throbber
(19) United States
`(12) Patent Application Publication (10) Pub. No.: US 2010/0312415 A1
`(43) Pub. Date:
`Dec. 9, 2010
`LOUCKS
`
`US 2010.0312415A1
`
`(54) ELECTRICAL DEVICE COOLING
`EFFICIENCY MONITORING
`
`(75) Inventor:
`
`David Glenn LOUCKS,
`Coraopolis, PA (US)
`
`Correspondence Address:
`KRAGULAC & KALNAY
`4700 ROCKSIDE ROAD, SUMMIT ONE, SUITE
`S10
`INDEPENDENCE, OH 44131 (US)
`
`(73) Assignee:
`
`EATON CORPORATION,
`Cleveland, OH (US)
`
`(21) Appl. No.:
`
`12/477.965
`
`
`
`(22) Filed:
`
`Jun. 4, 2009
`
`Publication Classification
`
`(51) Int. Cl.
`(2006.01)
`G05D 23/00
`(52) U.S. Cl. ........................................................ 700/300
`(57)
`ABSTRACT
`Changes in equipment cooling performance may be detected
`by indirectly measuring cooling performance by way of a
`cooling efficiency indicator. An operating cooling efficiency
`indicator is calculated as a ratio between equipment electrical
`power consumption and a temperature differential between
`the equipment and an ambient temperature. The operating
`cooling efficiency indicator is compared to a baseline cooling
`efficiency indicator to detect changes in cooling performance.
`
`X
`
`/...///
`Z-zS
`
`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010 Sheet 1 of 6
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`US 2010/0312415 A1
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`100
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`110
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`115
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`2
`
`2 :
`
`130
`
`%
`
`a
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`-
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`120
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`|
`
`%
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`2227 4 /
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`%
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`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010 Sheet 2 of 6
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`US 2010/0312415 A1
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`
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`2OO y
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`
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`ESTABLISHBASELNE
`COOLING EFFICIENCY
`kWh/degree
`
`210
`
`
`
`
`
`HDetermine kWh h\- 220
`
`230
`
`CALCULATEOPERATING
`COOLING EFFICIENCY
`
`240
`
`250
`
`
`
`BASELNE
`OPERATING )
`> THRESHOLD/
`
`
`
`
`
`
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`
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`
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`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010 Sheet 3 of 6
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`US 2010/0312415 A1
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`
`
`
`
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`
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`
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`Ambient
`Temperature
`320
`
`Equipment
`Temperature
`
`s Results
`
`Baseline
`Heat Transfer
`
`300
`
`
`
`Cooling
`Efficiency
`Comparison
`360
`
`Cooling
`Efficiency
`Calculation
`350
`
`Cooling Efficiency
`Fig. 3
`
`
`
`310
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`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010
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`Sheet 4 of 6
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`US 2010/0312415 A1
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`
`
`
`
`Overal
`Group
`POWer
`
`415.
`
`415g
`
`/
`
`Á /S
`
`--L||
`
`O
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`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010 Sheet 5 of 6
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`US 2010/0312415 A1
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`Incoming
`POWer
`
`
`
`550
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`HALLIBURTON EXHIBIT 1009
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`Patent Application Publication
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`Dec. 9, 2010 Sheet 6 of 6
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`US 2010/0312415 A1
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`714
`
`Process
`
`702
`
`Processor
`
`716
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`Computer 700
`
`704
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`708
`
`FBS
`718
`
`730
`Cooling Efficiency Logic
`
`
`
`
`
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`
`
`
`
`
`
`
`I/O line
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`710
`
`/O Ports
`
`
`
`720
`
`NetWork
`Devices
`
`HALLIBURTON EXHIBIT 1009
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`US 2010/031.2415 A1
`
`Dec. 9, 2010
`
`ELECTRICAL DEVICE COOLING
`EFFICIENCY MONITORING
`
`BACKGROUND
`
`0001. The First Law of Thermodynamics (system internal
`energy increases by the amount of energy added to it minus
`the work done by the system on its surroundings) applies to
`electrical equipment in that as electrical equipment consumes
`electrical energy, it produces heat as a waste byproduct. The
`magnitude of waste heat produced is related to the quantity of
`energy consumed by the device and the device's inherent
`efficiency. The temperature rise of the equipment is related to
`the magnitude of this waste heat and by the amount of cooling
`available. Cooling occurs from conduction, radiation and
`convection.
`0002. In the particular case of devices that rely on forced
`or natural convection cooling, several issues can restrict avail
`able cooling. A blocked air flow path may be caused when
`cabling routing within or external to equipment improperly
`blocks inlet, exhaust air duct(s) and/or a plenum. Drawing
`holders, barriers or electrical insulation sheeting mounted in
`equipment may block external grill covers, rodent or insect
`nests may block vents or air path, or insufficient clearance
`around vents may restrict airflow. Cooling fans may malfunc
`tion due to bearing failure, disconnected or loose wiring to a
`fan motor, fan power Supply failure, broken, bent or missing
`fan blades, or fan blades that become coated with contami
`nants. Dirty or oily air filters may degrade cooling perfor
`mance. External cooling air may be too hot due to undersized,
`malfunctioning or improperly set air conditioning, an exter
`nal Source of heat that has been placed too close to equipment,
`or improper routing of exhaust heat causing re-circulation
`into cooling inlet. External cooling air may flow too slowly
`due to changes in upstream ducting that cause system pres
`Sure changes, eddies, Vortices, dead-spots, backflow or other
`air mixing problems, or cool air that leaks into environment
`prior to reaching electrical equipment. Air ducts may become
`disconnected, resulting in a degradation of cooling perfor
`aCC.
`0003. As can be seen from the foregoing list, many differ
`ent factors may significantly impact cooling performance.
`Since any single or group of these issues can cause cooling
`problems, any of these problems can contribute to electrical
`equipment malfunction or accelerated degradation since
`overheated equipment does not operate as effectively as
`equipment operating at acceptable temperature limits. Tradi
`tional methods of detecting these problems include monitor
`ing rotational Velocity of fans, measuring air flow rates with
`damper Switches or pressure sensors or heated sensors, and
`measuring the temperature of inlet air, exhaustair, heat sinks,
`or other areas of equipment.
`
`SUMMARY
`
`0004 Changes in equipment cooling performance may be
`detected by indirectly measuring cooling performance by
`way of a cooling efficiency indicator. An operating cooling
`efficiency indicator is calculated as a ratio between equip
`ment electrical power consumption and a temperature differ
`ential between the equipment and an ambient temperature.
`The operating cooling efficiency indicator is compared to a
`baseline cooling efficiency indicator to detect changes in
`cooling performance.
`
`0005 Accordingly, a computer-readable medium is pro
`vided that has computer-executable instructions stored
`thereon for performing a cooling efficiency monitoring
`method. The method includes receiving a baseline rate of heat
`transfer with respect to the monitored electrical device and
`converting the baseline rate of heat transfer to a baseline
`cooling efficiency indicator. The baseline cooling efficiency
`indicator includes a ratio of input electrical power to the
`monitored electrical device and a temperature differential
`across the monitored electrical device. An amount of electri
`cal power consumed by the monitored electrical device is
`determined. A monitored electrical device temperature and an
`ambient temperature proximate the monitored electrical
`device are determined to compute a temperature differential
`between the temperature of the monitored electrical device
`and the ambient temperature.
`0006 An operating cooling efficiency indicator is calcu
`lated based, at least in part, on a ratio of the electrical power
`consumed by the monitored electrical device and the com
`puted temperature differential. The operating cooling effi
`ciency indicator is compared with the baseline cooling effi
`ciency. An output that communicates results of the
`comparison between the operating cooling efficiency and the
`baseline cooling efficiency is provided. The method may be
`performed on a per device, per enclosure, and/or a per equip
`ment room basis, as well as any other level of granularity that
`facilitates monitoring electrical device cooling performance.
`0007. A cooling efficiency monitoring system includes an
`ambient temperature input logic, an equipment temperature
`input logic, an electrical power consumption input logic, a
`cooling efficiency calculation logic, and a cooling efficiency
`comparison logic. The ambient temperature input logic
`receives an ambient temperature signal from an ambient tem
`perature sensor proximate to monitored electrical device. The
`equipment temperature input logic receives an equipment
`temperature signal from an equipment temperature sensor
`associated with the monitored electrical device. The electrical
`power consumption input logic receives an amount of elec
`trical power input to the device from an electrical power
`consumption sensor associated with the monitored electrical
`device.
`0008. The cooling efficiency calculation logic computes a
`temperature differential between the equipment temperature
`signal and the ambient temperature signal and calculates an
`operating cooling efficiency indicator based, at least in part,
`on a ratio of the electrical power input to the device and the
`computed temperature differential. The cooling efficiency
`comparison logic determines a baseline cooling efficiency,
`compares the operating cooling efficiency indicator with the
`baseline cooling efficiency, and provides an output that com
`municates results of the comparison between the operating
`cooling efficiency and the baseline cooling efficiency. The
`cooling efficiency system may be configured to receive tem
`perature and power consumption signals from sensors that are
`integral to the devices being monitored.
`0009. In some embodiments that may be configured to be
`used with electrical devices that convert only a fraction of the
`energy to heat, electrical power consumption is determined as
`an energy dissipation within the device. Energy dissipation is
`calculated, based on the electrical power input to the device.
`The energy dissipation is used, along with the temperature
`differential to determine the cooling efficiency indicator.
`Energy dissipation within the device may be calculated by
`measuring an amount of electrical power leaving the device
`
`HALLIBURTON EXHIBIT 1009
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`US 2010/031.2415 A1
`
`Dec. 9, 2010
`
`and determining the differential between the electrical power
`input to the device and the electrical power leaving the device.
`Energy dissipation may be calculated using a model of energy
`losses versus electrical power input to the device that has been
`determined with respect to the electrical device. The applica
`tion of the model may be accomplished using a look up table,
`a polynomial equation, or other techniques.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`0010. The accompanying drawings, which are incorpo
`rated in and constitute a part of the specification, illustrate
`various example systems, methods, and other example
`embodiments of various aspects of the invention. It will be
`appreciated that the illustrated element boundaries (e.g.,
`boxes, groups of boxes, or other shapes) in the figures repre
`sent one example of the boundaries. One of ordinary skill in
`the art will appreciate that in some examples one element may
`be designed as multiple elements or that multiple elements
`may be designed as one element. In some examples, an ele
`ment shown as an internal component of another element may
`be implemented as an external component and vice versa.
`Furthermore, elements may not be drawn to Scale.
`0011
`FIG. 1 is a functional block diagram of cooling
`operation in an equipment room;
`0012 FIG. 2 is a flow diagram outlining an example
`embodiment of a method of monitoring cooling efficiency;
`0013 FIG. 3 is a functional block diagram of an example
`embodiment of a cooling efficiency monitoring system;
`0014 FIG. 4 is a functional block diagram of cooling
`efficiency monitoring system installed on an equipment
`enclosure;
`0015 FIG. 5 is a functional block diagram of cooling
`efficiency monitoring system installed on an equipment
`enclosure;
`0016 FIG. 6 is a functional block diagram of cooling
`efficiency monitoring system installed on an equipment
`enclosure; and
`0017 FIG. 7 illustrates an example computing environ
`ment in which example systems and methods, and equiva
`lents, may operate.
`
`DETAILED DESCRIPTION
`0018. The large number of issues and causes of air flow
`problems means that fully instrumenting each device that
`may affect cooling performance can become cost prohibitive.
`However, since electrical or electronic equipment can mal
`function due to over-temperature, detecting these problems is
`important. Unfortunately, for a variably loaded system, sim
`ply waiting for a high temperature limit to be reached may
`result in equipment damage that occurs in the time it takes to
`resolve the cooling problem. Thus it is desirable to detect
`problems before temperatures reach alarm limits. Also, for
`devices that are externally cooled through refrigeration,
`insufficient cooling due to blocked air flow can result in the
`refrigeration system moving to a lower temperature set point
`as it attempts to reduce the temperature of the protected
`equipment. This results in wasted energy ifa better Solution of
`fixing the airflow exists. Finally, if the temperature of the
`equipment does rise above previous levels, the consequences
`of not cooling equipment properly may result in accelerated
`equipment degradation and early failure.
`0019 Convective heat loss (cooling) using air as the cool
`ing medium, may be modeled using the Navier-Stokes equa
`
`Equation 1
`
`tions. Simplifying these equations after plugging in the prop
`erties of air and Solving for imperial units of measure the
`following equation is obtained:
`Q=1.08VATn
`where:
`0020 Q-rate of heat transfer in BTU/hr
`0021 V=volumetric flow rate in CFM
`0022 AT-difference between inlet and exhaust tem
`perature (F. or R)
`0023 m=efficiency of heat transfer (intentional or unin
`tentional insulation)
`0024 Solving these equations in electrical equipment
`would require sensors that measure air flow, energy flow and
`temperature difference. The problem traditionally has been
`that that rate of heat transfer is difficult to measure. However,
`without complete instrumentation to measure Volumetric air
`flow, sufficient information would not be available to solve
`these fluid dynamic heat transfer equations. Obtaining Suffi
`cient instrumentation in forced air (advective) systems, such
`as under floor cooling in a data center, is difficult and expen
`S1V.
`0025 FIG. 1 is a functional block diagram illustrating a
`typical data center 100 that utilizes convection cooling to cool
`equipment. The data center 100 houses multiple racks or
`enclosures 110 of IT equipment 115, such as servers, routers,
`Switches, and circuit protection devices. A computer room air
`conditioner 120 intakes heated air from the room, cools it, and
`circulates the cooled air through the room as shown by the
`arrows in FIG. 1. Typically, at least part of the air from the
`computer room air conditioner 120 is routed below the floor
`of the room and is forced through holes in perforated floor
`tiles 130.
`0026. Most data centers require substantial cooling. In
`many cases, server density has outpaced the ability of the data
`center to cool those servers using the available cooling capac
`ity. In this situation, there is a desire to “find wasted cooling.
`Since any of the issues discussed above may cause a reduction
`in cooling system efficiency, locating these problems is
`important to those operators. Likewise, reducing energy con
`Sumption reduces expenses and frees up spare cooling capac
`ity, which reduces the amount of capital needed to provide the
`required cooling, since less cooling is needed.
`0027. One common technique for optimizing forced air
`cooling systems is to use a computational fluid dynamic
`(CFD) model of the data center. The output of the CFD model
`solves the Navier-Stokes equations and therefore solves for
`airflows, temperatures, pressures and densities. In particular,
`since equipment manufacturers place temperature limits on
`their equipment, a CFD analysis can be used to estimate how
`present routing of air flows will, or will not, adequately cool
`the equipment. AS IT equipment is repositioned, refrigeration
`is adjusted, fans or blowers and/or air ducting are modified,
`the CFD model is used to calculate new temperature and flow
`rates at various points within an installation. By optimally
`placing equipment with properly routed cooling air flow, the
`airflow required to maintain a particular temperature rise can
`be minimized, and an optimal cooling performance for a
`particular equipment layout may be determined. One draw
`back to using a CFD model to determine cooling performance
`is that any change to the equipment or cooling system typi
`cally means that another CFD model should be run. This is a
`real problem, since CFD models involve a certain amount of
`complexity and time.
`
`HALLIBURTON EXHIBIT 1009
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`US 2010/031.2415 A1
`
`Dec. 9, 2010
`
`0028. The following includes definitions of selected terms
`employed herein. The definitions include various examples
`and/or forms of components that fall within the scope of a
`term and that may be used for implementation. The examples
`are not intended to be limiting. Both singular and plural forms
`of terms may be within the definitions.
`0029 References to “one embodiment”, “an embodi
`ment”, “one example”, “an example, and so on, indicate that
`the embodiment(s) or example(s) so described may include a
`particular feature, structure, characteristic, property, element,
`or limitation, but that not every embodiment or example nec
`essarily includes that particular feature, structure, character
`istic, property, element or limitation. Furthermore, repeated
`use of the phrase “in one embodiment” does not necessarily
`refer to the same embodiment, though it may.
`0030 Referring back to Equation 1, the inputs of the
`Navier-Stokes equations include temperatures across a
`heated object (internal and ambient), energy consumed by the
`heated object, airflow across the object and efficiency of heat
`transfer (heat sink). Temperature monitoring is fairly straight
`forward. Measuring the heat input (kW), likewise, is also
`fairly straightforward. However, the determination of airflow
`rates or heat sink efficiencies is fairly involved. The cooling
`efficiency monitoring techniques and systems described
`herein detect changes from a baseline CFD model by com
`bining easily measured values into ratios that should remain
`constant regardless of how the system performs. If those
`ratios change, that is an indication of a change in the cooling
`system air flow and/or performance. Use of the techniques
`and systems described herein may thus allow detection of
`cooling infrastructure changes without running an additional
`CFD analysis. Problems may also be detected before tem
`perature alarms are reached, giving operators more time to
`locate and fix the problem.
`0031
`Equation 1 can be rewritten to isolate readily known
`quantities (temperatures and input power) and express them
`in terms of the less readily determined quantities (airflow and
`heat sink efficiency).
`
`and written as the variable X, with the resultant conversion
`rate written as 8(x). Since 3412 BTUs is approximately equal
`to one electrical kWh, Equation 2 may be rewritten as:
`
`W
`= 1.08Vn 34120(x) =3685Vnoty)
`
`Eduation 3
`quation
`
`where:
`0037 W=rate of heat transfer in kWh.
`0038 V=volumetric flow rate in CFM
`0039 AT-difference between inlet and exhaust tempera
`ture
`m=efficiency of heat transfer (intentional or uninten
`004.0
`tional insulation)
`0041
`8-conversion efficiency of electrical energy into
`heat as a function of parameter
`0042. The values on the right side of the Equation 3 are
`difficult to obtain, but are all substantially constant, or in the
`case of electrical equipment efficiency, can be modeled accu
`rately. If changes are made in the cooling air flow rate or the
`efficiency of the heat sinks that transfer the kWh energy into
`the air, then the values on the left hand side of Equation 3
`should not change. It follows that if any of these values do
`change, it can result in a change of the ratio of W divided by
`AT. Since two variables could change at one time, (e.g. air
`flow volume drop while the heat sink efficiency rise), changes
`in either could be masked. However, the net result of these
`values masking one another would be that the watts-per
`degree for the system would not change. In other words, the
`cooling performance would remain unchanged. This watts
`per-degree metric can be called a "cooling efficiency indica
`tor” and the difficult to obtain values are collapsed into a new
`variable e.
`
`W.
`AT
`
`Equation 4
`
`O
`
`= 1.08Vn
`
`Equation 2
`
`where:
`0032 Q-rate of heat transfer in BTU/hr
`0033 V=volumetric flow rate in CFM
`0034 AT-difference between inlet and exhaust tempera
`ture
`0035 m=efficiency of heat transfer (intentional or uninten
`tional insulation)
`0036. As electrical equipment converts electrical energy
`to heat, the amount of heat produced will be related to the
`electrical energy consumed by the equipment. Certain equip
`ment (such as computers) convert essentially 100% of the
`electrical energy into heat. Other devices such as transform
`ers, circuit breakers, uninterruptible power supplies (UPSs)
`or variable frequency drives (VFDs) are more efficient con
`Sumers of electrical energy, a certain percentage of energy
`consumed is converted into heat. Thus a percentage value is
`assigned to this heat conversion rate and called it delta 8.
`Since this conversion rate may vary based on percentage
`loading of the equipment (e.g., IR losses from transformers)
`or other effects, the conversion rate variable 6 is written as
`being a function of one or more external parameters grouped
`
`where:
`0043. W=rate of heat transfer in kWh.
`0044 AT-difference between inlet and exhaust tempera
`ture
`0045 e=epsilon, cooling efficiency indicator
`0046. The cooling efficiency indicator appears from a sys
`tem engineering point of view as a temperature gain param
`eter that predicts the effect of power input or consumption
`Versus the long term resultant change in temperature of a
`device or a group of devices consuming electrical energy.
`Depending on the location of the output temperature sensor
`relative to the device, the temperature process value may
`experience certain transport delay. For this reason, it may be
`advantageous to average instantaneous calculations of the
`cooling efficiency indicator over time.
`0047. Many different methods for calculating such a roll
`ing average can be used. One version calculates the mode
`(most common value of the cooling efficiency indicator). This
`method is useful when the input signals are noisy or include
`occasional transients (losses of input where the value drops to
`Zero). Smoothing the signal introduces additional transport
`delay (time delay from when an event occurs and when it is
`detected), so there is a trade-offbetween sampling frequency,
`amount of smoothing and speed of response. Greater levels of
`
`HALLIBURTON EXHIBIT 1009
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`US 2010/031.2415 A1
`
`Dec. 9, 2010
`
`Smoothing may allow for the detection of Smaller changes in
`cooling performance without incurring a high number of
`nuisance alarms, but may also slow the response time to
`detect those changes. The designer of the system can trade-off
`Smoothing (gain), cost (sampling rate and sensor accuracy)
`and speed of response by choosing the parameters appropri
`ately.
`0048 FIG. 2 is a flow diagram that illustrates an example
`embodiment of a method 200 that monitors cooling efficiency
`with respect to electrical equipment. At 210, a baseline cool
`ing efficiency is established in kWh/degree, or other analo
`gous units. The baseline cooling efficiency may be estab
`lished by receiving a baseline rate ofheat transfer with respect
`to the monitored electrical device and converting the baseline
`rate of heat transfer to a baseline cooling efficiency indicator
`that is ratio of input electrical power to the monitored elec
`trical device and a temperature differential across the moni
`tored electrical device. At 220 an amount of electrical power
`consumed by the monitored electrical device is determined.
`At 230 a monitored electrical device temperature and an
`ambient temperature proximate the monitored electrical
`device are determined to compute a temperature differential
`between the temperature of the monitored electrical device
`and the ambient temperature.
`0049. At 240 an operating cooling efficiency indicator is
`calculated based, at least in part, on a ratio of the electrical
`power consumed by the monitored electrical device and the
`computed temperature differential. At 250 the operating cool
`ing efficiency indicator is compared with the baseline cooling
`efficiency and at 260 if the difference in cooling efficiencies
`exceeds a threshold, a notification that communicates results
`of the comparison between the operating cooling efficiency
`and the baseline cooling efficiency is provided.
`0050. In some embodiments, the baseline heat transfer is
`converted to a baseline cooling efficiency indicator by assign
`ing a heat conversion rate to the monitored electrical device.
`The heat conversion rate is selected based, at least in part, an
`equipment classification of the monitored electrical device.
`For example, computer devices may be assigned a heat con
`version rate of 1 while more efficient (interms of electricity to
`heat generation) devices such as circuit breakers may be
`assigned a rate of less than one.
`0051. By definition, high efficiency equipment, such as
`circuit breakers, have correspondingly low losses as com
`pared to their power input. For Such devices, a model may be
`the preferred method of determining the heat conversion rate
`Ö(x) as compared to measuring the difference between the
`input and output powerfor a given device. This is because the
`difference between input and output power could be smaller
`than the inherent resolution of cost-efficient energy metering
`devices. Also, even if the available metering devices are lower
`cost, measuring input and output power would likely involve
`additional sensors with a commensurate increase in complex
`ity and cost. However, if no sufficiently accurate model exists
`for losses versus loading, even low accuracy energy meters
`could be employed to provide a more accurate measurement
`of Small differential losses using known oversampling tech
`niques.
`0052 While absolute measurement of the cooling effi
`ciency indicator may be less important than the ability to
`detect changes in the cooling efficiency indicator over time,
`determining an accurate baseline cooling efficiency indicator
`is useful to understand how well the equipment is operating at
`the beginning of the monitoring process. The cooling effi
`
`ciency indicator is determined by trending the cooling effi
`ciency of the device over time. However, if the starting point
`for the creation the baseline cooling efficiency indicator is on
`equipment in unknown and perhaps poor operating condition,
`the equipment may already be experiencing cooling prob
`lems yielding a less reliable baseline cooling efficiency
`indicator. Hence, establishing the baseline cooling efficiency
`indicator in conjunction with the performance of a CFD
`model may provide a more beneficial baseline cooling effi
`ciency indicator for high efficiency (in terms of electricity to
`heat generation) electrical devices.
`0053 To augment the CFD model, it is useful to have
`accurately metered losses within the device. For linear elec
`trical equipment operating near full load, these losses tend to
`be primarily resistive and are therefore proportional to the
`square of the current (IR). However, many other losses such
`as eddy current and hysteresis losses are frequently observed,
`especially in devices with magnetic elements (including
`structure Surrounding the equipment). In non-linear (semi
`conductor, iron-core) devices, losses related to Switching fre
`quency and device characteristics are prevalent. Those other
`losses are affected not only by the magnitude of current but
`also by the frequency components contained within the cur
`rent. Since real-world equipment operates in systems with
`current harmonics, accurate loss models should include the
`percentage of frequency current components within the
`energy passing through the device. In Such cases, the external
`parameter X in the calculation of a device's heat conversion
`rate Ö(x) is a function of both loading and frequency compo
`nents, or X f(a,b), where 'a' is a function related to energy
`magnitude and b is a function of changes in current over
`time (i.e., frequency harmonics).
`0054. In some embodiments the baseline heat transfer is
`converted to a baseline cooling efficiency indicator by con
`Verting heat transfer units into electrical power consumption
`units and Solving the Navier-Stokes equation to isolate a ratio
`of the electrical power consumption and a temperature dif
`ferential with respect to a monitored electrical device tem
`perature and an ambient temperature. The baseline heat trans
`fer may be computed using CFD analysis. In some
`embodiments, a rolling average of the operating cooling effi
`ciency indicator is computed and the computed rolling aver
`age is compared with the baseline cooling efficiency indica
`tOr.
`0055. The method 200 may be embodied as a set of com
`puter-executable instructions stored on a computer-readable
`medium. For example, the computer-readable medium may
`be configured to be portable and capable of being used to
`transfer or otherwise provide the set of instructions to a device
`that is to monitor cooling efficiency. Alternatively, the com
`puter-readable medium may be resident within a device that is
`to monitor cooling efficiency (i.e., ASIC). Of course other
`configurations of computer-readable medium, as defined
`herein, may be used in practice the method 200.
`0056 “Computer-readable medium', as used herein,
`refers to a medium that stores signals, instructions and/or
`data. A computer-readable medium may take forms, includ
`ing, but not limited to, non-volatile media, and volatile media.
`Non-volatile media may include, for example, optical disks,
`magnetic disks, and so on. Volatile media may include, for
`example, semiconductor memories, dynamic memory, and so
`on. Common forms of a computer-readable medium may
`include, but are not limited to, a floppy disk, a flexible disk, a
`hard disk, a magnetic tape, other magnetic medium, an ASIC,
`
`HALLIBURTON EXHIBIT 1009
`Halliburton Energy Services, Inc. v. U.S. Well Services, LLC, IPR2023-00558, Page 11
`
`

`

`US 2010/031.2415 A1
`
`Dec. 9, 2010
`
`a CD, other optical medium, a RAM, a ROM, a memory chip
`or card, a memory Stick, and other media from which a com
`puter, a processor or other electronic device can read.
`0057 “Logic', as used herein with respect to apparatus,
`includes but is not limited to hardware, firmware, a method
`encoded as executable steps on a computer-readable medium,
`and/or combinations thereof to perform a function(s) or an
`action(s), and/or to cause a function or action from another
`logic, method, and/or system. Logic may be encoded in one or
`more tangible media that stores computer executable instruc
`tions that if executed by a machine (e.g., ASIC) cause the
`machine to perform the encoded method. Logic may include
`a software controlled microprocessor, discrete logic (e.g.,
`application specific integrated circuit (ASIC)), an analog cir
`cuit, a digital circuit, a programmed logic device, a memory
`device containing instructions, and so on. Logic may include
`a gate(s), a combination of gates, other circuit components,
`and so on. Where multiple logical units are described, it may
`be possible in Some examples to incorporate the multiple
`logical units into one physical logic. Similarly, where a single
`logic is described, it may be possible in Some examples to
`distribute that single

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