Practical Energy Management Control of Fuel Cell Hybrid Electric Vehicles Using Artificial-Intelligence-Based Flatness Theory

Faculty Engineering Year: 2023
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Energies MDPI Volume:
Keywords : Practical Energy Management Control , Fuel Cell    
Abstract:
This paper proposes a practical solution to address the energy management issue in fuel cell hybrid electric vehicles (FCHEVs). This solution revolves around a powertrain system that contains a fuel cell (FC) as the main supply, a photovoltaic cell (PC) as the secondary energy source, and a battery bank (Batt) as backup storage to compensate for the FC’s low response rate. The energy in this hybrid powertrain system alternated between the designated elements and the load via a DC bus, and to maintain a stable output voltage, the DC link was adjusted using a nonlinear approach that is based on the flatness theory and the nonlinear autoregressive moving average (NARMA-L2) neuro-controller. As for the current regulation loops, the sliding mode technique was employed to attain the high dynamic of the reference signals produced by the energy manager loop. To validate the accuracy of the proposed energy management approach (EMA), a test bench was equipped with digital, electronic circuits and a dSPACE DS-1104 unit. This experimental bench contained a fuel cell emulator FC of 1200 W and 46 A, lithium-ion batteries of 24 V, and a solar source capable of 400 W. The obtained results, indeed, attested to the validity of the approach used, yielding a notable performance during multiple charge variations. This ultimately demonstrated that the management approach enhanced the efficiency of the hybrid powertrain.
   
     
 
       

Author Related Publications

  • Hytham Saad Mohamed Ramadan, "Efficient and Sustainable Reconfiguration of Distribution Networks via Metaheuristic Optimization", IEEE, 2022 More
  • Hytham Saad Mohamed Ramadan, "Efficient experimental energy management operating for FC/battery/SC vehicles via hybrid Artificial Neural Networks-Passivity Based Control", ELSEVIER, 2021 More
  • Hytham Saad Mohamed Ramadan, "Hydrogen storage technologies for stationary and mobile applications: Review, analysis and perspectives", ELSEVIER, 2021 More
  • Hytham Saad Mohamed Ramadan, "Efficient metaheuristic utopia-based multi-objective solutions of optimal battery-mix storage for microgrids", ELSEVIER, 2021 More
  • Hytham Saad Mohamed Ramadan, "Optimal reconfiguration for vulnerable radial smart grids under uncertain operating conditions", ELSEVIER, 2021 More

Department Related Publications

  • Raef Seam Sayed Ahmed, "Model predictive control algorithm for fault ride-through of stand-alone microgrid inverter", Elsevier Ltd., 2021 More
  • Enas Ahmed Mohamed Abdelhay, "Recent Maximum Power Point Tracking Methods for Wind Energy Conversion System", Elsevier, 2024 More
  • Raef Seam Sayed Ahmed, "Optimal design and analysis of DC–DC converter with maximum power controller for stand-alone PV system", Elsevier Ltd., 2021 More
  • Raef Seam Sayed Ahmed, "Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function", Elsevier Ltd., 2021 More
  • Mohammed Abdelhamied Abdelnaeem , "Artificial ecosystem-based optimiser to electrically characterise PV generating systems under various operating conditions reinforced by experimental validations", Wiley, 2021 More
Tweet