Intelligent control for improvements in PEM fuel cell flow performance

The performance of fuel cells and the vehicle applications they are embedded into depends on a delicate balance of the correct temperature, humidity, reactant pressure, purity and flow rate. This paper successfully investigates the problem related to flow control with implementation on a single cell membrane electrode assembly （MEA）. This paper presents a systematic approach for performing system identification using recursive least squares identification to account for the non-linear parameters of the fuel cell. Then, it presents a fuzzy controller with a simplified rule base validated against real time results with the existing flow controller which calculates the flow required from the stoichiometry value.     

基于变论域模糊增量理论的质子交换膜燃料电池温度控制

质子交换膜燃料电池(PEMFC)内部的电化学反应过程直接表现为温度的变化,所以有效的温度控制是保证燃料电池可靠性和耐久性的关键.本文将模糊增量控制用于PEMFC热管理系统中,将PEMFC的温度和电堆出入口温度差保持在设定值.首先,建立PEMFC热管理系统的动态模型,包括PEMFC电堆模型和辅助散热设备模型.然后,基于建立的系统模型,设计了一种变论域的模糊增量控制器.该控制器通过伸缩因子来动态调节模糊控制器中的量化因子和比例因子,实现对模糊论域的调节,从而提高控制的灵敏性和精确度.最后,将该温度控制方法用于10 kW燃料电池系统中,实验结果表明变论域模糊增量控制器相比于其他模糊控制方法,不仅具有更快的动态响应速度,还具有更强的鲁棒性和更高的控制精度.     

Real-time implementation of a sliding mode controller for air supply on a PEM fuel cell

This paper presents a control approach to the air feed of a fuel cell based on a single input single output sliding mode control. Fuel cells are electrochemical devices that generate electrical energy from chemical reactants and are good candidates for clean energy generation, since the waste product is water. An efficient operation of fuel cells depends on a good control strategy for the air supply system. The controller obtains its nonlinear behaviour through a variable structure strategy, whose tuning is proposed by making use of a low-order linear model of the process. This structure allows the real-time implementation of a robust control law that is able to deal with the nonlinearities and uncertainties without the need of heavy computation load for the controller algorithm, while allowing a fast sampling rate according to the needs of these power systems. The performance of the control scheme proposed is successfully evaluated on a medium-size PEM cell fuel.     

Modeling and control of a PEM fuel cell system: A practical study based on experimental defined component behavior

In this contribution, the dynamical behavior of a polymer electrolyte membrane (PEM) fuel cell system is modeled; related control approaches are developed. The system model used for experimental and modeling purposes describes a 1.2 kW PEM fuel cell stack and an air blower. Due to the dynamical fuel cell–blower interaction the fuel cell stack and the blower model are validated to real systems respectively. Additionally, a feedback based on PI-control is used for hydrogen pressure control with an anode inlet valve. This controller is able to eliminate a stationary error between the anode and cathode pressures. For principal investigations three control approaches, a classical static feed-forward control approach, a state-space feedback control, and a novel gain-scheduling approach are developed, applied, and compared. As result, it can be shown that the feed-forward approach lacks in performance recovering the excess oxygen ratio to the desired level. The state-space feedback control shows stationary error. The introduced gain-scheduling control approach leads to a fast excess oxygen ratio recovery without stationary deviations.     

Output Tracking Control of a Hydrogen-air PEM Fuel Cell

Hydrogen-air proton exchange membrane (PEM) fuel cell is a promising clean energy. However, the stack output tracking control is still a challenging problem due to the soft characteristic of the stack. Both over-and less-control will cause the stack flooding or oxygen lacking which dramatically decreases the life of stacks. Traditional control methods rely on the accurate model of the fuel cell system, which is a high-order nonlinear system, and involve a complex controller design process. This paper combines the data-based fuzzy cluster modeling technology with the sliding mode control and the integral actions. The sliding mode controller tracks the dynamic changes of the fuel cell system and the integral controller eliminates the steady-state errors. Simulation results demonstrate good performance of the proposed control method.      

Passivity based control of a distributed PEM fuel cell model

This work considers the controlled load change of proton exchange membrane (PEM) fuel cells. Due to the intrinsic nonlinearities of fuel cells, load changes are quite challenging. In the case of a low temperature PEM fuel cell, there is the possibility of undesired liquid water formation. Most available control concepts are heuristic linear controller structures based on a perfectly mixed fuel cell model. In this work a nonlinear controller for one-dimensional spatially distributed model of a PEM fuel cell is presented. The fuel cell model is derived from first principles. The concept of passivity is used to design the controller. A suitable control Lyapunov function is chosen and passivity of the fuel cell is shown. A state-feedback law is derived that can guarantee stability of the closed-loop system over a wide range of operation conditions. In order to make the feedback law applicable to fuel cells with limited measurement information an observer is designed. In a final step the state-feedback law and the observer are combined to an output-feedback controller.     

Hybrid modelling and control of the common rail injection system

We present an industrial case study in automotive control of significant complexity: the new common-rail fuel-injection system for Diesel engines under development at Magneti Marelli Powertrain. In this system, an inlet metering valve, inserted before the high pressure (HP) pump, regulates the fuel flow that supplies the common rail according to the engine operating point (e.g., engine speed and desired torque). The standard approach in automotive control based on a mean-value model for the plant does not provide a satisfactory solution as the discrete-continuous interactions in the fuel injection system, due to the slow time-varying frequency of the HP pump cycles and the fast sampling frequency of sensing and actuation, play a fundamental role. We present a design approach based on a hybrid model of the Magneti Marelli Powertrain common-rail fuel-injection system for four-cylinder multi-jet engines and a hybrid approach to the design of a rail pressure controller. The hybrid controller performs significantly better when compared with the classical mean-value based approach.     

柴油机油量执行器的干扰估计滑模控制方法

油量执行器是电控分配泵的核心部件之一,其直接控制着柴油发动机的燃油喷射量.模型非线性与外部扰动是油量执行器系统中不可避免的影响因素,前期的许多研究忽略了这些非线性,使得闭环系统性能并不理想.本文考虑了旋转电磁铁和复位弹簧等非线性特性的建模,得到了油量执行器系统的数学模型.进而,在基于模型对系统非线性进行抵消之后引入扩张状态观测器对系统外部干扰和不确定性进行估计,设计了基于扩张状态观测器的滑模控制律.该控制律在保证鲁棒性的同时,可以使得切换增益幅值更小,有利于减小滑模控制的抖振问题.最后,通过MATLAB/Simulink仿真和dSPACE平台实验验证了所提方法的可行性和有效性.     

闪速熔炼气流干燥优化控制系统的设计与实现

针对气流干燥过程水分难以稳定的问题，设计了一个由水分软测量模型和氮气专家控制器组成的双反馈控制系统．通过智能协调得到软测量的输出，结合约束条件，采用遗传算法搜索燃油量的最优值；由氮气专家控制器来调节氮气量，从而改变回转窑窑头含氧率，使精矿不着火．通过这两个反馈调节，使得耗氮量和燃油量同时达到最小．工业数据验证表明，累计平均耗氮量和燃油量分别下降了1.4%和0.3%．     

基于模糊逻辑与遗传算法的燃料电池热管理方法研究

有效的质子交换膜燃料电池(Proton Exchange Membrane Fuel Cell,PEMFC)热管理是提升氢燃料电池汽车安全性、耐久性以及运行效率的关键因素之一.该文提出一种PEMFC电堆热管理控制方法,使电堆出入口温度保持在设定值.该方法以PEMFC热管理系统模型中电堆出入口温度的变化为依据,设计一种二...     

级联触发策略下非结构化道路的自主卡车队列控制

本文针对非结构化道路上自主卡车队列系统的控制问题进行研究, 设计一种基于级联触发的控制器,有效提高复杂工况下的卡车队列系统性能. 首先, 建立不依赖于道路结构的纵–横耦合卡车队列系统模型, 该模型涉及复杂环境下车辆存在故障(包括执行器、传感器的失效故障以及随机网络故障)影响. 其次, 为降低燃油消耗, 设计了基于自触发和事件触发的级联触发控制器, 并利用李雅普诺夫方法证明了系统的闭环稳定性. 此外, 通过对系统Zeno行为的分析量化, 得到了触发时间间隔的下界值, 保证了算法的实际应用性. 本文为了实现卡车系统队列稳定性控制目标, 进一步给出了控制器设计限制条件. 最后, 仿真结果表明, 所提出的控制方法不但能保证单车渐近稳定以及队列稳定, 还能有效减少执行器更新频率, 提高燃油经济性.     

Energy-efficient operation of diesel–electric locomotives using ahead path data

Diesel–electric locomotives have significant fuel consumption. In this study, fuzzy look-ahead control is considered as an online approach for fuel consumption optimization. A fuzzy controller will modify the desired speed profile by accounting for the gradient and speed limits of the path ahead. Journey time increment is used as an optimization constraint. The existing models for train motion simulation are calculating the fuel consumption by an indirect index. A new model for train-movement simulation is proposed to calculate fuel consumption more accurately. This model considers the locomotive subsystems and satisfies the experimental fuel consumption data specified in the locomotive's catalog. Simulation of a train with a GM Sd40-2 on three local tracks showed considerable reduction in fuel consumption along with an acceptable journey time increment. Simulation results also showed that fuzzy look-ahead controller has very faster calculations in comparison with the controller based on the dynamic programming method.     

Control and real-time optimization of an automotive hybrid fuel cell power system

A real-time optimization method is used to find the point of maximum fuel efficiency of a hybrid fuel cell power system, in an automotive application. The controller performs as the master control in cascade with lower level controls. The lower level controls distribute the power between the ultra-capacitor and the fuel cell, during transients, to find the optimum operating point of the power system. The ultra-capacitor is used to protect fuel cell health and improve phase characteristics of the system. In simulations, the controller is able to find the optimum operating point for the hybrid system without requiring previous knowledge of the system dynamics or explicit representation of the optimization function.     

一类不确定系统的鲁棒可靠跟踪控制及其在飞行控制中的应用

针对多面体不确定系统,基于参数相关Lyapunov函数的方法,研究了考虑执行器故障的可靠跟踪控制器的设计问题．利用描述系统方法,得到可靠跟踪控制器存在的充分条件．状态反馈可靠跟踪控制器设计方法可以归结为求解一族线性矩阵不等式(LMIs)．通过飞行控制系统的实例仿真验证了文中提出的设计方法的可行性．     

A decoupled controller for fuel cell hybrid electric power split

The power management of a hybrid system composed of a fuel cell, a battery and a DC/DC power converter is developed. A decoupled control strategy is proposed, aimed at balancing the power flow between the stack and the battery and avoiding electrochemical damage due to low oxygen concentration in the fuel cell cathode. The controller is composed of two components. The first controller regulates the compressor, and as consequence the oxygen supplied to the cathode, via a classic proportional–integral controller. The second controller optimally manages the current demanded by the fuel cell and battery via linear-quadratic control strategy acting on the converter. The closed-loop performance has been tested both in simulation and in real-time simulation using a microprocessor for the controller.     

A method for carbon oxide concentration evaluation in high-temperature combustion processes

A method for evaluating carbon oxide concentration in high-temperature combustion processes is presented. The paper offers an optimizing control problem for fuel combustion process using a stabilizing regulatory controller, which affects the fuel/air ratio with respect to carbon oxide concentration in the firebox. In this connection, an approach is offered to solving this problem subject to the correction factor compensating for the error of carbon oxide concentration measurement.     

100W质子膜燃料电池应急供电系统

提出一种基于质子膜燃料电池(PEMFC)和锂电池的混合联供的应急供电系统。该系统由PEM燃料电池电堆、锂电池、控制系统、氢气储存及管路系统组成,控制系统利用模糊控制算法将锂电池的SOC、负载大小以及燃料经济性及PEMFC的最佳状态作为输入变量,将锂电池和燃料电池的输出功率配比作为输出,使应急供电系统的输出各部件工作于最佳状态。研制了样机,并应用于野外应急情况。实际测试和应用表明,系统各项指标满足战术技术要求,是抢险救灾应付突发事件的理想应急供电装备。     

A measurement-based approach for designing reduced-order controllers with guaranteed bounded error

The objective of this paper is to present a measurement-based control-design approach for single-input single-output linear systems with guaranteed bounded error. A wide range of control-design approaches available in the literature are based on parametric models. These models can be obtained analytically using physical laws or via system identification using a set of measured data. However, due to the complex properties of real systems, an identified model is only an approximation of the plant based on simplifying assumptions. Thus, the controller designed based on a simplified model can seriously degrade the closed-loop performance of the system. In this paper, an alternative approach is proposed to develop fixed-order controllers based on measured data without the need for model identification. The proposed control technique is based on computing a suitable set of fixed-order controller parameters for which the closed-loop frequency response fits a desired frequency response that meets the desired closed-loop performance specifications. The control-design problem is formulated as a nonlinear programming problem using the concept of bounded error. The main advantages of our proposed approach are: (1) it guarantees that the error between the computed and the desired frequency responses is less than a small value; (2) the difficulty of finding the globally optimal solution in the error minimisation problem is avoided; (3) the controller can be designed without the use of any analytical model to avoid errors associated with the identification process; and (4) low-order controllers can be designed by selecting a fixed low-order controller structure. To experimentally validate and illustrate the efficacy of the proposed approach, proportional-integral measurement-based controllers are designed for a DC (direct current) servomotor.