Real-Time Adaptive Parameter Estimation for a Polymer Electrolyte Membrane Fuel Cell

Abstract

In this paper we propose real-time adaptive parameter estimation methods for a polymer electrolyte membrane fuel cell (PEMFC) to facilitate the modeling and the subsequent control synthesis. Specifically, the electrochemical model of this fuel cell is in a nonlinearly parametric formulation. Hence, most of existing parameter estimation techniques for PEMFC mainly rely on the optimization approaches, requiring heavy computational costs or even offline implementation. In comparison to those methods, real-time adaptive parameter estimation methods for nonlinearly parametric system are developed in this paper. First, the nonlinearly parametric function is linearized by using the Taylor series expansion. Then, adaptive parameter estimation methods are proposed for estimating the constant or time-varying parameters of PEMFC. Different from the wellrecognized adaptive parameter estimation methods, the proposed adaptive laws are driven by the extracted estimation errors, so that exponential convergence of the parameter estimation error can be guaranteed, without using any predictors or observers. Finally, practical experiments in a H-100 PEMFC system are conducted, which illustrate satisfactory performances of the presented parameter estimation methods under different operation scenarios.

Observations on the Parameter Estimation Problem of Polymer Electrolyte Membrane Fuel Cell Polarization Curves

“…In addition, noise and drift elements could be utilized to stress the optimization algorithm performance, especially in terms of stability and reliability, as emphasized by Xu et al [53]. In real-time applications, where parameter estimation is performed in an adaptive manner (see, e.g., Ettihir et al [67], and Xing et al [68]), the convergence speed would become one of the key performance indicators.…”

Optimal Cost Minimization Strategy for Fuel Cell Hybrid Electric Vehicles Based on Decision-Making Framework

“…Therefore, an energy management strategy (EMS) is needed for FCHEVs to control the distribution of power demand among different power sources. Compared to other electric vehicles and internal combustion engine vehicles, FCHEVs are lack of competition on overall cost due to the high cost and low lifetime of fuel cell and batteries [2]. Therefore, in this paper, an optimal cost minimization strategy (OCMS) is developed to minimize the operating cost and improve the economy of FCHEVs.…”

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

“…Nowadays, inside the group of electrochemical ESS, more research is being done, specially in fuel cells and redox flow batteries. Fuel cells [30,31] convert chemical energy from a fuel (usually hydrogen) into electric energy through an electrochemical reaction between the fuel with an oxidizing agent (oxygen). Its main distinction from a battery is that requires a continuous source of species.…”

“…Online parameter estimation is based on updating the estimation when new information is available. Thus, the estimation is make in real-time [30]. This adjustment only needs a parameter estimation algorithm that calibrates the model parameters each time it receives information for the input signals and measured variables.…”