In this paper, a new aging detection method of a supercapacitor is proposed through the study of the charge process. Good indicators to describe this aging are equivalent series resistance (ESR) and capacitance evolution, which are online unmeasurable parameters of the component model. The proposed model belongs to the class of state and parameter affine nonlinear system. A new adaptive nonlinear observer is designed to estimate, under different aging phases, both states and parameters using measurements only available at each sampling instant. This unusual observer contains an adaptive gain, an unknown parameter into the measured output equation, and the control signal into state matrix. This discrete-continuous observer is proved to be globally exponentially convergent under some sufficient conditions. Theoretical results are implemented for two cases of study, the first one through some simulations and the second one applied on real data for different sampling times and different values of observer gain. Results highlight good performances of the observer in online parameter estimation; thus, the component aging is clearly shown.