This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters. Specifically, the filter is designed for the situation where...

In this article, our goal is to improve the estimation of the parameters of solar photovoltaic models, we propose a method based on Simulated Annealing (SA) Optimization, the proposed algorithm takes into account the uncertainties of measurements. This algorithm consists of three steps such as...

Recently, the application of the proton exchange membrane fuel cells (PEMFCs) is extensively increasing as a popular renewable energy source. PEMFCs need low temperature for the operation along with high power density and easy implementation ability. These characteristics turned them into the...

This paper presents a new optimal method for model estimation of the unknown parameters of circuit-based proton exchange membrane fuel cells (PEMFCs). The main idea is to minimize the sum of squared error (SSE) value between the actual data and the estimated results. The optimization process...

This paper presents an optimal technique for parameter estimation of a Solid Oxide Fuel Cell (SOFC) model. The idea is to minimize the Sum of Squared Error (SSE) between the output voltage and the experimental data. To achieve this purpose, a new metaheuristic, called the Converged Grass Fibrous...