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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/6/2026 has been entered.
Response to Amendment
Applicant' s amendment and response filed 7/6/2026 has been entered and made record. This application contains 12 pending claims.
Claims 1-3, and 6-8 have been amended.
Response to Arguments
Claims 1, 2, and 3 have been amended and the amended claims limitations overcome the claims objections in claims 1, 2, and 3. Therefore, the claims objections in claims 1, 2, and 3 have been withdrawn.
Applicant’s arguments filed 7/6/2026 regarding claims rejections under 35 U.S.C. 101 in claim 1-12 have been fully considered but they are not persuasive.
The applicant argues on pages 13-15 of the remark filed on 7/6/2026 that “…
This amendment integrates any alleged abstract idea into a practical application for at least the reasons set forth below. … Further, the independent claims recite a concrete technical improvement to motor control technology. … The claims recite that the motor is controlled by supplying current to an excitation coil based on an initial position determined without rotating the rotor. This eliminates the need for a physical, mechanical rotation of the rotor during initialization, which is a concrete improvement to how the motor physically operates. The benefit is not that the mathematics are performed differently, but that the motor can be used in applications where preliminary rotation is not allowed, such as robots, unmanned transport vehicles, and sewing devices, and that unintended physical operations of these machines are prevented. This is an improvement to motor control technology, not to the abstract idea. … .”
The Examiner respectfully disagrees applicant’s argument. Practical application can be demonstrated by additional elements that are sufficient to integrate the judicial exception into a practical application. The additional elements “acquiring learning data necessary for estimation of a rotational position of the rotor”; “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”, “acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”, “acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”, “on a basis of the N2 analog signals obtained in the learning period”, “acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position”, and “wherein the estimating the rotational position of the rotor” are not sufficient to integrate the abstract idea into a practical application.
The additional elements “acquiring the N1 digital signals by using the N1 first magnetic sensors”, and “acquiring the N2 analog signals by using the N2 second magnetic sensors” are considered necessary data gathering and thus, not sufficient to integrate the abstract idea into a practical application. As recited in MPEP section 2106.05(g), necessary data gathering (i.e., acquiring signal) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015).
The alleged improvement of eliminating the need for a physical, mechanical rotation of the rotor during initialization relates to improvement to the abstract idea itself. Therefore, the current claims do not recite additional elements that are indicative of integration of an abstract idea into a practical application.
The applicant argues on pages 13-14 of the remark filed that “Applicant respectfully submits that the independent claims are directly analogous to the claims found patent eligible in USPTO Subject Matter Eligibility Example 45 (Controller for Injection Mold). In Example 45, claim 1 was found ineligible because it recited mathematical calculations (calculating an extent of curing completion using the Arrhenius equation) and a mental process (determining the extent of cure as a percentage) without integrating these exceptions into a practical application. However, claim 2 of Example 45 was found eligible because it added the limitation that the controller is configured to "send control signals to the injection molding apparatus once the polyurethane has reached a target percentage, the control signals instructing the apparatus to open the mold and eject the molded polyurethane from the mold." The USPTO found that this limitation "does not merely link the judicial exceptions to a technical field, but instead adds a meaningful limitation in that it employs the information provided by the judicial exceptions (the calculated percentage of the extent of cure) to control the operation of the injection molding apparatus." The USPTO further found that "using the information obtained via the judicial exception to take corrective action and control the injection molding apparatus in a particular way is an 'other meaningful limitation' that integrates the judicial exception into the overall control scheme and accordingly practically applies the exception." … Applicant respectfully submits that the independent claims, like claim 2 of Example 45, employ the information provided by the alleged judicial exception to control the operation of a physical apparatus, and therefore integrate the exception into a practical application.”
The Examiner respectfully disagrees applicant’s argument. The present claims limitations are dissimilar to the claims in Example 45. In Example 45, claim 2 recites the same judicial exceptions as claim 1, but is eligible because claims adds the additional limitation regarding control signals that are sent to the injection molding apparatus once the polyurethane has reached a target percentage, so that the apparatus opens the mold and ejects the molded polyurethane from the mold. The limitation does not merely link the judicial exceptions to a technical field, but instead adds a meaningful limitation in that it employs the information provided by the judicial exceptions (the calculated percentage of the extent of cure) to control the operation of the injection molding apparatus. The claim limitation recites meaningful limitations that use the abstract ideas to improve the previous molding technology, such that the claim integrates the exceptions into a practical application. However, the present claims recite a judicial exception, and the abstract ideas are not integrated into a practical application, and thus, the claims are directed to the judicial exception, as similar to the claim 1 of Example 45.
The applicant argues on pages 15-16 of the remark filed that “… The Examiner has not provided any of these four required forms of evidence to support the assertion that the claimed elements are well- understood, routine, and conventional. Moreover, the Examiner's own prior art analysis expressly acknowledges that "the prior arts of record, alone or in combination, do not fairly teach or suggest" the claimed limitations. (Office Action, pages 44-58). This finding directly contradicts the assertion that these elements are well-understood, routine, and conventional. If the claimed elements were truly well-understood, routine, and conventional in the relevant art, the prior art would have disclosed them.”
The Examiner respectfully disagrees applicant’s argument. Significantly more can be demonstrated by additional elements that are not well-understood and conventional that integrate the abstract idea into a practical application. However, the claims do not recite them. The additional elements “acquiring learning data necessary for estimation of a rotational position of the rotor”; “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”, “acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”, “acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”, “on a basis of the N2 analog signals obtained in the learning period”, “acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position”, “wherein the estimating the rotational position of the rotor”, “acquiring the N1 digital signals by using the N1 first magnetic sensors”, and “acquiring the N2 analog signals by using the N2 second magnetic sensors” are well-understood and conventional. Therefore, the claims 1-3, and 6-8 do not contain additional elements that are not well-understood and conventional that integrate the abstract idea into a practical application.
Dependent claims 4-5 and 9-12 provide additional features/steps which are considered part of an expanded abstract idea of the independent claims, and do not integrate the abstract ideas into a practical application. Therefore, claims 4-5 and 9-12 are also patent ineligible.
Hence, the Examiner submits that the rejections of Claims 1-12 are proper.
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 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
As to claim 1, the claim recites “A method for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the method comprising:
acquiring learning data necessary for estimation of a rotational position of the rotor;
estimating the rotational position of the rotor on a basis of the learning data; and
controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor,
wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor,
acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet,
acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor,
dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position, and
wherein the estimating the rotational position of the rotor includes acquiring the N1 digital signals by using the N1 first magnetic sensors,
acquiring the N2 analog signals by using the N2 second magnetic sensors,
specifying a current quadrant from among the plurality of quadrants on a basis of the acquired N1 digital signals,
specifying a current section from among the plurality of sections on a basis of the acquired N2 analog signals, and
determining, as the initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.”
As to claim 2, the claim recites “A method for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the method comprising:
acquiring learning data necessary for estimation of a rotational position of a rotor;
estimating the rotational position of the rotor on a basis of the learning data; and
controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor,
wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor,
acquiring N3 (N3 is an integer of 2 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, by using N3 third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet,
acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor,
calculating time series data of a mechanical angle in a learning period on a basis of the N3 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
acquiring, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number, and
wherein the estimating the rotational position of the rotor includes
acquiring the N3 analog signals by using the N3 third magnetic sensors,
calculating a current value of the mechanical angle on a basis of the acquired N3 analog signals, and
determining, as an initial position of the rotor, a pole pair number corresponding to the current value of the mechanical angle on a basis of the learning data.”
As to claim 3, the claim recites “A method for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the method comprising:
acquiring learning data necessary for estimation of a rotational position of a rotor;
estimating the rotational position of the rotor on a basis of the learning data; and
controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor,
wherein the acquiring learning data includes
rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor,
acquiring N4 (N4 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, by using N4 fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet,
acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor,
dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position, and
wherein the estimating the rotational position of the rotor includes
acquiring the N4 analog signals by using the N4 fourth magnetic sensors, acquiring the N2 analog signals by using the N2 second magnetic sensors,
specifying a current quadrant from among the plurality of quadrants on a basis of the acquired N4 analog signals,
specifying a current section from among the plurality of sections on a basis of the acquired N2 analog signals, and
determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.”
As to claim 6, the claim recites “A device for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the device comprising:
a magnet having one magnetic pole pair and sharing a rotation axis with the rotor;
N1 (N1 is an integer of 3 or more) first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet;
N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor; and
a signal processing device that processes output signals of the first magnetic sensor and the second magnetic sensor, wherein
the signal processing device includes
a processor that executes:
learning processing of acquiring learning data necessary for estimation of a rotational position of the rotor,
position estimation processing of estimating the rotational position of the rotor on a basis of the learning data, and
controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and
a memory that stores the learning data, the processor executes, as the learning processing,
first processing of rotating the magnet together with the rotor,
second processing of acquiring N1 digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, via the N1 first magnetic sensors,
third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors,
fourth processing of dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
fifth processing of, on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position, and the processor executes, as the position estimation processing,
seventh processing of acquiring the N1 digital signals via the N1 first magnetic sensors,
eighth processing of acquiring the N2 analog signals via the N2 second magnetic sensors,
ninth processing of specifying a current quadrant from among the plurality of quadrants on a basis of the N1 digital signals acquired in the seventh processing,
tenth processing of specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing, and
eleventh processing of determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.”
As to claim 7, the claim recites “A device for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the device comprising:
a magnet having one magnetic pole pair and sharing a rotation axis with the rotor;
N3 (N3 is an integer of 3 or more) third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet;
N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor; and
a signal processing device that processes output signals of the second magnetic sensors and the third magnetic sensors, wherein
the signal processing device includes
a processor that executes:
learning processing of acquiring learning data necessary for estimation of a rotational position of a rotor,
position estimation processing of estimating the rotational position of the rotor on a basis of the learning data, and
controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and
a memory that stores the learning data,
the processor executes, as the learning processing,
first processing of rotating the magnet together with the rotor,
second processing of acquiring N3 analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, via the N3 third magnetic sensors,
third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors,
fourth processing of calculating time series data of a mechanical angle in a learning period on a basis of the N3 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
fifth processing of, on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number, and
the processor performs, as the position estimation processing,
seventh processing of acquiring the N3 analog signals via the N3 third magnetic sensors,
eighth processing of calculating a current value of the mechanical angle on a basis of the N3 analog signals acquired in the seventh processing, and
ninth processing of determining, as an initial position of the rotor, a pole pair number corresponding to the current value of the mechanical angle on a basis of the learning data stored in the memory.”
As to claim 8, the claim recites “A device for controlling a motor including a rotor having P (P is an integer of 2 or more) magnetic pole pairs, the device comprising:
a magnet having one magnetic pole pair and sharing a rotation axis with the rotor;
N4 (N4 is an integer of 3 or more) fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet;
N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along the rotation direction of the rotor; and
a signal processing device that processes output signals of the second magnetic sensors and the fourth magnetic sensors, wherein
the signal processing device includes a processor that executes:
learning processing of acquiring learning data necessary for estimation of the rotational position of a rotor,
position estimation processing of estimating the rotational position of the rotor on a basis of the learning data, and
controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and
a memory that stores the learning data,
the processor executes, as the learning processing,
first processing of rotating the magnet together with the rotor,
second processing of acquiring N4 analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, via the N4 fourth magnetic sensors,
third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors,
fourth processing of dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle,
fifth processing of, on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections, and
sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position, and
the processor executes, as the position estimation processing,
seventh processing of acquiring the N4 digital signals via the N4 fourth magnetic sensors,
eighth processing of acquiring the N2 analog signals via the N2 second magnetic sensors,
ninth processing of specifying a current quadrant from among the plurality of quadrants on a basis of the N4 digital signals acquired in the seventh processing,
tenth processing of specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing, and
eleventh processing of determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.”
Under the Step 1 of the eligibility analysis, we determine whether the claims are directed to a statutory category by 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. The above claims are considered to be in a statutory category (process for claim 1-3, and apparatus for claims 6-8).
Under the Step 2A, Prong One, we consider whether the claims recite a judicial exception (abstract idea). In the above claims, the bold type portion constitutes an abstract idea because, under a broadest reasonable interpretation, they recite limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the grouping of subject matter when recited as such in a claim that covers mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations) and mental processes (concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions).
In claim 1, the steps of “estimating the rotational position of the rotor on a basis of the learning data”,
“dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”, and
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”,
“specifying a current quadrant from among the plurality of quadrants on a basis of the acquired N1 digital signals” and
“specifying a current section from among the plurality of sections on a basis of the acquired N2 analog signals” are mathematical concepts, therefore, they are considered to be an abstract idea.
The steps of “determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
In claim 2, the steps of “estimating the rotational position of the rotor on a basis of the learning data”,
“calculating time series data of a mechanical angle in a learning period on a basis of the N3 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”, and
“calculating a current value of the mechanical angle on a basis of the acquired N3 analog signals” are mathematical concepts, therefore, they are considered to be an abstract idea.
The step of “determining, as an initial position of the rotor, a pole pair number corresponding to the current value of the mechanical angle on a basis of the learning data.” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
In claim 3, the steps of “estimating the rotational position of the rotor on a basis of the learning data”,
“dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”,
“specifying a current quadrant from among the plurality of quadrants on a basis of the acquired N4 analog signals”, and
“specifying a current section from among the plurality of sections on a basis of the acquired N2 analog signals” are mathematical concepts, therefore, they are considered to be an abstract idea.
The step of “determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
In claim 6, the steps of “learning processing of acquiring learning data necessary for estimation of a rotational position of the rotor”,
“position estimation processing of estimating the rotational position of the rotor on a basis of the learning data”,
“dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”,
“specifying a current quadrant from among the plurality of quadrants on a basis of the N1 digital signals acquired in the seventh processing”, and
“specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing” are mathematical concepts, therefore, they are considered to be an abstract idea.
The step of “determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
In claim 7, the steps of “learning processing of acquiring learning data necessary for estimation of a rotational position of a rotor”,
“position estimation processing of estimating the rotational position of the rotor on a basis of the learning data”,
“calculating time series data of a mechanical angle in a learning period on a basis of the N3 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”, and
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”, are mathematical concepts, therefore, they are considered to be an abstract idea.
The step of “determining, as an initial position of the rotor, a pole pair number corresponding to the current value of the mechanical angle on a basis of the learning data stored in the memory” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
In claim 8, the steps of “learning processing of acquiring learning data necessary for estimation of the rotational position of a rotor”,
“position estimation processing of estimating the rotational position of the rotor on a basis of the learning data”,
“dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”,
“specifying a current quadrant from among the plurality of quadrants on a basis of the N4 digital signals acquired in the seventh processing”, and
“specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing” are mathematical concepts, therefore, they are considered to be an abstract idea.
The step of “determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data” is a combination of a mathematical concept and a mental process, therefore, it is considered to be an abstract idea.
Next, under the Step 2A, Prong Two, we consider whether the claims that recite a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claims recite additional elements that integrate the exception into a practical application of that exception.
The claims comprise the following additional elements:
Claim 1: acquiring learning data necessary for estimation of a rotational position of the rotor; controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor, acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet, acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor, on a basis of the N2 analog signals obtained in the learning period, acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position, and wherein the estimating the rotational position of the rotor includes acquiring the N1 digital signals by using the N1 first magnetic sensors, acquiring the N2 analog signals by using the N2 second magnetic sensors.
The additional elements “acquiring learning data necessary for estimation of a rotational position of the rotor”; “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”, “acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”, “acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”, “on a basis of the N2 analog signals obtained in the learning period”, “acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position”, and “wherein the estimating the rotational position of the rotor” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional elements “acquiring the N1 digital signals by using the N1 first magnetic sensors”, and “acquiring the N2 analog signals by using the N2 second magnetic sensors” represent necessary data gathering and do not integrate the limitation into a practical application.
Claim 2: acquiring learning data necessary for estimation of the rotational position; controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor, acquiring N3 (N3 is an integer of 2 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, by using N3 third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet, acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor, on a basis of the N2 analog signals obtained in the learning period, acquiring, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number, and wherein the estimating the rotational position of the rotor, acquiring the N3 analog signals by using the N3 third magnetic sensors.
The additional elements “acquiring learning data necessary for estimation of the rotational position”; “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor”, “wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”, “acquiring N3 (N3 is an integer of 2 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, by using N3 third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”, “acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”, “on a basis of the N2 analog signals obtained in the learning period”, “acquiring, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number”, and “wherein the estimating the rotational position of the rotor” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional element “acquiring the N3 analog signals by using the N3 third magnetic sensors” represents necessary data gathering and does not integrate the limitation into a practical application.
Claim 3: acquiring learning data necessary for estimation of the rotational position; controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor, acquiring N4 (N4 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, by using N4 fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet, acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor, on a basis of the N2 analog signals obtained in the learning period, acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position, and wherein the estimating the rotational position of the rotor includes acquiring the N4 analog signals by using the N4 fourth magnetic sensors, acquiring the N2 analog signals by using the N2 second magnetic sensors.
The additional elements “acquiring learning data necessary for estimation of the rotational position”; “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “wherein the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”, “acquiring N4 (N4 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, by using N4 fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”, “acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”, “on a basis of the N2 analog signals obtained in the learning period”, “acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position”, and “wherein the estimating the rotational position of the rotor” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional elements “acquiring the N4 analog signals by using the N4 fourth magnetic sensors”, and “acquiring the N2 analog signals by using the N2 second magnetic sensors” represent necessary data gathering and do not integrate the limitations into a practical application.
Claim 6: a magnet having one magnetic pole pair and sharing a rotation axis with the rotor; N1 (N1 is an integer of 3 or more) first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet; N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor; and a signal processing device that processes output signals of the first magnetic sensor and the second magnetic sensor, wherein the signal processing device includes a processor that executes, controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and a memory that stores the learning data, the processor executes, as the learning processing, first processing of rotating the magnet together with the rotor, second processing of acquiring N1 digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, via the N1 first magnetic sensors, third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors, fifth processing of, on a basis of the N2 analog signals obtained in the learning period, sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position, and the processor executes, as the position estimation processing, seventh processing of acquiring the N1 digital signals via the N1 first magnetic sensors, eighth processing of acquiring the N2 analog signals via the N2 second magnetic sensors.
The additional elements “a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”; “N1 (N1 is an integer of 3 or more) first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet; N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”; and “a signal processing device that processes output signals of the first magnetic sensor and the second magnetic sensor, wherein the signal processing device includes a processor that executes”, “controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, “a memory that stores the learning data, the processor executes, as the learning processing”, “first processing of rotating the magnet together with the rotor, second processing of acquiring N1 digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, via the N1 first magnetic sensors”, “third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors”, “fifth processing of, on a basis of the N2 analog signals obtained in the learning period”, “sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position, and the processor executes, as the position estimation processing” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional elements “acquiring the N1 digital signals via the N1 first magnetic sensors”, “acquiring the N2 analog signals via the N2 second magnetic sensors” represent necessary data gathering and do not integrate the limitations into a practical application.
Claim 7: a magnet having one magnetic pole pair and sharing a rotation axis with the rotor; N3 (N3 is an integer of 3 or more) third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet; N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor; a signal processing device that processes output signals of the second magnetic sensors and the third magnetic sensors, wherein the signal processing device includes a processor that executes, controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and a memory that stores the learning data, the processor executes, as the learning processing, first processing of rotating the magnet together with the rotor, second processing of acquiring N3 analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, via the N3 third magnetic sensors, third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors, fifth processing of, on a basis of the N2 analog signals obtained in the learning period, sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number, and the processor performs, as the position estimation processing, seventh processing of acquiring the N3 analog signals via the N3 third magnetic sensors, eighth processing of calculating a current value of the mechanical angle on a basis of the N3 analog signals acquired in the seventh processing.
The additional elements “a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”; “N3 (N3 is an integer of 3 or more) third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”; “N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”; “a signal processing device that processes output signals of the second magnetic sensors and the third magnetic sensors, wherein the signal processing device includes a processor that executes”, “controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, and “a memory that stores the learning data, the processor executes, as the learning processing”, “first processing of rotating the magnet together with the rotor”, “second processing of acquiring N3 analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, via the N3 third magnetic sensors”, “third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors”, “fifth processing of, on a basis of the N2 analog signals obtained in the learning period”, “sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number”, and “the processor performs, as the position estimation processing”, “eighth processing of calculating a current value of the mechanical angle on a basis of the N3 analog signals acquired in the seventh processing” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional elements “acquiring the N3 analog signals via the N3 third magnetic sensors” represents necessary data gathering and do not integrate the limitations into a practical application.
Claim 8: a magnet having one magnetic pole pair and sharing a rotation axis with the rotor; N4 (N4 is an integer of 3 or more) fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet; N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along the rotation direction of the rotor; a signal processing device that processes output signals of the second magnetic sensors and the fourth magnetic sensors, wherein the signal processing device includes a processor that executes, controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor, and a memory that stores the learning data, the processor executes, as the learning processing, first processing of rotating the magnet together with the rotor, second processing of acquiring N4 analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, via the N4 fourth magnetic sensors, third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors, fifth processing of, on a basis of the N2 analog signals obtained in the learning period, sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position, and the processor executes, as the position estimation processing, seventh processing of acquiring the N4 digital signals via the N4 fourth magnetic sensors, eighth processing of acquiring the N2 analog signals via the N2 second magnetic sensors, ninth processing of specifying a current quadrant from among the plurality of quadrants on a basis of the N4 digital signals acquired in the seventh processing, tenth processing of specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing.
The additional elements “a magnet having one magnetic pole pair and sharing a rotation axis with the rotor”; “N4 (N4 is an integer of 3 or more) fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”; “N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along the rotation direction of the rotor”; “a signal processing device that processes output signals of the second magnetic sensors and the fourth magnetic sensors, wherein the signal processing device includes a processor that executes”, “controlling processing of controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”, and “a memory that stores the learning data, the processor executes, as the learning processing”, “first processing of rotating the magnet together with the rotor”, “second processing of acquiring N4 analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, via the N4 fourth magnetic sensors”, “third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors”, “fifth processing of, on a basis of the N2 analog signals obtained in the learning period”, “sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position”, and “the processor executes, as the position estimation processing”, “ninth processing of specifying a current quadrant from among the plurality of quadrants on a basis of the N4 digital signals acquired in the seventh processing”, and “tenth processing of specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing” are not sufficient to integrate the abstract idea into a practical application because they only add insignificant extra-solution activities to the judicial exception. The additional elements “acquiring the N4 digital signals via the N4 fourth magnetic sensors”, “acquiring the N2 analog signals via the N2 second magnetic sensors” represent necessary data gathering and do not integrate the limitations into a practical application.
In conclusion, the above additional elements, considered individually and in combination with the other claims elements do not reflect an improvement to other technology or technical field, do not reflect improvements to the functioning of the computer itself, do not recite a particular machine, do not effect a transformation or reduction of a particular article to a different state or thing, and, therefore, do not integrate the judicial exception into a practical application. Therefore, the claim is directed to a judicial exception and require further analysis under the Step 2B.
The above claims, do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they are generically recited and are well-understood/conventional in a relevant art as evidenced by the prior art of record (Step 2B analysis).
For example, acquiring the N1 digital signals by using the N1 first magnetic sensors, and acquiring the N2 analog signals by using the N2 second magnetic sensors
are considered necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. receiving data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015).
For example, rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor is disclosed by “Gopalakrishnan US 20210234447”, [0007], [0033], Claim 1, Claim 8, Claim 15; and “Strothmann US 20020152821”, [0007], [0016], [0040], [0041], Claim 1.
The claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 4-5, and 9-12 provide additional features/steps which are considered part of an expanded abstract idea of the independent claims, and do not integrate the abstract ideas into a practical application.
The dependent claims are, therefore, also not patent eligible.
Examiner’s Note
Regarding Claims 1-12, the most pertinent prior arts are “Dawn US 20210215157”, “Gopalakrishnan US 20210234447”, “Liu US 20150295525”, “Ishida US 20160109265”, “Markus DE 102016207643A1”, “Abbott US 20200274431”, “Iwamoto US 20160116304”, and “Weiland US 20200232822”.
As to claims 1-3, and 6-8, Dawn teaches wherein acquiring learning data necessary for estimation of the rotational position (Dawn, Abstract, [0007], [0012], [0029], [0034], [0084], [0201]); and
wherein estimating the rotational position of the rotor on a basis of the learning data (Dawn, Abstract, [0007], [0012], [0029], [0034], [0084], [0201]).
Gopalakrishnan teaches the acquiring learning data includes rotating, together with the rotor, a magnet having one magnetic pole pair and sharing a rotation axis with the rotor (Gopalakrishnan, [0007], [0033], Claim 1, Claim 8, Claim 15),
a magnet having one magnetic pole pair and sharing a rotation axis with the rotor (Gopalakrishnan, [0007], [0033], Claim 1, Claim 8, Claim 15),
a signal processing device that processes output signals of the second magnetic sensors and the third magnetic sensors (Gopalakrishnan, [0004], [0028], [0034], [0040], Claim 1, Claim 8, Claim 15, Claim17).
Liu teaches the estimating the rotational position of the rotor includes
acquiring the N1 digital signals by using the N1 first magnetic sensors (Liu, [0019], [0020], [0021], [0027], [0028]),
N1 (N1 is an integer of 3 or more) first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet (Liu, [0019], [0020], [0021], [0027], [0028]),
acquiring the N2 analog signals by using the N2 second magnetic sensors (Liu, [0019], [0020], [0021], [0027], [0030], [0033]),
a signal processing device that processes output signals of the first magnetic sensor and the second magnetic sensor (Liu, [0019], [0020], [0021], [0027], [0030], [0033]).
Markus teaches acquiring, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number (Markus, [0012], [0016], [0017], [0020], [0021], [0025], [0039], FIG. 2),
sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the time series data of the mechanical angle and the pole pair number (Markus, [0012], [0016], [0017], [0020], [0021], [0025], [0039], FIG. 2).
Dawn teaches wherein the signal processing device includes a processor that executes learning processing of acquiring learning data necessary for estimation of the rotational position and position estimation processing of estimating a rotational position of the rotor on a basis of the learning data (Dawn, Abstract, [0003], [0013], [0029], [0169] , [0201]), and
a memory that stores the learning data (Dawn, [0168], [0176]),
the processor executes, as the learning processing (Dawn, [0033], [0161], [0169]),
first processing of rotating the magnet together with the rotor (Dawn, [0138], [0181], [0190], [0194], [0218]),
the processor performs, as the position estimation processing (Dawn, [0013], [0030], [0039], [0043], [0079]).
However, the prior arts of record, alone or in combination, do not fairly teach or suggest “controlling the motor by supplying current to an excitation coil of the motor on a basis of the estimated rotational position of the rotor, wherein the estimated rotational position includes an initial position of the rotor determined without rotating the rotor”,
“acquiring N1 (N1 is an integer of 3 or more) digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, by using N1 first magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”,
“acquiring N3 (N3 is an integer of 2 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, by using N3 third magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”,
“acquiring N4 (N4 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, by using N4 fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”,
“N4 (N4 is an integer of 3 or more) fourth magnetic sensors opposed to the magnet and arranged along a rotation direction of the magnet”;
“acquiring N2 (N2 is an integer of 3 or more) analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, by using N2 second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”,
“N2 (N2 is an integer of 3 or more) second magnetic sensors opposed to the rotor and arranged along a rotation direction of the rotor”,
“third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors”,
“second processing of acquiring N4 analog signals having electric signals that fluctuate according to magnetic field strength and having a fourth phase difference from one another, via the N4 fourth magnetic sensors”,
“fourth processing of dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“calculating time series data of a mechanical angle in a learning period on a basis of the N3 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“dividing a learning period into a plurality of quadrants on a basis of the N4 analog signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”,
“acquiring, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number indicating the pole pair position”,
“acquiring the N3 analog signals by using the N3 third magnetic sensors”,
“acquiring the N4 analog signals by using the N4 fourth magnetic sensors”,
“acquiring the N2 analog signals by using the N2 second magnetic sensors”,
“calculating a current value of the mechanical angle on a basis of the N3 analog signals acquired”, and
“specifying a current quadrant from among the plurality of quadrants on a basis of the N1 digital signals acquired”,
“specifying a current quadrant from among the plurality of quadrants on a basis of the N4 analog signals acquired”,
“specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired”, and
“determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.”
“wherein the signal processing device includes a processor that executes learning processing of acquiring learning data necessary for estimation of the rotational position and position estimation processing of estimating a rotational position of the rotor on a basis of the learning data”, and
“second processing of acquiring N1 digital signals having levels inverted every time the magnet rotates by 180° and having a first phase difference from one another, via the N1 first magnetic sensors”,
“second processing of acquiring N3 analog signals having electric signals that fluctuate according to magnetic field strength and having a third phase difference from each other, via the N3 third magnetic sensors”,
“third processing of acquiring N2 analog signals having electric signals that fluctuate according to magnetic field strength and having a second phase difference from one another, via the N2 second magnetic sensors”,
“fourth processing of dividing a learning period into a plurality of quadrants having digital values of N1 bits different from one another on a basis of the N1 digital signals obtained in the learning period corresponding to one cycle in terms of a mechanical angle”,
“fifth processing of, on a basis of the N2 analog signals obtained in the learning period, dividing the learning period into P pole pair regions associated with pole pair numbers representing pole pair positions of the P magnetic pole pairs, further dividing each of the P pole pair regions into a plurality of sections, and associating a segment number representing the rotational position with each of the plurality of sections”, and
“sixth processing of storing, into the memory, as the learning data, data indicating a correspondence relationship between the segment number associated with the section included in each of the plurality of quadrants and the pole pair number representing the pole pair position”, and
“seventh processing of acquiring the N1 digital signals via the N1 first magnetic sensors”,
“seventh processing of acquiring the N3 analog signals via the N3 third magnetic sensors”,
“eighth processing of acquiring the N2 analog signals via the N2 second magnetic sensors”,
“eighth processing of calculating a current value of the mechanical angle on a basis of the N3 analog signals acquired in the seventh processing”,
“ninth processing of specifying a current quadrant from among the plurality of quadrants on a basis of the N1 digital signals acquired in the seventh processing”,
“ninth processing of determining, as an initial position of the rotor, a pole pair number corresponding to the current value of the mechanical angle on a basis of the learning data stored in the memory”
“tenth processing of specifying a current section from among the plurality of sections on a basis of the N2 analog signals acquired in the eighth processing”, and
“eleventh processing of determining, as an initial position of the rotor, a pole pair number corresponding to a segment number associated with the current section included in the current quadrant on a basis of the learning data.” including all limitations as claimed.
Dependent claims 4-5 and 9-12 are also distinguished over the prior art for at least the same reason as claims 1 and 6.
Examiner notes, however, that claims 1-12 are rejected under 35 U.S.C. 101, and therefore, not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
“Sawada US 20020117990” teaches “A synchronous motor controlling apparatus which can be applied to the carrier synchronized position estimating method as well and have protection-related functions such as detection of inverted magnetic pole position of a motor in a simple method, and an electric motor using the synchronous motor control apparatus. A controller controls a voltage applied to an AC motor with a PWM signal. A magnetic pole position detector of the controller detects a current of the AC motor to estimate a pole position of the AC motor. A fault detector detects a fault in the estimated magnetic position of the AC motor.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAL CE MANG whose telephone number is (571)272-0370. The examiner can normally be reached Monday to Friday- 8:30-12:00, 1:00-5:30 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine T Rastovski can be reached at (571) 270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LAL CE MANG/Primary Examiner, Art Unit 2857
Prosecution Insights