Active speed control for energy saving purposes on belt conveyor systems- Actieve snelheid regulering voor energie besparing op transportbanden

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Delft University of Technology

FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING

Department Maritime and Transport Technology

Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

This report consists of 102 pages and 4 appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice.

Specialization: Transport Engineering and Logistics Report number: 2014.TEL.7880

Title: Active speed control for energy saving purposes on belt conveyor systems

Author: L.R. de Lange

Title (in Dutch) Actieve snelheid regulering voor energie besparing op transportbanden.

Assignment: Master Thesis Confidential: no

Initiator (university): Prof. Dr. Ir. G. Lodewijks Supervisor (university): Dr. Ir. Y. Pang

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T

U

Delft

F A C U L T Y O F M E C H A N I C A L , M A R I T I M E AND M A T E R I A L S E N G I N E E R I N G

Delft University of T e c h n o l o g y Department of Marine and Transport Technology

Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl Student: Supervisors (TUD): Specialization: Creditpoints (EC): Lars de Lange

Prof. Dr. Ir. G. Lodewijks Dr. Ir. Y. Pang TEL 35 Assignment type: Report number: Confidential: Master Thesis 2014.TEL.7880 no

Subiect: Active s p e e d control for e n e r g y s a v i n g purposes of belt c o n v e y o r s y s t e m s . Belt conveyors have been proven to be a cost-effective way of

transporting large amounts of bulk materials. They are used in many industries and implemented all over the world. However, studies have show/n that the energy needed to power a belt conveyor system is in fact speed dependent. This opens up the possibility to save energy by regulating the operation speed of belt conveyor systems. This is known as speed control for belt conveyor system.

Speed control proves to have many challenges before a proper system can be implemented. As the dynamics of the belt conveyor system influence the control of the electric motor which powers the system. Also control algorithms for the desired speed in relationship to the feed flow alterations which take spillage risk into account must be implemented.

Fig. 1: Belt conveyor system (Courtesy of ABB) In this research assignment you will look into the dynamics of a belt

conveyor system to determine the information needed to be able to control the electric motor which powers the system. And how control algorithms for the speed control can have an effect on the energy savings or spillage risk. Relevant research questions are:

• Is it possible to use the start and stop procedures of belt conveyor systems to reconfigure into an active speed control system?

• What are the differences in the dynamics of a start or stop procedure compared to a change in speed during operations?

• How will the desired speed of the belt conveyor be calculated from the measured feed flow?

• What type of safety precautions can be used to enable energy savings without material spillage or the risk of overloading the system?

• Is there a possibility to save more energy with active speed control?

Use simulations to show the effects of different type of control algorithms on the possibilities for energy savings preventing spillage of bulk solid materials.

The report must be written in English and must comply with the guidelines ofthe section. Details can be found on the website.

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Summary

Transportation of material has always been of importance to the economy. For long distances, by boat, plane, truck, or for short distances, by conveyors, people, etc. The belt conveyor has been proven to be cost-effective, for transporting large amounts of material, in many scenarios. Improvements have been made in the past decades on energy efficiency as well as environmental impact. One of these improvements is the possibility to save energy by means of speed control.

Energy efficiency decreases when the belt conveyor is not loaded to it’s designed potential. Therefore adjusting the speed, to make sure the belt is loaded correctly, could increase the energy efficiency of the system. However as a speed transition costs energy the possibilities of saving energy whilst using speed transitions should be researched. In this thesis the possi-bilities for saving energy while using this continues speed transition method, known as active speed control, is researched.

Past research has proven that start and stop procedures of belt conveyor systems increase the lifetime expectancy of the belt form said system. This is because a smooth acceleration profile for these procedures reduces the jerk on the belt. This should be a constraint of the system, as a lower lifetime expectancy is not desirable. Other constraints would be overload-ing the system or spillage of material. When the belt conveyor is run at a lower conveyoverload-ing speed to make sure it is filled correctly a sudden increase in feed rate could lead to the system overloading, or even spill material. As overloading the system and spillage of material is not desirable, these should be constraints. Every belt conveyor system will also have certain res-onance frequencies which need to be avoided, as they can cause damage to the system. These frequencies often occur at specific speeds, these speeds will also be a constraint for the speed controller. For the system to become more energy efficient a control algorithm is designed to lower the speed whilst honoring the constraints.

This control algorithm should be implemented in the induction motor control of the system. Since the implementation of start and stop procedures requires the belt conveyor system to have a Variable Frequency Drive (VFD), instead of a fluid coupling, these devices have be-come more popular. Unfortunately these devices are based on scalar control strategies, which cannot handle the speed transition, required for active speed control, well. Therefore other vector control based strategies should be used, such as Field Oriented Control (FOC) and Direct Torque Control (DTC). The implementation of these strategies only require some more sensors and adding computational power.

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vi Summary

the induction motor can be controlled to handle the speed transitions and function within the boundaries of the constraints put on the system. This way the belt conveyor system can save energy whilst not reducing the belt’s life time expectancy or increase the risk of spillage or overloading the system.

The designed control algorithm for this research has proven to function within the boundaries of the constraints. Given the system has a long enough time window to speed up and slow down in, for safety precautions. The designed controller also saves energy in the researched scenario. The amount of energy it can save is dependent on for what peak the belt conveyor is designed, as well as the average feed rate of the operation. If the average feed rate of the operation is close to the peak rate the belt conveyor is designed for the energy saving possibilities are low (3-10%), but if the feed rate of the operation is lower than the peak rate the belt conveyor is designed for the energy savings are significantly higher (20-30%). The simulations of this research also show the difference between the two selected vector control based strategies. The FOC strategy shows a much more stable result than the DTC strategy. This is mainly due to time availability and the required computational power for long simulations with a short sample time. The sample time of the vector control based strategies influences the stability of the system on the one hand, but effect the duration of the simulation on the other hand. Since the FOC strategy is least influenced by this effect it is more stable, compared to the DTC strategy.

The conclusions of this research are the following:

1. Belt conveyor systems which use active speed control can save energy compared to non-controlled systems.

2. A correct control algorithm can save energy whilst honoring the constraints of spillage or overloading the system.

3. Start and stop procedures of belt conveyor systems that use a VFD can be transformed into active speed control systems.

4. Field Orientated Control is more stable than Direct Torque Control in simulations when a long sample time is used.

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Samenvatting

Transport van materiaal is altijd van belang voor de economie. Voor lange afstanden, per boot, vliegtuig, vrachtwagen, of voor korte afstanden, door transportbanden, mensen, enz. De transportband is bewezen kosteneffectief te zijn, voor het vervoer van grote hoeveelheden materiaal, in veel scenario’s. Er zijn verbeteringen aangebracht in de afgelopen decennia op de energie-efficiëntie en milieu-impact van deze transportbanen. Een van deze verbeteringen is de mogelijkheid om energie te besparen door middel van snelheid regulering.

Energie-efficiëntie neemt af wanneer de transportband niet is geladen om het ontworpen po-tentieel. Daarom geeft het aanpassen van de snelheid, om te zorgen dat de band correct is geladen, de mogelijkheid de energie-efficiëntie van het systeem te verhogen. Maar een snelheid overgang kost energie, dus zal de mogelijkheid om energie te besparen tijdens het gebruik van snelheidsovergangen moeten worden onderzocht. In deze scriptie worden de mogelijkheden om energie te besparen door het gebruik van snelheidsovergangen, die bekend staat als actieve snelheid regulering, worden onderzocht.

Eerder onderzoek heeft aangetoond dat het start en stop proces van transportband syste-men de verwachte levensduur van de banden verhoogd. Dit komt omdat een soepel acceler-atieprofiel in deze processen de ruk aan de band vermindert. Dit is een beperking van het systeem, aangezien een lagere verwachte levensduur van de band niet wenselijk is. Andere beperkingen zouden worden overbelasting van het systeem of het verspillen van materiaal. Wanneer de transportband op een lagere transportsnelheid wordt gezet, om ervoor te zorgen dat deze goed gevuld is, zal een plotselinge toename van de voeding ervoor kunnen zorgen dat het systeem overbelast raakt, of zelfs materiaal verspilt. Omdat het niet wenselijk is dat het system overbelast raakt of materiaal verspilt zullen dit dan ook beperkingen zijn. Elke transportband zal ook bepaalde resonantiefrequenties hebben die moeten worden vermeden, aangezien deze beschadiging aan het systeem kunnen veroorzaken. Deze frequenties komen voor bij specifieke snelheden, daarom zullen deze snelheden ook een beperking zijn voor het regelalgoritme. Om het systeem energiezuiniger te maken is een regelalgoritme ontworpen dat de snelheid verlaagt terwijl het binnen zijn beperkingen blijft.

Het regelalgoritme zal in de inductiemotor controle van het systeem worden geïmplementeerd. Omdat de invoering van de start en stop processen een VFD vereist van transportban-den, in plaats van een vloeistofkoppeling, zijn deze apparaten steeds populairder geworden.

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viii Summary

Helaas zijn deze apparaten gebaseerd op scalar control strategieën, die de snelheidovergan-gen, vereist actieve snelheid regulering, niet goed aankunnen. Hiervoor zijn andere, vector control gebaseerde, strategieën voor nodig, zoals FOC en DTC. Het implementeren van deze strategieën zou alleen vereisen dat er wat meer sensoren worden toegevoegd en wat meer rekenkracht.

Het regelalgoritme is geïmplementeerd in de controle van de vectoren gebaseerde strategieën. In een dergelijk scenario kan de inductiemotor worden gecontroleerd om de snelheid overgan-gen te reguleren binnen de grenzen van de beperkinovergan-gen van het systeem. Op deze manier kan het transportbanden systeem energie besparen, terwijl het niet de band zijn levensduur verwachting vermindert of het risico verhoogt op materiaal verspilling of overbelasting van het systeem.

Uit dit onderzoek is gebleken dat het ontworpen regelalgoritme blijkt te functioneren binnen de grenzen van de beperkingen. Het is wel nodig dat het systeem lang genoeg de tijd heeft om te versnellen en te vertragen voordat het materiaal op de band komt, in verband met veiligheidsmaatregelen. De ontworpen controller bespaart ook energie in het onderzochte sce-nario. De hoeveelheid energie die kan worden bespaard is afhankelijk van voor welke piek de transportband is ontworpen, alsmede de gemiddelde toevoer van materiaal van de operatie. Als de gemiddelde voeding van de operatie dichtbij de piekwaarde van de voeding, waarvoor de transportband is ontworpen, ligt zal de energiebesparende mogelijk laag zijn (3-10 %), maar als de voeding van de operatie is lager dan de piekwaarde, waarvoor de transportband is ontworpen, zal de energiebesparing significant hoger zijn (20-30 %).

De simulaties van dit onderzoek tonen ook het verschil tussen de twee geselecteerde vector control strategieën. De FOC strategie toont een veel stabieler resultaat dan de DTC strategie. Dit is voornamelijk te wijten aan de beschikbaarheid van tijd en de benodigde rekenkracht voor lange simulaties met een korte bemonsteringstijd. De bemonsteringstijd van de vector control strategieën beïnvloedt de stabiliteit van het systeem aan de ene kant, maar beïn-vloeden de duur van de simulatie anderzijds. Aangezien de FOC strategie het minste wordt beïnvloed door dit effect is deze strategie stabieler in vergelijking met de DTC strategie. De conclusies van dit onderzoek zijn de volgende:

1. Transportbanden systemen die gebruik maken van actieve snelheid regulering kunnen energie besparen ten opzichte van systemen die niet gereguleerd worden.

2. Een goed regelalgoritme kan energie besparen terwijl het de kans op overbelasting of materiaal verspilling binnen beperkingen houdt.

3. Start en stop processen van het transportbanden systeem die gebruik maken van een VFD kunnen worden getransformeerd naar actieve snelheid regulering systemen. 4. Field Orientated Control is stabieler dan Direct Torque Control in simulaties met een

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Glossary

List of Symbols

FH = Primary resistance (N) FN = Secondary resistance (N) FST = Gradient resistance (N) FS = Special resistance (N) f = Friction coefficient (-) g = Gravitational acceleration (m/s2)

L = Belt conveyor length (m)

m0_R = Mass of idlers per meter (kg/m) m0_B = Mass of belt per meter (kg/m)

m0_L = Mass of bulk material per meter (kg/m) δ = Gradient resistance (neglected if <18o) (o)

C = Length coefficient (-)

H = Height increase (m)

v = Belt conveyor speed (m/s)

η = Efficiency of the system (-)

t = Current time (s) t0 = Starting time (s) Vb = Desired velocity (m/s) Vb,0 = Velocity at t0 (m/s) Ta = Acceleration time (s) µ = Coefficient of friction (-)

α = Wrap of the belt around the pulley (o) kN = Nominal rupture force of the belt (N)

B = Belt width (m)

SA,min = Minimum safety factor (-)

FdA = Peripheral driving force on driving pulley (N)

Fd = Motional resistance (N)

Fac = Resistance force caused by acceleration (N) a = Belt acceleration (m/s2)

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x Glossary Uqs = Stator q-axis voltage (V)

Uds = Stator d-axis voltage (V) Rr = Rotor resistance (Ω) Rs = Stator resistance (Ω) iqs = Stator q-axis current (A) ids = Stator d-axis current (A) iqr = Rotor q-axis current (A) idr = Rotor d-axis current (A)

ia,b,c = Phase of the three-phase current (A) Lm = Magnetizing inductance of the motor (H)

Lr = Rotor inductance (H)

Ls = Stator inductance (H)

p = Pole pairs (-)

φqs = Stator flux linkage q-axis (Wb) φds = Stator flux linkage d-axis (Wb) φqr = Rotor flux linkage q-axis (Wb) φdr = Rotor flux linkage d-axis (Wb) ωe = Excitation frequency (rad/s) ωm = Mechanical frequency (rad/s) ωr = Slip frequency (rad/s)

Sa,b,c = Phase of the three-phase voltage (V)

List of Acronyms

VFD Variable Frequency Drive FOC Field Oriented Control DTC Direct Torque Control

AC Alternating Current

DC Direct Current

IGBT Insulated-Gate Bipolar Transistor

PWM Pulse-Width Modulator

MTPH Metric Tonnes Per Hour MPC Model Predictive Control PLC Programmable Logic Control

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List of Figures

1-1 An overview of the belt conveyor system . . . 3

2-1 An example for feed flow onto the belt conveyor . . . 10

3-1 Exploded view of an induction motor: (1) motor case (frame), (2) ball bearings, (3) bearing holders, (4) cooling fan, (5) fan housing, (6) connection box, (7) stator core, (8) stator winding (not visible), (9) rotor, (10) rotor shaft. (Courtesy of Danfoss A/S) . . . 15

3-2 Moving magnet cutting across a conducting ladder [1] . . . 15

3-3 Three examples of acceleration profiles . . . 16

3-4 Jerk of the acceleration profiles . . . 17

4-1 Overview of control strategies . . . 19

4-2 An overview of an Indirect Field Oriented Control system of an induction motor [2] 22 4-3 Sector division [3] . . . 24

4-4 An overview of a Direct Torque Control system of an induction motor [2] . . . . 26

5-1 Overview of the inputs and outputs of the speed controller in Matlab . . . 34

5-2 Decision tree . . . 37

5-3 Simulation model for FOC and DTC . . . 43

6-1 Simple feed input . . . 46

6-2 Acceleration prediction path combination example . . . 46

6-3 Deceleration prediction path combination within same time window example . . . 47

6-4 Deceleration prediction path combination with different time windows example . 47 6-5 Matlab SIMULINK model for mass distribution on secondary belt conveyor . . . 48

6-6 Matlab SIMULINK model for total mass on secondary belt conveyor . . . 49 6-7 Matlab SIMULINK model to calculate the power of the secondary belt conveyor . 50

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xvi List of Figures

6-8 Conveying speed of the secondary belt conveyor . . . 51

6-9 Mass per segment on the secondary belt conveyor . . . 51

6-10 Mass on the secondary belt conveyor . . . 52

6-11 Power of the secondary belt conveyor . . . 53

6-12 Power consumption compared to speed pattern . . . 54

6-13 Power consumption of the FOC strategy . . . 55

6-14 Power consumption of the DTC strategy . . . 55

B-1 Blockdiagram with Induction Motor Dynamics . . . 68

B-2 Blockdiagram for determining τ_e∗ from φr and iqs . . . 69

B-3 Blockdiagram for determining ωsl from φr and iqs . . . 69

B-4 Blockdiagram for determining φr from ids . . . 69

B-5 Blockdiagram for determining i∗_qs from φr and τref∗ . . . 70

B-6 Blockdiagram for determining i∗_ds from φ∗_ref . . . 70 C-1 Overview of the SIMULINK Field Oriented Control module (Courtesy of MathWorks) 72 C-2 Overview of the SIMULINK Direct Torque Control module (Courtesy of MathWorks) 73

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List of Tables

2-1 Transition times and feed rates . . . 10

3-1 Length coefficient C dependent on belt conveyor length L (Alles, 1994)[4] . . . . 13

4-1 Basic DTC switching table . . . 24

4-2 Corresponding voltage vectors of switch positions . . . 24

5-1 Secondary belt conveyor parameters taken from case study of D.He[15] . . . 33

6-1 Input parameters for the simulation . . . 50

6-2 Energy savings of different designed systems . . . 53

C-1 Field Oriented Control input parameters . . . 74

C-2 Direct Torque Control input parameters . . . 74

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Chapter 1 Introduction

Transport has always been an important aspect of industry, from moving grain by cart in early centuries to moving coal by belt conveyors in the modern world. Since the industrial revolution the energy efficiency has become more important [5] and new transportation sys-tems were invented, such as the belt conveyor. Conveyor belts are used in the modern world for conveying people, general cargo and bulk cargo in a cost-effective way. Because of their high reliability and availability they are used in a lot of different industries such as the mining industry, the chemical industry, the cement and concrete industry, etc. The costs for main-taining and operating a belt conveyor are high for certain industries as the belt conveyors they use are very large and almost always operational. To be able to keep a competitive edge in these industries reliability and availability become just as important as cost reductions for the maintenance and the operating costs of these belt conveyors. The industry demands belt conveyors to become longer, faster and more efficient with higher capacity and less environ-mental impact [6][7]. Research and development of the belt conveyor systems was boosted after the Second World War, due to the developments within the rubber industry [6]. This leads to a lot of belt conveyor system implementations within multiple industries where re-search was mostly done in increasing the capacity or length of the belt conveyor systems. The creation of longer belt conveyors with a higher capacity gave some problems, as scaling the belt conveyor systems is not a linear process. One dimensional models where created for predictions of scaling the belt conveyor systems [8]. These models where improved to two dimensional models as computational capacity increased over the years [9]. These models are still used to scale the belt conveyors, making them larger, faster and have higher capacity. However since the increase in energy consumption and the environmental awareness of the past decades the industries also demand the belt conveyor systems to become more efficient and have less environmental impact.

This is why in the past decades research has also been focusing on using Variable Frequency Drive (VFD) to control the driving force of the induction motor within the belt conveyor system to reduce energy consumption for certain scenarios [7][10].

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2 Introduction

1-1

Problem definition

Research into speed control of these long belt conveyor systems has been done to investigate the possibilities of energy savings [10]. This research shows that energy savings can indeed be achieved by means of speed control.

However this study does not take the dynamics of changing the speed of a belt conveyor into account, as the speed is not changed constantly but rather set to a certain speed according to the expected flow of an operation. The energy savings are calculated by the difference in energy consumption between two steady operating speeds of a belt conveyor system. The means of getting from one operating speed to another has been left out. This is mostly because there are models for the starting and stopping procedure of a belt conveyor system, however speed transition procedures are still in the early stages of research and have not yet been implemented.

To be able to create a model that uses active speed control (changing the speed constantly to the ideal state) the dynamics of the belt conveyor should be researched as well as the means of controlling the induction motor which drives the system. Research will also need to be done on the way in which the ideal speed for the belt conveyor is determined, as the safety of spillage and overloading the system should be considered.

In this Master Thesis the means of saving energy by active speed control will be further investigated by implementing the dynamics of a belt conveyor, control of the induction motor and the control strategy for the speed of the system into the equation.

1-2

Research Scope

Speed control cannot always provide energy savings, the feed of the belt conveyor system is of importance to performance of the energy saving control system. In some scenarios the feed of the belt conveyor might already be constant, creating a scenario where active speed control is not cost-effective (as there is an optimal speed for the belt conveyor to operate on and there is no need for changing this speed). The feed could also be so random that the response time of the system would not be quick enough to react on the changes in the feed, this would mean a lot of material would be spilled and energy would be wasted.

The scenario where speed control would be a useful implementation for energy savings would be that of a feed that is not constant and does not change faster than the response time of the system. This scenario can be found in terminals which handle bulk solid materials of multiple carrier on the same belt conveyor system, such terminals as the EMO in Rotterdam. The feed of empting a large sea going vessel would be different from empting a train on the terminal, however both flows would be relatively constant during operations. And since the same belt conveyor system is used for the transportation of the bulk solid material in both scenarios, the implementation of an active speed control system would have its benefits on the energy consumption of the system.

The specific scenario for the Master Thesis would also require the layout of the speed control system. As this research will be on the speed control system and not on the type of sensors or means of gathering the required information. There are multiple ways of predicting the feed of the belt conveyor which is speed controlled for energy saving purposes. For example a hopper could be installed at the beginning of the belt conveyor and the material level could be

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1-3 Research questions 3

measured or the opening of the hopper could be controlled. However this would require space within the layout of the belt conveyor system as well as knowledge on the type of material in the hopper, meaning it would not be ideal for this scenario.

Another way of speed control would be to install a material flow sensor on the main belt conveyor and speed control the secondary belt conveyor. The length of the track after the main belt conveyor could then be used for energy savings as the belt conveyors after the secondary belt conveyor could also be speed controlled (in the same way as the main and secondary are controlled). This would not require space or changes in the current layout of the belt conveyor systems, only the implementation of the material flow sensors. The layout shown in Figure 1-1 will be used in this Master Thesis for the implementation of speed control.

Figure 1-1: An overview of the belt conveyor system

Symbol

Feed sensor placement (-) S

Length of primary belt conveyor (m) Lp

Conveing speed of primary belt conveyor (m/s) vp Length of secondary belt conveyor (m) Ls Conveing speed of secondary belt conveyor (m/s) vs Average mass of the idlers on carrying side (kg/m) mcr Average mass of the idlers on return side (kg/m) mrr

Average mass of the belt (kg/m) mbelt

Mass of the bulk material on belt (kg/m) mbulk Height increase of the secondary belt conveyor (m) H

1-3

Research questions

For this research the following research question will be answered within the research scope presented.

“How can active speed control of belt conveyor systems save more energy than non-controlled systems when taking the dynamics of said system into account? ” The research question will be split up into multiple questions of the subject:

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4 Introduction • Is it possible to use the start and stop procedures of belt conveyor system to reconfigure

into an active speed control system?

– What type of control is used for the start and stop procedures of belt conveyor systems? And how do they work?

– Can these control strategies be used for active speed control?

– Give a detailed figure of the way in which the control strategy would be imple-mented.

• What are the differences in the dynamics of a start or stop procedure compared to a change in speed during operations?

– Which resistances come into play when the belt conveyor system need accelerates or decelerates during operation?

– How do these resistances relate to the design of the belt conveyor system?

• How will the desired speed of the belt conveyor be calculated from the measured feed flow?

– What are the constraints for this calculation?

– Can a controller be designed which functions within these boundaries?

• What type of safety precautions can be used to enable energy savings without material spillage or the risk of overloading the system?

– Are there any possibilities known for reducing material spillage?

– Can these possibilities be used for the design within the research scope?

– How does the energy saving of the speed control relate to possible material spillage or overloading the system?

• Is there a possibility to save more energy with active speed control?

– Can active speed control save more energy than non-controlled systems? – If not, what are the issues? And can these be solved?

– What are the advantages and disadvantages?

1-4

Approach and methodology

Answering the research question will be done using the following approach. Research will be done on the required input of the speed controller for the defined belt conveyor system. The information needed for the control will be divided into subjects and discussed.

The basic principles of speed controlling a belt conveyor system will be explained. As well as former research on the acceleration of a belt conveyor. This information will be used to create constraints for the speed controller.

A control algorithm will use these constraints to determine the optimal speed for energy saving purposes. This will be tested using simulations. The pro’s and con’s of the control

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1-5 Outline of the thesis 5

algorithm will be discussed.

Induction motor control will be introduced, and the main control strategies will be explained. Determining the possibilities of energy savings when using an induction motor will be simu-lated, and the results will be discussed.

1-5

Outline of the thesis

In the thesis the feed scenarios of belt conveyor systems will be considered first in chapter 2. One scenario will be selected and explained in detail for further research. Then chapter 3 will give a detailed overview on speed control of belt conveyor systems. After which chapter 4 will discuss the most commonly used control strategies for induction motor control and explain their working principles. Then a speed controller will be designed in chapter 5. In chapter 6 the information of all previous chapters will be combined to create simulations from which a conclusion and possible recommendations will be discussed in chapter 7.

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Chapter 2 Feed scenarios for belt conveyors

The effectiveness of using speed control for the purpose of saving energy varies along different scenarios. In this chapter the different scenarios will be discussed along with the possibilities for using speed control. First some scenarios with their excavation rate will be reviewed. Second the possibilities for energy savings by using speed control will be considered for every scenario. Last the way in which the belt conveyor is controlled will be discussed, this will also include the discussion on safety procedures.

2-1

Possible scenarios for active speed control

There are all sorts of feed scenarios for belt conveyor systems, however for the purpose of speed control we will discuss three types of scenarios which can be found all over the world. These types of scenarios will not focus on the type of equipment or technique that is used, but on the type of feed flow that is generated for the belt conveyor system. As the feed flow can be constant during all operations, or it might be constant and vary per operation, or either be random and unpredictable. In the next few sections these scenarios will be discussed in detail with examples.

2-1-1 Scenario 1: Constant feed during all operations

Belt conveyors which are fed by a constant feed can be found in all types of operations, for example a bucket wheel excavator in the mines of RWE Germany will feed a somewhat constant flow of material on a belt conveyor. The flow will be dependent on the operator’s experience as well as the soil the bucket wheel excavator is excavating, but overall it will have a very constant flow of mass which always feeds the same belt conveyor. What is important to note in this scenario is that the feed from one bucket wheel excavator will only feed one belt conveyor, thus if more excavators are used side-by-side there will also be more belt conveyors operating side-by-side.

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8 Feed scenarios for belt conveyors

thus there is no variation between operations. As a bucket wheel excavator is only designed for excavating large amounts of material and is not designed for other types of operations. In this scenario the feed flow of the belt conveyor system will be roughly constant and the same during operations. This scenario can be found all over the world in multiple industries, but it is different from the next two scenarios.

2-1-2 Scenario 2: Constant feed varying between operations

As in the previous scenario only one excavator would feed one belt conveyor, this scenario could have multiple feeders on one belt conveyor. The next scenario can be found at EMO in Rotterdam, as the cranes on the dock which unload a vessel feed the same belt conveyor. Every crane produces roughly the same mass flow onto the belt conveyor, again varying with operator, etc. However since one vessel will be emptied by three cranes and another vessel might be emptied by one the feed onto the belt conveyor is constant during operations, but varies between the two operations.

Also different types of operations can be done by one crane, as it can excavate or load vessels, which create constant, but varying, feed flows onto the belt conveyor.

This scenario can be found all over the world, as most of the transshipment terminals will work with belt conveyors which are used for multiple operations and have a somewhat constant feed.

2-1-3 Scenario 3: Random feed

The completely random scenario is that where the feed onto the belt conveyor is completely unpredictable. This could be the case due to the hard working conditions of the extracting equipment of deep coal mines, where the soil might vary so much in density that the feed becomes unpredictable. Or when many operations use the same belt conveyor, with different operation times.

This scenario is more rare, but should be kept in mind when active speed control is to be proven cost-effective. As there are possibilities for saving energy with speed controlling random feeded scenarios.

2-2

Active speed control cost-effectiveness per scenario

As speed control might not be cost-effective for all the scenarios where belt conveyors are used, the advantages and disadvantages of implementing active speed control in the scenarios mentioned in the previous section will be discussed for every scenario.

2-2-1 Active speed control cost-effectiveness for scenario 1

As the feed flow onto the belt conveyor of this scenario is always somewhat constant and doesn’t vary per operation the belt conveyors most energy efficient operation speed can be predetermined and will not vary. This means that the implementation of active speed control will not be suitable for this scenario, as there is no need for changing the speed of the belt

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2-3 Speed control of the scenario 9

conveyor to create a more energy efficient speed. The cost-effectiveness of the implementation of active speed control for this scenario will therefore be very low, as the implementation will cost money but doesn’t effect the energy savings of the system (assuming the correct operating speed is chosen for the belt conveyor).

The feed flow onto the belt conveyor of this scenario is somewhat constant during operations, but since it varies between different operations the most energy efficient speed will also change between operations. This means that the implementations of active speed control will be suitable for this scenario, as the change needed for the most energy efficient operating speed can be realized. Another advantage of this scenario is that the feed flow will be somewhat constant during a certain operation, making the changes in feed flow small. As a large belt conveyor system has many rotating parts and thus a high moment of inertia, changes in the operating speed will take some time. Therefore small changes of the feed flow can be handled and will not significantly increase the risk of either spillage or overloading the system. The cost-effectiveness of this scenario is therefore very promising, as active speed control will have the possibility to save energy during operations with lower feed flows. And since safety factors and expectations in designing a belt conveyor system usually mean the belt conveyor will be designed to be able to cope with peek moments, the feed flow onto the belt conveyor will be lower most of the time, creating more possibilities to save energy and make active speed control more cost-effective in this scenario.

The feed flow onto the belt conveyor of this scenario is completely random, thus the most energy efficient speed will also change constantly. This means that active speed control is suitable for this scenario, however as there are a lot of rotating parts on a belt conveyor system the moment of inertia is very high. This means the response time of the system is slow. Making it able to cope with minor changes in speed, but not large fast changes. Since the feed flow in this scenario is random the changes that are needed in speed might be very large in a short duration, this increases the risk of either spillage or overloading the belt conveyor system significantly. Therefore the implementation of active speed control for this scenario will not be very cost-effective as a lot of safety precautions would need to be in place to be able to save a little bit of energy. Further research within this scenario might prove it to be cost-effective to implement active speed control, but for now this scenario is neglected.

2-3

Speed control of the scenario

For the this research we will use a case study from literature where the feed flow onto a belt conveyor is simulair to the feed flow discribed in scenario 2. In a case study from S. Zhang [11] a belt conveyor is used to feed four coal bins of a power plant. The belt conveyor only feeds one of the coal bins when it is running low, however if two or more coal bins would need to be filled the mass flow over the belt conveyor would change, but still remain somewhat constant during operations. This is very simulair to the scenario 2 discription from this chapter. In this

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10 Feed scenarios for belt conveyors

literature the feed flow onto the belt conveyor is given. However for simulation and research purposes the flowrate and time should be adjustable and it is prefered that the feed flow starts and ends with 0. This is why for this research not the entire feed flow pattern from the research paper of Zhang [11] will be used, but only one operation which can be scaled for research purposes.

Figure 2-1 shows the feed of a 2500 Metric Tonnes Per Hour (MTPH) system running for 1400 seconds, which has the same pattern as that of the case study from the literature. Table 2-1 shows the exact feed and transition times.

0 350 700 1050 1400 0 200 400 600 Time (s) Feed rate (kg/s)

Figure 2-1: An example for feed flow onto the belt conveyor

Table 2-1: Transition times and feed rates

Time (s) Feed rate (kg/s)

0 0 192.5 548.6 225.0 666.6 261.8 694.4 400.4 652.8 782.6 625.0 856.1 611.1 892.9 479.2 926.5 0

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Chapter 3 Speed control of belt conveyors

In this chapter the basic principle of speed control on belt conveyors will be explained. Also a short introduction on the working principle of an induction motor will be given, as well as a model of the dynamics of a belt conveyor system which is used in this thesis.

3-1

Basic principle of speed control on belt conveyors

Speed control on belt conveyor systems has been argued over the past few years in the trans-portation industry, some studies say that it has no chance of succeeding [12] and others that it shows very promising results in early research stages [10]. In this section the standards [13][14] will be used to determine if there is a theoretical possibility for saving energy on belt conveyor systems using speed control.

3-2

Driving force resistances

To determine if speed control can actually be useful on belt conveyor systems the standards [13] Equation 3-1 for calculating the required driving force of a belt conveyor system will be used. F = FH+ FN + FST + FS FH = Primary resistance (N ) FN = Secondary resistance (N ) FST = Gradient resistance (N ) FS = Special resistance (N ) (3-1)

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12 Speed control of belt conveyors

3-2-1 Primary resistance of a belt conveyor

The primary resistance is the sum of all the friction related resistances of a conveyor belt system with the exception of special resistances. The equation for the primary resistance of a conveyor belt system according to the DIN 22101 is:

FH = f gL(m0R+ (2m0B+ m0L)cos(δ))

f = Friction coefficient (−)

g = Gravitational acceleration (m/s2) L = Belt conveyor length (m)

m0_R= Mass of idlers per meter (kg/m) m0_B= Mass of belt per meter (kg/m)

m0_L= Mass of bulk material per meter (kg/m) δ = Gradient resistance (neglected if <18o) (o)

(3-2)

3-2-2 Secondary resistance of a belt conveyor

The secondary resistance is the sum of all the resistances which are independent of the con-veyor belt length. The secondary resistances consists of:

• The feed resistance of the conveyed bulk materials

• The friction between the bulk material and the loading chute • The friction of the belt cleaners

• The detection resistance of the belt at the pulleys

According to Alles [4] the secondary resistance is a ratio of the primary resistance relative to the belt length. This relationship is given in Table 3-1.

The relationship between the secondary resistance and the primary resistance can be de-scribed by the following equation:

FN = (C − 1)FH

FH = Primary resistance (N ) C = Length coefficient (−)

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3-2 Driving force resistances 13 Table 3-1: Length coefficient C dependent on belt conveyor length L (Alles, 1994)[4]

L in m C L in m C L in m C L in m C 3 9.0 80 1.92 250 1.38 700 1.14 4 7.6 90 1.86 300 1.31 800 1.12 6 5.9 100 1.78 350 1.27 900 1.10 10 4.5 120 1.70 400 1.25 1000 1.09 16 3.6 140 1.63 450 1.22 1500 1.06 20 3.2 160 1.56 500 1.20 2000 1.05 25 2.9 180 1.50 550 1.18 2500 1.04 32 2.6 200 1.45 600 1.17 5000 1.03 40 2.4 50 2.2 63 2.0 3-2-3 Gradient resistance

The gradient resistance of the conveyor belt system is associated with the potential energy of a mass according to its height. For a mass flow across a conveyor belt the simple equation of potential energy can be used:

FST = m0LgH

m0_L= Mass of bulk material per meter (kg/m) g = Gravitational acceleration (m/s2) H = Height increase (m)

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3-2-4 Special resistance

The special resistance do not occur at every belt conveyor and are often only a fraction of the primary or secondary resistance (about 1% according to DIN 22101 [13]). This is why the special resistances will be neglected.

3-2-5 Determining driving power

The combination of all the resistances of the conveyor belt system will result in the following total force required to drive a conveyor belt system:

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The total driving force F_tot is related to the total electric power needed to drive the system by:

Pe= vFtot

η

v = Belt conveyor speed (m/s) η = Efficiency of the system (−)

(3-6)

3-2-6 Optimizing energy savings using speed control

However the problem with conveyor belts running as slow as possible is that they overflow and bulk material will be spilled. This is of course not desirable. The optimization of energy savings will therefore be the slowest speed when material is not spilled. This can easily be implemented when mass flows are constant, as the slowest speed where bulk material is not spilled can even be determined by eye.

However when mass flows vary active speed control can be implemented to save energy on the moments that the mass flow does not correspond to the optimal speed of the conveyor belt. Passive speed control as researched by Hiltermann [10] will control the speed of the conveyor belt system when the mass flow entering the conveyor belt system is expected to change, whereas active speed control will measure the entering mass flow and control the conveyor belt accordingly.

Since the Master Thesis will focus on the active speed control of conveyor belt systems it will need to take the dynamics of the system into account. This means a better understanding of the induction motor which powers the system, the frequency converter which controls the induction motor and the acceleration dynamics of the conveyor belt is needed.

3-3

Induction motor

Three-phased induction motors are used to power conveyor belt systems as they are very effi-cient, have low maintenance costs and have a wide range of power. A three-phased induction motor has two main parts, a stationary stator and a revolving rotor. The stator has a cylin-drical core made up of stacked laminations, which each have windings. The rotor also has laminations for either insulated wire windings (wound-rotor motor) or squirrel-cage windings (squirrel-cage motor). In Figure 3-1 an exploded view of a squirrel-cage motor is shown.

The operation of a three-phased induction motor is based upon the application of Faraday’s Law and the Lorentz force on a conductor. This is easily explained in Figure 3-2. Where a magnet moves along a conducting ladder rapidly. A voltage of E = Blv is induced in every conductor because it is cut by the flux (Faraday’s law). The induced voltage will produce a current which will flow in the conductor to the end and back through other conductors. A mechanical force will be experienced by the moving electrons within a magnetic field (Lorentz force) which forces the conducting ladder to move in the direction of the speed of the moving magnet.

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3-3 Induction motor 15

Figure 3-1: Exploded view of an induction motor: (1) motor case (frame), (2) ball bearings, (3) bearing holders, (4) cooling fan, (5) fan housing, (6) connection box, (7) stator core, (8) stator winding (not visible), (9) rotor, (10) rotor shaft. (Courtesy of Danfoss A/S)

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3-4

Speed transition procedures of a belt conveyor

To improve lifetime expectancy of conveyor belts fluid couplings where introduced. This was because the start and stop of a induction motor gives sudden speed changes on the system. When there is a sudden change in voltage and/or frequency, for example when turning the motor on or off, the induction motor will suddenly need to find a new equilibrium. This results in large shocks and accelerations when there is a big difference in the sudden voltage and/or frequency change. The introduced fluid couplings would smoothen out these shocks and accelerations, improving the lifetime expectancy of the conveyor belt. However the fluid couplings are not suitable for fast or controlled speed transitions. Therefore now a days the start and stop procedure of the belt conveyor systems are controlled by Variable Frequency Drive (VFD), which control the induction motor to start smoothly by ramping up the voltage and frequency slowly.

For speed transitions the same method should be used, as a change is speed should not result in a high jerk on the belt. From the research of Daijie He (TU Delft, 2014)[15] we see that speed transitions can have multiple acceleration profiles, which lead to different jerk patterns. In Figure 3-3 the three main acceleration profile of Daijie He his research are shown, the blue sinusoid acceleration, the red deltoid acceleration and the green rectangular accelera-tion. The jerk profiles of these acceleration profiles are shown in Figure 3-4. As can be seen the smoothest of transitions is the sinusoid acceleration profile.

0 0.5 1 −1 0 1 Acceleration timeframe Acceleration factor

Figure 3-3: Three examples of acceleration profiles

This will result in the following equation for acceleration and velocity if there is an original velocity V_b,0. a(t) = π 2 Vb− Vb,0 T a sin π(t − t0) T a , t0 ≤ t ≤ t0+ Ta (3-7)

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3-4 Speed transition procedures of a belt conveyor 17 Vba(t) = Vb− Vb,0 2 1 − cos _{π(t − t} 0) Ta + Vb,0 t = Current time (s) t0= Starting time (s) Vb= Desired velocity (m/s) Vb,0= Velocity at t0 (m/s) Ta= Acceleration time (s) (3-8) 0 0.5 1 −1 0 1 Acceleration timeframe Jerk factor

Figure 3-4: Jerk of the acceleration profiles

If an acceleration profile is selected the maximal driving force on the drive pulley should be determined. This is done by Daijie He using the DIN22101 [13]. Where the permitted maxi-mum acceleration is determined by the nominal rupture force of the specified belt, kN. The DIN22101 states that the quotient between the nominal rupture force and the maximum belt stress kin in the acceleration procedure is no less than the required minimum safety factor SA,min. This factor varies between 4.8 and 6.0 (5.4 is chosen for this research) for different materials of ply (See Table 1 of the article of Daijie He [15]).

Because there is a loss in friction when the force of the driving pulley acts upon the belt conveyor the following equation can be used to determine the maximum driving force during speed control in steady state operations.

FdA,max= _eµα_{− 1} eµα _k NB SA,min µ = Coefficient of friction (−)

α = Wrap of the belt around the pulley (o) kN = Nominal rupture force of the belt (N )

B = Belt width (m)

SA,min = Minimum safety factor (−)

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When accelerating the belt conveyor the driving force needed is equal to the forces to overcome the resistances. Therefore the sum of the motional resistances and the resistance force caused by accelerating is equal to the total driving force. This is shown in Equation 3-10.

FdA = Fd+ Fac

FdA = Peripheral driving force on driving pulley (N ) Fd= Motional resistance (N )

Fac = Resistance force caused by acceleration (N )

(3-10)

The resistance force caused by acceleration can be determined by Newton’s second law of motion. Giving the following equation:

Fac = L(m0R+ 2m 0 B+ m 0 L)a a = Belt acceleration (m/s2) L = Belt conveyor length (m)

m0_R= Mass of idlers per meter (kg/m) m0_B = Mass of belt per meter (kg/m)

m0_L= Mass of bulk material per meter (kg/m)

(3-11)

Combining the resistance forces discussed in chapter 3 which resulted into the Equation 3-5, and the acceleration force of a mass according to Newton’s second law of motion from Equa-tion 3-11 the permitted maximum acceleraEqua-tion during speed control in steady state running conditions can be given.

amax= eµα−1 eµα _k NB SA,min − f CgL(m0_R+ (2m0_B+ m0_L)cos(δ)) − m0_LgH L(m0_R+ 2m0_B+ m0_L) (3-12)

And given a sinusoid acceleration profile, the required acceleration time Ta will be the fol-lowing. Ta,min= π 2(Vb− Vb,0)L(m 0 R+ 2m0B+ m0L) eµα₋₁ eµα _k NB SA,min − f CgL(m0 R+ (2m0B+ m0L)cos(δ)) − m0LgH (3-13)

This maximum acceleration and minimum acceleration time will will be used to create con-straints for a control algorithm. The sinusoid acceleration profile should be implemented into this control algorithm to create a controller which reduced the jerk on the belt and therefore doesn’t decrease the lifetime expectancy of the belt conveyor during speed transitions. This process can be found in chapter 5.

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Chapter 4 Induction Motor Control

To be able to control the speed of the belt conveyor system the torque supplied by the induction motor must be controlled. There are many ways in which an induction motor can be controlled, but for this research the most widely implemented control strategies [16], Field Oriented Control (FOC) and Direct Torque Control (DTC), will be used. In this chapter the working principles as well as the creation of the Matlab SIMULINK models will be discussed.

Figure 4-1: Overview of control strategies

4-1

Induction motor control

Induction motors have to be controlled by a Variable Frequency Drive (VFD) to be able to run at different speeds [17]. As the frequency at which the current vector of the stator is rotated influences the rotating speed of the rotor. Control methods for the induction motor can be divided into two main categories, see Figure 4-1. The motor is either controlled with Scalar Control [18], which only controls magnitudes of the current vector, or with Vector Control, which controls magnitudes as well as angles.

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20 Induction Motor Control

Scalar control is used for simple applications with no feedback from the induction motor. It is easy to implement and does not require heavy computational power. However since it does not use the orientation of the current vector of the stator the dynamic performance is low and cannot handle transitions between speeds very well [3][19]. Since we want to save as much energy as possible and have a lot of speed transitions when performing active speed control this type of control strategy does not work for this research. Vector control type strategies use the orientation of the current vector to calculate the required input for optimal control [3][2]. These strategies have high dynamic performance, but are more complex to implement. In the following sections the FOC and the DTC strategies will be explained. For both of these control strategies the induction motor electrical equations will be needed to estimate or calculate the torque of the induction motor.

Uqs= Rsiqs+ d dtφqs+ ωeφds (4-1) Uds = Rsids+ d dtφds+ ωeφqs (4-2) 0 = Rsiqr+ d dtφqr+ (ωe− ωr)φdr (4-3) 0 = Rsidr+ d dtφdr+ (ωe− ωr)φqr (4-4) τe = 3 2p Lm Lr (φ_driqs− φqrids) (4-5) φqs= Lsiqs+ Lmiqr φds = Lsids+ Lmidr φqr= Lriqr+ Lmiqs φdr = Lridr+ Lmids (4-6)

These equations represent the electrical model of a squirrel cage induction motor. As it is the most commonly used type of motor due to its extreme simplicity and ruggedness. Therefore this motor will be used in this research.

4-2

Field Oriented Control

Field Oriented Control uses the orientation of the rotor flux vector to determine the position of the current vector to create the desired torque of the motor. In the early days Direct Current (DC) motors could only be used for speed control applications as the orientation of the magnetic field of the rotor and the stator are easy to determine. The torque was controlled varying either the orientation of the magnetic fields or the magnitude of the magnetic fields. Unfortunately the DC motor requires a lot of maintenance so that the research into the control of Alternating Current (AC) motor became more popular. The Induction Motor control however is harder as the rotor and stator field have non orthogonal orientations to

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4-2 Field Oriented Control 21

each other and varying orientations per operating condition. However if the orientation of the flux vector of the rotor is measured the input current vector of the stator can be determined. This is done with Direct Field Oriented Control, there is also the possibility to estimate the orientation of the flux vector using the rotating speed of the rotor, which is called Indirect Field Oriented Control. As induction motors with sensors in them that are able to measure the orientation of the flux vector are more expensive then estimating the orientation using the rotating speed of the motor the Direct Field Oriented Control will be discarded and Indirect Field Oriented Control will be used from now on.

To simplify the induction motor model the three phase current vector is transformed into a vector with only two axis (α, β) using a Clarke transformation. This vector could even be simplified more if the speed at which it rotates in used to create two rotating axis which rotate at the same speed making two constant currents, this is known as a Park transformation. These axis are known as the direct- and the quadrature-axis.

These currents (i_ds, i_qs) are used to calculate the estimated torque and flux and transformed back with the reversed Clarke and Park transformations to create a three phase input for the induction motor which create the torque that is desired.

From the main equations of the induction motor model the following equations can be derived, which are used to estimate the idsand iqsfrom the torque (Te∗) and flux (|φr|∗) input reference. The stator quadrature-axis current is calculated using:

i∗_qs = 2 3p Lr Lm T_e∗ |φr|est (4-7)

Where |φr|est is the estimated rotor flux linkage given by:

|φr|est = Lmids 1 + τrs

(4-8)

The stator direct-axis current is calculated using: i∗_ds = |φr|

∗

Lm

(4-9)

In Figure 4-2 an overview of the Indirect Field Oriented Control system is given, as shown the computation of the i∗_ds and i∗_qscurrents can be done using Equation 4-9 and Equation 4-7. However the rotor flux vector orientation estimation is needed to determine the angle θe, which is needed for the Park transformations of the control systems. This angle is calculated from the rotating speed of the rotor (ωm) and the slip frequency (ωsl) using the following equations.

θ∗_e = Z

(ω_m+ ω_sl)dt (4-10)

Where the slip frequency is calculated using: ωsl= Lm |φ_r|_est Rr Lr i∗_qs (4-11)

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4-3 Direct Torque Control 23

The output of the FOC module will be the desired three phase currents for the induction motor. Still transforming the power supply of the net to these desired currents will need steps. This process is known as an AC-DC-AC conversion, using a rectifier and a Low-pass LC-filter to transform the AC to a DC. To change the DC back into a controlled AC an Insulated-Gate Bipolar Transistor (IGBT) bridge is used with pulsed input. The pulses needed for this bridge to invert DC to AC are provided using a Pulse-Width Modulator (PWM), which creates pulses from a three phased input signal. The desired three phase input currents will be converted using a PWM into a pulsed signal from which the IGBT bridge creates the desired three phased currents as input for the induction motor.

This way an induction motor connected to a standard power AC source can have its output torque controlled. And since speed and torque of a dynamic system are directly related the speed can indirectly be regulated.

4-3

Direct Torque Control

Direct Torque Control has another approach to the control of the induction motor. Instead of measuring the flux vector orientation like FOC does it estimates its orientation by controlling the input voltage vector and measuring the current vector of the stator. DTC does not use the d- and q-axis that are orientated on the rotating rotor, but instead uses the stationary α-and β-axis of the stator (because there is no feedback loop in DTC all measurements must be done at the stator).

From the stator voltage and current vectors the stator flux vector is determined. This flux vector is used to estimate the torque of the motor and determine the next orientation of the input voltage of the induction motor. This is done by using a switching table and two hysteresis controllers (one two level for the flux and one three level for the torque), hysteresis controllers determine from the input error an output of either +1 or -1 (for a two level) or a +1, 0 and -1 (for a three level). The input error is measured from the referenced state and the current estimated state.

The angle of the stator flux vector is used to determine the sector in which the flux currently is in as shown in Figure 4-3, using the error of the torque and flux through the hysteresis controllers we can determine the switching position using Table 4-1. The corresponding voltage vector of the switching position for the three phase voltage input of the induction motor are given in Table 4-2.

In Figure 4-4 the dashed line shows the DTC module. Here the stator flux and the torque are calculated from the input voltage and current vector of the stator, which are compared to the reference state for comparison. The stator flux is obtained by integrating the motor emf vector using Equation 4-12.

~

φ_s= Z

( ~Vs− RsI~s)dt (4-12)

Where the voltage vector is calculated using: ~ Vs= 2V_dc 3 [Sa+ Sbe j2π/3_{+ S} cej4π/3] (4-13)

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Figure 4-3: Sector division [3]

Table 4-1: Basic DTC switching table

Sector 1 2 3 4 5 6 dλ = +1 dT = +1 ~u2 ~u3 ~u4 ~u5 ~u6 ~u1 dT = 0 ~u0 ~u7 ~u0 ~u7 ~u0 ~u7 dT = −1 ~u6 ~u1 ~u2 ~u3 ~u4 ~u5 dλ = −1 dT = +1 ~u3 ~u4 ~u5 ~u6 ~u1 ~u2 dT = 0 ~u7 ~u0 ~u7 ~u0 ~u7 ~u0 dT = −1 ~u5 ~u6 ~u1 ~u2 ~u3 ~u4

Table 4-2: Corresponding voltage vectors of switch positions

Sa Sb Sc ~ u0 0 0 0 ~ u1 1 0 0 ~ u2 1 1 0 ~ u3 0 1 0 ~ u4 0 1 1 ~ u5 0 0 1 ~ u6 1 0 1 ~ u7 1 1 1

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4-3 Direct Torque Control 25

And the current vector is calculated using: ~ Is= 2 3[ia+ ibe j2π/3_{+ i} cej4π/3] (4-14)

The flux vector and the current vector are used to determine the torque of the motor using Equation 4-15.

Te= 3

2p( ~Is• j ~φs) (4-15)

The same way as with FOC the AC-DC-AC converter will be used and the voltage input signal will be converted by a PWM into a pulsed signal which is fed into the IGBT bridge. This way the motor torque can be controlled using only the input signals of the motor, making DTC a much faster control method. However because DTC used the switching table and the hysteresis bandwidth (when something is considered +1 or -1 by this controller) the calculated flux vector does not follow the desired flux perfectly creating an uncertainty in the torque (a so called torque ripple). Since the flux vector orientation is included in the feedback loop of a FOC module it can determine the input voltage vector more fluently which results in a smaller torque ripple. The DTC module can improve the hysteresis bandwidth and reduce the torque ripple, however this would mean a drastic decrease of the sample time of the DTC module and thus an increase in computional power.

The two control strategies of an induction motor have their advantages and disadvantages. In the next chapter both strategies will be compared using simulations of Matlab SIMULINK to see if there is a difference in the energy consumption of a belt conveyor system using one of the control strategies.

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4-4 Improvements for induction motor control 27

4-4

Improvements for induction motor control

To be able to use the induction motor control strategies provided in this chapter for active speed control on belt conveyor systems some adjustments will have to be implemented. The control strategies are focussed on following a referenced torque pattern, however if a speed pattern is more desirable the control strategies simply implement a PI-controller. This con-troller uses the error of the referenced speed and the measured speed to output a torque for the control strategy. This torque is simply higher than the torque generated by the resistance forces on the induction motor if the reference speed is higher than the measured speed and lower when the reference speed is lower than the measured speed, with the possibility to limit the minimum and maximum torque that is put on the induction motor.

For active speed control however a simple PI-controller will not be sufficient to be able to control the speed correctly, as there are a lot more constraints on the belt conveyor system that need to be honoured. Where as a PI-controller is a very simple and highly efficient controller it does lack the possibility to implement multiple constraints. This is where Model Predictive Control (MPC) comes into play. MPC is used when multiple inputs and outputs of a system have multiple constraints on them and a cost-function is used to determine the path of least resistance. This type of control could be implemented before the PI-controller to regulate the referenced speed. The speed of the induction motor could then be controlled without altering the control strategy.

Unfortunatly the MPC cannot incorperate specific scenarios where it has to change its out-put. As if linearizes the system and stays within its boundaries provided by the contraints it cannot handel a specific scenario where it should function outside of its boundaries. Since there are different scenarios for the speed controller; controlling a loaded belt, discharging the belt, start and stop procedures, etc. the MPC cannot handle the entire control scope of the belt conveyor system. This is why a controller will be implemented which can operate in all these different scenarios, but still honours all the constraints that are put on the system. This type of control is known as Programmable Logic Control (PLC) and is based on the decision tree the programmer implements into the controller.

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