Fault-tolerant control through dynamic surface triple-step approach for proton exchange membrane fuel cell air supply systems

Due to complex electrochemical and thermal phenomena, varying operations towards automotive applications, and vulnerable ancillaries in proton exchange membrane fuel cells (PEMFCs), fault diagnosis and fault-tolerant control (FTC) design have become important aspects to improve the reliability, safety and performance of PEMFC systems. This paper presents a novel FTC scheme for automotive PEMFC air supply systems via coordinated control of the air flow rate and the pressure in cathodes. A dynamic surface triple-step approach is first proposed considering nonlinear dynamics and the multi-input multi-output (MIMO) property, which combines the advantage of dynamic surface control in avoiding an “explosion of complexity” and the advantage of triple-step control in guaranteeing a simple structure and high performance. The normal case, the faulty case at the supply manifold and the faulty case in the back pressure valve are considered in the FTC design, with the stability of the overall system proved using Lyapunov methods. MATLAB/Simulink simulations with a high-fidelity PEMFC model verify the effectiveness of the proposed FTC scheme in regulating the air flow rate and oxygen excess ratio and maintaining the pressure of the cathode at a desired level even under faulty conditions.     

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.     

Modeling and control of air stream and hydrogen flow with recirculation in a PEM fuel cell system—II. Linear and adaptive nonlinear control

In this part of the paper, linear and nonlinear multivariable controllers are designed for the air stream and hydrogen flow with recirculation in a proton exchange membrane (PEM) fuel cell system. The focus of the model is to obtain the desired transient performance of air stoichiometric ratio, cathode inlet pressure, and pressure difference between the anode and the cathode. Based on linearization of the nonlinear dynamic model in the first part of this paper, the coupling between control inputs and performance is analyzed first. The phase relationship between the stack voltage and water transport in frequency domain is meaningful to the future humidity estimation and active purge operation. Then, linear quadratic Gaussian (LQG) algorithm based on observer feedback is used for set-point tracking, and a model-predictive controller (MPC) with an on-line neural network identifier is also designed to improve robustness. Compared with decentralized PI controllers, the multivariable controllers improve the transient response and shows better disturbance rejection capability.     

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.     

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.     

Anti-disturbance control of oxygen feeding for vehicular fuel cell driven by feedback linearization model predictive control-based cascade scheme

The accurate control of automotive fuel cell oxygen excess ratio (OER) is necessary to improve system efficiency and service life. To this end, an anti-disturbance control driven by a feedback linearization model predictive control (MPC)-based cascade scheme is proposed. It considers strong nonlinear coupling and disturbance injection of fuel cell oxygen supply. A six-order nonlinear fuel cell oxygen feeding model is presented. It is further formulated using an extended state observer to rapidly reconstruct the OER, to overcome the slow response and interference errors of sensor measurements. In the proposed cascade control, the outer loop is the anti-disturbance control which is used to realize the optimized OER tracking and the inner loop via the feedback linearization to linearize the oxygen feeding behaviors conducts MPC to regulate the air compressor output mass flow. The feedback linearization demonstrates a robust tracking performance of nonlinear outputs, and the integral absolute error of anti-disturbance control is 0.3021 lower than that of PI control under a custom test condition. Finally, the numerical validation on a hybrid driving cycle indicates that the proposed cascade control can regulate the fuel cell OER with an average absolute error of 0.02313 in the high air compressor operation efficiency zone.     

Model-based control of cathode pressure and oxygen excess ratio of a PEM fuel cell system

For PEM fuel cells supplied with air, pressure and flow control is a key requirement for an efficient and dynamic operation because fuel cells are in risk of starvation when the partial pressure of oxygen at the cathode falls below a critical level. To avoid oxygen starvation and, at the same time, to allow for a dynamic operation of the fuel cell system, both excess ratio of oxygen and cathode pressure need to be adjusted rapidly.     

Oxygen excess ratio control for proton exchange membrane fuel cell using model reference adaptive control

Optimized robust oxygen excess ratio (OER) control for proton exchange membrane fuel cells (PEMFCs) is now a critical issue for improving their economic efficiency and performance. In general, it is very difficult to control the OER due to modeling errors, parameter uncertainties, and disturbances. To address these issues, we propose a control system based on model reference adaptive control (MRAC) various difficulties inherent air supply systems.We utilize an adaptive law to address uncertainties implementation of the MRAC and nominal feedback controllers on a nonlinear model of fuel cell system is presented for illustration of the proposed system's robustness with various operating conditions. In addition, the control performance of MRAC is compared with nominal feedback control. The results show that the presented MRAC strategy performs better than the nominal feedback control method with less wear and less control effort on the compressor. The proposed MRAC algorithm can increase the compressor efficiency by using the adaptive law even with uncertainties.     

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.     

Robust fault diagnosis and fault tolerant control for PEMFC system based on an augmented LPV observer

In order to improve the safety and reliability of proton exchange membrane fuel cell system, this paper proposes a novel robust fault observer for the fault diagnosis and reconstruction of the PEMFC air management system. First, considering the complexity and large computation of the nonlinear PEMFC system, a linear parameter-varying (LPV) model is introduced to describe the system behavior and reduce the computation cost. Then, an augmented state observer based on the LPV model is proposed for simultaneously estimating the internal states and component faults. The robustness is guaranteed by taking the system disturbances and measurement noises into consideration when designing the observer gain. The observer design is transformed into a process of solving a set of linear inequality matrices. According to the results, the augmented robust observer can accurately estimate the system states and faults under different conditions. Moreover, to realize the fault tolerant control of the air supply, the oxygen stoichiometry estimator is designed taking consideration of system fault information and a corresponding controller is employed for air compressor voltage following the net power maximization strategy.     

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.     

Adaptive energy management for fuel cell hybrid power system with power slope constraint and variable horizon speed prediction

An adaptive energy management strategy (EMS) is proposed to improve the economy and reliability of the fuel cell vehicle. Firstly, a variable horizon speed prediction method based on the principal component analysis and the K-means clustering is constructed. Then, an adaptive equivalent consumption minimization strategy (AECMS) with power slope constraints was designed to minimize the hydrogen consumption while ensuring reliability. Finally, a proportional-integral controller is used to track the air flow and pressure of the fuel cell engine (FCE) under energy distribution. Simulation results under West Virginia University Suburban (WVUSUB) show that the proposed strategy can improve the speed prediction accuracy by 2.80% and 25.57%, and reduce the hydrogen consumption by 2.79% and 2.66%, respectively, compared with the fixed 12 s and 15 s horizon. Moreover, the control error of oxygen excess ratio and the cathode pressure under energy distribution are 0.0102 (0.51%) and 189.4 Pa (0.0935%), respectively, indicating better reliability than the strategy without constraint.     

核电站蒸汽发生器水位的自抗扰多模型控制方法研究

针对核电站蒸汽发生器水位控制的非线性分布特点,在自抗扰控制技术的基础上结合多模型控制提出了蒸汽发生器水位系统新的控制方案.在该控制方案中,对蒸汽发生器设计了多模型控制系统,并针对各个模型分别设计了不同负荷下的自抗扰控制器,可以对扩张状态进行在线实时估计,因此设计的扰动补偿不依赖于模型便能够达到快速消去扰动的效果.将该方法用于蒸汽发生器水位控制系统进行仿真研究,结果表明：该控制方案实现了对蒸汽发生器水位良好的动态控制,具有较强的鲁棒性和抗干扰能力,且算法简单,便于调试.     

带恒功率负载多电平Boost变换器的复合非线性控制

针对带恒功率负载的多电平Boost变换器,提出一种将非线性干扰观测器和自适应滑模控制器相结合的复合非线性控制策略。首先应用精确反馈线性化方法将模型转化为布鲁诺夫斯基标准形式。然后在保证大信号稳定的前提下,将自适应控制方法和非线性干扰观测器加入到滑模控制器的设计中,利用李雅普诺夫理论证明整个闭环系统的稳定性。仿真和实验结果表明,与双闭环PI控制方法相比,该控制策略具有更好的动态调节性能和更强的鲁棒性。     

High-potential control for durability improvement of the vehicle fuel cell system based on oxygen partial pressure regulation under low-load conditions

In the state-of-the-art high-power self-humidifying proton exchange membrane fuel cell (PEMFC) systems for vehicles, the high potential and low water production at idle or low load conditions strongly cause corrosion and decay of key materials and thus reduce durability. Therefore, the control technology of system-level durability requires an innovative design. Cathode recirculation is beneficial in alleviating the above unfavorable factors from the perspective of regulating oxygen and vapor partial pressure. This paper presents a pioneering study on the dynamics and control of cathode recirculation in vehicle high-power self-humidifying PEMFC system under low load conditions. First, a control-oriented dynamic model of the vehicle PEMFC system with a cathode recirculation loop is developed and the steady-state and dynamic performance is verified with experimental data from a 120 kW system. Active control of the intake component is achieved by re-feeding the reacted cathode gas to the air compressor outlet through a recirculation pump. On this basis, a high-potential controller based on oxygen partial pressure regulation is designed in combination with the dynamics of cathode recirculation. Results show that the designed dynamic fuzzy logic segmented proportional integral derivative controller with feedforward compensation achieves the optimal high-potential control effect by managing the oxygen partial pressure under variable low load conditions. It not only has excellent anti-disturbance ability but also effectively reduces the dynamic response time, transient overshoot, and steady-state error to satisfy the rapid and stable voltage output. Finally, the concomitant effect of humidification brought by the implementation of the optimal high-potential controller is analyzed, and the results show that the proton membrane is completely humidified.     

Air supply regulation for PEMFC systems based on uncertainty and disturbance estimation

In this paper, a novel system analysis and controller design method for the air supply of proton exchange membrane (PEM) fuel cell systems is proposed. Firstly, a class of nonlinear systems with specific structures are introduced. In further analysis, the introduced system can be divided into two parts: one is fast and include disturbances and uncertainty, and the other is relatively slow. We change the introduced system into an equivalent cascade system. Some state variables of the first subsystem are acted as the inputs of the second subsystem. Furthermore, the similarities between the air supply system and the equivalent cascade system are proved, and a cascade controller is proposed based on uncertainty and disturbance estimation (UDE) and Lyapunov method. Moreover, we implement the algorithm in the air supply system for PEM fuel cells. Experimental results show the effectiveness of the proposed method.     

Nonlinear Decentralized Disturbance Attenuation Excitation Control for Power Systems With Nonlinear Loads Based on the Hamiltonian Theory

A novel nonlinear control scheme for disturbance attenuation of structure preserving multimachine power systems based on Hamiltonian theory is proposed in this paper. The proposed control scheme includes two steps: first, the dissipative Hamiltonian realization of structure preserving power system is completed using the singular perturbation approach in which the algebraic equations are considered as a limit of fast dynamics; second, a nonlinear decentralized disturbance attenuation excitation controller is designed without linearization to improve transient stability of power system as well as the robustness with respect to unknown exogenous disturbance in the sense of L₂-gain. Simulation on a two-area system demonstrates that the proposed scheme can enhance transient stability of the system regardless of the exogenous disturbance.     

Pressure control in a PEM fuel cell via second order sliding mode

Pressure difference inside the Polymer Electrolyte Membrane Fuel Cells (PEMFC) arises due to load variations, during which the pressure difference between anode and cathode rises. Practically, this problem can be avoided by equalizing anode and cathode pressures, to protect the fuel cell from permanent damage. This paper focuses on pressure regulation in the anode and cathode sides of the PEMFC. The control objective is achieved using second order sliding mode multi-input multi-output (MIMO) controller based on “Twisting algorithm”. Parametric uncertainty is formally presented and included in a nonlinear dynamic fuel cell model. The resultant nonlinear controller is robust and is proved to guarantee performance around any equilibrium point and under parametric uncertainty. Simulation results show that the proposed controller has a good transient response under load variations.     

Multi-loop nonlinear predictive control scheme for a simplistic hybrid energy system

A simplistic hybrid energy system is composed of the wind turbine, electrolyzer, and PEM fuel cell stack. In view of the high current demand and fast load changes, the hybrid dynamic simulation shows that the fuel cell may be in risk of oxygen starvation and overheating problems. Regarding the safe operation as well as long lifetime of the fuel cell, the effective control manner is expected to regulate both the stack temperature and oxygen excess ratio in the cathode at the desired level. Under the multi-loop nonlinear predictive control framework, the controlled output variables are specified independently by manipulating air (oxygen) and water flowrates, respectively. The dynamic modeling and control implementation are realized in the Matlab–Simulink? environment.     

Disturbance decoupling control of an ultra-high speed centrifugal compressor for the air management of fuel cell systems

This paper presents a control solution based on dynamic disturbance decoupling control (DDC) for a centrifugal compression system, which is used to supply the compressed air to the fuel cell, thereby reacting with the hydrogen to produce electricity. As a result of its ultra-high speed, this compressor has a great advantage of ultra-compactness, which makes it more suitable for transportation applications. However, unlike positive displacement compressors, the centrifugal compressor has strong coupling between mass flow and pressure, which gives rise to the difficulty of control and also limits its operating region. In this paper, a unique dynamic DDC strategy, based on the active disturbance rejection control (ADRC) framework, is developed to control the mass flow and pressure simultaneously. The experimental results show that, compared with a traditional PI controller this controller performs better in both the transient and steady states. This control system has been validated on a 10 kW fuel cell model under load variations.