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Han, Jaeyoung,Yu, Sangseok,Yi, Sun Elsevier 2017 International journal of hydrogen energy Vol.42 No.7
<P><B>Abstract</B></P> <P>Temperature control is a critical issue to ensuring the reliable performance of fuel cell systems. However, nominal feedback controllers currently used to regulate system temperature have limitations, due to the high inherent nonlinearity in the systems, and uncertainty in the parameters of the models, especially in the presence of dynamic load variations. In this study, a feedback controller was designed including Model Reference Adaptive Control (MRAC) to address uncertainties and robustly control the stack and the coolant inlet temperature in a proton exchange membrane fuel cell (PEMFC). The proposed controller was then evaluated by comparison with a nominal feedback controller. It was shown that if the parameters vary in the system the MRAC algorithm yields improved transient performances in terms of recovery speed and deviation in comparison to the nominal feedback control algorithm. The MRAC provides enhanced robustness.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A thermal management module is designed to predict the cooling performance. </LI> <LI> An MRAC algorithm is designed to control the fuel system temperature. </LI> <LI> Simulation is carried out to confirm feasibility of MRAC under dynamic load. </LI> <LI> By algorithm comparison, MRAC is proven to be more feasible for controlling the system temperature. </LI> <LI> MRAC comes to be more reliable under nominal dynamic operating schedules. </LI> </UL> </P>
Jaeyoung Han(한재영),Sangseok Yu(유상석),Sun Yi(이선),Seokyeon Im(임석연) 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.12
Temperature control is a critical issue to ensuring the reliable performance of fuel cell systems. However, feedback controllers currently used to regulate system temperature have limitations, due to the high inherent nonlinearity in the systems, and uncertainty in the parameters of the models, especially in the presence of dynamic load variations. In this study, a feedback controller was designed including Model Reference Adaptive Control (MRAC) to address uncertainties and robustly control the stack and the coolant inlet temperature in a proton exchange membrane fuel cell. The proposed controller was then evaluated by comparison with a nominal feedback controller. It was shown that if the parameters vary in the system the MRAC algorithm yields improved transient performances in terms of recovery speed and deviation in comparison to the nominal feedback control algorithm. The MRAC provides enhanced robustness.
Ram air compensation analysis of fuel cell vehicle cooling system under driving modes
Han, Jaeyoung,Yu, Sangseok Elsevier 2018 Applied thermal engineering Vol.142 No.-
<P><B>Abstract</B></P> <P>The cooling system is one of the major factors used to ensure the performance of the fuel cell vehicle system. In general, the cooling system is composed of a radiator, a reservoir, a water pump, a bypass valve, and a radiator fan. The ram air that enters the vehicle frontal area is also critically important while the vehicle is operating. In this study, cooling system responses considering ram air compensation were investigated to evaluate the control strategy, and control gain was addressed to optimize the control strategy. A dynamic vehicle model was integrated with the fuel cell system model.</P> <P>Three driving cycles were applied to investigate the responses of the cooling system under driving conditions. Three driving conditions considering ram air compensation were investigated to evaluate the cooling system operating trajectory. When the ram air compensation is considered, the cooling system operating trajectory and parasitic power can be accurately predicted. The control adjustment also needs to optimize the parasitic power. As a consequence, the trajectory of system pressure line 1 was found to be more effective for energy saving.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A FCVs model including a ram air compensation mode is designed. </LI> <LI> A controls strategy of a cooling system dependents on ram air compensation. </LI> <LI> A FCVs model is carried out to assess the cooling performance under driving modes. </LI> <LI> A control strategy should be strictly evaluated to reduce parasitic power in a FCVs. </LI> </UL> </P>
Han, Jaeyoung,Hwang, Janghwan,Yu, Sangseok Pergamon 2019 Applied thermal engineering Vol. No.
<P><B>Abstract</B></P> <P>Oxygen transport analysis is of critical importance during surge evolution for fuel cell systems because it is closely related with the safety and performance of the system. However, research has yet been insufficient on oxygen transport analysis to reaction site surface in catalyst layer under surge evolution. In this paper, an agglomerate model is used to investigate oxygen concentration, local current density, and activation over-potential along catalyst layer thickness under surge evolution. The results are validated versus experimental data from our test. Unlike previous analyses of oxygen transport in the catalyst layer, this study presents an analytic dynamic compressor model that is able to examine the various surge phenomenon. In this study, an agglomerate model is introduced and fuel cell system model including a dynamic compressor is implemented to investigate the influence of surge evolution on the cell performance. At the end, fuel cell system model is simulated during Highway Fuel Economy (HWFET) cycle. The results indicate that oxygen concentration at the GDL/CL interface within the range z = 0 μm to z = 3 μm is most strongly affected by surge evolution, and oxygen concentration changes are strongly affected by surge evolution up to z = 3 μm.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Dynamic compressor system modeled including a fuel cell system. </LI> <LI> Oxygen reaction reduction was modeled using an agglomerate model. </LI> <LI> Surge was examined by analytical dynamic compressor system model. </LI> <LI> Experiments were conducted to verify the designed agglomerate model. </LI> <LI> Oxygen mass transfer was analyzed in catalyst layer by surge evolution. </LI> </UL> </P>
차수 축약 추정 기반 모델 예측 제어기를 이용한 압축기 공기 유량 제어
한재영(Jaeyoung Han),김영현(Younghyeon Kim),유상석(Sangseok Yu),이선(Sun Yi) 대한기계학회 2018 大韓機械學會論文集B Vol.42 No.6
본 연구에서는 원심압축기 출구 공기 유량 제어를 위한 차수 Estimation(추정기), 축약 기반 모델예측 제어기를 설계하였다. 일반적으로 압축기 공기 유량의 측정은 고 비용의 센서를 필요로 한다. 하지만 압축기 출구 유량을 추정할 수 있는 추정기를 설계하면 센서 비용을 절감할 수 있다. 개발된 원심압축기 모델은 모델의 정확도를 보장하기 위해 실험과의 검증을 수행하였다. 원심압축기의 출구 공기 유량은 차수 축약 추정기를 이용하여 추정하였으며, 요구 공기 유량을 제어하기 위해 비용 함수를 최적화하는 기법을 본 연구에 적용하였다. 추정된 출구 공기 유량은 모델에서 출력되는 출구 공기 유량을 견실하게 추정한다. 결론적으로, 차수 축약 기반 모델 예측 제어는 압축기 공기 유량을 견실하게 추정하며, 압축기 출구 공기 유량을 적절히 제어하는 것을 확인할 수 있다. In this study, a model-prediction-controller (MPC)-based reduce order estimator is designed to regulate the outlet air flow rate of a centrifugal compressor. In general, measuring the compressor outlet air flow rate is costly. However, an estimation design method that properly estimates this air flow rate can reduce the sensor cost. The accuracy of our designed centrifugal compressor is validated through experimental data. The outlet air flow rate is estimated by reduce order estimation, which is necessary to control the desired air flow rate. In addition, a cost function is applied in this study. Our experiments yielded an estimated outlet air flow rate that is acceptable. In general, our MPC-based reduce order estimation proved robust and was regulated to achieve a desirable air flow rate.
한재영(Jaeyoung Han),윤진원(Jinwon Yun),임석연(Seokyeon Im),김성수(Sung-Soo Kim),유상석(Sangseok Yu) 한국자동차공학회 2011 한국자동차공학회 부문종합 학술대회 Vol.2011 No.5
The stringent emission regulation and future shortage of fossil fuel motivate the research of alternative powertrain. In this study, a system of proton exchange membrane fuel cell has been modeled to analyze the performance of the fuel cell system for automotive application. The model is composed of the fuel cell stack, air compressor, humidifier, and intercooler, and hydrogen supply which are implemented by using the Matlab/Simulinkⓡ. Fuel cell stack model is empirical model but the water transport model is included so that the system performance can be predicted over various humidity conditions. On the other hand, the model of air compressor is composed of motor, static air compressor, and some manifolds so that the motor dynamics and manifold dynamics can be investigated. Since the model is concentrated on the strategic operation of compressor to reduce the power consumption, other balance of components (BOP) are modeled to be static components. Since the air compressor model is empirical model which is based on curve fitting of experiments, the stack model is validated with the commercial software and the experiments. The dynamics of air compressor is investigated over unit change of system load. The results shows that the power consumption of air compressor is about 12% of stack gross power and dynamic response should be reduced to optimize the system operation.