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 .
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.
Status of Claims
The following is a non-final, first office action in response to the communication filed on 12/21/2025 (preliminary amendment).
Claims 62-81 are currently pending.
Claims 62-81 have been examined.
Information Disclosure Statement
The Information Disclosure Statement received on 12/21/2023 has been reviewed and considered.
Claim Objections
Claim 67 is objected to because of the following informalities: the claim currently recites “. . . the vehicle travelling in an inclined surface . . .” which the examiner notes appears to contain a minor typographical error and recommends updating to “. . . the vehicle travelling on an inclined surface . . .” for clarity. 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.
Claim 67 is 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. The claim current reads “. . . determines . . . a surface inclination as the one or more charge consumption factors that lead to the one or more events,” which is confusing to the examiner because claim 66, from which claim 67 depends, recites “. . . wherein the one or more events comprises the vehicle travelling [on] an inclined surface for a predefined distance,” which appears to create circular logic regarding the cause-effect nature being claimed. If the event is travelling at an incline as required by claim 67, then the cause of the event being travelling at an incline as required by claim 66 does not distinctly point out what cause-effect relationship is being claimed. For the sake of compact prosecution, the examiner is interpreting the limitations of claim 67 to mean “. . . determines . . . a surface inclination as a charge consumption factor . . .”
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.
Claims 61-64, 72-76, and 79-81 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite the judicial exception of a mental process. This judicial exception is not integrated into a practical application, nor do the claims include additional elements that are sufficient to amount to significantly more than the judicial exception.
Step 1: Yes, the claims are drawn to one or more statutory categories.
Step 1 of the Subject Matter Eligibility Test entails considering whether the claimed subject
matter falls within the four statutory categories of patentable subject matter identified by 35
U.S.C. 101: Process, machine, manufacture, or composition of matter.
Claims 74-76 are directed toward a method (i.e., process) with at least one step, claims 61-64 and 72-73 are directed toward a system (i.e., a machine), and claims 79-81 are directed toward a non-transitory computer readable storage medium (i.e., a manufacture).
Step 2A Prong 1: Yes, the claims recite an abstract idea.
If the claim recites a statutory category of invention, the claim requires further analysis
in Step 2A. Step 2A of the Subject Matter Eligibility Test is a two-prong inquiry. In Prong One,
examiners evaluate whether the claim recites a judicial exception.
Claim 74 recites abstract limitations, including those in bold below.
A method comprising:
determining a first state-of-charge of one or more batteries associated with a vehicle;
determining whether the first state-of-charge is below a threshold charge level;
determining one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge;
determining one or more charge consumption factors that influences charge consumption in the one or more batteries;
estimating the charge consumption based on the one or more charge consumption factors;
determining a second state-of-charge based on the charge consumption;
determining one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge; and
reserving one or more charging sessions with the one or more second charging stations for charging the one or more batteries.
These limitations, as drafted, are simple processes that, under their broadest reasonable interpretation, cover performance in the mind. For example, the claim encompasses making a simple mental determination on the state-of-charge of a vehicle battery, comparing that determination against a threshold charge level, making a simple mental judgement on what charging stations are in a geographical range given the state-of-charge, considering pertinent charge consumption factors, making an estimate of charge consumption based on those factors, making a simple mental determination on a second state of charge based on the estimate, making a simple mental judgement on what charging stations are in a geographical range given the second state-of-charge, and then mentally picking or otherwise reserving the best charging station out of those in range given the second state-of-charge. In another example, the claim encompasses determining a current state of charge of a vehicle battery, such as by reading sensor data from a display, comparing that to a threshold charge level, such as 50% of maximum charge, mentally determining what charging stations are in range the current charge based on that charging level, such as determining that at more than 50% charge, the vehicle is in range of a charging station 50 miles away, considering charge consumption factors, such as route length or outside temperature, using those charge consumption factors to determine an estimated future charge level, such as driving 25 miles equating to approximately 30% charge consumption, making a second determination on charging stations in range based on the estimated future charge level, such as a charging station located only 20 miles away, and then reserving that charging station by mentally picking that as a next stop or reserving the location using pen and paper, such as marking when a shared home charger will be use on a sheet located at the charger. The claim does not recite anything that precludes it from the mental process grouping.
Step 2A Prong 2: No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
If the claim recites a judicial exception in step 2A Prong One, the claim requires further
analysis in step 2A Prong Two. In step 2A Prong Two, examiners evaluate whether the claim
recites additional elements that integrate the exception into a practical application of that
exception.
Claim 74 does not recite additional element limitations.
Subsequently, there are no additional elements that integrate the judicial exception into a practical application (see MPEP 2106.04(II)(A)(2); MPEP 2106.05(g)).
Step 2B: No, the additional elements of this/these claim(s) do/does not amount to significantly more than the judicial exception.
If the additional elements do not integrate the exception into a practical application in
step 2A Prong Two, then the claim is directed to the recited judicial exception, and requires
further analysis under Step 2B to determine whether they provide an inventive concept (i.e.,
whether the additional elements amount to significantly more than the exception itself).
Claim 74 does not recite additional element limitations.
Thus, even when viewed as an ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The limitations of claim 75 merely serve to add additional abstract limitations and mere instructions to apply the exception. For the reasons described above with respect to claim 74, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract ideas.
The limitations of claims 76 merely serve to add additional abstract limitations. For the reasons described above with respect to claim 75, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract ideas.
The limitations of claim 62 are analogous to the limitations of claim 74 and thus the analysis of claim 74 is applied to claim 62. Claim 62 additionally recites a system including a sensor module, a control module with a processor and a memory communicatively coupled to the processor comprising a sensor control module that merely serves as a generic means to apply the otherwise abstract ideas.
The limitations of claim 63 are analogous to the limitations of claim 75 and thus the analysis of claim 75 is applied to claim 63. Claim 63 additionally recites a processor that merely serves as generic means to apply the otherwise abstract ideas.
The additional limitations of claim 64 are analogous to the limitations of claim 76 and thus the analysis of claim 76 is applied to claim 64. Claim 64 additionally recites a processor that merely serves as generic means to apply the otherwise abstract ideas.
The limitations of claim 72 merely serve to further characterize the sensor module using generic components, thus further characterizing generic means to apply the otherwise abstract ideas. For the reasons described above with respect to claim 63, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract ideas.
The limitations of claim 73 merely add insignificant extra-solution activity (changing a vehicle mode). For the reasons described above with respect to claim 63, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract ideas.
The limitations of claim 79 are analogous to the limitations of claim 74 and thus the analysis of claim 74 is applied to claim 79. Claim 79 additionally recites a non-transitory computer readable storage medium that merely serves as a generic means to apply the otherwise abstract ideas.
The limitations of claim 80 are analogous to the limitations of claim 75 and thus the analysis of claim 75 is applied to claim 80. Claim 80 additionally recites a non-transitory computer readable storage medium that merely serves as a generic means to apply the otherwise abstract ideas.
The limitations of claim 81 merely serve to add additional mental process steps, add insignificant extra-solution activity (compiling messages), and serve as a generic means to apply the otherwise abstract ideas (artificial intelligence engine). For the reasons described above with respect to claim 79, this judicial exception is not meaningfully integrated into a practical application or significantly more than the abstract ideas.
The examiner notes that claims 65-71 and 77-78 overcome the 35 U.S.C. 101 deficiencies present in claims 61-64, 72-76, and 79-81 because the claims require using an artificial intelligence engine to determine charge consumption factors, which fundamentally operates using mechanisms that are distinct from classical human mind-based approaches like root cause analysis or comparison to known factors.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim 74 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tsai et al. (TW I520864 B; hereinafter Tsai).
Regarding claim 74, Tsai discloses the subject matter indicated in bold below:
A method comprising (see Tsai at least pg. 1, paragraph 2 “The present invention relates to a driving assistance method . . .”):
determining a first state-of-charge of one or more batteries associated with a vehicle (see Tsai at least pg. 3, paragraph 8“Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining whether the first state-of-charge is below a threshold charge level (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining one or more charge consumption factors that influences charge consumption in the one or more batteries (see Tsai at least pg. 6, paragraph 4 “. . . other power consumption factors can also be taken into consideration, such as weight power consumption coefficient kw, vehicle speed power consumption coefficient kv, and other power consumption coefficients, etc., in this case, ki can be any of these power consumption coefficients[], or a product of more than two (ie, the product of at least one of these coefficients multiplied).”);
estimating the charge consumption based on the one or more charge consumption factors (see Tsai at least pg. 6, paragraph 5 “. . . when considering a coefficient, ki=kb or kw or kv or other power consumption coefficient; when considering two coefficients, ki=kb×kw or kb×kv or kv×kw, or the product of any two coefficients; [] ki = kb × kw × kv or the product of any three coefficients; and so on, ki can also be multiplied by a variety of coefficients. Various types of power consumption coefficients can be obtained by referring to existing literature or experimental data, or can be obtained by experiment . . . According to the Chinese urban construction industry standards, the weight loss coefficient kw=1.0875 (current vehicle weight/empty vehicle weight-1).”);
determining a second state-of-charge based on the charge consumption (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected . . . considering different parameters, such as: remaining power, battery status, geographic information and road condition information, calculate the safe driving range BSR and the battery warning driving range BWR of the electric vehicle C.”);
determining one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge (see Tsai at least pg. 3, paragraph 7 “Based on the definition of the safe driving range BSR, at least one power replenishment location will be found here.”; pg. 5, paragraph 4 “. . . a judging step may be added to monitor whether the electric vehicle C enters the electric power warning driving range BWR at any time (or at regular intervals) (step S542). If it enters the battery warning driving range BWR, it will switch to the charging warning step S544. On the other hand, in step S530, the above-described electric safety driving range BSR and the electric quantity warning driving range BWR are continuously updated dynamically, that is, the above-mentioned electric safety driving range BSR and the electric quantity warning driving range BWR are calculated again at regular intervals.”); and
reserving one or more charging sessions with the one or more second charging stations for charging the one or more batteries (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected (that is, in the step S510 of selecting the power replenishment location, the power replenishing device that may provide the supplemental power is obtained.”).
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 62 and 79 are rejected under 35 U.S.C. 103 as being unpatentable over Tsai in view of Pedersen (US 11422000 B2; hereinafter Pedersen).
Regarding claim 62, Tsai discloses the subject matter indicated in bold below:
A system comprising (see Tsai at least PG. 7, paragraph 5 “The driving assistance system 600 for an electric vehicle . . .”):
a sensor module (see Tsai at least pg. 7, paragraph 7 “The driving information collecting unit 610 receives the driving information by at least one sensor installed in the electric vehicle C . . .”); and
a control module that comprises (see Tsai at least pg. 8, paragraph 7 “620 . . . Input unit . . . 622 . . . Mode selection unit . . . 630 . . . Range operation unit . . . 640 . . . Covered arithmetic unit . . . 650 . . . Display device”; pg. 9, paragraph 10 “17 is a diagram showing a driving assistance system for an electric vehicle according to a third embodiment of the present invention.”; Figure 17- driving assistance unit with control hardware units 620, 630, and 640 shown): . . .
determine a first state-of-charge of one or more batteries associated with a vehicle (see Tsai at least pg. 3, paragraph 8“Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determine whether the first state-of-charge is below a threshold charge level (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determine one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determine one or more charge consumption factors that influence charge consumption in the one or more batteries (see Tsai at least pg. 6, paragraph 4 “. . . other power consumption factors can also be taken into consideration, such as weight power consumption coefficient kw, vehicle speed power consumption coefficient kv, and other power consumption coefficients, etc., in this case, ki can be any of these power consumption coefficients[], or a product of more than two (ie, the product of at least one of these coefficients multiplied).”);
estimate the charge consumption based on the one or more charge consumption factors (see Tsai at least pg. 6, paragraph 5 “. . . when considering a coefficient, ki=kb or kw or kv or other power consumption coefficient; when considering two coefficients, ki=kb×kw or kb×kv or kv×kw, or the product of any two coefficients; [] ki = kb × kw × kv or the product of any three coefficients; and so on, ki can also be multiplied by a variety of coefficients. Various types of power consumption coefficients can be obtained by referring to existing literature or experimental data, or can be obtained by experiment . . . According to the Chinese urban construction industry standards, the weight loss coefficient kw=1.0875 (current vehicle weight/empty vehicle weight-1).”);
determine a second state-of-charge based on the charge consumption (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected . . . considering different parameters, such as: remaining power, battery status, geographic information and road condition information, calculate the safe driving range BSR and the battery warning driving range BWR of the electric vehicle C.”);
determine one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge (see Tsai at least pg. 3, paragraph 7 “Based on the definition of the safe driving range BSR, at least one power replenishment location will be found here.”; pg. 5, paragraph 4 “. . . a judging step may be added to monitor whether the electric vehicle C enters the electric power warning driving range BWR at any time (or at regular intervals) (step S542). If it enters the battery warning driving range BWR, it will switch to the charging warning step S544. On the other hand, in step S530, the above-described electric safety driving range BSR and the electric quantity warning driving range BWR are continuously updated dynamically, that is, the above-mentioned electric safety driving range BSR and the electric quantity warning driving range BWR are calculated again at regular intervals.”); and
reserve one or more charging sessions with the one or more second charging stations for charging the one or more batteries (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected (that is, in the step S510 of selecting the power replenishment location, the power replenishing device that may provide the supplemental power is obtained.”).
While Tsai discloses a system comprising a sensor module and a control module configured to determine a first state-of-charge of one or more batteries associated with a vehicle, determine whether the first state-of-charge is below a threshold charge level, determine one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge, determine one or more charge consumption factors that influence charge consumption in the one or more batteries, estimate the charge consumption based on the one or more charge consumption factors, determine a second state-of-charge based on the charge consumption, determine one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge, and reserve one or more charging sessions with the one or more second charging stations for charging the one or more batteries, it does not appear to explicitly disclose that the control module comprises a processor and a memory communicatively coupled to the processor, the memory comprising a sensor control module that when executed by the processor causes the processor to perform the described functions.
Pedersen teaches the subject matter underlined below:
. . . a processor (see Pedersen at least pg. 20, col. 10, lines 13-18 “The processor (401) may be of any suitable configuration known to those of skill in the art.”); and
a memory communicatively coupled to the processor, the memory comprising a sensor control module that when executed by the processor causes the processor to (see Pedersen at least pg. 22/23, col. 14/15, lines 61-67/1-6 “In addition, as shown in FIG. 4, the EV control unit (400) may further include associated memory (418) for storing software programs . . .”; Figure 4- processor 401 interacts with memory 418): . . .
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the control module that determines a first state-of-charge of one or more batteries associated with a vehicle, determines whether the first state-of-charge is below a threshold charge level, determines one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge, determines one or more charge consumption factors that influence charge consumption in the one or more batteries, estimates the charge consumption based on the one or more charge consumption factors, determines a second state-of-charge based on the charge consumption, determines one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge, and reserves one or more charging sessions with the one or more second charging stations for charging the one or more batteries of Tsai with the processor and memory implementation as taught by Pedersen to have a processor and a memory communicatively coupled to the processor, the memory comprising a sensor control module that when executed by the processor causes the processor to perform the functions as described. Doing so would provide a means for the control module to function.
Regarding claim 79, Tsai discloses the subject matter indicated in bold below:
. . . determining a first state-of-charge of one or more batteries associated with a vehicle (see Tsai at least pg. 3, paragraph 8“Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining whether the first state-of-charge is below a threshold charge level (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
determining one or more charge consumption factors that influence charge consumption in the one or more batteries (see Tsai at least pg. 6, paragraph 4 “. . . other power consumption factors can also be taken into consideration, such as weight power consumption coefficient kw, vehicle speed power consumption coefficient kv, and other power consumption coefficients, etc., in this case, ki can be any of these power consumption coefficients[], or a product of more than two (ie, the product of at least one of these coefficients multiplied).”);
estimating the charge consumption based on the one or more charge consumption factors (see Tsai at least pg. 6, paragraph 5 “. . . when considering a coefficient, ki=kb or kw or kv or other power consumption coefficient; when considering two coefficients, ki=kb×kw or kb×kv or kv×kw, or the product of any two coefficients; [] ki = kb × kw × kv or the product of any three coefficients; and so on, ki can also be multiplied by a variety of coefficients. Various types of power consumption coefficients can be obtained by referring to existing literature or experimental data, or can be obtained by experiment . . . According to the Chinese urban construction industry standards, the weight loss coefficient kw=1.0875 (current vehicle weight/empty vehicle weight-1).”);
determining a second state-of-charge based on the charge consumption (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected . . . considering different parameters, such as: remaining power, battery status, geographic information and road condition information, calculate the safe driving range BSR and the battery warning driving range BWR of the electric vehicle C.”);
determining one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge (see Tsai at least pg. 3, paragraph 7 “Based on the definition of the safe driving range BSR, at least one power replenishment location will be found here.”; pg. 5, paragraph 4 “. . . a judging step may be added to monitor whether the electric vehicle C enters the electric power warning driving range BWR at any time (or at regular intervals) (step S542). If it enters the battery warning driving range BWR, it will switch to the charging warning step S544. On the other hand, in step S530, the above-described electric safety driving range BSR and the electric quantity warning driving range BWR are continuously updated dynamically, that is, the above-mentioned electric safety driving range BSR and the electric quantity warning driving range BWR are calculated again at regular intervals.”); and
reserving one or more charging sessions with the one or more second charging stations for charging the one or more batteries (see Tsai at least pg. 5, paragraph 1 “. . . after the power replenishment location is selected (that is, in the step S510 of selecting the power replenishment location, the power replenishing device that may provide the supplemental power is obtained.”).
While Tsai discloses determining a first state-of-charge of one or more batteries associated with a vehicle, determining whether the first state-of-charge is below a threshold charge level, determining one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge, determining one or more charge consumption factors that influence charge consumption in the one or more batteries, estimating the charge consumption based on the one or more charge consumption factors, determining a second state-of-charge based on the charge consumption, determining one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge, and reserving one or more charging sessions with the one or more second charging stations for charging the one or more batteries, it does not appear to explicitly disclose a non-transitory computer readable storage medium, comprising a sequence of instructions, which when executed by a processor causes the described functions to be performed.
Pedersen teaches the subject matter underlined below:
A non-transitory computer readable storage medium, comprising a sequence of instructions, which when executed by a processor causes (see Pedersen at least pg. 20, col. 10, lines 13-18 “The processor (401) may be of any suitable configuration known to those of skill in the art.”; pg. 22/23, col. 14/15, lines 61-67/1-6 “In addition, as shown in FIG. 4, the EV control unit (400) may further include associated memory (418) for storing software programs . . . The associated memory (418) may comprise random access memory (RAM), read only memory (ROM), solid-state memory, disk memory, optical memories or any other appropriate memory technology known to those of skill in the art.”; Figure 4- processor 401 interacts with memory 418) . . .
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the determining a first state-of-charge of one or more batteries associated with a vehicle, determining whether the first state-of-charge is below a threshold charge level, determining one or more first geographical ranges comprising one or more first charging stations based on the first state-of-charge, determining one or more charge consumption factors that influence charge consumption in the one or more batteries, estimating the charge consumption based on the one or more charge consumption factors, determining a second state-of-charge based on the charge consumption, determining one or more second geographical ranges comprising one or more second charging stations based on the second state-of-charge, and reserving one or more charging sessions with the one or more second charging stations for charging the one or more batteries of Tsai with the non-transitory computer readable storage medium, comprising a sequence of instructions, which when executed by a processor cause actions to be performed as taught by Pedersen to have a non-transitory computer readable storage medium, comprising a sequence of instructions, which when executed by a processor causes performance the functions as described. Doing so would provide a means for implementing the method.
Claims 63-64, 72-73, and 80 are rejected under 35 U.S.C. 103 as being unpatentable over Tsai in view of Pedersen and further in view of Sharma et al. (D. K. Sharma, H. V. B. K and V. R. Hulipalled, "EV Home Charging Infrastructure & Low Battery AI Algorithm," 2022 Third International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE), Bengaluru, India, 2022, pp. 1-9, doi: 10.1109/ICSTCEE56972.2022.10099943.; hereinafter Sharma).
Regarding claim 63, Tsai and Pedersen disclose the subject matter of claim 62 as recited in the claim and applied above. Additionally, Tsai discloses the subject matter indicated in bold below:
. . . determine . . . a distance range that the vehicle is capable to travel utilizing the first state-of-charge (see Tsai at least pg. 3, paragraph 8 “Select the center of the range and calculate the radius of the selected range, for example, centering on the estimated position P1 of the electric vehicle C after estimating the t time (0<t<T), and multiplying the current vehicle speed V by a predetermined time. T (for example, battery buffer time, that is, battery remaining time), as the radius D of the selected range, the selected range SRd is obtained (where d represents directionality).”);
identify . . . one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging (see Tsai at least pg. 2, paragraph 3 “. . . when the location of the electric vehicle exceeds the current safe driving range of the electric quantity, displaying an electric quantity warning driving range of the electric vehicle, and displaying at least one electric replenishing space located within the electric quantity warning driving range.”);
determine . . . the one or more first geographical ranges encompassing the one or more first zones (see Tsai at least pg. 2, paragraph 3 “. . . when the location of the electric vehicle exceeds the current safe driving range of the electric quantity, displaying an electric quantity warning driving range of the electric vehicle, and displaying at least one electric replenishing space located within the electric quantity warning driving range.”); and
provide . . . a layout of the one or more first geographical ranges (see Tsai at least pg. 3, paragraph 4 “. . . as shown in FIG. 4, when the position of the electric vehicle C exceeds the current electric safety driving range BSR, the electric vehicle warning driving range BWR of the electric vehicle C is calculated and displayed . . .”; pg. 5, paragraph 3 “The UI (user interface) display step S540 is the power replenishment location (and the power replenishment facility information) and the coverage range (the battery safety driving range BSR, and the battery warning) in the selected range obtained in the above steps S510 and S520. Driving range BWR), combining the two kinds of information with the map and presenting it to the user.”; Figure 4- zone around vehicle position with charger in zone shown).
While Tsai discloses determining a distance range that the vehicle is capable to travel utilizing the first state-of-charge, identifying one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging, determining the one or more first geographical ranges encompassing the one or more first zones, and providing a layout of the one or more first geographical ranges, it does not appear to explicitly disclose using a processor used to perform these steps nor using an artificial intelligence engine to perform these steps.
Pedersen discloses using a processor (see Pedersen at least pg. 20, col. 10, lines 13-18 “The processor (401) may be of any suitable configuration known to those of skill in the art.”).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the steps of Tsai with the processor implementation as taught by Pedersen to have a processor perform the functions as described. The examiner supplies the same rationale for the combination of these references as provided with regard to claim 62 above.
While Tsai and Pedersen disclose using a processor to determine a distance range that the vehicle is capable to travel utilizing the first state-of-charge, identify one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging, determine the one or more first geographical ranges encompassing the one or more first zones, and provide a layout of the one or more first geographical ranges, they do not appear to explicitly disclose using an artificial intelligence engine to perform these steps.
Sharma teaches using an artificial intelligence engine to make battery and geographically-sensitive determinations such as determining a distance range that the vehicle is capable to travel utilizing the first state-of-charge and identifying one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging (see Sharma at least pg. 4, col. 1, paragraph 2 “For locating and finding the charging station we are using the geofencing method which enables us to create a radius over the user’s location and find any nearby chargers . . .”; pg. 5, col. 1, paragraph 1 “. . . the algorithm which we have named EVon Algo considers factors such as Traffic, Destination Distance, and Rider’s riding style and suggests the user any nearby chargers (home/fast), up to what percentage should the user need to charger their electric vehicle and under what mode they need to ride to get the shortest estimation time of reach to their destination.”; pg. 5, col. 2, paragraph 1 “The algorithm doesn’t use any complicated calculations, in-fact it uses a simple deep-learning algorithm to get the best solution to the problem.”; pg. 6, col. 1, paragraph 1 “Fig. 5. represents the input given to the multi-layer perceptron and the desired output we expect from the model.”; Figure 5- Deep learning is used to determine the zones containing chargers (“Nearby chargers” output element)).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the using a processor to determine a distance range that the vehicle is capable to travel utilizing the first state-of-charge, identify one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging, determine the one or more first geographical ranges encompassing the one or more first zones, and provide a layout of the one or more first geographical ranges of Tsai and Pedersen with the using an artificial intelligence engine to make battery and geographically-sensitive determinations such as determining a distance range that the vehicle is capable to travel utilizing the first state-of-charge and identifying one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging as taught by Sharma to, using an artificial intelligence engine, determine a distance range that the vehicle is capable to travel utilizing the first state-of-charge, identify one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging, determine the one or more first geographical ranges encompassing the one or more first zones, and provide a layout of the one or more first geographical ranges. Doing so would optimize solution results, as recognized by Sharma (see Sharma at least pg. 4, col. 2, paragraph 1 “The algorithm doesn’t use any complicated calculations, in-fact it uses a simple deep-learning algorithm to get the best solution to the problem.”).
Regarding claim 64, Tsai, Pedersen, and Sharma disclose the subject matter of claim 63 as recited in the claim and applied above. Additionally, Tsai discloses the subject matter indicated in bold below:
. . . determine a real-time location of the vehicle (see Tsai at least pg. 4, paragraph 10 “. . . the direction information may be further obtained . . . by using GPS . . .”);
determine the one or more first charging stations around the real-time location of the vehicle (see Tsai at least pg. 4, paragraph 10 “Step S510 (same as step S110 of the first embodiment) for selecting a power replenishment location, the purpose of which is to estimate the range of movement of the electric vehicle C, thereby selecting the location of at least one power replenishing device that may provide supplemental power . . .”; pg. 5, paragraph 1 “. . . after the power replenishment location is selected (that is, in the step S510 of selecting the power replenishment location, the power replenishing device that may provide the supplemental power is obtained . . . ) . . .”);
mapping the one or more first charging stations around the real-time location of the vehicle into the one or more first zones (see Tsai at least pg. 3, paragraph 4“. . . as shown in FIG. 4, when the position of the electric vehicle C exceeds the current electric safety driving range BSR, the electric vehicle warning driving range BWR of the electric vehicle C is calculated and displayed . . .”; pg. 5, paragraph 3 “The UI (user interface) display step S540 is the power replenishment location (and the power replenishment facility information) and the coverage range (the battery safety driving range BSR, and the battery warning) in the selected range obtained in the above steps S510 and S520. Driving range BWR), combining the two kinds of information with the map and presenting it to the user.”; Figure 4- zone around vehicle position with charger in zone shown); and
marking the one or more first charging stations within the one or more first zones (see Tsai at least pg. 3, paragraph 4 “. . . as shown in FIG. 4, when the position of the electric vehicle C exceeds the current electric safety driving range BSR, the electric vehicle warning driving range BWR of the electric vehicle C is calculated and displayed . . .”; pg. 5, paragraph 3 “The UI (user interface) display step S540 is the power replenishment location (and the power replenishment facility information) and the coverage range (the battery safety driving range BSR, and the battery warning) in the selected range obtained in the above steps S510 and S520. Driving range BWR), combining the two kinds of information with the map and presenting it to the user.”; Figure 4- zone around vehicle position with charger in zone shown).
While Tsai discloses determining a real-time location of the vehicle, determining the one or more first charging stations around the real-time location of the vehicle, mapping the one or more first charging stations around the real-time location of the vehicle into the one or more first zones, and marking the one or more first charging stations within the one or more first zones, it does not appear to explicitly disclose using a processor or artificial intelligence engine to perform the steps.
Pedersen teaches using a processor to perform vehicle actions (see Pedersen at least pg. 20, col. 10, lines 13-18 “The processor (401) may be of any suitable configuration known to those of skill in the art.”).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the steps of Tsai with the processor implementation as taught by Pedersen to use a processor to perform the described functions. The examiner supplies the same rationale for the combination of these references as provided with regard to claim 62 above.
While Tsai and Pedersen disclose using a processor for determining a real-time location of the vehicle, determining the one or more first charging stations around the real-time location of the vehicle, mapping the one or more first charging stations around the real-time location of the vehicle into the one or more first zones, and marking the one or more first charging stations within the one or more first zones, they do not appear to explicitly disclose using an artificial intelligence engine for performing the described functions.
Sharma teaches using an artificial intelligence engine to identify one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging (see Sharma at least pg. 4, col. 2, function locateCharger() “output: nearby fast or home chargers . . . var chargersAvail = geo.getAllChargers(radius);”; Examiner notes that the algorithm identifies chargers in a radius around the current vehicle location).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention with a reasonable expectation of success to have modified the using a processor to identify one or more first zones, of Tsai and Pedersen with the using an artificial intelligence engine to identify one or more first zones, around the vehicle, comprising the one or more first charging stations that are available for charging as taught by Sharma to, using an artificial intelligence engine, perform the steps involved