PEMFC电化学建模及其PID控制

针对目前质子膜燃料电池(PEMFC)模型难以适用控制系统的设计,因此提出了电化学方法建立PEMFC数学模型,并在此基础上采用PID控制其输出电压。首先分析PEMFC内部运行机理;然后假定外部负载电流干扰的情况下,PEMFC电堆工作温度稳定在80℃,在M atlab/simu link环境下建立系统仿真模型,模拟输出电压动态变化过程;并采用PID算法控制电堆阴阳极入口气体压力,使PEMFC系统的输出电压达到预定值。仿真结果表明该模型能够较好的反映出系统的动态特性,且PID算法用于PEMFC发电系统的控制是可行的。     

质子交换膜燃料电池风机控制技术研究

该文首先研究了质子交换膜燃料电池(PEMFC)风机的性能,分析了PEMFC的工作温度对其性能的影响,并给出了控制PEMFC风机的数学模型。然后,对高电压、大电流运算放大器OPA548进行了详细的介绍,设计了用OPA548控制PEMFC风机工作电压的硬件电路,最后,对使用OPA548时应注意的事项进行了讨论。     

开放式阴极PEMFC动态水管理的研究分析

质子交换膜燃料电池(PEMFC)正在赢得越来越多的关注,广泛地在汽车、固定基站及便携式等应用作为能量转换装置。然而,需要深入了解燃料电池的系统动力学以达到更好的性能。在PEMFC中,了解水的传输和热的管理至关重要,本文基于阴极开放式自增湿的PEMFC系统,在已有的控制机制中深入地研究PEMFC电池电解质膜中水的管理及对性能的影响。     

质子交换膜燃料电池的神经网络建模与控制

该文从设计质子交换膜燃料电池（PEMFC）控制方案的角度出发,首先提出了采用Elman动态神经网络对PEMFC系统进行建模的新方法,以实验中采样到的PEMFC系统的工作温度输入输出数据训练网络,并采用动态反向传播学习算法根据误差不断调整网络参数直至达到要求精度;Elman神经网络辨识可使辨识过程简化并提高了辨识精度。然后在此基础上设计了自适应模糊神经网络控制器。最后的仿真实验以Elman神经网络模型为参考模型,使用自适应神经网络控制算法控制PEMFC的工作温度,取得了较好的控制效果。结果显示所设计的控制系统适合于控制PEMFC这样一类复杂非线性系统。     

质子交换膜燃料电池动态建模及其双模控制

由于已提出的质子交换膜燃料电池(PEMFC)模型难于控制, 提出利用MATLAB/SIMULINK仿真工具进行PEMFC系统动态建模, 同时为实现对PEMFC系统输出电压的控制, 采用了基于模糊规则切换的模糊逻辑控制器(FLC)和比例积分微分控制器(PID)相结合的双模控制方式. 仿真结果证明该动态模型易于控制, 能够反映出PEMFC系统的动态输出特性, 而且验证了基于模糊规则切换的双模控制能够有效抑制扰动, 改善PEMFC系统的动态输出特性, 保证系统的稳定运行, 有助于对PEMFC系统的输出性能分析以及实时控制系统的设计.     

质子交换膜燃料电池建模与动态仿真

对质子交换膜燃料电池（PEMFC）电堆进行电输出特性研究,有助于改善燃料电池的设计,提高其性能。运用MATLAB的Simulink仿真工具对PEMFC建立仿真模型,通过所建立的电堆参数模型,就能够研究主要运行参变量对电堆动态输出性能和电堆非线性内阻产生的影响。当电堆输出电流出现阶跃变化时,对电堆电压,输出功率,消耗功率,电堆效率,非线性内阻的动态响应,进行了仿真和结果分析。仿真结果符合文献[7]实验数据,表明此参数模型是可操作和有效的,并可方便地用于PEMFC控制方法研究。     

质子交换膜燃料电池自校正控制模型研究

质子交换膜燃料电池(PEMFC)是2l世纪最有生命力的发电技术之一。该论文从PEMFC实际应用的角度出发，应用改进遗传算法、神经网络技术，建立了一个PEMFC自校正控制模型，并在仿真和实验中取得了比较满意的控制效果。     

质子交换膜燃料电池的连续模型预测控制器的设计

在对质子交换膜燃料电池(PEMFC)的工作原理进行研究分析的基础上,对其进行了数学描述,在Matlab/Simulink仿真平台下建立了质子膜燃料电池的动态仿真模型。维持PEMFC系统的正常运行需要良好的控制系统。通过将拉盖尔函数应用到连续模型预测控制(CMPC)算法中去,分析了CMPC的不足之处并通过指数权值函数进行了简单的修正,随后将两种控制策略与传统的离散预测控制(DMPC)施加到PEMFC系统中去并进行了仿真对比分析,仿真结果证明了CMPC算法的有效性以及优越性。     

PEMFC的模糊辨识和非线性预测控制

质子交换膜燃料电池(PEMFC)是21世纪最有前景的发电技术之一。该文针对PEMFC等一类具有严重非线性的复杂被控对象,提出一种基于模糊模型的非线性预测控制算法对PEMFC系统进行建模与控制。在建模与控制过程中,采用模糊聚类和线性辨识方法在线建立PEMFC控制系统的T-S模糊预测模型,然后基于分支定界法的基本原理对控制量进行离散寻优,从而实现PEMFC的非线性预测控制。仿真和实验结果证明了该算法的有效性和优越性。     

PEMFC的PSO优化LS-SVM动态建模仿真

质子交换膜燃料电池(PEMFC)作为一种电化学反应装置,湿度管理对于它的运行性能十分关键.为了建立相应的动态模型,采用了最小二乘支撑向量机(LS-SVM)算法,并使用微粒群算法(PSO)对LS-SVM模型参数进行了自动优化.这种方法建立的动态数学模型能够以进气湿度和工作电压为输入量预测输出的电流密度.仿真结果显示,模型的预测值和实验数据间的平均平方相对误差小于0.0001,能够达到很好的预测精度.因此,这种优化建模策略可以有效的应用到PEMFC研究中.     

PEMFC发电系统的自适应模糊控制与动态分析

监测和控制燃料电池的过程中,需要获得各种实时数据.质子交换膜燃料电池(PEMFC)发电系统中的参数强耦合、高度非线性特性增加了对其控制的难度,传统的PI控制虽然对模型精确的系统有较好的控制效果,但对于参数波动的系统则无法获得较高的控制性能.针对以上情况,基于PEMFC发电系统的动态仿真模型,根据重整器在燃料电池发电系统中的作用,设计了自适应模糊控制器.利用模糊控制规则在线控制氢气摩尔流,从而控制PEMFC发电系统的输出功率.仿真结果表明,该动态模型能够预测输出电压.响应曲线显示出自适应模糊控制算法能够较好控制燃料电池有功和无功功率的输出.模型具有良好的负载跟踪特性.     

水冷型PEMFC温湿度建模与智能控制

当负载电流一定时,质子交换膜燃料电池(PEMFC)的工作温度和质子膜的相对湿度是影响电池输出性能的主要因素.分析电池电流密度与最优工作温湿度的关系,建立基于温湿度耦合模型的最优温湿度操作条件的电压模型.通过对冷却水流量和阴阳极气体加湿度进行综合控制,保持电堆的工作温湿度在最佳状态,不仅保证了电池最优的输出性能,还可以延...     

Parameter derivation of a proton exchange membrane fuel cell based on coevolutionary ribonucleic acid genetic algorithm

Precise modeling of a polymer electrolyte membrane fuel cell (PEMFC) is a crucial issue in analyzing and controlling electrical energy production. In this paper, a novel semiexperimental model is proposed for forecasting of PEMFC output voltage. As well, the coevolution ribonucleic acid genetic algorithm (coRNA‐GA) is presented as a novel estimation approach for determination of proposed model coefficients. This optimization method is motivated by the biological RNA, encodes the chromosomes by RNA nucleotide basics, and accepts a few RNA operations. This paper proposed several genetic operators to preserve the diversity of particles, and two sets from particles are chosen using various validation functions. In these two subpopulations, different evolutionary methods have been employed for balancing of seeking and extraction. Input pressure of cathode is chosen in this paper as a further parameter for modifying the depiction of concentration overvoltage (V_con ) in the case of conventional Amphlett's PEMFC system. Finally, the performance of the coRNA‐GA algorithm, as well as the precision of the obtained model, is authenticated via empirical results. Also, the obtained results are compared with some other methods, and the superiority of the proposed model is demonstrated in voltage prediction accuracy.     

Nonlinear time-variant model of the PEM type fuel cell for automotive applications

This paper deals with nonlinear dynamic modeling of the Proton Exchange Membrane Fuel Cell (PEMFC) dedicated for automotive applications. A time-variant state space model taking into account most of internal phenomena is built. Based on electrical and diffusion approaches, the model proposes a more complete equivalent circuit including all cell components. The proposed circuit couple between gas diffusion, membrane water content, temperature, activation, ohmic and concentration losses, as well as double layer and geometrical capacitances. Similarly to engine vehicles, the model consider the hydrogen flow rate as input controlled by the pilot to change vehicle’s speed. Urban and highway driving cycles similar to those of Nissan LEAF are simulated. Simulation results show that the model responds to both low and high dynamics of power demand. Results reveal that membrane humidity has a considerable effect on the cell’s efficiency. This offer the opportunity to use the model, in a future work, to improve the fuel cell’s efficiency through the control of humidity. The model is validated by experimental tests on a 50 W PEMFC.     

燃料电池的模糊控制

在所有类型的燃料电池中,质子交换膜燃料电池因具有重量轻,效率高、电流密度大、工作温度低、启动速度快以及使用无毒性的固态电解质膜等优点近年来发展最快。针对这种燃料电池提出了一种模糊控制算法,改善了燃料电池的输出性能。有实验结果证明所提出算法的有效性。     

Experimental results applying second order sliding mode control to a PEM fuel cell based system

A robust control solution is proposed to solve the air supply control problem in autonomous polymer electrolyte membrane fuel cells (PEMFC) based systems. A Super Twisting controller is designed using a nonlinear model of a laboratory fuel cell test station, even a Lyapunov based stability discussion is included. Subsequently, the proposed control strategy is successfully implemented in the laboratory test bench. Highly satisfactory results are obtained, regarding dynamic behaviour, oxygen stoichiometry regulation and robustness against uncertainty.     

Real‐time thermal Management of Open‐Cathode PEMFC system based on maximum efficiency control strategy

Improving the efficiency of the proton exchange membrane fuel cell (PEMFC) system is the main problem should be solved for the commercialization of PEMFC. In this paper, the efficiency characteristic of PEMFC system under load and stack temperature variation is analyzed through theoretical modeling and experimental verification. For high efficiency operation of PEMFC system, the maximum efficiency control strategy (MECS) is proposed for thermal management of PEMFC system. According to the efficiency characteristics of PEMFC system, the optimal efficiency trajectory of system is obtained under maximum efficiency optimization (MEO). As PEMFC system is a nonlinear system with the characteristics of time‐variation, and uncertainty, a constrained generalized predictive control (CGPC) is proposed to realize real‐time optimal efficiency trajectory tracking. The MECS based on MEO and CGPC is implemented on‐line, experimentally validated on the established H‐300 open‐cathode PEMFC system. The experimental result shows better tracking ability compared with PID control and testifies the validity of MECS for increasing the system efficiency. Therefore, the proposed MECS can provide better system dynamic response and higher system efficiency.