Contents & References of Optimum design of flow field geometry in polymer fuel cell using genetic algorithm
List:
Chapter 1: 1
1-1 Preface 2
1-2 What is a fuel cell? 2
1-3 optimization of polymer fuel cell parameters 4
1-3-1 optimization of process parameters 4
1-3-2 optimization in cell design and manufacturing 5
1-4 researches conducted on optimization of process parameters of polymer fuel cell 6
1-5 optimization of process parameters of polymer fuel cell 8
Chapter two: 11
2-1 Brief history of fuel cells 12
2-2 Types of fuel cells: 15
2-2-1 Alkaline fuel cells 16
2-2-2 Polymer fuel cells 16
2-2-3 Phosphoric acid fuel cells 16
2-2-4 Molten Carbonate Fuel Cells 17
2-2-5 Solid Oxide Fuel Cells 17
2-3 How Polymer Fuel Cells Work 17
2-4 The Importance of Needing Fuel Cells 20
2-4-1 High Efficiency 20
2-4-2 adjusting the system according to the need 20
2-4-3 compatibility with environmental laws 20
2-4-4 flexibility towards fuel 21
2-4-5 increasing production and reducing distribution 21
2-4-6 no need for repair 21
2-4-7 no emission or minimal dispersion of energy 21
2-4-8 Simplicity of structure 22
2-4-9 Small size and dimensions 22
2-5 Fuel cell applications 22
2-5-1 Power systems 23
2-5-2 Transportation systems 24
2-5-3 Portable systems 24
2-5-4 Audio and video devices 24
2-5-5 Military systems 24
Chapter three: 25
3-1 Introduction 26
3-2 Genesis of genetic algorithm 27
3-3 Genetic algorithm 28
3-3-1 main operators GA 29
3-3-1-1 Coding methods 29
3-3-1-2 Initial population 31
3-3-1-3 Fitness function 32
3-3-1-4 Selection 32
3-3-1-4-1 Selection of rotary wheel (RWS) 33
3-3-1-4-2 Competitive selection 34
3-3-1-5 Integration 35
3-3-1-6 Mutation 37
3-3-1-6-1 Mutation probability) 38
3-3-1-7 Other genetic operators 38
3-3-2 Genetic algorithm with elite Simple bureaucracy 38 3-3-3 replacement methods 39 3-3-4 convergence criteria 40 3-3-5 performance criteria 3-3-6 GA differences with conventional optimization methods [21] 41 3-3-7 GA strengths 42 3-3-8 GA weaknesses 42
3-3-9 When GA is used 43
3-3-10 Applications of GA 43
3-4 Optimization of fuel cell process parameters using genetic algorithm 44
3-4-1 Use of analytical solution in the current genetic algorithm 44
3-4-1-1 Use of practical tests 45
3-4-1-2 using CFD solution 46
3-4-1-3 using analytical solution 46
3-4-2 defining the fitness function 47
3-4-3 programming in Manuscript File environment of MATLAB software 48
3-4-4 using elitist genetic algorithm 48
3-4-4-1 Coding of parameter values ??48
3-4-4-2 Selecting the number of initial population and number of generations 49
3-4-4-3 Applying the link and mutation operator in the current genetic algorithm 50
3-4-5 Using Lookup Table in the MATLAB Simulink environment 50
3-4-6 The reason for choosing the current 3 parameters for optimization 52
Chapter four: 53
4-1 Polymer fuel cell modeling using analytical solution 54
4-1-1 Channel modeling 54
4-1-2 MEA modeling 55
4-1-3 Equation solving methodology 57
4-2 Validation of modeling with practical tests 57
4-3 constant modeling parameters 61
Chapter five: 62
5-1 values ??of fitness obtained from analytical solution 63
5-2 Implementation of genetic algorithm linked with MATLAB Simulink 63
5-3 Effect of temperature on fuel cell performance 65
5-4 Effect of pressure on fuel cell performance 66
5-5 importance of anode pressure compared to cathode pressure 67
6-5 three-dimensional temperature-pressure diagrams 70
Sixth chapter: 72
6-1 conclusion 73
6-2 suggestions 74
List of references 75
Appendix A 78
MATLAB program linked with MATLAB Simulink 78 84
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