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 .
DETAILED ACTION
This communication is a Non-Final Office Action in response to communications received on 10/31/25.
Claims 1-20 are now pending and have been addressed below.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4/2/26 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The disclosure is objected to because of the following informalities: Drawing Fig 1 elements 101, 115, 125 not included in specification. Spec [0004] recites processing equipment, however Fig 1 element 101, 115, 125 are not included in [0025]. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
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: processing equipment configured to in claims 17-18.
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. Fig 1 # 101 processing equipment.
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 § 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 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (an abstract idea) without significantly more.
Step 1: Identifying Statutory Categories
In the instant case, claims 1-16 are directed to a method, claims 19-20 are directed to a non-transitory medium and claims 17-18 are directed to a system. Thus, the claims fall within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A: Prong 1 Identifying a Judicial Exception
Under Step 2A, prong 1, Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites an abstract idea without significantly more. Independent claims 1, 17 and 19 recite methods that generating, a travel diary for each user profile of a plurality of user profiles based on a plurality of travel patterns, drive cycle information of a vehicle type, and charging information to result in a plurality of travel diaries; generating a plurality of load histories corresponding to a vehicle component of the vehicle type based on the plurality of travel diaries; generating a distribution of a load parameter based on the plurality of load histories; and determining, vehicle information based on the distribution of the load parameter.
These limitations as drafted, are a process that, under its broadest reasonable interpretation, covers methods of organizing human activity (including commercial interactions such as business relations, managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) including interaction between person and computer), but for the recitation of generic computer components. That is, other than reciting the structural elements (such as using processing equipment, non-transitory medium), the claims are directed to determining vehicle information based on travel diary and load parameter. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of organizing human activity but for the recitation of generic computer components, the claim recites an abstract idea.
Step 2A Prong 2 - This judicial exception is not integrated into a practical application because the claim merely describes how to generally “apply” the concept of receiving data, analyzing it, and generating travel diary and load parameter. In particular, the claims only recites the additional element – using processing equipment, non-transitory medium. The additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component or merely uses a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). The claims are directed to an abstract idea. Simply implementing the abstract idea on generic components is not a practical application of the abstract idea. Accordingly, these additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims are directed to an abstract idea. When considered in combination, the claims do not amount to improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a), applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b), effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c), or applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they does not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
Step 2B: Considering Additional Elements
The claimed invention is directed to an abstract idea without significantly more. The claim does not include additional elements that are sufficient to amount significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claims describe how to generally “apply” to; determine vehicle information based on load parameter. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The independent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. The claims are not patent eligible. The dependent claim(s) when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail to establish that the claim(s) is/are not directed to an abstract idea. The dependent claims are not significantly more because they are part of the identified judicial exception. See MPEP 2106.05(g). The claims are not patent eligible. With respect to the processing equipment, non-transitory medium these limitations are described in Applicant’s own specification as generic and conventional elements. See Applicants specification, Paragraph [0004] details “The methods may be performed by processing equipment based on computer instructions stored in non-transitory computer-readable medium.” These are basic computer elements applied merely to carry out data processing such as, discussed above, receiving, analyzing, transmitting and displaying data, which fall under well-understood, routine and conventional functions of generic computers. Furthermore, the use of such generic computers to receive or transmit data over a network has been identified as a well understood, routine and conventional activity by the courts. See Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AVAuto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93, OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result-a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added)); Also see MPEP 2106.05(d) discussing elements that the courts have recognized as well-understood, routine and conventional activities in particular fields. Lastly, the additional elements provides only a result-oriented solution which lacks details as to how the computer performs the claimed abstract idea. Therefore, the additional elements amount to mere instructions to apply the exception. See MPEP 2106.05(f).
Furthermore, these steps/components are not explicitly recited and therefore must be construed at the highest level of generality and amount to mere instructions to implement the abstract idea on a computer. Therefore, the claimed invention does not demonstrate a technologically rooted solution to a computer-centric problem or recite an improvement to another technology or technical field, an improvement to the function of any computer itself, applying the exception with, or by use of, a particular machine, effect a transformation or reduction of a particular article to a different state or thing, add a specific limitation other than what is well-understood, routine and conventional in the field, add unconventional steps that confine the claim to a particular useful application, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment such as computing. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. Taking the additional claimed elements individually and in combination, the computer components at each step of the process perform purely generic computer functions. Viewed as a whole, the claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field. Use of an unspecified, generic computer does not transform an abstract idea into a patent-eligible invention. Thus, the claims do not amount to significantly more than the abstract idea itself.
Dependent claims 2-16, 18, and 20 add additional limitations, but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as Independent claims.
Claims 2-5 recite generating, based on the plurality of load histories, a design parameter for the vehicle component; generating, based on the plurality of load histories, a testing parameter for the vehicle component; generating, based on the plurality of load histories, a servicing parameter for the vehicle component; modifying, based on the plurality of load histories, at least one of (i) a design parameter of the vehicle component or (ii) a testing parameter of the vehicle component. These limitation further limit the abstract idea of independent claims and merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The claims do not provide any new additional elements beyond abstract idea. Therefore, whether analyzed individually or as an ordered combination, they fail to integrate the abstract idea into a practical application or provide significantly more than the abstract idea.
Claims 6-7 recite determining, based on the plurality of load histories, warranty information corresponding to the vehicle component, wherein the warranty information comprises a target warranty life of the vehicle type, and wherein each of the plurality of travel diaries spans the target warranty life; and generating a warranty notification based on the warranty information; determining, using the processing equipment, a remaining life of the vehicle component based on the plurality of load histories; and generating an indication of the remaining life at a user interface. These limitation further limit the abstract idea of independent claims and merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The additional element of user interface is recited at high level of generality and is generic computer interface. The claims do not provide any new additional elements beyond abstract idea. Therefore, whether analyzed individually or as an ordered combination, they fail to integrate the abstract idea into a practical application or provide significantly more than the abstract idea.
Claims 8-10 recite updating, in memory storage of a vehicle of the vehicle type, a threshold value corresponding to the plurality of load histories, receiving updated information corresponding to the vehicle component; and updating the plurality of load histories based on the updated information, generating a damage distribution based on the plurality of load histories and a damage model. These limitation further limit the abstract idea of independent claims and merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The additional elements of damage model, memory are recited at apply it level. The claims do not provide any new additional elements beyond abstract idea. Therefore, whether analyzed individually or as an ordered combination, they fail to integrate the abstract idea into a practical application or provide significantly more than the abstract idea.
Claims 11-14, 16 recites each travel diary comprises a respective plurality of trips, and wherein generating the plurality of load histories comprises applying a load model to each respective plurality of trips; determining the plurality of user profiles based on a plurality of predetermined user archetypes corresponding to a target customer base; generating the plurality of travel patterns based on a stochastic, multi-year model; wherein the plurality of user profiles is a first plurality of user profiles, the method further comprising: determining a second plurality of user profiles; and repeating generating the travel diary for each user profile and generating the plurality of load histories based on the second plurality of user profiles; identifying a subset of user profiles of the plurality of user profiles corresponding to an attribute, wherein a subset of travel diaries of the plurality of travel diaries correspond to the subset of user profiles; identifying a target stress corresponding to the vehicle component based on the subset of travel diaries; and determining at least one of a design parameter, a testing parameter, a service parameter, or a warranty parameter based on the target stress. These limitation further limit the abstract idea of independent claims and merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The claims do not provide any new additional elements beyond abstract idea. Therefore, whether analyzed individually or as an ordered combination, they fail to integrate the abstract idea into a practical application or provide significantly more than the abstract idea.
Claim 15, 18, 20 further narrow the abstract idea by adding generating a travel pattern for each user profile to result in the plurality of travel patterns corresponding to the vehicle type; generating a drive history for each user profile based on the plurality of travel patterns and based on the drive cycle information to result in a plurality of drive histories; and generating the charging information based on the travel pattern and the drive history for each user profile. These limitation further limit the abstract idea of independent claims and merely adds the words apply it (or an equivalent) with the judicial exception , or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea as discussed in MPEP 2106.05(f). The claims do not provide any new additional elements beyond abstract idea. Therefore, whether analyzed individually or as an ordered combination, they fail to integrate the abstract idea into a practical application or provide significantly more than the abstract idea.
The dependent claims do not integrate into a practical application. As such, the additional elements individually or in combination do not integrate the exception into a practical application, but rather, the recitation of any additional element amounts to merely reciting the words “apply it” (or equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (See MPEP 2106.05(f)). The dependent claims also do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are merely used to apply the abstract idea to a technological environment. These limitations do not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. See MPEP 2106.05d. Thus, the claims do not add significantly more to an abstract idea. The claims are ineligible. Therefore, since there are no limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself, the claims are rejected under 35 USC 101 as being directed to non-statutory subject matter. See (Alice Corporation Pty. Ltd. v. CLS Bank International, et al.).
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.
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, 3-4, 8-20 are rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire et al. (US 2026/0116411 A1) n view of Sandmann (CN117501086 A1)
Regarding Claims 1, 17 and 19, Beaurepaire discloses the method comprising:
Beaurepaire discloses generating, using processing equipment, a travel diary for each user profile of a plurality of user profiles based on a plurality of travel patterns, drive cycle information of a vehicle type, and charging information to result in a plurality of travel diaries (Fig 2 # 204A user profile data 204B historical usage information, [0007] The user profile data may further include charging information associated with one or more historical charging sessions of the electric vehicle. [0008] the charging information associated with the one or more historical charging sessions of the electric vehicle may include timestamp information associated with each charging session of the one or more historical charging sessions, location information associated with each charging session of the one or more historical charging sessions, cost information associated with each charging session [0009] the historical usage information of the vehicle may include timestamp information associated with each driving session of the one or more historical driving sessions, route information associated with each driving session of the one or more historical driving sessions, speed information associated with the vehicle during each driving session of the one or more historical driving sessions, vehicle information associated with the vehicle (drive cycle of a vehicle type), [0071] The user profile data includes historical usage information of the vehicle 104 during one or more historical driving sessions (travel diaries) by the user 104A. The historical usage information of the vehicle 104 may refer to data associated with the historical usage pattern of the vehicle 104 during a past driving session by the user 104A.);
Beaurepaire discloses generating a plurality of load histories corresponding to a vehicle component of the vehicle type based on the plurality of travel diaries ([0008] the charging information associated with the one or more historical charging sessions of the electric vehicle may include timestamp information associated with each charging session of the one or more historical charging sessions, location information associated with each charging session of the one or more historical charging sessions, cost information associated with each charging session [0014] the deviation in the usage of the vehicle during the first driving session is determined based on one of a modification in vehicle health information associated with the vehicle, a modification in charge information associated with the vehicle, a modification in speed information associated with the vehicle, a modification in route information associated with the first driving session [0071] usage information includes speed information associated with the vehicle during each driving session of the one or more historical driving sessions, vehicle information associated with the vehicle 104, or a combination thereof. Such historical usage information of the vehicle 104 may be employed to determine mobility patterns (load histories) associated with the usage of vehicle 104. [0096] The battery Management System may include suitable logic, circuitry, and/or interfaces that may be configured to analyze battery metering data (load history) to determine available charging. [0099] For example, for a given activity, the charging levels of the vehicle 104 (component) may be monitored and stored in the map database 108B or the database 316. For example, when the user 104A goes to the gym on a Tuesday night, the electric vehicle charging level is usually between 65%-70%. Further, the mobility pattern or usage information (such as speed, number of people in the vehicle 104, driving style, and the like) may be stored, for each route segment, over the database 316.);
Beaurepaire discloses determining, using the processing equipment, vehicle information ([0074] Based on the user profile data, and the first contextual information, the apparatus 102 may be configured to determine a deviation associated with a usage of the vehicle 104. The deviation in the usage of the vehicle 104 during the first driving session may be determined based on one of a modification in vehicle health information associated with the vehicle 104, a modification in charge information associated with the vehicle 104, a modification in speed information associated with the vehicle 104,)
Beaurepaire does not specifically teach generating a distribution of a load parameter based on the plurality of load histories; determining, using the processing equipment, vehicle information based on the distribution of the load parameter
Sandmann teaches travel diary (Page 8 Fig 4 #402 The travel diary 402 includes a plurality of user-travel combinations. The first user-travel combination 404 and the last user-travel combination 406 of the plurality of user-travel combinations are shown in Figure 4. In this example, travel is identified by the following characteristics: the working day of driving, the starting time of driving, the geographical area of driving, the duration of driving and the distance of driving. ); generating a distribution of a load parameter based on the plurality of load histories (Page 2 para 7-8 The degree of damage, in particular the degree of fatigue, of the at least one component is preferably determined from a set of output parameters containing the output parameters. Such stress or more generally damaging mechanisms may, in particular, include wear, corrosion, or generally fatigue and statistical failure. Selecting the subset comprises: selecting an input parameter defining a route and an input parameter defining a driver configuration file, and wherein the input parameter defining the route is selected from a plurality of input parameters defining different routes, wherein the input parameter defining the driver configuration file is selected from a plurality of input parameters defining different driver configuration files. This makes it possible to simulate a large number of different travel cycles to determine stress and load (distribution of load parameter) Page 3 para 2 determining the degree of damage, comprises: An operator, in particular a driver or a user of the machine, is selected in a machine-specific statistical table or a machine-specific log (load histories), a plurality of output parameters in the set of output parameters are determined for the operator, and the degree of damage is preferably determined using the plurality of output parameters. Determining the degree of damage, comprises: The machine-specific statistics are selected from a set of machine-specific statistics. Thus, a machine-specific weight is provided. Page 5 the distribution is derived from changes in driver behaviour and route. Additionally, the distribution may be determined for changes in the use of the machine. A non-exhaustive list of examples of damage, in particular fatigue, is the damage of components, in particular fatigue, Page 6 In step 206, the subset is mapped to the output parameter of the model by the model, the output parameter representing the stress caused by the load factor in the case of at least one component of the machine. Different subsets are mapped to different output parameters by the model. The set of output parameters of the model includes a plurality of output parameters that characterize stresses caused by load factors in different circumstances in at least one component of the machine. In step 208, the degree of fatigue of at least one component is determined from the set of output parameters), determining, using the processing equipment, vehicle information based on the distribution of the load parameter (Page 2 para 7The degree of damage, in particular the degree of fatigue, of the at least one component is preferably determined from a set of output parameters containing the output parameters. Such stress or more generally damaging mechanisms may, in particular, include wear, corrosion, or generally fatigue and statistical failure. The extent of damage should, in particular, be understood as the extent of damage to the components or machine, in particular with adverse effects on functionality, caused by stress or by a damage mechanism. Page 5 para 5 The analyzer 106 is configured to determine damage, in particular fatigue, of the machine or components of the machine from the distribution of stress or the time-varying process. The analyzer 106 is configured to determine damage, in particular fatigue, based on an analysis of a count, such as rain flow count, linear damage accumulation, high cycle damage).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating a distribution of a load parameter based on the plurality of load histories; determining, using the processing equipment, vehicle information based on the distribution of the load parameter, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Claim 17, Beaurepaire discloses the system comprising: processing equipment configured to ([0078] The processor 202 of the apparatus 102 may be configured to determine deviation in vehicle driving behavior and generate recommendations associated with a modification in the driving range of the vehicle 104 and further output the generated recommendation.
Claim 19, Beaurepaire discloses the non-transitory computer-readable medium ([0085] The memory 204 may be non-transitory and may include, for example, one or more volatile and/or non-volatile memories ) having instructions encoded thereon that when executed by processing equipment cause the processing equipment to
Regarding Claim 3. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire does not specifically teach generating, based on the plurality of load histories, a testing parameter for the vehicle component.
Sandmann teaches generating, based on the plurality of load histories, a testing parameter for the vehicle component.( Page 4 para 5 the first portion 108 may be configured to simulate a machine or component thereof. In this example, the second portion 110 may be configured to simulate the stress (testing parameter) of the machine or components of the machine. The simulation model determines the acceleration from the speed curve, and determines the stress of the powertrain based on the speed, the acceleration, and the gradient of the route. Page 6 para 9 the output parameter representing the stress caused by the load factor in the case of at least one component of the machine. Different subsets are mapped to different output parameters by the model. The set of output parameters of the model includes a plurality of output parameters (testing parameters) that characterize stresses caused by load factors in different circumstances in at least one component of the machine.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating, based on the plurality of load histories, a testing parameter for the vehicle component, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 4. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire teaches generating, a servicing for the vehicle component. ([0096] provide on-board diagnostics data associated with the vehicle 104. The on-board diagnostics data may include but not be limited to engine load parameters, rotation per minute data, vehicle break data, and information related to service time and wear and tear associated with vehicle 104. The Tire Pressure Monitoring System may include suitable logic, circuitry, and/or interfaces that may be configured to analyze air metering data to determine tire pressure. The Battery Management System may include suitable logic, circuitry, and/or interfaces that may be configured to analyze battery metering data to determine available charging.).
Beaurepaire does not specifically teach generating, based on the plurality of load histories, a servicing parameter for the vehicle component
Sandmann teaches generating, based on the plurality of load histories, a servicing parameter for the vehicle component ( Page 5 para 5 the distribution is derived from changes in driver behaviour and route. Additionally, the distribution may be determined for changes in the use of the machine. A non-exhaustive list of examples of damage, in particular fatigue, is the damage of components, in particular fatigue, caused by pressure changes in the fuel injection system of the engine (service parameter). The analyzer 106 may be configured to determine a combination of input parameters that cause higher damage, particularly fatigue, than other combinations. For example, a key combination is determined by detecting a distribution that is located in a predetermined percentile as compared to other distributions resulting from the change.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating, based on the plurality of load histories, a servicing parameter for the vehicle component, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 8. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire does not specifically teach updating, in memory storage of a vehicle of the vehicle type, a threshold value corresponding to the plurality of load histories.
Sandmann teaches updating, in memory storage of a vehicle of the vehicle type, a threshold value corresponding to the plurality of load histories. (Page 2 para 2-4 testing a machine having a plurality of components or for testing a component of a machine, in particular a computer-implemented method, comprises: providing a set of input parameters for the model, wherein the set of input parameters represents a load factor at the machine (Belastungsfaktoren) or a load factor at least one component of the machine, selecting a subset of the set, The subset is mapped to an output parameter of the model by the model, the output parameter characterizing the stress caused by the load factor (threshold value) in the case of at least one component of the machine. This enables the specific stress of the component to be determined significantly and more efficiently, and is evaluated based on the stress distribution derived from a plurality of (e.g., tens of thousands) different stress scenes or test repeats with the same stress scene. Deriving functional loads (updating threshold value) for evaluating and optimizing machine or component behaviour, in particular evaluating and/or adapting/optimizing operating strategies Page 4 para 7 determine the load of the components of powertrain of the vehicle when the speed curve is applied Page 5 para 4 determine distribution of stress by changes to input in model))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included updating, in memory storage of a vehicle of the vehicle type, a threshold value corresponding to the plurality of load histories, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of deriving functional loads for evaluating and optimizing machine or component behaviour, in particular evaluating and/or adapting/optimizing operating strategies (page 2 para 2)and determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 9. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising:
Beaurepaire teaches receiving updated information corresponding to the vehicle ([0053] the vehicle 104 may generate the sensor data in real-time and transmit it to the apparatus 102 to determine the deviation. In certain cases, the vehicle 104 may be configured to send updated sensor data periodically, for example, every five seconds, every thirty seconds, every minute, and so forth.);
Beaurepaire does not specifically teach receiving updated information corresponding to the vehicle component and updating the plurality of load histories based on the updated information.
Sandmann teaches receiving updated information corresponding to the vehicle component (Page 4 para 8 Page 5 para 1 the simulation model determines the acceleration from the speed curve, and determines the stress of the powertrain based on the speed, the acceleration, and the gradient of the route. Page 5 para 4 determine distribution of stress by changes to input in model) and updating the plurality of load histories based on the updated information (page 5 para 4 The analyzer 106 may be configured to determine the distribution of stress by changes to the input in the model 104. The analyzer 106 may be configured to determine the distribution of the process of change of the stress by the change of the input. Page 3 para 15 The database 102 contains a set of input parameters for the model 104. The input parameter is indicative of a load factor at the machine or a load factor at least one component of the machine. The database 102 contains a plurality of input parameters defining different routes and different driver profiles. The database may include input parameters defining different environmental conditions. )
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included receiving updated information corresponding to the vehicle component and updating the plurality of load histories based on the updated information, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 10. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire does not specifically teach generating a damage distribution based on the plurality of load histories and a damage model.
Sandmann teaches generating a damage distribution based on the plurality of load histories and a damage model. (Page 9 para 1The analyzer 106 includes a damage model. The damage model is designed for deriving the centrifugal force from the turbine speed. In this example, the damage model is designed to perform a rain flow count for the time resolved turbine speed at a predetermined resolution and based on the Walker curve.) calculating damage accumulation. The output of the damage model is an output parameter representative of the damage accumulation Page 5 para 2-4 the simulation model determines the acceleration from the speed curve, and determines the stress of the powertrain based on the speed, the acceleration, and the gradient of the route. The analyzer 106 is configured to determine the degree of fatigue of at least one component based on the set of output parameters. The analyzer 106 may be configured to determine a time-varying process of stress. Page 5 para 10 The device 100 is configured to select a plurality of different subsets to be mapped and determine a distribution of stress or damage, in particular fatigue, as determined from the output parameters resulting from mapping the different subsets.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating a damage distribution based on the plurality of load histories and a damage model., as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 11. Beaurepaire as modified by Sandmann teaches the method of claim 1,
Beaurepaire teaches wherein each travel diary comprises a respective plurality of trips ([0094] the user profile data 204A may include the historical usage information 204B of the vehicle 104 during one or more historical driving sessions by the user 104A. timestamp information associated with each driving session of the one or more historical driving sessions, route information associated with each driving session of the one or more historical driving sessions, weather information associated with a location of the vehicle or a route traversed by the vehicle during each driving session of the one or more historical driving sessions [0098] the historical usage information 204B for a given duration such as for the past 6 months may be employed to determine the vehicle driving behavior of the user 104A.), and wherein generating the plurality of load histories comprises each respective plurality of trips. ([0098] the historical usage information 204B for a given duration such as for the past 6 months may be employed to determine the vehicle driving behavior of the user 104A.Further, based on the user profile data 204A, the processor 202 may be configured to determine the mobility and charge patterns, one or more activities performed by the user 104A while the vehicle 104 is being charged, and the like. [0101] a deviation associated with the usage of vehicle may be determined))
Beaurepaire does not specifically teach applying a load model
Sandmann teaches generating the plurality of load histories comprises applying a load model to each respective plurality of trips (Page 2 para 7The analyzer 106 is configured to determine damage, in particular fatigue, of the machine or components of the machine from the distribution of stress or the time-varying process. The analyzer 106 is configured to determine damage, in particular fatigue, based on an analysis of a count, such as rain flow count, linear damage accumulation, high cycle damage, in particular high cycle fatigue or low cycle damage, in particular low cycle fatigue. Such stresses may, in particular, include wear, corrosion, or generally fatigue and statistical failure. Page 6 para 2Testing a machine having a plurality of components or for testing a component of the machine. The model 104 (load model) and analyzer 106 are designed to model and analyze the machine or components of the machine. The model 104 represents a load factor at the machine or a load factor at least one component of the machine.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating the plurality of load histories comprises applying a load model to each respective plurality of trips., as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Regarding Claim 12. The method claim 1, further comprising
Beaurepaire teaches determining the plurality of user profiles based on a plurality of predetermined user archetypes corresponding to a target customer base. ([0099] The weekday user profile may include data associated with driving from the office to home and vice-versa, whereas the weekend user profile may include data associated with driving to the gym or other leisure activities. Further, the processor 202 may utilize the user profile data 204A to generate multiple profiles of the user (such as highway versus city, weekday versus weekends, and the like).
Sandmann also teaches user profiles based on a plurality of predetermined user archetypes corresponding to a target customer base (Page 8 para 6 The first input 302 and the second input 304 are mapped to road type specific results for the plurality of driver profiles using the model 104. Figure 3 shows road type specific results 318-1,318-2, 318-3 for the first driver profile 318 and road type specific results 320-1, 320-2, 320-3 for the last driver profile 320 for the plurality of driver profiles. Driver profile-vehicle combination)
Regarding Claim 13. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire teaches generating the plurality of travel patterns based on a stochastic, multi-year model. ([0098] the processor 202 may be configured to employ the user profile data 204A to establish a usage pattern of the vehicle 104 by the user 104A. Such usage patterns may act as a baseline for a personal setting associated with the driving range, thereby making a user centric prediction for the electric vehicle range in contrast to the existing technological based forecast. For an example, the historical usage information 204B for a given duration such as for the past 6 months may be employed to determine the vehicle driving behavior of the user 104A. [0099])
Regarding Claim 14. Beaurepaire as modified by Sandmann teaches the method of claim 1,
Beaurepaire teaches wherein the plurality of user profiles is a first plurality of user profiles (Fig 2 # 204A user profile data, [0018] retrieving user profile data associated with the user of the vehicle. The user profile data includes historical usage information of the vehicle during one or more historical driving sessions by the user. ), the method further comprising: determining a second plurality of user profiles (Fig 2 # 204A user profile data, [0018] retrieving user profile data associated with the user of the vehicle. The user profile data includes historical usage information of the vehicle during one or more historical driving sessions by the user.); and repeating generating the travel diary for each user profile ([0018] The user profile data includes historical usage information of the vehicle during one or more historical driving sessions by the user. The method further includes steps of obtaining contextual information associated with a first driving session by the user, [0058] store the sensor data and map data, which may be collected from the vehicle 104 traveling on the road.) and generating the plurality of load histories based on the second plurality of user profiles.([0096] The on-board diagnostics data may include but not be limited to engine load parameters, rotation per minute data, vehicle break data, and information related to service time and wear and tear associated with vehicle 104. The Tire Pressure Monitoring System may include suitable logic, circuitry, and/or interfaces that may be configured to analyze air metering data to determine tire pressure. )
Regarding Claims 15, 18 and 20. Beaurepaire as modified by Sandmann teaches the method of claim 1,
Beaurepaire teaches wherein generating the travel diary for each user profile of the plurality of user profiles comprises: generating a travel pattern for each user profile to result in the plurality of travel patterns corresponding to the vehicle type ([0071] The user profile data includes historical usage information of the vehicle 104 during one or more historical driving sessions by the user 104A. The historical usage information of the vehicle 104 may refer to data associated with the historical usage pattern of the vehicle 104 during a past driving session by the user 104A. Such historical usage information of the vehicle 104 may include timestamp information associated with each driving session of the one or more historical driving sessions. Such historical usage information of the vehicle 104 may be employed to determine mobility patterns associated with the usage of vehicle 104, [0074] Based on the user profile data, and the first contextual information, the apparatus 102 may be configured to determine a deviation associated with a usage of the vehicle 104. The deviation in the usage of the vehicle 104 during the first driving session may be determined based on one of a modification in vehicle health information associated with the vehicle 104, a modification in charge information associated with the vehicle 104, a modification in speed information associated with the vehicle 104, a modification in route information associated with the first driving session);
generating a drive history for each user profile based on the plurality of travel patterns and based on the drive cycle information to result in a plurality of drive histories ([0123] The user profile data 204A comprises historical usage information 204B of the vehicle 104 during one or more historical driving sessions by the user 104A (drive history). The historical usage information 204B of the vehicle 104 may include, but is not limited to, timestamp information associated with each driving session of the one or more historical driving sessions, route information associated with each driving session of the one or more historical driving sessions, weather information associated with a location of the vehicle 104 or a route to be traversed by the vehicle 104 during each driving session of the one or more historical driving sessions); and
generating the charging information based on the travel pattern and the drive history for each user profile ([0124] The user profile data 204A may further include the historical charging information 204C associated with one or more historical charging sessions of the electric vehicle. The historical charging information 204C associated with the one or more historical charging sessions of the electric vehicle may include, but not limited to, timestamp information associated with each charging session of the one or more historical charging sessions, location information associated with each charging session of the one or more historical charging sessions, cost information associated with each charging session of the one or more historical charging sessions ).
Regarding Claim 16. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising:
Beaurepaire does not specifically teach identifying a subset of user profiles of the plurality of user profiles corresponding to an attribute, wherein a subset of travel diaries of the plurality of travel diaries correspond to the subset of user profiles; identifying a target stress corresponding to the vehicle component based on the subset of travel diaries determining at least one of a design parameter, a testing parameter, a service parameter, or a warranty parameter based on the target stress
Sandmann teaches identifying a subset of user profiles of the plurality of user profiles corresponding to an attribute (Page 6 para 6 An input parameter defining a driver profile is selected from a plurality of input parameters defining different driver profiles, wherein a subset of travel diaries of the plurality of travel diaries correspond to the subset of user profiles (Page 6 para 15The database 102 may contain a mapping of characteristics to a plurality of input parameters defining different routes or different driver profiles. Characteristics may be available from the metadata assigned to the input parameter.); identifying a target stress corresponding to the vehicle component based on the subset of travel diaries (Page 2 para 7The analyzer 106 is configured to determine damage, in particular fatigue, of the machine or components of the machine from the distribution of stress or the time-varying process. The analyzer 106 is configured to determine damage, in particular fatigue, based on an analysis of a count, such as rain flow count, linear damage accumulation, high cycle damage, in particular high cycle fatigue or low cycle damage, in particular low cycle fatigue. Such stresses may, in particular, include wear, corrosion, or generally fatigue and statistical failure Page 6 para 2 testing a machine having a plurality of components or for testing a component of the machine. The model 104 and analyzer 106 are designed to model and analyze the machine or components of the machine. The model 104 represents a load factor at the machine or a load factor at least one component of the machine.); and determining at least one of a design parameter, a testing parameter, a service parameter, or a warranty parameter based on the target stress. (Page 6 para 15-17, page 7 para 1-2The telemetry data can define the time change process of the input parameter. In one example, a set of output parameters for n different operators includes a mapping to a total degree of fatigue D; Operator 1: D 1 Operator n: Dn In step 208, the degree of fatigue of at least one component is determined from the set of output parameters. Page 7The machine-specific log may contain a plurality of maps of operator-to-run characteristics. The machine-specific log may be a travel diary in which different operators are mapped to corresponding operating characteristics. The travel diary for n operators, m travel and o types of characteristics may include the following characteristics P (testing parameters))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included identifying a subset of user profiles of the plurality of user profiles corresponding to an attribute, wherein a subset of travel diaries of the plurality of travel diaries correspond to the subset of user profiles; identifying a target stress corresponding to the vehicle component based on the subset of travel diaries determining at least one of a design parameter, a testing parameter, a service parameter, or a warranty parameter based on the target stress, as disclosed by Sandmann in the system disclosed by Beaurepaire, for the motivation of providing a method of determining damage of the machine or components of machine from the distribution of stress (Page 5 para 5 Sandmann).
Claims 2, 5 are rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire et al. (US 2026/0116411 A1) n view of Sandmann (CN117501086 A1) as applied to claim 1, further in view of Oswald (CN10916337 A1)
Regarding Claim 2. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire does not specifically teach generating, based on the plurality of load histories, a design parameter for the vehicle component.
Oswald teaches generating, based on the plurality of load histories, a design parameter for the vehicle component.(Page 11 para 11determining the running state parameter, the one or more values defining the at least one variable is simulated and/or at least one manipulated variable and is adapted to at least one running state characteristic of the motor vehicle, especially the driving state, and wherein the at least one of the simulated values of the variables with the corresponding running state parameter related output. Design proposal of the method based on the sub-model of function having at least one function parameter, through which changes can change the running of simulation vehicle operation changes.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included generating, based on the plurality of load histories, a testing parameter for the vehicle component, as disclosed by Oswald in the system disclosed by Beaurepaire, for the motivation of providing a method of performing simulation based on analysis and/or optimization of motor vehicle (abstract Oswald)
Regarding Claim 5. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising
Beaurepaire does not specifically teach modifying, based on the plurality of load histories, at least one of (i) a design parameter of the vehicle component or (ii) a testing parameter of the vehicle component.
Oswald teaches modifying, based on the plurality of load histories, at least one of (i) a design parameter of the vehicle component or (ii) a testing parameter of the vehicle component. (Page 12 para 9 if the value is the simulation of at least one variable or at least one evaluation parameter value is outside the desired range of values, then change the at least one sub-model (modify) based on the comparison for at least one function parameter (design/testing parameter) of the function of the simulation)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included modifying, based on the plurality of load histories, at least one of (i) a design parameter of the vehicle component or (ii) a testing parameter of the vehicle component, as disclosed by Oswald in the system disclosed by Beaurepaire, for the motivation of providing a method of performing simulation based on analysis and/or optimization of motor vehicle (abstract Oswald)
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire et al. (US 2026/0116411 A1) n view of Sandmann (CN117501086 A1) as applied to claim 1, further in view of Ricci (US 2019/0279447 A1)
Regarding Claim 6. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising:
Beaurepaire does not specifically teach determining, based on the plurality of load histories, warranty information corresponding to the vehicle component, wherein the warranty information comprises a target warranty life of the vehicle type, and wherein each of the plurality of travel diaries spans the target warranty life; and generating a warranty notification based on the warranty information.
Ricci teaches determining, based on the plurality of load histories, warranty information corresponding to the vehicle component ([0435] Warranty data 2408 contains data associated with a particular user 216 and mapped to a particular vehicle 104 regarding, for example, the level of compliance agreed upon between Warranty provider 2414 and user 216 for that particular vehicle 104. Warranty is defined as a guarantee or promise that if the user (e.g. car driver, the “obligee”) meets certain requirements, the other party (the “obligor”) will provide something of value. For example, the Warranty data 2408 may contain terms and conditions of the original vehicle manufacturer as to replacement or repair of defective vehicle components. Terms and conditions may include a restriction as to owner (i.e. a particular item may only be covered if the vehicle is owned by the original purchaser), vehicle mileage, or not exceeded a maximum RPM and/or speed., [0444] the health status 1278 may include any type of information related to a state of the systems to include the warrant compliance data and maintenance data discussed. For instance, an operational condition, manufacturing date, update status, revision information, time in operation, fault status, state of damage detected) , wherein the warranty information comprises a target warranty life of the vehicle type, and wherein each of the plurality of travel diaries spans the target warranty life; and generating a warranty notification based on the warranty information ([0445] The warnings data 1286 may include warning generated by the vehicle 104 (e.g. “oil change required within next 500 miles”), systems of the vehicle 104 (e.g. “brake pads now at 80% wear”), manufacturer of the vehicle, federal agency, third party, and/or a user associated with the vehicle. [0437] The historical user compliance data 2412 maintains data associated with a particular user 216 as to their compliance with maintenance data items and/or warranty data items. For example, the dates of tune-ups and identification of entity who performed the tune-up are stored. The historical user compliance data 2412 may categorize data according to specific vehicle 104.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included determining, based on the plurality of load histories, warranty information corresponding to the vehicle component, wherein the warranty information comprises a target warranty life of the vehicle type, and wherein each of the plurality of travel diaries spans the target warranty life; and generating a warranty notification based on the warranty information, as disclosed by Ricci in the system disclosed by Beaurepaire/Sandmann, for the motivation of providing a method of monitor the health of vehicle systems and subsystems and diagnose detected anomalies is provided. In the event an anomaly or unhealthy state is detected within a vehicle, subsystem or component, the system may take a number of actions.(abstract Ricci) and maintaining data associated with a particular user 216 as to their compliance with maintenance data items and/or warranty data items ([0437] Ricci)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire et al. (US 2026/0116411 A1) n view of Sandmann (CN117501086 A1) as applied to claim 1, further in view of Sharma (US 2025/0296580 A1)
Regarding Claim 7. Beaurepaire as modified by Sandmann teaches the method of claim 1, further comprising:
Beaurepaire does not specifically teach determining, using the processing equipment, a remaining life of the vehicle component based on the plurality of load histories; and generating an indication of the remaining life at a user interface.
Sharma teaches determining, using the processing equipment, a remaining life of the vehicle component based on the plurality of load histories ([0036] The system includes monitoring a vehicle health that supports accurate battery state of charge (SoC), state of health (SoH)/remaining useful life (RUL) calculations of batteries. [0049] The transmitted data (load histories) to the cloud storage may generate key performance indicators (KPIs) and dashboards, thereby providing insights into the electric vehicle's 110 battery's health, performance, and operational status. The SoH may be expressed in terms of percentage. The SOH may provide insights of the battery's life expectancy and potential replacement dates.); and generating an indication of the remaining life at a user interface. ([0092]dashboards may include visualizations (such as line charts, gauges, and color-coded alerts) and insights (such as, detecting of abnormal degradation patterns, identifying potential thermal runaway risks, and predicting remaining battery lifespan)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included determining, using the processing equipment, a remaining life of the vehicle component based on the plurality of load histories; and generating an indication of the remaining life at a user interface., as disclosed by Sharma in the system disclosed by Beaurepaire/Sandmann, for the motivation of providing a method of monitoring a vehicle health that supports accurate battery state of charge (SoC), state of health (SoH)/remaining useful life (RUL) calculations of batteries ([0036] Sharma) and determining abnormality associated with the electric vehicle, followed by determining action for rectifying the abnormality.(Abstract Sharma)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Li (CN121901518A1) discloses a processing method and device of vehicle travel information, which can be used in the technical field of intelligent driving. The method comprises: displaying the history travel report in the form of list according to the pre-set format in the history travel general view interface.
Switkes (US 12,181,873) teaches generating a distribution of a load parameter based on the plurality of load histories (Col 7 lines 38-46 Historical data 192 can refer to collected historical data, estimated historical data, extrapolated data, forecast data, estimated data, predicted data, or the like. As used herein, instead of, in addition to, or included with historical data 192, forecast data (e.g., forecast traffic, forecast wind, forecast recommended lane, etc.), and the like can be used to generate mass distribution data 196, Col 8 lines 4-16 The mass distribution data 196 may include one or more of mass values associated with different distal ends of one or more axles, weight values associated with different distal ends of one or more axles, pressure values associated with different distal ends of one or more axles), determining, using the processing equipment, vehicle information based on the distribution of the load parameter (Col 3 lines 57-62 The processing device causes, based on the mass distribution data, performance of a corrective action associated with the AV. A corrective action may be a main action (e.g., no first action to be corrected) or a corrective action may be a subsequent action (e.g., one or more first actions to be corrected). A corrective action may be referred to as an action, a driving action, a planning action, a routing action, a motion control action, and/or the like. Col 4 lines 35-42 autonomous vehicles can include any motor vehicles, such as cars, tractors (with or without trailers), buses, motorcycles, all-terrain vehicles, recreational vehicles, any specialized farming or construction vehicles, and the like), or any other self-propelled vehicles capable of being operated in a self-driving mode (without a human input or with a reduced human input).
Muller (DE102008047958) discloses a method for stress-dependent design a component or a component combination
Sivalingam (US 2018/0122165) discloses creating a user profile for vehicle and generating data regarding condition of components
CN117439078 discloses an ultra-short term prediction method of charging load in electric automobile area considering user action, comprising obtaining EV travel history data of electric automobile in the area to be predicted, then establishing a neural network and performing training
JP7539869B2 discloses generating a user profile indicating attribute information such as the user's age based on the user's location history obtained via a mobile phone or the like.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANGEETA BAHL whose telephone number is (571)270-7779. The examiner can normally be reached 7:30 - 4PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at 571-270-3445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SANGEETA BAHL/Primary Examiner, Art Unit 3626
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