Adaptive inverse control of air supply flow for proton exchange membrane fuel cell systems

To prevent the oxygen starvation and improve the system output performance, an adaptive inverse control （AIC） strategy is developed to regulate the air supply flow of a proton exchange membrane fuel cell （PEMFC） system in this paper. The PEMFC stack and the air supply system including a compressor and a supply manifold are modeled for the purpose of performance analysis and controller design. A recurrent fuzzy neural network （RFNN） is utilized to identify the inverse model of the controlled system and generates a suitable control input during the abrupt step change of external disturbances. Compared with the PI controller, numerical simulations are performed to validate the effectiveness and advantages of the proposed AIC strategy.

Modeling of Fuel Elements Cycling System in Pebble Bed Reactor Based on Timed Places Control Petri Nets

Pebble bed reactors use cycling scheme of spherical fuel elements relying on fuel elements cycling system (FECS). The structure and control logic of FECS are very complex. Each control link has strict requirements on time and sequence. This increases the difficulties of description and analysis. In this paper, timed places control Petri nets (TPCPN) is applied for the modeling of FECS. On this basis the simulation of two important processes, namely uploading fuel elements into the core for the first time and emptying the core is finished by simulation software Arena. The results show that as TPCPN is able to describe different kinds of logic relationship and has time properties and control properties, it’s very suitable for the modeling and analysis of FECS.

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.

Air flow control based on optimal oxygen excess ratio in fuel cells for vehicles

Air flow control is one of the most important control methods for maintaining the stability and reliability of a fuel cell system, which can avoid oxygen starvation or oxygen saturation. The oxygen excess ratio （OER） is often used to indicate the air flow condition. Based on a fuel cell system model for vehicles, OER performance was analyzed for different stack currents and temperatures in this paper, and the results show that the optimal OER was affected weakly by the stack temperature. In order to ensure the system working in optimal OER, a control scheme that includes an optimal OER regulator and a fuzzy control was proposed. According to the stack current, a reference value of air flow rate was obtained with the optimal OER regulator and then the air compressor motor voltage was controlled with the fuzzy controller to adjust the air flow rate provided by the air compressor. Simulation results show that the control method has good dynamic and static characteristics.

Embedded Software Control of a Hybrid Vehicle＇s ECU/FCM System

This paper describes a research project that uses embedded systems design principles to construct and simulate an Engine Control Unit （ECU） for a hybrid car. The ECU is designed to select a fuel type based on the stress level of the simulated engine. The primary goal of the project was to use a robotics kit, connected to sensors, to simulate a hybrid car under certain stress conditions such as hill climbing or full throttle. The project uses the LEGO~ Mindstorms~ NXT robotics kit combined with a Java-based firmware, a pressure sensor to simulate a gas pedal, and a tilt sensor to determine when the car is traveling uphill or downhill. The objective was to develop, through simulation, a framework for adjusting the ratios/proportions of fuel types and mixture under the stress conditions. The expected result was to establish a basis for determining the ideal/optimal fuel-mix-stress ratios on the hybrid car＇s performance. Using the NXT robotics kit abstracted the low level details of the embedded system design, which allowed a focus on the high level design details of the research. Also, using the NXJ Java-based firmware allowed the incorporation of object oriented design principles into the project. The paper outlines the evolution and the compromises made in the choice of hardware and software components, and describes the computations and methodologies used in the project.

DISOPE distributed model predictive control of cascade systems with network communication

A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.

PEMFC空气系统流量和压力协同控制策略设计

为提高质子交换膜燃料电池(PEMFC)空气系统的动态响应性能,避免局部缺气而导致其输出性能降低等问题的出现,针对空气系统存在流量和压力耦合的问题,分别采用PID、前馈解耦控制和模型预测控制(MPC)对空气系统进行控制,通过仿真和台架测试,验证控制算法的有效性。结果表明,两种控制算法相比较PID均具有较好的控制效果,空气流量和空气压力均能快速跟随设定值,PEMFC发动机的输出性能平稳。

基于LabVIEW的燃料电池控制程序设计

燃料电池作为一种新兴的高效、安全、环保的动力源,逐渐在汽车、船舶等领域得到广泛应用。然而燃料电池结构复杂、所包含元器件多,因此要求燃料电池控制系统能够全面监测运行状态并能够对运行过程进行实时控制。该文针对现有燃料电池样机,基于LabVIEW软件搭建燃料电池控制系统,完成上下位机通信程序及软件界面设计。通过仿真调试,所设计的燃料电池控制程序可实现燃料电池的全面状态监测及实时控制,满足燃料电池的控制需要。

燃料电池氢气流量控制系统变负载匹配设计与仿真

针对车载质子交换膜燃料电池供氢系统负载工况多变时的氢气流量控制问题,提出一种基于比例减压阀与流量控制阀的氢气流量负载匹配控制系统架构与方法。建立了从高压储氢瓶至燃料电池堆的供氢系统整体模型,基于该模型设计了比例减压阀、流量控制阀与氢气循环泵的控制策略,并就某一型号电堆的变负载工况对系统模型与控制策略进行仿真验证。结果表明:电堆阳极压力可快速跟踪给定压力,响应时间约2~3s;氢气流量可适应负载变化需求,其瞬时超调量与压力响应速度成正相关;稳态时氢气利用率维持在95%以上,供氢过量比维持在1.27以上,供气氮含量维持在5%以下,满足电堆性能需求。

某型航空发动机主燃油控制系统频率特性研究

为研究某型航空发动机数控系统主燃油控制系统频率特性,基于力平衡方程和流量连续方程建立元件和系统的动态数学模型。在其稳态工作点附近采用小偏离线性化建立等压差模块、主燃油计量模块、停车控制模块和整个系统的传递函数,并通过Fluent流场仿真重点研究了关键元件的稳态液动力及影响因素。在此基础上建立了主燃油控制系统的Simulink仿真模型,研究了控制系统的频率特性和关键活门固有频率。结果表明:主燃油控制系统的频率特性与实际工程经验一致,稳定裕度较高;系统的固有频率与系统中固有频率最低的元件基本一致;当元件结构确定时,稳态液动力对固有频率的影响较大。研究结果为燃油控制系统频率域优化设计提供了理论支持。

直升机发动机燃油控制机械备份的操纵特性

针对典型的采用自动控制+机械备份操纵的直升机发动机燃油控制系统,分析了不同控制模式下机械备份操纵的油门响应特性。依据发动机手册图示的燃油控制系统原理,推导了机械备份操纵的油门响应特性函数,并与试验数据进行了对比验证。机械备份操纵特性分析表明:手动控制模式下的机械备份操纵的油门响应与自动控制失效时锁定的位置相关;自动控制有效时进行的机械备份操纵是一种混合模式操纵,具有与手动控制模式不同的油门响应特性。

基于模糊控制的惰化反应器温度控制

为了抑制飞机耗氧型燃油惰化系统整体式反应器内飞温现象的发生,为提升工作效率,延长使用寿命,利用Modelica语言对整体式反应器建立双温度模型,开展动态仿真,并设计了逆流式冷却措施。根据反应器温度特性,制定了相对应的控制策略,建立模糊控制器,研究了不同工况下模糊控制器在逆流式反应器温度控制上的工作特性,以及冷却管道排布对反应通道工作效率的影响。研究结果表明:模糊控制对逆流式反应器温度控制稳定性较好,有效抑制了反应器尾部的飞温现象;相比无温控管道,单侧和双侧存在温控管道时,单根反应通道的平均反应速率分别提升了1倍和10倍,添加温度控制后,反应器整体燃油蒸气转化率从10%提升至99%。隶属函数方差σ^(2)对控制效果有明显的影响,方差σ^(2)越大,控制精度越低,响应速度越快,要根据不同进口状态选取合适的σ^(2),以获得最佳控制性能。

车用燃料电池系统控制策略综述

针对车用燃料电池系统控制策略,从系统结构、控制对象、控制目标、控制方法等方面总结了其研究现状和发展趋势。在系统结构设计方面,需要研发高性能关键部件,简化控制系统结构,降低控制难度。在控制对象方面,针对强耦合物理量的解耦控制有待深入研究。在控制目标方面,多目标优化控制策略将是未来的研究重点。在控制方法方面,复合控制策略和基于学习的智能控制策略将是未来的研究方向。

基于阴极再循环的燃料电池系统建模与动态性能分析

阴极再循环通过调节电堆进气中的氧分压和水蒸气分压特别适合解决车用燃料电池系统在低怠速工况下的缺水和高电势问题。建立了一个带阴极再循环功能的燃料电池非线性系统控制模型,使用阴极再循环泵将阴极出口的气体引回到空压机出口实现了进气加湿和氧分压调节。该模型可捕捉由阴极再循环带来的一系列动态响应。结果表明,阴极再循环可以极大地改善小电流密度下的进气湿度,随着阴极再循环比的增加,加湿动态响应加快;氧分压调节的动态响应较慢,但通过合理的阴极再循环策略仍能将小电流密度下的高电势限制在0.8V以下。通过抑制小电流密度下的电压,实现了50%的怠速功率降幅。

液冷型燃料电池热管理子系统建模与控制研究

温度是影响燃料电池系统性能的关键因素之一,利用热管理子系统实现良好的温度控制是提高燃料电池性能及寿命的重要手段。针对液冷型燃料电池热管理子系统,在分析其结构及工作原理的基础上,利用机理及经验公式建立完整的热管理系统模型,并利用该模型分析燃料电池的温度特性,仿真结果表明合适的温度能够有效提高系统性能。制定相应的控制策略实时调节冷却系统进而实现电堆温度控制,采用流量跟随的方法削弱了控制变量间的耦合作用,仿真结果表明该控制策略能够实现电堆温度的有效控制,在负载连续变化的情况下将出口温度及温差稳定在理想范围内。

基于LabVIEW的比例压力控制阀自动测试系统

根据某公司比例压力控制阀的出厂测试要求,本文设计了一套比例控制阀自动测试系统。该系统基于LabVIEW编程和PLC控制,可实现共轨管稳定的超高压供给,并自动实现比例压力控制阀的耐久测试、流量滞环测试及压力-流量测试,且操作简便,满足企业需求。

燃料电池重卡动力系统参数匹配与能量管理策略仿真分析

为提高燃料电池重卡综合性能,首先确定了其动力系统构型方案,依据整车动力性与经济性要求对驱动电机、燃料电池以及动力电池进行部件选型和参数匹配,利用AVL Cruise软件搭建了整车物理模型。制定了一种基于模糊控制方法的能量管理策略,并在MATLAB/Simulink环境下建立模糊控制能量管理策略模型。通过MATLAB DLL方式实现了能量管理策略模型与整车物理模型的联合仿真。仿真结果表明所提出的整车动力系统设计方案和能量管理策略能够满足整车动力性并有效地提高了整车的燃料经济性。

双堆燃料电池热管理系统自抗扰控制

为对双堆燃料电池热管理系统进行有效控制,基于试验数据建立了电堆模型,并耦合水泵、换热器等关键零部件模型形成完整的热管理系统模型。为保证阶跃工况下电堆温度的稳定,设计了基于比例积分与线性自抗扰算法的联合控制策略,并进行仿真验证。提出了基于前馈解耦及串级LADRC的改进控制策略,通过仿真对比改进前后的控制效果。结果表明,改进后的控制策略能有效减小超调量,反映温控精度的时间乘绝对误差积分量最高可降低66.39%。

某型汽轮燃油泵控制系统故障分析

为提升蒸汽轮机推进系统的可靠性和维护效率,以某型汽轮燃油泵控制系统为例,对系统的组成和工作原理进行分析,并对该型装备具体故障实例进行剖析。在此基础上,提出故障产生的原因和解决要点。研究成果可为汽轮燃油泵控制系统故障预防和维修提供一定参考。

基于SCADA的航空发动机HMU自动化试验系统设计与应用

航空发动机HMU是发动机燃油控制系统中的一个关键单元,主要作用是根据发动机电子控制器的输入要求对燃油增压、计量以及伺服作动,为发动机提供燃油,确保发动机发挥其最佳性能,为保证其产品在生产过程中更高效率、更高精度的试验及交付过程,需要进行智能化试验系统交付平台的设计,从而消除因人工主观因素对产品的影响,针对整个系统进行网络部署和技术架构进行研究,分别采用硬件和软件两方面进行升级配置,基于LabVIEW软件进行算法程序编辑,并创新性地将程序与SCADA系统进行通讯连接,实现自动化试验的功能,同时采用二分法自动找点的方式进行自动交付报告的生成,经实际产品应用已验证其系统设计的科学可行性,满足集中控制自动化试验及交付的目标,具有非常重大的工程意义。