Method of controlling fan systems

Abstract

A method of providing a model of a fan comprises running a motor at a plurality of fixed speeds and measuring or estimating flow rate and pressure differential across the fan, to obtain curves of pres

Description

Method of Controlling Fan Systems Field of the Invention This invention relates to a method and apparatus to control fans, blowers, vaned pumps, and such like. The invention has particular but non-exclusive application to centrifugal fans and in particular extractor fans, which are driven by electric motors. Background of the Invention A typical arrangement of an extractor fan system includes a fan, and fan housing where typically the fan resides. A motor, typically electrically powered, drives the fan and there is a motor controller which may be included in the fan housing. Often there is at least one filter. The term “inlet” is the location where air / fluid enters the extractor / fan, and “outlet” refers to where air / fluid exits the extractor / fan. Itis an object of the invention to provide improved and accurate determination of fluid / air flow as well as control of a motorised fan / extractor system to give an accurate flow rate; under a variety of conditions, such as motor speed, pressure differential (pressure head) as well as in refinements, atmospheric conditions such as air temperature, ambient pressure and relative humidity, without the need for operational flow sensors. In particular known systems in operation, determine the flow by using flow sensors such as a pitot tube. Not only does this add to expense as well associated installation problems, but also measurements are not always reliable. In addition, the presence of a pitot tube introduces arestriction. Therefore in some situations the sensor itself becomes a restriction to the pump. There are ideal proportions and dimensions for a pitot tube which ensures that air flow is laminar when it reaches the Pitot sensor (not turbulent). In systems that use a pitot sensor these dimensions are never met due to physical limitations of the units. Due to this, the Pitot housings are normally much shorter than ideal. This shortened housing has the effect of drifting and the Pitot tube becoming less accurate as the restriction changes and for example when a unit is calibrated with clean filters. When the filters are 70% blocked air flow through the sensor may be as much as 15% less than when calibrated. Additionally, inaccuracies may be caused by pitot readings not being temperature compensated. This is because as the unit becomes more restricted, air temperature tends to rise which in turn reduces its density. Both these effects contribute to errors. The pitot tube arrangement also adds restriction to a pump. Often therefore the pitot arrangement that is used with extractors are technically incorrect and provide spurious signals. Furthermore, when using a pitot sensor, the signal can fluctuate about a mean value due to the nature of the moving air and the sensors output signal requires conditioning to obtain a stable value. The signal derived from pitot tubes in many current units is therefore unstable in part due to sporadic mass flow rates that are encountered in air flow which is not always laminar. This may be partially solved by using signal conditioning methods to obtain a smooth signal value. For example, one method is to obtain a rolling average of the pitot signal over a second (outputs the average of the last seconds worth of data). Another option is to include an RC circuit. However, all available options inherently introduce lag into the signal. This lag affects how responsive a proportional integral derivate (PID) controller can be. Prior Art European patent application number EP 3 249 236 (BOFA International limited) discloses a fume extraction apparatus. It is one object of the invention to overcome the aforementioned problems. Aspects of the invention provide improved accuracy not only for individual motors and fan systems, whose characteristics may vary due to manufacturing tolerances, but also dependent on the installation environment, as well as temperature and air pressure, without the need for flow sensors in operations such as pitot tubes. Summary of the Invention According to a first aspect of the invention there is provided a method of providing a model of a fan system, said system comprising a pump or fan, driven by an electric motor, comprising the steps of providing a model characteristics of said system by: i) running the motor at a plurality of fixed speeds and measuring or estimating flow rate and pressure differential across said fan; ii) determining a curve of the relationship of pressure differential across said fan against flow rate for each of the cases in i); iii)) selecting one of the curves from step ii) as a designated calibration curve; iv) selecting a pertinent or designated flow rate value; v) for each of the curves in ii) determining an offset value required to shift said curve to coincide / intersect with the calibration curve, such that the same value of pressure differential is matched at the designated flow rate with the same value of pressure differential as the calibration curve at the designated flow rate, and shifting each of said curves of step ii) by said corresponding offset value; vi) storing said offset values; vii) scaling each of said shifted curves of v) to be substantially coincident with said calibration curve, said scaling providing a head scaler value for each curve of ii) and v); viii) storing said scaling values for each curve of ii) and v). In some embodiments the step viii) comprises storing a curve of scaling value against rotational speed. In some embodiments the scaling value (SV) for a selected curve from step (vii) is derived from the formula: SV= (B-C) / (A-C), where A is the value of head on the calibration curve at said designated flow rate; C is the value of the head of the selected curve at a point P on said selected curve, and B is the value of the head on the calibration curve for a value of flow coincident with point P. Optionally where point P is selected to be the end point at the maximum or minimum level of flow on the selected shifted curve of step v). This ensures that pressure can be selected to be at any point between a maximum and a minimum. Ideally the maximum flow point is used. However another flow point may be selected along this line. It is understood that the term “curve” or “line” are interchangeably used throughout this specification and thus as interchangeable alternatives. The term “curve” or “line” represents two variable such as flow and head pressure, and can also be considered a data set representing these two variables. Such data may be stored by known methods and formats as table, MAPs, or even equations representing the lines or tables. In general in the majority of charts / graphs unless otherwise stated, shows pressure differential across the fan although referred to alternatively as “head” on the y-axis, against flow (on x- axis). Also the term “fan” and “pump” may be regarded as interchangeable. The invention will be described with reference to example and the following Figures of which Brief Description of the Drawings Figure 1 shows a typical extractor fan configuration; Figure 2 shows a location of a DP sensor for the system shown in Figure 1; Figure 3 shows an example of a dual temperature sensor placement location for the Figure 1 system; Figure 4 shows components of a fan motor controller according to one example; Figure 5 shows raw pump model data; Figure 6 shows smoothed pump model data; Figure 7 shows a model calibration line; Figure 8 shows the calibration data to be loaded into the motor controller; Figure 9 shows pump model data overlaid; Figure 10 shows “DP Offset” data to be loaded into the motor controller; Figure 11 shows “scaled” overlaid data; Figure 12 shows example data lines in scaling method; Figure 13 shows data point on the figure 12; Figure 14 shows the RPM line scaled onto the calibration line; Figure 15 shows microcontroller scaled data; Figure 16 shows an example of uncompensated characteristic data curves; Figure 17 shows curves of figure 16 compensated for temperature (temperature normalised data at 24 degrees C); Figure 18 shows a chart of the effect of changes of air density with static (head) pressure; Figure 19 shows the effect of air density on altitude; Figure 20 shows a maximum pump curve of flow speed against pressure head; Figure 21 shows a maximum pump curve showing flow verses speed; Figure 22 shows model flow module data charts to recap; Figure 23 shows a motor control circuit which may be used to implement aspects; Figure 24 shows an example pump curve; and Figure 25 shows multiple fan control architecture. Preferred embodiments of the invention will now be described in detail below. Description This disclosure provides a model-based flow determination and control method. In some aspects the invention also relates to a model-based method for controlling variable speed “blowers” or “centrifugal fans” to a desired flow rate for an operator specified or a user specified period. The term “fan system” should be interpreted as any system including a fan, blower or such like which is motor driven, and includes necessary sensors as disclosed hereinafter when used for purposes of controlling the fan system. This method provides for accurate determination of the flow using the system characteristics rather than a dedicated flow sensor. The term “fan” should be interpreted as any fan, blower or such like. Its characteristics are important. For example, once specific fan data is known, the fan is able to be incorporated into any system and its flow is able to be derived because each fan perceives a system to which it is connected as providing a restriction to the fan. Fans are typically calibrated in situ, that is when they are installed in a system, as this is more convenient. Figure 1 shows a typical schematic arrangement of an extractor fan arrangement / system to which the invention has particular application. Figure 1 shows a fan 1, a fan housing 2, where typically the fan 1 and motor controller 7 are housed. Also shown is a filter 3, a filter housing 4, inlet 5 (where air enters the extractor fan) and an outlet 6 (where the air exits the extractor fan). Figure 2 shows schematically a typical location of a sensor arrangements in the extractor fan system of Figure 1. Figure 2 shows a differential pressure sensor 8 and the pressure sensing locations. This may comprise two sensors or sub-sensors; a low-pressure sensor 8b where its sensing location is typically located between the fan inlet and filter. Itis important to distinguish the fan inlet and the extractor inlet. A high pressure sensor 8a, where its sensing location is also placed at the fan outlet. Although measurements can be derived using separate sensors other options are envisaged. For example a single differential pressure sensor may be deployed. This has two ports - a high pressure port and a low pressure port. Dual temperature sensors are used to monitor air temperature. Figure 3 shows the dual temperature sensors sensing locations. The temperature sensors monitor air temperature either side of the pump. The units are ideally operative to obtain averages of these readings from each sensor. Optionally a weighted average of the readings may also be obtained. The position of the temperature sensors is in shown in Figure 3. Having dual temperature sensors also assists in so-called “dead-headed” scenarios as the temperature differential between inlet and outlet can be used to detect when a pump is “dead- headed”. When a pump is “dead-headed” the temperature differential between inlet / outlet can increase rapidly In normal operations (flow calculations) the average or weighted average temperature value is used. Also the temperature differential between inlet / outlet to detect “Dead-Head” scenarios is monitored. Qverview of Invention In one aspect is provided a model based method to determine the fan (system flow) and in a further aspect there is provided a method and system to control the flow accurately from the determined flow. In some embodiments there may be a motor controller which implements a “Model Based Flow” control method by using the determination of the flow in the first aforesaid aspect. Figure 4 shows components in the further aspect in one example. In the control aspect, there may be the main components of microcontroller, motor control interface. There may be multiple interfaces to control multiple pumps. Optionally a value for relative humidity may be derived from an integrated circuit (IC) which obtains atmospheric pressure and relative humidity. This may be used in situations where air with high humidity is being passed through the fan or where the fan is being used to extract air that has a different humidity to the ambient. In such situations a humidity sensor may be included between the filter and pump inlet to monitor the humidity and provide a signal indicating the humidity. In some cases though another sensor may be required to measure the relative humidity in a different location (for example between the filter and fan inlet) than where the atmospheric sensor is being measured. Optionally atmospheric pressure and relative humidity can be obtained. This can be achieved using a single integrated circuit (IC) containing one or more sensors. The above 3 sections describe the requirement for “Atmospheric Pressure” and “Relative Humidity”. The “Atmospheric Pressure” and “Relative Humidity” sensors are optional. The system would function without them but this requires the unit to either have fixed values input into the system which effectively “tune” the unit for its environment; or the unit would need calibrating on site. The “Relative Humidity” sensor is optionally removable from the board. It may be connected via a communication link, to allow the sensor to be located within the airflow path. The interface may include a motor output drive have either or both of a PWM pulse width modulation or analogue outputs. The interface includes a motor speed feedback input which may include a rev counter or RPM monitor or another form of speed sensor. This is described in more detail below. Further provided is a differential pressure sensor this measure “head pressure” which is the differential pressure across the fan. Dual temperature sensors 9 measures the air temperature. The fact that the temperature sensors are included overcomes problems associated with varying air density, due to temperature, that were encountered in many existing systems Optionally a barometer 14 may be provided to measure atmospheric pressure so that the control methodology can compensate for air density. In a yet further embodiment, a value for humidity of air may be included. General Methodology Pump / fan system model data are required for the control methodology and flow determination methodology. Although these could be pre-stored, as system (motor and fan) characteristics i) may vary over time; ii) may have some manufacturing differences, and iii) the characteristic will vary dependent on installation arrangements. For these reason model data can be collected in an initial data collection techniques. The term “model data” can be regarded as any data which is connected with characteristics of the systems. This is why data is collected for each fan as so many physical differences exist between fans. Therefore, provided pump data is correctly obtained, it should be able to be used, with the same data accurately, even if a pump is moved to another installation. Thus units are calibrated when installed as pump data can be collected during a different process and then tested when newly installed in a bespoke system. Therefore, for example, a pump manufacturer may embed a flow controller into pumps which perform the aforementioned method of control. System Model Data |) data collection System model data is first required to be obtained, and this is used in operation to determine flow. The obtained data may be “normalised” to a reference temperature. In the first step, a motor controller of the system runs the system at a desired fan revolution rate per minute (RPM), using RPM feedback control for example. Characteristics i.e. “curve” data at this fixed RPM are collected. The “curve” data that is collected is the flow rate and head pressure. Flow sensors may be used to do this under controlled conditions for example in a laboratory environment of in a factory or manufacturing facility with the necessary flow Sensors. This data thus represent a line or a curve, effectively a relationship of flow against head pressure for a particular fan speed. Such curves / relationships may be stored as is well known, as data sets, tables, MAPS or such like. The data may be collected from the pump / fan system, from a range of least restricted flows to a fully blocked state. This first step is repeated for a number of different fixed speeds and curve / relationship data stored. That is the process is repeated until a number of desired RPMs have been collected. Figure 5 shows some examples of such curves; on the y-axis is head pressure and the x-axis shows flow. The different curves are for different pump speeds (varying RPMs). Figure 5 thus shows obtained “raw” pump model data showing collected data from 4000 to 15000 RPM in 1000 RPM increments. Optionally a calibration system, which may be a personal computer or laptop computer, operating in accordance with bespoke calibration software, may be used to calibrate a pump. Optionally controllable air valves may also be used in order to automate the data collection process. 11) Smoothing data In this optional step, the data of the curves obtained in the first step may be smoothed by known techniques. Figure 6 shows plots of smoothed data. II) Providing a calibration curve by selection A calibration curve (often referred to alternatively as “line”) needs to be provided. This may simply be any of the curves determined above from steps | or preferably Il. However, it is preferable that the curve which is selected is that which shows the longest RPM data line; that is the curve which has the longest range in terms data flow; or the longest curve along the x- axis. This is shown in Figure 7, and a clear version shown in Figure 8. In this example the curve selected is the 12000 RPM data line (which is the longest). Figure 7 shows an example of data obtained during the collection process. Figure 8 is the same data but separated into discrete points; in this case there are 10 points which are shown as black dots and a dashed line. These data points are what are input into the motor controller to represent this data line. Accuracy can be increased / decreased by points to either reduce required data or increase accuracy. Optionally data may be loaded into a processor as a mathematical function. |\V) Data Overlaying Step to Obtain DP Offset Curve In this step the data lines are shifted to where a units flow range starts so as to assist with the calibration of lines at a desired / selected nominal operational flow rate. The desired flow range may be selected to be that in which the system is designed for optimal operation. In the example the unit has a workable range of 100-380 m%h and data has been shifted to a range of around 80 mh. This is because the data to the right, that is above around 80 m¥h, is accurate whereas the data to the left — that is 0 m¥%h — 80 mh is less accurate. Data is preferentially shifted to 80 m%h rather than 100 m%h because the unit can be set at 100 m¥h but momentarily drops below this due to blockages. In other words at a selected flow rate (here 80 m%hour) all the curves of Figure 6 are moved (shifted) vertically up or down such that their points at this flow rate coincide with a pressure head of the same value as the calibration line. That is they are coincident at point Q in Figure 9 so the value of head on the calibration line at a flow of 80 is 6200. In order for the curves to ‘move’ up or down by an amount such that at this point (flow rate) the heads of the y-axis are all at the same value of 6200. The term shifting of a curve should be interpreted broadly, and in general, as manipulating data by addition or subtraction of appropriate values so as to achieve the coincident effect, and to record the degree of shift or translation of data. In other words in the above example, it may be regarded that data has been “overlaid” with “calibration curve” data line (12000 RPM) at 80 m%h. This is done by finding the difference between each data line and the calibration line with flow rates of 80 m¥%h and adding the difference to each line. In another example chosen 80 m%h was chosen as the system with which this is used has a flow range of 100-380 m%h. Setting the “overlay” point to 80 m¥h gives the greatest accuracy over this range of volumetric flow rates. The data used to “overlay” the lines is referred to as the “DP Offset” data. : In other words what is stored or recorded in this step is a relationship between pump speed (or pressure head) and the amount of vertical shift in the above overlaying step. This is shown in Figure 10 and illustrates the “DP Offset” data used to “overlay” the smoothed pump curve data. This data will also be used in the model for obtaining flow in operation and to control the flow accurately. Again the DP offset data may be stored as a curve. MAP, table or look-up table in electronic memory. Figure 10 shows the "DP Offset" data as 10 discrete data points which are points indicating speed vs head offset. These are shown as black dots and dashed line. As with the "Calibration Curve / line" these can be increased / decreased depending on how many data points are required. Optionally data may be loaded into a processor as a mathematical function. V) Scaling In this step the overlaid data may be scaled. Figure 11 shows the results of “scaling” the “overlaid” data, such that each of the curve of step | (RPM line) now better matches the “Calibration” curve (line). Figures 12 to 15 show example with detail of scaling methodology. In Figure 12 the top / curve 20 shows the calibration line and the bottom curve / line 21 shows an example of curve from step | or || for a different speed (different RPM than the calibration curve speed selected). The curve 21 is to be scaled. In the example the value of point P is scaled. It should be noted that Figures 12 to 15 only show a portion of the curves, which are generally to the right-hand side of the line 80 in Figure 9. Any point along the curve / line 21 may be selected but preferably the point P selected is that for maximum (stored) flow. Currently only single data point data is used to "scale" the data. Although multi point data may be used as an alternative and in order to improve accuracy. Optionally a single data point may be used in combination with shifting data curves. This may improve accuracy in a different part of the curve. The aforementioned techniques may be applied to the data shown in Figures 12 to 15, the values A B and C are shown in Figure 13. Value A is the maximum value of the pressure head (DP) for the calibration curve 20 at the selected flow rate in that is to say the differential pressure on the calibration line at the designated reference flow. That is the desired / selected nominal operational flow rate from step IV) (in the example of 80 mh), A = 6187 Pa. Value B: Is the value of the head (DP) on calibration line 20 at the maximum flow of the RPM line 21. Thus value of B =6006 Pa and is the DP on the “Calibration Line” 20 for the maximum flow on the Line to be scaled 21 Value C is the Head (DP) value at point P (at the max flow of the line 21. C= 5921 Pa. Value C is the DP at maximum flow of the data line to be scaled. A scale factor value is determined = (B-C) / (A-C). So for the example the scale factor is derived as = (6006-5921) / (6187-5921) = 0.32. This scale factor or “scaler” is used to obtain the difference between a reference line (An “offset” RPM line other than the calibration line: Figure 9) and the calibration line (Figure 7) relative to the difference between the so-called “Max Cal DP” (Value A) and the DP on the reference line (Value C). The calculated data differences can then be added to the reference data, bringing this into agreement with the “Calibration” data. Scaled Head = Head + ( (A - Head) * Scaler). Although this step here is not used in providing the model data it is explained for the purpose of completeness. This step is subsequently used when the model is used to determine flow. Figure 14 shows the RPM line "Scaled" onto "Calibration Line". The “Scaler” values are obtained for each RPM data line. This data is used by a processor or microcontroller to obtain the flow. The processor or microcontroller is loaded with an array of discrete “Scaler” values. In the below example rows of “Scaler” data have been used (RPM vs Scaler). These values are computed for each of the curves determined in step |) and these data are scaler values against corresponding speed values. Again these data may be stored as tables, MAPs or look-up tables. This results in the plot shown in Figure 15. The processor or microcontroller may use this data and data interpolation techniques to obtain intermediary “Scaler” values. Option A Temperature Compensation Air density is affected by temperature. The head pressure of a pump is affected by air density. As such, as air temperature changes so does a pumps head pressure at a fixed RPM. To compensate for this temperature is monitored of the air passing through the pump. How head pressure is affected by temperature is represented by the following formula: Compensated Head = Head * (Temperature / Reference Temperature ) where: Compensated Head: Temperature compensated head pressure Head: Head pressure of fan during operation (at a known reference temperature) Temperature: Temperature of fan during operation (Kelvin) Reference Temperature: Temperature of fan (Kelvin) represented by “Calibration” line (“Calibration Line” normalised to reference temperature, as shown below). Two temperature sensors are preferably used to obtain an average temperature between inlet / outlet. Optionally a weighted average may be used. Normalising Calibration data for temperature When obtaining “Pump Curve” data the head pressure is normalised to a reference temperature. In this example data is normalised to a reference temperature of 24°C. This way the pump data represents the pumps performance at 24°C. Figures 16 and 17 show pump curves for uncompensated data; Figure 17 shows the curve for the data which are temperature normalised at 24 degrees. The processor or microcontroller uses the current head pressure and temperature to compensate the obtained head pressure to the reference temperature using the above- mentioned temperature compensation formula. Option B Air density / pressure Compensation Air-density affects the head pressure of a pump relative to speed. As air-density lowers so does a pumps static pressure (Head) at fixed speeds. There is a proportional relationship between air-density and static pressure, viz: if the air-density halves so will the static pressure. Fans are “constant volume” devices. A fan at a fixed speed will provide the same flow regardless of air-density. If there is a fan at fixed speed and the air-density halves, the static pressure will half but the flow remains constant. Figure 18 shows a graph showing the effect of changes in air-density on static pressure (head). There are three variables that affect air- density. |) Temperature. A rise in temperature lowers air density; temperature affects are handled by monitoring the air temperature through the fan. I) Atmospheric pressure. Air density is related to elevation above sea level (Atmospheric pressure). Air density is at its highest at sea level and reduces with elevation. 11) Humidity. Air density reduces with increase in humidity; compared to Temperature and Atmospheric pressure, humidity has the least affect. As can be seen from the Figure 19 which shows altitude against air density that a system at 1,000m above sea level will have an air- density 10% lower than one at sea level. Several compensation options may be provided according to refined aspects to compensate for this affect. One requires additional circuitry and the other auto compensates during operation. The motor controller may be fitted with an atmospheric pressure circuit such as the TDK Invensense (RTM) ICP-10100 ICP-10101 ICP-10110 ICP-10111. Optionally an IC may be used which combines atmospheric pressure and humidity data. Auto Air Density Compensation Feature During calibration a further step is to obtain the fan system maximum “curve” data. This is obtained by driving the fan at maximum capability and recording its head pressure from lowest restriction to fully blocked. Data pertaining to “Flow vs Head” and “Flow vs Speed” is collected. Figure 20 shows a Maximum "Pump / Fan Curve" (Flow vs Head) and Figure 21 shows Maximum "Pump / Fan Curve" — (Flow vs Speed). Changes in air density have a direct relationship with head pressure. If the air density halves so the fans head pressure halves at a fixed speed. Example: 1 Fan speed: 14000 RPM, Flow: 220 m%h; Air density 1.2: (During calibration) Head = 6800 Pa; 0.6: (During operation, @ altitude) Head = 3400 Pa. This data can be used to auto compensate for air density. When a fan becomes “blocked” it can no longer meet the desired flow setpoint. There is constant monitoring for this scenario. When the motor controller can no longer meet the flow setpoint the flow drops below the target and a proportional integral derivative (PID) controller output saturates (drive to maximum in an attempt to match the flow setpoint). At this instant “Pump Curve” line data is used. Knowing this, and the fact that flow is constant with speed, the “Flow vs Speed” data can be used to calculate what flow is required. Example: Fully blocked, Flow setpoint not being met and the PID controller is saturated. Fan Speed: 14000 RPM; Flow: 220 m¥h is obtained from the “Flow vs Speed” data @ 14000 RPM. It is known that @ 14000 RPM on the “Pump Curve” (maximum capability of the fan) is 220 mh. This data can now be used to determine what the “Head” pressure is at the reference air density. This is the head pressure on the “Pump Curve” data for the same flow. Example: Flow: 220 m3h Head Pump Curve Data; 6800 Pa. This value can now be used with the actual head pressure which is used to calculate an “Air density factor”: By way of example: Head Pump Curve Data: 6800 Pa Actual: 6000 Pa; Air Density Factor Pump Curve Data / Actual 6800 / 6000 = 1.13. The "Air Density Factor” is now be saved and used to compensate the actual head pressure readings. Example: Actual head = 6000 Pa; Compensated head = Actual head * Air Density Factor (ie 6000 * 1.13 = 6800 Pa). This feature is selectable. If enabled, it is recommended that the user at first operation intentionally blocks the fan. This then auto compensates the fan for its environment. If this is not done then the first time the fan is operated its flow readings may be inaccurate due to local, ambient air density until it is first “blocked”. Optionally this feature may be disabled for specific applications when desired by an operator. Flow Determination and Control Process Previously reference has been made to obtaining data for the system to provide a model of the system — effectively stored data which is subsequently used to determine the flow rate as well as control during the operation of the fan, along with measurements from sensors. These model data are the result of the calculations above are: the calibration line, the DP offset line / curve and the scaler line. To recap these three model data sets are i) Calibration line: Longest RPM data line; All other lines will be “Offset” and “Scaled” to represent this line ii) DP Offset Data: Differences between the “Calibration Line” and other RPM data lines at a fixed flow iii) Scaler Data: Scales the RPM data lines to better fit the “Calibration Line”. Figure 22 shows model (module) data used subsequently for determining flow rate and control subsequently in operation. In an example of operation once all data has been stored (previously obtained e.g. by the procedures above). The microcontroller calculates the fans air flow using the model as well as measured values: of a) Speed: RPM b) Head: Differential pressure across pump and optionally c) Air temperature: (temperature of the air passing through the pump) and optionally air density and relative humidity. The microcontroller or system may pass these variables to a module ("Model Pump Flow” module) which will convert them to a flow. The model data may be loaded into e.g. a microcontroller as arrays of discrete data points or mathematical equations. In the example the “Calibration Line” and “DP Offset Line” have been reduced to an array of 10 rows, the “Scaler Line” 12 rows (one for each data line). The number of rows can be adjusted to either improve accuracy or reduce memory size. Discrete data points are used to obtain intermediary data points using interpolation. For example, the “DP Offset” data can be obtained for an RPM of 9,500 by interpolating between the 9,000 and 10,000 data points. Method of Determining Flow in Operation - Conversion Process details Basically, the model data is processed with sensor data to get a flow. Alternatively view a “Model Pump Fan Flow” flow module (having the model data stored therein) is input sensor variables, being a minimum of speed: RPM, Head: Differential pressure across pump (Pa). Air temperature (temperature of the air passing through the pump (°C)). Optionally atmospheric pressure and relative humidity values may also be used as an input variables. The “Model Pump Flow” module is now explained using the curves shown in summary in Figure 22 (Model Flow Module Data). Step 1 In a first step the temperature from a sensor is used to adjust (that is to temperature compensate) the sensed “Head” pressure. So in other words this adjusts the input “Head” data to its equivalent pressure at reference temperature (in this example: 24°C); i.e. this adjusts the current head pressure to match the “Calibration Line” temperature (This data was normalised to 24°C). Step 2 Atmospheric pressure compensation; here the sensed “Head” value is further adjusted to allow for atmospheric pressure. In some cases sensors may be used or a value that is obtained during an "auto compensation" process, as described above may be used. In other cases data from an on-board barometer may be used to obtain direct atmospheric pressure. Optionally a method of loading the atmospheric pressure may be used so a user can manually input local atmospheric pressure. This could be by a user interface or a data upload. Step 3 A value for relative humidity may also be used to obtain a value to compensate for varying air density. This step is optional so may be bypassed if no sensor or value used. Step 4 Overlay “Adjusted Head” data Using the “DP Offset Line” the sensed Head pressure (optionally adjust by steps 1 and / or 2 and / or 3) is adjusted so as to lie on the “Calibration Line” Example: @ 11,000 RPM the “DP Offset’ value is approx. 1,000 Pa. This value is added to the current “Head” pressure to put us on the “Calibration Line”. Adjusted Head is the raw head pressure compensated for temperature, atmospheric pressure and humidity. Step 5 “Scale” the “Head” data Using the “Scale Line” data, the “Adjusted Head” is scaled to better lie on the “Calibration Line”. Example: @ 11,000 RPM the “Scale” value is 0.05. The current “Head” is scaled using this value within a scaling function to adjust the “Head” to better lie on the “Calibration Line”. This gives an “Adjusted Head” value. Step 6 Calculate “Flow” The “Adjusted Head” computed in step 5 is used to calculate the “Flow” using the “Calibration Line”. Example: After “Temperature Compensation”, “Atmospheric Pressure”, “Relative Humidity”, “DP Offset’ and “Scaling” the “Adjusted Head” is 3000 Pa. 3000 Pa on the “Calibration Line” equates 300 m¥h. Hardware - Control The flow may be controlled by standard control technology. In an example the block diagram of such flow control is shown in Figure 24 Flow Control Process i.e. showing Motor Control PID architecture. The calculated flow to maintain a desired flow. A PID controller may be used to maintain a desired flow. Although a single PID architecture could be used a cascaded PID architecture is preferred. Here the motor controller has 2 PID controllers: Inner PID which is RPM Control: Maintains a desired pump speed, and an Outer PID which is Flow Control: Maintains a desired flow. Using this architecture, the motor is configured to the controller to maintain fixed RPMs. This configuration is used to obtain the “Pump Model” data. In the above example a “Pulse Width Modulated” (PWM) signal is output to control the fan. Some fans may require an analogue voltage. The motor controller can be configured to output an analogue voltage if required. Using this architecture the motor is configured to the controller to maintain a fixed RPM. This configuration may be used to maintain fixed RPM to allow collection of the pump model data. A cascaded PID architecture improves overall stability. Another benefit of this architecture is that RPM PID can be used to control and obtain the pump model data. This is yet another benefit of the topology but not essential. A different controller may be used to obtain the pump model data. Blockage Calculations A module that calculates a systems “Blockage”. A “Blockage” is the percentage of a fans available “Head” pressure at a set flow that is taken up by the system. The fans “Pump Curve” data is obtained by setting the fan to maximum drive (PWM: 100%) and measuring its “Head” pressure from minimum restriction to maximum: Figure 24 shows “Pump Curve” of the example system. This plots the maximum head pressure the fan can output for a given flow. For example: @ 180m¥h the pump can handle approximately 8000Pa Head pressure. This data is loaded into the microcontroller in discrete data points. The above example shows the data being split into 10 rows of data (Flow vs Head). The above data “Head” values have been “Normalised” to 24°C. In refined aspects the system and method may be modified for the effects of blockages. A “blockage Module” may be provided with input two variables: Flow and Head (which may optionally be temperature compensated) as that Head value which is used is the "Adjusted Head". This is the temperature, atmospheric pressure and humidity adjusted head To calculate system blockage the following steps are taken i) Obtain "Maximum Head" for given flow - use the “Pump Curve” data to obtain the maximum available “Head” for given flow. Example: @ 180 / h the pump can handle approx. 8000Pa. ii) Calculate the percentage of current “Head” pressure is relative to “Maximum Head” at current flow - Example: Current “Head” = 4000Pa, Current Flow = 180 m%h, Maximum Head = 8000Pa Blockage = (E 4000 / 8000) * 100 Blockage = 50%. The Current Head is therefore the Adjusted Head (Compensated head for temperature, atmospheric pressure and humidity). Multiple Systems The same methodology can be used in multiple pump / fan systems: Figure 25 shows and example of how the motor controller is configured for multiple pumps In the above example each pump has its own RPM PID controller. These are driven by a single Flow PID controller. The “Flow Calculator” module is fed the “Average RPM” of both fans and the “Head” pressure across both fans. In the above example the fans both share the same inlet and outlet, this will make the “Head” pressure across both fans the same. This architecture can scale up to any number of pumps. Advantages The invention removes the need and cost for a pitot tube and so overcomes issues of instability: This has several benefits. Another advantage is that the response time is quicker as the methodology according to aspects does not require the signal to be conditioned and so can be controlled more quickly than existing systems because it is calibrating absolute values. The signal for flow obtained in current aspects is inherently smoother than that obtained with a pitot tube. Because of this control (e.g. with a PID controller) can be more aggressive and the control can be implemented more quickly and be more responsive to disturbances because the pitot signal is far noisier than the "Head" pressure signal that is obtained at the same flow rate. The "Head" pressure data does not require conditioning. This is partly because, even when a system is held at a steady flow of 100m%h the pitot signal will fluctuate around this point, requiring constant signal conditioning to obtain a smooth reading. Therefore current systems incorporate signal conditioning but values they obtain can fluctuate in comparison with the present invention. The methodology does not require extra calibration because there is an ambient pressure, Relative humidity and temperature sensors that automatically adjust fan speed parameters A single differential pressure sensor may be used for measuring the pumps head pressure (difference between its inlet / outlet). The temperature, barometer and relative humidity sensors will be used to compensate for air density. The pumps speed is provided by the pump itself (Tacho feedback). Another benefit of having this system is that your control system enables the flow rate to be derived precisely so that fan speed (and so energy usage) can be accurately controlled. Flow control can be provided without the need of a pitot tube. This now allows flow control to be added to all systems, not just those that historically had pitot tubes. There are many applications that could benefit from having flow control which currently do not due to their physical size being too small to incorporate a pitot tube arrangement. The invention removes the need and cost for a Pitot tube and so overcomes issues of instability. Another advantage is that the response time is quicker as the flow rate that is calculated is more stable than that obtained using a Pitot tube sensor A benefit of having this system is that your control system enables the flow rate to be derived precisely so that fan speed (and so energy usage) can be accurately controlled. Variation to the aforementioned embodiments may be made without departing from the scope of protection as defined by the claims.

Claims

Claims 1, A method of providing a model of a fan system, said system comprising a pump or fan, driven by an electric motor, comprising the steps of providing a model characteristics of said system by: i) running the motor at a plurality of fixed speeds and measuring or estimating flow rate and pressure differential across said fan; ii) determining a curve of the relationship of pressure differential across said fan against flow rate for each of the cases in i); iii)) selecting one of the curves from step ii) as a designated calibration curve; iv) selecting a pertinent or designated flow rate value; v) for each of the curves in ii) determining an offset value required to shift said curve to coincide / intersect with the calibration curve, such that the same value of pressure differential is matched at the designated flow rate with the same value of pressure differential as the calibration curve at the designated flow rate, and shifting each of said curves of step ii) by said corresponding offset value; vi) storing said offset values; vii) scaling each of said shifted curves of v) to be substantially coincident with said calibration curve, said scaling providing a head scaler value for each curve of ii and v; viii) storing said scaling values for each curve of ii and v.

2. A method as claimed in claim 1 where step viii) comprises storing a curve of scaling value against rotational speed.

3. A method as claimed in claim 3 wherein said scaling value (SV) for a selected curve from step (vii) is calculated from the formula: SV= (B-C) / (A-C), where A is the value of head on the calibration curve at said designated flow rate; C is the value of the head of the selected curve at a point P on said selected curve, and B is the value of the head on the calibration curve for a value of flow coincident with point P.

5. A method as claimed in claim 4 where point P is selected to be the end point at the maximum or minimum level of flow on the selected shifted curve of step v).

6. A method as claimed in any claim including the step of smoothing or filtering the curves determined from step ii) before subsequent processing steps.

7. A method of estimating the operational flow rate in a fan system, said system comprising a fan, driven by an electric motor, comprising the steps of providing a model of said system by the methods of any of claims 1 to 6: and further determining operational flow by the steps of: X) measuring the value of the pressure differential across the fan and the speed of the fan motor; y) determining operational actual flow rate based said measured values from x) and said model characteristics determined or stored in steps iii), vi) and viii).

8. A method as claimed in claim 7 where steps x) and y) comprises: a) measuring or determining the fan motor speed; b) measuring or determining the pressure differential across the fan; c) from said measured speed, determining a value from offset data from vi) and using this and the measured head pressure to determine an adjusted head pressure; d) from said measured speed, determining a value from scaler data from viii) and using this to further adjust head pressure from step c): e) estimating the flow based on said further adjusted head pressure of step d) and said calibration curve of step iii).

9. A method as claimed in claims 7 or 8 additionally comprising the step of f) measuring the air temperature at points in the system, and using the value said temperature in step y).

10. A method as claimed in claim 9 when dependent on claim 8 wherein said temperature value is used to further adjust the head computed in either steps c) or d) before step e).

11. A method as claimed in claims 7 to 10 additionally comprising the step of: [)] measuring the ambient pressure at a point in the system, and using the value of said ambient pressure in step y).

12. A method as claimed in claim 11 when dependent on claim 8 wherein said ambient pressure values is used to further adjust the head computed from step c) or d) before step e).

13. A method of controlling a fan system, said system comprising a fan, driven by an electric motor, comprising the steps of determined the flow rate from any of method steps 7 to 12.

14. A method as claimed in claim 13 wherein said system includes a pressure differential sensor adapted to determine the pressure differential across the fan and / or means to determine motor speed and wherein said controlling step comprises setting a required flow rate and comparing this to a determined flow rate. 15 A method as claimed in claim 13 or 14 includes a humidity sensor and a compensator that is operative to compensate density of air in dependence on a signal derived from the humidity Sensor.

16. A controller adapted to implement the control method of any of claims 13 to 15.

17. A data processing apparatus / device / system comprising means for carrying out the method of claim 1to 15.

18. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the method of claim 1 to 15.

19. A computer-readable medium having data stored thereon said data being that determined in steps iii) vi) and viii) of claim 1.

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