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

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3 System description 34 3.3.1 Energy efficiency Because of the heat transport a heat pump can “produce” more heat energy than it consumes through the compressor in the form of electricity. The efficiency is therefore indicated by the so-called coefficient of performance (COP) [20]. It is defined as the energy delivered (in the heating case) divided by the electric energy consumed by the compression. A physical upper limit is given by the ideal (lossless) COP of a Carnot process. ℃ (3.38) For the cooling case the extracted heat is compared to the compressor energy. An upper limit can be given by the ideal process. This means the closer both temperature levels of the heat sink and its source are, the better the COP can be. Figure 3.11: Comparison of refrigerants for the cooling case. [19] ℃ (3.39) The efficiency also depends on the refrigerant and the compressor. They give the limits for and and an optimal working point. Examples of coefficients
3 System description 35 of performance for three refrigerants and different ambient temperatures are shown in Figure 3.11. A typical COP around 2 can be seen. 3.3.2 Heat exchanger icing One main problem for the use of a heat pump in cars is the icing of the front (ambient air) heat exchanger. Acting as an evaporator when heating the cabin, its temperature has to be lower than the ambient air in order to extract heat from it. Given a humid autumn or winter weather this can easily lead to condensation of water and - below zero degree - to the development of an ice layer. This ice will prevent air flow through the structure and decrease the heat transfer (and with it the COP) dramatically. This is not acceptable since a car heating system has to be able to provide warm air under all circumstances to defog the windscreen - especially when it is cold and humid outside. Deicing V1 Compressor V4 HVAC EV1 EV3 EV2 EV4 PTC-Heater Condenser Evaporator E-Machine-Chiller Battery-Chiller Receiver V7 IHX Condenser Mixed Air Flap Figure 3.12: The de-icing mode in the ePerformance heat pump system. [19] One solution to this problem taken in the ePerformance system [21] is to temporar- V8 V3 V2 V6 V5
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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 and 50: 3 System description 29 width modul
Page 51 and 52: 3 System description 31 ��
Page 53: 3 System description 33 shown in Fi
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
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8 System and functionality integrat
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9 The MUTE project 95 order to fit
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10 Hardware and characteristics of
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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
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Bibliography [1] Holger Großmann.
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Bibliography 133 [22] M. Wang, T.M.
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Appendices
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B In- and outputs The interface bet
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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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