Multi-Objective Optimization of a Vehicular PEM Fuel Cell

8/2/2019 Multi-Objective Optimization of a Vehicular PEM Fuel Cell

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Multi-objectiveoptimization of a vehicular

PEM fuel cell system

NIDHIN BS7 M2

27227


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CONTENTS Introduction Proton Exchange Membrane(PEM) fuel cell ( construction ,

arrangement , modeling )

Multi objective optimization.

Multi objective optimization of PEM fuel cell system. Evaluation of Results.

Observation.

Conclusion.

References.


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INTRODUCTION Nowadays with an increase in pollution and the decrease of

fossil

fuel resources a movement has begun towards moreenvironmentally benign and more efficient power production.

Fuel cells are considered as one of the most promisingalternative power sources used in many areas includingtransportation applications, domestic uses, heat production,etc.

Fuel cells have an increasing demand with their highefficiency ( since operating at low temp) and the aim ofthis study is to apply a multi-objective optimization scheme toa PEM fuel cell system used for transportation purposes


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Proton ExchangeMembrane(PEM) fuel cell


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Main Characteristics The Ballards Xcellsis HY-80 Fuel Cell Engine was used. Fits beneath the floor of the vehicle, the size of the passenger

compartment is not affected.

The engine is a lightweight, 68 kW hydrogen-fueled , fuel cellengine.

The hydrogen is stored in a tank at 10 atm at 298 K

The fuel cell stack is composed of 97 cells each having a 900cm2 active surface area.

The cooling system is used in order to maintain a constant

operating temperature inside the fuel cell stack


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Arrangement of PEM fuel cell ina

vehicular system


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Modelling


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Multi-Objective Optimization Multi-objective optimization seeks the solution to a problem

that has two or more objectives simultaneously.

Objectives of the problem may be conflicting with each othersuch as the search for the best performance and least cost.

There are a set of solutions that one called the ParetoSolution.

The multi-objective optimization problem can be defined as:


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Solution methods The alternative solutions to the multi-objective problem

generally are in a conflict with some of the objectives.

The Pareto set is the set of solutions that has minimumconflict. The Weighing Sum of Objectives Method was used inthis study.

The multiple objective functions are combined in one functionas;


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Multi Objective Optimization of aPEM Fuel cell In order to apply a multi-objective optimization technique to

the derived model an objective function is to be prepared forthe solution.

In this study, a weighing method is used to form the objectivefunction that is a weighing factor is given to the objective

function parameters which are the produced work , energyefficiency, energy, exergy efficiency, exergy, and the cost ofproduced work.

It must also be considered that cost must be minimized whereas, the other parameters have to be maximized in the search

for the optimum condition.


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Continues A selection for the weighing factors is not made, instead a

parametric study for different weighting factors is applied andthe multi-objective problem is separately solved for eachcase.

The fitness function is formed depending on the objective

function derived. The main problem for optimizing this objective function is the

difference in the scales of the parameters.

The values of W lies between 0 and 120 kW, on the otherhand, the values of Cw lies between 2 to 6*10^-3 $/kW.

To avoid this situation the parameters are normalized to formthe fitness function between 0 and 1.

The normalization is done by dividing each parameter with itsmaximum value which is obtained by single optimization of

that parameter by using the developedcomputer programMULOP


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So the fitness function is changed as


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Some results of the multi-objective optimization procedure


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Evaluation of Results

The variation of produced workand efficiencies with respect to

the weight of work in the

objective function.

The variation of producedwork and cost with respect to

the weight of work in the

objective function.


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The Variation of produced work andcost with respect to the weight of

energy eff. in the objective function.

The variation of produced workand efficiencies with respect to

the weight of energy eff. in the

objective function.


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The variation of produced work

and efficiencies with respect to

the weight of exergy eff. in the

objective function.

The Variation of produced work

and cost with respect to the

weight of exergy eff. in the

objective function.


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The Variation of produced

work and cost with respect tothe weight of cost in the

objective function.

The variation of produced work

and efficiencies with respect tothe weight of cost in the objective

function.


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Conclusions The change of produced work and energy and exergyefficiencies with respect to the weight of work in the objective

function is seen. It is seen that the work and efficiencies areproportional with each other and when the produced workamount increases the cost of production decreases

It is seen that the best values for efficiencies lies in the lowervalues of contribution but, in these values the produced workvalues are low since the values between 0.5 and 0.6 is muchmore acceptable.

When the variation of the energy efficiency objective weight isconsidered the optimum results for these sets lie in 0.7

weight of the energy efficiency which has the and meaningfulefficiency and produced work results. It is seen that when the weight of an objective increased it

does not guarantee a better result for that objectiveparticularly because of the dynamics and complexity of theproblem.


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Continues.. The results for the exergy efficiency objective are similar to

the values of the energy efficiency since both values dependon the performance of the fuel cell system.

When the variation of the work, efficiencies, and cost withrespect to the weight of cost of the production objective

function is observed it is seen that the 0.6 value both thework, efficiencies and cost has the smallest values differingfrom the other sets.

The optimum results seem to lie between 0.8 and 0.9 from,the cost and produced work point of view. If the efficiencies

are considered, the best optimum value seems to be thevalues between 0.3 and 0.4 weights.


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References

Multi-objective optimization of avehicular PEM fuel cell systemSuha Orun Mert , Zehra zelik ,Yavuz zelik , IbrahimDiner .

Thermodynamic analysis of a PEMfuel cell power systemM.M. Hussain a, J.J. Baschuka, X. Li a, I. Dincer.

A grid based multi-objectiveevolutionary algorithm for theoptimization of power plants

J. Dipama a, A. Teyssedou a, F. Aub b, L. Lizon-A-Lugrin a


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Multi-Objective Optimization of a Vehicular PEM Fuel Cell