Online System Identification of a Fuel Cell Stack With Guaranteed Stability for Energy Management Applications

Designing an accurate model for a proton exchange membrane fuel cell (PEMFC) is very difficult owing to its multivariate nature. Hence, PEMFC online system identification (OSI), which serves as a basis for its application in energy management of hybrid fuel cell vehicles, is considerably important to cope with the performance drifts. In this paper, an OSI method is proposed for estimating the time-varying parameters of a well-known PEMFC semi-empirical model in the literature. Unlike the other similar approaches, the proposed technique in this manuscript suggests a Lyapunov-based adaptation law with guaranteed stability to estimate online the fuel cell parameters. To highlight the effectiveness of the suggested approach, it is used to estimate the characteristics of a 500-W Horizon PEMFC and its performance is compared with Kalman filter which is perceived as a reliable linear estimator. Experimental results along with the comparative study prove the successful performance of the suggested technique.