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

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C Simulation parameters The parameters for the controller used in the simulation in Chapter 12 are found in this appendix. Partly, they are already mentioned in the hardware description in Chapter 10. Some might already be good enough for the use in the MUTE car, while others need further measurements or adjustments. The Source column indicates where this value has been obtained from and gives an idea about the reliability of the data. The column Used in gives the section number to show in which context this parameter is used in this work and the controller.
and system parameters 2 concentration 700 �� Value Unit Used in Source 3.1.3, 5.2, 8.1.5 [14] MUTE cabin 2.4 �� 3.1.1, 3.1.2, 3.1.3 CAD-measurements of the car interior parts 100 (37500) � � 3.1.1 Estimation f the car body 52 � � 3.1.1 Estimation based on [1] oefficient of the CFRP-parts 5.14 � � � ¡� 8.1.2 5mm air gap, see 10.1 r of the car body parts 0.365 - 8.1.2 CAD-measurements r of the windows 0.274 - 8.1.2 CAD-measurements r of the interior parts 0.361 - 8.1.2 CAD-measurements ssure coefficient 0.75 - 3.1.4 Estimation, [15] ckness 3.85 �� 3.1.4 Product data ght 0.735 � 3.1.4 CAD-measurements a 0.84 � � 3.1.4 CAD-measurements ost outlets 96.0 �� 3.1.4, �� in 2.2.1 CAD-measurements ost outlets to side windows 33.6 �� 3.1.4, �� in 2.2.1 CAD-measurements ozzle size 15.6 �� 3.1.4 CAD-measurements air speed reaching the passenger 0.3 - �� in 2.2.1 Estimation ing power 1000 � 8.1.6, 8.2 Fuel heater data sheet Continued on the next page Simulation parameters 143
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ISSN 0280-5316 ISRN LUTFD2/TFRT--58
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Diploma thesis subject Problem stat
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Acknowledgements ii Acknowledgement
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Acknowledgements iv 3.1.4 Windscree
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Acknowledgements vi 8.5 System simu
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Nomenclature viii Nomenclature Symb
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Nomenclature x Other symbols Symbol
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Nomenclature xii Subscript Descript
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1 Introduction Energy consumption t
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1 Introduction 3 adjustment of the
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2 Control objectives 5 2.1 Windscre
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2 Control objectives 7 2.2 Comfort
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2 Control objectives 9 � Metaboli
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2 Control objectives 11 ��
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2 Control objectives 13 Figure 2.6:
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2 Control objectives 15 2.4 Influen
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3 System description 17 or heat com
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3 System description 19 calculated
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3 System description 21 ��
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3 System description 23 � � �
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3 System description 25 defrost tem
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3 System description 27 Figure 3.4:
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3 System description 29 width modul
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3 System description 31 ��
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3 System description 33 shown in Fi
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3 System description 35 of performa
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4 Control strategy The main goal of
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4 Control strategy 39 limits are di
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4 Control strategy 41 ��
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4 Control strategy 43 cabin. This s
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4 Control strategy 45 controlled. T
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5 The disturbance estimator 47 in e
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6 The optimiser: an evolutionary al
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7 The HVAC-system controller 69 �
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7 The HVAC-system controller 71 7.5
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8 System and functionality integrat
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Page 111 and 112: 8 System and functionality integrat
Page 113 and 114: 8 System and functionality integrat
Page 115 and 116: 9 The MUTE project 95 order to fit
Page 117 and 118: 10 Hardware and characteristics of
Page 129 and 130: 11 Matlab implementation The climat
Page 131 and 132: 11 Matlab implementation 111 Only r
Page 133 and 134: 11 Matlab implementation 113 left i
Page 135 and 136: 11 Matlab implementation 115 tion a
Page 137 and 138: 12 Controller evaluation 117 ��
Page 139 and 140: 12 Controller evaluation 119 be not
Page 141 and 142: 12 Controller evaluation 121 Number
Page 143 and 144: 12 Controller evaluation 123 Table
Page 145 and 146: 12 Controller evaluation 125 In the
Page 147 and 148: 12 Controller evaluation 127 ��
Page 149 and 150: 13 Conclusion 129 13.2 Possible imp
Page 151 and 152: Bibliography [1] Holger Großmann.
Page 153 and 154: Bibliography 133 [22] M. Wang, T.M.
Page 155 and 156: Appendices
Page 157 and 158: B In- and outputs The interface bet
Page 159 and 160: Signal Unit Range Type Comment Stat
Page 161: In- and outputs 141 B.3 Error codes
Page 165 and 166: Simulation parameters 145 C.2 Contr
Page 167 and 168: Simulation parameters 147 Panic han
Page 169 and 170: Simulation parameters 149 C.5 Test
Page 171 and 172: Additional simulation results 151 D
Page 173 and 174: Optimiser code 153 real_T ∗panic_
Page 175 and 176: Optimiser code 155 52 return 10; 54
Page 177 and 178: Optimiser code 157 138 /∗ return
Page 179 and 180: Optimiser code 159 230 ∗/ ∗ ===
Page 181 and 182: Optimiser code 161 ∗ IMEA_breedin
Page 183 and 184: Optimiser code 163 414 } 416 } } st
Page 185 and 186: Optimiser code 165 if (sortedPop [
Page 187 and 188: Optimiser code 167 596 ∗ Printout
Page 189: Optimiser code 169 690 ∗ Latest R
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