Method for operating a linear compressor

Information

  • Patent Grant
  • 10502201
  • Patent Number
    10,502,201
  • Date Filed
    Wednesday, January 28, 2015
    9 years ago
  • Date Issued
    Tuesday, December 10, 2019
    4 years ago
Abstract
A method for operating a linear compressor includes providing a dynamic model for a motor of the linear compressor, estimating values for each unknown constant of a plurality of unknown constants of the dynamic model for the motor and repeatedly updating the estimate for each unknown constant of the plurality of unknown constants of the dynamic model for the motor in order to reduce an error between a measured value for the electrical dynamic model and an estimated valve for the electrical dynamic model.
Description
FIELD OF THE INVENTION

The present subject matter relates generally to linear compressors, such as linear compressors for refrigerator appliances.


BACKGROUND OF THE INVENTION

Certain refrigerator appliances include sealed systems for cooling chilled chambers of the refrigerator appliances. The sealed systems generally include a compressor that generates compressed refrigerant during operation of the sealed systems. The compressed refrigerant flows to an evaporator where heat exchange between the chilled chambers and the refrigerant cools the chilled chambers and food items located therein.


Recently, certain refrigerator appliances have included linear compressors for compressing refrigerant. Linear compressors generally include a piston and a driving coil. The driving coil receives a current that generates a force for sliding the piston forward and backward within a chamber. During motion of the piston within the chamber, the piston compresses refrigerant. Motion of the piston within the chamber is generally controlled such that the piston does not crash against another component of the linear compressor during motion of the piston within the chamber. Such head crashing can damage various components of the linear compressor, such as the piston or an associated cylinder.


While head crashing is preferably avoided, it can be difficult to determine a position of the piston within the chamber. For example, parameters of the linear compressor can vary due to material and/or production differences. In addition, utilizing a sensor to measure the position of the piston can require sensor wires to pierce a hermetically sealed shell of the linear compressor. Passing the sensor wires through the shell provides a path for contaminants to enter the shell.


Accordingly, a method for determining parameters of a linear compressor would be useful. In particular, a method for determining electrical and mechanical parameters of a linear compressor in order to assist with determining a position of a piston of the linear compressor within a chamber of the linear compressor without utilizing a position sensor would be useful.


BRIEF DESCRIPTION OF THE INVENTION

The present subject matter provides a method for operating a linear compressor. The method includes providing a dynamic model for a motor of the linear compressor, estimating values for each unknown constant of a plurality of unknown constants of the dynamic model for the motor and repeatedly updating the estimate for each unknown constant of the plurality of unknown constants of the dynamic model for the motor in order to reduce an error between a measured value for the electrical dynamic model and an estimated valve for the electrical dynamic model. Additional aspects and advantages of the invention will be set forth in part in the following description, or may be apparent from the description, or may be learned through practice of the invention.


In a first exemplary embodiment, a method for operating a linear compressor is provided. The method includes providing an electrical dynamic model for a motor of the linear compressor. The electrical dynamic model for the motor includes a plurality of unknown constants. The method also includes estimating each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor and supplying the motor of the linear compressor with a time varying voltage. The method further includes calculating an error between a measured variable of the electrical dynamic model at a first time and an estimated variable of the electrical dynamic model at the first time and repeatedly updating the estimate for each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor at each time after the first time in order to reduce the error between a measured variable of the electrical dynamic model at each time after the first time and an estimated variable of the electrical dynamic model at each time after the first time.


In a second exemplary embodiment, a method for operating a linear compressor is provided. The method includes providing a mechanical dynamic model for the linear compressor. The mechanical dynamic model for the linear compressor includes a plurality of unknown constants. The method also includes estimating each unknown constant of the plurality of unknown constants of the mechanical dynamic model for the linear compressor and supplying the motor of the linear compressor with a time varying voltage. The method further includes calculating an error between a measured variable of the mechanical dynamic model at a first time and an estimated variable of the mechanical dynamic model at the first time and repeatedly updating the estimate for each unknown constant of the plurality of unknown constants of the mechanical dynamic model for the linear compressor at each time after the first time in order to reduce the error between a measured value for the mechanical dynamic model at each time after the first time and an estimated variable of the mechanical dynamic model at each time after the first time.


These and other features, aspects and advantages of the present invention will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.





BRIEF DESCRIPTION OF THE DRAWINGS

A full and enabling disclosure of the present invention, including the best mode thereof, directed to one of ordinary skill in the art, is set forth in the specification, which makes reference to the appended figures.



FIG. 1 is a front elevation view of a refrigerator appliance according to an exemplary embodiment of the present subject matter.



FIG. 2 is schematic view of certain components of the exemplary refrigerator appliance of FIG. 1.



FIG. 3 provides a perspective view of a linear compressor according to an exemplary embodiment of the present subject matter.



FIG. 4 provides a side section view of the exemplary linear compressor of FIG. 3.



FIG. 5 provides an exploded view of the exemplary linear compressor of FIG. 4.



FIG. 6 illustrates a method for operating a linear compressor according to an exemplary embodiment of the present subject matter.



FIG. 7 illustrates a method for operating a linear compressor according to another exemplary embodiment of the present subject matter.



FIG. 8 illustrates a method for operating a linear compressor according to an additional exemplary embodiment of the present subject matter.



FIGS. 9, 10 and 11 illustrate exemplary plots of experimental electrical motor parameter estimates.





DETAILED DESCRIPTION

Reference now will be made in detail to embodiments of the invention, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Thus, it is intended that the present invention covers such modifications and variations as come within the scope of the appended claims and their equivalents.



FIG. 1 depicts a refrigerator appliance 10 that incorporates a sealed refrigeration system 60 (FIG. 2). It should be appreciated that the term “refrigerator appliance” is used in a generic sense herein to encompass any manner of refrigeration appliance, such as a freezer, refrigerator/freezer combination, and any style or model of conventional refrigerator. In addition, it should be understood that the present subject matter is not limited to use in appliances. Thus, the present subject matter may be used for any other suitable purpose, such as vapor compression within air conditioning units or air compression within air compressors.


In the illustrated exemplary embodiment shown in FIG. 1, the refrigerator appliance 10 is depicted as an upright refrigerator having a cabinet or casing 12 that defines a number of internal chilled storage compartments. In particular, refrigerator appliance 10 includes upper fresh-food compartments 14 having doors 16 and lower freezer compartment 18 having upper drawer 20 and lower drawer 22. The drawers 20 and 22 are “pull-out” drawers in that they can be manually moved into and out of the freezer compartment 18 on suitable slide mechanisms.



FIG. 2 is a schematic view of certain components of refrigerator appliance 10, including a sealed refrigeration system 60 of refrigerator appliance 10. A machinery compartment 62 contains components for executing a known vapor compression cycle for cooling air. The components include a compressor 64, a condenser 66, an expansion device 68, and an evaporator 70 connected in series and charged with a refrigerant. As will be understood by those skilled in the art, refrigeration system 60 may include additional components, e.g., at least one additional evaporator, compressor, expansion device, and/or condenser. As an example, refrigeration system 60 may include two evaporators.


Within refrigeration system 60, refrigerant flows into compressor 64, which operates to increase the pressure of the refrigerant. This compression of the refrigerant raises its temperature, which is lowered by passing the refrigerant through condenser 66. Within condenser 66, heat exchange with ambient air takes place so as to cool the refrigerant. A fan 72 is used to pull air across condenser 66, as illustrated by arrows AC, so as to provide forced convection for a more rapid and efficient heat exchange between the refrigerant within condenser 66 and the ambient air. Thus, as will be understood by those skilled in the art, increasing air flow across condenser 66 can, e.g., increase the efficiency of condenser 66 by improving cooling of the refrigerant contained therein.


An expansion device (e.g., a valve, capillary tube, or other restriction device) 68 receives refrigerant from condenser 66. From expansion device 68, the refrigerant enters evaporator 70. Upon exiting expansion device 68 and entering evaporator 70, the refrigerant drops in pressure. Due to the pressure drop and/or phase change of the refrigerant, evaporator 70 is cool relative to compartments 14 and 18 of refrigerator appliance 10. As such, cooled air is produced and refrigerates compartments 14 and 18 of refrigerator appliance 10. Thus, evaporator 70 is a type of heat exchanger which transfers heat from air passing over evaporator 70 to refrigerant flowing through evaporator 70.


Collectively, the vapor compression cycle components in a refrigeration circuit, associated fans, and associated compartments are sometimes referred to as a sealed refrigeration system operable to force cold air through compartments 14, 18 (FIG. 1). The refrigeration system 60 depicted in FIG. 2 is provided by way of example only. Thus, it is within the scope of the present subject matter for other configurations of the refrigeration system to be used as well.



FIG. 3 provides a perspective view of a linear compressor 100 according to an exemplary embodiment of the present subject matter. FIG. 4 provides a side section view of linear compressor 100. FIG. 5 provides an exploded side section view of linear compressor 100. As discussed in greater detail below, linear compressor 100 is operable to increase a pressure of fluid within a chamber 112 of linear compressor 100. Linear compressor 100 may be used to compress any suitable fluid, such as refrigerant or air. In particular, linear compressor 100 may be used in a refrigerator appliance, such as refrigerator appliance 10 (FIG. 1) in which linear compressor 100 may be used as compressor 64 (FIG. 2). As may be seen in FIG. 3, linear compressor 100 defines an axial direction A, a radial direction R and a circumferential direction C. Linear compressor 100 may be enclosed within a hermetic or air-tight shell (not shown). The hermetic shell can, e.g., hinder or prevent refrigerant from leaking or escaping from refrigeration system 60.


Turning now to FIG. 4, linear compressor 100 includes a casing 110 that extends between a first end portion 102 and a second end portion 104, e.g., along the axial direction A. Casing 110 includes various static or non-moving structural components of linear compressor 100. In particular, casing 110 includes a cylinder assembly 111 that defines a chamber 112. Cylinder assembly 111 is positioned at or adjacent second end portion 104 of casing 110. Chamber 112 extends longitudinally along the axial direction A. Casing 110 also includes a motor mount mid-section 113 and an end cap 115 positioned opposite each other about a motor. A stator, e.g., including an outer back iron 150 and a driving coil 152, of the motor is mounted or secured to casing 110, e.g., such that the stator is sandwiched between motor mount mid-section 113 and end cap 115 of casing 110. Linear compressor 100 also includes valves (such as a discharge valve assembly 117 at an end of chamber 112) that permit refrigerant to enter and exit chamber 112 during operation of linear compressor 100.


A piston assembly 114 with a piston head 116 is slidably received within chamber 112 of cylinder assembly 111. In particular, piston assembly 114 is slidable along a first axis A1 within chamber 112. The first axis A1 may be substantially parallel to the axial direction A. During sliding of piston head 116 within chamber 112, piston head 116 compresses refrigerant within chamber 112. As an example, from a top dead center position, piston head 116 can slide within chamber 112 towards a bottom dead center position along the axial direction A, i.e., an expansion stroke of piston head 116. When piston head 116 reaches the bottom dead center position, piston head 116 changes directions and slides in chamber 112 back towards the top dead center position, i.e., a compression stroke of piston head 116. It should be understood that linear compressor 100 may include an additional piston head and/or additional chamber at an opposite end of linear compressor 100. Thus, linear compressor 100 may have multiple piston heads in alternative exemplary embodiments.


Linear compressor 100 also includes an inner back iron assembly 130. Inner back iron assembly 130 is positioned in the stator of the motor. In particular, outer back iron 150 and/or driving coil 152 may extend about inner back iron assembly 130, e.g., along the circumferential direction C. Inner back iron assembly 130 extends between a first end portion 132 and a second end portion 134, e.g., along the axial direction A.


Inner back iron assembly 130 also has an outer surface 137. At least one driving magnet 140 is mounted to inner back iron assembly 130, e.g., at outer surface 137 of inner back iron assembly 130. Driving magnet 140 may face and/or be exposed to driving coil 152. In particular, driving magnet 140 may be spaced apart from driving coil 152, e.g., along the radial direction R by an air gap AG. Thus, the air gap AG may be defined between opposing surfaces of driving magnet 140 and driving coil 152. Driving magnet 140 may also be mounted or fixed to inner back iron assembly 130 such that an outer surface 142 of driving magnet 140 is substantially flush with outer surface 137 of inner back iron assembly 130. Thus, driving magnet 140 may be inset within inner back iron assembly 130. In such a manner, the magnetic field from driving coil 152 may have to pass through only a single air gap (e.g., air gap AG) between outer back iron 150 and inner back iron assembly 130 during operation of linear compressor 100, and linear compressor 100 may be more efficient than linear compressors with air gaps on both sides of a driving magnet.


As may be seen in FIG. 4, driving coil 152 extends about inner back iron assembly 130, e.g., along the circumferential direction C. Driving coil 152 is operable to move the inner back iron assembly 130 along a second axis A2 during operation of driving coil 152. The second axis may be substantially parallel to the axial direction A and/or the first axis A1. As an example, driving coil 152 may receive a current from a current source (not shown) in order to generate a magnetic field that engages driving magnet 140 and urges piston assembly 114 to move along the axial direction A in order to compress refrigerant within chamber 112 as described above and will be understood by those skilled in the art. In particular, the magnetic field of driving coil 152 may engage driving magnet 140 in order to move inner back iron assembly 130 along the second axis A2 and piston head 116 along the first axis A1 during operation of driving coil 152. Thus, driving coil 152 may slide piston assembly 114 between the top dead center position and the bottom dead center position, e.g., by moving inner back iron assembly 130 along the second axis A2, during operation of driving coil 152.


A piston flex mount 160 is mounted to and extends through inner back iron assembly 130. A coupling 170 extends between piston flex mount 160 and piston assembly 114, e.g., along the axial direction A. Thus, coupling 170 connects inner back iron assembly 130 and piston assembly 114 such that motion of inner back iron assembly 130, e.g., along the axial direction A or the second axis A2, is transferred to piston assembly 114. Piston flex mount 160 defines an input passage 162 that permits refrigerant to flow therethrough.


Linear compressor 100 may include various components for permitting and/or regulating operation of linear compressor 100. In particular, linear compressor 100 includes a controller (not shown) that is configured for regulating operation of linear compressor 100. The controller is in, e.g., operative, communication with the motor, e.g., driving coil 152 of the motor. Thus, the controller may selectively activate driving coil 152, e.g., by supplying current to driving coil 152, in order to compress refrigerant with piston assembly 114 as described above.


The controller includes memory and one or more processing devices such as microprocessors, CPUs or the like, such as general or special purpose microprocessors operable to execute programming instructions or micro-control code associated with operation of linear compressor 100. The memory can represent random access memory such as DRAM, or read only memory such as ROM or FLASH. The processor executes programming instructions stored in the memory. The memory can be a separate component from the processor or can be included onboard within the processor. Alternatively, the controller may be constructed without using a microprocessor, e.g., using a combination of discrete analog and/or digital logic circuitry (such as switches, amplifiers, integrators, comparators, flip-flops, AND gates, field programmable gate arrays (FPGA), and the like) to perform control functionality instead of relying upon software.


Linear compressor 100 also includes a spring assembly 120. Spring assembly 120 is positioned in inner back iron assembly 130. In particular, inner back iron assembly 130 may extend about spring assembly 120, e.g., along the circumferential direction C. Spring assembly 120 also extends between first and second end portions 102 and 104 of casing 110, e.g., along the axial direction A. Spring assembly 120 assists with coupling inner back iron assembly 130 to casing 110, e.g., cylinder assembly 111 of casing 110. In particular, inner back iron assembly 130 is fixed to spring assembly 120 at a middle portion 119 of spring assembly 120.


During operation of driving coil 152, spring assembly 120 supports inner back iron assembly 130. In particular, inner back iron assembly 130 is suspended by spring assembly 120 within the stator or the motor of linear compressor 100 such that motion of inner back iron assembly 130 along the radial direction R is hindered or limited while motion along the second axis A2 is relatively unimpeded. Thus, spring assembly 120 may be substantially stiffer along the radial direction R than along the axial direction A. In such a manner, spring assembly 120 can assist with maintaining a uniformity of the air gap AG between driving magnet 140 and driving coil 152, e.g., along the radial direction R, during operation of the motor and movement of inner back iron assembly 130 on the second axis A2. Spring assembly 120 can also assist with hindering side pull forces of the motor from transmitting to piston assembly 114 and being reacted in cylinder assembly 111 as a friction loss.



FIG. 6 illustrates a method 600 for operating a linear compressor according to an exemplary embodiment of the present subject matter. Method 600 may be used to operate any suitable linear compressor. For example, method 600 may be used to operate linear compressor 100 (FIG. 3). Thus, method 600 is discussed in greater detail below with reference to linear compressor 100. Utilizing method 600 various mechanical and electrical parameters or constants of linear compressor 100 may be established or determined. For example, method 600 may assist with determining or establishing a spring constant of spring assembly 120, a motor force constant of the motor of linear compressor 100, a damping coefficient of linear compressor 100, a resistance of the motor of linear compressor 100, an inductance of the motor of linear compressor 100, a moving mass (such as mass of piston assembly 114 and inner back iron assembly 130) of linear compressor 100, etc. Knowledge of such mechanical and electrical parameters or constants of linear compressor 100 may improve performance or operation of linear compressor 100, as will be understood by those skilled in the art.


At step 610, an electrical dynamic model for the motor of linear compressor 100 is provided. Any suitable electrical dynamic model for the motor of linear compressor 100 may be provided at step 610. For example, the electrical dynamic model for the motor of linear compressor 100 may be







di
dt

=



v
a


L
i


-



r
i


i


L
i


-


α


x
.



L
i







where

    • va is a voltage across the motor of linear compressor 100;
    • ri is a resistance of the motor of linear compressor 100;
    • i is a current through the motor of linear compressor 100;
    • α is a motor force constant;
    • {dot over (x)} is a velocity of the motor of linear compressor 100; and
    • Li is an inductance of the motor of linear compressor 100.


The electrical dynamic model for the motor of linear compressor 100 includes a plurality of unknown constants. In the example provided above, the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 includes the resistance of the motor of linear compressor 100 (e.g., the resistance of driving coil 152), the inductance of the motor of linear compressor 100 (e.g., the inductance of driving coil 152), and the motor force constant. Knowledge or accurate estimates of such unknown constants can improve operation of linear compressor 100, e.g., by permitting operation of linear compressor 100 at a resonant frequency without head crashing.


At step 610, the electrical dynamic model for the motor of linear compressor 100 may also be solved for a particular variable, such as di/dt in the example provided above. Thus, as an example, the electrical dynamic model for the motor of linear compressor 100 may be provided in parametric form as






Φ


=
Δ



W






θ
e







where






W


=
Δ



[




v
a




-
i




-

x
.





]


;





and






θ
e



=
Δ




[




1

L
i






r
i


L
i







L
i





]

.





However, di/dt is difficult to accurately measure or determine. Thus, a filtering technique may be used to account for this signal and provide a useable or implementable signal. In particular, the electrical dynamic model for the motor of linear compressor 100 may be filtered, e.g., with a low-pass filter, to account for this signal. Thus, a filtered electrical dynamic model for the motor of linear compressor 100 may be provided as

Φfcustom characterWfθe.


In alternative exemplary embodiments, the electrical dynamic model for the motor of linear compressor 100 may be solved for {dot over (x)} at step 610. Thus, the electrical dynamic model for the motor of linear compressor 100 may be provided in parametric form as






Φ


=
Δ



W






θ
e







where






Φ


=
Δ



[

di
dt

]


;







W


=
Δ



[




v
a




-
i




-

di
dt





]


;





and






θ
e



=
Δ




[




1






r
i







L
i






]

.






Again, the electrical dynamic model for the motor of linear compressor 100 may be filtered, e.g., to account for di/dt.


At step 620, each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 is estimated. For example, a manufacturer of linear compressor 100 may have a rough estimate or approximation for the value of each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100. Thus, such values of the each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 may be provided at step 620 to estimate each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100.


At step 630, the motor (e.g., driving coil 152) of linear compressor 100 is supplied with a time varying voltage, e.g., by the controller of linear compressor 100. Any suitable time varying voltage may be supplied to the motor of linear compressor 100 at step 630. For example, the time varying voltage may have at least two frequencies components at step 630 when the electrical dynamic model for the motor of linear compressor 100 is solved for di/dt. Thus, the time varying voltage may be

va(t)=v0[sin(2πf1t)+sin(2πf2t)]


where

    • va is a voltage across the motor of linear compressor 100;
    • f1 is a first frequency; and
    • f2 is a second frequency.


The first and second frequencies f1, f2 may be about the resonant frequency of linear compressor 100. In particular, the first and second frequencies f1, f2 may be just greater than and just less than the resonant frequency of linear compressor 100, respectively. For example, the first frequency f1 may be within five percent greater than the resonant frequency of linear compressor 100, and the second frequency f2 may be within five percent less than the resonant frequency of linear compressor 100. In alternative exemplary embodiments, the time varying voltage may have a single frequency at step 630, e.g., when the electrical dynamic model for the motor of linear compressor 100 is solved for {dot over (x)}. When the time varying voltage has a single frequency at step 630, the gas force of fluid within linear compressor 100 may be incorporated within the model for the motor of linear compressor 100.


A time varying current through the motor of linear compressor 100 may also be determined, e.g., during step 630. An ammeter or any other suitable method or mechanism may be used to determine the time varying current through the motor of linear compressor 100. A velocity of the motor of linear compressor 100 may also be measured, e.g., during step 630. As an example, an optical sensor, a Hall effect sensor or any other suitable sensor may be positioned adjacent piston assembly 114 and/or inner back iron assembly 130 in order to permit such sensor to measure the velocity of the motor of linear compressor 100 at step 630. Thus, piston assembly 114 and/or inner back iron assembly 130 may be directly observed in order to measure the velocity of the motor of linear compressor 100 at step 630. In addition, a filtered first derivative of the current through the motor of linear compressor 100 with respect to time may also be measured or determined, e.g., during step 630. Accordingly, the values or filtered values of W may be measured during step 630. To permit such measuring, step 630 and the measurements described above may be conducted prior to sealing the motor of linear compressor 100 within a hermetic shell.


At step 640, an error between a measured variable (e.g., di/dt or {dot over (x)}) of the electrical dynamic model at a first time and an estimated variable of the electrical dynamic model at the first time is calculated. For example, an estimate of θe, {circumflex over (θ)}e, is available, e.g., from step 620. An error between θe and {circumflex over (θ)}e may be given as

{tilde over (θ)}ecustom characterθe−{circumflex over (θ)}e.

However, θe may be unknown while Φf is known or measured. Thus, a related error signal may be used at step 640. The related error signal may be given as

{tilde over (Φ)}fcustom characterΦf−{circumflex over (Φ)}f.

The related error signal along with Wf may be used to update {circumflex over (θ)}e, as described in greater detail below.


At step 650, the estimate for each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 are repeatedly updated at each time after the first time in order to reduce the error between a measured variable of the electrical dynamic model at each time after the first time and an estimated variable of the electrical dynamic model at each time after the first time. In particular, an adaptive least-squares algorithm may be utilized in order to drive the error between the measured value for the electrical dynamic model at each time after the first time and the estimated variable of the electrical dynamic model at each time after the first time towards zero. In particular, the Adaptive Least-Squares Update Law ensures that









θ
~

e



(
t
)





0





as





t






:













θ
^

.

e



=
Δ




-

k
e






P
e



W
f
T




Φ
~

f



1
+


γ
e



W
f



P
e



W
f
T






,








θ
^

e



(

t
0

)







is





estimated

,





e
.
g
.

,





at





step





620.





where Pe(t)∈custom character3×3 is the covariance matrix









P
.

e



=
Δ




-

k
e






P
e



W
f
T



W
f



P
e



1
+


γ
e



W
f



W
f
T






,







P
e



(

t
0

)


=


ρ
e



I
3







where ke, γe, ρecustom character+ are constant gains.


From {circumflex over (θ)}e, estimates of each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 may be given as








α
^

=



θ
^


e
3




θ
^


e
1




,


R
^

=



θ
^


e
2




θ
^


e
1




,


L
^

=

1


θ
^


e
1









when the electrical dynamic model for the motor of linear compressor 100 is solved for di/dt at step 610 or








α
^

=

1


θ
^


e
1




,


R
^

=



θ
^


e
2




θ
^


e
1




,


L
^

=



θ
^


e
3




θ
^


e
1









when the electrical dynamic model for the motor of linear compressor 100 is solved for {dot over (x)} at step 610.



FIGS. 9, 10 and 11 illustrate exemplary plots of experimental electrical motor parameter estimates, e.g., taken during steps 640 and 650. As may be seen in FIGS. 9, 10 and 11, the initial estimate provided for the electrical motor parameters of linear compressor 100 may be off an actual or previously determined value. However, the experimental electrical motor parameter estimates converge to the previously determined values over time.


With the unknown constants of the electrical dynamic model for the motor of linear compressor 100 suitably estimated, a final estimate for each unknown constant of the plurality of unknown constants of the electrical dynamic model for the motor of linear compressor 100 may be saved within the controller of linear compressor 100. The saved constant values may be used to facilitate efficient and/or proper operation of linear compressor 100. In particular, knowledge of the constants of the electrical dynamic model for the motor of linear compressor 100 may assist with operating linear compressor 100 at a resonant frequency while avoiding head crashing.


As discussed above, method 600 may also provide estimates of the mechanical parameters or constants of linear compressor 100. Thus, method 600 may also include providing a mechanical dynamic model for linear compressor 100. Any suitable mechanical dynamic model for linear compressor 100 may be provided. For example, the mechanical dynamic model for linear compressor 100 may be







F
m

=


i


(
t
)


=



M
α



x
¨


+


C
α



x
.


+


K
α


x







where

    • M is a moving mass of linear compressor 100;
    • α is a motor force constant;
    • {umlaut over (x)} is an acceleration of the motor of linear compressor 100;
    • C is a damping coefficient of linear compressor 100;
    • {dot over (x)} is a velocity of the motor of linear compressor 100;
    • K is a spring stiffness of linear compressor 100; and
    • x is a position of the moving mass of linear compressor 100.


The mechanical dynamic model for linear compressor 100 includes a plurality of unknown constants. In the example provided above, the plurality of unknown constants of the mechanical dynamic model of linear compressor 100 includes a moving mass of linear compressor 100 (e.g., a mass of piston assembly 114 and inner back iron assembly 130), a damping coefficient of linear compressor 100, and a spring stiffness of linear compressor 100 (e.g., a stiffness of spring assembly 120). Knowledge or accurate estimates of such unknown constants can improve operation of linear compressor 100, e.g., by permitting operation of linear compressor 100 at a resonant frequency without head crashing.


The mechanical dynamic model for linear compressor 100 may also be solved for a particular variable, such as i(t) in the example provided above. Thus, as an example, the electrical dynamic model for the motor of linear compressor 100 may be provided in parametric form as






Ψ


=
Δ



Y






θ
m







where






Ψ


=
Δ



[
i
]


;







Y


=
Δ



[




x
¨




x
.



x



]


;





and






θ
m



=
Δ





[




M





C





K





]

T

.





However, {umlaut over (x)} is difficult to accurately measure or determine. Thus, a filtering technique may be used to account for this signal and provide a measurable variable. In particular, the mechanical dynamic model for linear compressor 100 may be filtered, e.g., with a low-pass filter, to account for this signal. Thus, a filtered electrical dynamic model for the motor of linear compressor 100 may be provided as

Ψfcustom characterYfθm.

Each unknown constant of the plurality of unknown constants of the mechanical dynamic model for linear compressor 100 may also be estimated, and the motor (e.g., driving coil 152) of linear compressor 100 may be supplied with a time varying voltage, e.g., in the manner described above for steps 620 and 630.


An error between a measured variable of the mechanical dynamic model at the first time and an estimated variable of the mechanical dynamic model at the first time may also be calculated. For example, an estimate of θm, {circumflex over (θ)}m, is available as discussed above. An error between θm, and {circumflex over (θ)}m may be given as

{tilde over (θ)}mcustom characterθm−{circumflex over (θ)}m.

However, θm, may be unknown while Ψf is known or measured. Thus, a related error signal may be used. The related error signal may be given as

{tilde over (Ψ)}fcustom characterΨf−{circumflex over (Ψ)}f.

The related error signal along with Yf may be used to update {circumflex over (θ)}m, as described in greater detail below.


The estimate for each unknown constant of the plurality of unknown constants of the mechanical dynamic model for linear compressor 100 are repeatedly updated at each time after the first time in order to reduce the error between a measured variable of the mechanical dynamic model at each time after the first time and an estimated variable of the mechanical dynamic model at each time after the first time. In particular, an adaptive least-squares algorithm may be utilized in order to drive the error between the measured value for the mechanical dynamic model at each time after the first time and the estimated variable of the mechanical dynamic model at each time after the first time towards zero. In particular, the Adaptive Least-Squares Update Law ensures that











θ
~

m



(
t
)





0





as





t




:







θ
^

.


m











=
Δ




-

k
m






P
m



Y
f
T




Ψ
~

f



1
+


γ
m



Y
f



P
m



Y
f
T






,








θ
^

m



(

t
0

)







is






estimated
.






where Pm(t)∈custom character3×3 is the covariance matrix









P
.

m



=
Δ




-

k
m






P
m



Y
f
T



Y
f



P
m



1
+


γ
m



Y
f



Y
f
T






,







P
m



(

t
0

)


=


ρ
m



I
3







where km, γm, ρmcustom character+ are constant gains.


From {circumflex over (θ)}m and the estimate of the motor force constant from step 650, estimates of each unknown constant of the plurality of unknown constants of the mechanical dynamic model for linear compressor 100 may be given as

{circumflex over (M)}={circumflex over (α)}{circumflex over (θ)}m1,Ĉ={circumflex over (α)}{circumflex over (θ)}m2,{circumflex over (K)}={circumflex over (α)}{circumflex over (θ)}m3.


With the unknown constants of the mechanical dynamic model for linear compressor 100 suitably estimated, a final estimate for each unknown constant of the plurality of unknown constants of the mechanical dynamic model for linear compressor 100 may be saved within the controller of linear compressor 100. The saved constant values may be used to facilitate efficient and/or proper operation of linear compressor 100. In particular, knowledge of the constants of the mechanical dynamic model for linear compressor 100 may assist with operating linear compressor 100 at a resonant frequency while avoiding head crashing.



FIG. 7 illustrates a method 700 for operating a linear compressor according to another exemplary embodiment of the present subject matter. Method 700 may be used to operate any suitable linear compressor. For example, method 700 may be used to operate linear compressor 100 (FIG. 3). Thus, method 700 is discussed in greater detail below with reference to linear compressor 100. Utilizing method 700, a stroke length of the motor of linear compressor 100 may be established or determined. Knowledge of the stroke length of the motor of linear compressor 100 may improve performance or operation of linear compressor 100, as will be understood by those skilled in the art.


At step 710, an electrical dynamic model for the motor of linear compressor 100 is provided. Any suitable electrical dynamic model for the motor of linear compressor 100 may be provided at step 710. For example, the electrical dynamic model for the motor of linear compressor 100 described above for step 610 of method 600 may be used at step 710. The electrical dynamic model for the motor of linear compressor 100 may also be modified such that







di
dt

=



v
a


L
i


-



r
i


i


L
i


-
f






where





f
=


α

L
i





x
.

.






At step 720, the motor (e.g., driving coil 152) of linear compressor 100 is supplied with a time varying voltage, e.g., by the controller of linear compressor 100. Any suitable time varying voltage may be supplied to the motor of linear compressor 100 at step 720. As an example, the motor (e.g., driving coil 152) of linear compressor 100 may be supplied with a time varying voltage in the manner described above for step 630 of method 600. A time varying current through the motor of linear compressor 100 may also be determined, e.g., during step 720. An ammeter any other suitable method or mechanism may be used to determine the time varying current through the motor of linear compressor 100.


At step 730, a back-EMF of the motor of linear compressor 100 is estimated, e.g., during step 720. The back-EMF of the motor of linear compressor 100 may be estimated at step 730 using at least the electrical dynamic model for the motor of linear compressor 100 and a robust integral of the sign of the error feedback. As an example, the back-EMF of the motor of linear compressor 100 may be estimated at step 730 by solving

{circumflex over (f)}=(K1+1)e(t)+∫t0t[(K1+1)e(σ)+K2sgn(e(σ))]dσ−(K1+1)e(t0)


where

    • {circumflex over (f)} is an estimated back-EMF of the motor of linear compressor 100;
    • K1 and K2 are real, positive gains; and
    • e=î−i and ė=f−{circumflex over (f)}; and
    • sgn is the signum or sign function.


At step 740, a velocity of the motor of linear compressor 100 is estimated. The velocity of the motor of linear compressor 100 may be estimated at step 740 based at least in part on the back-EMF of the motor from step 730. For example, the velocity of the motor of linear compressor 100 may be determined at step 740 by solving








x
.

^

=



L
i

α



f
^






where

    • {dot over ({circumflex over (x)})} is an estimated velocity of the motor of linear compressor 100;
    • α is a motor force constant; and
    • Li is an inductance of the motor of linear compressor 100.


      The motor force constant and the inductance of the motor of linear compressor 100 may be estimated with method 600, as described above.


At step 750, a stroke length of the motor of linear compressor 100 is estimated. The stroke length of the motor of linear compressor 100 may be estimated at step 750 based at least in part on the velocity of the motor from step 740. In particular, the stroke length of the motor of linear compressor 100 may be estimated at step 750 by solving






X
=




L
i

α






f
^


dt



=



x
^

initial

+


x
^



(
t
)








where {circumflex over (x)} is an estimated position of the motor of linear compressor 100.


It should be understood that steps 720, 730, 740 and 750 may be performed with the motor of linear compressor 100 sealed within a hermitic shell of linear compressor 100. Thus, method 700 may be performed at any suitable time during operation of linear compressor 100 in order to determine the stroke length of the motor of linear compressor 100, e.g., because moving components of linear compressor 100 need not be directly measured with a sensor. Knowledge of the stroke length of the motor of linear compressor 100 may assist with operating linear compressor 100 efficiently and/or properly. For example, such knowledge may assist with adjusting the time varying voltage supplied to the motor of the linear compressor 100 in order to operate the motor of linear compressor 100 at a resonant frequency of the motor of linear compressor 100 without head crashing, etc., as will be understood by those skilled in the art.



FIG. 8 illustrates a method 800 for operating a linear compressor according to an additional exemplary embodiment of the present subject matter. Method 800 may be used to operate any suitable linear compressor. For example, method 800 may be used to operate linear compressor 100 (FIG. 3). Thus, method 800 is discussed in greater detail below with reference to linear compressor 100. Utilizing method 800, a position of the motor of linear compressor 100 when the motor of linear compressor 100 is at a top dead center point may be established or determined. Knowledge of the motor of linear compressor 100 at the top dead center point may improve performance or operation of linear compressor 100, as will be understood by those skilled in the art.


At step 810, a mechanical dynamic model for linear compressor 100 is provided. Any suitable mechanical dynamic model for linear compressor 100 may be provided. For example, the mechanical dynamic model for linear compressor 100 described above for method 600 may be used at step 810. As another example, the mechanical dynamic model for linear compressor 100 may be

Fm=αi=M{umlaut over (x)}+C{dot over (x)}+K(xavg−x0)+Fgas


where

    • M is a moving mass of linear compressor 100;
    • α is a motor force constant;
    • {umlaut over (x)} is an acceleration of the motor of linear compressor 100;
    • C is a damping coefficient of linear compressor 100;
    • {dot over (x)} is a velocity of the motor of linear compressor 100;
    • K is a spring stiffness of linear compressor 100;
    • x is a position of the moving mass of linear compressor 100; and
    • Fgas is a gas force.


      Solving for acceleration, the mechanical dynamic model for linear compressor 100 may be given as







x
¨

=




-

C
M




x
.


-


K
M



(


x
avg

-

x
0


)


+


α
M


i

+


1
M



F
gas



=



α
M


i

+


f
x



(
t
)









where







f
x



(
t
)


=



1
M



F
gas


-


C
M



x
.


-


K
M



(


x
avg

-

x
0


)


+


α
M



i
.







At step 820, the motor (e.g., driving coil 152) of linear compressor 100 is supplied with a time varying voltage, e.g., by the controller of linear compressor 100. Any suitable time varying voltage may be supplied to the motor of linear compressor 100 at step 820. As an example, the motor (e.g., driving coil 152) of linear compressor 100 may be supplied with a time varying voltage in the manner described above for step 630 of method 600. At step 830, a time varying current through the motor of linear compressor 100 may also be determined, e.g., during step 820. In particular, a current to the motor of linear compressor 100 may be measured at step 830 when the motor of linear compressor 100 is at a bottom dead center point. Thus, a velocity of the motor of linear compressor 100 may be zero or about (e.g., within about a tenth of a meter per second) zero when the current to the motor of linear compressor 100 is measured at step 830. A voltmeter or any other suitable method or mechanism may be used to determine the current through the motor of linear compressor 100.


At step 840, an acceleration of the motor of linear compressor 100 is estimated, e.g., during step 820. The acceleration of the motor of linear compressor 100 may be estimated at step 840 using at least the mechanical dynamic model for linear compressor 100 and a robust integral of the sign of the error feedback. As an example, the acceleration of the motor of linear compressor 100 may be estimated at step 840 by solving








x
¨

^

=



α
M


i

+



f
^

x



(
t
)








with {circumflex over (f)}x being given as

{circumflex over (f)}x=(k1+1)ex(t)+∫t0t[(k1+1)ex(σ)+k2sgn(ex(σ))]dσ−(k1+1)ex(t0)


and where

    • {umlaut over ({circumflex over (x)})} is an estimated acceleration of the motor of linear compressor 100;
    • k1 and k2 are real, positive gains; and
    • ex={dot over (x)}−{circumflex over ({dot over (x)})} and sxx+ex.


At step 850, a position of the motor of linear compressor 100 when the motor of the linear compressor 100 is at the bottom dead center point is determined. The position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the bottom dead center point may be estimated at step 850 based at least in part on the current to the motor of linear compressor 100 from step 830 and the acceleration of the motor from step 840. For example, the position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the bottom dead center point may be estimated at step 850 by solving







x
BDC

=



α
K



i
BDC


-


M
K




x
¨

BDC







where

    • α is a motor force constant;
    • K is a spring stiffness of linear compressor 100;
    • iBDC is the current to the motor of linear compressor 100 at the bottom dead center point;
    • M is a moving mass of linear compressor 100; and
    • {umlaut over (x)}BDC is the acceleration of the motor at the bottom dead center point.


      The motor force constant, the spring stiffness of linear compressor 100 and the moving mass of linear compressor 100 may be estimated with method 600, as described above.


At step 860, a position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the top dead center point is determined. The position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the top dead center point may be estimated at step 860 based at least in part on the position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the bottom dead center point from step 850 and a stroke length of the motor of linear compressor 100. For example, the position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the top dead center point may be estimated at step 860 by solving

xTDC=xBDC−SL


where SL is the stroke length of the motor of linear compressor 100. The stroke length of the motor of linear compressor 100 may be estimated with method 700, as described above.


It should be understood that steps 820, 830, 840, 850 and 860 may be performed with the motor of linear compressor 100 sealed within a hermitic shell of linear compressor 100. Thus, method 800 may be performed at any suitable time during operation of linear compressor 100 in order to determine the position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the top dead center point, e.g., because moving components of linear compressor 100 need not be directly measured with a sensor. Knowledge of the position of the motor of linear compressor 100 when the motor of linear compressor 100 is at the top dead center point may assist with operating linear compressor 100 efficiently and/or properly. For example, such knowledge may assist with adjusting the time varying voltage supplied to the motor of the linear compressor 100 in order to operate the motor of linear compressor 100 at a resonant frequency of the motor of linear compressor 100 without head crashing, etc., as will be understood by those skilled in the art.


This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they include structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.

Claims
  • 1. A method for estimating parameters of a linear compressor, comprising: providing an electrical dynamic model for a motor of the linear compressor, the electrical dynamic model for the motor comprising a plurality of constants and a plurality of variables, the plurality of constants of the electrical dynamic model for the motor comprising a resistance of the motor of the linear compressor, an inductance of the motor of the linear compressor, and a motor force constant, the plurality of constants of the electrical dynamic model for the motor comprising a velocity of the motor of the linear compressor;estimating each constant of the plurality of constants of the electrical dynamic model for the motor;supplying the motor of the linear compressor with a time varying voltage;measuring the velocity of the motor of the linear compressor with a sensor while supplying the motor of the linear compressor with the time varying voltage;determining a time varying current through the motor of the linear compressor while supplying the motor of the linear compressor with the time varying voltage;calculating an error between the measured velocity of the motor of the linear compressor-at a first time and an estimated velocity of the motor of the linear compressor from the electrical dynamic model at the first time;repeatedly updating the estimate for each constant of the plurality of constants of the electrical dynamic model for the motor at each time after the first time in order to reduce the error between the measured velocity of the motor of the linear compressor at each time after the first time and an estimated velocity of the motor of the linear compressor from the electrical dynamic model at each time after the first time;saving a final estimate for each constant of the plurality of constants of the electrical dynamic model for the motor in a controller of the linear compressor after said step of repeatedly updating, the controller configured to operate the motor of the linear compressor based at least in part with the final estimate for each constant of the plurality of constants of the electrical dynamic model; andsealing the motor of the linear compressor within a hermetic shell after said steps of supplying, calculating and repeatedly updating.
  • 2. The method of claim 1, wherein the electrical dynamic model for the motor comprises
  • 3. The method of claim 1, further comprising filtering the electrical dynamic model for the motor with a low-pass filter.
  • 4. The method of claim 1, wherein said step of repeatedly updating comprises utilizing an adaptive least-squares algorithm in order to drive the error between the measured value for the electrical dynamic model at each time after the first time and the estimated variable of the electrical dynamic model at each time after the first time towards zero.
  • 5. The method of claim 1, wherein the time varying voltage has at least two frequencies components during said step of supplying.
  • 6. The method of claim 1, further comprising: providing a mechanical dynamic model for the linear compressor, the mechanical dynamic model for the linear compressor also comprising a plurality of constants;estimating each constant of the plurality of constants of the mechanical dynamic model for the linear compressor;calculating an error between a measured variable of the mechanical dynamic model at the first time and an estimated variable of the mechanical dynamic model at the first time; andrepeatedly updating the estimate for each constant of the plurality of constants of the mechanical dynamic model for the linear compressor at each time after the first time in order to reduce the error between a measured value for the mechanical dynamic model at each time after the first time and an estimated variable of the mechanical dynamic model at each time after the first time.
  • 7. A method for estimating parameters of a linear compressor, comprising: providing a mechanical dynamic model for the linear compressor, the mechanical dynamic model for the linear compressor comprising a plurality of constants and a plurality of variables, the plurality of constants of the mechanical dynamic model for the linear compressor comprising a moving mass of the linear compressor, a damping coefficient of the linear compressor, and a spring stiffness of the linear compressor, the plurality of constants of the mechanical dynamic model for the motor comprising a velocity of the motor of the linear compressor;estimating each constant of the plurality of constants of the mechanical dynamic model for the linear compressor;supplying a motor of the linear compressor with a time varying voltage;measuring the velocity of the motor of the linear compressor with a sensor while supplying the motor of the linear compressor with the time varying voltage;determining a time varying current through the motor of the linear compressor while supplying the motor of the linear compressor with the time varying voltage;calculating an error between the measured velocity of the motor of the linear compressor at a first time and an estimated velocity of the motor of the linear compressor from the mechanical dynamic model at the first time; andrepeatedly updating the estimate for each constant of the plurality of constants of the mechanical dynamic model for the linear compressor at each time after the first time in order to reduce the error between the measured velocity of the motor of the linear compressor at each time after the first time and an estimated velocity of the motor of the linear compressor from the mechanical dynamic model at each time after the first time;saving a final estimate for each constant of the plurality of constants of the mechanical dynamic model for the linear compressor in a controller of the linear compressor after said step of repeatedly updating, the controller configured to operate the motor of the linear compressor based at least in part with the final estimate for each constant of the plurality of constants of the mechanical dynamic model; andsealing the motor of the linear compressor within a hermetic shell after said steps of supplying, calculating and repeatedly updating.
  • 8. The method of claim 7, wherein the mechanical dynamic model for the linear compressor comprises Fm=M{umlaut over (x)}+C{dot over (x)}+Kx where M is a moving mass of the linear compressor;{umlaut over (x)} is an acceleration of the motor of the linear compressor;C is a damping coefficient of the linear compressor;{dot over (x)} is a velocity of the motor of the linear compressor;K is a spring stiffness of the linear compressor; andx is a position of the moving mass of the linear compressor.
  • 9. The method of claim 7, further comprising filtering the mechanical dynamic model for the linear compressor with a low-pass filter.
  • 10. The method of claim 7, wherein said step of repeatedly updating comprises utilizing an adaptive least-squares algorithm in order to drive the error between the measured value for the mechanical dynamic model at each time after the first time and the estimated variable of the mechanical dynamic model at each time after the first time towards zero.
  • 11. The method of claim 7, wherein the time varying voltage has at least two frequencies components during said step of supplying.
US Referenced Citations (113)
Number Name Date Kind
3782859 Schuman Jan 1974 A
4291258 Clark et al. Sep 1981 A
4353220 Curwen et al. Oct 1982 A
4538964 Brown Sep 1985 A
5146124 Higham et al. Sep 1992 A
5342176 Redlich Aug 1994 A
5381092 Freedman Jan 1995 A
5496153 Redlich Mar 1996 A
5525845 Beale et al. Jun 1996 A
5598076 Neubauer et al. Jan 1997 A
5818131 Zhang Oct 1998 A
5944302 Loc et al. Aug 1999 A
5980211 Tojo et al. Nov 1999 A
6231310 Tojo et al. May 2001 B1
6247900 Archibald Jun 2001 B1
6289680 Oh et al. Sep 2001 B1
6753665 Ueda Jun 2004 B2
6811380 Kim Nov 2004 B2
6812597 McGill et al. Nov 2004 B2
6883333 Shearer et al. Apr 2005 B2
6946754 Inagaki et al. Sep 2005 B2
6960893 Yoshida et al. Nov 2005 B2
7020595 Adibhatla et al. Mar 2006 B1
7187152 Tsai Mar 2007 B1
7439692 Lee Oct 2008 B2
7453229 Lee et al. Nov 2008 B2
7456592 Yoo et al. Nov 2008 B2
7497146 Clausin Mar 2009 B2
7550941 Dainez Jun 2009 B2
7614856 Inagaki et al. Nov 2009 B2
7618243 Tian et al. Nov 2009 B2
7628591 Yoo Dec 2009 B2
7663275 McGill et al. Feb 2010 B2
8011183 Berchowitz Sep 2011 B2
8127560 Dicken et al. Mar 2012 B2
8177523 Patel et al. May 2012 B2
8241015 Lillie et al. Aug 2012 B2
8749112 Buquet Jun 2014 B2
8784069 Lilie Jul 2014 B2
9470223 Mallampalli et al. Oct 2016 B2
9518578 Dainez et al. Dec 2016 B2
9890778 Kusumba et al. Feb 2018 B2
9970426 Kim May 2018 B2
20010005320 Ueda et al. Jun 2001 A1
20020093327 Yoo et al. Jul 2002 A1
20020150477 Hwang et al. Oct 2002 A1
20030026703 Yoo Feb 2003 A1
20030044286 Kim Mar 2003 A1
20030099550 Kim May 2003 A1
20030108430 Yoshida et al. Jun 2003 A1
20030147759 Chang Aug 2003 A1
20030161734 Kim Aug 2003 A1
20030177773 Kim Sep 2003 A1
20030201745 Hayashi Oct 2003 A1
20040005222 Yoshida et al. Jan 2004 A1
20040066163 Yoo Apr 2004 A1
20040067140 Yoo Apr 2004 A1
20040071556 Sung Apr 2004 A1
20040119434 Dadd Jun 2004 A1
20040169480 Ueda et al. Sep 2004 A1
20040189103 Duncan Sep 2004 A1
20040236494 DeBotton et al. Nov 2004 A1
20050031470 Lee Feb 2005 A1
20050083196 Furem et al. Apr 2005 A1
20050111987 Yoo May 2005 A1
20050137722 Yoo Jun 2005 A1
20050141998 Yoo Jun 2005 A1
20050168179 McGill Aug 2005 A1
20060070518 McGill Apr 2006 A1
20060110259 Puff et al. May 2006 A1
20060171814 Dainez Aug 2006 A1
20060171822 Seagar et al. Aug 2006 A1
20060228221 Heo Oct 2006 A1
20060228224 Hong Oct 2006 A1
20060251524 Yoo Nov 2006 A1
20060257264 Kim Nov 2006 A1
20070095073 Tian et al. May 2007 A1
20070159128 Dainez et al. Jul 2007 A1
20070196214 Bocchiola Aug 2007 A1
20070241697 Sung et al. Oct 2007 A1
20070241698 Sung et al. Oct 2007 A1
20070276544 Dainez Nov 2007 A1
20080294098 Sarkinen Nov 2008 A1
20090004026 Yoo et al. Jan 2009 A1
20090010766 Yoo et al. Jan 2009 A1
20090039655 Berchowitz Feb 2009 A1
20090047138 Yoo et al. Feb 2009 A1
20090094977 Hill Apr 2009 A1
20090097987 Sung et al. Apr 2009 A1
20090263262 McGill Oct 2009 A1
20100047079 Reinschke Feb 2010 A1
20110056196 Berchowitz et al. Mar 2011 A1
20110056235 Hoshino Mar 2011 A1
20110058960 Bernhard Lilie et al. Mar 2011 A1
20110103973 Dainez May 2011 A1
20120177513 Lilie et al. Jul 2012 A1
20120257993 Ono Oct 2012 A1
20130034456 Schoegler Feb 2013 A1
20130189119 Dainez Jul 2013 A1
20130243607 Dainez et al. Sep 2013 A1
20140072461 Barito Mar 2014 A1
20140186194 Dainez Jul 2014 A1
20140234137 Roman Aug 2014 A1
20140333236 Yamanaka et al. Nov 2014 A1
20150125323 Stair May 2015 A1
20150226195 Mallampalli et al. Aug 2015 A1
20160215767 Kusumba et al. Jul 2016 A1
20160215770 Kusumba et al. Jul 2016 A1
20160215772 Kusumba et al. Jul 2016 A1
20160305420 Adler et al. Oct 2016 A1
20170009762 Lilie et al. Jan 2017 A1
20170122305 Kusumba et al. May 2017 A1
20170122309 Kusumba et al. May 2017 A1
Foreign Referenced Citations (10)
Number Date Country
0620367 Apr 1993 EP
2686554 Jan 2014 EP
H09287558 Nov 1997 JP
2003315205 Nov 2003 JP
3762469 Apr 2006 JP
WO 0079671 Dec 2000 WO
WO 2005028841 Mar 2005 WO
WO 2006013377 Feb 2006 WO
WO 2006081642 Aug 2006 WO
WO 2013003923 Jan 2013 WO
Non-Patent Literature Citations (8)
Entry
Bidikli, Tatlicioglu, Bayrak, Zergeroglu, A New Robust ‘Integral of Sign of Error’ Feedback Controller with Adaptive Compensation Gain, 52nd IEEE Conference on Decision and Control Dec. 10-13, 2013 pp. 3782-3786.
Xian, Dawson, Queiroz, Chen, A Continuous Asymptotic Tracking Control Strategy for Uncertain Nonlinear Systems, IEEE Transactions on Automatic Control, vol. 49, No. 7, Jul. 2004, pp. 1206-1210.
Chen, Zhen; Yao, Bin; Wang, Qingfeng, Accurate Motion Control of Linear Motors with Adaptive Robust Compensation of Non-Linear Electromagnetic Field Effect, Proceedings of the ASME 2011 Dynamic Systems and Control Conference, DSCC2011-5991, Arlington VA, 2011.
Beck, Wesley, Pump Handbook (2007) McGraw-Hill, 4th Edition, Chapter 16 Pump Testing (Year: 2007).
Chiang et al., Innovative Linear Compressor by Magnetic Drive and Control, (Proceedings of 2011 International Conference on Modelling, Identification and Control, Shanghai, China, Jun. 26-29, 2011), pp. 300-305.
Mantri et al., Development and Validation of Integrated Design Framework for Compressor System Model, Purdue University / Purdue e-Pubs, International Compressor Engineering Conference, School of Mechanical Engineering, 2014 (10 pages).
Mehta et al., Principles of Electrical Engineering and Electronics, Jan. 1, 2006, S. Chand & Company Ltd., 2nd Ed., pp. 275-277.
Smith, The Scientist and Engineer's Guide to Digital Signal Processing, Second Edition, published 1999, 22 pages.
Related Publications (1)
Number Date Country
20160215772 A1 Jul 2016 US