1. A method of predicting remaining useful life (RUL) of a rechargeable battery, comprising the steps of:
(a) determining a capacity of a battery based on at least changes between a first state of charge (SOC) value determined at a first time (SOC1) and a second SOC value determined at a second time (SOC2) and a net charge flow of the battery;
(b) applying a particle filter to a capacity degradation model using the determined capacity to form an adjusted capacity degradation model for the battery; and
(c) predicting the RUL of the battery using the adjusted capacity degradation model with a pre-defined EOS threshold.
2. The method of claim 1, wherein the capacity degradation model can be a hybrid or exponential capacity degradation model.
3. The method of claim 1, wherein the exponential capacity degradation model is expressed by the formula:
c
i
=
C
i
C
0
=
1
–
\u03b1
\ue8a0
1
–
exp
\ue8a0
(
–
\u03bb\uf74e
)
–
\u03b2\uf74e
wherein Ci is a capacity at ith the cycle, C0 is the initial capacity, \u03b1 is a coefficient of the exponential component of capacity fade, \u03bb is an exponential capacity fade rate, \u03b2 is a coefficient of the linear component of capacity fade, and ci is a normalized capacity at the ith cycle.
4. The method of claim 1, wherein the battery is selected from a group consisting of nickel-metal hydride battery, nickel-cadmium battery, lithium-ion polymer battery, lithium sulfur battery, thin film battery, smart battery, carbon foam-based lead acid battery, potassium-ion battery, and sodium-ion battery.
5. The method of claim 1, wherein the SOC1 value is determined as a function of a first open circuit voltage measurement (V1) of the battery made before a partial charge or discharge period and the SOC2 value is determined as a function of a second open circuit voltage measurement (V2) made after a partial charge or discharge period.
6. The method of claim 5, wherein the net charge flow (\u0394Q) is determined by measuring the current of the charge and integrating the current over the charge or discharge period.
7. The method of claim 6, wherein the capacity (C) of the battery is determined using the following equation:
C=\u0394Q|SOC1\u2212SOC2|.
8. The method of claim 5, wherein the C is determined using the following equation:
C
k
=
\u222b
t
k
t
k
+
L
\ue89e
\uf74e
\ue8a0
(
t
)
\ue89e
\ue89e
\uf74c
t
SOC
k
+
L
–
SOC
k
wherein Ck is the capacity, SOC is the state of charge, k is the index of the measurement time step at the beginning of the partial charge or discharge, L is the number of measurement time steps over the partial charge or discharge, tk and tk+L are respectively the time points at the beginning and end of the partial charge or discharge, and i is the current
9. The method of claim 1, wherein the particle filter is selected from a group consisting of a standard sequential importance sampling and resampling particle filter, a standard sequential importance sampling particle filter, a standard sequential importance resampling filter, an extended Kalman filter, an unscented Kalman filter, and a Gauss-Hermite particle filter.
10. The method of claim 9, wherein an optimal proposal importance density used in the particle filter is derived from formula:
q(xi|x0:i\u22121,y1:i)=p(xi|xi\u22121,yi)
wherein x is a state estimate and y is a system observation.
11. The method of claim 10, wherein the Gauss-Hermite particle filter is used in the determination of the RUL of the battery, and the method further comprises the steps of:
(a) determining the capacity at an ith cycle;
(b) determining a system transition and a measurement function;
(c) determining a posterior PDF of the normalized capacity by the Gauss-Hermite particle filter;
(d) predicting normalized capacity forward by a cycle number;
(e) determining RUL for each particle; and
(f) determining RUL distribution.
12. The method of claim 11, wherein the determination of system transition and measurement function uses formulas:
ci=1\u2212\u03b1i\u221211\u2212exp(\u2212\u03bbi\u22121i)\u2212\u03b2i\u22121i+ui,\u03b1i=\u03b1i\u22121+r1,i,\u03bbi=\u03bbi\u22121+r2,i,\u03b2i=\u03b2i\u22121+r3,i\u2003\u2003Transition:
yi=ci+vi\u2003\u2003Measurement:
wherein ci is the normalized capacity at the ith cycle, \u03b1 is the coefficient of the exponential component of capacity fade, \u03bb is the exponential capacity fade rate, \u03b2 is the coefficient of the linear component of capacity fade, yi is the capacity measurement at the ith cycle, and u, r1, r2, r3 and v are the Gaussian noise variables with zero means.
13. The method of claim 11, wherein determination of a posterior PDF of the normalized capacity by the Gauss-Hermite particle filter uses formula:
p
\ue8a0
(
c
i
|
y
1
\ue89e
:
\ue89e
i
)
\u2248
1
N
P
\ue89e
\u2211
i
=
1
N
P
\ue89e
\ue89e
\u03b4
\ue8a0
(
c
i
–
c
i
j
)
wherein NP is the number of particles, \u03b4 is the Dirac delta function, and cij is the jth particle after the resampling step at the ith cycle.
14. The method of claim 11, further comprising the step of predicting a normalized capacity forwarded by a cycle number using the formula:
p
\ue8a0
(
c
i
+
l
|
y
1
\ue89e
:
\ue89e
i
)
\u2248
1
N
P
\ue89e
\u2211
i
=
1
N
P
\ue89e
\ue89e
\u03b4
\ue8a0
(
c
i
+
l
–
c
i
+
l
j
)
wherein ci=1\u2212\u03b1ij1\u2212exp(\u2212\u03bbij(i+l))\u2212\u03b2ij(i+l)
wherein NP is the number of particles, \u03b4 is the Dirac delta function, cij is the jth particle after the resampling step at the ith cycle, \u03b1ij is the coefficient of the exponential component of capacity fade, \u03bbij is the exponential capacity fade rate, and \u03b2ij is the coefficient of the linear component of capacity fade.
15. The method of claim 11, wherein the step of determining the RUL for the particle as the number of cycles between a current cycle and an end of service cycle (EOS) uses formula:
Lij=root\u03b1ij1\u2212exp(\u2212\u03bbiji)+\u03b2iji=x\u2212i
wherein \u03b1ij is the coefficient of the exponential component of capacity fade, \u03bbij is the exponential capacity fade rate, \u03b2ij is the coefficient of the linear component of capacity fade and x=1\u2212pre-defined EOS threshold (%).
16. The method of claim 11, wherein the RUL distribution is determined using formula:
p
\ue8a0
(
L
i
|
y
1
\ue89e
:
\ue89e
i
)
\u2248
1
N
P
\ue89e
\u2211
i
=
1
N
P
\ue89e
\ue89e
\u03b4
\ue8a0
(
L
i
–
L
i
j
)
;
wherein NP is the number of particles, and \u03b4 is the Dirac delta function.
17. The method of claim 15, wherein the pre-defined EOS threshold is between 20%-90% of the normalized capacity.
18. The method of claim 15, wherein the pre-defined EOS threshold is between 30%-80% of the normalized capacity.
19. The method of claim 15, wherein the pre-defined EOS threshold is between 40%-70% of the normalized capacity.
20. The method of claim 15, wherein the pre-determined EOS threshold is between 50%-60% of the normalized capacity.
21. A system, comprising: an implantable medical device having a rechargeable battery said rechargeable battery having a voltage, a total capacity which changes over time and a charge level; a processor configured to predict the RUL of the rechargeable battery by performing the steps comprising of:
(a) determining a capacity of a battery based on at least changes between a first state of charge (SOC) value determined at a first time (SOC1) and a second SOC value determined at a second time (SOC2) and a net charge flow of the battery;
(b) applying a particle filter to a capacity degradation model using the determined capacity to form an adjusted capacity degradation model for the battery; and
(c) predicting the RUL of the battery using the adjusted capacity degradation model with a pre-defined EOS threshold, electronic componentry, operatively coupled to said implantable medical device, configured to measure electrical signals of the battery used to determine the SOC1 and SOC2 values and net charge flow and transmit the electrical signals or SOC1 SOC2 values and the net charge flow values to the processor; and a user output, operatively coupled to said electrical componentry or processor, configured to communicate said RUL to a user.
22. The system of claim 21, wherein the battery is selected from a group consisting of nickel-metal hydride battery, nickel-cadmium battery, lithium-ion polymer battery, lithium sulfur battery, thin film battery, smart battery, carbon foam-based lead acid battery, potassium-ion battery, and sodium-ion battery.
23. The system of claim 21, wherein electronic componentry is configured to make a first open circuit voltage measurement (V1) before a partial charge or discharge period and to make a second open circuit voltage measurement after the partial charge or discharge period (V2) and to communicate V1 and V2 to the processor.
24. The system of claim 21, wherein the electronic componentry is configured to make a first open circuit voltage measurement (V1) before a partial charge or discharge period and to determine the SOC1 value as a function of V1 and to make a second open circuit voltage measurement after the partial charge or discharge period (V2) and to determine the SOC2 value as a function of V2 and to communicate SOC1 and SOC2 to the processor.
25. The system of claim 23, wherein the electronic componentry is further configured to measure the current of the battery charge and communicate the measured current value to the processor.
26. The system of claim 25, wherein the processor is configured to determine the net charge flow (\u0394Q) by integrating the current over the charge or discharge period.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A color coded instrument comprising:
a metal handle comprising one end and another end;
a colored resin cone connected to at least one end of the handle; and
a working tip extending from the colored resin cone; wherein the colored resin cone provides a means to visually identify the instrument and will not harbor pathogens.
2. The color coded instrument of claim 1, wherein said instrument is heat treated by induction heating.
3. The color coded instrument of claim 1, wherein said colored resin cone is adhered to said metal handle.
4. The color coded instrument of claim 1, wherein said colored resin cone is adhered to said metal handle with an adhesive.
5. The color coded instrument of claim 1, wherein said colored resin cone is adhered to said metal handle by induction heating.
6. The color coded instrument of claim 1, wherein said working tip is adhered to said colored resin cone.
7. The color coded instrument of claim 1, further comprising a non-slip surface on said metal handle where said metal handle is connected to said resin cone and wherein said instrument is heat treated by induction heating.
8. The color coded instrument of claim 6, wherein said working tip has a shank end that extends from said resin cone and further comprises a non-slip surface on said shank end, and wherein said instrument is heat treated by induction heating.
9. The color coded instrument of claim 1, wherein said metal handle is selected from a group consisting of, stainless steel, chromed brass and aluminum.
10. The color coded instrument of claim 1, wherein said colored resin cone is connected to said metal handle when at least one bore in at least one end of said handle receives a shaft of said resin cone.
11. The color coded instrument of claim 1, wherein said colored resin cone is connected to said metal handle when at least one pin on at least one end of said handle is received by a bore in said resin cone.
12. The colored coded instrument of claim 11, wherein said pin is a threaded stem.
13. The color coded instrument of claim 11, wherein said pin extends to a tip of said cone and said working tip is connected to said pin.
14. A color coded instrument comprising:
a metal handle comprising one end and another end and comprising at least one bore in at least one end;
a colored resin cone comprising a shaft and a tip, connected to at least one end of the handle when the shaft of the cone is received by the bore of the metal handle; and
a working tip connected to and extending from the colored resin cone; wherein the colored resin cone provides a means to visually identify the instrument and will not harbor pathogens.
15. The color coded instrument of claim 14, wherein said instrument is heat treated by induction heating.
16. The color coded instrument of claim 14, wherein said working tip has a shank end that extends from said resin cone and further comprises a non-slip surface on said shank end, and wherein said instrument is heat treated by induction heating.
17. A color coded instrument comprising:
a metal handle comprising one end and another end and comprising at least one pin on at least one end;
a colored resin cone comprising a bore, connected to at least one end of the handle when the pin of the handle is received by the bore of the cone; and
a working tip extending from the colored resin cone; wherein the colored resin cone provides a means to visually identify the instrument and will not harbor pathogens.
18. The color coded instrument of claim 16, wherein said instrument is heat treated by induction heating.
19. The color coded instrument of claim 16, wherein said pin is a threaded stem.
20. The color coded instrument of claim 14, further comprising a non-slip surface on said metal handle where said metal handle is connected to said resin cone, and wherein said instrument is heat treated by induction heating.