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Abstract—Nowadays, the use of prepayment water meters is becoming more prominent in certain parts of the world, such as Asia, Africa and South America. Thus, the development of new methodologies for controlling and reading water consumption in households is in line with scientific and economic reasons, and not only due to social awareness. Therefore, upon these beliefs, it was raised the decision of studying and developing a system capable of managing the water supply passing through a conventional water meter, which would be already installed on an arbitrary residence. This project was set under a partnership between IST and Resul, and it was carried out during this master’s thesis period. The line of work was divided in two main courses. The first one was focused on the project of an electro-mechanical actuator, to be installed on a solenoid valve, which would be applied in parallel with a conventional water meter for water flow delimitation purposes. There were some electrical characteristics under attention during this study, such as the electromagnetic force, the power consumption, the magnetic saturation and the temperature variation, besides all aspects concerning mechanical, electric and thermal dynamics of the actuator. The second line of work was centered on developing a system to obtain the water metering measure, via a non-intrusive methodology. Afterwards, it was mounted a solenoid valve to restrict the water flow, and created a control and energy supply circuit, for all the equipment used in the prototype.

I. INTRODUCTION

N the present days, it is becoming more common the use of prepayment water meters, in households centered on

African, Asian and South American continents. The water transactions needed for the equipment to work, are ruled by the Standard Transfer Specification (STS), which is the only globally accepted standard that guarantees the interoperability between system components of different manufacturers. As of now, there are several prepayment water meter technologies on the market that suffice the requirements needed to operate with the STS, but some of them lack in reliability. Therefore, it is important to develop a new prepayment water metering concept that is both reliable and fit to be implemented on already installed conventional water meters [1].

This ideology brought together Resul – Equipamentos de Energia and Instituto Superior Técnico (IST), in order to

investigate the possibility of converting a conventional water meter into a prepayment water meter. This effort was translated in the form of a Master Thesis, from which were drawn the lines of work and final conclusions presented in this paper.

This Master Thesis was separated in two main fields of work. The first one was focused on the project of a solenoid valve, to be installed in parallel with a conventional water meter, for a water flow adjustment process. Therefore, this project paid a more detailed attention to the electromagnetic actuator part of the valve, which should be capable of working on an ON-OFF mode, controlled by a PWM signal, and thus permitting a delimitation of the water flow to a small percentage of its nominal value. The task consisted of a preliminary hydraulics investigation, followed by the conceptualization of geometric designs for the electromagnetic actuator. Afterwards, it was mounted a simulation on a graphical programming environment Simulink©, that helped studying the dynamics of the mechanic, electric and thermal parts of the system. The study was concluded by a parameter optimization to minimize the volume of the actuator and the power it would need to run.

The second line of work of this thesis consisted on the construction of a prototype that would allow the conversion of a conventional water meter into a prepayment water meter. In this context, the work started by a study of a know-how the water meters work, followed by the development of a non-intrusive method for acquiring the mechanical metering registered by the water meter, and subsequent conversion into digital data. Afterwards, it was coupled a solenoid valve with the water meter, and mounted an electronic circuit for controlling the valve and interpret the data related to the water consumption, which used a microcontroller. Lastly, it was installed a power supply for the equipment and some tests were ran on a hydraulic circuit, assembled on the Hydraulics Laboratory, of the Civil Engineering Department.

II. ELECTROMAGNETIC ACTUATOR PROJECT

N order to begin the project of the electromagnetic actuator it is necessary to understand the difference between the

concepts “solenoid valve” and “electromagnetic actuator”. In this paper, it is understood as “electromagnetic actuator” the upper portion of a solenoid valve, formed by the magnetic circuit and the solenoid (see Figure 1). The dimension of the

Project of an Electromagnetic Actuator for water flow adjustment in Prepayment Water Meters,

using the STS standard

Valter L. D. Jardineiro, Student DEEC/AC Energia, Paulo J. C. Branco, LAETA/IDMEC

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lower part of the valve, through which the water flows, wasn’t approach during this project, since its project concerns a mechanical scope. Therefore, since the dimensions of this lower portion were needed for calculations concerning the water forces put into play, some usual dimensions of existing valves were used, for simulation purposes [2]. All the remnant geometry, including the magnetic circuit of the actuator, was devised, so that the valve would function as a “direct action normally-open valve”. This type of valve is meant to close only when supplied with a voltage signal, and act upon the water flow directly, without the assistance of membranes, as happens in more complex valves.

Figure 1 - Section of the solenoid valve designed for this project,

with the electromagnetic actuator mounted on top

In this context, it is important to refer that all the parts represented by light gray are made of ferromagnetic material, while the solenoid is made of copper wire capable of resist a temperature rise of 80ºC [3]. After the valve is closed, if the voltage signal is withdrawn, the piston retracts to its original position not only due to the water force, but also because there’s a spring allocated on the top of the actuator, assisting the movement. Following this line of work, a hydraulic study was conducted, to calculate the water force on the central point of the valve, since it is the point where the electromagnetic actuator suppresses the water flow. This process was conducted making use of Bernoulli’s Equation for incompressible fluids. Considering that the height difference between the entering point of the water flow and the acting point of the actuator is negligible, this equation can be set as:

����� � 12��� � ���� � 12�� (2.1)

Thus, the pressure between the two points is only dependable of the velocity of the water. Afterwards, considering the continuity equation for fluids, it is possible to set the velocity on the first point as a variable of the velocity on the second point, such that[4]:

� � ��� (2.2)

Finally, considering that the water flow is defined as the product of the velocity by the section through which passes the water, conjugating both (2.1) and (2.2), it is possible to calculate the water pressure on the actuator closing point. The force exerted by the water on that point is then given by the product of the pressure by the section:

�� � �� � � ��� � 12� ����� �1 � �����

�� (2.3)

For these calculations it was considered that the entering section of the valve equals the biggest section of the water meter samples given by Resul; consequently, the water flow value was assumed to be the maximum water flow permitted by the same water meter. As for the entering pressure, it was used the value under which the water meter would be set in the worst condition: 6 Bar (parameter stated by Resul).

A. Electric, Mechanical and Thermal Dynamic Equations

In order to build a simulation model of the electromagnetic actuator, it was necessary to understand three main aspects of its dynamics. Therefore, it was defined a first model ruled by three dynamic equations, set upon some simplifications. In this first model there was no consideration of the magnetic saturation processes, and the thermal model was defined by a simplified model used for electric machinery, presented by [5]. The electric equation that defines the electromagnetic actuator is given by [6]:

� � �� � � ���� � � ���� ���� (2.4)

Since the voltage, �, is a controlled parameter which will be set, and the current, �, is the dynamic parameter, the only remnant parameters that must be calculated are the resistance, R, and the induction coefficient, L, of the copper winding. The resistance can be easily calculated through:

� � �� !"��#$ (2.5)

Where, �� is the copper conductivity, ! the winding length, and "��#$ its section. However, it is important to understand that, since there’s a current flowing through the copper winding, there are going to be power losses, due to Joule heating, which will lead to a temperature rise. This increase varies the copper conductivity value, accordingly to:

�� � �� %&1 � '() � )%*+ (2.6)

Where, �� % is the copper conductivity at 20ºC, and ' is a constant. On another hand, since the winding length is dependable of the number of coils of the solenoid — and these are set according to the dimensions of the actuator —, it would be useful to define an expression that would translate the length of the wire in terms of the actuator dimensions and number of coils, ,. Thus, it was derived a formula to calculate this

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length, after establishing some conditions concerning coils distribution around the central axis of the actuator. The full explanation can be read on [13]. The final definition of the winding length is given by:

! � - .,/ � ,� 0 21��2�34567�89% : (2.7)

Where ;��< defines the number of coil layers surrounding the central axis of the actuator; ��2� is the diameter of the wire; and / is the diameter of the thickest part of the central piston that forms the axis of the actuator. Here, is also taken the chance to define another physical dimension of actuator (width), which is given by some of the last referred parameters: = � 2> � / � 2;��<��2� (2.8)

With s being the thickness of the iron armature that forms the magnetic circuit. After defining this set of variables, the next step concerns the induction coefficient, L, calculation. For this, it is necessary to analyze the magnetic circuit of the actuator, which can be done, by applying Ampère’s Law:

? @A �! � B CD ,E �" (2.9)

Figure 2 - Magnetic circuit of the electromagnetic actuator

(neglecting magnetic saturation)

The magnetic path for the circuit is marked on the Figure 2. It must be pointed out that, on the central axis, even though the lower portion of the piston is formed by non-ferromagnetic material, the magnetic path is kept on a straight line for simplification purposes concerning calculations. This is only pertinent once the magnetic saturation is considered, and will not cause issues if the section value for this stretch comprises only the area of the surrounding ferromagnetic material (further and thorough explanation can be read on [13]). Applying the Ampère’s Law to the circuit, neglecting magnetic saturation and attending to the magnetic flux definition given by [7], it is possible to describe the magnetic flux as:

G � ,�H$"$(I$ � �* (2.10)

Recalling the definition of flux linkage, given by [7], it is

possible to define the induction coefficient of the winding as:

� � ,H$"$(I$ � �* (2.11)

The system’s second dynamic equation — the mechanical equation — can be expressed in terms of the sum of forces put into play. Hence, the mechanical equation is presented as:

JK � �� � 1� � ����� (2.12)

Where JK is the electromagnetic force, �� is the water force, 1 is the spring constant, and � is the piston’s mass. It should be kept in mind that during this project, the positive direction of movement was considered to be the downward direction. In order to use the (2.12) equation, it is necessary to calculate the electromagnetic force value, which can be obtain through the analysis of the magnetic circuit. Recalling the definition of the magnetic energy, given by [7]:

L< � M � �N (2.13)

It is possible to calculate the electromagnetic force, knowing that it is defined as the negative value of the magnet energy’s derivative in order to the movement. For the actuator studied in this project the electromagnetic force is then described as:

JK � ��L<�� � � ,�H$"$2(I$ � �* (2.14)

As for the spring force, it is a parameter which has some adjacent subjectivity. In this specific case, the water is always going to be under pressure, which means that in a situation where the voltage signal is withdrawn, the water force is enough to bring the piston to its initial position. Therefore, the spring it’s going to act only as cushion during the closing movement of the piston. Nevertheless, the spring must still be characterized by a constant. As it is, it was presumed as an initial approach that the spring should be capable of retracting the piston during a hypothetical case, in which there was no water force present. By postulating such condition, it is possible to calculate a minimum value for spring constant, using the following expression:

1 O �P��QR�K (2.15)

Where P is the gravitational acceleration and ��QR�K the position in which the piston is farther from the initial position. Lastly, a third equation concerning thermal dynamics should be defined, before trying to model and simulating the actuator behavior. As such, for a first simplified model, it was used a thermal equation usually used for electric machinery, presented by [5]. This model is set upon the following initial condition:

ST � S� � SU (2.16)

In which ST are power losses, S� is the thermal power accumulated inside a body, and SU is the thermal power traded with the external environment. Then, considering that the power transfers can be split into conduction losses and convection losses, each characterized by its own coefficient;

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and that the accumulated power can be defined by the thermal capacity of the material and the temperature variation, the expression (2.16) can be manipulated into a differential equation that stipulates the temperature dynamics:

VW �∆)�� � ∆) � STYJ�J (2.17)

Where YJ is a coefficient that takes into account the convection and conduction coefficients; �J is the exposed area through which are set the thermal power transfers; and VW is the thermal time constant, defined in terms of YJ, �J, and the thermal capacity of the material, C. A more detailed explanation is given on the [13].

B. 1st Simulation Model

After establishing all three dynamic equations, they were translated under the form of a Simulink© model, through which was analyzed the behavior of the different parameters inherent to the electromagnetic actuator. Since there was no optimization concerning the actuator physical dimensions at this point, the simulation was feed with typical values of a solenoid valve present in the market [2]. On a first instance, it was applied to the system a voltage step strong enough to close the valve in under a 1 second period. The current evolution obtained is presented in Figure 3 and an explanation concerning the momentary current drop around the 0.45s instant should be given.

Figure 3 – Current evolution after applying a step voltage to the

system

As it is, from the moment the voltage step is applied (0.2s) until the instant 0.35s, the current keeps increasing, making the electromagnetic force increase accordingly (see (2.14)). Around the moment 0.35s, the electromagnetic force becomes strong enough to suppress the water force and the valve closes. This occurrence implies a fast reduction on the actuator air gap, defined as I in the Figure 2. This leads to a fast increase on the induction coefficient, and since both the resistance and voltage values are kept constant, there must be a decrease on the current amplitude so that the differential equation (2.4)

keeps its veracity. Also, it should be noticed that the term UZU[

rises momentarily, since the piston’s movement induces a speed increase. That’s another factor that has to be

compensated through a current reduction, thus explaining the current drop. Afterwards, the current rises again because the piston becomes immobilized after closing the valve, thus eliminating the effects of the velocity and the derivative of the induction coefficient in the electric equation. Since the voltage value is kept the same, the current increases to compensate the fading of these terms. This behavior is in order with [6]

Figure 4 – Electromagnetic force evolution after applying a step

voltage to the system

In Figure 1 it’s also possible to verify the behavior of the electromagnetic force, for the same time interval. A most pertinent observation should be given around the instant 0.35s: it is noticeable that, even though the current falls at this point, the force is increased in a much larger ratio. This is explained with the decrease of the air gap, which establishes an inverse quadratic proportion with the electromagnetic force. Lastly, an analysis is given to the increase on temperature due to power losses, for two separate situations: one in which it is applied a continuous voltage signal through time, and a second where the actuator receives pulses of 2 seconds period time, with a 50% duty-cycle. For both situations, even though the temperature increases exponentially, it is clear that for the situation in which the actuator is working with voltage pulses, the maximum temperature reached was the lowest. The maximum values of temperature registered for both situations had a rough percentage difference of 40%. Also it is noticeable that during the voltage pulse situation, the temperature keeps increasing through gradual steps. Both conclusions prove the behavior described in [5].

C. Magnetic Saturation and 2nd Simulation

After analyzing the preliminary behavior of the actuator via the first simulation, the following step consisted on taking into account the limitations imposed by the magnetic saturation of the ferromagnetic material. The saturation processes are relevant during the project of such actuator, because once the ferromagnetic material enters the saturation zone, it is

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necessary to provide greater current amplitude to raise the magnetic flux, by the same amount it would increase on a no-saturation zone. Therefore, an uncontrolled increase of the current might lead to bigger power losses (translated in the form of temperature rise), that might put in danger the material safety. Hence, in order to consider the saturation processes, it’s necessary to review the equations of the magnetic circuit, considering different zones of the actuator where the magnetic flux intensity is different.

Figure 5 - Magnetic circuit, showing zones with different

magnetic flux intensity

As it is shown in Figure 5, there are three zones with different magnetic flux intensity: the “purple zone” is characterized by a section of radius c and the iron magnetic permeability, H�J; the “orange zone” is characterizes by the section given in “red” and the air magnetic permeability, H$; and the “blue zone” is characterized by the “red” section and the iron magnetic permeability. It is also important to refer, that the actuator is dimensioned so that the magnetic flux density is kept the same throughout the entire “blue zone”; is this wasn’t established as a condition the calculations presented on this thesis would lose coherence. On another note, by paying attention to Figure 6, is possible to understand how this condition can be set: the flux density maintains its valor on the entire “blue zone”, if the exterior part of the iron armature of the actuator is dimensioned so that its section equals half of the red section given by Figure 5. To do this, it’s necessary to size the measure “z” (see Figure 6) such that:

\ � "$2> (2.18)

Where "$ represents the “red” section. After establishing this condition, the use of the Ampère’s Law (2.9), results in:

]^H�J !^T�[_ � ]$H�J !T�[_ � ]$H$ I � ,� (2.19)

Where ]^ is the magnetic flux density on the “purple zone”; ]$ is the magnetic flux density of the “orange and blue zones”; and !^T�[_ and !T�[_ are the magnetic paths marked in dark blue and red, on the Figure 5, respectively.

Figure 6 – 3D inside view of the electromagnetic actuator

Since the magnetic flux density, ]$, is the first one to reach saturation (lower section), if it is guaranteed that ]$ doesn’t saturate, the rest of the ferromagnetic material doesn’t come to saturation. The implementation of the saturation concept in the simulation was done by adding a block that calculates continuously the value of the iron magnetic permeability. Hence, this block uses a programmable function (where the data points of the iron magnetic saturation curve are stored), fed with the piston’s position and current of the system, and keeps calculating the values of magnetic flux density and intensity, during a continuous time simulation.

D. Lumped Element Thermal Model and 3rd Simulation

After entering the concepts of magnetic saturation, it was necessary to describe the thermal evolution of the system through a more specific model, than the general concept used for electric machinery. Therefore, it was developed a lumped element model, to characterize the heat transfers taking place in the electromagnetic actuator. To understand this type of model it is necessary to elaborate on the analogy established between electric and thermal parameters. On a thermal lumped element model, the resistors represent conduction and convection energy transfers; the capacitors are seen as the thermal capacities of the materials; the voltages are equivalent to temperature values; and the currents represents heat injections in the system. These heat injections can be calculated as power losses, given by Joule heat. In order to apply this ideology, the electromagnetic actuator should be remembered to have cylindrical geometry, and, therefore, it can be described as a multi-layered mass, in which heat transfers happen from the central axis to the outer limit. That way, the lumped element model is going to be described by four layers. The first one concerns the mass of the central piston; the second one represents the copper winding; the third one is set as the mass of insulating used in the copper wire (and this is one of the most important layers, since is a place where the heat is retained the most); and the forth layer represents the outside iron armature of the

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magnetic circuit. As it is, there is going to be one resistor to represent each of these layers in the circuit of the lumped element model. It should be noticed in Figure 7 that the resistor which represents the copper winding was split in two, so that it was possible to set a current source in between the two; this current source stands for the power losses due to Joule heat. As for the last resistor, Rconv, it represents the convections transfers between the actuator and the external environment, and is the one which assumes higher value on the circuit.

Figure 7 – Electromagnetic actuator equivalent thermal lumped

parameter circuit

After defining the elements that constitute the model, since all layers transfer heat radially, a resistor’s value that has no internal heat production can be given by [8]:

��$RU � � 12-`�K� ln �cc�� (2.20)

Where �K represents the length of the cylindrical structure; c� its inner radius; c its outer radius; and ̀ the thermal conductivity of the material. Through this expression, it is possible to calculate the numerical values of the resistors representing the layers of iron and insulating material. However, for a resistor in which there is internal heat production (such as the resistor that stands for the copper layer), it must be applied another expression, given by [9]:

��$RUT � 14-`�K �1 � 2 c�c � c� ln �cc��� (2.21)

Finally, the resistor concerning the convection transfer is calculated via:

��$Re � 1Y�e�J (2.22)

Where Y�e is the convection transfer coefficient. Also, the thermal capacities of the materials can be found using:

f � /�<g (2.23)

Where / is the specific heat capacity, �< is the material density and g its volume. This lumped parameter model was incorporated in the previous simulation instead of the simplified model for electric machinery. The circuit acts as an electric circuit in a physical system environment that is connected with all the other blocks of simulation via a “physical signal to Simulink signal” converter. To test this model, it was a applied a voltage step to the system, which kept it fed for 7000 seconds, until the temperature reached its limit (see Figure 8). As it is shown, the temperature evolves exponentially, just like the previous system; however, the temperature reached a much higher

elevation, mainly due to two of the resistors: the one concerning the wire insulation and the one simulating the convection transfer.

Figure 8 - Temperature elevation evolution, after applying a step

voltage signal

E. Optimization of parameters for the electromagnetic actuator

Once all parts of modeling and simulation were set correctly, the final step comprised a parameter optimization, in order to reach two main objectives: reduce the power consumed by the actuator and minimize the volume occupied by the materials. However, these objectives should be in order with certain constrains that would guarantee the correct operation of the actuator. As such, three constrains were imposed: (1) the electromagnetic force should be strong enough to oppose both the water strength and the spring strength on the point the piston is farther form the initial position; (2) the magnetic flux density,]$, should not surpass the 1.2T barrier, since that point establishes the beginning of magnetic saturation; (3) the temperature rise should not exceed 60ºC. This last condition was set as a preventive measure, since the magnet wire was capable of supporting 85ºC of temperature rise. However, as it can be seen ahead, the temperature rise is calculated based on an approximation, thus the reason for prevention. Once the constrains and objectives were set, finding the values for the electromagnetic force and for the magnetic flux density could be done using the equations developed in the previous sections; however, an expression to calculate the temperature rise was still amiss. It should be noticed that until this point every conclusion concerning temperature rise was drawn from simulation and never from an actual calculation. Nevertheless, there is an expression that defines the current density that can flow through a winding, in terms of the temperature rise it is capable of supporting [10]:

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C� � �2Y�e∆)�� �1E��/

(2.24)

If this expression is rearranged and fed by the current density value that passes through the wire, then an approximation to the factual temperature rise can be given, in the form of:

∆) � �� �1E2Y�e � 4i-��2�� (2.25)

It should be noticed, however, that this expression will lead to slight greater values than the actual value of the temperature rise. Nevertheless, it constitutes a way of defining the last constrained through an actual formula. Once the constraints and objectives were defined, the following step consisted on describing them through a set of variables. After some mathematical manipulation, it was possible to describe all the objectives and constraints in terms of five variables: (1) ‘a’, height of the actuator; (2) ‘n’, number of coils; (3) ‘u’, voltage applied; (4) ‘e’, diameter of the thinnest part of the piston; (5) ‘c’, diameter of the thickest part of the piston (see Figure 5). The optimization problem is then defined as:

min�,R,J,�, g��[ �U$m(2, ,*;i(2, ,, �*

>�=op/��q ]$(2, ,, /, p, �* r 1.2; J(2, ,, /, p, �* t �� � <$K�∆)(2, ,, �* r 60 Where g��[ �U$m is the actuator volume and i is the maximum current value (which occurs after the closing of the valve). To solve the optimization problem it was used a Matlab© program that runs a multi-objective genetic algorithm, named “NSGA-II Program in Matlab”. For a quick introduction, genetic algorithms start by giving random values to the variables of a problem, thus creating a random population of solutions. From those solutions, those that better fulfill the constraints are chosen to breed a new generation of solutions. After every generation, the solutions tend to an optimized generation of solutions, comprised under an optimization curve. This means that there’s no solution better than other: only solutions that fulfill better an objective than the other. For this particular case, the genetic algorithm was set to run for 500 generation, with 250 elements each, until there was convergence to an optimization curve. As for the variable intervals under which the algorithm should procure solutions, were set as follow: for the height ‘a’, the maximum acceptable value was of 7 cm; the number of coils were restricted to a maximum of 1100, since a bigger number would lead to an actuator width that would largely surpass the height, thus making a disproportional actuator; the voltage was given an interval of [7;15]V; as for the diameters ‘c’ and ‘e’, is was set the interval limits [1;2.5] cm and [2.5;3] cm, respectively, so that the central piston wouldn’t expand too much the width value of the actuator. However, a initial run of the algorithm prove it to be impossible to find a space of solutions that would fulfill all constraints and variable limits. Hence, it was necessary to ease the constraints values, in order to find a

solution. Thus, the new constraints were set as: ]$ r 1.82,� ∆) r 80 (2.26)

This new limit for the magnetic flux density is situated on the saturation zone, but if the current value is restricted so that the temperature rise doesn’t exceed the temperature limit the wiring can withstand, then the saturation effects don’t damage the material. After setting these new constraints, it was obtained an optimization curve, with a set of 250 solutions. Afterwards, the variable values of each solution were run through the simulation to verify the proper actuator operation. For every single solution, the temperature rise was seen to be slightly lower than the one calculated by the genetic algorithm, and the current showed an increase in 100mA. Besides, even though this constituted a first step towards optimization, a second methodology was used to prove the obtained results. Since both simulation and genetic algorithm were developed in Matlab© environment, is was decided to run the genetic algorithm fed by the results of the simulation, instead of calculating the actuator parameters via equations. For this methodology to work, the genetic algorithm must run a 1 second simulation for every element of a population, thus delaying the optimization process. However, the temperature and current values obtained for each set of variables is much more precise and leads to better results.

Figure 9 - Optimization curve using the genetic algorithm in parallel with the simulation

The optimization curve obtained through this method can be observed on Figure 9. For the optimal set of solutions, it was verified that as the power consumption decreases, the volume of the actuator increases. Also, this volume increment is characterized by a decrement of proportionality between the height and width of the actuator, meaning that when the volume is the largest, there is the largest length difference between height and width.

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III. CONVERSION OF A CONVENTIONAL WATER METER TO A

PREPAYMENT WATER METER

The second part of this thesis concerned some equipment applications on a conventional water meter, with the goal of converting it into a prepayment water meter. Therefore, the first step consisted on finding method for acquiring the mechanical record of the water consumption, and transform it into digital data. In this context, it was identified the existence of a reflective pointer in every water meter sample made available by Resul. Through further study, it was discovered that every rotation of this pointer was equivalent to a dm3 of water consumption. As such, it was developed a method of counting the number of pointer rotations, through the use of a optical reflective sensor. This optical sensor is set over the tip of the pointer and outputs and analog voltage pulse following each rotation. This pulse is then sent to a comparator for an analog-digital signal conversion. The output of this comparator is made to be 5V (digital 1) if the voltage is greater than 3.125V, and 0V (digital 0) if not. The circuit mounted for these operations can be seen on Figure 10.

Figure 10

The digital signal outputted by the comparator is then sent to a microcontroller board, Arduino, which keeps count of the number of pulses received, thus registering the water consumption. As a whole, each water dm3 consumed corresponds to a pulse that is counted by the Arduino. This value is then stored into a variable, that might be accessed later. Also, since one pulse corresponds to fixed water measure and the Arduino is capable of register time intervals, it is possible to calculate the instantaneous water flow value, each time the Arduino receives a pulse. On a side note, it must be referred that the microcontroller Arduino functions on a C++ program base, and can output 5V digital outputs, besides receiving them. This way, it was possible to use the Arduino for further operations. The next step consisted on testing the water metering reliability measured by the Arduino. For this, it was constructed a hydraulic circuit on the Hydraulics Laboratory of the Civil Engineering Department, where several trials were run for different water flow conditions. The trials revealed two counting errors that had to be dealt with. The first one was due to fast undesirable impulses, caused by trepidation or

undesirable reflexes. However, these impulses were so short that the water flow value calculated by the Arduino surpassed the limits accepted by the water meter. Hence, it was established that the Arduino should ignore pulses that led to water flow values that surpassed 2 dm3/s. This action solved the first measuring error. Nevertheless, there was a second error recurrent for small water flow values. This second error was related to the evolution of the analog signal outputted by the optical sensor. Since the analog output value depends on the quantity of light that is reflected, for small water flows it takes a long period for the full metal tip of the pointer to be placed under the sensor. In other words, it takes a much longer period for the analog output to reach the maximum amplitude, on a small water flow situation. As such, the analog signal presents a gradual amplitude increase; but, since it is an analog signal, sometimes there’s a slight voltage drop during the evolution. If this drop occurred around the voltage value 3.125V, the Arduino would register and erroneous pulse. To solve this problem, it was set a condition establishing that the Arduino could only register a pulse, if a certain time interval had already passed since the last registration. Further explanation can be read on [13]. After solving these two issues, all the metering measures done by the Arduino, during trials, kept the same precision as the mechanical metering done by the water meter (see Figure 11).

Figure 11 – Comparison between Arduino registering and the water meter mechanical registering (trial results comprising smaller water flows are present on [13][13])

Once the metering system was outputting reliable data, it was necessary to install a device which could adjust the water flow running through the water meter. For this application it was acquired a solenoid valve, meant to be controlled by a PWM signal. This way, the valve would work on a cycle ON-OFF, thus restricting the water flow to a small percentage of its value. It should be noticed at this point that the solenoid valve acquired for this purpose was a “normally closed” type, due to a strategic decision made by Resul. At the beginning of the project, a “normally open” solenoid valve was supposed to be implemented (which is in accord with the project presented in section 2), since the water supply would be on most of the time. For this case, a normally open solenoid valve would be the most adequate, in order to reduce power consumption. However, if a “normally open” valve was used, considering a hypothetical scenario in which the valve was supposed to

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suppress the water flow, a cut on the power supply would mean the continuation of the water supply. Since this was an undesirable situation, for safety reasons, it was decided to use a “normally closed” solenoid valve. The solenoid valve acquired works with a 9V-DC power supply, and it is controlled through a control circuit and a PWM signal generated by the Arduino board.

Figure 12 – Solenoid valve control circuit (adapted from [12])

As it is shown in Figure 12, the 9V-DC power supply is connected to a relay that closes the solenoid valve supply circuit each time the Arduino signal is outputted as digital 1. That way, it is possible to create the cycle ON-OFF that will open and close the solenoid valve, thus adjusting the water flow. As for the power supply, since the Arduino can work with the same voltage amplitude as the solenoid valve (9V), it was acquired a transformer that could feed both the Arduino and the solenoid valve. As for the 5V needed by the electronic circuit pieces, they are supplied by the Arduino which possesses a 5V output. The current consumption of these electronic circuits, along with the Arduino board, sum up to 150mA. Also, it was measured a value of 100mA for the current consumption of the solenoid valve, while applying a continuous voltage signal. Since the transformer acquired is capable of supplying up to 500mA, it is an adequate power supply for the whole system. Lastly, it was developed a way of adjusting the water flow through an operation cycle ON-OFF of the solenoid valve, which is controlled by a PWM signal generated by the Arduino. It is important to make notice that for different water pressures, the water flow is going to exhibit different behaviors, and thus, a different PWM must be used. However it is also important to refer that this is a methodology that produces good results, when the water at the entrance of the water meter is kept under the network’s pressure. That way, the pressure guarantees a water flow strong enough to supply the household, even after the water flow delimitation. On the other hand, if the entrance pressure is not strong enough the delimitated water flow is not going to have enough pressure and continuity for supplying water through the pipes. Figure 13 shows the final prototype of the conventional water meter turned to a prepayment water meter

Figure 13 – Final prototype of a conventional water meter turned to a prepayment water meter

IV. CONCLUSIONS AND PROSPECTIVE WORK

In this last section it is taken the chance to compare results from sections II and III, and to present some future work that might be conducted in this field of expertise. The first conclusion that must be drawn is in order with the power consumed by the solenoid valve projected on section II and the one used in section III. The valve projected consumes a minimum power of 16W, while the one installed on the water meter consumes 0.9W. This difference is explained by the volume difference between the actuators; however, it is important to understand why this volume difference occurs. While the actuator dimensioned in section II is meant for a direct acting solenoid valve, in which the water force is suppressed directly, the valve installed in section II uses an auxiliary membrane and spring system, which reduces the electromagnetic force needed by the actuator. Therefore the first future work proposed is a study concerning the mechanics and hydraulics of the lower part of the solenoid valve, so it might be possible to reduce the force needed by the actuator, and, consequently, its volume and consumed power. In this field, it is proposed a second project which comprises the production of an actuator, for a normally open valve, to be installed on the lower armature of the solenoid valve used in section III. Through the valve behavior observed during trials, it was deduced that if an actuator with inverse function is applied on the top of the lower armature, the valve works with a reverse topology: it works as a “normally open” valve, instead of a “normally closed” one. That way, it is possible to use the project developed in this thesis to create such and actuator, knowing from start that it will be much smaller and will need an electromagnetic force with minor magnitude than the one studied in this project. To achieve this goal, the only step that must be taken for dimensioning it, is to run the optimization again, adjusting the force constraint and the variables’ interval limits. On a similar note, it must be recalled that all system dynamics concerning an electromagnetic actuator were modeled and

Transformer

Control and power Supply Circuit

Optical Sensor

Solenoid Valve

10

simulated in this thesis, and that the parameter optimization is prepared to be run along with this simulation. Therefore, this is a model that can be used for dimensioning a “normally closed” valve as well, keeping in mind that only certain formulas must be changed, when calculating parameters such as the magnetic flux density or the electromagnetic force. This is necessary, because these parameters vary in accord with the geometry of the actuator. As for the work conducted in section III, there were some practical conclusions which were drawn, and must be referred here, as they set important interpretations given to the project’s future. In this context, it must be noticed that the optical metering solution developed is fully operational, and could be seen as an independent system. After adding some more elements, this subsystem could be used as a low cost remote metering device. For the water flow adjustment system, it must be kept in mind that it is a system that guarantees good results only if the water is kept under typical pressure at the entrance of the water meter. Another illation that can be retained is that, since this system uses a “normally closed” solenoid valve, it is necessary to apply a continuous signal during water supply, which increases the energy consumption. Therefore, it should be conducted a study on how to activate the valve, only when there is need for water supply. Lastly, it must not be forgotten that the prepayment water meter must work with the STS system to receive transactions information, which implies the installation of a STS decoder.

REFERENCES [1] “STS Association Services”, [Online]. Available: http://www.sts.org.za/ .

[Acedido em 13 de Dezembro de 2014] [2] “PVL”, 2/2 Brass Type UWNO Datasheet [3] Centelsa, Magnet Wires Datasheet [4] Y. Cengel, J. Cimbala, Fluid Mechanics – Fundamentals and Applications, 2nd

Edition, 2010 [5] António Dente, A Componente Térmica das Máquinas Eléctricas, Lisboa:

Instituto Superior Técnico, 2012 [6] Marcel Jufer, Traité d’Electricité Volume IX Électromécanique, 1995 [7] J. A. Brandão Faria, Electromagnetic Foundations of Electrical Engeneering,

2008 [8] J. Holman, Heat Transfer, McGraw-Hill, 10ª edição, 1997 [9] Z. Makni, Contribution au Développment d’un Outil d’Analyse Multiphysique

pour la Conception et l’Optimisation d’Actionneurs Électromagnétiques, Universite Paris-Sud XI-Faculté des Sciences d’Orsay, 2006

[10] G. Slemon, Electric Machines and Drives, Addison-Wesley Publishing Comapany, 1992

[11] Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm NSGA-II. Evolutionary Computation, 2002

[12] “Wiring of the Solenoid Valves”,” [Online]. Available: http://web.cecs.pdx.edu/~eas199/B/howto/fishtank/wiring/solenoid_wiring.html [Acedido em 27 de Agosto de 2014]

[13] V. Jardineiro, Projecto de actuador electromagnético para o ajuste de caudal em contadores de água com regime de pré-pagamento utilizando a norma STS, Lisboa: Dissertação de Mestrado, Instituto Superior Técnico, 2015