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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/09/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
1. Claims 12 and 15 are objected to because of the following informalities:
“wherein determine” is grammatically incorrect.
Appropriate correction is required.
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 12-14 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 12 recites “penalizing a first derivative of a variable of the objective function wherein the variable comprises a discharge of the electric vehicle battery based on a heuristic term”. The derivative of a variable, as opposed to a function, is zero. Penalizing a derivative of a variable, which is zero, is not a mathematical operation that is understood by one of ordinary skill in the art. Basing this on a heuristic term, similarly, is not a mathematical operation that is understood by one of ordinary skill in the art. Given the verbiage of the algorithm that is described here, one of ordinary skill in the art would not be able to understand the nature of the algorithm, and at its base level, zeroing a variable invariant of whatever a heuristic term might mean will still return zero. The claim and the dependent claims are considered indefinite as a result.
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.
3. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites determining a dispatch schedule for an electric vehicle battery, and controlling a charge or discharge of the battery based on the determined schedule. The limitation of determining a dispatch schedule, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “one or more processors coupled to a storage media” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “one or more processors coupled to a storage media” language, “determining” in the context of this claim encompasses the user manually calculating the dispatch schedule for the electric vehicle battery. Similarly, the limitation of controlling a charge or discharge of the electric battery, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, but for the “one or more processors coupled to a storage media” language, “controlling” in the context of this claim encompasses the user using or not using the battery.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a processor to perform both the determining and the controlling steps. The processor in both steps is recited at a high-level of generality (i.e., as a generic processor and memory performing a generic computer function of determining a schedule) such that it amounts no more than mere instructions to apply the exception using a generic computer component. An “optimization algorithm” is further expressed in the claims, but this limitation on its own without further context is any process of determination, which also is a process that can be done in the human mind. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform both the determining and controlling steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
4. Claims 1-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sinha (2019/0217739).
As to claim 1: Sinha teaches an electronic device for determining a dispatch schedule for an electric vehicle battery in communication with the electronic device, the electronic device comprising:
one or more non-transitory computer-readable storage media including instructions (figure 6A, 610, paragraphs 0120-0121); and
one or more processors coupled to the storage media, the one or more processors configured to execute the instructions to (paragraph 0117, figure 6A, processor 608):
determine, using an optimization algorithm, the dispatch schedule for the electric vehicle battery (figure 12, step 1204); and
control a charge or discharge of the electric vehicle battery based on the dispatch schedule (figure 12, step 1206).
As to claim 2: Sinha teaches that the one or more processors are further configured to execute instructions to:
determine a future state of charge of the electric vehicle battery in communication with the electronic device using a piecewise linear approximation (paragraphs 0231-0233);
determine a discharge efficiency number based on the future state of charge; and determine anticipated energy needs of a building (paragraph 0261),
wherein the optimization algorithm uses the discharge efficiency number and the anticipated energy needs of the building to determine the dispatch schedule (paragraphs 0261-0262).
As to claim 3: Sinha teaches that the one or more processors are further configured to execute the instructions to:
determine, using the optimization algorithm, an amount of power to charge or discharge the electric vehicle battery based on the anticipated energy needs of the building and the state of charge of the electric vehicle battery, wherein the dispatch schedule of the electric vehicle battery is further based on the amount of power to charge or discharge (paragraphs 0257, 0261).
As to claim 4: Sinha teaches that the piecewise linear approximation determines
the discharge efficiency number based on at least one or more parameters relating to efficiency losses, the at least one or more parameters comprising an amount of power that is being discharged by the electric vehicle battery, a state of charge of the electric vehicle battery, or an internal temperature of the electric vehicle battery (paragraph 0227).
As to claim 5: Sinha teaches determining the discharge efficiency number
based on at least one or more parameters comprises applying one or more weights to the one or more parameters to assign different values to each of the one or more parameters (paragraph 0257).
As to claim 6: Sinha teaches that the piecewise linear approximation has a threshold number of inflection points (as seen in figure 8).
As to claim 7: Sinha teaches that controlling the charge of the electric vehicle battery comprises one or more of starting the charge of the electric vehicle battery and stopping the charge of the electric vehicle battery (paragraph 0270); and
controlling the discharge of the electric vehicle battery comprises one or more of starting the discharge of the electric vehicle battery and stopping the discharge of the electric vehicle battery (paragraph 0270).
As to claim 8: Sinha teaches that the discharge efficiency number is further based on the discharge of the electric vehicle battery (paragraph 0261).
As to claim 9: Sinha teaches that the one or more processors are further configured to execute instructions to:
determine, using the optimization algorithm, an amount of power to discharge based on the discharge efficiency number and the anticipated energy needs of the building, wherein the dispatch schedule is further based on the amount of power to discharge (paragraph 0261).
As to claim 10: Sinha teaches that controlling the charge of the electric vehicle battery comprises one or more of setting a start time to charge the electric vehicle battery and setting a stop time to charge the electric vehicle battery (paragraph 0270); and
controlling the discharge of the electric vehicle battery comprises one or more of setting a start time to discharge the electric vehicle battery and setting a stop time to discharge the electric vehicle battery (paragraph 0270).
As to claim 11: Sinha teaches that the optimization algorithm comprises an objective function to reduce oscillations in the discharge profile (paragraphs 0055, 0090).
As to claim 12: Sinha teaches determining, using an optimization algorithm,
the dispatch schedule for the electric vehicle battery comprises penalizing a first derivative of a variable of the objective function wherein the variable comprises a discharge of the electric vehicle battery based on a heuristic term (figure 8).
As to claim 13: Sinha teaches that the one or more processors are further
configured to execute the instructions to:
receive an input from a user of the electric vehicle indicative of charge preferences or discharge preferences; and
adjusting the heuristic term based on the received input (paragraph 0020).
As to claim 14: Sinha teaches that the heuristic term smooths a curve of a charge profile or a discharge profile associated with the dispatch schedule to reduce the oscillations (paragraphs 0020, 0055, 0090).
As to claim 15: Sinha teaches that determining, using the optimization algorithm comprises:
determining a simulation of discharging power flowing of the electric vehicle battery over a predetermined period of time; and
setting a marginal cost associated with a maximum annual discharge of the electric vehicle battery (value function, described in paragraphs 0090-0095, figure 5).
As to claim 16: Sinha teaches that the optimization algorithm determines to
discharge the electric vehicle battery only if an economic gain from the simulation of discharging power is greater than the marginal cost (paragraph 0143, wherein the on/off states are determined based on the optimization process, which is based on costs).
As to claim 17: Sinha teaches that determining, using the optimization algorithm, comprises:
determining parameters relating to efficiency losses using a data set derived from
controlled tests that measure battery efficiency at different battery state values over a limited number of charge-discharge cycles;
determining uncertainties in relevant battery states over an optimization period (paragraphs 0126-0128, predictor for utility prices, which are unknown);
generating a plurality of scenarios that represent a set of possible battery-state uncertainties over the optimization period (paragraph 0200, average); and
formulating a multi-period stochastic optimization using one or more of the plurality of scenarios and the determined parameters (paragraph 0126).
As to claim 18: Sinha teaches that the one or more processors are further configured to execute instructions to:
generate a plurality of forecasts for future anticipated energy needs of a building; and
generate a plurality of forecasts for future anticipated energy production of the building,
and wherein the optimization algorithm determines the dispatch schedule by solving for a dispatch plan that maximizes the expected value of the dispatch plan given the plurality of forecasts for future anticipated energy needs of a building and the plurality of forecasts for future anticipated energy production of the building (paragraph 0162, paragraphs 0124-0126, equation for predicting the load of the building, and solving for the most efficient outcome).
As to claim 19: Sinha teaches that each of the future anticipated energy needs of
a building is associated with a respective probability of the future anticipated energy need occurring (paragraph 0116, event probabilities).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID P TARDIF whose telephone number is (571)270-7810. The examiner can normally be reached on M-F 11AM-7:30PM. If the examiner cannot be reached by telephone, he can be reached through the following email address: david.tardif@uspto.gov
If attempts to reach the examiner by telephone and email are unsuccessful, the examiner’s supervisor, Thomas Pham can be reached on (571)272-3689. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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DAVID TARDIF
Examiner
Art Unit 2876
/DAVID TARDIF/
Examiner, Art Unit 2876
david.tardif@uspto.gov
/THOMAS K PHAM/Supervisory Patent Examiner, Art Unit 2876
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