Methods, devices, storage media, and vehicles for indicating battery charging status.

Abstract

This invention discloses a method, apparatus, storage medium, and vehicle for providing charging reminders for a vehicle battery. The method includes: acquiring vehicle driving information and battery information during the process of a target driver controlling the vehicle; segmenting the battery charging process based on the battery information and merging the driving information into the segmented charging processes to obtain target driving data; determining the target driver's charging preference information based on the target driving data, wherein the charging preference information represents the target driver's preference for the timing of battery charging; determining the target battery capacity based on the charging preference information, wherein the target capacity represents the charging timing that satisfies the target driver's preference; and generating battery charging reminder information in response to the battery's actual capacity reaching the target capacity. This invention solves the technical problem of low accuracy in vehicle battery charging reminders.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a method, apparatus, storage medium, and vehicle for indicating battery charging in a vehicle. Background Technology

[0002] Currently, low battery warnings for vehicles are typically based on fixed values ​​to determine whether the vehicle needs recharging. This method cannot cater to the individual needs and habits of different car owners. By analyzing historical and real-time data, it's possible to more accurately predict when a car owner needs to recharge, thereby improving the driving and charging experience and achieving personalization. Analyzing historical and real-time vehicle data allows us to understand the owner's driving habits, charging habits, and daily driving patterns.

[0003] Based on the above data, it's possible to predict when a car owner will need to recharge and adjust certain settings of in-vehicle functions according to the owner's behavioral profile. For example, for owners who prefer to recharge when the battery is low, a charging reminder can be issued earlier; for owners who prefer to recharge when the battery is nearly depleted, the charging reminder can be delayed to meet the individual needs of different owners. However, the above charging reminders can only roughly estimate the charging timing and cannot accurately determine it. Therefore, the technical problem of low accuracy in battery charging reminders in vehicles still exists.

[0004] There is currently no effective solution to the technical problem of low accuracy of battery charging indications in the aforementioned vehicles. Summary of the Invention

[0005] This invention provides a method, apparatus, storage medium, and vehicle for providing charging reminders for batteries in vehicles, thereby addressing at least the technical problem of low accuracy in battery charging reminders in vehicles.

[0006] According to one aspect of the present invention, a method for providing a charging reminder for a battery in a vehicle is provided. The method may include: acquiring vehicle driving information and battery information of the vehicle's battery during the process of a target driver controlling the vehicle's movement, wherein the battery information represents the battery's charge state and / or charging state; segmenting the battery's charging process based on the battery information and merging the driving information into the segmented charging process to obtain target driving data, wherein the charging process is a time period consisting of a corresponding charging start time to a corresponding charging end time; determining the target driver's charging preference information based on the target driving data, wherein the charging preference information represents the target driver's preference for the timing of battery charging; determining the target battery charge level based on the charging preference information, wherein the target charge level represents the charging timing that satisfies the target driver's preference; and generating a battery charging reminder message in response to the battery's actual charge level reaching the target charge level.

[0007] Optionally, the target battery capacity is determined based on charging preference information, including: obtaining charging preference information corresponding to the target number of charging segments and battery information corresponding to the target number of charging start times; and determining the target battery capacity based on the target number of charging preference information and the target number of battery information.

[0008] Optionally, the target power is determined based on the target number of charging preference information and the target number of battery information, including: obtaining the average charging preference information of the target number of charging preference information and obtaining the average battery information of the target number of battery information; and determining the quotient between the average battery information and the average charging preference information as the target power.

[0009] Optionally, the battery information includes charging status information, wherein, based on the battery information, the charging segment of the battery is divided into segments, including: determining the time when the charging status information jumps from the idle state to the running state as the charging start time; determining the time when the charging status information jumps from the running state to the idle state as the charging end time; and determining the time period consisting of the same charging start time and charging end time as a charging segment.

[0010] Optionally, the driving information includes cumulative mileage and remaining mileage, and the target driving data includes target cumulative mileage and target remaining mileage. The process of merging the driving information into the segmented charging segments to obtain the target driving data includes: merging the cumulative mileage into the segmented charging segments to obtain the target cumulative mileage at the start of charging and the target cumulative mileage at the end of charging; and merging the remaining mileage into the segmented charging segments to obtain the target remaining mileage at the start of charging and the target remaining mileage at the end of charging.

[0011] Optionally, based on the target driving data, the charging preference information of the target driver is determined, including: obtaining a first difference between the target cumulative driving range at the start time of charging of a charging segment and the target cumulative driving range at the end time of charging of the previous charging segment; obtaining a second difference between the target remaining driving range at the end time of charging of a charging segment and the target remaining driving range at the start time of charging of a charging segment; and determining the charging preference information based on the first difference and the second difference.

[0012] Optionally, determining charging preference information based on the first difference and the second difference includes: determining the quotient between the first difference and the second difference as the charging preference information.

[0013] Optionally, the driving information includes the vehicle's location information, and the charging prompt information includes navigation prompt information. The navigation prompt information is used to indicate whether the vehicle has driven to a target charging device to charge the battery. Specifically, in response to the battery's actual charge reaching a target charge level, navigation prompt information is generated, including: obtaining road information and charging device information of the road where the vehicle is located; determining the target charging device based on the road information, charging device information, and location information, wherein the target charging device is a charging device located at a distance less than or equal to a distance threshold from the vehicle; and generating navigation prompt information based on the charging device information of the target charging device.

[0014] According to another aspect of the present invention, a charging reminder device for a vehicle battery is also provided. The device may include: an acquisition unit, configured to acquire vehicle driving information and battery information of the vehicle battery during the process of a target driver controlling the vehicle to drive, wherein the battery information is used to represent the battery's charge state and / or charging state; a merging unit, configured to segment the battery charging segments based on the battery information and merge the driving information into the segmented charging segments to obtain target driving data, wherein the charging segment is a time period consisting of a corresponding charging start time to a corresponding charging end time; a first determining unit, configured to determine the target driver's charging preference information based on the target driving data, wherein the charging preference information is used to represent the target driver's preference for the timing of battery charging; a second determining unit, configured to determine the target battery charge level based on the charging preference information, wherein the target charge level is used to represent the charging timing that satisfies the target driver's preference; and a generating unit, configured to generate battery charging reminder information in response to the battery's actual charge level reaching the target charge level.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the charging reminder method for a vehicle battery according to the present invention.

[0016] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program, when running, executes the charging reminder method for a vehicle battery according to the embodiments of the present invention.

[0017] According to another aspect of the present invention, a computer program product is also provided. This computer program product includes a computer program that, when executed by a processor, implements the battery charging reminder method in a vehicle described in the present application embodiments.

[0018] In this embodiment of the invention, during the process of the target driver controlling the vehicle's movement, vehicle driving information can be collected, and the battery's charge status and / or charging status can be detected to obtain corresponding battery information. The battery charging segment can be segmented based on the battery information, and driving information can be merged into the segmented charging segment to obtain target driving data. Based on the target driving data, the target driver's preference for battery charging timing can be analyzed to obtain corresponding charging preference information. Based on the charging preference information, a target charge level that meets the target driver's preference is determined. If the battery's actual charge level reaches the target charge level during vehicle movement, a battery charging reminder can be generated. In this embodiment, by collecting and analyzing vehicle driving information and battery information, combined with analyzing the target driver's preference for battery charging timing, a more intelligent and personalized charging reminder service can be achieved. By evaluating the driver's charging timing preference, the system can understand their charging habits and behavioral patterns, providing a reference for subsequent charging reminders. The above method can better help drivers plan their charging trips rationally, improve charging efficiency, reduce the inconvenience and frustration caused by insufficient battery power, and enhance the driving experience and vehicle convenience. Through intelligent charging prompts and analysis, the system can achieve more intelligent and personalized charging management based on driver behavior preferences and vehicle status, providing a more convenient and intelligent experience for electric vehicle users. This improves the accuracy of battery charging prompts and solves the technical problem of low accuracy in vehicle battery charging prompts. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0020] Figure 1 This is a flowchart of a charging reminder method for a battery in a vehicle according to an embodiment of the present invention;

[0021] Figure 2 This is a flowchart of a method for pushing charging reminders based on driver personality factors according to an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of a battery charging indicator device in a vehicle according to an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] According to an embodiment of the present invention, an embodiment of a method for indicating the charging status of a battery in a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0026] Figure 1 This is a flowchart of a battery charging reminder method in a vehicle according to an embodiment of the present invention, such as... Figure 1 As shown, the method may include the following steps:

[0027] Step S102: During the process of the target driver controlling the vehicle to drive, obtain the vehicle's driving information and the battery information of the vehicle's battery.

[0028] In the technical solution provided in step S102 of the present invention, the vehicle can be a new energy vehicle, such as an electric vehicle. The target driving object can be the driver in the vehicle, such as the vehicle owner. Driving information, also known as driving data, can be used to better understand the vehicle's status and location information. For example, it can include the cumulative driving mileage, remaining driving range, and the longitude and latitude of the vehicle's location. It should be noted that the above driving information is only an example and is not specifically limited. As long as the driving information can be used to determine the charging time for charging the battery in the vehicle, it is within the protection scope of the embodiments of the present invention.

[0029] Optionally, cumulative mileage refers to the total distance the vehicle has traveled since it rolled off the production line, usually expressed in kilometers (km). This data reflects the vehicle's usage frequency and historical driving patterns, helping to assess the vehicle's wear and tear, maintenance intervals, and usage condition. Remaining Drive Distance indicates the predicted driving range the car can maintain until the battery is depleted, also usually expressed in kilometers (km). This data is predicted based on the current battery level and the vehicle's average energy consumption, helping drivers understand the vehicle's current range and avoid situations where they cannot drive due to insufficient battery power. Remaining drive distance is an important reference for drivers in trip planning and charging decisions, helping them to rationally arrange driving routes and charging plans. Location longitude and location latitude are the geographic coordinates of the vehicle's current location, representing its longitude and latitude respectively. These can be used for real-time positioning and route tracking, helping navigation systems accurately locate the vehicle's position and provide real-time navigation guidance. By recording vehicle location information, real-time vehicle monitoring and management can be achieved, and drivers can also find nearby service facilities such as gas stations and charging stations.

[0030] Optionally, the battery information can be used to represent the battery's state of charge and / or charging status, and may include charging data and power information, wherein the charging data corresponds to the charging status and the power information corresponds to the state of charge.

[0031] Optionally, charging data can record the vehicle's current charging status and charging method, helping to monitor and manage the vehicle's charging situation. Charging status indicates the vehicle's current charging condition, typically including two states: idle and charging. Idle status indicates that the vehicle is not currently charging, meaning the charging socket is idle and the vehicle is not connected to charging equipment. Charging status indicates that the vehicle is currently charging, the charging socket is connected to charging equipment, and the vehicle is receiving electrical energy. By recording the charging status, the vehicle's charging situation can be monitored in real time, helping the driver understand whether the vehicle is charging and to perform charging operations promptly when needed. This ensures the vehicle has sufficient battery power, improving driving convenience and safety.

[0032] Optionally, the charging state indicates the vehicle's current charging method, typically including AC charging and DC charging. AC charging refers to the vehicle using AC power, generally applicable to home charging stations or public AC charging stations. DC charging refers to the vehicle using DC power, generally applicable to fast charging stations or DC charging piles, allowing for faster charging. Recording the charging state helps drivers understand the vehicle's current charging mode and select the appropriate charging method to meet charging needs in different scenarios. Simultaneously, monitoring the charging state also helps optimize charging efficiency, improving charging speed and effectiveness.

[0033] In summary, by recording charging status and charging method, the vehicle's charging situation can be monitored in real time, helping drivers to understand the charging status and method in a timely manner for appropriate charging operations. This data is crucial for vehicle management and charging efficiency, improving charging convenience and efficiency, thereby enhancing the user experience of electric vehicles.

[0034] Optionally, the State of Charge (SOC) displayed in the battery information refers to the current battery charge of the vehicle, usually expressed as a percentage (%). This parameter is crucial for electric vehicles because it reflects the battery's current charging status, i.e., how much charge remains for the vehicle. Instrument State of Charge (ISOC) is an integer representing the percentage of the battery's charge; that is, ISOC can also represent the battery's actual charge level. For example, if the instrument SOC value is 80%, it means the battery currently has 80% charge available for use. The instrument SOC value typically ranges from 0% to 100%, with 0% indicating a depleted battery and 100% indicating a fully charged battery. Instrument SOC is an important indicator for drivers to understand the vehicle's battery status, helping them determine whether the vehicle needs charging and when to charge. Real-time monitoring and recording of instrument SOC can help drivers plan charging trips effectively, avoiding disruptions to driving safety and convenience due to insufficient battery power.

[0035] Optionally, by recording the instrument cluster's State of Charge (SOC) data, the vehicle system can monitor changes in battery charge in real time, promptly reminding the driver to charge and ensuring the vehicle always maintains a sufficient charge. This improves the driver's understanding of the electric vehicle's charging status, while also increasing the convenience and comfort of using the vehicle.

[0036] In this embodiment, during the process of the target driver controlling the vehicle's movement, vehicle driving data and battery information can be collected.

[0037] Optionally, vehicle driving and battery information can be obtained. Driving information may include cumulative mileage, remaining range, and the vehicle's current location (longitude and latitude). Cumulative mileage represents the total mileage driven since the vehicle rolled off the production line, which can be used to assess the vehicle's usage frequency and condition, aiding in vehicle maintenance. Remaining range predicts the distance the vehicle can travel before the battery is depleted, helping drivers plan their trips and avoid running out of power. The vehicle's current location (longitude and latitude) provides its geographic coordinates, enabling real-time positioning and route tracking, helping navigation systems accurately locate the vehicle and plan suitable routes. Battery information may include battery level and charging data. Battery level information may include the instrument cluster's State of Charge (SOC), indicating the battery's current charging status as a percentage, a crucial indicator for drivers to understand the battery's condition. Charging data records the vehicle's current charging status and method, helping to monitor and manage the vehicle's charging status, improving charging efficiency and convenience.

[0038] Optionally, acquiring this driving and battery information can help drivers understand the vehicle's real-time status, enabling them to plan their trips and make charging decisions. Simultaneously, by monitoring and recording this information in real time, the vehicle system can promptly remind the driver to charge, ensuring the vehicle always has a sufficient charge and improving convenience and comfort. This data is crucial for the management and charging efficiency of electric vehicles, enhancing the user experience and safety.

[0039] Step S104: Based on the battery information, the charging segment of the battery is divided, and the driving information is merged into the divided charging segment to obtain the target driving data.

[0040] In the technical solution provided by step S104 of the present invention, the charging segment can be a time period consisting of the corresponding charging start time and the corresponding charging end time. The target driving data, also known as a new data field, can be used to record relevant information in the nth charging segment of the vehicle's history. For example, it can include the cumulative driving mileage and remaining range at the charging start and end times. It should be noted that the above-mentioned target driving data is merely an example and is not intended to be specific. By analyzing and calculating the target driving data, we can better understand the vehicle's charging behavior and the driver's charging habits, providing drivers with more scientific and reasonable charging suggestions. This also helps optimize the vehicle's range performance and charging efficiency, improving the user experience and convenience of electric vehicles.

[0041] In this embodiment, after obtaining the vehicle's driving information and the battery's battery information, the battery's charging segments can be segmented based on the battery information, and the driving information can be merged into the segmented charging segments to obtain the target driving data.

[0042] Optionally, the charging segments of the battery can be divided based on battery information. A charging segment can be defined as a time period consisting of the start and end times of charging. Such segmentation helps to refine the vehicle's charging behavior into multiple segments, enabling more precise analysis and monitoring of the charging status. Each charging segment includes time information for the start and end times of charging, as well as battery information such as the charging status and charging method during this period.

[0043] Optionally, driving information can be merged into the segmented charging segments to obtain the target driving data. This means that by correlating the vehicle's driving information with the charging segments, the driving situation in each charging segment can be recorded, such as the cumulative mileage at the start and end of charging and the remaining driving range. Such merging operations can help link charging behavior and driving behavior, providing more detailed and comprehensive data support for subsequent analysis and optimization.

[0044] In this embodiment of the invention, by analyzing and calculating target driving data, a better understanding of the vehicle's charging behavior and the driver's charging habits can be achieved, providing the driver with more scientific and reasonable charging suggestions. Simultaneously, by optimizing the vehicle's range performance and charging efficiency, the user experience and convenience of electric vehicles can be improved. Through the detailed analysis and operations described above, it is possible to achieve overall management and optimization of vehicle charging and driving behavior, thereby improving the performance and reliability of electric vehicles.

[0045] Step S106: Based on the target driving data, determine the charging preference information of the target driver.

[0046] In the technical solution of step S106 of the present invention, the charging preference information can be used to represent the degree of preference of the target driving object for the timing of battery charging, and can be used as a personality factor for the driver to judge the timing of charging, and can also be called a derived field.

[0047] In this embodiment, after segmenting the battery charging segment based on battery information and merging driving information into the segmented charging segment to obtain target driving data, the charging preference information of the target driving object can be determined based on the target driving data. That is, derived fields can be calculated based on the defined new data fields.

[0048] Optionally, determining the charging preferences of the target driver based on the target driving data is crucial. This step aims to understand the target driver's charging preferences by analyzing the target driving data—that is, under what circumstances the target driver is more inclined to charge, and under what circumstances the target driver is more inclined to delay charging. Determining the target driver's charging preferences can achieve the following objectives: Personalized charging recommendations, i.e., providing personalized charging suggestions based on the target driver's charging preferences, such as suggesting charging when the battery has a certain remaining percentage, or providing suitable charging solutions based on the driving route and destination; Charging behavior analysis, i.e., understanding the target driver's charging preferences helps optimize charging strategies and improve charging efficiency and convenience; and Improving user experience, i.e., helping the target driver better manage the electric vehicle's range and charging, improving user experience and ease of use.

[0049] In this embodiment of the invention, to determine the charging preference information of a target driver, data such as charging timing, charging frequency, and charging duration can be analyzed based on charging segments, driving information, and battery information in the target driving data to infer the target driver's charging preferences. Such analysis facilitates personalized charging management, improving the efficiency and comfort of electric vehicle use. In summary, the above method aims to determine the charging preference information of a target driver through target driving data, thereby providing drivers with personalized charging suggestions, optimizing charging strategies, and improving user experience and the convenience of using electric vehicles.

[0050] Step S108: Determine the target battery capacity based on charging preference information.

[0051] In the technical solution provided by step S108 of the present invention, the target battery level can be used to indicate the charging timing that satisfies the preferences of the target driver, and can be the timing for initiating a charging prompt.

[0052] In this embodiment, after determining the charging bias information of the target driving object based on the target driving data, the target battery capacity can be determined based on the charging preference information.

[0053] Optionally, determining the target battery capacity based on charging preference information is to meet the charging preferences of the target driver, i.e., to determine the appropriate charging time, in order to improve the driver's charging experience and the efficiency of electric vehicle use.

[0054] Optionally, the charging preference information of the identified target driver, including preferences for charging timing and frequency, can be analyzed in detail. Understanding the charging preferences of the target driver will help determine the most suitable charging strategy for that driver. Based on charging preference information, determining the target battery capacity refers to determining the appropriate charging state that the vehicle battery should reach. This target capacity can be determined according to the driver's charging preferences and driving needs to meet their preferences for charging timing and driving requirements. Determining the target battery capacity can also be used to determine when to issue a charging reminder, that is, to issue a charging reminder to the driver when the battery capacity is close to the target capacity, reminding them to charge. This helps the driver better manage the battery's charging state and avoid affecting driving safety and convenience due to insufficient power. By determining the target battery capacity based on charging preference information, more intelligent charging management can be achieved, charging efficiency can be improved, battery life can be extended, and the driver's charging experience and the ease of use of electric vehicles can also be enhanced.

[0055] In summary, the above methods aim to determine the target battery level based on the driver's charging preference information, providing an opportunity to initiate charging reminders, thereby improving the intelligence of charging management, optimizing charging strategies, enhancing user experience, and increasing the efficiency of electric vehicle use.

[0056] In this embodiment of the invention, the target battery level is determined based on charging preference information, thereby determining the appropriate charging time to improve the driver's charging experience and the efficiency of electric vehicle use. By accurately determining the target battery level and initiating a charging reminder, the driver can charge the battery in a timely manner when the battery level is close to the target level, avoiding situations where insufficient power prevents driving. This ensures the vehicle always has sufficient power, improving driving convenience and safety. Accurately determining the timing of the charging reminder avoids charging too early or too late, effectively utilizing charging equipment and charging time, and improving charging efficiency. This saves charging time and costs, while extending battery life and improving the lifespan and economy of the electric vehicle. Accurately determining the target battery level and initiating a charging reminder based on the driver's charging preferences and driving needs enables personalized charging management. This allows for customized charging suggestions based on different drivers' habits and needs, improving user experience and meeting user requirements. Accurately determining the timing of the charging reminder helps drivers better manage the battery's charging status, avoiding disruptions to driving plans due to insufficient power, and increasing driver trust and comfort with the electric vehicle. This enhances the user experience and increases user favorability towards electric vehicles.

[0057] In conclusion, by precisely determining when to issue charging reminders, appropriate charging management can be achieved, improving charging efficiency, extending battery life, enabling personalized charging management, enhancing user experience, and increasing the ease of use of electric vehicles. This intelligent charging management approach will provide drivers with a more convenient, efficient, and comfortable charging experience, promoting the popularization and development of electric vehicles.

[0058] In step S110, in response to the battery's actual charge reaching the target charge, a battery charging reminder message is generated.

[0059] In the technical solution provided by step S110 of the present invention, the actual battery level can be the vehicle's ISOC. The charging prompt information may include battery level prompt information and navigation reminders. The battery level prompt information can be used to indicate that the current battery level is low and charging is required. The navigation reminder can be used to indicate that navigation to a nearby charging station is possible to charge the battery. It should be noted that the above charging prompt information is only an example and is not intended to be specific.

[0060] In this embodiment, when the actual battery charge reaches the target charge level, a battery charging reminder message can be generated.

[0061] Optionally, when the battery's actual charge level reaches the target level, the system will generate a battery charging reminder. This step aims to remind the driver to charge the battery in a timely manner to ensure the vehicle's range and improve convenience and safety.

[0062] Optionally, the actual battery charge typically refers to the vehicle battery's ISOC, i.e., the current percentage of battery charge. The target charge is the battery's target charge determined using the method described above, representing the appropriate charging state the vehicle should achieve. When the battery's actual charge reaches the target charge, a charging reminder can be generated. These reminders can include battery charge warnings and navigation alerts: The battery charge warning might alert the driver that the battery is low and needs charging. This alert helps the driver recognize the low battery level promptly, preventing them from being unable to drive due to a depleted battery. Alternatively, navigation could guide the driver to a nearby charging station. This alert helps the driver find the nearest charging station for convenient charging.

[0063] Optionally, generating a charging reminder when the battery's actual charge reaches the target level can help drivers plan charging time and location more effectively, improving charging efficiency. This avoids disrupting driving plans due to insufficient battery power, enhancing the convenience and efficiency of vehicle use. Generating battery charging reminders can prompt drivers to charge in a timely manner, ensuring smooth driving. This improves the user experience, increasing user trust and comfort in electric vehicles.

[0064] In summary, the above methods aim to generate a charging reminder message when the battery's actual charge reaches the target charge level, prompting the driver to charge the battery in a timely manner. This optimizes charging management, improves charging efficiency and vehicle convenience, and enhances user experience and the ease of use of electric vehicles.

[0065] In steps S102 to S110 of this application, during the process of the target driver controlling the vehicle's movement, vehicle driving information can be collected, and the battery's charge status and / or charging status can be detected to obtain corresponding battery information. The battery charging segment can be segmented based on the battery information, and driving information can be merged into the segmented charging segment to obtain target driving data. Based on the target driving data, the target driver's preference for battery charging timing can be analyzed to obtain corresponding charging preference information. Based on the charging preference information, a target charge level that meets the target driver's preference is determined. If the battery's actual charge level reaches the target charge level during vehicle movement, a battery charging reminder can be generated. In this embodiment, by collecting and analyzing vehicle driving information and battery information, combined with analyzing the target driver's preference for battery charging timing, a more intelligent and personalized charging reminder service can be achieved. By evaluating the driver's charging timing preference, the system can understand their charging habits and behavioral patterns, providing a reference for subsequent charging reminders. The methods described above can better help drivers plan their charging trips, improve charging efficiency, reduce the inconvenience and frustration caused by insufficient battery power, and enhance the driving experience and vehicle convenience. Through intelligent charging prompts and analysis, the system can achieve more intelligent and personalized charging management based on driver behavior preferences and vehicle status, providing a more convenient and intelligent experience for electric vehicle users. This achieves the technical effect of improving the accuracy of battery charging prompts in vehicles, solving the technical problem of low accuracy in battery charging prompts.

[0066] The method described in this embodiment will be further described below.

[0067] As an optional embodiment, step S108, determining the target battery capacity based on charging preference information, includes: acquiring charging preference information corresponding to the target number of charging segments, and battery information corresponding to the target number of charging start times; and determining the target capacity based on the target number of charging preference information and the target number of battery information.

[0068] In this embodiment, during the process of determining the target battery capacity based on charging preference information, the charging preference information corresponding to each of the target number of charging segments, as well as the battery information corresponding to each of the target number of charging start times, can be obtained. The target capacity can be determined based on the target number of charging preference information and the target number of battery information. The target number can be a preset value or a value set according to actual conditions, for example, it can be preset to 50. It should be noted that the above-described method of setting the target number and the value are only illustrative examples and are not specifically limited here.

[0069] Optionally, if it is necessary to determine the target power level, battery information of the target number of charging segments and the target number of charging preference information can be collected in a recent period to calculate the target power level.

[0070] Optionally, a target number of charging segments are acquired, each corresponding to charging behavior over a period of time. For each charging segment, the system collects and records corresponding charging preference information, including preferences for charging timing, charging frequency, etc. This information helps the system understand the driver's charging habits and preferences. Battery information corresponding to the start time of the target number of charging segments can also be acquired, i.e., the battery charge level at the start of each charging segment is recorded, such as ISOC. This battery information can be used to determine the charge state at the start of the charging segment, providing data support for subsequent calculation of the target charge level. Based on the target number of charging preference information and battery information, each charging segment is analyzed and calculated to determine the target charge level. By comprehensively considering the charging preference information and battery information, the target charge level for each charging segment can be calculated, i.e., the charge level required to be achieved at the start of each charging segment.

[0071] Optionally, if a target battery level needs to be determined, battery information and charging preference information for the target number of charging segments over a recent period can be collected. This provides a more comprehensive understanding of the driver's charging behavior and preferences, leading to a more accurate calculation of the target battery level. Using the above method, the target battery level can be determined by acquiring the target number of charging segments, corresponding charging preference information, and battery information. Such refined operations help the system more accurately formulate personalized charging strategies for drivers, improving the efficiency and intelligence of charging management.

[0072] As an optional embodiment, determining the target power capacity based on the target number of charging preference information and the target number of battery information includes: obtaining the average charging preference information of the target number of charging preference information and obtaining the average battery information of the target number of battery information; and determining the quotient between the average battery information and the average charging preference information as the target power capacity.

[0073] In this embodiment, during the process of determining the target power level based on the target amount of charging preference information and battery information, the average charging preference information of the target amount of charging preference information and the average battery information of the target amount of battery information can be obtained. The quotient between the average battery information and the average charging preference information is determined as the target power level.

[0074] Optionally, the system acquires a target amount of charging preference information, including charging preference information for each charging segment. This information is then averaged to calculate an average charging preference. This provides a comprehensive charging preference profile reflecting the overall trend of driver charging preferences. Alternatively, the system acquires a target amount of battery information, including battery information at the start of each charging segment, such as ISOC. This information is then averaged to calculate an average battery information profile. This provides a comprehensive battery information profile reflecting the overall battery status at the start of each charging segment. The quotient between the average battery information and the average charging preference information is used as the target battery level. By calculating the quotient between the average battery information and the average charging preference information, the system obtains a comprehensive target battery level value. This value reflects the overall charging preference and battery status, thus determining a suitable target battery level.

[0075] The above method allows for the determination of the target battery level by acquiring the average value of charging preference information and battery information for the target quantity and comparing them. This simplified approach helps the system determine the target battery level more quickly and intuitively, providing drivers with a more intelligent and convenient charging management service.

[0076] For example, you can obtain charging preference information (Charging_personality) for the 50 most recent charging segments. (n) The average value of the above 50 charging preference information can be determined, that is, the average charging preference information (Charging_personality_avg), where Charging_personality_avg∈(0,1).

[0077] For another example, it is possible to obtain the battery information (Start_ISOC) at the start time of each of the most recent 50 charging segments. (n) The average value of the above 50 battery information can be determined, that is, the average battery information (Start_ISOC_avg), where Start_ISOC_avg∈(0,1).

[0078] As an alternative example, the target power can be determined using the following formula:

[0079]

[0080] As an optional embodiment, the battery information includes charging status information. In step S104, based on the battery information, the charging segment of the battery is divided, including: determining the time when the charging status information jumps from the idle state to the running state as the charging start time; determining the time when the charging status information jumps from the running state to the idle state as the charging end time; and determining the time period composed of the same charging start time and charging end time as a charging segment.

[0081] In this embodiment, during the process of segmenting the battery charging segment based on battery information, the moment when the charging status information transitions from an idle state to a running state can be determined as the charging start time. The moment when the charging status information transitions from a running state to an idle state can be determined as the charging end time. The time period consisting of the same charging start time and charging end time can be determined as a charging segment. The battery information may include charging status information, also known as Charge Status signal data.

[0082] Optionally, charging segments can be segmented based on the Charge Status signal data to identify the start and end times of charging and divide them into different charging segments.

[0083] Optionally, Charge Status signal data can be used as the segmentation condition. Charge Status represents the vehicle's charging state, including two states: "idle" and "charging," i.e., idle state and running state. Based on the data upload frequency, Charge Status data can be acquired periodically and its changes monitored. If Charge Status transitions from "idle" to "charging," it indicates that the vehicle has started charging from the idle state; if Charge Status transitions back to "idle," it indicates that charging has ended.

[0084] Optionally, when the Charge Status changes from "Idle" to "Charging," this moment can be recorded as the start of charging. This moment marks the beginning of the charging operation. When the Charge Status changes from "Charging" to "Idle," this moment can be recorded as the end of charging. This moment indicates that the vehicle has completed the charging operation, and the charging segment can be considered complete.

[0085] Optionally, the time period from the start of charging to the end of the first charge is divided into a charging segment. This charging segment represents a complete charging process, including the entire process from the start to the end of charging. By dividing the charging process into different segments, the system can better monitor and analyze the vehicle's charging behavior, understand the start and end times of each charge, and thus track and manage the charging process.

[0086] In this embodiment of the invention, the above method can accurately segment charging segments based on Charge Status signal data, identify the start and end times of charging, help monitor and manage vehicle charging behavior, and provide effective recording and analysis of the vehicle charging process. This improves the monitoring and management level of vehicle charging behavior and ensures the accuracy and reliability of the charging process.

[0087] As an optional embodiment, the driving information includes cumulative driving mileage and remaining driving mileage, and the target driving data includes target cumulative driving mileage and target remaining driving mileage. In step S104, the driving information is merged into the segmented charging segments to obtain the target driving data, which includes: merging the cumulative driving mileage into the segmented charging segments to obtain the target cumulative driving mileage corresponding to the start time of charging and the target cumulative driving mileage corresponding to the end time of charging; merging the remaining driving mileage into the segmented charging segments to obtain the target remaining driving mileage corresponding to the start time of charging and the target remaining driving mileage corresponding to the end time of charging.

[0088] In this embodiment, during the process of merging driving information into the segmented charging segments, the cumulative driving mileage can be merged into the segmented charging segments to obtain the target cumulative driving mileage at the start time of charging and the target cumulative driving mileage at the end time of charging. The remaining driving mileage can also be merged into the segmented charging segments to obtain the target remaining driving mileage at the start time of charging and the target remaining driving mileage at the end time of charging. The driving information can include the cumulative driving mileage and the remaining driving mileage. The target driving data can include the target cumulative driving mileage and the target remaining driving mileage.

[0089] Optionally, new data fields can be defined by combining driving information and charging segments.

[0090] Optionally, based on driving information and charging segments, four new data fields can be defined to record relevant information in the nth charging segment of the vehicle's history, including the cumulative driving mileage at the start and end times of charging and the remaining driving range.

[0091] Optionally, the target cumulative mileage at the start of charging (Start_OdometerValue(n)) can be used to record the cumulative mileage at the start of charging in the nth charging segment of the vehicle's history. Cumulative mileage refers to the total distance traveled from when the vehicle rolls off the production line to a specific point in time. Recording this value helps to understand the total mileage the vehicle has traveled at the start of each charging session, and aids in assessing the vehicle's usage and driving conditions during the charging process.

[0092] Optionally, the target cumulative mileage at the end of charging (End_OdometerValue(n)) can be used to record the cumulative mileage at the end of the nth charging segment in the vehicle's history. Similar to Start_OdometerValue(n), End_OdometerValue(n) can be used to record the vehicle's cumulative mileage at the end of each charging session, helping to understand the total mileage traveled by the vehicle during the charging process.

[0093] Optionally, the target remaining driving range at the start of charging (Start_RemainingDriveDistance(n)) can be used to record the remaining driving range at the start of charging in the nth charging segment of the vehicle's history. Remaining driving range refers to the estimated distance the vehicle's battery can travel at a specific time. Recording this value helps to understand the battery's charge level and expected driving range at the start of charging.

[0094] Optionally, the target remaining driving range at the end of charging (End_RemainingDriveDistance(n)) is recorded. This field records the remaining driving range at the end of the nth charging segment in the vehicle's history. Similar to Start_RemainingDriveDistance(n), End_RemainingDriveDistance(n) is used to record the vehicle's remaining driving range at the end of each charging session, helping to evaluate the battery's charging efficiency and range capability during the charging process.

[0095] In this embodiment of the invention, by defining the aforementioned new data fields, key information in each charging segment can be recorded and analyzed more comprehensively, including data such as mileage and remaining range, providing detailed recording and analysis support for the vehicle's charging behavior and range capability. This information helps assess vehicle usage and charging efficiency, assists drivers in better managing and planning charging trips, and improves the convenience and efficiency of electric vehicle use.

[0096] As an optional embodiment, step S106, based on the target driving data, determines the charging preference information of the target driver, including: obtaining a first difference between the target cumulative driving range at the start time of charging of a charging segment and the target cumulative driving range at the end time of charging of the previous charging segment; obtaining a second difference between the target remaining driving range at the end time of charging of a charging segment and the target remaining driving range at the start time of charging of a charging segment; and determining the charging preference information based on the first difference and the second difference.

[0097] In this embodiment, during the process of determining the charging preference information of the target driver based on target driving data, a first difference can be obtained between the target cumulative driving range at the start time of a charging segment and the target cumulative driving range at the end time of the previous charging segment. A second difference can be obtained between the target remaining driving range at the end time of a charging segment and the target remaining driving range at the start time of a charging segment. Charging preference information can be determined based on the first and second differences.

[0098] Optionally, the process of calculating derived fields based on the defined new data fields includes the cumulative range from the start time of the nth charging segment to the end time of the (n-1)th charging segment, the increased range, and a personality factor characterizing the driver's judgment of when to charge.

[0099] Optionally, interval_last_mileage(n), this derived field (first difference), can be used to represent the cumulative driving range from the start time of the nth charging segment to the end time of the (n-1)th charging segment; that is, the difference between the target cumulative driving range at the start time of this charging segment and the target cumulative driving range at the end time of the previous charging segment. The value of this field can be obtained by calculating the difference between Start_OdometerValue(n) and End_OdometerValue(n-1). Through the aforementioned first difference, the driving situation between two charging segments can be understood, that is, the total mileage traveled by the vehicle between the two charging segments.

[0100] That is, interval_last_mileage(n)=Start_OdometerValue(n)-End_OdometerValue(n-

[0101] 1).

[0102] Optionally, add_RemainingDriveDistance(n), this derived field (second difference), can be used to represent the increase in driving range during the nth charging segment, that is, the increase in battery driving range during charging, or the difference between the target remaining driving range at the end of the same charging segment and the target remaining driving range at the start of charging. The value of this field can be obtained by calculating the difference between End_RemainingDriveDistance(n) and Start_RemainingDriveDistance(n). This value indicates the increase in battery driving range during each charging session.

[0103] That is, add_RemainingDriveDistance(n)=End_RemainingDriveDistance(n)-Start_RemainingDriveDistance(n).

[0104] As an optional embodiment, determining charging preference information based on a first difference and a second difference includes: determining the quotient between the first difference and the second difference as the charging preference information.

[0105] In this embodiment, during the process of determining charging preference information based on the first difference and the second difference, the quotient between the first difference and the second difference can be determined as the charging preference information.

[0106] Alternatively, charging preference information can be determined using the following formula:

[0107]

[0108] Among them, Charging_personality (n) It can be used to represent charging preference information for the nth charging segment; interval_last_mileage (n) It can be used to represent the first difference;

[0109] add_RemainingDriveDistance (n-1) It can be used to represent the second difference.

[0110] Optionally, Charging_personality(n), a derived field, represents the personality factor of the driver's judgment on when to charge during the nth charging segment, reflecting the driver's behavioral preferences when replenishing energy. This field is obtained by calculating interval_last_mileage(n) divided by add_RemainingDriveDistance(n-1). This value reflects the driver's sensitivity to remaining driving range and battery power, and under what circumstances they would choose to replenish energy.

[0111] Optionally, when Charging_personality is close to 1, it indicates that the driver is more aggressive and tends to recharge the battery before it is about to run out of power; while when Charging_personality is close to 0, it indicates that the driver is more conservative and tends to recharge the battery when there is still a relatively large amount of power remaining.

[0112] In this embodiment of the invention, by calculating these derived fields, historical charging segment data can be analyzed in greater depth to understand the vehicle's driving conditions and driver behavior preferences during the charging process, providing more reference information for vehicle management and charging planning. These derived fields help optimize charging strategies and improve charging efficiency, while also helping drivers better manage the vehicle's range and charging behavior.

[0113] As an optional embodiment, the driving information includes the vehicle's location information, and the charging prompt information includes navigation prompt information. The navigation prompt information is used to indicate whether the vehicle has driven to a target charging device to charge the battery. In step S110, in response to the battery's actual charge reaching the target charge, navigation prompt information for the battery is generated, including: obtaining road information of the road where the vehicle is located and charging device information; in response to the actual charge reaching the target charge, determining the target charging device based on the road information, charging device information, and location information, wherein the target charging device is a charging device that is less than or equal to a distance threshold from the vehicle; and generating navigation prompt information based on the charging device information of the target charging device.

[0114] In this embodiment, during the process of generating navigation prompts when the battery's actual charge reaches the target charge level, the target charging device can be determined based on road information, charging device information, and location information. Navigation prompts can be generated based on the charging device information of the target charging device, where driving information can include the vehicle's location information, i.e., the longitude and latitude of the vehicle's location. The charging prompts include navigation prompts. The navigation prompts can be used to indicate whether the vehicle needs to drive to the target charging device to charge the battery. The target charging device can be a charging device located less than or equal to a distance threshold from the vehicle, for example, the charging device closest to the vehicle's location. Road information can be real-time road information of the road where the vehicle is located. Charging device information can be used to indicate information such as the location of the charging device.

[0115] Optionally, the system acquires road information about the vehicle's location, including real-time road conditions, road type, and traffic status. Simultaneously, it also acquires information about surrounding charging equipment, including their location, type, and availability. This information is used to determine suitable charging equipment and plan the route. In response to the actual battery level reaching the target level, the system determines the target charging equipment based on road information, charging equipment information, and vehicle location information. Generally, the target charging equipment is defined as the nearest available charging equipment located less than or equal to a set distance threshold from the vehicle. This ensures the driver can easily and quickly reach the charging station. Based on the charging equipment information of the determined target charging equipment, the system generates navigation prompts. These prompts instruct the driver on how to reach the target charging equipment to charge the battery. This includes route planning, route guidance, and estimated arrival time to help the driver reach the charging equipment smoothly. Driving information may include the vehicle's location information, i.e., the longitude and latitude of the vehicle's location. The charging prompts include navigation prompts indicating whether the vehicle needs to proceed to the target charging equipment for charging.

[0116] Using the above method, when the battery's actual charge reaches the target charge level, a suitable target charging station can be determined based on road information, charging equipment information, and location information. Navigation prompts are then generated, providing drivers with intelligent charging navigation services and facilitating convenient and quick battery charging. This approach helps improve charging efficiency and the driver's charging experience, thereby optimizing the ease of use and user satisfaction of electric vehicles.

[0117] Optionally, the process involves considering the driver's personality factors in determining when to charge, current vehicle SOC information, and whether the owner's voice-driven navigation information has changed. The driver's personality factors in determining when to charge are calculated based on historical charging data and reflect the driver's behavioral preferences when recharging. When the current vehicle SOC drops to... At that time, the system will record the current moment as t1. This condition indicates that when the vehicle's battery level drops to a certain level (which may vary depending on the driver's personality), subsequent operations can be triggered.

[0118] Optionally, real-time road information and charging equipment information can be obtained using map software. Combining the vehicle's longitude and latitude information, the system can calculate the nearest charging station (equipment) to the vehicle's current location as x1. This method aims to provide drivers with information on the nearest charging equipment, facilitating charging when needed.

[0119] For example, the vehicle's infotainment system uses its speaker to ask the driver whether to change the navigation information based on their voice commands, thus triggering navigation prompts. At time t1, the system will ask the driver through the speaker: "Do you want to add x1 as a waypoint?"

[0120] Based on the driver's voice response and whether the navigation information has changed, the system will further determine whether to add the nearest charging station x1 as a waypoint to the navigation route. If the driver agrees to add x1 as a waypoint, the navigation route can be updated accordingly to include the charging station information.

[0121] In this embodiment of the invention, the above method can provide drivers with personalized charging prompts and navigation services based on their personality factors, vehicle SOC information, and real-time charging equipment information. This intelligent process helps drivers better plan their trips, manage charging needs, and improve the driving experience and route planning convenience. Simultaneously, by using voice-driven navigation information changes, it can promptly respond to drivers' needs and provide more personalized navigation services. This intelligent process contributes to improving the driver's driving experience and driving safety.

[0122] In this embodiment of the invention, during the process of the target driver controlling the vehicle's movement, vehicle driving information can be collected, and the battery's charge status and / or charging status can be detected to obtain corresponding battery information. The battery charging segment can be segmented based on the battery information, and driving information can be merged into the segmented charging segment to obtain target driving data. Based on the target driving data, the target driver's preference for battery charging timing can be analyzed to obtain corresponding charging preference information. Based on the charging preference information, a target charge level that meets the target driver's preference is determined. If the battery's actual charge level reaches the target charge level during vehicle movement, a battery charging reminder can be generated. In this embodiment, by collecting and analyzing vehicle driving information and battery information, combined with analyzing the target driver's preference for battery charging timing, a more intelligent and personalized charging reminder service can be achieved. By evaluating the driver's charging timing preference, the system can understand their charging habits and behavioral patterns, providing a reference for subsequent charging reminders. The above method can better help drivers plan their charging trips rationally, improve charging efficiency, reduce the inconvenience and frustration caused by insufficient battery power, and enhance the driving experience and vehicle convenience. Through intelligent charging prompts and analysis, the system can achieve more intelligent and personalized charging management based on driver behavior preferences and vehicle status, providing a more convenient and intelligent experience for electric vehicle users. This improves the accuracy of battery charging prompts and solves the technical problem of low accuracy in vehicle battery charging prompts.

[0123] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0124] Currently, OEMs are significantly increasing the amount of data collected for new energy vehicles, and equipment manufacturers related to new energy vehicles are also paying more and more attention to the data from their terminals. However, with the explosive growth in the amount of data uploaded by new energy vehicles, the value generated by the data has not increased accordingly. In particular, for a specific user, their historical driving data, charging data, location data, time data, etc. have not been studied in depth. As a result, new energy vehicles are still mainly regarded as mobile terminals with the value of transportation tools, and have not been able to leverage the in-depth research on the usage scenarios and usage methods of new energy vehicles in today's big data era.

[0125] Alternatively, as new energy vehicles serve as another mobile terminal for human life, people are increasingly inclined to customize vehicle interaction functions, and OEMs are also placing greater emphasis on customer personalization. Therefore, major OEMs and equipment manufacturers are monitoring vehicle driving data, charging data, and other data in real time to understand users' usage habits and behavioral preferences for new energy vehicle products in a data-driven manner.

[0126] Alternatively, in the current electric vehicle charging field, most systems rely on the vehicle's own Battery Management System (BMS) to monitor the battery's State of Charge (SOC) value and remind users to charge based on preset thresholds. When users need to charge, they typically search for nearby charging facilities through the in-vehicle navigation system or a mobile application (APP). While these systems provide convenience for charging services to some extent, they do not take into account users' personalized charging needs and preferences for charging timing.

[0127] Specifically, existing charging reminder systems typically only issue a reminder when the SOC value drops to a certain fixed threshold. This method ignores the different charging times that users may choose due to personal habits, travel arrangements, or electricity price fluctuations. Furthermore, existing charging device search functions usually only offer simple location-based searches and do not provide intelligent recommendations based on users' personalized needs.

[0128] In summary, current technology lacks personalized charging timing judgment and fails to determine the appropriate charging time based on factors such as user personality and habits. Users with different personalities may react and make different decisions when faced with low battery power. For example, some users may prefer to charge in advance when the battery is fully charged to avoid inconvenience in emergencies, while others may prefer to charge when the battery is nearly depleted to maximize driving range. Existing technology fails to fully consider these differences between users.

[0129] In one related technology, an intelligent method for determining electric vehicle charging time is proposed. This method calculates the distance to the target charging station and the vehicle's range, compares this result with a defined warning threshold, and monitors the driver's physiological characteristics to reflect their range anxiety level. The warning threshold is then adjusted based on the driver's range anxiety level and actual charging needs. This allows for timely and accurate charging of electric vehicles, effectively alleviating range anxiety and improving the travel quality for electric vehicle drivers.

[0130] Another related technology proposes a vehicle charging reminder method. This method involves acquiring a vehicle dataset of the target vehicle, where the dataset is used to determine at least the vehicle's historical driving and charging information; redefining the vehicle dataset to determine the target dataset for the target vehicle; calculating the charging timing based on the target dataset to obtain a target charging factor for the target vehicle, where the target charging factor is used to predict the expected charging timing for the target vehicle; and generating charging reminder information for the target vehicle based on the target charging factor, where the charging reminder information is used to provide a charging reminder at the expected charging timing. This method addresses the technical problem of low flexibility and accuracy in vehicle charging reminders and poor user experience caused by relying on fixed low battery warning values ​​for vehicle charging reminders.

[0131] However, the aforementioned technologies still cannot accurately pinpoint the specific charging time to issue a charging reminder, thus the technical problem of low accuracy in battery charging reminders in vehicles remains.

[0132] This invention proposes a method for pushing charging reminders based on driver personality factors. This method aims to address two core problems in the electric vehicle charging field: the lack of personalized charging timing judgment and the unintelligent nature of charging equipment information push notifications. By deeply analyzing the personality factors that influence a user's judgment of charging timing, and combining this with the vehicle's current State of Charge (SOC) value, a more accurate and personalized charging reminder and charging equipment information push service can be achieved. Specifically, by collecting and analyzing the user's historical charging behavior, personality factors that influence the user's judgment of charging timing are extracted, such as conservative, adventurous, or balanced. Simultaneously, combined with the vehicle's current SOC value, it is possible to determine whether the user currently needs charging and the appropriate charging time. After determining the user's charging needs, information on nearby charging equipment can be intelligently pushed based on the Baidu API. This information is based not only on geographical location but also on the user's travel planning. By integrating these factors, this invention can recommend the charging equipment that best suits the user's actual needs. By deeply analyzing the personality factors that influence a user's judgment of charging timing, and combining this with the vehicle's current battery SOC value, this invention aims to achieve a more accurate and personalized charging reminder and charging equipment information push service. This achieves the technical effect of improving the accuracy of battery charging indications in vehicles, and solves the technical problem of low accuracy of battery charging indications in vehicles.

[0133] The embodiments of the present invention will be further described below.

[0134] In this embodiment of the invention, by deeply analyzing the personality factors that influence users' decision to charge, factors such as charging habits, behavioral preferences, and daily routines of different users can be considered, thereby more accurately predicting users' charging needs. Different users may choose to charge at different times based on their personal habits and needs; therefore, analyzing user personality factors helps the system better understand user behavior patterns and provide personalized charging reminder services. Combining the vehicle's current SOC value, the appropriate charging time can be determined based on the vehicle's actual situation and the user's personality factors. By comprehensively considering user personality factors and the vehicle's battery status, the system can provide users with more accurate and personalized charging reminders, avoiding the limitations of relying solely on fixed threshold reminders. The aim is to provide intelligent charging equipment information push services. By analyzing user personality factors and real-time vehicle data, the system can intelligently push charging equipment information that meets user needs, such as charging pile locations, charging speeds, and charging costs, thereby improving user experience and enabling users to more easily find suitable charging equipment.

[0135] In summary, by comprehensively considering user personality factors and real-time vehicle data, personalized and accurate charging reminders and intelligent charging equipment information push services have been achieved, providing users with a better charging experience and promoting the development and innovation of the electric vehicle charging field.

[0136] Optionally, by collecting and analyzing users' historical charging behavior, personality factors that influence their decision to charge can be extracted, such as conservative, adventurous, or balanced. These personality factors reflect users' charging preferences and habits, helping the system to more accurately understand users' charging behavior patterns and needs. Historical charging behavior data can be collected, including charging time, frequency, and duration. Analyzing this data reveals users' charging habits and behavior patterns. Based on this historical charging behavior data, user personality factors can be extracted. For example, a conservative user might tend to charge when the battery is high to ensure the vehicle doesn't run out of power; while an adventurous user might prefer to delay charging until the battery is low to maximize driving range. The system can also combine this with the vehicle's current battery SOC value to determine whether the user needs to charge and the appropriate charging time. Based on the user's personality factors and the vehicle's actual condition, the system can provide personalized charging reminders and recommendations to ensure users charge at the most suitable time.

[0137] By combining users' personalized charging behavior patterns with personality factors, more accurate and personalized charging reminders and recommendations can be achieved. This personalized approach better meets user needs, enhances user experience, and also helps improve the charging efficiency and utilization rate of electric vehicles. After determining the user's charging needs, information on nearby charging facilities is intelligently pushed using the Baidu API. This information is based not only on geographical location but also on the user's travel plans, thus enabling a more intelligent and personalized recommendation service.

[0138] Optionally, based on factors such as the user's personality factors, historical charging behavior, and current SOC value, the system can determine the user's charging needs, including charging timing and charging amount. By comprehensively analyzing the user's behavioral patterns and preferences, the system can better understand the user's actual needs. Once the user's charging needs are determined, the system can access a map and intelligently push information about nearby charging devices. The map provides geolocation services and charging station information, and the system can obtain nearby charging station data based on the user's current location and travel plan. In addition to pushing nearby charging device information based on geolocation, this invention also considers the user's travel plan. By analyzing the user's travel path and destination, combined with charging needs, the system recommends the most suitable charging devices for the user. For example, if the user is traveling to a destination, the system will recommend charging stations along the way or near the destination, making it convenient for the user to charge en route or upon arrival. By comprehensively considering factors such as the user's charging needs, geolocation, and travel plan, the system can recommend charging devices that best meet the user's actual needs. It can intelligently match the user's travel and charging needs, providing personalized charging device recommendations, enabling users to find suitable charging stations more conveniently.

[0139] In summary, by combining factors such as user charging needs, geographical location, and travel planning, and using Baidu API to intelligently push information on nearby charging equipment, a more intelligent and personalized charging equipment recommendation service is achieved, providing users with a better charging experience and improving the charging efficiency and utilization rate of electric vehicles.

[0140] In this embodiment, Figure 2 This is a flowchart of a method for pushing charging reminders based on driver personality factors according to an embodiment of the present invention, such as... Figure 2 As shown, the method may include the following steps:

[0141] Step S201: Collect vehicle driving data, charging data and power information through the vehicle terminal.

[0142] In this embodiment, the vehicle terminal collects the vehicle's driving data, charging data, and battery information.

[0143] Optionally, the driving data specifically includes: cumulative mileage, remaining driving range, current longitude, and current latitude. The cumulative mileage, in km, is denoted as Odometer Value, representing the distance traveled since the vehicle rolled off the production line. The remaining driving range, in km, is denoted as Remaining Drive Distance, representing the predicted driving range until the battery is depleted. The current longitude, in degrees-minutes-seconds, is denoted as Longitude, representing the longitude of the vehicle's current location. The current latitude, in degrees-minutes-seconds, is denoted as Latitude, representing the latitude of the vehicle's current location.

[0144] Optionally, the charging data may include charging status and charging method. The charging status, in null units, is denoted as Charge Status and represents the current charging state of the vehicle (idle / charging), and is an enumeration type. The charging method, also in null units, is denoted as Charge State and represents the current charging method of the vehicle (AC charging / DC charging), and is an enumeration type.

[0145] Optionally, the battery information may include the instrument cluster SOC. The instrument cluster SOC, expressed as a percentage (ISOC), represents the current battery charge of the vehicle and is an integer.

[0146] Step S202: Upload the data to the data processing platform.

[0147] In this embodiment, the aforementioned driving data, charging data, and power data can be uploaded to the data processing platform.

[0148] Step S203: Divide the charging segment according to certain rules.

[0149] In this embodiment, the charging segment can be divided according to certain rules in the data processing platform.

[0150] Optionally, the Charge Status signal data can be used as the segmentation condition for charging segments. Based on the data upload frequency, if the Charge Status changes from "Idle" to "Charging", it is determined that the charging has started; if the Charge Status changes from "Charging" to "Idle", it is determined that the charging has ended. The period from the start of charging to the end of the first charging session is divided into one charging segment.

[0151] Step S204: Define new data fields based on the collected basic data fields of the charging segment.

[0152] In this embodiment, new data fields can be defined based on the charging segment and the aforementioned driving data.

[0153] Optionally, the cumulative mileage at the start of charging in the nth charging segment of the vehicle's history is denoted as Start_OdometerValue(n). The cumulative mileage at the end of charging in the nth charging segment of the vehicle's history is denoted as End_OdometerValue(n). The remaining driving range at the start of charging in the nth charging segment of the vehicle's history is denoted as Start_RemainingDriveDistance(n). The remaining driving range at the end of charging in the nth charging segment of the vehicle's history is denoted as End_RemainingDriveDistance(n).

[0154] Step S205: Obtain the derived fields according to certain calculation rules.

[0155] In this embodiment, derived fields can be calculated based on newly defined data fields.

[0156] Optionally, the cumulative range from the start time of the nth charging segment to the end time of the (n-1)th charging segment is denoted as: interval_last_mileage(n) = Start_OdometerValue(n) - End_OdometerValue(n-1); the increased range of the nth charging segment is denoted as: add_RemainingDriveDistance(n) = End_RemainingDriveDistance(n) - Start_RemainingDriveDistance(n).

[0157] Step S206: Extract key mileage parameters of historical charging segments based on historical charging behavior, and use them to characterize the personality factors of the driver in judging the timing of charging.

[0158] In this embodiment, the driver's personality factors can be determined based on the aforementioned derived fields.

[0159] Optionally, let the nth charging segment represent the driver's personality factor in judging the timing of charging as:

[0160]

[0161] Here, Charging_personality represents the driver's personality factor in judging when to charge, where Charging_personality∈(0,1). The closer Charging_personality is to 1, the more aggressive the driver is, meaning the driver will recharge the battery just before it is completely depleted; the closer Charging_personality is to 0, the more conservative the driver is, meaning the driver will recharge the battery when there is still a relatively large amount of charge remaining.

[0162] Optionally, record the Charging_personality of the most recent 50 charging segments. (n) The above 50 Charging_personality can be identified. (n) The average value of Charging_personality_avg, where Charging_personality_avg∈(0,1). Let Start_ISOC be the value corresponding to the most recent 50 charging segments. (n) The average value Start_ISOC_avg of the above 50 battery information can be determined, where Start_ISOC_avg∈(0,1).

[0163] Alternatively, the appropriate charging timing can be determined using the following formula:

[0164] Step S207: Drive navigation reminders based on driver personality factors, current vehicle SOC status, real-time road information, charging equipment information, etc.

[0165] In this embodiment, navigation prompts are driven by factors such as the driver's personality, the current vehicle SOC (actual battery level), real-time road information, and charging equipment information.

[0166] Optionally, the navigation information can be changed based on the driver's personality factors in determining the charging timing, the current vehicle SOC information, and the owner's voice-driven navigation. After the driver starts navigation, when the ISOC drops to [a certain value], [the navigation information will be updated accordingly]. Let's denote the current time as t1. Based on real-time road and charging equipment information obtained from the map, and combined with the vehicle's length and latitude information, calculate the nearest charging station (equipment) x1 to the vehicle at time t1. At time t1, the vehicle's infotainment system uses its speaker to ask, "Should we add x1 as a waypoint?" The navigation information is then updated based on the driver's voice prompts.

[0167] In this embodiment of the invention, during the process of the target driver controlling the vehicle's movement, vehicle driving information can be collected, and the battery's charge status and / or charging status can be detected to obtain corresponding battery information. The battery charging segment can be segmented based on the battery information, and driving information can be merged into the segmented charging segment to obtain target driving data. Based on the target driving data, the target driver's preference for battery charging timing can be analyzed to obtain corresponding charging preference information. Based on the charging preference information, a target charge level that meets the target driver's preference is determined. If the battery's actual charge level reaches the target charge level during vehicle movement, a battery charging reminder can be generated. In this embodiment, by collecting and analyzing vehicle driving information and battery information, combined with analyzing the target driver's preference for battery charging timing, a more intelligent and personalized charging reminder service can be achieved. By evaluating the driver's charging timing preference, the system can understand their charging habits and behavioral patterns, providing a reference for subsequent charging reminders. The above method can better help drivers plan their charging trips rationally, improve charging efficiency, reduce the inconvenience and frustration caused by insufficient battery power, and enhance the driving experience and vehicle convenience. Through intelligent charging prompts and analysis, the system can achieve more intelligent and personalized charging management based on driver behavior preferences and vehicle status, providing a more convenient and intelligent experience for electric vehicle users. This improves the accuracy of battery charging prompts and solves the technical problem of low accuracy in vehicle battery charging prompts.

[0168] According to embodiments of the present invention, a battery charging reminder device for a vehicle is also provided. It should be noted that this battery charging reminder device for a vehicle can be used to execute the battery charging reminder method for a vehicle described in the above embodiments.

[0169] Figure 3 This is a schematic diagram of a battery charging indicator device in a vehicle according to an embodiment of the present invention. Figure 3 As shown, the battery charging indicator device 300 in the vehicle may include: an acquisition unit 302, a merging unit 304, a first determining unit 306, a second determining unit 308, and a generating unit 310.

[0170] The acquisition unit 302 is used to acquire the vehicle's driving information and the battery information of the battery in the vehicle during the process of the target driving object controlling the vehicle to drive. The battery information is used to indicate the battery's charge status and / or charging status.

[0171] The merging unit 304 is used to segment the charging segment of the battery based on the battery information and merge the driving information into the segmented charging segment to obtain the target driving data. The charging segment is a time period consisting of the corresponding charging start time to the corresponding charging end time.

[0172] The first determining unit 306 is used to determine the charging preference information of the target driving object based on the target driving data, wherein the charging preference information is used to represent the target driving object's preference for the timing of battery charging.

[0173] The second determining unit 308 is used to determine the target battery capacity based on charging preference information, wherein the target battery capacity is used to represent the charging timing that satisfies the preferences of the target driving object.

[0174] The generation unit 310 is used to generate a battery charging reminder message in response to the battery's actual charge reaching the target charge.

[0175] Optionally, the second determining unit 308 may include: a first acquiring module, configured to acquire charging preference information corresponding to the target number of charging segments and battery information corresponding to the target number of charging start times; and a first determining module, configured to determine the target charge based on the target number of charging preference information and the target number of battery information.

[0176] Optionally, the first determining module may include: a first obtaining submodule, used to obtain the average charging preference information of the target number of charging preference information and the average battery information of the target number of battery information; and a first determining submodule, used to determine the quotient between the average battery information and the average charging preference information as the target power.

[0177] Optionally, the first control unit 304 may include: determining the time when the charging status information jumps from the idle state to the running state as the charging start time; determining the time when the charging status information jumps from the running state to the idle state as the charging end time; and determining the time period consisting of the same charging start time and charging end time as a charging segment.

[0178] Optionally, the merging unit 304 may include: a second determining module, used to determine the time when the charging state information jumps from the idle state to the running state as the charging start time; a third determining module, used to determine the time when the charging state information jumps from the running state to the idle state as the charging end time; and a fourth determining module, used to determine the time period composed of the same charging start time and charging end time as a charging segment.

[0179] Optionally, the merging unit 304 may include: a first merging module, used to merge the accumulated driving mileage into the segmented charging segments to obtain the target accumulated driving mileage corresponding to the start time of charging and the target accumulated driving mileage corresponding to the end time of charging; and a second merging module, used to merge the remaining driving mileage into the segmented charging segments to obtain the target remaining driving mileage corresponding to the start time of charging and the target remaining driving mileage corresponding to the end time of charging.

[0180] Optionally, the first determining unit 306 may include: a second obtaining module, used to obtain a first difference between the target cumulative driving range at the start time of charging of the charging segment and the target cumulative driving range at the end time of charging of the previous charging segment; a third obtaining module, used to obtain a second difference between the target remaining driving range at the end time of charging of the charging segment and the target remaining driving range at the start time of charging of the charging segment; and a fifth determining module, used to determine charging preference information based on the first difference and the second difference.

[0181] Optionally, the fifth determining module may include: a second determining submodule, used to determine the quotient between the first difference and the second difference as charging preference information.

[0182] Optionally, the generation unit 310 may include: a fourth acquisition module, used to acquire road information and charging equipment information of the road where the vehicle is located; a sixth determination module, used to determine the target charging equipment based on the road information, charging equipment information and location information in response to the actual power reaching the target power, wherein the target charging equipment is a charging equipment that is less than or equal to a distance threshold from the vehicle; and a generation module, used to generate navigation prompt information based on the charging equipment information of the target charging equipment.

[0183] In this embodiment of the invention, the acquisition unit 302 acquires vehicle driving information and battery information of the vehicle's battery during the process of the target driver controlling the vehicle's driving. The battery information is used to represent the battery's charge status and / or charging status. The merging unit 304 segments the battery's charging segments based on the battery information and merges the driving information into the segmented charging segments to obtain target driving data. The charging segment is a time period consisting of the corresponding charging start time to the corresponding charging end time. The first determining unit 306 determines the target driver's charging preference information based on the target driving data. The charging preference information is used to represent the target driver's preference for the timing of battery charging. The second determining unit 308 determines the target battery charge based on the charging preference information. The target charge is used to represent the charging timing that satisfies the target driver's preference. The generating unit 310 generates battery charging prompt information in response to the battery's actual charge reaching the target charge. This solves the technical problem of low accuracy of battery charging prompts in the vehicle and achieves the technical effect of improving the accuracy of battery charging prompts in the vehicle.

[0184] According to embodiments of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein the program executes the charging reminder method for a vehicle battery in the above embodiments.

[0185] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the charging reminder method for a vehicle battery in the above embodiments.

[0186] Embodiments of this application also provide a computer program product. Optionally, in this embodiment, the computer program product may include a computer program that, when executed by a processor, implements the battery charging reminder method in a vehicle according to the embodiments of this application.

[0187] According to an embodiment of the present invention, a vehicle is also provided for performing the vehicle battery charging reminder method of the present invention.

[0188] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0189] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0190] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0191] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0192] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0193] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for indicating battery charging in a vehicle, characterized in that, include: During the process of the target driving object controlling the vehicle to drive, the driving information of the vehicle and the battery information of the battery in the vehicle are acquired, wherein the battery information is used to represent the battery power information and the power information is used to represent the battery power status. Based on the battery information, the charging segment of the battery is divided, and the driving information is merged into the divided charging segment to obtain the target driving data. The charging segment is a time period consisting of the corresponding charging start time to the corresponding charging end time. Based on the target driving data, the charging preference information of the target driver is determined, wherein the charging preference information is used to represent the degree of preference of the target driver for the timing of charging the battery; Based on the charging preference information, a target battery capacity is determined, wherein the target battery capacity is used to represent the charging timing that satisfies the preferences of the target driver. In response to the battery's actual charge reaching the target charge level, a charging reminder message for the battery is generated; The driving information includes cumulative mileage and remaining mileage, and the target driving data includes target cumulative mileage and target remaining mileage. The process of merging the driving information into the segmented charging segments to obtain the target driving data includes: merging the cumulative mileage into the segmented charging segments to obtain the target cumulative mileage corresponding to the start time of charging and the target cumulative mileage corresponding to the end time of charging; and merging the remaining mileage into the segmented charging segments to obtain the target remaining mileage corresponding to the start time of charging and the target remaining mileage corresponding to the end time of charging. Based on the target driving data, determining the charging preference information of the target driver includes: obtaining a first difference between the target cumulative driving range at the start time of the charging segment and the target cumulative driving range at the end time of the previous charging segment; obtaining a second difference between the target remaining driving range at the end time of the charging segment and the target remaining driving range at the start time of the charging segment; and determining the quotient between the first difference and the second difference as the charging preference information. Determining the target battery capacity based on the charging preference information includes: obtaining the charging preference information corresponding to the target number of charging segments, and the battery information corresponding to the target number of charging start times; obtaining the average charging preference information of the target number of charging preference information, and obtaining the average battery information of the target number of battery information; and determining the quotient between the average battery information and the average charging preference information as the target battery capacity.

2. The method according to claim 1, characterized in that, The battery information also includes charging status information, wherein, based on the battery information, the charging segment of the battery is divided, including: The moment when the charging status information transitions from idle state to running state is determined as the charging start time. The moment when the charging status information transitions from the running state to the idle state is determined as the charging end time. The time period consisting of the same charging start time and the same charging end time is defined as the charging segment.

3. The method according to claim 1, characterized in that, The driving information includes the vehicle's location information, and the charging prompt information includes navigation prompt information. The navigation prompt information is used to indicate whether the vehicle has reached a target charging device to charge the battery. Specifically, in response to the battery's actual charge reaching the target charge level, navigation prompt information for the battery is generated, including: Obtain road information and charging equipment information of the road where the vehicle is located; In response to the actual battery level reaching the target battery level, a target charging device is determined based on the road information, the charging device information, and the location information, wherein the target charging device is a charging device located at a distance less than or equal to a distance threshold from the vehicle; The navigation prompt information is generated based on the charging device information of the target charging device.

4. A charging indicator device for a vehicle battery, characterized in that, The device is used to perform the charging reminder method for the battery in the vehicle according to any one of claims 1 to 3.

5. A processor, characterized in that, The processor is used to run a program, wherein the program, when run by the processor, executes the charging reminder method for the battery in the vehicle according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the charging reminder method for a battery in a vehicle as described in any one of claims 1 to 3.

7. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the charging reminder method for a battery in a vehicle as described in any one of claims 1 to 3.

8. A computer program product, characterized in that, The system includes a computer program that, when executed by a processor, implements the charging reminder method for the battery in the vehicle according to any one of claims 1 to 3.

9. A vehicle, characterized in that, Used to perform the charging reminder method for a battery in a vehicle as described in any one of claims 1 to 3.

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