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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Status of the Claims
This Office Action is in response to the claims filed on November 6, 2024.
Claims 1-20 have been presented for examination.
Claims 1-20 are currently rejected.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (U.S. Patent Publication Number 2020/0109678) in view of Surnilla et al. (2015/0047603).
Claim Interpretation
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a blowing device” in claims 1 and 16.
Support for “a blowing device” is provided in at least paragraph 37 of the instant specification.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (U.S. Patent Publication Number 2020/0109678) in view of Surnilla et al. (2015/0047603).
Regarding claim 1, Nakamura discloses a system for controlling a vehicle based on an air flow rate, the system comprising:
a fluid transfer device including an inlet receiving an outside air introduced thereinto from an outside of the vehicle (Nakamura ¶ 55 discloses an air flow meter 71 arranged in the intake pipe 32 that “detects the flow rate of air inside the intake pipe 32” including detecting pressure of the intake of fresh air in the intake manifold 31) and a blowing device configured to adjust a flow rate of the outside air introduced into the inlet; and (Nakamura ¶ 45 discloses that a “throttle valve 36 can be made to turn by a throttle valve drive actuator 37 so as to change the opening area of the intake passage,” wherein one having ordinary skill in the art would recognize that internal combustion engine systems include an engine fan to perform cooling, see “The Engine Cooling Fan”)
a controller (Nakamura in at least ¶ 52 “control device 60” which includes ECU 61) operatively connected to the fluid transfer device (Nakamura Fig. 1) and configured to control introduction of the outside air through the fluid transfer device based on an estimated driving current value of the blowing device, obtained based on a current model preset ... (Nakamura ¶ 115 discloses outputting a command value from ECU 61 to EGR control valve 52, wherein the flow rate of the intake at the intake manifold 31 is calculated based on the air flow meter 71, and wherein the opening degree of the EGR control valve 52 is controlled and adjusts the amount of flow to the intake manifold 31, which includes a total amount of fresh air, see ¶ 49. The ECU 61 further receives a trained model to calculate output parameters of the vehicle, see at least ¶ 141)
Nakamura does not expressly disclose:
... based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed, and an estimated air flow rate value of the inlet, obtained based on an air flow rate model preset based on an outside wind state in which the outside wind speed exceeds the predetermined reference wind speed.
However, Surnilla discloses:
... based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed (Surnilla ¶ 40 discloses “determining if EGR [exhaust gas recirculation] flow is less than a threshold [i.e., a calm wind state]. The threshold may include a threshold amount of EGR or a threshold EGR flow rate [i.e., a predetermined reference wind speed],” such that at the intake passage for the recirculation, “Ambient air flow from outside the vehicle may enter engine 10 through a vehicle front end and pass across the CAC, to aid in cooling the charge air,” see ¶ 24, wherein the driving motion of a turbine 62 [i.e., blowing device] may “drive the compressor 60. As such, the speed of the compressor 60 may be based on the speed of the turbine 62.” Also see Fig. 1.), and an estimated air flow rate value of the inlet, obtained based on an air flow rate model preset based on an outside wind state in which the outside wind speed exceeds the predetermined reference wind speed. (Surnilla ¶ 32 discloses determining “if the EGR rate is greater than a threshold rate,” also see ¶ 82)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the controller of Nakamura to control the introduction outside air to be based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed, as disclosed by Surnilla, with reasonable expectation of success, so that the controller may then make adjustments to the model to increase the accuracy of the model (Surnilla ¶ 60), rendering the limitation to be an obvious modification.
Regarding claim 2, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the controller is further configured to input a degree of opening of the inlet, an operation amount of the blowing device, and a vehicle speed to the current model to obtain the estimated driving current value of the blowing device. (Nakamura ¶ 49 discloses “the EGR pipe 51 is provided with an EGR control valve 52 able to change the opening area of the EGR passage formed by the EGR pipe 51. By controlling the opening degree of the EGR control valve 52, the amount of flow of the EGR gas recirculated from the exhaust manifold 41 to the intake manifold 31 is adjusted and, as a result, the EGR rate is changed. Note that, the EGR rate is the ratio of the amount of EGR gas to the total amount of gas fed to the insides of the cylinders 11 (total of amount of fresh air and amount of EGR gas),” wherein the EGR control valve receives command values from ECU 61 [i.e., the controller], see ¶ 115, and the model uses an engine speed as an input parameter, see ¶ 84. One having ordinary skill in the art would recognize that engine speed is indicative of vehicle speed, see “How to calculate wheel and vehicle speed from engine speed”)
Regarding claim 3, Nakamura in combination with Surnilla discloses the system of claim 2, wherein:
the controller is further configured to additionally input a pressure and a temperature of the outside air to the current model to obtain the estimated driving current value of the blowing device. (Nakamura ¶ 45 discloses a “a compressor 34 for compressing [i.e., additionally input pressure] and discharging intake air flowing through the intake pipe 32
Regarding claim 4, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the current model is trained based on a degree of opening of the inlet, an operation amount of the blowing device, and a driving current measurement value of the blowing device for each vehicle speed in the calm wind state. (Nakamura ¶ 115 discloses “The injection pressure of the fuel injected into the cylinders 11 of the internal combustion engine 1 is calculated based on the output of the fuel temperature sensor 74,” such that at the neural network, “The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air,” see ¶ 153, wherein “processing part 81 uses a trained model using a neural network to calculate the output parameters of the vehicle,” see ¶ 58)
Regarding claim 5, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the controller is further configured to input a degree of opening of the inlet, an operation amount of the blowing device, a driving current measurement value of the blowing device, a vehicle speed, and the outside wind speed to the air flow rate model to obtain the estimated air flow rate value of the inlet. (Nakamura ¶ 153 discloses that “at the neural network, the input parameters of the vehicle input to the first input layer, the design values of the vehicle drive device input to the second input layer, and the output parameters of the vehicle may be set as follows: The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air.” Also see Fig. 4.)
Regarding claim 6, Nakamura in combination with Surnilla discloses the system of claim 5, wherein:
the outside wind speed input to the air flow rate model is an estimated outside wind speed value obtained based on an outside wind model preset for a relationship between a driving current of the blowing device and the outside wind speed. (Nakamura ¶ 115 discloses that “The flow rate of the intake in the intake manifold 31 is calculated based on the output of the air flow meter 71 and the command value output from the ECU 61 to the EGR control valve 52” of the neural network. Also see ¶ 17.)
Regarding claim 7, Nakamura in combination with Surnilla discloses the system of claim 6, wherein:
the outside wind model is trained so that the estimated air flow rate value of the inlet obtained by inputting the estimated outside wind speed value to the air flow rate model coincides with an air flow rate measurement value of the inlet. (Nakamura ¶ 108 “the processing part 81 uses the trained model using a neural network to calculate the output parameter of the vehicle.” One having ordinary skill in the art would recognize that “so that” indicates an intended use and therefore, the ensuing limitation is not required by the claim under the broadest reasonable interpretation.)
Regarding claim 8, Nakamura in combination with Surnilla discloses the system of claim 6, wherein:
the outside wind model is set so that a sign of the estimated outside wind speed value is varied depending on a magnitude relationship between the driving current measurement value of the blowing device and a reference current corresponding to the calm wind state. (Nakamura ¶ 102 discloses that “In learning of the neural network, sets of training data including the design values of the vehicle drive device, the actually measured values of input parameters other than the design values, and actually measured values (true data) of the output parameters corresponding to the same are used.” One having ordinary skill in the art would recognize that “so that” indicates an intended use and therefore, the ensuing limitation is not required by the claim under the broadest reasonable interpretation.)
Regarding claim 9, Nakamura in combination with Surnilla discloses the system of claim 6, wherein:
the outside wind model is set so that a magnitude of the estimated outside wind speed value is varied depending on a difference between the driving current measurement value of the blowing device and a reference current corresponding to the calm wind state. (Nakamura ¶ 102 discloses that “In learning of the neural network, sets of training data including the design values of the vehicle drive device, the actually measured values of input parameters other than the design values, and actually measured values (true data) of the output parameters corresponding to the same are used.” One having ordinary skill in the art would recognize that “so that” indicates an intended use and therefore, the ensuing limitation is not required by the claim under the broadest reasonable interpretation.)
Regarding claim 10, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the air flow rate model is trained based on a degree of opening of the inlet, an operation amount of the blowing device, a driving current measurement value of the blowing device, a vehicle speed, and an air flow rate measurement value of the inlet for each outside wind speed measurement value in the outside wind state. (Nakamura ¶ 115 discloses “The injection pressure of the fuel injected into the cylinders 11 of the internal combustion engine 1 is calculated based on the output of the fuel temperature sensor 74,” such that at the neural network, “The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air,” see ¶ 153, wherein “processing part 81 uses a trained model using a neural network to calculate the output parameters of the vehicle,” see ¶ 58)
Regarding claim 11, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
in response that the estimated driving current value of the blowing device obtained based on the current model is different from a driving current measurement value of the blowing device, the controller is further configured to control the introduction of the outside air through the fluid transfer device based on the estimated air flow rate value of the inlet obtained based on the air flow rate model. (Nakamura ¶ 49 discloses “By controlling the opening degree of the EGR control valve 52, the amount of flow of the EGR gas recirculated from the exhaust manifold 41 to the intake manifold 31 is adjusted and, as a result, the EGR rate is changed,” such that “parameters for sets of training data may be acquired at other vehicles different from the vehicle 100,” see ¶ 139. Also see Fig. 8.)
Regarding claim 12, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the controller is further configured to control an operation amount of the blowing device to control the introduction of the outside air. (Nakamura ¶ 49 discloses “By controlling the opening degree of the EGR control valve 52, the amount of flow of the EGR gas recirculated from the exhaust manifold 41 to the intake manifold 31 is adjusted”)
Regarding claim 13, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the fluid transfer device further includes an inlet opening/closing device operatively connected to the controller and configured to adjust a degree of opening of the inlet, and (Nakamura ¶ 42 discloses “at the cylinder head, intake valves configured to open and close the intake ports and exhaust valves configured to open and close the exhaust ports,” such that “The throttle valve 36 can be made to turn by a throttle valve drive actuator 37 so as to change the opening area of the intake passage”)
wherein the controller is further configured to control the degree of opening of the inlet through the inlet opening/closing device to control the introduction of the outside air. (Nakamura ¶ 55 discloses “The air flow meter 71 is arranged in the intake pipe 32 between the air cleaner 33 and the compressor 34 and detects the flow rate of air inside the intake pipe 32. The intake pressure sensor 73 is arranged in the intake manifold 31 and detects the pressure of the intake in the intake manifold 31 (in the present embodiment, fresh air and EGR gas).” Also see ¶ 42 and Fig. 1.)
Regarding claim 14, Nakamura in combination with Surnilla discloses the system of claim 1, wherein:
the fluid transfer device further includes: an outside air port allowing the outside air introduced through the inlet to flow into an indoor space in the vehicle therethrough; and (Nakamura ¶ 55 discloses “The air flow meter 71 is arranged in the intake pipe 32 between the air cleaner 33 and the compressor 34 and detects the flow rate of air inside the intake pipe 32.”)
an outside air port opening/closing device operatively connected to the controller and configured to adjust a degree of opening of the outside air port, and (Nakamura ¶ 47 discloses “If the opening degree of the variable nozzle is changed, the flow rate of the exhaust gas supplied to the turbine blades of the turbine 43 changes. As a result, the rotational speed of the turbine 43 changes.”)
wherein the controller is further configured to control the degree of opening of the outside air port through the outside air port opening/closing device to control the introduction of the outside air. (Nakamura ¶ 47 discloses “the compressor 34 is turned and accordingly the intake air is compressed,” wherein the intake air includes “fresh air,” see ¶ 55)
Regarding claim 15, Nakamura in combination with Surnilla discloses the system of claim 1, further including:
a driving unit (Nakamura ¶ 52 “electronic control unit (ECU) 61”) operatively connected to the controller and configured to supply driving force to the vehicle through at least one of an engine or a motor, (Nakamura ¶ 57 discloses “The ECU 61 outputs control signals for controlling these actuators from the output port 67 to thereby control the internal combustion engine 1.” Also see Fig. 1.)
wherein the controller (Nakamura ¶ 52 “control device 60”) is further configured to determine air resistance for the vehicle based on the estimated air flow rate value, and (Nakamura ¶ 114 “As the input parameters of the vehicle input to the first input layer, the pressure [i.e., air resistance] and the flow rate of the intake inside the intake manifold 31 are used”)
to control the driving force through the driving unit based on the determined air resistance. (Nakamura ¶ 145 discloses acquiring “the output torque [i.e., drive force] of the internal combustion engine 1′ calculated based on the output of the torque sensor 76,” and controlling the vehicle drive system, see Fig. 8 and corresponding ¶¶ 105 and 109)
Regarding claim 16, Nakamura discloses a method of controlling, based on an air flow rate, a vehicle including a fluid transfer device including an inlet receiving an outside air introduced thereinto from an outside of the vehicle and a blowing device configured to adjust a flow rate of the outside air introduced into the inlet, the method comprising:
obtaining, by a controller, an estimated driving current value of the blowing device based on a current model preset ... (Nakamura ¶ 115 discloses outputting a command value from ECU 61 to EGR control valve 52, wherein the flow rate of the intake at the intake manifold 31 is calculated based on the air flow meter 71, and wherein the opening degree of the EGR control valve 52 is controlled and adjusts the amount of flow to the intake manifold 31, which includes a total amount of fresh air, see ¶ 49. The ECU 61 further receives a trained model to calculate output parameters of the vehicle, see at least ¶ 141)
controlling, by the controller operatively connected to the fluid transfer device, introduction of the outside air through the fluid transfer device based on the estimated driving current value of the blowing device ... (Nakamura ¶ 49 discloses “By controlling the opening degree of the EGR control valve 52, the amount of flow of the EGR gas recirculated from the exhaust manifold 41 to the intake manifold 31 is adjusted and, as a result, the EGR rate is changed,” such that “parameters for sets of training data may be acquired at other vehicles different from the vehicle 100,” see ¶ 139. Also see Fig. 8.)
Nakamura does not expressly disclose:
[obtaining, by a controller, an estimated driving current value of the blowing device] based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed;
obtaining, by the controller, an estimated air flow rate value of the inlet based on an air flow rate model preset based on an outside wind state in which the outside wind speed exceeds the predetermined reference wind speed; and
However, Surnilla discloses:
[obtaining, by a controller, an estimated driving current value of the blowing device] based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed; (Surnilla ¶ 40 discloses “determining if EGR [exhaust gas recirculation] flow is less than a threshold [i.e., a calm wind state]. The threshold may include a threshold amount of EGR or a threshold EGR flow rate [i.e., a predetermined reference wind speed],” such that at the intake passage for the recirculation, “Ambient air flow from outside the vehicle may enter engine 10 through a vehicle front end and pass across the CAC, to aid in cooling the charge air,” see ¶ 24, wherein the driving motion of a turbine 62 [i.e., blowing device] may “drive the compressor 60. As such, the speed of the compressor 60 may be based on the speed of the turbine 62.” Also see Fig. 1.)
obtaining, by the controller, an estimated air flow rate value of the inlet based on an air flow rate model preset based on an outside wind state in which the outside wind speed exceeds the predetermined reference wind speed; and (Surnilla ¶ 32 discloses determining, thereby obtaining, “if the EGR rate is greater than a threshold rate,” also see ¶ 82)
controlling, by the controller operatively connected to the fluid transfer device, introduction of the outside air through the fluid transfer device based on the estimated driving current value of the blowing device and the estimated air flow rate value of the inlet. (Surnilla ¶ 19 discloses “The intake passage 42 includes a throttle 21 having a throttle plate 22 to regulate flow to the intake manifold 44,” wherein “the position (TP) of the throttle plate 22 may be varied by the controller 12 to enable electronic throttle control (ETC)” such that “Increasing the opening of the throttle 21 may increase the amount of air supplied to the intake manifold 44”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the estimated driving current value of Nakamura to be based on a calm wind state in which an outside wind speed is less than or equal to a predetermined reference wind speed, and to further include controlling the introduction of the outside air to be based on an estimated air flow rate value of the inlet based on an air flow rate model preset based on an outside wind state in which the outside wind speed exceeds the predetermined reference wind speed, as disclosed by Surnilla, with reasonable expectation of success, so that the controller may then make adjustments to the model to increase the accuracy of the model (Surnilla ¶ 60), rendering the limitation to be an obvious modification, and to increase CAC cooling efficiency (Surnilla ¶ 34), rendering the limitation to be an obvious modification.
Regarding claim 17, Nakamura in combination with Surnilla discloses the method of claim 16, wherein:
the obtaining of the estimated driving current value includes inputting a degree of opening of the inlet, an operation amount of the blowing device, and a vehicle speed to the current model to obtain the estimated driving current value of the blowing device, and (Nakamura ¶ 153 discloses that “at the neural network, the input parameters of the vehicle input to the first input layer, the design values of the vehicle drive device input to the second input layer, and the output parameters of the vehicle may be set as follows: The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air.” Also see Fig. 4.)
wherein the obtaining of the estimated air flow rate value includes inputting the degree of opening of the inlet, the operation amount of the blowing device, a driving current measurement value of the blowing device, the vehicle speed, and the outside wind speed to the air flow rate model to obtain the estimated air flow rate value of the inlet. (Nakamura ¶ 115 discloses “The injection pressure of the fuel injected into the cylinders 11 of the internal combustion engine 1 is calculated based on the output of the fuel temperature sensor 74,” such that at the neural network, “The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air,” see ¶ 153, wherein “processing part 81 uses a trained model using a neural network to calculate the output parameters of the vehicle,” see ¶ 58)
Regarding claim 18, Nakamura in combination with Surnilla discloses the method of claim 17, wherein:
the outside wind speed input to the air flow rate model is an estimated outside wind speed value obtained based on an outside wind model preset for a relationship between a driving current of the blowing device and the outside wind speed. (Nakamura ¶ 115 discloses that “The flow rate of the intake in the intake manifold 31 is calculated based on the output of the air flow meter 71 and the command value output from the ECU 61 to the EGR control valve 52” of the neural network. Also see ¶ 17.)
Regarding claim 19, Nakamura in combination with Surnilla discloses the method of claim 16, wherein:
the current model is trained based on a degree of opening of the inlet, an operation amount of the blowing device, a vehicle speed, and a driving current measurement value of the blowing device in the calm wind state, and (Nakamura ¶ 115 discloses “The injection pressure of the fuel injected into the cylinders 11 of the internal combustion engine 1 is calculated based on the output of the fuel temperature sensor 74,” such that at the neural network, “The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air,” see ¶ 153, wherein “processing part 81 uses a trained model using a neural network to calculate the output parameters of the vehicle,” see ¶ 58)
wherein the air flow rate model is trained based on the degree of opening of the inlet, the operation amount of the blowing device, the driving current measurement value of the blowing device, the vehicle speed, an outside wind speed measurement value, and an air flow rate measurement value of the inlet in the outside wind state. (Nakamura ¶ 153 discloses that “at the neural network, the input parameters of the vehicle input to the first input layer, the design values of the vehicle drive device input to the second input layer, and the output parameters of the vehicle may be set as follows: The input parameters of the vehicle include the engine speed, fuel injection amount, fuel injection timing, fuel injection pressure, temperature and pressure of the intake inside the intake manifold 31, opening degree of the EGR control valve 52, and amount of intake air.” Also see Fig. 4.)
Regarding claim 20, Nakamura in combination with Surnilla discloses the method of claim 16, wherein:
the controlling of the introduction of the outside air includes controlling the introduction of the outside air through the fluid transfer device based on the estimated air flow rate value of the inlet obtained based on the air flow rate model in response that the estimated driving current value of the blowing device obtained based on the current model is different from a driving current measurement value of the blowing device. (Nakamura ¶ 49 discloses “By controlling the opening degree of the EGR control valve 52, the amount of flow of the EGR gas recirculated from the exhaust manifold 41 to the intake manifold 31 is adjusted and, as a result, the EGR rate is changed,” such that “parameters for sets of training data may be acquired at other vehicles different from the vehicle 100,” see ¶ 139. Also see Fig. 8.)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Echlin et al. (U.S. Patent Publication Number 2022/0056860) discloses a method for determining a state of an air diverter valve of an air induction system of a vehicle, wherein the determined state of the air diverter valve may be based on an intercooler-based estimated ambient air temperature and a comparison between an ambient air temperature sensor value and a pre-compressor sensor value.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEPHANIE T SU whose telephone number is (571)272-5326. The examiner can normally be reached Monday to Friday, 9:30AM - 5:00PM 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, ANISS CHAD can be reached at (571)270-3832. 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.
/STEPHANIE T SU/Patent Examiner, Art Unit 3662