Prosecution Insights
Last updated: August 17, 2026
Application No. 19/276,594

BATTERY ELECTRIC VEHICLE

Non-Final OA §102
Filed
Jul 22, 2025
Priority
Nov 27, 2024 — JP 2024-206436
Examiner
AFRIN, NAZIA
Art Unit
3666
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Toyota Motor Corporation
OA Round
1 (Non-Final)
50%
Grant Probability
Moderate
1-2
OA Rounds
1y 11m
Est. Remaining
68%
With Interview

Examiner Intelligence

Grants 50% of resolved cases
50%
Career Allowance Rate
11 granted / 22 resolved
-2.0% vs TC avg
Strong +18% interview lift
Without
With
+18.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
49 currently pending
Career history
85
Total Applications
across all art units

Statute-Specific Performance

§101
12.5%
-27.5% vs TC avg
§103
59.8%
+19.8% vs TC avg
§102
22.6%
-17.4% vs TC avg
§112
5.1%
-34.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 22 resolved cases

Office Action

§102
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-5 are rejected under 35 U.S.C. 102(a) (1) as being anticipated by US20230322094 A1 to Nus (herein after “Nus”). Regrading claim 1, Nus teaches A battery electric vehicle (see Nus figure 4, para[0060] FIG. 4 schematically shows an example block diagram of an EV 400. Some aspects of the EV 400 are omitted for simplicity. The EV 400 can be used in combination with one or more other examples described elsewhere herein. The EV 400 includes an accelerator pedal 402 that a driver can depress or release so that it assumes any of a range of positions schematically indicated by an arrow 404 (e.g., the position represented as a percentage of a fully depressed position) including an electric motor as a drive source, the battery electric vehicle comprising one or more processors configured to control an output of the electric motor (See Nus para[0047] For example, the performance EV (graph 302) can have multiple electric motors (e.g., permanent-magnet motors) ) wherein the one or more processors are configured to, when the battery electric vehicle is in a proficiency mode, (See Nus emulation operation mode) acquire information on a target virtual vehicle selected from among a plurality of virtual vehicles, (See para[0004] a user selection of a first vehicle type from among multiple vehicle types each having an internal combustion engine,) control the output of the electric motor such that an acceleration characteristic of the battery electric vehicle with respect to a driving operation of a driver becomes a simulated acceleration characteristic (see Nus para[0023] When the driver selects an emulation operation mode, the EV can automatically and seamlessly simulate the powertrain of a selected ICE vehicle, based on driver inputs and state inputs of the EV. The EV can dynamically limit the torque output of its powertrain to match the ICE vehicle’s acceleration output according to a model) of the target virtual vehicle when the proficiency mode is initiated(See Nus emulation operation mode), and control the output of the electric motor such that the acceleration characteristic of the battery electric vehicle with respect to the driving operation of the driver is close to a standard acceleration characteristic, as proficiency of the driver increases. (See Nus para[0005] Providing the EV with the second acceleration comprises emulating an acceleration of the first vehicle type, applying the second input in emulating the first vehicle type comprises adjusting the second acceleration based on the second input. The second acceleration is based on a scaling of an acceleration capability of the first vehicle type. Para[0068] while the emulation operation mode is active and using a powertrain of the EV (e.g., the powertrain 424 in FIG. 4 ), with a second acceleration (e.g., corresponding to the output 422 in FIG. 4 ) determined based on the first vehicle type and the input. The second acceleration is capped by the first acceleration (e.g., using the emulation controller 420 in FIG. 4 ).) Regrading claim 2, Nus teaches further comprising: a driving operation member used for driving; (See Nus para[0006] the user selection made with regard to an emulation operation mode of the EV; an accelerator pedal to generate, with the first vehicle type chosen for the emulation operation mode, a first input made by a driver of the EV,) and one or more storage devices configured to manage a plurality of vehicle models that models the virtual vehicles, wherein the one or more processors are configured to (See Nus para[0106] the computing device 1200 also includes a system memory 1204, and a system bus 1206 that couples various system components including the system memory 1204 to the processing device 1202. ), when the battery electric vehicle is in the proficiency mode, acquire, from the one or more storage devices, a target vehicle model corresponding to the target virtual vehicle, (See Nus para[0026] For example, an over-the-air software update can be provided via a wireless communication channel to install the emulation operation mode, or to add one or more new emulation models to choose between. A specific type of ICE vehicle can be added to the emulation operation mode either as part of a group of emulation vehicle types, or individually (e.g., upon request).) calculate a first target drive force with which the standard acceleration characteristic is realized, (See Nus para[0062] The model 412 can calculate the emulation of the ICE vehicle in any of multiple different ways. The model 412 can take inputs such as accelerator pedal position gear selection, and reactive load, and output the calculated torque and resultant acceleration value.) calculate, based on an operation state of the driving operation member and a traveling state of the battery electric vehicle, using the target vehicle model, a second target drive force with which the simulated acceleration characteristic is realized, (See Nus para[0007] wherein the model adjusts the second acceleration based on the gearshift request. The model has inputs including acceleration pedal input, gearshift requests, and vehicle state, and wherein the model generates outputs including a longitudinal acceleration target, sound, and driver metrics. The second acceleration is capped by the first acceleration at least once. ) calculate a third target drive force that changes from the first target drive force to the second target drive force as the proficiency increases (See Nus para[0024] the emulated vehicle acceleration calculated by the model (e.g., a value measured in meters per square second (m/s2)), can be subjected to one or more comparisons., para[0054] At time T+1 second, the driver maintains full throttle and some of the characteristics increase numerically while the turbocharger accelerates and the EV defines an emulated acceleration target of +5 m/s2,para[0055] At time T+2 seconds, the driver maintains full throttle and some of the characteristics increase numerically while the turbocharger reaches full speed.) control the output of the electric motor to provide the battery electric vehicle with the third target drive force. (See Nus para[0022] the EV can provide an “emulation operation mode” where the EV selectively and dynamically reduces the torque output by its powertrain to simulate that of an ICE vehicle.) Regrading claim 3, Nus teaches wherein the one or more processors are configured to end the proficiency mode when a driving time or a traveling distance exceeds a predetermined value after the proficiency has been maximized. (see Nus para[0007] The second acceleration is capped by the first acceleration in response to a magnitude of the second acceleration exceeding a limit.). Regrading claim 4, Nus teaches wherein the one or more processors are configured to (See Nus para[0094] For example, the processing component 908 can include a vehicle control unit 910 that is implemented in form of one or more processors), when the battery electric vehicle is in the proficiency mode, increase the proficiency in proportion to a driving time or a traveling distance from a point at which the proficiency mode is initiated. (see Nus Scenario A, paras[0054]-[0057]). Regrading claim 5, Nus teaches wherein the one or more processors are configured to(See Nus para[0094] For example, the processing component 908 can include a vehicle control unit 910 that is implemented in form of one or more processors), when the battery electric vehicle is in the proficiency mode, decrease the proficiency when a condition that the driving operation of the driver indicates the driver is not accustomed to driving is satisfied (see Nus para[0028] When such legacy manufacturers contemplate adding EVs to their range of offerings, they sometimes have concerns that these loyal customers may not feel comfortable or familiar with the markedly different experience of driving an EV.,para[0024] That is, with the emulation operation mode being active the EV can filter torque demands via an onboard model to limit output torque to replicate the longitudinal acceleration of a particular ICE powertrain, and such torque output can be scaled to take into account (e.g., compensate for) differences in weight between the EV and the ICE vehicle.). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to NAZIA AFRIN whose telephone number is (703)756-1175. The examiner can normally be reached Monday-Friday 7:30-6. 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, Scott A Browne can be reached at 5712700151. 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. /NAZIA AFRIN/ Examiner, Art Unit 3666 /JESS WHITTINGTON/ Primary Examiner, Art Unit 3666c
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Prosecution Timeline

Jul 22, 2025
Application Filed
Aug 04, 2026
Non-Final Rejection mailed — §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
50%
Grant Probability
68%
With Interview (+18.3%)
3y 0m (~1y 11m remaining)
Median Time to Grant
Low
PTA Risk
Based on 22 resolved cases by this examiner. Grant probability derived from career allowance rate.

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