Control design is important for PEMFC （proton exchange membrane fuel cell） distributed power generator to satisfy user requirement for safe and stable operation. For a complex multi-variable dynamic system, a dynami...Control design is important for PEMFC （proton exchange membrane fuel cell） distributed power generator to satisfy user requirement for safe and stable operation. For a complex multi-variable dynamic system, a dynamic simulation model is first established. In view of close coupling and non-linear relationships between variables, the intelligent auto-adapted PI decoupling control method is used. From the simulation results it is found that, by bringing quadratic performance index in the single neuron, constructing adaptive PI controller, and adjusting gas flow rates through the second pressure relief valve and air compressor coordinately, both anode and cathode pressures can be maintained at ideal levels.展开更多
Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidificat...Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.展开更多
Control design is important for proton exchange membrane fuel cell (PEMFC) generator. This work researched the anode system of a 60-kW PEMFC generator. Both anode pressure and humidity must be maintained at ideal leve...Control design is important for proton exchange membrane fuel cell (PEMFC) generator. This work researched the anode system of a 60-kW PEMFC generator. Both anode pressure and humidity must be maintained at ideal levels during steady operation. In view of characteristics and requirements of the system, a hybrid intelligent PID controller is designed specifically based on dynamic simulation. A single neuron PI controller is used for anode humidity by adjusting the water injection to the hydrogen cell. Another incremental PID controller, based on the diagonal recurrent neural network (DRNN) dynamic identification, is used to control anode pressure to be more stable and exact by adjusting the hydrogen flow rate. This control strategy can avoid the coupling problem of the PEMFC and achieve a more adaptive ability. Simulation results showed that the control strategy can maintain both anode humidity and pressure at ideal levels regardless of variable load, nonlinear dynamic and coupling characteristics of the system. This work will give some guides for further control design and applications of the total PEMFC generator.展开更多
Operating temperature of proton exchange membrane fuel cell stack should be controlled within a special range. The input-output data and operating experiences were used to establish a PEMFC stack model and operating t...Operating temperature of proton exchange membrane fuel cell stack should be controlled within a special range. The input-output data and operating experiences were used to establish a PEMFC stack model and operating temperature control system. A nonlinear predictive control algorithm based on fuzzy model was presented for a family of complex system with severe nonlinearity such as PEMFC. Based on the obtained fuzzy model, a discrete optimization of the control action was carried out according to the principle of Branch and Bound method. The test results demonstrate the effectiveness and advantage of this approach.展开更多
近年来,质子交换膜燃料电池(PEMFC)作为车载燃料电池的主要动力源受到广泛关注。空气压缩机为电堆提供系统所需的氧气和阴极压力,是质子交换膜燃料电池系统中必不可少的一部分,其工作性能对燃料电池稳态和动态工作性能有很大的影响。基...近年来,质子交换膜燃料电池(PEMFC)作为车载燃料电池的主要动力源受到广泛关注。空气压缩机为电堆提供系统所需的氧气和阴极压力,是质子交换膜燃料电池系统中必不可少的一部分,其工作性能对燃料电池稳态和动态工作性能有很大的影响。基于实验室已有150 k W质子交换膜燃料电池系统,对离心式空压机的工作特性进行了研究,建立了包含离心式空气压缩机的空气供给系统应用模型。通过实验验证,仿真模型能够准确地反映离心式空压机与空气系统的特性,同时能真实反映包含离心式空压机的大功率质子交换膜燃料电池空气系统的稳态控制效果,以及不同控制策略下的动态响应效果。该模型对研究大功率质子交换膜燃料电池空气供给系统以及相应的控制策略提供理论支持,仿真模型与实验结果为下一步控制策略优化提供基础与参考。展开更多
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） s...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.展开更多
The control objective and several key parameters of PEMFC hybrid system are analyzed. Control strategy design and energy optimization simulation are made individually for given cycle case and realtime operating case. ...The control objective and several key parameters of PEMFC hybrid system are analyzed. Control strategy design and energy optimization simulation are made individually for given cycle case and realtime operating case. For the given cycle case, genetic algorithm is adopted to solve the multi-constraint combinatorial optimization problem. Simulation result showed the algorithm＇s feasibility. As far as the realtime operation is concerned, based on the original fuzzy control strategy, the fuel cell voltage and voltage variance parameters are introduced to apply result reveals that the improved fuzzy control strategy can enhance the two-level modification on the fuzzy control output. The fuel cell efficiency and reduce the power fluctuations.展开更多
基金Project supported by National High-Technology Research andDevelopment Program of China (Grant No .2002AA517020)
文摘Control design is important for PEMFC （proton exchange membrane fuel cell） distributed power generator to satisfy user requirement for safe and stable operation. For a complex multi-variable dynamic system, a dynamic simulation model is first established. In view of close coupling and non-linear relationships between variables, the intelligent auto-adapted PI decoupling control method is used. From the simulation results it is found that, by bringing quadratic performance index in the single neuron, constructing adaptive PI controller, and adjusting gas flow rates through the second pressure relief valve and air compressor coordinately, both anode and cathode pressures can be maintained at ideal levels.
基金Project (No. 2003AA517020) supported by the Hi-Tech Researchand Development Program (863) of China
文摘Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.
基金Project (No. 2002AA517020) supported by the Hi-Tech Research and Development Program (863) of China
文摘Control design is important for proton exchange membrane fuel cell (PEMFC) generator. This work researched the anode system of a 60-kW PEMFC generator. Both anode pressure and humidity must be maintained at ideal levels during steady operation. In view of characteristics and requirements of the system, a hybrid intelligent PID controller is designed specifically based on dynamic simulation. A single neuron PI controller is used for anode humidity by adjusting the water injection to the hydrogen cell. Another incremental PID controller, based on the diagonal recurrent neural network (DRNN) dynamic identification, is used to control anode pressure to be more stable and exact by adjusting the hydrogen flow rate. This control strategy can avoid the coupling problem of the PEMFC and achieve a more adaptive ability. Simulation results showed that the control strategy can maintain both anode humidity and pressure at ideal levels regardless of variable load, nonlinear dynamic and coupling characteristics of the system. This work will give some guides for further control design and applications of the total PEMFC generator.
文摘Operating temperature of proton exchange membrane fuel cell stack should be controlled within a special range. The input-output data and operating experiences were used to establish a PEMFC stack model and operating temperature control system. A nonlinear predictive control algorithm based on fuzzy model was presented for a family of complex system with severe nonlinearity such as PEMFC. Based on the obtained fuzzy model, a discrete optimization of the control action was carried out according to the principle of Branch and Bound method. The test results demonstrate the effectiveness and advantage of this approach.
文摘近年来,质子交换膜燃料电池(PEMFC)作为车载燃料电池的主要动力源受到广泛关注。空气压缩机为电堆提供系统所需的氧气和阴极压力,是质子交换膜燃料电池系统中必不可少的一部分,其工作性能对燃料电池稳态和动态工作性能有很大的影响。基于实验室已有150 k W质子交换膜燃料电池系统,对离心式空压机的工作特性进行了研究,建立了包含离心式空气压缩机的空气供给系统应用模型。通过实验验证,仿真模型能够准确地反映离心式空压机与空气系统的特性,同时能真实反映包含离心式空压机的大功率质子交换膜燃料电池空气系统的稳态控制效果,以及不同控制策略下的动态响应效果。该模型对研究大功率质子交换膜燃料电池空气供给系统以及相应的控制策略提供理论支持,仿真模型与实验结果为下一步控制策略优化提供基础与参考。
基金Project supported by the National Natural Science Foundation of China (Grant No.20576071)the Natural Science Foundation of Shanghai Municipality (Grant No.08ZR1409800)
文摘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.
基金Project (No. 2003AA517020) supported by the Hi-Tech Researchand Development Program (863) of China
文摘The control objective and several key parameters of PEMFC hybrid system are analyzed. Control strategy design and energy optimization simulation are made individually for given cycle case and realtime operating case. For the given cycle case, genetic algorithm is adopted to solve the multi-constraint combinatorial optimization problem. Simulation result showed the algorithm＇s feasibility. As far as the realtime operation is concerned, based on the original fuzzy control strategy, the fuel cell voltage and voltage variance parameters are introduced to apply result reveals that the improved fuzzy control strategy can enhance the two-level modification on the fuzzy control output. The fuel cell efficiency and reduce the power fluctuations.
