of the number of cells in a packaged battery andx000D
its appropriate and safe handling. Many major telecommunication device manufacturers have shown interest inx000D
this area by filing patents for such a device. However, these patented systems are directed towards use withinx000D
the company and mainly distinguishes between the various battery models specific to the manufacturer. Theyx000D
have yet to show a working prototype of a universal battery identifier. During the first Engage grant supportedx000D
research, the specific characteristics of the various battery technologies were studied to determine thex000D
distinguishing features of each battery type. Battery classification was handled by fitting to physical models andx000D
then through data cleansing and machine learning techniques. The results showed that the proof of concept wasx000D
successful. This initial success will be further developed with the company to create a universal batteryx000D
monitoring and charging system.