Vehicle storage battery power shortage analysis method and device and storage medium

Abstract

The invention provides a vehicle storage battery power shortage analysis method and device and a storage medium, and belongs to the technical field of vehicle storage batteries. The method comprises the following steps: acquiring storage battery data and vehicle state data; and if the storage battery voltage in the storage battery data meets the first voltage early warning range within the preset duration, determining the power shortage reason of the storage battery based on at least one of the storage battery data and the vehicle state data, so that the power shortage reason of the storage battery is determined based on at least one of the storage battery data and the vehicle state data. The method does not need manual power shortage reason analysis, thereby improving the efficiency of determining the power shortage reason of the vehicle storage battery.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle batteries, and in particular to a method, device and storage medium for analyzing power failure of a vehicle battery. Background Art

[0002] The vehicle battery is an important component of the vehicle. It provides electrical energy for starting the vehicle. When the vehicle battery is low on power, it will affect the normal use of the vehicle.

[0003] In the related art, after a battery failure occurs in a vehicle, a technician is required to analyze the cause of the battery failure based on experience.

[0004] Manual analysis of the cause of power failure requires a lot of time and manpower, resulting in low efficiency in the analysis of the cause of power failure. Summary of the Invention

[0005] The present invention provides a method, device, and storage medium for analyzing battery failure in a vehicle, which can improve the efficiency of analyzing the cause of battery failure. The technical solution is as follows:

[0006] In one aspect, a method for analyzing a low-power state of a vehicle battery is provided, the method comprising:

[0007] Acquiring target data related to the battery, the target data including battery data and vehicle status data;

[0008] If the battery voltage in the battery data meets a first voltage warning range within a preset time period, a reason for the battery power shortage is determined based on at least one of the battery data and vehicle status data.

[0009] Optionally, determining a cause of battery power loss based on at least one of the battery data and the vehicle status data includes:

[0010] Determining whether the vehicle triggers a network non-sleep warning based on the battery data and the vehicle data;

[0011] If the vehicle triggers the network non-sleep warning, determining the network non-sleep reason based on the vehicle status data;

[0012] The reason for the battery power shortage is determined based on the reason why the network does not sleep.

[0013] Optionally, the vehicle status data includes an operating status of a controller in the vehicle, and determining the reason why the network is not in sleep mode based on the vehicle status data includes:

[0014] Determine each target controller corresponding to a sleep abnormal state within a target network monitoring time period; the door switch state of the vehicle remains unchanged within the target network monitoring time period; the sleep abnormal state of the controller includes at least one of network wakeup and network hold;

[0015] A reason why the network is not in sleep mode is determined based on the operating status of each target controller and a controller corresponding to the target controller.

[0016] Optionally, the vehicle status data includes the status of the lights in the vehicle, and determining the reason why the network is not in sleep mode based on the vehicle status data includes: determining the reason why the network is not in sleep mode based on the status of the lights in the vehicle within a first time period corresponding to the preset duration.

[0017] Optionally, the vehicle is a gasoline vehicle, and the vehicle status data includes a power gear and an engine start status of the vehicle; and determining a cause of battery power loss based on at least one of the battery data and the vehicle status data includes:

[0018] Before the start time corresponding to the preset duration, determining the stop time of the most recent engine stop;

[0019] From the stall time to the target monitoring end time, determining a first proportion corresponding to the engine being in an inactive state when the power gear is in the ON gear or the ACC gear, and the target monitoring end time is the time corresponding to the battery voltage being greater than the first voltage warning range;

[0020] Based on the first proportion, a reason for the battery power shortage is determined.

[0021] Optionally, the type of the vehicle is a new energy vehicle type, and the vehicle status data includes an ignition status and a high voltage status of the vehicle; and determining a cause of battery power loss based on at least one of the battery data and the vehicle status data includes:

[0022] The reason for the battery power failure is determined based on the ignition state and high voltage state of the vehicle within a preset time period before the start time corresponding to the preset duration.

[0023] Optionally, the battery data further includes: at least one of battery state of charge data, voltage change rate, and state of charge data reached during each discharge; and determining a cause of battery power loss based on at least one of the battery data and vehicle status data includes:

[0024] determining an aging tag of the battery based on at least one of the state of charge data, the voltage change rate, and the state of charge data reached during each discharge of the battery, wherein the aging tag is used to identify the aging state of the battery;

[0025] A reason for the battery power shortage is determined based on the aging tag.

[0026] In another aspect, a vehicle battery low-power analysis device is provided, the device comprising:

[0027] An acquisition module, configured to acquire target data related to the battery, wherein the target data includes battery data and vehicle status data;

[0028] The first determination module is configured to determine a cause of battery depletion based on at least one of the battery data and vehicle status data if the battery voltage in the battery data meets a first voltage warning range within a preset time period.

[0029] Optionally, the first determining module includes:

[0030] A first determining submodule is configured to determine whether the vehicle triggers a network non-sleep warning based on the battery data and the vehicle data;

[0031] a second determining submodule, configured to determine a reason for the network not sleeping based on the vehicle status data if the vehicle triggers the network not sleeping warning;

[0032] The third determining submodule is configured to determine a reason for the battery power shortage based on the reason why the network does not sleep.

[0033] Optionally, the vehicle status data includes an operating status of a controller in the vehicle, and the second determining submodule includes:

[0034] A first determining unit is configured to determine each target controller corresponding to a sleep abnormality state within a target network monitoring time period; wherein the door switch state of the vehicle remains unchanged within the target network monitoring time period; and wherein the sleep abnormality state of the controller includes at least one of network wakeup and network hold;

[0035] The second determining unit is configured to determine a reason why the network does not sleep based on the operating status of each target controller and a controller corresponding to the target controller.

[0036] Optionally, the vehicle status data includes a status of lights in the vehicle, and the second determination submodule is used to determine the reason why the network is not in sleep mode based on the status of lights in the vehicle within a first time period corresponding to the preset duration.

[0037] Optionally, the type of the vehicle is a gasoline vehicle, and the vehicle status data includes a power level and an engine start status of the vehicle; the first determining module further includes:

[0038] a fourth determining submodule, configured to determine a stop time of the most recent engine stop before a start time corresponding to the preset duration;

[0039] a fifth determining submodule, configured to determine, from the stall time to a target monitoring end time, a first proportion corresponding to the engine being in an inactive state when the power gear is in the ON gear or the ACC gear, wherein the target monitoring end time is a time corresponding to when the battery voltage is greater than the first voltage warning range;

[0040] The sixth determining submodule is configured to determine a reason for the battery being low on power based on the first proportion.

[0041] Optionally, the type of the vehicle is a new energy vehicle type, and the vehicle status data includes an ignition status and a high voltage status of the vehicle; the first determining module further includes:

[0042] The seventh determination submodule is configured to determine a cause of battery depletion based on an ignition state and a high voltage state of the vehicle within a preset time period before a start time corresponding to the preset duration.

[0043] Optionally, the battery data further includes: at least one of the battery's state of charge data, voltage change rate, and state of charge data reached during each discharge; and the first determining module includes:

[0044] an eighth determining submodule, configured to determine an aging tag of the battery based on at least one of the state of charge data of the battery, the voltage change rate, and the state of charge data reached during each discharge, the aging tag being used to identify the aging state of the battery;

[0045] A ninth determining submodule is configured to determine a reason for the battery to be low on power based on the aging tag.

[0046] On the other hand, a computing device is provided, characterized in that the computing device includes a processor and a memory, the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the operations performed by the above-mentioned vehicle battery low power analysis method.

[0047] On the other hand, a computer storage medium is provided, in which at least one instruction is stored. The instruction is loaded and executed by a processor to implement the operations performed by the above-mentioned vehicle battery low power analysis method.

[0048] The beneficial effects of the technical solutions provided in the embodiments of the present application include at least:

[0049] The present application provides a vehicle battery low power analysis method, which obtains battery data and vehicle status data; if the battery voltage in the battery data meets the first voltage warning range within a preset time period, the battery low power cause is determined based on at least one of the battery data and the vehicle status data, thereby achieving the determination of the battery low power cause based on at least one of the battery data and the vehicle status data, without the need for manual analysis of the battery low power cause, thereby improving the efficiency of determining the vehicle battery low power cause. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 This is a flow chart showing a method for analyzing a low-power battery in a vehicle according to an exemplary embodiment;

[0052] Figure 2 is a flow chart showing a method for determining a cause of battery power failure according to an exemplary embodiment;

[0053] Figure 3 The present invention is a structural block diagram showing a vehicle battery low power analysis method according to an exemplary embodiment. DETAILED DESCRIPTION

[0054] Unless otherwise defined, all technical terms used in the embodiments of the present invention have the same meanings as those commonly understood by those skilled in the art. To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0055] Figure 1 FIG. 1 is a flow chart showing a method for analyzing a vehicle battery power shortage according to an exemplary embodiment. Figure 1 As shown, the method is applied to a computing device, which may be a server or a terminal, and includes:

[0056] Step 101: Acquire target data related to the battery, where the target data includes battery data and vehicle status data.

[0057] In an embodiment of the present application, the battery data may include a battery voltage, which may be greater than or equal to a preset voltage threshold. The preset voltage threshold is used to filter out invalid data and may be set according to actual conditions, for example, 6V.

[0058] It should be noted that, for each moment, the battery data and the vehicle status data are stored in a one-to-one correspondence. From the multiple battery data, the battery voltage greater than or equal to the preset voltage threshold is screened out. Based on the fact that the battery data and the vehicle status data are stored in a one-to-one correspondence, the vehicle status data corresponding to the battery voltage greater than or equal to the preset voltage threshold is determined.

[0059] Step 102 : If the battery voltage in the battery data meets the first voltage warning range within a preset time period, determine the cause of battery power loss based on at least one of the battery data and the vehicle status data.

[0060] Among them, the first voltage warning range is set according to actual conditions. If the vehicle is a gasoline vehicle, the first voltage warning range is less than or equal to 10.5V; if the vehicle is an electric vehicle, the first low voltage warning range is less than or equal to 9.5V.

[0061] In an embodiment of the present application, the monitoring time of low-power monitoring is determined by judging whether the battery voltage meets the first voltage threshold range, and the first acquisition time corresponding to the initial detection of the battery voltage meeting the first voltage threshold range is used as the start time of the monitoring time. Within a preset time period after the first detection of the second acquisition time corresponding to the battery voltage greater than the first voltage threshold range, if the battery voltage within the preset time period is greater than the first voltage threshold range, the time corresponding to the preset time period after the second acquisition time is used as the end time of the monitoring time.

[0062] After the monitoring time is determined, the time corresponding to the preset duration after the start time of the monitoring time is used as the time to trigger the low-battery alarm. In other words, when the battery voltage is detected to be within the first voltage warning range, the low-battery alarm is not triggered immediately. Instead, the low-battery alarm is triggered after the battery voltage has been within the first voltage warning range for a preset duration. The low-battery alarm ends at the end time of the monitoring time. Only one warning message is sent between the start time and the end time of the low-battery alarm.

[0063] In an embodiment of the present application, the battery low power warning is divided into three levels: the first level is when the remaining battery capacity drops to 30% of the total capacity and the remaining power battery is greater than 15%, the warning is triggered. At this time, the user can remotely start the vehicle on the APP for recharging through the vehicle's built-in remote recharging function, so the warning information is only sent to the user; the second level is when the remaining battery capacity drops to 30% of the total capacity, but the remaining power battery is less than 15%, the warning is triggered. At this time, the remote recharging function cannot be used, and the user needs to get in the car and start the vehicle for recharging. The warning information is also only sent to the user; the third level is when the remaining battery capacity drops to 10% of the total capacity, the warning is triggered. At this time, the vehicle can no longer be started and needs to be started using an emergency starting power supply or a new battery needs to be replaced. Since it involves on-site rescue, the warning information will be sent to the user and the after-sales service department at the same time, so that the after-sales service department can promptly arrange for technicians to proactively contact the user and provide door-to-door service according to user needs.

[0064] It should be noted that after the first voltage warning range is met for a preset period of time, a low-battery alarm is triggered. Not only will the warning information be sent to the relevant department, but the cause of the low-battery alarm will also be determined. The following describes the specific steps for determining the cause of battery low-battery from different perspectives.

[0065] The following first introduces the specific steps to determine the battery power loss caused by the network not sleeping.

[0066] Determining the cause of battery power loss based on at least one of the battery data and the vehicle status data includes the following steps 1021 to 1023.

[0067] Step 1021: Based on the battery data and the vehicle data, determine whether the vehicle triggers a network non-sleep warning.

[0068] In the embodiment of the present application, the battery data includes the battery voltage, and the battery voltage greater than or equal to the preset voltage threshold and the corresponding vehicle status data are obtained. The vehicle data is determined in the same manner as the vehicle status data in step 102 and will not be repeated here.

[0069] In an embodiment of the present application, the target network monitoring time period is determined based on vehicle status data. If the vehicle is a new energy vehicle, monitoring begins when the power mode is initially detected as OFF and the high voltage state is OFF. The acquisition time corresponding to the start of monitoring is used as the start time of the target network monitoring time period. Monitoring is stopped when the power mode is non-OFF or empty, or the high voltage state is non-OFF. The acquisition time corresponding to the power mode is non-OFF or empty, or the high voltage state is non-OFF is used as the end time of the target network monitoring time period. If the vehicle is a gasoline vehicle, monitoring begins when the engine state is initially detected as not started. The acquisition time corresponding to the start of monitoring is used as the start time of the target network monitoring time period. If the engine state is detected as engine started, monitoring is stopped, and the last acquisition time is recorded as the end time of the target network monitoring time period.

[0070] It should be noted that during the monitoring process, the door switch status and lock status are determined to see if they have changed from the previous state. If any of these states have changed, the timer is reset to determine the target network monitoring period. The door switch status includes the driver's side door switch status, passenger side door switch status, rear left door switch status, rear right door switch status, and trunk door switch status. The lock status includes the trunk lock status, left front door lock status, and hood lock status.

[0071] Step 1022: If the vehicle triggers a network non-sleep warning, the reason for the network non-sleep is determined based on the vehicle status data.

[0072] In an embodiment of the present application, if the network monitoring duration corresponding to the target network monitoring time period is greater than or equal to the preset network monitoring duration or the number of frequent wake-ups is greater than the preset number of times, the network non-sleep alarm is triggered and the alarm trigger time is recorded. The alarm trigger time is the time corresponding to the preset network monitoring duration after the start time of the monitoring time period. The non-sleep monitoring start time is the start time corresponding to the target network monitoring time period. When the monitoring is ended, the alarm is ended and the non-sleep end time is updated. The non-sleep end time is the end time corresponding to the target network monitoring time period, and this monitoring event is recorded as a non-sleep alarm.

[0073] Among them, when the continuous reporting time interval exceeds 1 minute, it is a non-sleep-sleep cycle, which is recorded as one frequent wake-up number.

[0074] In an embodiment of the present application, the vehicle status data also includes the operating status of the controller in the vehicle, and determining the reason why the network is not in sleep mode based on the vehicle status data includes: determining each target controller corresponding to the abnormal sleep mode within the target network monitoring time period; and determining the reason why the network is not in sleep mode based on the operating status of each target controller and the controller corresponding to the target controller.

[0075] The door switch state and the lock state of the vehicle remain unchanged during the target network monitoring time period. The abnormal sleep state of the controller includes at least one of network wake-up and network hold.

[0076] It should be noted that the operating status of the controller is determined from the high-frequency signal in the received message. If the controller state is determined to be the controller corresponding to the network wake-up state, the hexadecimal signal corresponding to the network wake-up state is obtained from the high-frequency signal. If the controller state is determined to be the controller corresponding to the network hold state, the hexadecimal signal corresponding to the network hold state is obtained from the high-frequency signal. The hexadecimal signal in the message is converted to binary. For example, 00 00 40 00 4000 0C 00 (hexadecimal) is converted to: 00000000000000000 01000000 00000000 01000000 000000000001100 00000000 (binary); the number of digits in the number 1 is determined to be subtracted by 1. For example, in the example above, the position of 1 is subtracted by 1, which is 17, 33, 52, and 53, respectively. The corresponding controller is determined based on the correspondence between the controller and the sequence number list.

[0077] In an embodiment of the present application, for each target controller, when the number of network maintenance status reports or network wake-up status reports of the target controller during the target network monitoring time period accounts for 90% of the total reporting times, the controller is recorded as a possible cause of non-sleep.

[0078] It should be noted that the total number of reports refers to the total number of reports on the operating status of all controllers within the target network monitoring time period.

[0079] In another embodiment of the present application, the vehicle status data includes the status of the lights in the vehicle, and determining the reason why the network is not in sleep mode based on the vehicle status data includes: determining the reason why the network is not in sleep mode based on the status of the lights in the vehicle within a first time period corresponding to a preset duration.

[0080] It should be noted that the first time period is the time between the start time corresponding to the target network monitoring time period and the alarm triggering time.

[0081] In this embodiment of the present application, the vehicle light status indicates whether the width lights, left turn signal, and right turn signal are on. If the number of reports indicating the width lights are on accounts for 80% of the total number of reports, the network is determined to be active because the user has turned on the width lights. If the number of reports indicating the left turn signal and the right turn signal are both on accounts for 40% of the total number of reports, the network is determined to be active because the user has turned on both the left and right turn signals.

[0082] In the embodiment of the present application, if the alarm is caused by frequent wake-up times, it is determined that the reason why the network is not in sleep mode is that the network wakes up frequently.

[0083] In an embodiment of the present application, the type of vehicle is a gasoline vehicle type, and the vehicle status data includes the power gear and engine start status of the vehicle; the reason for the battery depletion is determined based on at least one of the battery data and the vehicle status data, including: determining the stop time of the most recent engine stop before the start time corresponding to the preset duration; from the stop time to the target monitoring end time, determining the first proportion corresponding to the engine status being the non-start state when the power gear is ON or ACC, and the target monitoring end time is the time corresponding to the battery voltage being greater than the first voltage warning range; based on the first proportion, determining the reason for the battery depletion.

[0084] It should be noted that the start time before the preset duration is the start time of the monitoring time. The target monitoring end time is the end time of the above monitoring time.

[0085] In the embodiment of the present application, the first proportion refers to the proportion of the total number of reports corresponding to the stop time to the target monitoring end time. The first proportion is greater than or equal to 90%, and the reason for the power loss is recorded as the engine not starting.

[0086] In an embodiment of the present application, the type of vehicle is a new energy vehicle type, and the vehicle status data includes the ignition status and high-voltage status of the vehicle; determining the cause of battery power loss based on at least one of the battery data and the vehicle status data includes: determining the cause of battery power loss based on the ignition status and high-voltage status of the vehicle within a preset time period before the start time corresponding to the preset duration.

[0087] For example: In the hour before monitoring begins, filter out data where the ignition state is not OFF and the high voltage state is not ON, and the number of reports accounts for greater than or equal to 90% of the total number of reports, and record the cause of power loss as high voltage failure.

[0088] In an embodiment of the present application, the battery data also includes: the battery's state of charge data, voltage change rate, and at least one of the state of charge data reached during each discharge. Determining the cause of battery power loss based on at least one of the battery data and vehicle status data includes: determining an aging label of the battery based on the battery's state of charge data, voltage change rate, and at least one of the state of charge data reached during each discharge, the aging label being used to identify the battery's aging status; and determining the cause of battery power loss based on the aging label.

[0089] In the data collected that day, if the vehicle's engine status or high-voltage status changes, the battery voltage change rate is obtained and used to determine whether the battery is aging. If no data is reported that day, the aging indicator is not updated.

[0090] For example, if a gasoline vehicle's engine status changes from started to not started, the voltage change is monitored. If the voltage change exceeds 2V within a preset time period, the vehicle's label for that day will be marked as battery aging. If a new energy vehicle's high voltage status changes from on to off, the current and voltage change rates are monitored. If the voltage change exceeds 2V within a preset time period, the vehicle's label for that day will be marked as battery aging.

[0091] In an embodiment of the present application, within a preset time period, the total state of charge data of the battery increased during the charging process is obtained. Every time the increased state of charge data reaches 100%, the number of cycles increases once. The preset time period can be the number of cycles of the vehicle battery on the same day / nearly 30 days / nearly 180 days / nearly 360 days.

[0092] During a preset time period, the battery discharge times are obtained based on the SOC reached during each discharge, and the times of moderate or deep discharge are determined according to the threshold, for example, 70% is moderate discharge and 50% is deep discharge.

[0093] In an embodiment of the present application, the vehicle's most recent engine start date (for gasoline vehicles) or most recent high-voltage application date (for new energy vehicles) is updated daily. The time interval between the current date and the most recent engine start date or most recent high-voltage application date is determined to be greater than or equal to a preset number of days. If so, the vehicle is determined to be a long-term stationary vehicle and is labeled a long-term stationary vehicle.

[0094] Step 1023: Determine the reason for the battery power shortage based on the reason why the network does not sleep.

[0095] In the embodiment of the present application, the reason for the network not sleeping is determined to be a battery power failure. For example, the battery power failure reason may be: network wake-up or network hold of the target controller, user turning on the width indicator light, and user turning on the left and right turn signals.

[0096] The present application provides a vehicle battery low power analysis method, which obtains battery data and vehicle status data; if the battery voltage in the battery data meets the first voltage warning range within a preset time period, the battery low power cause is determined based on at least one of the battery data and the vehicle status data, thereby achieving the determination of the battery low power cause based on at least one of the battery data and the vehicle status data, without the need for manual battery low power cause analysis, thereby improving the efficiency of determining the vehicle battery low power cause.

[0097] This application also provides a vehicle battery low power analysis device, such as Figure 3 As shown, the device includes:

[0098] An acquisition module 301 is used to acquire target data related to the battery, the target data including battery data and vehicle status data;

[0099] The first determining module 302 is configured to determine a cause of battery power loss based on at least one of the battery data and the vehicle status data if the battery voltage in the battery data meets a first voltage warning range within a preset time period.

[0100] Optionally, the first determining module 302 includes:

[0101] A first determination submodule is configured to determine whether the vehicle triggers a network non-sleep warning based on battery data and vehicle data;

[0102] A second determination submodule is configured to determine a network non-sleep reason based on vehicle status data if the vehicle triggers a network non-sleep warning;

[0103] The third determining submodule is configured to determine a reason for battery power shortage based on a reason why the network is not in sleep mode.

[0104] Optionally, the vehicle status data includes an operating status of a controller in the vehicle, and the second determining submodule includes:

[0105] A first determining unit is configured to determine each target controller corresponding to a sleep abnormality state within a target network monitoring period; the door switch state of the vehicle remains unchanged within the target network monitoring period; the sleep abnormality state of the controller includes at least one of network wakeup and network hold;

[0106] The second determining unit is configured to determine a reason why the network is not in sleep mode based on the operating status of each target controller and the controller corresponding to the target controller.

[0107] Optionally, the vehicle status data includes a status of lights in the vehicle, and the second determination submodule is used to determine the reason why the network is not in sleep mode based on the status of lights in the vehicle within a first time period corresponding to a preset duration.

[0108] Optionally, the type of vehicle is a gasoline vehicle, and the vehicle status data includes the vehicle's power gear and engine start status; the first determination module further includes:

[0109] a fourth determining submodule, configured to determine a stop time of a most recent engine stop before a start time corresponding to a preset duration;

[0110] A fifth determination submodule is configured to determine, from the stall time to the target monitoring end time, a first proportion corresponding to the engine being in an inactive state when the power gear is in the ON gear or the ACC gear, and the target monitoring end time being the time corresponding to the battery voltage being greater than the first voltage warning range;

[0111] The sixth determining submodule is configured to determine a reason for the battery power shortage based on the first proportion.

[0112] Optionally, the type of vehicle is a new energy vehicle type, and the vehicle status data includes the ignition status and high voltage status of the vehicle; the first determination module further includes:

[0113] The seventh determination submodule is configured to determine a cause of battery depletion based on an ignition state and a high voltage state of the vehicle within a preset time period before a start time corresponding to the preset duration.

[0114] Optionally, the battery data further includes: at least one of the battery's state of charge data, voltage change rate, and state of charge data reached during each discharge. The first determining module includes:

[0115] an eighth determining submodule, configured to determine an aging tag of the battery based on at least one of the battery's state of charge data, a voltage change rate, and state of charge data reached during each discharge, the aging tag being used to identify the battery's aging state;

[0116] The ninth determining submodule is configured to determine a reason for battery power failure based on the aging tag.

[0117] The present application provides a vehicle battery low-power analysis device, which obtains battery data and vehicle status data; if the battery voltage in the battery data meets the first voltage warning range within a preset time period, the battery low-power cause is determined based on at least one of the battery data and the vehicle status data, thereby achieving the determination of the battery low-power cause based on at least one of the battery data and the vehicle status data, without the need for manual analysis of the battery low-power cause, thereby improving the efficiency of determining the battery low-power cause of the vehicle.

[0118] It should be noted that the vehicle battery low-power analysis device provided in the above embodiment is only illustrated by the division of the above-mentioned functional modules. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle battery low-power analysis device provided in the above embodiment and the vehicle battery low-power analysis method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0119] On the other hand, a computing device is provided, characterized in that the computing device includes a processor and a memory, the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the operations performed by the above-mentioned vehicle battery low power analysis method.

[0120] On the other hand, a computer storage medium is provided, in which at least one instruction is stored. The instruction is loaded and executed by a processor to implement the operations performed by the above-mentioned vehicle battery low power analysis method.

[0121] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the claims.

[0122] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for analyzing a vehicle battery power shortage, characterized in that: The method comprises: Acquiring target data related to the battery, the target data including battery data and vehicle status data; If the battery voltage in the battery data meets a first voltage warning range within a preset time period, a reason for the battery power shortage is determined based on at least one of the battery data and vehicle status data.

2. The method according to claim 1, characterized in that The determining the cause of the battery power failure based on at least one of the battery data and the vehicle status data includes: Determining whether the vehicle triggers a network non-sleep warning based on the battery data and the vehicle data; If the vehicle triggers the network non-sleep warning, determining the network non-sleep reason based on the vehicle status data; The reason for the battery power shortage is determined based on the reason why the network does not sleep.

3. The method according to claim 2, characterized in that The vehicle status data includes an operating status of a controller in the vehicle, and determining the reason why the network is not dormant based on the vehicle status data includes: Determine each target controller corresponding to a sleep abnormal state within a target network monitoring time period; the door switch state of the vehicle remains unchanged within the target network monitoring time period; the sleep abnormal state of the controller includes at least one of network wake-up and network hold; A reason why the network is not in sleep mode is determined based on the operating status of each target controller and a controller corresponding to the target controller.

4. The method according to claim 2, characterized in that The vehicle status data includes the status of the lights in the vehicle, and determining the reason why the network is not in sleep mode based on the vehicle status data includes: determining the reason why the network is not in sleep mode based on the status of the lights in the vehicle within a first time period corresponding to the preset duration.

5. The method according to claim 1, wherein The type of the vehicle is a gasoline vehicle, and the vehicle status data includes a power gear position and an engine start status of the vehicle; and determining a reason for the battery power failure based on at least one of the battery data and the vehicle status data includes: Before the start time corresponding to the preset duration, determining the stop time of the most recent engine stop; From the stall time to the target monitoring end time, determining a first proportion corresponding to the engine being in an inactive state when the power gear is in the ON gear or the ACC gear, and the target monitoring end time is the time corresponding to the battery voltage being greater than the first voltage warning range; Based on the first proportion, a reason for the battery power shortage is determined.

6. The method according to claim 1, characterized in that The type of the vehicle is a new energy vehicle type, and the vehicle status data includes an ignition status and a high voltage status of the vehicle; and determining the cause of the battery power loss based on at least one of the battery data and the vehicle status data includes: The reason for the battery power failure is determined based on the ignition state and high voltage state of the vehicle within a preset time period before the start time corresponding to the preset duration.

7. The method according to claim 1, characterized in that The battery data further includes: at least one of the battery's state of charge data, voltage change rate, and state of charge data reached during each discharge; and determining the cause of battery power loss based on at least one of the battery data and vehicle status data includes: determining an aging tag of the battery based on at least one of the state of charge data, the voltage change rate, and the state of charge data reached during each discharge of the battery, wherein the aging tag is used to identify the aging state of the battery; A reason for the battery power shortage is determined based on the aging tag.

8. A vehicle battery low power analysis device, characterized in that: The device comprises: An acquisition module, configured to acquire target data related to the battery, wherein the target data includes battery data and vehicle status data; The first determination module is configured to determine a cause of battery depletion based on at least one of the battery data and vehicle status data if the battery voltage in the battery data meets a first voltage warning range within a preset time period.

9. A computing device, characterized in that The computing device includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the operations performed by the vehicle battery low power analysis method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores at least one instruction, which is loaded and executed by the processor to implement the operations performed by the vehicle battery low power analysis method according to any one of claims 1 to 7.

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