CN115923690A - Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle - Google Patents
Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle Download PDFInfo
- Publication number
- CN115923690A CN115923690A CN202211463864.8A CN202211463864A CN115923690A CN 115923690 A CN115923690 A CN 115923690A CN 202211463864 A CN202211463864 A CN 202211463864A CN 115923690 A CN115923690 A CN 115923690A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- abnormal
- analyzed
- awakening
- state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Abstract
The invention discloses a method, a device, equipment and a medium for analyzing abnormal sleeping and awakening of a vehicle, wherein the method comprises the following steps: acquiring vehicle operation data of a vehicle to be analyzed; performing abnormal dormancy identification or abnormal awakening identification on the vehicle running data according to a preset identification strategy, and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state; acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period; and according to the online characterization signal, performing awakening source identification on the vehicle to be analyzed, and determining at least one awakening source of the vehicle to be analyzed. The invention can analyze the awakening source of the abnormal dormancy or abnormal awakening condition according to the on-line characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the running time period of the abnormal dormancy or abnormal awakening state.
Description
Technical Field
The present invention relates to the field of vehicle technologies, and in particular, to a method and an apparatus for analyzing abnormal hibernation and wake-up of a vehicle, a terminal device, and a computer-readable storage medium.
Background
In the running process of the electric automobile, due to the fact that a vehicle key frequently approaches a vehicle, a vehicle-mounted network is abnormal, a vehicle door is locked abnormally, and the like, the individual controller in the vehicle cannot sleep and is frequently wakened, and therefore the vehicle is abnormally sleeped and wakened, wherein the abnormal sleeping condition means that the vehicle cannot sleep when the use requirement does not exist, and the abnormal wakening condition means that the vehicle is frequently wakened when the use requirement does not exist. When the abnormal sleeping or abnormal waking of the vehicle occurs, the power consumption of the vehicle in the standing state will increase rapidly, so that it is necessary to analyze the cause of the abnormal sleeping or waking in order to avoid the abnormal sleeping or waking of the vehicle again.
The prior art can only detect the abnormal dormancy and the abnormal wake-up condition, but cannot analyze the wake-up source aiming at the abnormal dormancy and the abnormal wake-up condition.
Disclosure of Invention
The invention provides a method, a device, equipment and a medium for analyzing abnormal dormancy and awakening of a vehicle, which are used for solving the technical problem that the awakening source analysis cannot be carried out aiming at the abnormal dormancy and awakening conditions in the prior art, and can carry out the awakening source analysis on the abnormal dormancy or abnormal awakening conditions according to online characterization signals corresponding to each communication network segment or a controller of the vehicle to be analyzed in the abnormal dormancy state or the abnormal awakening state within the running time period.
In order to solve the above technical problem, a first aspect of an embodiment of the present invention provides a method for analyzing abnormal sleeping and waking of a vehicle, including the following steps:
acquiring vehicle operation data of a vehicle to be analyzed;
performing abnormal dormancy identification or abnormal awakening identification on the vehicle running data according to a preset identification strategy, and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state;
acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period;
and according to the online characterization signal, performing awakening source identification on the vehicle to be analyzed, and determining at least one awakening source of the vehicle to be analyzed.
As a preferred scheme, the identifying the awakening source of the vehicle to be analyzed according to the online characterization signal, and determining at least one awakening source of the vehicle to be analyzed specifically includes the following steps:
determining a plurality of online communication network segments and online controllers in an awakening state according to the online characterization signals;
and determining at least one common awakening source of all online communication network segments and online controllers based on preset awakening relations between the communication network segments and the awakening sources and awakening relations between the controllers and the awakening sources, and taking the common awakening source as the awakening source of the vehicle to be analyzed.
Preferably, the method further comprises the following steps:
when an online characterization signal corresponding to any one awakening source of the vehicle to be analyzed in the operation time period is received, selecting the common awakening source according to the online characterization signal corresponding to any one awakening source, and taking the selected common awakening source as the awakening source of the vehicle to be analyzed.
As a preferred scheme, the method specifically performs abnormal dormancy identification on the vehicle to be analyzed through the following steps, and determines the running time period of the vehicle to be analyzed in an abnormal dormancy state:
determining the current online time and the normal operation time of the vehicle to be analyzed according to the vehicle operation data; the normal running time is the running time of the vehicle to be analyzed according to a preset running state;
when the current online time length is larger than a first preset time length threshold value, determining the abnormal operation time length of the vehicle to be analyzed according to the difference value of the current online time length and the normal operation time length;
when the abnormal operation time length is larger than a second preset time length threshold value, judging that the vehicle to be analyzed has an abnormal dormancy condition;
and determining the running time period of the vehicle to be analyzed in the abnormal dormant state according to the vehicle running data.
As a preferred scheme, the method specifically performs abnormal awakening identification on the vehicle to be analyzed through the following steps, and determines the running time period of the vehicle to be analyzed in an abnormal awakening state:
judging whether the vehicle to be analyzed has abnormal operation conditions in any one-time online process within a preset time period according to the vehicle operation data; wherein the judgment condition of the abnormal operation condition is as follows: the vehicle to be analyzed does not operate according to a preset operation state;
when the abnormal running condition exists in the vehicle to be analyzed, counting the occurrence frequency of the abnormal running condition in the preset time period, and judging whether the occurrence frequency is larger than a preset threshold value or not;
when the occurrence frequency is larger than the preset threshold value, judging that the vehicle to be analyzed has an abnormal awakening condition;
and determining the running time period of the vehicle to be analyzed in the abnormal awakening state according to the vehicle running data.
Preferably, the preset operation state at least includes a vehicle driving state, a vehicle charging state, a parking use state, a remote use state, a camping state and an external discharging state.
Preferably, the method further comprises the following steps:
and generating alarm information according to the awakening source of the vehicle to be analyzed, and pushing the alarm information to a user.
A second aspect of the embodiments of the present invention provides an apparatus for analyzing abnormal sleeping and waking-up of a vehicle, including:
the data acquisition module is used for acquiring vehicle operation data of a vehicle to be analyzed;
the abnormal recognition module is used for performing abnormal dormancy recognition or abnormal awakening recognition on the vehicle running data according to a preset recognition strategy and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state;
the online characterization signal acquisition module is used for acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period;
and the awakening source identification module is used for carrying out awakening source identification on the vehicle to be analyzed according to the online characterization signal and determining at least one awakening source of the vehicle to be analyzed.
A third aspect of embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method for analyzing abnormal vehicle hibernation and awakening according to any one of the first aspect when executing the computer program.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device in which the computer-readable storage medium is located is controlled to perform the analysis method for abnormal vehicle hibernation and wake-up according to any one of the first aspects.
Compared with the prior art, the method and the device have the advantages that the vehicle running data of the vehicle to be analyzed are obtained; performing abnormal dormancy identification or abnormal awakening identification on the vehicle running data according to a preset identification strategy, and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state; acquiring online characterization signals corresponding to each communication network segment of the vehicle to be analyzed in the operation time period; and according to the online characterization signals, performing awakening source identification on the vehicle to be analyzed, and determining at least one awakening source of the vehicle to be analyzed, so that the awakening source analysis on the abnormal dormancy or abnormal awakening condition is performed according to the online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the abnormal dormancy state or abnormal awakening state in the operation time period.
Drawings
FIG. 1 is a flowchart illustrating an analysis method for abnormal vehicle hibernation and wake-up according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a determination matrix of a wake-up source according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating abnormal sleep recognition in an embodiment of the present invention;
FIG. 4 is a flowchart illustrating an abnormal wake-up identification according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an analysis apparatus for abnormal vehicle hibernation and wake-up in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a first aspect of the embodiment of the present invention provides a method for analyzing abnormal sleeping and waking of a vehicle, including the following steps S1 to S4:
s1, acquiring vehicle operation data of a vehicle to be analyzed;
s2, performing abnormal dormancy identification or abnormal awakening identification on the vehicle running data according to a preset identification strategy, and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state;
s3, acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period;
and S4, performing awakening source identification on the vehicle to be analyzed according to the online characterization signal, and determining at least one awakening source of the vehicle to be analyzed.
In step S1, vehicle operation data of the vehicle to be analyzed is obtained, and it is worth mentioning that the vehicle operation data can be uploaded to the cloud end in the operation process of the vehicle, so that the vehicle operation data of the vehicle to be analyzed can be collected from the cloud end in this embodiment.
In step S2, since the vehicle operation data is data generated during the operation of the vehicle, it can be identified whether an abnormal sleeping situation or an abnormal waking situation occurs in the vehicle to be analyzed according to the vehicle operation data. Based on this, the embodiment performs the abnormal sleep recognition or the abnormal awakening recognition on the vehicle operation data according to the preset recognition strategy, and determines the operation time period when the vehicle to be analyzed is in the abnormal sleep state or the abnormal awakening state.
In step S3, in the running time period when the vehicle to be analyzed is in the abnormal sleeping state or the abnormal waking state, the controllers corresponding to one or more communication network segments of the vehicle may be in the waking state, and when the controllers are in the waking state, the service function signals of the controllers are uploaded, and the service function signals can be used to represent the online state of the communication network segments. In the embodiment, the online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the running time period of the abnormal sleep state or the abnormal wake-up state are obtained, so that the online state or the offline state of each communication network segment or controller can be determined.
It should be noted that, in the prior art, when a Controller in a vehicle has an abnormal sleep condition or an abnormal wake-up condition, the Controller sends a non-sleep reason or a wake-up reason to a CAN (Controller Area Network) Network in the form of a Network management message, but the method needs to rely on a sleep wake-up reason signal developed separately by the vehicle end, and when the vehicle type is changed, the separately developed sleep wake-up reason signal is no longer applicable, so the development difficulty in the prior art is large, and the application range is small. The embodiment of the invention only depends on the service function signals uploaded by each controller in the vehicle, does not need to independently develop the reason signals for waking up from sleep, and can be suitable for vehicles of different vehicle types, so that the embodiment of the invention has a wider application range.
As a preferred scheme, the identifying the awakening source of the vehicle to be analyzed according to the online characterization signal, and determining at least one awakening source of the vehicle to be analyzed specifically includes the following steps:
determining a plurality of online communication network segments and online controllers in an awakening state according to the online characterization signals;
and determining at least one common awakening source of all online communication network segments and online controllers based on preset awakening relations between the communication network segments and the awakening sources and between the controllers and the awakening sources, and taking the common awakening source as the awakening source of the vehicle to be analyzed.
Specifically, according to the obtained online characterization signal, a plurality of online communication segments and online controllers in the wake-up state within the running time period when the vehicle to be analyzed is in the abnormal sleep state or the abnormal wake-up state can be determined in the embodiment. It can be understood that when the vehicle is not in use, each communication segment and the controller should be in a sleep state, and if there is an online communication segment or an online controller in an awake state in a time period without use requirement, it indicates that the online communication segment or the online controller cannot sleep for a long time due to the wake-up of the wake-up source or is frequently woken up during sleep.
Further, at least one common awakening source of all the online communication network segments and the online controllers is determined based on the preset awakening relationship between each communication network segment and each awakening source and the awakening relationship between each controller and each awakening source, and the common awakening source is used as the awakening source of the vehicle to be analyzed. It should be noted that each communication segment and each controller have an awakening relationship with each awakening source in the vehicle, and for one of the communication segments, some awakening sources can awaken the communication segment, and some awakening sources cannot awaken the communication segment.
And determining at least one common awakening source capable of awakening the online communication network segments and the online controllers simultaneously based on the determined plurality of online communication network segments and the online controllers, and taking the determined common awakening source as an awakening source of the vehicle to be analyzed.
Exemplarily, as shown in fig. 2, the judgment matrix is a judgment matrix of an awakening source, where a symbol "o" indicates that the awakening source can awaken a current communication segment or controller, a symbol "x" indicates that the awakening source cannot awaken the current communication segment or controller, and it is assumed that online characterization signals of the communication segment 1/ECU1 and the communication segment 2/ECU2 are obtained within an operation time period in which a vehicle to be analyzed is in an abnormal sleep state or an abnormal awakening state, and according to an awakening relationship between the communication segment 1/ECU1, the communication segment 2/ECU2 and each awakening source, the awakening source 2 is a common awakening source of the communication segment 1/ECU1 and the communication segment 2/ECU2, and thus the awakening source 2 is an awakening source causing an abnormal sleep or abnormal awakening condition.
Preferably, the method further comprises the following steps:
when an online characterization signal corresponding to any one awakening source of the vehicle to be analyzed in the operation time period is received, selecting the common awakening source according to the online characterization signal corresponding to any one awakening source, and taking the selected common awakening source as the awakening source of the vehicle to be analyzed.
It should be noted that there may be more than one determined common wake-up source, and in order to further narrow the wake-up source identification range, in this embodiment, when an online characterization signal corresponding to any one wake-up source is received within an operation time period in which the vehicle to be analyzed is in an abnormal sleep state or an abnormal wake-up state, the online characterization signal corresponding to the wake-up source is used as an auxiliary judgment basis, the determined common wake-up source is further selected according to the online characterization signal corresponding to the wake-up source, and the selected common wake-up source is used as a wake-up source of the vehicle to be analyzed, so that the wake-up source causing the abnormal sleep or abnormal wake-up condition can be more accurately identified.
As a preferred scheme, the method specifically performs abnormal dormancy identification on the vehicle to be analyzed through the following steps, and determines the running time period of the vehicle to be analyzed in an abnormal dormancy state:
determining the current online time length and the normal operation time length of the vehicle to be analyzed according to the vehicle operation data; the normal operation time length is the time length of the vehicle to be analyzed operating according to a preset operation state;
when the current online time length is larger than a first preset time length threshold value, determining the abnormal operation time length of the vehicle to be analyzed according to the difference value between the current online time length and the normal operation time length;
when the abnormal operation time length is larger than a second preset time length threshold value, judging that the vehicle to be analyzed has an abnormal dormancy condition;
and determining the running time period of the vehicle to be analyzed in the abnormal dormant state according to the vehicle running data.
Referring to fig. 3, a flow chart of abnormal sleep recognition is shown. It is worth to be noted that, in the present embodiment, the current online time length and the normal operation time length of the vehicle to be analyzed can be determined according to the vehicle operation data, where the normal operation time length is a time length for the vehicle to be analyzed to operate according to a preset operation state, as a preferred scheme, the preset operation state includes a vehicle driving state, a vehicle charging state, a parking use state, a remote use state, a camping state, an external discharge state, and the like, and according to the vehicle operation data, it can be determined whether the vehicle to be analyzed is in one or more preset operation states. If the vehicle runs according to one or more preset running states, the vehicle is indicated to run normally, and the abnormal sleep or abnormal awakening condition does not occur; if the vehicle does not operate according to one or more preset operation states, the abnormal operation of the vehicle is indicated, and the abnormal sleep or abnormal awakening condition occurs.
When the time length of the secondary online is greater than a first preset time length threshold, according to the difference value between the time length of the secondary online and the time length of the normal operation, the abnormal operation time length in the process of the secondary online can be determined; and when the abnormal operation time length is greater than a second preset time length threshold value, judging that the vehicle to be analyzed cannot sleep for a long time, and generating an abnormal sleep condition.
Further, when the vehicle is in the abnormal sleep state, the controller in the wake-up state in the vehicle uploads the operation data to the cloud, so that the embodiment can determine the operation time period of the vehicle to be analyzed in the abnormal sleep state according to the uploading time period of the operation data.
It should be noted that, because the probability of the abnormal sleep condition is small when the online time of the vehicle is short, the first preset time threshold is set in the embodiment, and when the secondary online time is greater than the first preset time threshold, the abnormal sleep identification is performed on the vehicle operation data in the secondary online time period.
As a preferred scheme, the method specifically performs abnormal awakening identification on the vehicle to be analyzed through the following steps, and determines the running time period of the vehicle to be analyzed in the abnormal awakening state:
judging whether the vehicle to be analyzed has abnormal operation conditions in any one-time online process within a preset time period according to the vehicle operation data; wherein the judgment condition of the abnormal operation condition is as follows: the vehicle to be analyzed does not operate according to a preset operation state;
when the abnormal operation condition exists in the vehicle to be analyzed, counting the occurrence frequency of the abnormal operation condition in the preset time period, and judging whether the occurrence frequency is greater than a preset threshold value or not;
when the occurrence frequency is larger than the preset threshold value, judging that the vehicle to be analyzed has an abnormal awakening condition;
and determining the running time period of the vehicle to be analyzed in the abnormal awakening state according to the vehicle running data.
Referring to fig. 4, a flow chart of abnormal wake-up recognition is shown. In this embodiment, it is judged whether an abnormal operation condition that the vehicle to be analyzed does not operate according to the preset operation state exists in any one online process within the preset time period according to the vehicle operation data, and it is worth explaining that the preset operation state is the above-mentioned operation state including the vehicle running state, the vehicle charging state, the parking use state, the remote use state, the camping state, the external discharge state, and the like.
When the abnormal operation condition exists in any one-time online process of the vehicle to be analyzed in the preset time period, counting the occurrence frequency of the abnormal operation condition in the preset time period, and when the occurrence frequency is greater than a preset threshold value, indicating that the vehicle to be analyzed is frequently awakened, and judging that the abnormal awakening condition of the vehicle to be analyzed occurs.
Because when the vehicle is in the abnormal awakening state, the controller in the awakening state in the vehicle can upload the operation data to the cloud end, so that the embodiment can determine the operation time period when the vehicle to be analyzed is in the abnormal awakening state according to the uploading time period of the operation data.
It should be noted that the preset time period may be set according to actual requirements, for example, the preset time period is set to be within a day, a week, and the like, and the embodiment of the present invention is not limited in detail herein.
It should be noted that the preset threshold may be set according to the vehicle usage habit of the user and the preset time period, for example, the user mainly uses the vehicle in the work time period and the work time period at ordinary times, and the number of times of powering on the vehicle does not exceed 5 times, so when the preset time period is within one day, the preset threshold may be set to be more than 5 times, for example, 6 times, 8 times, 10 times, and the embodiment is not limited specifically herein.
Preferably, the method further comprises the following steps:
and generating alarm information according to the awakening source of the vehicle to be analyzed, and pushing the alarm information to a user.
It should be noted that, in this embodiment, after the wake-up source of the vehicle to be analyzed is determined, the warning information is generated according to the wake-up source of the vehicle to be analyzed, and the warning information is pushed to a user, such as a maintenance worker, a vehicle owner, and the like, so that the user can know the wake-up source causing the abnormal sleep or abnormal wake-up in time.
The analysis method for abnormal dormancy and awakening of the vehicle provided by the embodiment of the invention can analyze the awakening source of the abnormal dormancy or abnormal awakening condition according to the online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period of the abnormal dormancy or abnormal awakening condition.
In addition, the embodiment of the invention only depends on the service function signals uploaded by each controller in the vehicle, does not need to independently develop the reason signal for waking up from sleep, and can be suitable for vehicles of different vehicle types, so the embodiment of the invention has a wider application range.
Referring to fig. 5, a second aspect of the embodiment of the present invention provides an apparatus for analyzing abnormal sleep and wake-up of a vehicle, including:
the data acquisition module 501 is used for acquiring vehicle operation data of a vehicle to be analyzed;
the abnormal recognition module 502 is configured to perform abnormal sleep recognition or abnormal awakening recognition on the vehicle operation data according to a preset recognition strategy, and determine an operation time period when the vehicle to be analyzed is in an abnormal sleep state or an abnormal awakening state;
an online characterization signal obtaining module 503, configured to obtain online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operating time period;
and a wake-up source identification module 504, configured to perform wake-up source identification on the vehicle to be analyzed according to the online characterization signal, and determine at least one wake-up source of the vehicle to be analyzed.
As a preferred scheme, the awakening source identification module 504 is configured to perform awakening source identification on the vehicle to be analyzed according to the online characterization signal, and determine at least one awakening source of the vehicle to be analyzed, specifically including:
determining a plurality of online communication network segments and online controllers in an awakening state according to the online characterization signals;
and determining at least one common awakening source of all online communication network segments and online controllers based on preset awakening relations between the communication network segments and the awakening sources and between the controllers and the awakening sources, and taking the common awakening source as the awakening source of the vehicle to be analyzed.
Preferably, the wake-up source identification module 504 is further configured to:
when an online characterization signal corresponding to any one awakening source of the vehicle to be analyzed in the operation time period is received, selecting the common awakening source according to the online characterization signal corresponding to any one awakening source, and taking the selected common awakening source as the awakening source of the vehicle to be analyzed.
As a preferable scheme, the abnormal recognition module 502 is configured to perform abnormal dormancy recognition on the vehicle operation data according to a preset recognition strategy, and determine an operation time period in which the vehicle to be analyzed is in an abnormal dormancy state, and specifically includes:
determining the current online time and the normal operation time of the vehicle to be analyzed according to the vehicle operation data; the normal running time is the running time of the vehicle to be analyzed according to a preset running state;
when the current online time length is larger than a first preset time length threshold value, determining the abnormal operation time length of the vehicle to be analyzed according to the difference value of the current online time length and the normal operation time length;
when the abnormal operation time length is larger than a second preset time length threshold value, judging that the vehicle to be analyzed has an abnormal dormancy condition;
and determining the running time period of the vehicle to be analyzed in the abnormal dormant state according to the vehicle running data.
As a preferred scheme, the abnormal recognition module 502 is configured to perform abnormal awakening recognition on the vehicle operation data according to a preset recognition strategy, and determine an operation time period in which the vehicle to be analyzed is in an abnormal awakened state, and specifically includes:
judging whether the vehicle to be analyzed has abnormal operation conditions in any one-time online process within a preset time period according to the vehicle operation data; wherein the judgment condition of the abnormal operation condition is as follows: the vehicle to be analyzed does not operate according to a preset operation state;
when the abnormal operation condition exists in the vehicle to be analyzed, counting the occurrence frequency of the abnormal operation condition in the preset time period, and judging whether the occurrence frequency is greater than a preset threshold value or not;
when the occurrence frequency is larger than the preset threshold value, judging that the vehicle to be analyzed has an abnormal awakening condition;
and determining the running time period of the vehicle to be analyzed in the abnormal awakening state according to the vehicle running data.
Preferably, the preset operation state at least includes a vehicle driving state, a vehicle charging state, a parking use state, a remote use state, a camping state and an external discharging state.
Preferably, the apparatus further comprises an alarm module, configured to:
and generating alarm information according to the awakening source of the vehicle to be analyzed, and pushing the alarm information to a user.
It should be noted that, the apparatus for analyzing abnormal vehicle hibernation and wake-up provided in the embodiment of the present invention can implement all the processes of the method for analyzing abnormal vehicle hibernation and wake-up described in any one of the embodiments, and the functions and technical effects of each module in the apparatus are respectively the same as those of the method for analyzing abnormal vehicle hibernation and wake-up described in the embodiment, and are not described herein again.
A third aspect of an embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the method for analyzing abnormal sleep and wake-up of a vehicle according to any embodiment of the first aspect when executing the computer program.
The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device may include, but is not limited to, a processor, a memory. The terminal device may also include input and output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal device and connects the various parts of the whole terminal device using various interfaces and lines.
The memory may be used for storing the computer programs and/or modules, and the processor may implement various functions of the terminal device by executing or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device on which the computer-readable storage medium is located is controlled to perform the method for analyzing abnormal sleep and wake-up of a vehicle according to any one of the embodiments of the first aspect.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present invention may be implemented by software plus a necessary hardware platform, and may also be implemented by hardware entirely. With this understanding in mind, all or part of the technical solutions of the present invention that contribute to the background can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments or some parts of the embodiments of the present invention.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A method for analyzing abnormal sleeping and awakening of a vehicle is characterized by comprising the following steps:
acquiring vehicle operation data of a vehicle to be analyzed;
performing abnormal dormancy identification or abnormal awakening identification on the vehicle running data according to a preset identification strategy, and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state;
acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period;
and according to the online characterization signal, performing awakening source identification on the vehicle to be analyzed, and determining at least one awakening source of the vehicle to be analyzed.
2. The method for analyzing abnormal vehicle dormancy and awakening according to claim 1, wherein the step of identifying the awakening source of the vehicle to be analyzed according to the online characterization signal and determining at least one awakening source of the vehicle to be analyzed specifically comprises the steps of:
determining a plurality of online communication network segments and online controllers in an awakening state according to the online characterization signals;
and determining at least one common awakening source of all online communication network segments and online controllers based on preset awakening relations between the communication network segments and the awakening sources and between the controllers and the awakening sources, and taking the common awakening source as the awakening source of the vehicle to be analyzed.
3. The method for analyzing abnormal sleep and wake-up of a vehicle according to claim 2, further comprising the steps of:
when an online characterization signal corresponding to any one awakening source of the vehicle to be analyzed in the operation time period is received, selecting the common awakening source according to the online characterization signal corresponding to any one awakening source, and taking the selected common awakening source as the awakening source of the vehicle to be analyzed.
4. The analysis method for the abnormal sleeping and awakening of the vehicle as claimed in claim 1, wherein the method specifically identifies the abnormal sleeping of the vehicle to be analyzed and determines the running time period of the vehicle to be analyzed in the abnormal sleeping state by the following steps:
determining the current online time and the normal operation time of the vehicle to be analyzed according to the vehicle operation data; the normal running time is the running time of the vehicle to be analyzed according to a preset running state;
when the current online time length is larger than a first preset time length threshold value, determining the abnormal operation time length of the vehicle to be analyzed according to the difference value of the current online time length and the normal operation time length;
when the abnormal operation time length is larger than a second preset time length threshold value, judging that the vehicle to be analyzed has an abnormal dormancy condition;
and determining the running time period of the vehicle to be analyzed in the abnormal dormant state according to the vehicle running data.
5. The vehicle abnormal sleep and wake analysis method according to claim 1, wherein the method specifically performs abnormal wake recognition on the vehicle to be analyzed and determines the operation time period of the vehicle to be analyzed in the abnormal wake state by the following steps:
judging whether the vehicle to be analyzed has abnormal operation conditions in any one-time online process within a preset time period according to the vehicle operation data; wherein the judgment condition of the abnormal operation condition is as follows: the vehicle to be analyzed does not operate according to a preset operation state;
when the abnormal running condition exists in the vehicle to be analyzed, counting the occurrence frequency of the abnormal running condition in the preset time period, and judging whether the occurrence frequency is larger than a preset threshold value or not;
when the occurrence frequency is larger than the preset threshold value, judging that the vehicle to be analyzed has an abnormal awakening condition;
and determining the running time period of the vehicle to be analyzed in the abnormal awakening state according to the vehicle running data.
6. The method for analyzing abnormal sleeping and awakening of a vehicle according to claim 4 or 5, wherein the preset operation state at least comprises a vehicle driving state, a vehicle charging state, a parking use state, a remote use state, a camping state and an external discharging state.
7. The method for analyzing abnormal sleep and wake-up of a vehicle according to claim 1, further comprising the steps of:
and generating alarm information according to the awakening source of the vehicle to be analyzed, and pushing the alarm information to a user.
8. An apparatus for analyzing abnormal sleep and wake-up of a vehicle, comprising:
the data acquisition module is used for acquiring vehicle operation data of a vehicle to be analyzed;
the abnormal recognition module is used for performing abnormal dormancy recognition or abnormal awakening recognition on the vehicle running data according to a preset recognition strategy and determining the running time period of the vehicle to be analyzed in an abnormal dormancy state or an abnormal awakening state;
the online characterization signal acquisition module is used for acquiring online characterization signals corresponding to each communication network segment or controller of the vehicle to be analyzed in the operation time period;
and the awakening source identification module is used for carrying out awakening source identification on the vehicle to be analyzed according to the online characterization signal and determining at least one awakening source of the vehicle to be analyzed.
9. A terminal device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the analysis method for abnormal vehicle hibernation and awakening according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, comprising a stored computer program, wherein when the computer program runs, the computer-readable storage medium is controlled to execute the analysis method for abnormal vehicle hibernation and wakeups according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211463864.8A CN115923690A (en) | 2022-11-22 | 2022-11-22 | Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211463864.8A CN115923690A (en) | 2022-11-22 | 2022-11-22 | Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115923690A true CN115923690A (en) | 2023-04-07 |
Family
ID=86650017
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211463864.8A Pending CN115923690A (en) | 2022-11-22 | 2022-11-22 | Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115923690A (en) |
-
2022
- 2022-11-22 CN CN202211463864.8A patent/CN115923690A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107564518B (en) | Intelligent device control method and device and computer device | |
| CN109272728B (en) | Electric quantity management method and device | |
| CN106959857B (en) | Application control method and device of electronic equipment | |
| CN112141122A (en) | Vehicle dormancy anomaly detection method, device, equipment and storage medium | |
| CN110658905B (en) | Early warning method, early warning system and early warning device for equipment operation state | |
| CN115396860A (en) | NFC chip intelligent regulation method, device, equipment and storage medium | |
| CN112668211B (en) | Limit power consumption control system and control method based on equipment power supply state | |
| CN112203346B (en) | Power consumption management method, device, equipment and medium for vehicle-mounted terminal | |
| CN104808767A (en) | Terminal control method | |
| CN104156050A (en) | Task monitoring method and electronic device | |
| CN111103963A (en) | Fingerprint module starting method and device, storage medium and terminal | |
| CN111261160A (en) | Signal processing method and device | |
| CN114506292A (en) | Automobile tail gate control method and system and vehicle | |
| CN109933419B (en) | Control method and device | |
| CN115923690A (en) | Analysis method, device, equipment and medium for abnormal sleeping and awakening of vehicle | |
| US20160147630A1 (en) | Method and system of detecting abnormal power consumption | |
| CN112644420A (en) | Vehicle awakening method and system, computer readable storage medium and vehicle terminal | |
| CN111045507B (en) | List management and control method, device, mobile terminal and storage medium | |
| CN116723560A (en) | Network awakening method and device, electronic equipment and vehicle | |
| CN115723692A (en) | Monitoring method and device for abnormal awakening of vehicle, server and storage medium | |
| CN113947827A (en) | Method and device for adjusting running power consumption of door lock, electronic equipment and storage medium | |
| CN111161452A (en) | Scanning method and scanning device for controlling electronic lock authentication module | |
| CN115474227B (en) | Abnormality detection method and device and vehicle | |
| KR100677121B1 (en) | Apparatus and method for controlling status battery in low voltage | |
| CN116600262B (en) | Method and device for determining sleep wakeup abnormality, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |