Modelling, simulation and control of a proton exchange membrane fuel cell (PEMFC) power system (original) (raw)
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An adaptive fuzzy logic controller (AFLC) for PEMFC fuel cell
International Journal of Hydrogen Energy, 2015
Among the various fuel cell technologies available for use in vehicular systems, the Proton Exchange Membrane Fuel Cell (PEMFC) has drawn the most attention due to its simplicity, viability, higher power density and operation at lower temperatures. Due to this features, PEMFC is considered to be the most suitable technology for vehicular systems, industry and other applications. As fuel cells are likely to be used in many future applications, great efforts have recently been made for their comprehension and design. This paper focuses on a 1.2 W PEM fuel cell unit and develops the models of stack voltage and stack power. While PEM fuel cell is a nonlinear process, it is very suitable to use fuzzy control to solve the control issue of the fuel cell. The stack output power can be controlled to a given value by using a variable universe fuzzy controller by controlling input gases flow rate. In this paper a FLC controller have been designed to control the voltage of at the presence of fluctuations. The results of implementation of this designed FLC controller on a dynamic electrochemical model of a small size 1.2 W, PEM fuel cell have been simulated by MATLAB SIMUlINK and compared with a traditional PID controller. Simulation results show that good control effects can be achieved by using the adaptive fuzzy control system.
Fuel Cells with Proton Exchange Membrane Modeling and Control Techniques
Edison Journal for Electrical and Electronics Engineering, 2024
Comprehensive mathematical models with three distinct controllers (PID, FOPID, and fuzzy + PID) for polymer electrolyte fuel cells (PEFCs) are constructed in this work. The models are made to indirectly control the input hydrogen mass flow rate in order to set the output voltage of the PEMFCs at a predetermined value. The simulation results demonstrate how effectively the established model fits the task of characterizing a PEFC's performance. While the developed controllers are capable of stabilizing voltage, the fuzzy + PID controller performs better, exhibiting a reduced overshoot and a faster response time.
Control of miniature proton exchange membrane fuel cells based on fuzzy logic
Journal of Power Sources, 2004
A control strategy is presented in this paper which is suitable for miniature hydrogen/air proton-exchange membrane (PEM) fuel cells. The control approach is based on process modelling using fuzzy logic and tested using a PEM stack consisting of 15 cells with parallel channels on the cathode side and a meander-shaped flow-field on the anode side. The active area per cell is 8 cm 2 . Commercially available materials are used for the bipolar plates, gas diffusion layers and the membrane-electrode assembly (MEA). It is concluded from a simple water balance model that water management at different temperatures can be achieved by controlling the air stoichiometry. This is achieved by varying the fan voltage for the air supply of the PEM stack. A control strategy of the Takagi Sugeno Kang (TSK) type, based on fuzzy logic, is presented. The TSK-type controller offers the advantage that the system output can be computed in an efficient way: the rule consequents of the controller combine the system variables in linear equations. It is shown experimentally that drying out of the membrane at high temperatures can be monitored by measuring the ac impedance of the fuel cell stack at a frequency of 1 kHz. Flooding of single cells leads to an abrupt drop of the corresponding single-cell voltage. Therefore, the fuzzy rule base consists of the ac impedance at 1 kHz and all single-cell voltages. The parameters of the fuzzy rule base are determined by plotting characteristic diagrams of the fuel cell stack at constant temperatures. The fuel cell stack can be controlled at T = 60 • C up to a power level of 7.5 W. The fuel cell stack is controlled successfully even when the external electric load changes. At T = 65 • C, a maximum power level of 8 W is found. A decrease of the maximum power level is observed for higher temperatures.
Design, Implementation and Evaluation of Fuzzy Logic and PID Controllers for Fuel Cell Systems
International Journal of Electronics and Electrical Engineering
In this paper, fuel cell control is investigated in addition to the use of fuzzy logic to control fuel cells. For fuzzy rules, the maximum power point tracking algorithm is used. Additionally, PID control is used and tested in this paper. As simulation results show, the performance of fuzzy logic is better than PID control. In general, for fuel cell systems, humidification is required for the air or the hydrogen, or both the air and hydrogen at the fuel cell inlets. Moreover, water content is very important for the protonic conductivity in the proton exchange membranes. If membrane dehydration or drying occurs, electrical performance decreases due to significant ohmic losses.
An Electrical Modeling and Fuzzy Logic Control of a Fuel Cell Generation System
Fuel cell generation system consists of a stack, a reformer, and converters. The stack generates DC power by electrochemical reaction. For system design and analysis, it is necessary to obtain electrical models. Simplified electrical models of a fuel cell generation system for system control are proposed. Then using the electrical models, system performance of a fuel cell generation system in which power is boosted by step-up choppers is analyzed. A fuzzy controller is designed for improved system performance. Simulation and experimental results confirmed the high performance capability of the designed system.
Symmetry
Proton exchange membrane fuel cells (PEMFC) are capable of transforming chemical energy into electrical energy with zero emissions. Therefore, these devices had been a point of attention for the scientific community as to provide another solution to renewable sources of energy. Since the PEMFC is commonly driven with a power converter, a controller has to be implemented to supply a convenient voltage. This is an important task as it allows the system to be driven at an operative point, which can be related to the maximum power or an user desired spot. Along this research article, a robust controller was compared against a fuzzy logic strategy (with symmetric membership functions) where both were implemented to a commercial PEMFC through a dSPACE 1102 control board. Both proposals were analysed in an experimental test bench. Outcomes showed the advantages and disadvantages of each scheme in chattering reduction, accuracy, and convergence speed.
Fuzzy logic -based control of power of PEM fuel cell system for residential application
2009
This paper presents a dynamic model of Fuel cell system for residential power generation. The models proposed include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore a fuzzy logic (FLC) controller is used to control active power of PEM fuel cell system. The controller modifies the hydrogen flow feedback from the terminal load. Simulation results confirmed the high performance capability of the fuzzy logic controller to control power generation.
Fuzzy-based modelling technique for PEMFC electrical power generation systems emulation
IET Power Electronics, 2009
A fuzzy-based technique for modelling both static and dynamic responses of the voltage in proton exchange membrane fuel cell energy power generation systems (PEMFC-EPGS) is presented. Based on dynamical effects present on the PEMFC, the technique requires lower calculation capacity than complex physical models. This modelling technique is validated by developing a fuzzy-based model of a user-designed PEMFC-EPGS comparing its accuracy and calculation time to a previously parameterised physical model. The technique is intended to support the design and simulation of control strategies and the development of PEMFC-EPGS models and hardware emulators. The simple structure of the models obtained with the technique results in a small calculation processing demand, this being an effective option for real-time and embedded implementations. Finally, the development and experimental validation of a fuzzy-based model in a low-cost emulator is presented. This emulator permits to evaluate control strategies and the behaviour of power systems interacting with the PEMFC-EPGS dynamics.
Dynamic and control of fuel cell system
2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008, 2008
In this paper, dynamic simulation of a fuel cell system studied using MATLAB/SIMULINK. The paper presents the dynamic model of Proton Exchange Membrane Fuel Cell (PEMFC). The fuel cell output voltage is proportional to the change of the current drawn from the fuel cell model. Phase control full bridge dc/dc converter considered to match the unregulated voltage produced by the fuel cell model to the needed application voltage. PID controller has been selected to regulate the fuel cell output voltage. PWM-based inverter serves as the interface between the dc/dc converter and the ac load. Three-phase inverter used to drive three phase load. Third Harmonic Injection Pulse Width Modulation used to drive the three-phase inverter so that minimum harmonic distortion and maximum usage of the fuel cell voltage on the three-phase inverter output. Simulation results provided to validate the design. http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=4582883
Coolant circuit modeling and temperature fuzzy control of proton exchange membrane fuel cells
International Journal of Hydrogen Energy, 2010
Effective temperature management is necessary for the safe and efficient operation of proton exchange membrane fuel cells (PEMFC). Generally circulating coolant can be applied in removing the excess heat of the PEMFC whose electrical power exceeds 5 kW. So a coolant circuit modeling method and a temperature fuzzy control strategy are presented in the paper in order to keep the PEMFC within the ideal operation temperature range. Firstly, a coolant circuit mathematical model is developed, which includes a PEMFC thermal model, a water reservoir model, a water pump model, a bypass valve model, a heat exchanger model and a PEMFC electrochemical model. Secondly, the incremental fuzzy control with integrator technique is designed according to the established model and control experience rule. And the PEMFC temperature and circulating coolant inlet temperature are controlled by regulating the circulating coolant flux and bypass valve factor respectively. Finally, the established model and fuzzy controllers are simulated and analyzed in Matlab software, and the simulation results demonstrate that the incremental fuzzy controller with integrator can effectively control the PEMFC temperature and the inlet coolant temperature within their objective working ranges respectively. In addition, the modeling and control process are very concise, and they can be easily applied in various power classes PEMFC temperature control in real-time.