Fuzzy control of hydrogen pressure in fuel cell system

Precise control of hydrogen pressure is crucial for the performance and durability of fuel cell systems. With the widely used common-rail injection system, traditional PID controller still dominates. For a long time, the hydrogen pressure fluctuates acutely when hydrogen purge valve switches or load sharply changes with using PID controller. In recent studies, several new control strategies are presented. However, mostly of them are theoretical and experimental. In this study, an improved common-rail injection system, hydrogen injector/ejector assembly is introduced. Based on a real fuel cell system, a Mamdani fuzzy controller is designed to regulate the hydrogen pressure. The algorithm of fuzzy controller is explained in detail. A comparative study is carried out between fuzzy controller and PID controller. According to the results, the stability of hydrogen pressure with using fuzzy controller is better than using PID controller. This research could be useful for the control of fuel cell system.     

A fuzzy logic PI control with feedforward compensation for hydrogen pressure in vehicular fuel cell system

In a vehicular fuel cell system, alternative load and frequent purge action can lead to anode pressure varies with the hydrogen mass flow fluctuation. It's crucial to control the pressure difference between anode and cathode within a reasonable range to avoid adverse phenomena such as membrane failure, reactant starvation, or even water management fault. In this paper, an improved proportional integrative (PI) controller by the fuzzy logic technique that considers the engineer experience and knowledge on the hydrogen supply system behavior is proposed for hydrogen pressure control, in which the PI parameters are tuned by a fuzzy decision process. Furthermore, load current and purge action regarded as input disturbances are applied for feedforward compensation to reduce the pressure response hysteresis. A hydrogen supply subsystem based on the proportional valve is modeled, and corresponding parameters are determined by analyzing the response time and steady pressure fluctuation. The performance of the conventional PI controller, the fuzzy logic PI (FLPI) controller and fuzzy logic PI with feedforward (FLPIF) controller is validated. The presented results indicated that the FLPI controller significantly improves the dynamic response of hydrogen pressure compared to the PI controller, and the FLPIF controller can further reduce overshoot caused by disturbance. Finally, the proposed FLPIF controller is implemented on a rapid prototype platform of the hydrogen supply subsystem and an actual fuel cell system, exhibiting satisfactory performance.     

On-line implementation of model free controller for oxygen stoichiometry and pressure difference control of polymer electrolyte fuel cell

This paper proposes and validates a model free controller to improve the real time operating conditions of Proton Exchange Membrane Fuel Cells (PEMFC). This approach is based on an ultra-local model that does not depend on a precise knowledge of the system. It is perfectly adapted to a complex system such as the fuel cell, while benefiting from the ease of online implementation and low computational cost. The designed controller is used to regulate both the oxygen stoichiometry and the membrane inlet pressure, which are crucial operating conditions for the fuel cell's lifetime. The objectives of the proposed control strategy are twofold: preventing the starvation failure, and limiting the potential for mechanical degradation of the membrane during a large pressure difference. The performance of the proposed control strategy is initially evaluated by a simulation environment for both oxygen stoichiometry and inlet pressure difference control of fuel cell stack. An online validation on 1.2 KW fuel cell stack is conducted to control the membrane pressure drop. Two case studies are comprehensively investigated in relation to stoichiometry control: set point tracking and rejection of unmeasured disturbances caused by current variations. Simulations and experimental results reveal that the proposed controller provides significantly better performance in terms of fast trajectory tracking, and ensures less overshoot compared to the Fuzzy PID and PID controller. This efficiency is proven using the Integral Absolute Error (IAE), Integral Squared Error (ISE) and Integral of the Square input (ISU) performance indexes.     

Thermal modeling and temperature control of a PEM fuel cell system for forklift applications

Temperature changes in PEM fuel cell stacks are considerably higher during load variations and have a negative impact as they generate thermal stresses and stack degradation. Cell hydration is also of vital importance in fuel cells and it is strongly dependent on operating temperature. A combination of high temperature and reduced humidity increases the degradation rate. Stack thermal management and control are, thus, crucial issues in PEM fuel cell systems especially in automotive applications such as forklifts.     

A cold start mode of proton exchange membrane fuel cell based on current control

In this study, a mathematical model is established to simulate the cold start of fuel cell, including the calculation of the temperature distribution and heat exchange. Moreover, a novel cold-start mode is designed and compared with the constant and linear current cold-start modes. It uses the ice volume and heat absorbed by the membrane as fuzzy control inputs and outputs current density. Compared with other modes at 263 K, the cold startup time is shortened by 25.6–41.6 s, and the ice volume fraction is reduced by 29.4%–31.8%. Only the proposed mode achieves a successful cold start at a lower temperature. Also, the proposed mode has better thermal behavior, as indicated by the temperature distribution diagrams. Furthermore, to avoid performance degradation caused by cold starts, an inertia link is added to the controller, so that the current amplitude is reduced by 7.98%, and the maximum change rate by 57.44%.     

Pressure analysis on two-step high pressure reducing system for hydrogen fuel cell electric vehicle

Hydrogen fuel cell electric vehicle (FCEV) can achieve zero exhaust emission and zero pollution. In order to make FCEV reach a farther travel distance, greater demands are put on its pressure reducing system. In this paper, a two-step high pressure reducing system for FCEV is proposed. The system is made up of two parts, a new high multi-stage pressure reducing valve (HMSPRV) and a multi-stage muffler. As a new system, its feasibility has to be verified. Since the valve opening condition has a great effect on hydrogen flow, pressure reduction and energy consumption, different valve opening conditions are taken as the research point. The flow field analysis of the new HMSPRV is conducted on three aspects: pressure field, velocity field and energy consumption. It can be found that both the pressure reducing and velocity increasing gradients mainly reflect at those throttling components for all valve openings. For energy consumption, in the comprehensive study of flow vortexes and turbulent dissipation rate, it can be found that the larger of the valve opening, the larger of energy consumption. Then, a thermo-fluid-solid coupling analysis is conducted on the new HMSPRV, and it is concluded that the new system meets strength requirement. Furthermore, as the second step of the high pressure reducing system, the flow and pressure fields of multi-stage muffler are investigated. The five-stage muffler is exactly designed to complete the whole pressure reducing process. This study can provide technological support for achieving pressure regulation in the hydrogen transport system of FCEV when facing complex conditions, and it can also benefit the further research work on energy saving and multi-stage flow of pressure reducing devices.     

Role of chromium: Iron ratio and oxygen partial pressure on the processing and chemical stability of iron doped lanthanum strontium chromite based OTM

The present research, as a part of the OTM materials development and testing effort, examines the combined effect of the Cr: Fe ratio (7:3, 8:2 and 9:1) and oxygen partial pressure (PO₂) on the densification, microstructural development, and chemical stability of lanthanum chromite (La_0.8Sr_0.2)_0.95Cr_1-xFe_xO₃ (LSCrF) for application in oxygen transport membrane and solid oxide fuel cell electrode. While highest density of 96.3 (±0.5) % is achieved for LSCrF with Cr: Fe ratio of 7:3 at 1400 °C and PO₂ ～ 10^?10 atm., the relative density decreases with increase in Cr: Fe ratio and PO₂. LSCrF perovskite stability increases with increase in Cr: Fe ratio in reducing gas atmosphere. LSCrF (7:3) dissociates into FeO_x and Fe_1+xCr_2-xO₄ under reducing gas atmosphere (Ar-3%H₂-3%H₂O). LSCrF (9:1) perovskite does not show any evidence of second phase (FeO_x and Fe_1+xCr_2-xO₄) formation with decrease in PO₂ unlike LSCrF (7:3 and 8:2). Defect chemistry and mechanism for FeO_x and Fe_1+x Cr_2?x O₄ formation in reducing atmosphere is described. LSCrF decomposition and the formation of the secondary phases are in agreement with the thermodynamic simulation results obtained with the La-Sr-Cr-Fe-O thermodynamic database.     

Performance improvement of PEM fuel cell power system using fuzzy logic controller-based MPPT technique to extract the maximum power under various conditions

Power generation of a fuel cell (FC) is mostly dependent upon operational variables such as cell temperature and membrane water content. There is an individual maximum power point (MPP) on the P-I curve of the FC. The location of the MPP varies with respect to the MPP position. Thus, an MPP tracking (MPPT) system should exist to guarantee that the FC works at the MPP in order to maximize the functionality. Due to their straightforward structure, prevalent MPPT methods had strong functionality. However, their primary limitations include fluctuations around the MPP and inefficiency under abrupt variations of operating conditions. The primary objective of this paper is to maintain the PEMFCs operation at an efficient power point. To this purpose, the efficiency of PEM-FC is tested and enhanced using a variety of MPPT-based smart controller techniques. To determine the appropriate MPPT controller parameters, the modified fluid search optimization (MFSO) approach and fuzzy logic controller (FLC) are employed. Furthermore, the MFSO method is deployed to adjust the membership functions (MFs) of the FLC. The MFSO is an excellent approach for coping with the stochastic behavior of the PEM-FC system when the temperature and water content of the membrane change. In terms of improved dynamic behavior, better convergence rate, reduced oscillations, and better tracking of the MPP, the results obtained by employing the suggested strategy demonstrate the superior functionality of the system compared to case using other methods. Moreover, the power generated by the PEMFC system is less than the nominal capacity for the temperature's rated capacity. Therefore, the deficit in power would be covered by transacting power with the grid.     

Robust energy management strategy based on non-linear cascade control of fuel cells-super capacitors hybrid power system

The use of super capacitors as secondary sources in fuel cell power systems with adequate energy management strategy strongly contributes to increasing the lifespan of fuel cells by protecting them against sudden variations of the load current and improves the efficiency and the dynamics of the hybrid power system, thus obtained. This paper presents an innovative management strategy of fuel cells-super capacitors hybrid power system, based on a nonlinear control using an integral hysteresis sliding mode controller combined with two cascaded linear controllers. The hybrid power system consists of the fuel cells system, the super capacitors, two power converters, the energy management system and the load. The proposed technique takes into account the physical operating limits of the secondary source such as deep discharges and excessive overloads. Furthermore, the integral effect added to the hysteresis sliding mode controller improves the robustness against disturbances and variations in parameters such as filtering inductances and DC bus capacitors. A detailed model of the system is established and simulated in Matlab/Simulink software, which allows showing its behavior with a very satisfactory accuracy. The simulation results clearly show that the proposed control strategy insures efficient and safe energy transfer. In addition, the control robustness is very satisfactory despite the variation of the system parameters.     

Nonlinear model predictive control based on the moving horizon state estimation for the solid oxide fuel cell

As a nonlinear power generation device, the solid oxide fuel cell (SOFC) often operates under small window of operating conditions due to the constraints stemming from the environmental and safety considerations. The nonlinear model predictive control (NMPC) appears to be well suited control algorithm for this application. NMPC is a closed-loop feedback control scheme that predicts the open-loop optimal input based on the measurements and the setting trajectory. This work aims to develop a closed-loop feedback control strategy based on the NMPC controller for a planar SOFC. The current density, fuel and air molar flow rates are chosen as manipulated variables to control the output power, fuel utilization and temperature. The mole fraction and temperature of the exit gases are set as state variables, which can be estimated from the moving horizon estimation (MHE) method. The validation here is referred to robustness and stability of the controller, a typical case study has been conducted with the power output changes under constant fuel utilization and temperature. Simulation results show that the noise of the output is successfully filtered by the MHE. The NMPC controller works satisfactorily following the setting output trajectory.     

燃煤锅炉母管压力/给粉调节系统的前馈及反馈复合控制

针对并列母管制运行锅炉母管压力参数具有大滞后、锅炉之间相互干扰、相互耦合的特点，提出了协调控制的策略。根据主设备运行工况自动区分内外扰动类型，根据扰动强弱判断燃烧稳定状态，以运行相应的控制策略。实际运行证明在各种复杂工况下，母管压力协调控制均能取得良好的控制效果。     

Analysis of air conditioning system impact on a fuel cell vehicle performance based on a realistic model under actual urban conditions

In this study, a practical fuel cell vehicle considering the Heating, Ventilation, and Air conditioning system is considered to analyze hydrogen consumption under different working conditions. As a prevalent hydrogen-fueled vehicle, Toyota Mirai has been meticulously modeled in Simecenter Amesim software. The simulated model covers all of the vehicle's components with a concentration on Heating, Ventilation, and Air conditioning system. Since the air temperature and ‘weather conditions can significantly impact the vehicle's overall performance, various environmental conditions, including temperature variations, humidity, and varied solar fluxes, are taken into account. Furthermore, New York City is chosen as a densely populated megacity to simulate the dynamic behavior of the fuel cell vehicle under actual driving circumstances. The results illustrate that the Heating, Ventilation, and Air conditioning system can notably alter hydrogen consumption under real driving conditions. In this regard, turning on the Heating, Ventilation, and Air Conditioning system results in a 19% increase in fuel consumption. Moreover, the degradation phenomenon, which is a typical result of using fuel cell vehicles under urban driving conditions, impacts the vehicle's mileage and hydrogen consumption. The simulation results indicate that a fresh fuel cell stack consumes 80 g of hydrogen, while for 2500 and 5500 working hours fuel cells, the stack consumes 89.6 and 107 g of hydrogen, respectively. Based on the obtained results, a 33.75% increase in fuel consumption occurs by implementing a degraded fuel cell stack under real driving conditions.     

Control of a fuel cell based on the SIRMs fuzzy inference model

A typical working mode for the fuel cell hybrid system is that the fuel cell produces constant power output while the auxiliary storage energy device such as ultracapacitor or battery provides the deviation between the desired power demand and the value of the actual operation. This paper concentrates on the control of the fuel cell flow system. The system which is like an under-actuated mechanical system needs to control two objects (the cathode pressure and the air flow) with one manipulated variable (the set voltage of the air mass flow controller). A SIRMs-based fuzzy inference model is successfully implemented in the system. Online random search optimization algorithm based on Simulink C-S functions is developed to adjust the parameters in the model. By alternative control of the two objects, experimental results demonstrate the realization of the control strategy with one adjustment means.     

A hybrid multi-level optimization approach for the dynamic synthesis/design and operation/control under uncertainty of a fuel cell system

During system development, large-scale, complex energy systems require multi-disciplinary efforts to achieve system quality, cost, and performance goals. As systems become larger and more complex, the number of possible system configurations and technologies, which meet the designer’s objectives optimally, increases greatly. In addition, both transient and environmental effects may need to be taken into account. Thus, the difficulty of developing the system via the formulation of a single optimization problem in which the optimal synthesis/design and operation/control of the system are achieved simultaneously is great and rather problematic. This difficulty is further heightened with the introduction of uncertainty analysis, which transforms the problem from a purely deterministic one into a probabilistic one. Uncertainties, system complexity and nonlinearity, and large numbers of decision variables quickly render the single optimization problem unsolvable by conventional, single-level, optimization strategies.To address these difficulties, the strategy adopted here combines a dynamic physical decomposition technique for large-scale optimization with a response sensitivity analysis method for quantifying system response uncertainties to given uncertainty sources. The feasibility of such a hybrid approach is established by applying it to the synthesis/design and operation/control of a 5 kW proton exchange membrane (PEM) fuel cell system.     

A comparison of high-speed flywheels, batteries, and ultracapacitors on the bases of cost and fuel economy as the energy storage system in a fuel cell based hybrid electric vehicle

Fuel cells aboard hybrid electric vehicles (HEVs) are often hybridized with an energy storage system (ESS). Batteries and ultracapacitors are the most common technologies used in ESSs aboard HEVs. High-speed flywheels are an emerging technology with traits that have the potential to make them competitive with more established battery and ultracapacitor technologies in certain vehicular applications. This study compares high-speed flywheels, ultracapacitors, and batteries functioning as the ESS in a fuel cell based HEV on the bases of cost and fuel economy. In this study, computer models were built to simulate the powertrain of a fuel cell based HEV where high-speed flywheels, batteries, and ultracapacitors of a range of sizes were used as the ESS. A simulated vehicle with a powertrain using each of these technologies was run over two different drive cycles in order to see how the different ESSs performed under different driving patterns. The results showed that when cost and fuel economy were both considered, high-speed flywheels were competitive with batteries and ultracapacitors.     

Small signal modelling and control of high gain coupled inductor boost inverter for solid oxide fuel cell based power generation system

Small signal model of high gain coupled inductor boost inverter is established in presented work. Developed small signal model is then integrated with the model of planar solid oxide fuel cell and simulation of complete system is realized using MATLAB/Simulink environment and compared with the already developed fuel cell-based power converters. Coupled inductor boost converter was chosen to achieve higher gain in dc link voltage by selecting the appropriate turn ratio. Small signal model for dc-dc and dc-ac stages is derived separately and accordingly control system is designed. Dual loop with feed forward control scheme for coupled inductor boost inverter resulted in good performance like stable dc link, fast transient response, low total harmonic distortion (THD) and input disturbance rejection. Mathematical analysis, simulation and hardware results prove the stability and reliability of the complete system.     

Experimental investigation on the dynamic performance of a hybrid PEM fuel cell/battery system for lightweight electric vehicle application

A hybrid system combining a 2 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack and a lead–acid battery pack is developed for a lightweight cruising vehicle. The dynamic performances of this PEMFC system with and without the assistance of the batteries are systematically investigated in a series of laboratory and road tests. The stack current and voltage have timely dynamic responses to the load variations. Particularly, the current overshoot and voltage undershoot both happen during the step-up load tests. These phenomena are closely related to the charge double-layer effect and the mass transfer mechanisms such as the water and gas transport and distribution in the fuel cell. When the external load is beyond the range of the fuel cell system, the battery immediately participates in power output with a higher transient discharging current especially in the accelerating and climbing processes. The DC–DC converter exhibits a satisfying performance in adaptive modulation. It helps rectify the voltage output in a rigid manner and prevent the fuel cell system from being overloaded. The dynamic responses of other operating parameters such as the anodic operating pressure and the inlet and outlet temperatures are also investigated. The results show that such a hybrid system is able to dynamically satisfy the vehicular power demand.     

Bluetooth wireless monitoring,diagnosis and calibration interface for control system of fuel cell bus in Olympic demonstration

With the worldwide deterioration of the natural environment and the fossil fuel crisis, the possible commercialization of fuel cell vehicles has become a hot topic. In July 2008, Beijing started a clean public transportation plan for the 29th Olympic games. Three fuel cell city buses and 497 other low-emission vehicles are now serving the Olympic core area and Beijing urban areas. The fuel cell buses will operate along a fixed bus line for 1 year as a public demonstration of green energy vehicles. Due to the specialized nature of fuel cell engines and electrified power-train systems, measurement, monitoring and calibration devices are indispensable. Based on the latest Bluetooth wireless technology, a novel Bluetooth universal data interface was developed for the control system of the fuel cell city bus. On this platform, a series of wireless portable control auxiliary systems have been implemented, including wireless calibration, a monitoring system and an in-system programming platform, all of which are ensuring normal operation of the fuel cell buses used in the demonstration.