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.     

A new sliding mode position controller with adaptive load torqueestimator for an induction motor

A new sliding mode control algorithm with an adaptive load torque estimator is presented to control the position of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer in the rotor reference frame and the feedback linearization theory is used to decouple the rotor position and the rotor flux amplitude. Then, a new sliding mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with the classical sliding mode position controller can be eliminated. Stability analysis is carried out using the Lyapunov stability theorem. Experimental results are presented to confirm the characteristics of the proposed approach. The good position tracking and load regulating responses can be obtained by the proposed position controller     

Study on the control strategy for a boost converter used in hybrid energy storage system of electric vehicles

升压型直流变换器采用滑模变结构控制策略存在收敛速度较慢、抖振剧烈等导致的动态响应品质差问题。本文提出一种双幂次滑模趋近滞环控制策略,在电流跟踪误差估计值的基础上定义滑模面以实现电流跟踪控制,依据系统的未知扰动和负载变化建立自适应状态观测器,结合李雅普诺夫函数设计自适应律,并计算自适应占空比。提出一种双幂次趋近律,根据系统不同趋近过程的特点制定参数选择标准,对系统的动态响应品质进行目的性调节,并设计滑模滞环控制器以削弱由符号函数项所引起的抖振。对以上方法进行了仿真验证,结果显示可有效改善系统的动态特性和电流控制鲁棒性。     

Oxygen excess ratio control of PEM fuel cells using observer-based nonlinear triple-step controller

This paper proposes a novel observer-based nonlinear triple-step controller for the air supply system of polymer electrolyte membrane (PEM) fuel cell. The control objective is adjusting the oxygen excess ratio to its reference value under fast current transitions, so as to avoid the oxygen starvation and obtain the maximum net power. Considering that the cathode pressure cannot be measured directly, we design a disturbance observer to estimate the cathode pressure based on the developed third-order nonlinear model of air supply system. Next, a triple-step nonlinear method is applied to derive an oxygen excess ratio tracking controller, wherein the stability of closed-loop system is guaranteed by Lyapunov-based technique. Subsequently, several key issues of controller in practical implementation are explained, and then the robustness analysis against the considered lumped disturbance is carried out. Finally, the performance of the proposed control scheme is validated through a series of comparative simulations, and the simulation results demonstrate the effectiveness and robustness of the proposed approach under different load variations and parameter uncertainties.     

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。     

Improving the PEMFC energy efficiency by optimizing the fueling rates based on extremum seeking algorithm

In this paper, the energy efficiency of the Proton Exchange Membrane Fuel Cell (PEMFC) systems based on the fueling rates is systematically investigated. The PEMFC system under dynamic load must be operated close to the Maximum Efficiency Point (MEP) to obtain the highest energy efficiency. This is a difficult task because the MEP is dependent on the PEMFC parameters and the control PEMFC variables, besides the load profile. Thus, the MEP must be tracked dynamically with a safe search speed and funded accurately during the stationary regimes. Consequently, a real-time control is recommended to be used. The Extremum Seeking (ES) control scheme is proposed here to evaluate the FC net power at the MEP under different fueling rates and load profiles. Some interesting conclusions are obtained based on the comparative method proposed using as reference a base control technique or a PEMFC stack: 1) the MEP is different based on the control of the fuel or air flow rate; 2) the energy efficiency increases if both fueling flow rates are controlled; 3) the energy efficiency is less sensitive to power losses if the MEP is tracked by the ES controller based on air flow rate; 4) the strategy of load following control considering the fuel flow rate as an input variable is recommended based on the observation that the MEP is more sensitive to this in comparison to the air flow rate; 5) the design of an appropriate MEP tracking controller should equally focus on safe operation and the increase of the performances such as the search speed and tracking accuracy under dynamic load. All these remarks are based on an extensive numerical simulation, which are highlighted in this paper by the main results shown.     

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.     

Experimental analysis of optimal performance for a 5 kW PEMFC system

This paper investigates the issue of performance optimization for proton exchange membrane fuel cell (PEMFC) system. In PEMFC system, the system efficiency is the key parameters to evaluate the system performance which is sensitive to the air flow rate. Thus, the careful selection of the air flow rate is crucial to ensure efficient, reliable and durable operation of the PEMFC system. In this paper, the dynamic response of the system under variable air flow rate is studied in detail by means of experiments on the built 5 kW PEMFC system with 110 cells and a catalyst active area of 250 cm². The oxygen excess ratio (OER) is defined to indicate the state of oxygen supply. The experimental results show that the maximum efficiency is existed under certain net current. The OER conditions have the optimal characteristic for system efficiency. Through the optimization of system performance, the system efficiency can be increased by 12.2% on average. At the same time, the system dynamic characteristic under oxygen starvation and oxygen saturation are analyzed in detail based on the experimental data.     

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.     

基于自适应非奇异智能终端滑模观测器的风力机载荷增广预测控制

为有效降低风力机在高风速运行时的不平衡载荷,提出一种基于自适应非奇异智能终端滑模观测器的载荷增广预测控制策略。首先,针对模型不匹配导致的模型预测控制性能下降的问题,将指令跟踪误差与系统状态的变化量增广为状态向量,设计增广预测模型以消除稳态跟踪误差;其次,设计自适应非奇异终端滑模观测器对系统状态进行估计,以提高控制系统的可靠性;然后,设计多目标变速灰狼优化算法同时对控制器和观测器参数寻优;最后,基于Simulink仿真平台验证了所提控制策略的有效性。结果表明,所提控制策略可有效消除稳态误差,缩短调节时间并提高控制性能。     

Weighted fusion control for proton exchange membrane fuel cell system

Oxygen excess ratio (OER) is closely correlated with the power generation efficiency and dynamic performance of proton exchange membrane fuel cell (PEMFC) system. As OER changes with varying load, it is prone to oxygen starvation and slow response to OER reference value, and great challenges to OER control technology are brought. To this end, a dual closed-loop weighted fusion control for PEMFC system is proposed. The outer loop is utilized to obtain the optimal OER reference value, and the inner loop is utilized to track the OER reference value. This inner loop combines the merits of active disturbance rejection control (ADRC) algorithm and fuzzy self-tuned PID (FSTPID) method. Simulation results reveal that the proposed approach is superior to the other three methods in reducing the overshoot, settling time and avoiding oxygen starvation issues, and also in improving several key performance indices, such as integrated absolute error, settling time, etc.     

永磁直驱风力发电机自抗扰技术及其无位置传感器控制策略

针对永磁直驱风力发电机传统矢量控制动态性能差,抗扰动能力弱的问题,提出一种双环线性自抗扰控制系统。在此基础上针对传统滑模观测器抖振等因素造成的速度和位置角观测误差较大的问题,提出改进型自适应滑模观测器。结果表明所设计的速度和电流双环线性自抗扰控制策略能有效提高转速跟踪性能和电流波形质量;在滑模观测器的基础上结合自适应算法精确观测反电动势,借鉴锁相环原理代替反正切函数估算出转子转速和位置角,相比传统滑模观测器具有更高的估算精度。     

Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

This paper proposes a design of control and estimation strategy for induction motor based on the variable structure approach. It describes a coupling of sliding mode direct torque control (DTC) with sliding mode flux and speed observer. This algorithm uses direct torque control basics and the sliding mode approach. A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC drawbacks and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple level. The sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation (SVM) inverter. The second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.     

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.     

Control of PEM fuel cell power system using sliding mode and super-twisting algorithms

Traditional sliding mode controller applied to a DC/DC boost converter for the improvement and optimization of the proton exchange membrane fuel cell (PEMFC) system efficiency, has the drawback of chattering phenomenon. Thus, based on the analysis of the mathematical model of PEMFC, this paper addresses the second order super twisting algorithm (STA) as a solution of chattering reduction, Stability of the closed loop system is analytically proved using Lyapunov approach for the proposed controller. The model and the controllers are implemented in the MATLAB and SIMULINK environment. A comparison of results indicates that the suggested approach has considerable advantages compared to the classical sliding mode control.     

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.     

A novel robust adaptive sliding mode control using stochastic gradient descent for PEMFC power system

This study represents a comparison of novel robust adaptive sliding mode control using stochastic gradient descent (ASMCSGD) versus the super twisting algorithm (STA) for the proton exchange membrane fuel cell (PEMFC) power system. PEMFC has been constantly encountered with external disturbances such as inlet gas pressures and temperature fluctuations which a novel adaptive control law should be designed to be robust against the mentioned perturbations. The proposed ASMCSGD is based on the conventional sliding mode control (SMC), which guarantees robustness and restraining external disturbances. As is common, the main drawback of conventional SMC is the generation of a chattering phenomenon. Therefore, by using the stochastic gradient descent (SGD), a novel adaptive control law is designed. Hence, the SGD can continuously calculate the adaptive gain and then guarantee robustness besides minimizing the chattering phenomenon. The stability of the PEMFC power system for both controllers ASMCSGD and STA is demonstrated via the Lyapunov theorem. Simulation results have been studied and illustrate the effectiveness of the proposed controller successfully using Matlab/Simulink.     

Real-time AC voltage control and power-following of a combined proton exchange membrane fuel cell,and ultracapacitor bank with nonlinear loads

The nonlinear loads create a wide range of current harmonics in the system. Such loads can make distortions on the output voltage profile, influence on the fuel cell (FC) performance, and endanger safe operation of the FC unit. In this paper, new strategies for power-following and AC voltage control have been developed. The proposed system consists of the ultracapacitor (UC) bank and proton exchange membrane fuel cell (PEMFC) supplying nonlinear AC loads. The power tracking strategy is based on the Fourier analysis of total load demand. The Fourier analysis is used as an effective tool to eliminate destructive effect of current harmonics on the PEMFC output current. To supply the nonlinear AC loads under sinusoidal voltage with the fast response, a dynamic model for the inverter control loop is also presented. This model is used to enhance the input reference tracking and reject input/output disturbances. The simulation outcomes confirm the desirable PEMFC performance against nonlinear load disturbances. In addition, the output AC voltage is kept sinusoidal and has low deviations under nonlinear load variations.     

Passivity-based sliding mode position control for induction motor drives

In this paper, a passivity-based sliding-mode controller is proposed to control the motion of an induction motor. At first, the induction motor is proved to be a state strictly passive system. Then, a sliding-mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with a classical sliding-mode position controller can be eliminated. The stability analysis of the overall position control system is carried out by the passivity theory. The proposed approach is robust with regard to variations of motor mechanical parameters and load torque disturbances. Finally, experimental results are included to demonstrate that good position tracking can be obtained without the rotor flux observer.     

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.