Design of an Automatic Control Algorithm for Energy-Efficient ...

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3 System description 30 � � �� Figure 3.7: The dehumidification process. by three equations [18]: Mass, water and energy balance. �� ¡ � � (3.28) (3.29) (3.30) The enthalpy of the condensed water � � is dependent on its temperature. If all possible water in the air is condensed, � �� will be saturated � �� . The amount of condensed water can then be estimated with the following equation (assuming that the air in point 2 was oversaturated, otherwise �� ). �� ¡ �� This gives a temperature at point 3 of �� ¡ � � � �� ¡ ¡� � with �� ¡ � � � � ��¡� � � � �� ¡ � �� 3.2.4 Heating � � � �� ¡ � �� (3.31) (3.32) Heating can be expressed quite easily compared to the other cases, since the humidity and the mass flow do not change.
3 System description 31 �� (3.33) � �� The heated air has a temperature of � � � � � � 3.2.5 The flaps �� ¡ �� ¡ � �� (3.34) (3.35) (3.36) Different models of flaps or air doors exist. An overview and a comparison of the different types can be found in Figure 3.8. The most common type is the plate door. FIG� Space Temp. Control SLIDE DOOR + - FILM DOOR ��+ + ++ FLEXIBLE DOOR ��+ ++ MULTI BUTTERFLY DOOR + ++ PLATE DOOR Figure 3.8: An overview and comparison of different flap types. [2] In general each flap can be represented by a function describing the amount of air going through it. The shape of the curve will differ by the type and the position towards the air flow direction. It is also dependent on the air speed. Neglecting other possible - +
Page 1: ISSN 0280-5316 ISRN LUTFD2/TFRT--58
Page 5: Diploma thesis subject Problem stat
Page 8 and 9: Acknowledgements ii Acknowledgement
Page 10 and 11: Acknowledgements iv 3.1.4 Windscree
Page 12 and 13: Acknowledgements vi 8.5 System simu
Page 14 and 15: Nomenclature viii Nomenclature Symb
Page 16 and 17: Nomenclature x Other symbols Symbol
Page 18 and 19: Nomenclature xii Subscript Descript
Page 21 and 22: 1 Introduction Energy consumption t
Page 23 and 24: 1 Introduction 3 adjustment of the
Page 25 and 26: 2 Control objectives 5 2.1 Windscre
Page 27 and 28: 2 Control objectives 7 2.2 Comfort
Page 29 and 30: 2 Control objectives 9 � Metaboli
Page 31 and 32: 2 Control objectives 11 ��
Page 33 and 34: 2 Control objectives 13 Figure 2.6:
Page 35 and 36: 2 Control objectives 15 2.4 Influen
Page 37 and 38: 3 System description 17 or heat com
Page 39 and 40: 3 System description 19 calculated
Page 41 and 42: 3 System description 21 ��
Page 43 and 44: 3 System description 23 � � �
Page 45 and 46: 3 System description 25 defrost tem
Page 47 and 48: 3 System description 27 Figure 3.4:
Page 49: 3 System description 29 width modul
Page 53 and 54: 3 System description 33 shown in Fi
Page 55 and 56: 3 System description 35 of performa
Page 57 and 58: 4 Control strategy The main goal of
Page 59 and 60: 4 Control strategy 39 limits are di
Page 61 and 62: 4 Control strategy 41 ��
Page 63 and 64: 4 Control strategy 43 cabin. This s
Page 65 and 66: 4 Control strategy 45 controlled. T
Page 67 and 68: 5 The disturbance estimator 47 in e
Page 69 and 70: 6 The optimiser: an evolutionary al
Page 89 and 90: 7 The HVAC-system controller 69 �
Page 91 and 92: 7 The HVAC-system controller 71 7.5
Page 93 and 94: 8 System and functionality integrat
Page 101 and 102:
8 System and functionality integrat
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Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
9 The MUTE project 95 order to fit
Page 117 and 118:
10 Hardware and characteristics of
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Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
11 Matlab implementation The climat
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11 Matlab implementation 111 Only r
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11 Matlab implementation 113 left i
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11 Matlab implementation 115 tion a
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12 Controller evaluation 117 ��
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12 Controller evaluation 119 be not
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12 Controller evaluation 121 Number
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12 Controller evaluation 123 Table
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12 Controller evaluation 125 In the
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12 Controller evaluation 127 ��
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13 Conclusion 129 13.2 Possible imp
Page 151 and 152:
Bibliography [1] Holger Großmann.
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Bibliography 133 [22] M. Wang, T.M.
Page 155 and 156:
Appendices
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B In- and outputs The interface bet
Page 159 and 160:
Signal Unit Range Type Comment Stat
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In- and outputs 141 B.3 Error codes
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and system parameters 2 concentrati
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Simulation parameters 145 C.2 Contr
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Simulation parameters 147 Panic han
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Simulation parameters 149 C.5 Test
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Additional simulation results 151 D
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Optimiser code 153 real_T ∗panic_
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Optimiser code 155 52 return 10; 54
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Optimiser code 157 138 /∗ return
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Optimiser code 159 230 ∗/ ∗ ===
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Optimiser code 161 ∗ IMEA_breedin
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Optimiser code 163 414 } 416 } } st
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Optimiser code 165 if (sortedPop [
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Optimiser code 167 596 ∗ Printout
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Optimiser code 169 690 ∗ Latest R
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