Abstract: Assembly of the proton exchange membrane fuel cells (PEMFC) has a very important influence on its performance and efficiency. The various components of PEMFC stack are usually locked and fixed by bolts. Locking bolt will cause the deformation of the bipolar plate and the other components, which will affect directly the deformation degree of the integral parts of the PEMFC as well as the performance of PEMFC. This paper focuses on the object of three-cell stack of PEMFC. Finite element simulation is used to investigate the deformation of bipolar plate caused by quantity and layout of bolts, bolt locking pressure, and bolt locking sequence, etc. Finally, we made a conclusion that the optimal combination packaging scheme was adopted to assemble the fuel cell stack. The scheme was in use of 3.8 MPa locking pressure imposed on the fuel cell stack, type Ⅱ of four locking bolts and longitudinal locking method. The scheme was obtained by comparatively analyzing the overall displacement contour of PEMFC stack, absolute displacement curve of bipolar plate along the given three paths in the Z direction and the polarization curve of fuel cell. The research results are helpful for the fuel cell stack assembly.
Abstract: Thermal enhancement of a single mini channel in
Proton Exchange Membrane Fuel Cell (PEMFC) cooling plate is
numerically investigated. In this study, low concentration of Al2O3 in
Water - Ethylene Glycol mixtures is used as coolant in single channel
of carbon graphite plate to mimic the mini channels in PEMFC
cooling plate. A steady and incompressible flow with constant heat
flux is assumed in the channel of 1mm x 5mm x 100mm. Nano
particle of Al2O3 used ranges from 0.1, 0.3 and 0.5 vol %
concentration and then dispersed in 60:40 (water: Ethylene Glycol)
mixture. The effect of different flow rates to fluid flow and heat
transfer enhancement in Re number range of 20 to 140 was observed.
The result showed that heat transfer coefficient was improved by
18.11%, 9.86% and 5.37% for 0.5, 0.3 and 0.1 vol. % Al2O3 in 60:40
(water: EG) as compared to base fluid of 60:40 (water: EG). It is also
showed that the higher vol. % concentration of Al2O3 performed
better in term of thermal enhancement but at the expense of higher
pumping power required due to increase in pressure drop
experienced. Maximum additional pumping power of 0.0012W was
required for 0.5 vol % Al2O3 in 60:40 (water: EG) at Re number 140.
Abstract: Polymer Electrolyte Membrane Fuel Cell (PEMFC) is
such a time-vary nonlinear dynamic system. The traditional linear
modeling approach is hard to estimate structure correctly of PEMFC
system. From this reason, this paper presents a nonlinear modeling of
the PEMFC using Neural Network Auto-regressive model with
eXogenous inputs (NNARX) approach. The multilayer perception
(MLP) network is applied to evaluate the structure of the NNARX
model of PEMFC. The validity and accuracy of NNARX model are
tested by one step ahead relating output voltage to input current from
measured experimental of PEMFC. The results show that the obtained
nonlinear NNARX model can efficiently approximate the dynamic
mode of the PEMFC and model output and system measured output
consistently.
Abstract: This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
Abstract: This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.
Abstract: In this research, the flow pattern influence on
performance of a micro PEMFC was investigated
experimentally. The investigation focused on the impacts of
bend angels and rib/channel dimensions of serpentine flow
channel pattern on the performance and investigated how they
improve the performance. The fuel cell employed for these
experiments was a micro single PEMFC with a membrane of
1.44 cm2 Nafion NRE-212. The results show that 60° and 120°
bend angles can provide the better performances at 20 and 40
sccm inlet flow rates comparing to that the conventional design.
Additionally, wider channel with narrower rib spacing gives
better performance. These results may be applied to develop
universal heuristics for the design of flow pattern of micro
PEMFC.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.