Jove
Visualize
Contact Us

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

255
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
255
Batteries and Fuel Cells03:12

Batteries and Fuel Cells

30.6K
A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
30.6K
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

776
Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the power flow program computes...
776
PD Controller: Design01:26

PD Controller: Design

582
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
582
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

705
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
705

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Joint optimization of smart inverters and EV charging coordination for enhanced DG-EV hosting capacity under uncertain conditions for resilient distribution systems.

PloS one·2026
Same author

Double deep reinforcement learning twin-delayed agents for performance improvement of a grid-connected wave energy conversion system.

Scientific reports·2026
Same author

Fuzzy logic-based reactive power control for power factor enhancement in EV drives.

Scientific reports·2026
Same author

State and disturbance estimation with supertwisting sliding mode control for frequency regulation in hydrogen based microgrids.

Scientific reports·2025
Same author

Improved fault-clearing strategy for large renewable energy systems using advanced optimization and FLC.

Scientific reports·2025
Same author

Robust techno-economic optimization of energy hubs under uncertainty using active learning with artificial neural networks.

Scientific reports·2025
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jan 8, 2026

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells
11:18

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

Published on: December 11, 2019

7.1K

Advanced modeling and parameter estimation of PEM fuel cells using the g-function and self-adaptive differential

Martin Ćalasan1, Snežana Vujošević1, Mihailo Micev2

  • 1Faculty of Electrical Engineering, University of Montenegro, Džordža Vašingtona, Podgorica, 81000, Montenegro.

Scientific Reports
|December 22, 2025
PubMed
Summary

This study introduces a new method for modeling proton exchange membrane fuel cells (PEMFCs) using the g-function and a self-adaptive differential evolution (SaDE) algorithm for parameter estimation, improving accuracy and stability.

Keywords:
g-functionLambert W functionMathematical modelingMetaheuristic optimizationPEM fuel cellsParameter estimationRenewable energy

More Related Videos

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.6K
Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells
08:16

Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells

Published on: October 2, 2016

9.9K

Related Experiment Videos

Last Updated: Jan 8, 2026

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells
11:18

A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells

Published on: December 11, 2019

7.1K
A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.6K
Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells
08:16

Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells

Published on: October 2, 2016

9.9K

Area of Science:

  • Energy Systems Engineering
  • Computational Modeling
  • Electrochemical Engineering

Background:

  • Proton exchange membrane fuel cells (PEMFCs) are crucial for sustainable energy, requiring accurate electrical characteristic models.
  • Traditional voltage-current models are insufficient for control systems; current-voltage models are needed.
  • Existing models face numerical limitations and require robust parameter estimation.

Purpose of the Study:

  • To develop a novel current-voltage model for PEMFCs using the g-function.
  • To introduce a self-adaptive differential evolution (SaDE) algorithm for efficient PEMFC parameter estimation.
  • To validate the proposed modeling and parameter estimation approach through comparative analysis.

Main Methods:

  • Utilized the g-function, a stable transformation of the Lambert W function, for PEMFC modeling.
  • Employed the self-adaptive differential evolution (SaDE) algorithm for parameter estimation.
  • Conducted comparative analysis and sensitivity analysis across three PEMFC systems (Ballard Mark V, BCS 500, NedStack PS6).

Main Results:

  • The proposed g-function model with SaDE parameter estimation demonstrated improved accuracy and numerical stability.
  • Achieved root mean square error (RMSE) reductions up to 6.65% and sum of squared errors (SSE) gains up to 12.87%.
  • The methodology showed robustness and transferability across different PEMFC types.

Conclusions:

  • The novel g-function based PEMFC model and SaDE algorithm offer enhanced accuracy and efficient parameter estimation.
  • The validated framework supports optimized PEMFC performance and integration into sustainable energy systems.
  • This approach advances PEMFC modeling for real-world applications.