DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites, in the second element “determining, based on, salt precipitation.” It is unclear what effect the words “based on” have to the scope of the claim and this leaves the scope of the claim unclear. The Examiner believes that Claim 1 was meant to mimic Claim 9 and that “based on” was meant to read “based on the at least one parameter” and is examining Claim 1 under that understanding.
Claims 2-8 are rejected based on their dependence from Claim 1.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claims are directed to a computer program per se [see MPEP 2106 – “Non-limiting examples of claims that are not directed to one of the statutory categories: … iv. a computer program per se, Gottschalk v. Benson, 409 U.S. at 72, 175 USPQ at 676-77”].
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) the abstract idea of a mathematical algorithm for modelling a lithium ion battery and estimating salt precipitation.
This judicial exception is not integrated into a practical application because no improvement to the underlying lithium ion battery is realized through performance of the algorithm.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recitation of the memory, processor, and computer program amounts to the recitation of a general-purpose computer for implementing the algorithm and does not serve to amount to the recitation of significantly more than the abstract idea itself (see Alice Corp. v. CLS Bank International, 573 U.S. 208 (2014)).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Horstmann et al., Precipitation in aqueous lithium–oxygen batteries: a model-based analysis, Energy Environ. Sci., 2013 [hereinafter “Horstmann”] and Lee (US 20160023567 A1).
Regarding Claims 1 and 9, Horstmann discloses a method of diagnosing battery abnormalities [Abstract – “In this paper we present a model of the discharge of a lithium–oxygen battery with aqueous electrolyte. … We demonstrate that GDEs remove power limitations due to slow oxygen transport in solutions and that lithium hydroxide tends to precipitate on the anode side. We discuss the system architecture to engineer where nucleation and growth predominantly occurs and to optimize for discharge capacity.”] comprising:
acquiring at least one parameter of a battery [See Fig. 7 and Section 4.1 Inhomogeneous precipitation (discharge current, discharge capacity, and cell voltage) – “First, we study the galvanostatic discharge of a Li–O2 battery with a GDE and a porous separator at moderately high currents i = 10 A m-2 (see Fig. 7). … The Li–O2 battery discharges in two stages (see Fig. 7). Initially, up to point B, the salt concentration rises from its initial value to the solubility limit, the voltage decreases slowly, and LiOH-H2O does not form. After point B, the salt concentration remains constant, slightly above its solubility limit, the voltage is constant, and the LiOH-H2O volume fraction increases linearly in time. Eventually, at point D, an abrupt drop in cell voltage represents the end of discharge.”]; and
determining, based on the at least one parameter, salt precipitation of the battery [Page 1302, first column – “lithium hydroxide salt”Section 4.1 Inhomogeneous precipitation – “Fig. 8 shows spatial profiles of dissolved salt concentration, precipitate volume fraction, and the surface area of precipitation during discharge. … At point D, just before end of discharge, the reason for capacity limitation becomes obvious: A film of LiOH-H2O forms at the separator/anode interface, completely blocking the lithium ion transport. The battery tries to overcome the transport limitations and further increases the salt concentration near the anode. This results in resumed nucleation (see also Fig. 11) and accelerated end of discharge.”] by using an electrochemical model [Figs. 1, 7, 8, and 11]
Horstmann fails to disclose that the electrochemical model is calculated based on a single particle model of a cathode and an anode of the battery, the electrochemical model comprising a model configured to calculate internal lithium ion concentrations of the cathode and the anode by considering a difference in diffusion of lithium ions between the cathode and the anode of the battery and to estimate an internal state of the battery by using a difference between the internal lithium ion concentrations of the cathode and the anode.
However, Lee discloses an electrochemical model [See Fig. 4 and Paragraph [0038] – “The full-order electrochemical model of a Metal-ion battery 400 is the basis of a reduced-order electrochemical model. The full-order electrochemical model resolves Metal-ion concentration through the electrode thickness (406 & 410) and assumes the Metal-ion concentration is homogeneous throughout the other coordinates. This model accurately captures the key electrochemical dynamics.”Paragraph [0037] – “The anode 406 and cathode 410 may be modeled as a spherical material (i.e. spherical electrode material model) as illustrated by the anode spherical material 430 and the cathode spherical material 432.”] calculated based on a single particle model of a cathode [Paragraph [0011] – “FIG. 4B is an illustration of Li-ion concentration profiles inside representative particles in the positive electrode resulting from the Li-ion diffusion process during discharging.”] and an anode of the battery [Paragraph [0010] – “FIG. 4A is an illustration of Li-ion concentration profiles inside representative particles in the negative electrode resulting from the Li-ion diffusion process during discharging.”], the electrochemical model comprising a model configured to calculate internal lithium ion concentrations of the cathode and the anode by considering a difference in diffusion of lithium ions between the cathode and the anode of the battery and to estimate an internal state of the battery by using a difference between the internal lithium ion concentrations of the cathode and the anode [Paragraph [0037] – “The anode spherical material 430 has a metal-ion concentration 434 which is shown in relation to the radius of the sphere 436. The concentration of the Metal-ion 438 changes as a function of the radius 436 with a metal-ion concentration at the surface to electrolyte interface of 440. Similarly, the cathode spherical material 432 has a metal-ion concentration 442 which is shown in relation to the radius of the sphere 444. The concentration of the Metal-ion 446 changes as a function of the radius 444 with a metal-ion concentration at the surface to electrolyte interface of 448.”Paragraph [0038] – “The model describes the electric potential changes and the ionic mass transfer in the electrode and the electrolyte by four partial differential equations non-linearly coupled through the Butler-Volmer current density equation.”See Paragraphs [0039]-[0043].].
It would have been obvious to use such a modelling technique in order to better characterize the battery (See the battery model of Fig. 1 of Horstmann).
Regarding Claim 9, Horstmann fails to disclose an apparatus comprising the recited memory and processor. However, Lee discloses the use of a computer [Paragraph [0093]]. It would have been obvious to use a computer to implement the method because computers are effective and reliable for performing data analysis.
Regarding Claims 2 and 10, Horstmann discloses that the diagnosing the salt precipitation of the battery comprises: estimating a potential of an electrolyte between the anode and a separator of the battery; estimating a potential of the anode of the battery; and calculating a value of an overpotential between the anode and the separator of the battery by using the potential of the electrolyte and the potential of the anode [Page 1301, first column – “
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is the potential step between the lithium anode and the electrolyte”], but fails to disclose diagnosing the salt precipitation of the battery based on the value of the overpotential.
However, Horstmann teaches that salt precipitation occurs under such a scenario [See Equation 4 and Fig. 7.Page 1302, first column – “lithium hydroxide salt”Section 4.1 Inhomogeneous precipitation – “Fig. 8 shows spatial profiles of dissolved salt concentration, precipitate volume fraction, and the surface area of precipitation during discharge. … At point D, just before end of discharge, the reason for capacity limitation becomes obvious: A film of LiOH-H2O forms at the separator/anode interface, completely blocking the lithium ion transport. The battery tries to overcome the transport limitations and further increases the salt concentration near the anode. This results in resumed nucleation (see also Fig. 11) and accelerated end of discharge.”].
It would have been obvious to diagnose that salt precipitation is occurring under such a scenario in order to better assess the state of health of the battery.
Regarding Claims 3 and 11, Horstmann discloses that the estimating the potential of the electrolyte between the anode and the separator of the battery comprises estimating the potential of the electrolyte [See Fig. 1 and Page 1301, first column – “
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is the potential step between the lithium anode and the electrolyte”], but fails to disclose doing so based on the electrochemical model by using the difference between the internal lithium ion concentrations occurring due to a diffusion difference between the cathode and the anode of the battery.
However, Lee discloses determining electrolyte potential in such a manner [See Fig. 6 and Paragraph [0046] – “FIG. 6 is a graphical representation of the change in electrolyte electrical potential (electrical potential) with respect to distance on an axis, in this example, the radius of the spherical battery model. The electrolyte electrical potential difference of the electrolyte between the current collectors 600, expressed as φ.sub.e|.sub.x=L−φ.sub.e|.sub.x=0,”Paragraph [0035] – “There are multiple ranges of time scales existent in electrochemical dynamic responses of a Metal-ion battery 400. For example with a Li-ion battery, factors which impact the dynamics include but are not limited to the electrochemical reaction in active solid particles 412 in the electrodes and the mass transport of Lithium-ion across the electrodes 416.”]. It would have been obvious to use such a modelling technique in order to better characterize the battery.
Regarding Claims 4 and 12, Lee discloses that the electrochemical model comprises a model configured to calculate the internal lithium ion concentrations of the cathode and the anode of the battery [See Figs. 4A, 4B, and 4C and Paragraphs [0035]-[0036]] by discretizing the single particle model of the cathode and the anode of the battery into a sphere having a plurality of layers [Paragraph [0037] – “The anode 406 and cathode 410 may be modeled as a spherical material (i.e. spherical electrode material model) as illustrated by the anode spherical material 430 and the cathode spherical material 432.”Fig. 9 and corresponding text], and by using a diffusion coefficient according to concentration distributions of the cathode and the anode of the battery, the diffusion coefficient being determined according to a concentration and a temperature [Paragraph [0057] – “Equation (18) may be expressed as three model parameters, the anode effective diffusion coefficients (D.sub.s,n.sup.eff), the cathode effective diffusion coefficients (D.sub.s,p.sup.eff), effective internal resistance of both the anode and cathode (R.sub.0.sup.eff), and one state vector, the effective Metal-ion concentration (c.sub.s.sup.eff). The state vector effective Metal-ion concentration (c.sub.s.sup.eff) includes the anode state vector effective Metal-ion concentration (c.sub.s.sup.eff), which may be governed by the anode effective diffusion coefficients (D.sub.s.sup.eff), and cathode state vector effective Metal-ion concentration (c.sub.s,p.sup.eff), which may be governed by the cathode effective diffusion coefficients (D.sub.s,p.sup.eff) based on the application of equation (14). The parameters may be expressed as functions of, but not limited to, temperature[.]”] of each layer of the plurality of layers of the single particle model [See Fig. 9 and Paragraph [0066] – “The derived state-space equations using uneven discretization are (Equations 22, 22a, and 22b)”].
Regarding Claims 5 and 13, Lee discloses that the electrochemical model comprises a model configured to estimate a voltage of the battery [Paragraph [0049] – “From eqns. (7) and (8), the terminal voltage may be expressed by equation (9)”] based on a value of an overpotential [Paragraph [0049] – “the over potential at each electrode may be expressed by equation (8)”] that is a difference between a measured voltage of the battery [See Equation 8 and Paragraph [0043] – “φ is the electric potential”] and an open-circuit voltage of the battery [See Equation 8 and Paragraph [0049] – “U.sub.i(θ.sub.i) is the open-circuit potential”].
Regarding Claims 6 and 14, Lee discloses that the electrochemical model comprises a model configured to calculate a value of a priori overpotential [Paragraph [0043] – “Butler-Volmer current density is expressed by equation (6), … in which … η=φ.sub.s−φ.sub.e−U(c.sub.se) is the over potential at the solid-electrolyte interface at an active solid particle[.]”Paragraph [0045] – “FIG. 5 is a graphical representation of the change in overpotential with respect to distance on an axis, in this example, the radius of the spherical battery model. Here, the overpotential difference between the current collectors 500 is expressed as
j.sub.0=k(C.sub.e).sup.α.sup.a(C.sub.s,max−C.sub.se).sup.α.sup.a(C.sub.se).sup.α.sup.c.
The x axis represents the electrode thickness 502, and the y axis represents the overpotential 504. At the positive current collector when a 10 sec current pulse is applied, the instantaneous voltage drop is observed. At zero second 506, the voltage is influenced by the Ohmic term 508. As time increases, as shown at 5 seconds 510, the voltage is additional influenced by the polarization term 512 wherein the voltage is influenced by both the Ohmic and the polarization term, until the voltage influence reaches steady state as shown at time 100 seconds 514.”] by using information regarding a lithium ion concentration of an outermost layer from among the plurality of layers of the single particle model [Figs. 9 and 10, “Li-ion Concentration”], information regarding an average lithium ion concentration of the cathode and the anode of the battery [Fig. 10, Li-ion Concentration interpolation being an “average”], and voltage drop information of the battery [Paragraph [0045] – “instantaneous voltage drop”], and to calculate the value of the overpotential by using the value of the priori overpotential and a predetermined overpotential proportional coefficient [Paragraph [0045] – “At zero second 506, the voltage is influenced by the Ohmic term 508. As time increases, as shown at 5 seconds 510, the voltage is additional influenced by the polarization term 512 wherein the voltage is influenced by both the Ohmic and the polarization term, until the voltage influence reaches steady state as shown at time 100 seconds 514.”].
Regarding Claims 7 and 15, Lee discloses that the predetermined overpotential proportional coefficient comprises an experimental value [Paragraph [0045] – “At zero second 506, the voltage is influenced by the Ohmic term 508. As time increases, as shown at 5 seconds 510, the voltage is additional influenced by the polarization term 512 wherein the voltage is influenced by both the Ohmic and the polarization term, until the voltage influence reaches steady state as shown at time 100 seconds 514.”] for simulating, with a Butler-Volmer equation [Paragraph [0043] – “Butler-Volmer current density is expressed by equation (6)”], a relationship between the value of the priori overpotential and the value of the overpotential by using curve fitting [Fig. 5].
Regarding Claim 8, Horstmann fails to disclose a computer program stored in a recording medium to execute the method of claim 1 by using a computing apparatus. However, Lee discloses the use of such a computer program [Paragraph [0093]]. It would have been obvious to use a computer program to implement the method because computers are effective and reliable for performing data analysis.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Bazak et al., Multi-Temperature in Situ Magnetic Resonance Imaging of Polarization and Salt Precipitation in Lithium-Ion Battery Electrolytes, J. Phys. Chem. C, 2017
Kirk et al., MODELLING ELECTRODE HETEROGENEITY IN LITHIUM-ION BATTERIES: UNIMODAL AND BIMODAL PARTICLE-SIZE DISTRIBUTIONS, arXiv, 2020
Wang et al., PARAMETERISING CONTINUUM LEVEL LI-ION BATTERY MODELS & THE LiionDB DATABASE, arXiv, 2021
US 20180198300 A1 – METHOD AND APPARATUS ESTIMATING AND CONTROLLING BATTERY STATE
US 20220163589 A1 – Battery Monitoring System
US 20210013731 A1 – Charging Apparatus And Method Of Secondary Battery
US 20220013813 A1 – APPARATUS FOR MINING BATTERY CHARACTERISTIC DATA HAVING SENSITIVITY TO VOLUME FRACTION OF ACTIVE MATERIAL OF BATTERY ELECTRODE AND METHOD THEREOF
US 20240176929 A1 – ESTIMATION DEVICE, ESTIMATION METHOD, AND COMPUTER PROGRAM
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE ROBERT QUIGLEY whose telephone number is (313)446-4879. The examiner can normally be reached 9AM-5PM EST.
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/KYLE R QUIGLEY/Primary Examiner, Art Unit 2857