Performance Improvement of Fuel Cells Using Perturbation‐Based Extremum Seeking and Model Reference Adaptive Control

This paper develops a hysteresis band‐based multivariable sliding mode control (SMC) for the double input buck buck–boost fused converter. The considered converter is operated at a controlled output voltage, while supplied from two different levels of input voltages from two different sources. The proposed control is to ensure the faster time of responses during the variation in the dual references, the output voltage, and low‐voltage source current, simultaneously. The controller is developed by considering these two controlled variables, which are directly dependent on each other. This multivariable SMC is shown to perform successfully to maintain the controlled variables at their desired values despite the variation in the input voltage sources and also during perturbation in the load impedance. The stability analysis for the closed‐loop system is established with the Lyapunov method, which confirms that both of the controlled variables reach the desired stable band at the steady state. The control is implemented in the simulation environment for different operating conditions. A laboratory prototype is developed to implement the multivariable SMC. The experimental results successfully validate their simulated counterparts.

Section: Introductionmentioning

confidence: 99%

Sliding mode control of double input buck buck–boost fused converter

Sen

Saha

Dey

2020

“…Fuzzy logic based control systems provide a much‐improved performance to operate the wind system under maximum power point in fast‐changing environmental conditions and uncertainties . The core interest of fuzzy logic controllers is their ability to incorporate experience, intuition, and heuristics into the system instead of relying on mathematical models, making them more effective in power system applications where existing models are ill‐defined and not reliable enough .…”

Section: Introductionmentioning

confidence: 99%

“…As a result of the non‐linear nature of wind turbines, it can be challenging to uplift the performance of the system over distinct functioning conditions .…”

Section: Introductionmentioning

confidence: 99%

Intelligent maximum power tracking control of a PMSG wind energy conversion system

Aicha

Youcef

Hassaine

et al. 2019

A comparative control study for a maximum power tracking strategy of variable speed wind turbine is provided. The system consists of a direct drive permanent magnet synchronous generator (PMSG) and an uncontrolled rectifier followed by a DC/DC switch-mode step down converter connected to a DC load. The buck converter is used to catch the maximum power from the wind by generating an efficient duty cycle. Distinct Maximum Power Point Tracking (MPPT) algorithms are analyzed and compared: a classical Proportional-Integral controller (PI) and two based Fuzzy Logic Controllers (FLC), including a conventional Fuzzy-PI and an Adaptive FLC-PI. The main aim of the presented study is to develop an advanced control scheme for wind generators to ensure a high level operating of the system and a maximum power extraction from the wind. This is achieved by analyzing the behavior of the system under fluctuating wind conditions employing Matlab Simpower Systems tool.Simulation results confirm that the Adaptive FLC-PI controller algorithm has better performances in terms of dynamic response and efficiency especially in comparison with the ones of a PI controller under variable wind speed. KEYWORDS DC-DC buck converter, fuzzy logic controller (FLC), maximum power point tracking (MPPT), permanent magnet synchronous generator (PMSG), proportional integral (PI) controller, wind turbine

“…In , in consideration of air compressor power consumption, the energy management strategy based on power coordinating algorithm is presented to distribute the power demand to the PEMFC system and the battery while maintaining the battery SOC at the same time. In , the maximum power point tracking (MPPT) is studied in a Fuel cell and DC‐DC converter cascade systems in the conditions of the fuel cell parameter variations and load changes.…”

Section: Introductionmentioning

confidence: 99%

“…For better thermal management and avoiding temperature fluctuation, through electrochemical reaction mechanism and thermodynamic principle analysis, a control-oriented cooling system model is established which is verified on an experimental Ballard 14.4 kW system [10]. In [13], the maximum power point tracking (MPPT) is studied in a Fuel cell and DC-DC converter cascade systems in the conditions of the fuel cell parameter variations and load changes. In [12], in consideration of air compressor power consumption, the energy management strategy based on power coordinating algorithm is presented to distribute the power demand to the PEMFC system and the battery while maintaining the battery SOC at the same time.…”

mentioning

confidence: 99%

Real‐time thermal Management of Open‐Cathode PEMFC system based on maximum efficiency control strategy

Yin

Wang

et al. 2019

Improving the efficiency of the proton exchange membrane fuel cell (PEMFC) system is the main problem should be solved for the commercialization of PEMFC. In this paper, the efficiency characteristic of PEMFC system under load and stack temperature variation is analyzed through theoretical modeling and experimental verification. For high efficiency operation of PEMFC system, the maximum efficiency control strategy (MECS) is proposed for thermal management of PEMFC system. According to the efficiency characteristics of PEMFC system, the optimal efficiency trajectory of system is obtained under maximum efficiency optimization (MEO). As PEMFC system is a nonlinear system with the characteristics of time-variation, and uncertainty, a constrained generalized predictive control (CGPC) is proposed to realize realtime optimal efficiency trajectory tracking. The MECS based on MEO and CGPC is implemented on-line, experimentally validated on the established H-300 open-cathode PEMFC system. The experimental result shows better tracking ability compared with PID control and testifies the validity of MECS for increasing the system efficiency. Therefore, the proposed MECS can provide better system dynamic response and higher system efficiency. KEYWORDS constrained generalized predictive control (CGPC), maximum efficiency control strategy (MECS), maximum efficiency optimization (MEO), Proton exchange membrane fuel cell (PEMFC), thermal management 1 | INTRODUCTIONWith the rapid development of science and technology, energy shortage and environmental pollution have attracted widely attention in the last decade. Hence, the development and utilization of clean and renewable energy become the inevitable trend in the world [1,2]. As the renewable energy such as solar and wind have the characteristic of intermittency and uncertainty, it is generally difficult to match the energy production with the energy demand in application [3,4]. Therefore, it is necessary to introduce hydrogen energy as the transit energy to help matching the energy production and energy demand. As an energy storage medium, hydrogen energy cross the fields of electricity, heat and fuel, which can promote the integration of energy supply and improve ---This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.