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

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12 Controller evaluation 124 �� Figure 12.5: Results of the heat-up simulation with and without preconditioning. passengers enter the car, the cabin is already heated up to around �� ℃. The overall fuel consumption is �� or �� less due to the recirculation mode used in the first 20 minutes. However, the 20 minutes longer heating during the trip has to be subtracted from this saving. Therefore, this feature is mainly increasing comfort. The fuel saving of the standard control was obtained by a comparison with a simulation with blocked recirculation. With this limitation �� or �� more fuel were consumed with the resulting comfort and safety related figures being comparable in the end. The detailed simulation result of this “no-recirculation”-case is found in Appendix D.1.1. In the results the effects of the slow starting fuel heater are seen. The first 3 minutes not much happens since the heater has not started, yet. In the precondition mode, the heater is shut down twice and requires time to start again (at � � �� and � � �� ) because the cabin heats up fast and the heater has a minimum heating power.
12 Controller evaluation 125 In the summer case, fuel saving is no matter. The interesting points here are the achieved comfort and if the precondition mode is useful. �� Figure 12.6: Results of the cool-down simulation with and without preconditioning. The temperature cannot be kept below 43 ℃ due to the high sun radiation, as seen in Figure 12.6. The car is standing and the cabin has a quite big window share, which leads to this extreme condition. Preconditioning lowers the extreme temperature in the car before the persons enter it and is therefore recommendable. Nevertheless, the attained comfort level is not acceptable, but can, due to the hardware limitations, only be faced by opening the windows. The full results of this simulation are found in Appendix D.2. A more comfortable functioning of the control can be shown in the case of fogging prevention. This is tested in the case of an ambient humidity at the saturation level, for example when it is raining, and comparable high temperatures. The controller still keeps the humidity on the windshield at a high, but acceptable level of around �� as seen in Figure 12.7. The comfort would be judged as quite good. The stopping and the starting of the heater can be seen in this simulation twice as well. The final test case shows the handling of a problematic case for the employed fuel heater and the control. The ambient temperatures are only some degrees Celsius away from a comfortable sensation and therefore the heater, which has a minimum heating power of 1000 Watt, is only required from time to time. This behaviour of switching can is visible in the results in Figure 12.8. As seen in the fuel consumption chart, the heater is only active the first 21 minutes. After that only
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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
Page 93 and 94: 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: 12 Controller evaluation 123 Table
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 and 162: In- and outputs 141 B.3 Error codes
Page 163 and 164: and system parameters 2 concentrati
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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