An improved thermal control of open cathode proton exchange membrane fuel cell

Proton exchange membrane fuel cell is a well-known technology that has shown high efficiency and performance as a power system compared to conventional sources such as internal combustion engines. Especially, open cathode proton exchange membrane is growing more popular thanks to its simple structure, low cost and low parasitic losses. However, the open cathode fuel cell performance is highly related to the operating temperature variation and the airflow rate which is adjusted through the fan voltage. In this regard, the present study investigates the thermal management of an open cathode proton exchange membrane fuel cell. The objectives are the stack performance improvement and the stack degradation prevention. Indeed, a safety and optimal operating zone governed by the load current, the stack temperature and the air stoichiometry, is designed. This optimal operating zone is defined based on the system thermal balance and the operating constraints. Hence, the proposed control strategy deals concurrently with the stack temperature regulation and the air stoichiometry adjustment to guarantee the goals achievement. The performance of the proposed control strategy is verified through experimental studies with different operating conditions and results prove its efficiency. To properly design an appropriate control strategy, a multiphysic fuel cell model is developed based on acausal approach by mean of Matlab/Simscape and experimentally validated.     

A new control strategy for a higher order proton exchange membrane fuel cell system

In this paper, a new cascade control strategy is proposed for a higher order Proton Exchange Membrane (PEM) Fuel Cell system for improving the performance on the basis of stack voltage. In the proposed strategy, stack voltage is considered as the primary objective and maintaining oxygen excess ratio value as a secondary aim, by manipulating the air compressor voltage. A higher-order PEMFC model is reduced to lower order integer and fractional models using varied model reduction techniques, which are then used to realize the primary as well as secondary controllers. Both integer and fractional order PID controllers are designed for the reduced order models and then implemented for the higher order system. The control performance is evaluated for disturbance rejection, system model mismatch and better controlled output for continuous random disturbance on the basis of Integral Absolute Error and controller effort. The outcome of the proposed control strategy is advantageous in terms of disturbance rejection, robustness, parameter uncertainty and reduction of plant-model mismatch.     

Maximum power point tracking of a proton exchange membrane fuel cell system using PSO-PID controller

Fuel cells output power depends on the operating conditions, including cell temperature, oxygen partial pressure, hydrogen partial pressure, and membrane water content. In each particular condition, there is only one unique operating point for a fuel cell system with the maximum output. Thus, a maximum power point tracking (MPPT) controller is needed to increase the efficiency of the fuel cell systems. In this paper an efficient method based on the particle swarm optimization (PSO) and PID controller (PSO-PID) is proposed for MPPT of the proton exchange membrane (PEM) fuel cells. The closed loop system includes the PEM fuel cell, boost converter, battery and PSO-PID controller. PSO-PID controller adjusts the operating point of the PEM fuel cell to the maximum power by tuning of the boost converter duty cycle. To demonstrate the performance of the proposed algorithm, simulation results are compared with perturb and observe (P&O) and sliding mode (SM) algorithms under different operating conditions. PSO algorithm with fast convergence, high accuracy and very low power fluctuations tracks the maximum power point of the fuel cell system.     

Nonlinear model predictive control for efficient and robust airpath management in fuel cell vehicles

The fuel cell airpath multivariable control problem of optimally coordinating the electric compressor motor and the back-pressure valve to achieve efficient and safe conditions, for both steady state and transient operation, has not been completely addressed in the literature. This paper proposes a nonlinear model predictive control strategy, implemented via the Garrett Motion proprietary NMPC toolbox, to regulate the oxygen stoichiometry and the cathode pressure of an automotive fuel cell airpath system, while avoiding compressor surge and air starvation. The controller set-points are optimized, using the nonlinear model, to achieve the maximum system power as a function of the operating stack condition. The effectiveness and robustness of the proposed control strategy have been validated by means of a simulated World harmonized Light-duty vehicles Test Cycle (WLTC), under both state feedback and model parameters uncertainties.     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

Nonlinear controller design based on cascade adaptive sliding mode control for PEM fuel cell air supply systems

Optimized robust control for proton exchange membrane (PEM) fuel cell air supply systems is now a hot topic in improving the performance of oxygen excess ratio (OER) and the net power. In this paper, a cascade adaptive sliding mode control method is proposed to regulate oxygen excess ratio (OER) for proton exchange membrane (PEM) fuel cell air supply systems. Based on a simplified sixth-order nonlinear dynamic model, which takes parametric uncertainties, external disturbances and measurement noises into consideration, the nonlinear controller based on cascade adaptive sliding mode (NC-ASM) control is proposed. The method combines the nonlinear terms of super twisting algorithm and two added linear terms, and the modified second order sliding mode (SOSM) algorithm based on an observer is employed to form a cascade structure. Besides, an adaptive law is also utilized to regulate the parameters of the NC-ASM controller online. The performance of the controller is implemented on a real-time emulator. The results show that the proposed strategy performs better than the conventional constant sliding mode (CSM) control and PID method. Though during large range of load current and in the presence of various uncertainties, disturbances and noises, the NC-ASM controller can always converge rapidly, the feasibility and effectiveness are validated.     

Steady state and dynamic performance of proton exchange membrane fuel cells (PEMFCs) under various operating conditions and load changes

The steady-state performance and transient response for H₂/air polymer electrolyte membrane (PEM) fuel cells are investigated in both single fuel cell and stack configurations under a variety of loading cycles and operating conditions. Detailed experimental parameters are controlled and measured under widely varying operating conditions. In addition to polarization curves, feed gas flow rates, temperatures, pressure drop, and relative humidity are measured. Performance of fuel cells was studied using steady-state polarization curves, transient I–V response and electrochemical impedance spectroscopy (EIS) techniques. Different feed gas humidity, operating temperature, feed gas stoichiometry, air pressure, fuel cell size and gas flow patterns were found to affect both the steady state and dynamic response of the fuel cells. It was found that the humidity of cathode inlet gas had a significant effect on fuel cell performance. The experimental results showed that a decrease in the cathode humidity has a detrimental effect on fuel cell steady state and dynamic performance. Temperature was also found to have a significant effect on the fuel cell performance through its effect on membrane conductivity and water transport in the gas diffusion layer (GDL) and catalyst layer. The polarization curves of the fuel cell at different operating temperatures showed that fuel cell performance was improved with increasing temperature from 65 to 75 °C. The air stoichiometric flow rate also influenced the performance of the fuel cell directly by supplying oxygen and indirectly by influencing the humidity of the membrane and water flooding in cathode side. The fuel cell steady state and dynamic performance also improved as the operating pressure was increased from 1 to 4 atm. Based on the experimental results, both the steady state and dynamic response of the fuel cells (stack) were analyzed. These experimental data will provide a baseline for validation of fuel cell models.     

Performance improvement of a PEMFC system controlling the cathode outlet air flow

This paper presents a stationary and dynamic study of the advantages of using a regulating valve for the cathode outlet flow in combination with the compressor motor voltage as manipulated variables in a fuel cell system. At a given load current, the cathode input and output flowrate determine the cathode pressure and stoichiometry, and consequently determine the oxygen partial pressure, the generated voltage and the compressor power consumption. In order to maintain a high efficiency during operation, the cathode output regulating valve has to be adjusted to the operating conditions, specially marked by the current drawn from the stack. Besides, the appropriate valve manipulation produces an improvement in the transient response of the system. The influence of this input variable is exploited by implementing a predictive control strategy based on dynamic matrix control (DMC), using the compressor voltage and the cathode output regulating valve as manipulated variables. The objectives of this control strategy are to regulate both the fuel cell voltage and oxygen excess ratio in the cathode, and thus, to improve the system performance. All the simulation results have been obtained using the MATLAB-Simulink environment.     

Uncertainty analysis and robust control of fuel delivery systems considering nitrogen crossover phenomenon

In this paper, the fuel delivery subsystem (FDS) with hydrogen recirculation and anode bleeding is applied in proton exchange membrane fuel cell (PEMFC) system, which is utilized to supply hydrogen to the anode of stack and recirculate fuel back to the supply line. As the diffusion of nitrogen from cathode to anode is inevitable in a real PEMFC during long-term operation. To prevent system performance decline due to nitrogen accumulation. Therefore, this paper firstly develops a control-oriented nonlinear dynamic FDS model involving gas diffusion. Additionally, the FDS is very sensitive to operating environment, uncontrolled operation conditions may cause stack degradation. Specifically, a method based on Monte Carlo simulation is proposed to identify the key parameter boundaries. Then the gas distribution in FDS due to nitrogen crossover is analyzed in detail. After this, a hybrid robust methodology based on sliding mode algorithm is also proposed to maintain adequate hydrogen pressure supply, suitable hydrogen and nitrogen content in the system in presence of nitrogen crossover and renewed uncertainties. Finally, the performance of the presented controller is compared with nonlinear PID (NPID) control and nonlinear multi-input-multi-output (NMIMO) control through a hardware-in-the-loop test bench. Experimental results show that the hybrid controller is accurate and suitable for control purpose, the nitrogen content is restricted to the given range and the variation of output voltage is limited to the desired boundaries, the feasibility and effectiveness are validated.     

Parametric analysis of a hybrid power system using organic Rankine cycle to recover waste heat from proton exchange membrane fuel cell

Using fuel cell systems for distributed generation (DG) applications represents a meaningful candidate to conventional plants due to their high power density and the heat recovery potential during the electrochemical reaction. A hybrid power system consisting of a proton exchange membrane (PEM) fuel cell stack and an organic Rankine cycle (ORC) is proposed to utilize the waste heat generated from PEM fuel cell. The system performance is evaluated by the steady-state mathematical models and thermodynamic laws. Meanwhile, a parametric analysis is also carried out to investigate the effects of some key parameters on the system performance, including the fuel flow rate, PEM fuel cell operating pressure, turbine inlet pressure and turbine backpressure. Results show that the electrical efficiency of the hybrid system combined by PEM fuel cell stack and ORC can be improved by about 5% compared to that of the single PEM fuel cell stack without ORC, and it is also indicated that the high fuel flow rate can reduce the PEM fuel cell electrical efficiency and overall electrical efficiency. Moreover, with an increased fuel cell operating pressure, both PEM fuel cell electrical efficiency and overall electrical efficiency firstly increase, and then decrease. Turbine inlet pressure and backpressure also have effects on the performance of the hybrid power system.     

Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems

This paper presents the oxygen stoichiometry control problem of proton exchange membrane (PEM) fuel cells and introduces a solution through an optimal control methodology. Based on the study of a non-linear dynamical model of a laboratory PEM fuel cell system and its associated components (air compressor, humidifiers, line heaters, valves, etc.), a control strategy for the oxygen stoichiometry regulation in the cathode line is designed and tested. From a linearised model of the system, an LQR/LQG controller is designed to give a solution to the stated control problem. Experimental results show the effectiveness of the proposed controllers design.     

Model-based decoupling control for the thermal management system of proton exchange membrane fuel cells

As one of the most promising sustainable energy technologies available today, proton exchange membrane fuel cell (PEMFC) engines are becoming more and more popular in various applications, especially in transportation vehicles. However, the complexity and the severity of the vehicle operating conditions present challenges to control the temperature distribution in single cells and stack, which is an important factor influencing the performance and durability of PEMFC engines. It has been found that regulating the input and output coolant water temperature can improve the temperature distribution. Therefore, the control objective in this paper is regulating the input and output temperature of coolant water at the same time. Firstly, a coupled model of the thermal management system is established based on the physical structure of PEMFC engines. Then, in order to realize the simultaneous control of the inlet and outlet cooling water temperature of the PEMFC stack, a decoupling controller is proposed and its closed-loop stability is proved. Finally, based on the actual PEMFC engine platform, the effectiveness, accuracy and reliability of the proposed decoupling controller are tested. The experimental results show that with the proposed decoupling controller, the inlet and outlet temperatures of the PEMFC stack cooling water can be accurately controlled on-line. The temperature error range is less than 0.2 °C even under the dynamic current load conditions.     

ANFIS-MPPT control algorithm for a PEMFC system used in electric vehicle applications

Fuel cell has been considered as one of the optimistic renewable power technologies for the automotive applications. The output power of a fuel cell is immensely dependent on cell temperature and membrane water content. Hence, a maximum power point tracking controller is essentially required to extract the optimum power from the fuel cell stack. In this paper, an adaptive neuro-fuzzy inference system based maximum power point tracking controller is presented for 1.26 kW proton exchange membrane fuel cell system used in electric vehicle applications. In order to extract the optimum power, a high step-up boost converter is connected between the fuel cell and the BLDC motor. The duty cycle of the converter is controlled by using ANFIS reference model, so that the maximum power is delivered to the BLDC motor. The performance of the proposed controller is tested under normal operating conditions and also for sudden variations in the cell temperatures of the fuel cell. In addition to this, to analyze the effectiveness and tracking behaviour of the proposed controller, the results were compared with those obtained using the fuzzy logic controller. Compared to the fuzzy logic controller, the proposed ANFIS controller has increased the average DC link power by 1.95% and the average time taken to reach the maximum power point is reduced by 17.74%.     

Characterization of flooding and two-phase flow in polymer electrolyte membrane fuel cell stacks

A partially flooded gas diffusion layer (GDL) model is proposed and solved simultaneously with a stack flow network model to estimate the operating conditions under which water flooding could be initiated in a polymer electrolyte membrane (PEM) fuel cell stack. The models were applied to the cathode side of a stack, which is more sensitive to the inception of GDL flooding and/or flow channel two-phase flow. The model can predict the stack performance in terms of pressure, species concentrations, GDL flooding and quality distributions in the flow fields as well as the geometrical specifications of the PEM fuel cell stack. The simulation results have revealed that under certain operating conditions, the GDL is fully flooded and the quality is lower than one for parts of the stack flow fields. Effects of current density, operating pressure, and level of inlet humidity on flooding are investigated.     

An application of indirect model reference adaptive control to a low-power proton exchange membrane fuel cell

Nonlinearity and the time-varying dynamics of fuel cell systems make it complex to design a controller for improving output performance. This paper introduces an application of a model reference adaptive control to a low-power proton exchange membrane (PEM) fuel cell system, which consists of three main components: a fuel cell stack, an air pump to supply air, and a solenoid valve to adjust hydrogen flow. From the system perspective, the dynamic model of the PEM fuel cell stack can be expressed as a multivariable configuration of two inputs, hydrogen and air-flow rates, and two outputs, cell voltage and current. The corresponding transfer functions can be identified off-line to describe the linearized dynamics with a finite order at a certain operating point, and are written in a discrete-time auto-regressive moving-average model for on-line estimation of parameters. This provides a strategy of regulating the voltage and current of the fuel cell by adaptively adjusting the flow rates of air and hydrogen. Experiments show that the proposed adaptive controller is robust to the variation of fuel cell system dynamics and power request. Additionally, it helps decrease fuel consumption and relieves the DC/DC converter in regulating the fluctuating cell voltage.     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Temperature and hydrogen flow rate controls of diesel autothermal reformer for 3.6 kW PEM fuel cell system with autoignition delay time analysis

In this paper catalyst temperature and hydrogen flow rate controls are an area of interest for autothermal reforming (ATR) of diesel fuel to provide continuous and necessary hydrogen flow to the on-board fuel cell vehicle system. ATR control system design is important to ensure proper and stable performance of fuel processor and fuel cell stack. Fast system response is required for varying load changes in the on-board fuel cell system. To cope with control objectives, a combination of PI and PID controllers are proposed to keep the controlled variables on their setpoints. ATR catalyst temperature is controlled with feedback PID controller through variable OCR (oxygen to carbon ratio) manipulation and kept to the setpoint value of 900 °C. Additionally diesel auto-ignition delay time is implemented through fuel flow rate delay to avoid complete oxidation of fuel. Hydrogen flow rate to the fuel cell stack is kept to setpoint of required hydrogen flow rate according to fuel cell load current using PI controller. An integrated dynamic model of fuel processor and fuel cell stack is also developed to check the fuel cell voltage. Product gas composition of 35, 18 and 4% is achieved for hydrogen, nitrogen, and carbon dioxide, respectively. The results show fast response capabilities of fuel processor following the fuel cell load change and successfully fulfills the control objectives.     

Adaptive thermal control for PEMFC systems with guaranteed performance

Proton exchange membrane fuel cell (PEMFC) s are faced with dynamical load scenario in practical applications, and the resulting temperature variation will decrease the performance and consequently shorten the fuel cell lifetime. To address this problem, a control strategy for regulating the stack temperature is proposed in this paper. Firstly, a thermal management-oriented dynamic model of a water-cooled PEMFC system is built to facilitate the control design. Secondly, considering that the stack temperature should be maintained in a certain range regardless of the dynamical changing current demand, a Barrier Lyapunov function is employed to construct a feedback error of the stack temperature. Thirdly, a set of adaptation laws is designed to estimate the unknown parameters related to the gas flow rates in the flow fields. Particularly, a dynamic inversion tracking methodology is applied to design the non-affine input. A Lyapunov method based analysis demonstrates the stability and convergence of the closed-loop properties. Simulation results are provided to show that the proposed control strategy can satisfy all the control objectives and enhance the control performance compared to the proportional-integral controlled case.     

Exergoeconomic analysis of a vehicular PEM fuel cell system

In this study, we deal with the exergoeconomic analysis of a proton exchange membrane (PEM) fuel cell power system for transportation applications. The PEM fuel cell performance model, that is the polarization curve, is previously developed by one of the authors by using the some derived and developed equations in literature. The exergoeconomic analysis includes the PEM fuel cell stack and system components as compressor, humidifiers, pressure regulator and the cooling system. A parametric study is also conducted to investigate the system performance and cost behaviour of the components, depending on the operating temperature, operating pressure, membrane thickness, anode stoichiometry and cathode stoichiometry. For the system performance, energy and exergy efficiencies and power output are investigated in detail. It is found that with an increase of temperature and pressure and a decrease of membrane thickness the system efficiency increases which leads to a decrease in the overall production cost. The minimization of the production costs is very crucial in commercialization of the fuel cells in transportation sector.     

Improving dynamic performance of proton-exchange membrane fuel cell system using time delay control

Transient behaviour is a key parameter for the vehicular application of proton-exchange membrane (PEM) fuel cell. The goal of this presentation is to construct better control technology to increase the dynamic performance of a PEM fuel cell. The PEM fuel cell model comprises a compressor, an injection pump, a humidifier, a cooler, inlet and outlet manifolds, and a membrane-electrode assembly. The model includes the dynamic states of current, voltage, relative humidity, stoichiometry of air and hydrogen, cathode and anode pressures, cathode and anode mass flow rates, and power. Anode recirculation is also included with the injection pump, as well as anode purging, for preventing anode flooding. A steady-state, isothermal analytical fuel cell model is constructed to analyze the mass transfer and water transportation in the membrane. In order to prevent the starvation of air and flooding in a PEM fuel cell, time delay control is suggested to regulate the optimum stoichiometry of oxygen and hydrogen, even when there are dynamical fluctuations of the required PEM fuel cell power. To prove the dynamical performance improvement of the present method, feed-forward control and Linear Quadratic Gaussian (LQG) control with a state estimator are compared. Matlab/Simulink simulation is performed to validate the proposed methodology to increase the dynamic performance of a PEM fuel cell system.