Big data-based automobile storage battery feeding identification and replacement reminding method and system

Abstract

The application discloses a kind of based on big data's automobile battery feed identification and replacement reminding method and system, and it is related to battery monitoring technical field.The present application includes: by establishing the ignition difficulty and whether index based on single car owner, the ignition abnormality and whether situation of vehicle is monitored in real time, to identify whether car owner exists battery feed situation in time;Based on the driving information of vehicle, another judgment system is established, to make up the uncertainty of single index judgment, to strengthen the accuracy of identification group.The present application uses Internet of Vehicles big data, according to the ignition of car owner and voltage and driving state, excavates battery feed situation.The technology provides battery feed identification and reminding service, can monitor the battery feed situation of car owner in real time, reminds car owner to do well back to factory protection and preparation in real time, while helping 4S shop to actively provide corresponding series of services, improves battery replacement back to factory rate.

Description

Technical Field

[0001] This invention belongs to the field of battery monitoring technology, and in particular relates to a method and system for identifying and reminding automobile batteries of low power levels based on big data. Background Technology

[0002] With the continuous intelligent development of automotive electronics technology, the electricity consumption of vehicles has increased significantly, making it crucial to provide sufficient power. However, common vehicle battery failures include battery depletion. When a vehicle battery is depleted, it not only causes considerable inconvenience to users but may also endanger the lives of drivers and passengers. According to statistics from CheZhi.com, from 2014 to 2019, there were 4,090 vehicle battery failures, of which approximately 97% involved battery depletion.

[0003] For example, Chinese patent CN110641284A provides a low-voltage power management system for the safety monitoring of electric vehicle power batteries. This battery management system monitors vehicle status information, primarily the high-voltage status within the high-voltage box and the status of the power battery pack, in real-time or intermittently. Regardless of whether the vehicle is in operation, as long as the DC-DC converter outputs power, components including, but not limited to, the battery management system, on-board monitoring unit, and vehicle controller can monitor the vehicle status online and transmit the monitoring data to a remote monitoring platform. The platform then performs data monitoring and accident warnings, thereby achieving offline vehicle monitoring and improving the reliability and safety of the monitoring. However, it cannot combine other status data of the vehicle itself for precise monitoring.

[0004] Furthermore, because OEMs struggle to quickly identify and alert vehicle owners to low battery levels within their systems, owner complaints are frequent, and battery replacement rates at the repair shop are generally low. Therefore, real-time battery low-level alerts and intelligent services that provide targeted battery maintenance reminders during daily use are of paramount importance to both OEMs and users. A key challenge is how OEMs can leverage vast amounts of vehicle connectivity platform data to provide timely battery low-level alerts to vehicle owners. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for identifying and reminding car battery depletion based on big data. By utilizing vehicle network big data, the system identifies battery depletion scenarios based on the owner's ignition, voltage, and driving status. This technology provides battery depletion identification and reminder services, enabling real-time monitoring of the owner's battery depletion status and timely reminders for the owner to return the vehicle to the service center for maintenance and preparation. It also helps 4S stores proactively provide corresponding services, increasing the battery replacement return rate. Targeted battery health maintenance reminders can extend the lifespan of the owner's battery and enhance brand reputation.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0007] As the first aspect provided by this invention, the invention provides a method for identifying and reminding a car battery to be out of power based on big data, comprising the following steps:

[0008] Step S1: Monitor the vehicle's ignition status in real time based on the ignition status data of a single car owner to determine if the ignition status is abnormal.

[0009] Step S2: Obtain auxiliary battery depletion index information based on historical and current driving data for a single vehicle owner;

[0010] Step S3: Combine steps S1 and S2 to identify the battery power status in real time and send the identification results to the vehicle owner.

[0011] Furthermore, in step S1, the method for determining whether the vehicle's ignition status is abnormal is as follows:

[0012] Within the most recent T time interval, determine whether multiple ignition attempts have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can be driven normally.

[0013] If a vehicle experiences multiple ignition attempts within a time interval T, and the vehicle's voltage range is within the abnormal battery voltage range during the first and last ignition attempts, and ignition fails, resulting in the inability to drive normally, then the vehicle is considered to have ignition difficulties.

[0014] Where T is a preset value.

[0015] Furthermore, the method for identifying vehicle ignition difficulties is as follows:

[0016] Step S11: Judgment based on the driver's ignition action:

[0017] By obtaining the ignition status data and corresponding time within the most recent time period T, it can be determined whether the ignition status of the vehicle owner at the corresponding time is continuous ignition.

[0018] Step S12: Ignition difficulty judgment based on ignition action judgment:

[0019] Step S121: Obtain and calculate voltage and vehicle speed: First, obtain and calculate the voltage and vehicle speed at times t(n), t(n-1)...t(1) within the time interval T;

[0020] Step S122: Threshold-based ignition count judgment: Within the time interval T, the calculated number of ignitions is compared with the set threshold N. If the number is less than the threshold, the ignition is considered normal and the judgment ends. If the number is greater than the threshold, the next step is to judge whether the voltage is abnormal.

[0021] Step S123: Voltage-based judgment:

[0022] The first and last ignition actions within the time interval T are obtained by judging the ignition action, and the lowest and highest voltages when the ignition state is 0 during the first and last ignition actions are calculated.

[0023] When the ignition state is 0 during the first and last ignition actions, the corresponding highest voltage Vbmax is less than or equal to the set highest voltage threshold Vmax, and the corresponding lowest voltage Vbmin is less than or equal to the set lowest voltage threshold Vmin, which satisfies the following:

[0024] If Vbmin≤Vmin and Vbmax≤Vmax), proceed to the next step; otherwise, consider the ignition normal and end the judgment.

[0025] Step S124: Speed-based determination: Based on the determinations in steps S121-S123, continue with the speed determination:

[0026] The system determines the first and last ignition actions within a time interval T by judging the ignition action, and calculates the highest vehicle speed when the ignition state is 0 during the first and last ignition actions within a time interval T.

[0027] If the ignition status is 0 during the period between the first and last ignition attempts, but the vehicle speed is greater than 0, the judgment ends and the ignition is considered normal.

[0028] When the corresponding vehicle speed is equal to 0, it is considered that ignition is difficult, the judgment ends, and the ignition difficulty record is output: ["Owner ID", TimeC, ign_1_cnts], where TimeC is the time of the last ignition action, and ign_1_cnts is the number of ignitions within the time interval T;

[0029] An ignition status of 0 indicates that no ignition action has occurred.

[0030] Furthermore, in step S11, the method for determining whether the vehicle owner's ignition status at the corresponding moment is continuous ignition is as follows:

[0031] S1101: Obtain the ignition status data and corresponding time within the most recent T time interval, and form time and ignition status key-value pairs sorted in descending order by time.

[0032] S1102: Based on the time series, examine the ignition status at a specific moment within a continuous time period T, and obtain the corresponding set:

[0033] I (n) ={(t (n) ign(n) ), (t (n-1) ign (n-1) )…(t (1) ign (1) )}

[0034] Where: (t) (n) ign (n) ) indicates that at t (n) At any given moment, the ignition state is IGN. (n) , among which ign (n) The corresponding value has two states: 1 or 0. Let 1 represent that ignition has occurred and 0 represent that ignition has not occurred.

[0035] S1103: From t (1) to t (n) During this continuous time interval, IGN occurred. (n) to ign (1) When all values ​​are equal to 1, it is considered that continuous ignition action occurred within that continuous time interval.

[0036] S1104: via ign (n) to ign (1) The number of times ignition occurs within a time interval T is equal to 1.

[0037] Furthermore, in step S2, the method for obtaining the auxiliary power supply index information is as follows:

[0038] Step S21: Calculate basic information: Basic information includes vehicle age and cumulative mileage;

[0039] Step S22: Obtain the longest consecutive parking days in the last K1 days;

[0040] Step S23: Within the past K2 days, is there a trip that meets the conditions of driving time ≥ A min and maximum speed > B km / h? If so, there is a rechargeable trip.

[0041] Step S24: Within the past K2 days, is there a trip that meets the conditions of travel time < A min or maximum speed < B km / h? If so, there are short-distance and low-speed travel situations, and the number and percentage of short-distance and low-speed travel situations are calculated.

[0042] Step S25: Output auxiliary judgment feature fields: ["Owner ID", "Vehicle Age", "Cumulative Mileage", "Number of Days Parked", "Whether There is a Charging Route", "Short-distance and Low-speed Driving Status"];

[0043] Among them, K1, K2, A, and B are all preset values.

[0044] Furthermore, in step S3, the step of identifying the battery power supply status in real time in conjunction with steps S1 and S2 is as follows:

[0045] Step S31: Based on a single vehicle owner and the corresponding auxiliary judgment feature fields, after determining that ignition is difficult, proceed to step S32 to determine battery depletion.

[0046] Step S32: Determine if the vehicle age is greater than the preset threshold AGE. If it is, proceed to step S33. Otherwise, push maintenance knowledge and jump-start methods to the vehicle owner.

[0047] Step S33: Determine whether the longest number of days of parking is less than the preset threshold AGE1. If it is less than the threshold, proceed to the next step. Otherwise, it is considered that the battery has been depleted.

[0048] Step S34: Determine if there is a rechargeable stroke. If so, proceed to the next step. Otherwise, consider that the battery is depleted.

[0049] Step S35: Determine whether the proportion of short-distance and low-speed driving is greater than the preset threshold AGE2. If the condition is met, proceed to the next step; otherwise, consider that the battery is depleted.

[0050] Step S36: Determine whether the vehicle's cumulative mileage has reached the preset threshold AGE3. If the condition is met, it is considered that the battery has been depleted, and the final judgment ends; otherwise, it is considered that the battery has not been depleted.

[0051] Furthermore, in step S3, the method for sending the battery discharge detection result to the vehicle owner is as follows:

[0052] Within Tm time after the battery is detected to be depleted, send the following to the vehicle owner: ["Vehicle Owner ID", address, latitude and longitude, time of battery depletion];

[0053] Where Tm is a preset value.

[0054] As a second aspect of the present invention, the present invention provides a vehicle battery depletion identification and replacement reminder system based on big data, the system being used to implement the battery depletion identification and replacement reminder method described in the first aspect.

[0055] Furthermore, a big data-based automotive battery depletion identification and replacement reminder system includes:

[0056] The vehicle ignition difficulty real-time identification module: Based on ignition status data, it obtains the data within a recent time interval to determine whether multiple ignition attempts have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can drive normally. If, within a recent time interval, the vehicle has multiple ignition attempts, and the vehicle's voltage range is within the abnormal battery voltage range between the first and last ignition attempts, and ignition fails, resulting in the inability to drive normally, then the vehicle is considered to have ignition difficulty.

[0057] Auxiliary battery depletion judgment module: Based on the characteristics of battery depletion, it provides further judgment basis for battery depletion based on the driving behavior data of an individual car owner;

[0058] Battery depletion judgment module: It receives the ignition difficulty recognition result output by the vehicle ignition difficulty recognition module, as well as the auxiliary judgment feature fields output by the auxiliary depletion judgment module. The battery depletion judgment module uses the owner's historical driving behavior, such as vehicle age, cumulative mileage, longest idle days, recent vehicle speed, and short-distance and low-speed driving, to establish a relatively complete judgment process, thereby making a final judgment on whether the owner has experienced battery depletion, and comprehensively judging the depletion status of the vehicle battery.

[0059] Battery low power replacement reminder module: It sends a low power information to the vehicle owner after the battery is low.

[0060] Furthermore, the driving behavior data of an individual car owner includes: historical and current driving data, and calculates vehicle age, cumulative mileage, longest parking days, availability of charging trips, and information on short-distance and low-speed driving based on the driving behavior data.

[0061] The present invention has the following beneficial effects:

[0062] This invention constructs an ignition difficulty index based on vehicle ignition status data, voltage data, and vehicle speed data transmitted from the vehicle terminal. If a vehicle owner attempts to ignite multiple times within a certain continuous time interval, but fails to ignite due to abnormal vehicle voltage, resulting in the inability to drive normally, then the vehicle is considered to have an ignition difficulty. By establishing an ignition difficulty index based on individual vehicle owners, the invention monitors the occurrence of ignition abnormalities in real time, thereby promptly identifying whether the vehicle owner has a battery depletion issue. Based on vehicle driving information, including vehicle age, cumulative mileage, longest idle days, recent speed, short-distance and low-speed driving, an additional judgment system is established to compensate for the uncertainty of single-index judgment, thereby enhancing the accuracy of identifying groups.

[0063] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0064] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is a flowchart illustrating the process of determining the vehicle owner's ignition action according to the present invention.

[0066] Figure 2 The following is a flowchart of the process for determining vehicle ignition difficulties according to the present invention;

[0067] Figure 3 This is a flowchart of the auxiliary power supply discrimination method of the present invention;

[0068] Figure 4 (left) The right side represents the overall judgment logic of the battery power supply judgment method of the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] Example 1:

[0071] As a crucial component of automobiles, the battery cannot be identified or warned in advance when it is low on charge. Therefore, this patent proposes a method and system for reminding drivers to replace their batteries based on vehicle network big data mining. Utilizing vehicle network big data, it identifies battery depletion scenarios based on the owner's ignition, voltage, and driving status. This technology provides battery depletion identification and reminder services, enabling real-time monitoring of the owner's battery status and timely reminders for necessary repairs and maintenance. It also helps 4S dealerships proactively provide corresponding services, increasing battery replacement rates. Targeted battery health maintenance reminders can extend the lifespan of the owner's battery and enhance brand reputation.

[0072] like Figure 1 As shown in Figure 4, as the first embodiment of the present invention, the present invention is a method for identifying and reminding about the depletion of automotive batteries based on big data, comprising the following steps:

[0073] Step S1: Real-time monitoring of the vehicle's ignition status based on individual owner's ignition status data to determine if the ignition status is abnormal; as an embodiment of the present invention, preferably, the method for determining whether the vehicle's ignition status is abnormal is as follows:

[0074] Within the most recent T time interval, determine whether multiple ignition attempts have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can be driven normally.

[0075] If a vehicle experiences multiple ignition attempts within a time interval T, and the vehicle's voltage range is within the abnormal battery voltage range during the first and last ignition attempts, and ignition fails, resulting in the inability to drive normally, then the vehicle is considered to have ignition difficulties.

[0076] Where T is a preset value; it is sufficient to construct ignition difficulty indicators based on the vehicle ignition status data, electrical usage status data, voltage data, vehicle speed data, etc. transmitted by the vehicle terminal.

[0077] Step S2: Based on historical and current driving data of a single vehicle owner, auxiliary battery depletion indicator information is obtained; the auxiliary battery depletion judgment method is a further auxiliary judgment to the real-time vehicle ignition difficulty identification method. For the battery and the vehicle itself, factors such as prolonged vehicle inactivity, alternator damage, expiration of service life, insufficient electrolyte, battery terminal corrosion, loose cable connections, and leakage in the battery or vehicle circuit can all cause battery depletion. This method, tailored to a single vehicle owner, calculates indicators such as vehicle age, cumulative mileage, longest idle days, availability of rechargeable routes, and short-distance and low-speed driving based on historical and current driving data, providing further basis for judging battery depletion.

[0078] Step S3: Combining steps S1 and S2, the battery depletion status is identified in real time, and the identification result is sent to the vehicle owner. The battery depletion judgment method, after receiving the ignition difficulty identification sequence result output by the vehicle ignition difficulty identification module, utilizes the vehicle owner's historical driving behavior structure in the auxiliary depletion judgment method: vehicle age, cumulative mileage, longest idle days, recent vehicle speed, and short-distance and low-speed driving indicators; a relatively complete judgment process is established to make a final judgment on whether the vehicle owner has experienced battery depletion.

[0079] As an embodiment of the present invention, preferably, the method for identifying vehicle ignition difficulties is as follows:

[0080] Step S11: Judgment based on the driver's ignition action:

[0081] By obtaining the ignition status data and corresponding time within the most recent time period T, it can be determined whether the ignition status of the vehicle owner at the corresponding time is continuous ignition.

[0082] Step S12: Ignition difficulty judgment based on ignition action judgment:

[0083] Step S121: Obtain and calculate voltage and vehicle speed: First, obtain and calculate the voltage and vehicle speed at times t(n), t(n-1)...t(1) within the time interval T;

[0084] Step S122: Threshold-based ignition count judgment: Within the time interval T, the calculated number of ignitions is compared with the set threshold N. If the number is less than the threshold, the ignition is considered normal and the judgment ends. If the number is greater than the threshold, the next step is to judge whether the voltage is abnormal.

[0085] Step S123: Voltage-based judgment:

[0086] The first and last ignition actions within the time interval T are obtained by judging the ignition action, and the lowest and highest voltages when the ignition state is 0 during the first and last ignition actions are calculated.

[0087] When the ignition state is 0 during the first and last ignition actions, the corresponding highest voltage Vbmax is less than or equal to the set highest voltage threshold Vmax, and the corresponding lowest voltage Vbmin is less than or equal to the set lowest voltage threshold Vmin, which satisfies the following:

[0088] If Vbmin≤Vmin and Vbmax≤Vmax), proceed to the next step; otherwise, consider the ignition normal and end the judgment.

[0089] Step S124: Speed-based determination: Based on the determinations in steps S121-S123, continue with the speed determination:

[0090] The system determines the first and last ignition actions within a time interval T by judging the ignition action, and calculates the highest vehicle speed when the ignition state is 0 during the first and last ignition actions within a time interval T.

[0091] If the ignition status is 0 during the period between the first and last ignition attempts, but the vehicle speed is greater than 0, the judgment ends and the ignition is considered normal.

[0092] When the corresponding vehicle speed is equal to 0, it is considered that ignition is difficult, the judgment ends, and the ignition difficulty record is output: ["Vehicle Owner ID", TimeC, ign_1_cnts], where TimeC is the time of the last ignition action, and ign_1_cnts is the number of ignitions within the time interval T;

[0093] An ignition status of 0 indicates that no ignition action has occurred.

[0094] As an embodiment of the present invention, preferably, in step S11: the method for determining whether the ignition state of the vehicle owner at the corresponding time is continuous ignition is as follows:

[0095] S1101: Obtain the ignition status data and corresponding time within the most recent T time interval, and form time and ignition status key-value pairs sorted in descending order by time.

[0096] S1102: Based on the time series, examine the ignition status at a specific moment within a continuous time period T, and obtain the corresponding set:

[0097] I (n) ={(t (n) ign (n) ), (t (n-1) ign (n-1) )…(t (1) ign (1) )}

[0098] Where: (t) (n) ign (n) ) indicates that at t (n) At any given moment, the ignition state is IGN. (n) , among which ign (n) The corresponding value has two states: 1 or 0. Let 1 represent that ignition has occurred and 0 represent that ignition has not occurred.

[0099] S1103: From t (1) to t (n) During this continuous time interval, IGN occurred. (n) to ign (1) When all values ​​are equal to 1, it is considered that continuous ignition action occurred within that continuous time interval.

[0100] S1104: via ign (n) to ign (1) The number of times ignition occurs within a time interval T is equal to 1.

[0101] Generally, a car battery's lifespan is about 2 to 3 years. However, due to the popularity of car audio modifications and the increasing number of other in-car electrical appliances, many car owners use their cars as entertainment spaces while waiting, which shortens the lifespan of many car batteries. This method first obtains basic information such as vehicle age and cumulative mileage. Batteries left unused for extended periods will slowly self-discharge until they are unusable; therefore, the car should be started periodically to charge the battery. This method uses driving behavior data to identify the longest idle days: the longest idle days are defined as the number of days between the last day's driving record and the current day, and it also determines whether a charging trip occurred. Frequent short-distance driving and low-speed driving also accelerate battery wear. Due to frequent short-distance and low-speed driving, the alternator cannot fully charge the battery, potentially leading to battery depletion. Therefore, based on recent driving behavior, such as driving time and speed, it obtains recent short-distance and low-speed driving indicators for the vehicle. Based on a system of indicators including vehicle age, cumulative mileage, longest idle days, availability of charging range, and short-distance and low-speed driving, the data is stored independently for the vehicle owner to assist in determining battery depletion. As an embodiment of this invention, preferably, the method for obtaining the auxiliary depletion indicator information in step S2 is as follows:

[0102] Step S21: Calculate basic information: Basic information includes vehicle age and cumulative mileage;

[0103] Step S22: Obtain the longest consecutive parking days in the last K1 days;

[0104] Step S23: Within the past K2 days, is there a trip that meets the conditions of driving time ≥ A min and maximum speed > B km / h? If so, there is a rechargeable trip.

[0105] Step S24: Within the past K2 days, is there a trip that meets the conditions of travel time < A min or maximum speed < B km / h? If so, there are short-distance and low-speed travel situations, and the number and percentage of short-distance and low-speed travel situations are calculated.

[0106] Step S25: Output auxiliary judgment feature fields: ["Owner ID", "Vehicle Age", "Cumulative Mileage", "Number of Days Parked", "Whether There is a Charging Route", "Short-distance and Low-speed Driving Status"];

[0107] Among them, K1, K2, A, and B are all preset values.

[0108] The battery depletion information-assisted judgment side starts from other factors that affect battery depletion, and is based on the behavioral characteristics of car owners with depleted batteries. It establishes a supplementary judgment logic chain to compensate for the uncertainty of single-indicator judgment to a certain extent, increases the accuracy of identification, and adds battery depletion identification for car owners with depleted batteries, thereby achieving the purpose of grouping and improving the population profile.

[0109] As an embodiment of the present invention, preferably, in step S3, the step of real-time identification of the battery power supply status in conjunction with steps S1 and S2 is as follows:

[0110] Step S31: Based on a single vehicle owner and the corresponding auxiliary judgment feature fields, after determining that ignition is difficult, proceed to step S32 to determine battery depletion.

[0111] Step S32: Determine if the vehicle age is greater than the preset threshold AGE. If it is, proceed to step S33. Otherwise, push maintenance knowledge and jump-start methods to the vehicle owner.

[0112] Step S33: Determine whether the longest number of days of parking is less than the preset threshold AGE1. If it is less than the threshold, proceed to the next step. Otherwise, it is considered that the battery has been depleted.

[0113] Step S34: Determine if there is a rechargeable stroke. If so, proceed to the next step. Otherwise, consider that the battery is depleted.

[0114] Step S35: Determine whether the proportion of short-distance and low-speed driving is greater than the preset threshold AGE2. If the condition is met, proceed to the next step; otherwise, consider that the battery is depleted.

[0115] Step S36: Determine whether the vehicle's cumulative mileage has reached the preset threshold AGE3. If the condition is met, it is considered that the battery has been depleted, and the final judgment ends; otherwise, it is considered that the battery has not been depleted.

[0116] As an embodiment of the present invention, preferably, the method for sending the battery discharge identification result to the vehicle owner in step S3 is as follows:

[0117] Within Tm time after the battery is detected to be depleted, send the following to the vehicle owner: ["Vehicle Owner ID", address, latitude and longitude, time of battery depletion];

[0118] Where Tm is a preset value.

[0119] As a second aspect of the present invention, the present invention provides a vehicle battery depletion identification and replacement reminder system based on big data, the system being used to implement the battery depletion identification and replacement reminder method described in the first aspect.

[0120] As an embodiment of the present invention, a preferred embodiment of the automotive battery depletion identification and replacement reminder system based on big data includes:

[0121] The vehicle ignition difficulty real-time identification module: Based on ignition status data, it obtains the data within a recent time interval to determine whether multiple ignition attempts have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can drive normally. If, within a recent time interval, the vehicle has multiple ignition attempts, and the vehicle's voltage range is within the abnormal battery voltage range between the first and last ignition attempts, and ignition fails, resulting in the inability to drive normally, then the vehicle is considered to have ignition difficulty.

[0122] Auxiliary battery depletion judgment module: Based on the characteristics of battery depletion, it provides further judgment basis for battery depletion based on the driving behavior data of an individual car owner;

[0123] Battery depletion judgment module: It receives the ignition difficulty recognition result output by the vehicle ignition difficulty recognition module, and the owner's historical driving behavior from the auxiliary judgment feature field index calculation module output by the auxiliary depletion judgment module: vehicle age, cumulative mileage, longest idle days, recent vehicle speed, and short-distance and low-speed driving indicators, etc., to establish a relatively complete judgment process, thereby making a final judgment on whether the owner has experienced battery depletion, and comprehensively judging the battery depletion status of the vehicle.

[0124] Battery low battery replacement reminder module: This module sends a low battery notification to the vehicle owner after the battery has reached a low battery level. It provides 4S dealerships with feedback on the owner's battery status, thereby accurately identifying vehicle owners whose batteries are low.

[0125] Furthermore, the driving behavior data of an individual car owner includes: historical and current driving data, and calculates vehicle age, cumulative mileage, longest parking days, availability of charging trips, and information on short-distance and low-speed driving based on the driving behavior data.

[0126] A big data-driven method and system for identifying and reminding car battery owners of low battery status can monitor the battery's condition in real time. The monitoring results are transmitted to the OEM (Original Equipment Manufacturer) in real time, providing a basis for message pushes and proactive services to the OEM and dealerships. This enhances user experience and marketing effectiveness, and provides customers with timely services. Furthermore, by monitoring battery usage behavior, targeted battery maintenance knowledge can be provided to users during daily use, maximizing battery life and improving brand reputation.

[0127] Specifically, compared with existing systems, the advantages of this invention are:

[0128] 1. To overcome the current problem that OEMs and 4S stores cannot accurately monitor the battery depletion of car owners in real time, this method can monitor whether the car owner's battery is depleted in real time through vehicle connectivity big data.

[0129] 2. Based on the historical driving behavior data of car owners, we can explore the auxiliary judgment indicators of each car owner, optimize the drawbacks of single indicators, improve customer profiles, and provide personalized services.

[0130] 3. Based on the time and location of the vehicle owner's battery depletion, feedback is sent to the OEM; this allows the OEM to allocate dealerships to respond to the vehicle owner's needs and provide faster service.

[0131] 4. Targeted battery health maintenance reminders can extend the lifespan of car owners' batteries and enhance brand reputation.

[0132] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0133] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for identifying and reminding users of low battery status in automobiles based on big data, characterized in that: Includes the following steps: Step S1: Real-time monitoring of whether the vehicle's ignition status is abnormal based on the ignition status data of a single vehicle owner; Step S2: Obtain auxiliary battery depletion index information based on historical and current driving data for a single vehicle owner; Step S3: Combine steps S1 and S2 to identify the battery's power status in real time and send the identification result to the vehicle owner; In step S2, the method for obtaining auxiliary power supply index information is as follows: Step S21: Calculate basic information: Basic information includes vehicle age and cumulative mileage; Step S22: Obtain the longest consecutive parking days in the last K1 days; Step S23: Within the past K2 days, is there a trip that meets the conditions of travel time ≥ A min and maximum speed > B km / h? If so, there is a rechargeable trip. Step S24: Within the past K2 days, is there a trip that meets the conditions of travel time < A min or maximum speed < B km / h? If so, there are short-distance and low-speed travel situations, and the number and percentage of short-distance and low-speed travel situations are calculated. Step S25: Output auxiliary judgment feature fields: ["Owner ID", "Vehicle Age", "Cumulative Mileage", "Number of Days Parked", "Whether There is a Charging Route", "Short-distance and Low-speed Driving Status"]; Where K1, K2, A, and B are all preset values; In step S3, the step of identifying the battery power status in real time in combination with steps S1 and S2 is as follows: Step S31: Based on a single car owner and the corresponding auxiliary judgment feature field, after the ignition difficulty is met, proceed to step S32 to judge the battery power status: Step S32: Determine whether the vehicle age is greater than the preset threshold AGE. If it is greater, proceed to step S33. Otherwise, push maintenance knowledge and jump-start methods to the car owner. Step S33: Determine whether the longest number of days of parking is less than the preset threshold AGE1. If it is less than the threshold, proceed to the next step. Otherwise, it is considered that the battery has been depleted. Step S34: Determine if there is a rechargeable stroke. If so, proceed to the next step. Otherwise, consider that the battery is depleted. Step S35: Determine whether the proportion of short-distance and low-speed driving is greater than the preset threshold AGE2. If the condition is met, proceed to the next step; otherwise, consider that the battery is depleted. Step S36: Determine whether the vehicle's cumulative mileage has reached the preset threshold AGE3. If the condition is met, it is considered that the battery has been depleted, and the final judgment ends; otherwise, it is considered that the battery has not been depleted.

2. The method for identifying and reminding about battery depletion in automobiles based on big data according to claim 1, characterized in that, In step S1, the method for determining whether the vehicle's ignition status is abnormal is as follows: within the most recent time interval T, determine whether multiple ignition actions have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can drive normally. If a vehicle experiences multiple ignition attempts within a time interval T, and the vehicle's voltage range is within the abnormal battery voltage range during the first and last ignition attempts, and ignition fails, then the vehicle is considered to have difficulty starting. Where T is a preset value.

3. The method for identifying and reminding about battery depletion in automobiles based on big data according to claim 2, characterized in that, The method for identifying vehicle ignition difficulties is as follows: Step S11: Judgment based on the driver's ignition action: By obtaining the ignition status data and corresponding time within the most recent time period T, it can be determined whether the ignition status of the vehicle owner at the corresponding time is continuous ignition. Step S12: Ignition difficulty judgment based on ignition action judgment: Step S121: Obtain and calculate voltage and vehicle speed: First, obtain and calculate the voltage and vehicle speed at times t(n), t(n-1)...t(1) within the time interval T; Step S122: Threshold-based ignition count judgment: Within the time interval T, the calculated number of ignitions is compared with the set threshold N. If the number is less than the threshold, the ignition is considered normal and the judgment ends. If the number is greater than the threshold, the next step is to judge whether the voltage is abnormal. Step S123: Voltage-based judgment: The first and last ignition actions within the time interval T are obtained by judging the ignition action, and the lowest and highest voltages when the ignition state is 0 during the first and last ignition actions are calculated. If the ignition state is 0 during the first and last ignition actions, the corresponding highest voltage Vbmax is less than or equal to the set highest voltage threshold Vmax, and the corresponding lowest voltage Vbmin is less than or equal to the set lowest voltage threshold Vmin. That is, if Vbmin≤Vmin and Vbmax≤Vmax, then proceed to the next step of judgment; otherwise, the ignition is considered normal and the judgment ends. Step S124: Speed-based judgment: Based on the judgments in steps S121-S123, continue to judge the speed: By judging the ignition action, obtain the first ignition action and the last ignition action within the time interval T, and calculate the highest speed when the ignition state is 0 during the first ignition action and the last ignition action within the time interval T. If the ignition status is 0 during the period between the first and last ignition attempts, but the vehicle speed is greater than 0, the judgment ends and the ignition is considered normal. When the corresponding vehicle speed is equal to 0, it is considered that ignition is difficult, the judgment ends, and the ignition difficulty record is output: ["Owner ID", TimeC, ign_1_cnts], where TimeC is the time of the last ignition action, and ign_1_cnts is the number of ignitions within the time interval T; An ignition status of 0 indicates that no ignition action has occurred.

4. The method for identifying and reminding about battery depletion in automobiles based on big data according to claim 3, characterized in that, In step S11, the method for determining whether the ignition status of the vehicle owner at the corresponding time is continuous ignition is as follows: S1101: Obtain the ignition status data and corresponding time within the most recent T time interval, and form a time and ignition status key-value pair sorted in descending order by time. S1102: Based on the time series, examine the ignition state at a certain moment within a continuous time T and obtain the corresponding set: I(n) = {(t(n), ign(n)), (t(n-1), ign(n-1)) ... (t(1), ign(1))} where: (t(n), ign(n)) represents that the ignition state is ign(n) at time t(n), where the value of ign(n) has two states: 1 or 0. Let: 1 represents that ignition behavior has occurred, and 0 represents that ignition behavior has not occurred; S1103: If, during the continuous time interval from t(1) to t(n), all values ​​from ign(n) to ign(1) are equal to 1, then it is considered that continuous ignition action has occurred during this continuous time interval. S1104: Count the number of ignitions that occur within the time interval T by counting the number of ign(n) to ign(1) equal to 1.

5. The method for identifying and reminding about battery depletion in automobiles based on big data according to claim 1, characterized in that, In step S3, the method for sending the identification result of the battery being discharged to the vehicle owner is as follows: within Tm time after the battery being discharged is identified, send to the vehicle owner: ["Vehicle Owner ID", address, latitude and longitude, discharge time]; Where Tm is a preset value.

6. A big data-based automotive battery depletion identification and replacement reminder system, characterized in that, The system is used to implement the big data-based automotive battery depletion identification and replacement reminder method as described in any one of claims 1-5.

7. The automotive battery depletion identification and replacement reminder system based on big data according to claim 6, characterized in that, include: Real-time vehicle ignition difficulty identification module: Based on ignition status data, it obtains the most recent time interval and determines whether multiple ignition attempts have occurred, whether the vehicle's voltage range is normal, and whether the vehicle can drive normally. If a vehicle experiences multiple ignition attempts within a recent time interval, and the voltage range of the vehicle is within the abnormal voltage range of the battery during the first and last ignition attempts, and ignition fails, resulting in the inability to drive normally, then the vehicle is considered to have ignition difficulties. Auxiliary battery depletion judgment module: Based on the characteristics of battery depletion and the driving behavior data of an individual vehicle owner, it provides a basis for judging battery depletion; Battery power depletion judgment module: It receives the ignition difficulty recognition result output by the vehicle ignition difficulty recognition module and the auxiliary judgment feature field output by the auxiliary power depletion judgment module, and comprehensively judges the power depletion status of the vehicle battery. Battery low power replacement reminder module: It sends a low power information to the vehicle owner after the battery is low.

8. The automotive battery depletion identification and replacement reminder system based on big data according to claim 7, characterized in that, The driving behavior data of a single vehicle owner includes historical and current driving data, and calculates vehicle age, cumulative mileage, longest parking days, availability of charging range, and information on short-distance and low-speed driving based on the driving behavior data.

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