Adaptive Online Parameter Estimation Algorithm of PEM Fuel Cells

Xing, Yashan; Na, Jing; Costa‐Castelló, Ramon

doi:10.23919/ecc.2019.8795875

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…State observers are algorithms that allow estimating the value of state variables, whose evolution is described by the system model, combining the use of the model and information from the measured variables [131,132]. In Figure 6 it is shown an scheme of a state observer with its main blocks and variables, wherex corresponds to the state estimation, u is the input control action, y is the output measured, p corresponds to the model parameters, f represents the model, h is the output computation function, Φ is the correction action function and v is the correction control action.…”

Section: State Observers To Estimate the Socmentioning

confidence: 99%

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

Clemente

Costa‐Castelló

2020

Energies

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This paper presents a literature review about the concept of redox flow batteries and its automation and monitoring. Specifically, it is focused on the presentation of all-vanadium redox flow batteries which have several benefits, compared with other existing technologies and methods for energy stored purposes. The main aspects that are reviewed in this work correspond to the characterization, modeling, supervision and control of the vanadium redox flow batteries. A research is presented where redox flow batteries are contextualized in the current energy situation, compared with other types of energy storage systems. Furthermore, a presentation about the current challenges on research, and the main existing installations is view. A discussion about the main dynamic models that have been proposed during last years, as well as the different control strategies and observers, is presented.

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Section: State Observers To Estimate the Socmentioning

confidence: 99%

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

Clemente

Costa‐Castelló

2020

Energies

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“…Compared to the PEMFC and SOFC fuel cells, the number of publications in the literature devoted to the modelling of the DMFC seems to be quite minimal. Mostly researchers estimate the unknown parameters using meta heuristic algorithm like swam based algorithms [ 22 , 23 ], genetic based algorithms [ 24 ] and currently focusing on artificial intelligence based algorithms [ 25 , 26 ]. Most of these works have had great difficulty in solving the Butler–Volmer equation.…”

Section: Introductionmentioning

confidence: 99%

Sustainable development of fuel cell using enhanced weighted mean of vectors algorithm

Singla¹,

Gupta²,

Nijhawan³

et al. 2023

Heliyon

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“…The durability, cost, reliability, and energy efficiency of the stack largely depend on the correct design of its cooling control system [26]- [29]. For an adequate design of the control system it is necessary to have an accurate nonlinear model [30]- [33]. By using the methodology presented in this paper, optimal and nearly optimal models that are nondominated in their neighborhood are obtained using the evolutionary nevMOGA [14].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Nearly Optimal Solutions in a Multi-Objective Optimization Approach for the Multivariable Nonlinear Identification of a PEM Fuel Cell Cooling System

et al. 2020

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In this work, the parametric identification of a cooling system in a PEM (proton exchange membrane) fuel cell is carried out. This system is multivariable and nonlinear. In this type of system there are different objectives and the unmodeled dynamics cause conflicting objectives (prediction errors in each output). For this reason, resolution is proposed using a multi-objective optimization approach. Nearly optimal alternatives can exist in any optimization problem. Among them, the nearly optimal solutions that are significantly different (that we call nearly optimal solutions nondominated in their neighborhood) are potentially useful solutions. In identification problems, two situations arise for consideration: 1) aggregation in the design objectives (when considering the prediction error throughout the identification test). When an aggregation occurs in the design objectives, interesting non-neighboring (significantly different) multimodal and nearly optimal alternatives appear. These alternatives have different tradeoffs in the aggregated objectives; 2) new objectives in decision making appear. Some models can, with similar performance in the design objectives, obtain a significant improvement in new objectives not included in the optimization phase. A typical case of additional objectives are the validation objectives. In these situations, nearly optimal solutions nondominated in their neighborhood play a key role. These alternatives allow the designer to make the final decision with more valuable information. Therefore, this work highlights, as a novelty, the relevance of considering nearly optimal models nondominated in their neighborhood in problems of parametric identification of multivariable nonlinear systems and shows an application in a complex problem. INDEX TERMS Multi-objective, nearly optimal, multivariable nonlinear system identification, PEM fuel cell.

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Adaptive Online Parameter Estimation Algorithm of PEM Fuel Cells

Cited by 7 publications

References 25 publications

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

Sustainable development of fuel cell using enhanced weighted mean of vectors algorithm

Analyzing the Nearly Optimal Solutions in a Multi-Objective Optimization Approach for the Multivariable Nonlinear Identification of a PEM Fuel Cell Cooling System

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