Charging method, vehicle controller, cloud server and vehicle

Abstract

The present disclosure relates to the field of vehicle networking technology, and more particularly to a charging method, vehicle controller, cloud server, and vehicle. The method comprises: when the actual health of a target vehicle's battery is less than a health threshold, determining an actual optimized charging curve based on the actual health; wherein each actual optimized charging curve corresponds to a theoretical charging configuration; selecting at least one theoretical charging position that satisfies the theoretical charging configuration from the target vehicle's historical charging positions; wherein the theoretical charging position includes any one of the historical charging positions; and sending a charging instruction message to the target vehicle containing the actual optimized charging curve and the theoretical charging position.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle networking technology, and in particular to a charging method, a vehicle controller, a cloud server, and a vehicle. Background Art

[0002] Currently, users typically charge their vehicles at their own charging stations or at other charging stations. When using other charging stations, users often lack understanding of the compatibility between the charging station and the vehicle's battery, resulting in the vehicle's battery being unable to select the appropriate charging mode, which in turn shortens the vehicle's battery life.

[0003] Therefore, how to extend the life of vehicle batteries has become an urgent problem to be solved. Summary of the Invention

[0004] In order to solve the above technical problems, the present disclosure provides a charging method, a vehicle controller, a cloud server and a vehicle, which are used to solve the problem of how to extend the life of the vehicle's battery.

[0005] In a first aspect, the present application provides a charging method, comprising: when the actual health of a battery of a target vehicle is less than a health threshold, determining an actual optimized charging curve based on the actual health; wherein one actual optimized charging curve corresponds to one theoretical charging configuration information; screening at least one theoretical charging position that meets the theoretical charging configuration information from the historical charging positions of the target vehicle; wherein the theoretical charging position includes any one of the historical charging positions; sending charging indication information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle; wherein the charging indication information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging information and the theoretical charging position after the target vehicle is powered off.

[0006] In some feasible examples, the theoretical charging configuration information includes charging time and / or charging price; when the actual health of the battery of the target vehicle is less than the health threshold, the actual optimized charging curve is determined based on the actual health, including: when the actual health of the battery of the target vehicle is less than the health threshold and the actual health is less than or equal to the aging threshold, the actual optimized charging curve is determined based on the charging time and charging price.

[0007] In some feasible examples, the charging method adopted by the present disclosure also includes: when the actual health of the battery of the target vehicle is less than the health threshold, and the actual health is greater than the aging threshold, and the actual health is greater than the activation reversible capacity damage threshold corresponding to each health interval, obtaining the historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment; and using the historical charging curve as the actual optimized charging curve.

[0008] In some feasible examples, the charging method adopted by the present disclosure also includes: when the actual health of the battery of the target vehicle is less than the health threshold, and the actual health is greater than the aging threshold, and the actual health is lower than one or more activation reversible capacity damage thresholds, obtaining the number of optimizations corresponding to the health interval to which the actual health belongs; wherein the number of optimizations includes the total number of times the battery has been charged using the actual optimized charging curve in history; when the number of optimizations is less than the number threshold, generating an activation charging curve with reversible capacity loss activation as the optimization target; and using the activation charging curve as the actual optimized charging curve.

[0009] In some feasible examples, the charging method disclosed herein further includes: when the number of optimizations is greater than or equal to a threshold number of times, generating an extended charging curve with extending battery life as the optimization goal; and using the extended charging curve as the actual optimized charging curve.

[0010] In a second aspect, the present application provides a charging method, comprising: receiving charging indication information carrying an actual optimized charging curve and a theoretical charging position sent by a cloud server; wherein the charging indication information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after the target vehicle is powered off; after the target vehicle is powered off, obtaining the current actual charging position and the state of charge of the battery; when the actual distance between the theoretical charging position and the actual charging position is less than or equal to a distance threshold and the state of charge is less than the charge threshold, generating a first prompt information including the use of the actual optimized charging curve for charging; and in response to a selection operation for a charging function, charging is performed according to the actual optimized charging curve.

[0011] In some feasible examples, the charging method adopted by the present disclosure also includes: when the actual distance is greater than the distance threshold and the charge state is less than the charge threshold, generating a second prompt information for prompting whether to execute the target information; wherein the target information includes the duration of using AC charging being greater than a preset time; in response to the selection operation of executing the target information and receiving the selection operation of the charging function, charging is performed according to the actual optimized charging curve.

[0012] In some feasible examples, the charging method adopted by the present disclosure also includes: in response to the selection operation of executing the target information and without receiving the selection operation of the charging function, generating a third prompt information; wherein the third prompt information is used to prompt one or more of the battery health information and charging suggestions of the battery, and the battery health information includes the actual health.

[0013] In some feasible examples, the charging method disclosed herein further includes: in response to not executing a selection operation of target information and receiving a selection operation of a charging function, charging according to a preconfigured charging curve; wherein the preconfigured charging curve is different from the actual optimized charging curve.

[0014] In a third aspect, the present application provides a cloud server, comprising: a processing module, for determining an actual optimized charging curve based on the actual health of the battery of a target vehicle when the actual health of the battery is less than a health threshold; wherein, an actual optimized charging curve corresponds to a theoretical charging configuration information; the processing module, for screening at least one theoretical charging position that meets the theoretical charging configuration information from the historical charging positions of the target vehicle; wherein, the theoretical charging position includes any one of the historical charging positions; the processing module, for controlling the transceiver module to send charging indication information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle; wherein, the charging indication information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging information and the theoretical charging position after the target vehicle is powered off.

[0015] In a fourth aspect, the present application provides a vehicle controller, comprising: a transceiver module for receiving charging indication information carrying an actual optimized charging curve and a theoretical charging position sent by a cloud server; wherein the charging indication information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after the target vehicle is powered off; the transceiver module is also used to obtain the current actual charging position and the state of charge of the battery after the target vehicle is powered off; a processing module is used to generate a first prompt information including the use of the actual optimized charging curve for charging when the actual distance between the theoretical charging position and the actual charging position obtained by the transceiver module is less than or equal to a distance threshold and the state of charge is less than the charge threshold; the processing module is also used to charge according to the actual optimized charging curve in response to a selection operation of the charging function.

[0016] In a fifth aspect, the present application provides a vehicle, which includes the vehicle control as described above.

[0017] In a sixth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above method.

[0018] The technical solution provided by the present disclosure has the following advantages compared with the existing technology:

[0019] The charging method disclosed herein determines, when the actual health of a target vehicle's battery is less than a health threshold, that multiple instances of improper charging may have occurred, significantly reducing the actual health of the target vehicle's battery. Therefore, an actual optimized charging curve needs to be determined based on the actual health. Subsequently, at least one theoretical charging location that satisfies theoretical charging configuration information is selected from the target vehicle's historical charging locations. The theoretical charging location includes any of the historical charging locations. A charging instruction message containing the actual optimized charging curve and the theoretical charging location is sent to the target vehicle. The charging instruction message is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging location. Because the actual optimized charging curve better matches the target vehicle's battery, charging according to the actual optimized charging curve can slow the decline in the battery's actual health. This allows for real-time management of each vehicle's battery life, preventing significant reduction in battery life due to multiple instances of improper charging, and thus addresses the issue of extending vehicle battery life. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0021] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0022] Figure 1 exemplarily shows one of the flow charts of a charging method provided in the first embodiment;

[0023] Figure 2 2 is a flow chart of a charging method provided in the first embodiment;

[0024] Figure 3 Schematic diagram 3 of a charging method provided in the first embodiment is shown as an example;

[0025] Figure 4 Schematic diagram 4 of a charging method provided in the first embodiment is shown as an example;

[0026] Figure 5 FIG5 exemplarily shows a fifth flow chart of a charging method provided in the first embodiment;

[0027] Figure 66 is a flow chart of a charging method provided in the first embodiment;

[0028] Figure 7 FIG7 exemplarily shows a seventh flow chart of a charging method provided in the first embodiment;

[0029] Figure 8 FIG8 exemplarily shows an eighth flow chart of a charging method provided in the first embodiment;

[0030] Figure 9 FIG9 exemplarily shows a ninth flow chart of a charging method provided in the first embodiment;

[0031] Figure 10 exemplarily shows one of the structural diagrams of the cloud server provided in the second embodiment;

[0032] Figure 11 2 shows an exemplary structural diagram of the cloud server provided in the second embodiment;

[0033] Figure 12 exemplarily shows one of the structural diagrams of the vehicle controller provided in the second embodiment;

[0034] Figure 13 FIG2 exemplarily shows the second structural diagram of the vehicle controller provided in the second embodiment. DETAILED DESCRIPTION

[0035] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that, in the absence of conflict, the embodiments of the present disclosure and the features therein can be combined with each other.

[0036] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0037] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0038] In some examples, vehicle power-off in the presently disclosed embodiments refers to the process of transitioning from a normal operating state (e.g., engine operation or high-voltage system operation) to a completely powered-off state. In traditional fuel-powered vehicles, power-off primarily involves shutting down the engine and onboard electrical equipment; in electric vehicles, this also involves shutting down the high-voltage system. This process involves multiple steps, such as turning off the ignition, disconnecting power transmission, and shutting down electronic equipment, to ensure vehicle safety and avoid unnecessary battery drain.

[0039] Example 1

[0040] Figure 1 A schematic diagram of a charging method is shown in FIG. 1 , and the execution subject of this example may be a cloud server, such as Figure 1 As shown, the method includes:

[0041] S11. When the actual health of the battery of the target vehicle is less than a health threshold, determine an actual optimized charging curve based on the actual health, wherein one actual optimized charging curve corresponds to one theoretical charging configuration information.

[0042] In some examples, when the actual health of the current target vehicle is greater than or equal to a health threshold, the actual health of the battery of the next target vehicle is obtained.

[0043] In some examples, the charging method provided by the embodiments of the present disclosure further requires executing a process for obtaining the actual health of the battery of the target vehicle before executing S11. The process for obtaining the actual health of the battery of the target vehicle includes:

[0044] Obtain configuration information and historical operation information of the target vehicle's battery; wherein the configuration information includes one or more of the battery's capacity, charging mode, charging voltage, and charging current; and the historical operation information includes one or more of the historical charging locations and the charging time, charging cost, and charging depth at each historical charging location.

[0045] Determine the actual health of the battery based on configuration information and historical operating information.

[0046] For example, the configuration information and historical operation information can be input into the health model to calculate the health and obtain the actual health of the battery. The training process of the health model includes:

[0047] Obtain first training sample data and a first labeling result of the first training sample data, wherein the first training sample data includes historical configuration information and operation information of a battery of a vehicle, and the first labeling result includes battery health.

[0048] Inputting the first training sample data into the first neural network model for learning, and obtaining a first prediction result of the first neural network model on the first training sample data;

[0049] Based on the first prediction result and the first labeling result, the network parameters of the first neural network model are adjusted until the first neural network model converges to obtain a health model.

[0050] In some examples, determining the actual health of the battery based on the configuration information and the historical operating information includes:

[0051] At least one preset battery health algorithm is used to calculate the health corresponding to the operating information and the configuration information, and a theoretical health calculated by each preset battery health algorithm is obtained; based on the theoretical health, the actual health of the battery is obtained.

[0052] Exemplarily, the actual health is equal to an average value of the theoretical healths; or, the actual health is equal to a minimum value of the theoretical healths.

[0053] In some examples, the cloud server pre-configures a correspondence between different health intervals and theoretically optimized charging curves. This correspondence can then be queried based on the actual health, and the theoretically optimized charging curve for the health interval in which the actual health falls is determined as the actual optimized charging curve.

[0054] Alternatively, if the actual health of the target vehicle's battery is less than a health threshold and less than or equal to an aging threshold, an actual optimized charging curve is determined based on the charging time and charging price. Alternatively, if the actual health of the target vehicle's battery is less than a health threshold, greater than an aging threshold, and greater than the activation reversible capacity damage threshold corresponding to each health interval, a historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment is obtained, and the historical charging curve is used as the actual optimized charging curve. Alternatively, if the actual health of the target vehicle's battery is less than a health threshold, greater than an aging threshold, and lower than one or more activation reversible capacity damage thresholds, the number of optimizations corresponding to the health interval to which the actual health belongs is obtained. The number of optimizations includes the total number of times the battery has been charged using the actual optimized charging curve in history. If the number of optimizations is less than a number threshold, an activation charging curve is generated with reversible capacity loss activation as the optimization objective, and the activation charging curve is used as the actual optimized charging curve. Alternatively, if the number of optimizations is greater than or equal to the number threshold, an extended charging curve is generated with battery life extension as the optimization objective, and the extended charging curve is used as the actual optimized charging curve.

[0055] S12: Filter at least one theoretical charging position that satisfies the theoretical charging configuration information from the historical charging positions of the target vehicle, wherein the theoretical charging position includes any one of the historical charging positions.

[0056] In some examples, because charging devices deployed at different charging locations have different charging configuration information, the charging curves that can be output by these charging devices differ. Therefore, it is necessary to select at least one theoretical charging location from the target vehicle's historical charging locations that meets the theoretical charging configuration information. This prevents the target vehicle from being charged using the pre-configured charging curve when at that theoretical charging location, potentially damaging the battery.

[0057] In some examples, a user profile corresponding to the target vehicle can be generated based on the target vehicle's historical charging locations and charging data at each historical charging location. Thus, when the cloud server checks the target vehicle's battery, it can determine the user profile corresponding to the target vehicle's vehicle ID based on the target vehicle's corresponding vehicle ID. Subsequently, based on the user profile and the theoretical charging configuration information, at least one theoretical charging location that satisfies the theoretical charging configuration information is selected from the target vehicle's historical charging locations.

[0058] S13: Sending charging instruction information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle. The charging instruction information is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off based on the actual charging information and the theoretical charging position.

[0059] As can be seen from the foregoing, the charging method provided by the disclosed embodiments, when the actual health of the target vehicle's battery is less than a health threshold, indicates that multiple instances of improper charging may have occurred, significantly reducing the actual health of the target vehicle's battery. Therefore, it is necessary to determine an actual optimized charging curve based on the actual health. Subsequently, at least one theoretical charging position that satisfies the theoretical charging configuration information is selected from the target vehicle's historical charging positions; the theoretical charging position includes any one of the historical charging positions. Charging instruction information containing the actual optimized charging curve and the theoretical charging position is sent to the target vehicle. The charging instruction information is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging position. Because the actual optimized charging curve is more consistent with the target vehicle's battery, charging according to the actual optimized charging curve can slow the rate at which the battery's actual health deteriorates. This allows for real-time management of each vehicle's battery life, preventing a significant reduction in battery life due to multiple instances of improper charging.

[0060] In some feasible examples, the theoretical charging configuration information includes charging time and / or charging price; Figure 1 ,like Figure 2 As shown, the above S11 can be specifically implemented through the following S110.

[0061] S110 : When the actual health of the battery of the target vehicle is less than a health threshold and is less than or equal to an aging threshold, determine an actual optimized charging curve based on charging time and charging price.

[0062] In some examples, the healthy threshold, the aging threshold, and the activation reversible capacity damage threshold are different. For example, the aging threshold can be 95%.

[0063] In some examples, the cloud server calculates the charging time required to charge the battery to 100% SOC using different theoretically optimized charging curves based on the target vehicle's battery's current remaining state of charge (SOC). The server then calculates the corresponding charging cost based on the product of the charging time and the charging price. The theoretically optimized charging curve corresponding to the minimum charging cost is then used as the actual optimized charging curve. If multiple theoretically optimized charging curves correspond to the minimum charging cost, the theoretically optimized charging curve corresponding to the minimum charging time is used as the actual optimized charging curve.

[0064] As can be seen from the foregoing, the charging method provided by the disclosed embodiments, when the actual health of a target vehicle's battery is less than a health threshold, indicates that multiple charging failures may have occurred, significantly reducing the actual health of the target vehicle's battery. Therefore, an actual optimized charging curve is determined based on charging time and charging price. Subsequently, at least one theoretical charging location that satisfies the theoretical charging configuration information is selected from the target vehicle's historical charging locations; the theoretical charging location includes any of the historical charging locations. Charging instruction information containing the actual optimized charging curve and the theoretical charging location is sent to the target vehicle. The charging instruction information is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging location. Because the actual optimized charging curve is more consistent with the target vehicle's battery, charging according to the actual optimized charging curve can slow the rate at which the battery's actual health deteriorates. This allows for real-time management of each vehicle's battery life, preventing significant reductions in battery life due to multiple charging failures.

[0065] In some possible implementations, combining Figure 2 ,like Figure 3 As shown, the charging method provided in the embodiment of the present disclosure further includes S14 and S15.

[0066] S14. When the actual health of the battery of the target vehicle is less than the health threshold, the actual health is greater than the aging threshold, and the actual health is greater than the activation reversible capacity damage threshold corresponding to each health interval, obtain the historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment.

[0067] In some examples, the cloud server stores historical optimized charging curves issued for each vehicle ID, along with the time of issuance. Subsequently, when the cloud server determines that the actual health of the target vehicle's battery is less than a health threshold, greater than an aging threshold, and greater than the activation reversible capacity damage threshold corresponding to each health interval, it retrieves at least one historical optimized charging curve for the target vehicle's corresponding vehicle ID. The difference between the current time and the time of issuance of each historical optimized charging curve is calculated. The historical charging curve corresponding to the smallest difference is then used as the actual optimized charging curve.

[0068] S15. Using the historical charging curve as the actual optimized charging curve.

[0069] As can be seen from the foregoing, the charging method provided by the disclosed embodiments, when the actual health of a target vehicle's battery is less than a health threshold, indicates that multiple instances of improper charging may have occurred, significantly reducing the actual health of the target vehicle's battery. The method obtains a historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment; the historical charging curve is used as the actual optimized charging curve. The method then selects at least one theoretical charging position from the target vehicle's historical charging positions that satisfies the theoretical charging configuration information; the theoretical charging position includes any of the historical charging positions. A charging instruction message containing the actual optimized charging curve and the theoretical charging position is sent to the target vehicle. The charging instruction message is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging position. Because the actual optimized charging curve better matches the target vehicle's battery, charging according to the actual optimized charging curve can slow the rate at which the battery's actual health deteriorates, thereby enabling real-time management of each vehicle's battery life, preventing significant reduction in battery life due to multiple instances of improper charging.

[0070] In some possible implementations, combining Figure 3 ,like Figure 4 As shown, the charging method provided in the embodiment of the present disclosure also includes S16-S18.

[0071] S16. If the actual health of the battery of the target vehicle is less than the health threshold, greater than the aging threshold, and lower than one or more activation reversible capacity damage thresholds, obtain the number of optimizations corresponding to the health interval to which the actual health belongs. The number of optimizations includes the total number of times the battery has been charged using the actual optimized charging curve in history.

[0072] S17. When the number of optimizations is less than the number threshold, reversible capacity loss activation is used as the optimization target to generate an activation charging curve.

[0073] In some examples, the cloud server pre-stores a correspondence between activation charging curves corresponding to different optimization objectives. Subsequently, when the cloud server determines that the optimization objective is reversible capacity loss activation, it queries the correspondence to determine the activation charging curve corresponding to reversible capacity loss activation.

[0074] When multiple activation charging curves are available, the target vehicle's battery's current remaining SOC can be used to calculate the time required to charge the battery to 100% SOC using different theoretically optimized charging curves. The corresponding charging cost is then calculated by multiplying the charging time and the charging price. The activation charging curve with the lowest charging cost is then used as the actual optimized charging curve.

[0075] In some examples, if the number of optimizations is less than a threshold, and the target vehicle's battery is pre-configured with a locked battery region, the batteries in that region are excluded from the health calculation. Subsequently, if that battery region is not activated, an activation charging curve is generated with reversible capacity loss activation as the optimization target, and this activation charging curve is used as the actual optimized charging curve. Subsequently, when the battery is charged according to the actual optimized charging curve, the locked battery region is activated, thereby improving the battery's health.

[0076] S18. Using the activated charging curve as the actual optimized charging curve.

[0077] As can be seen from the foregoing, the charging method provided by the disclosed embodiments, when the actual health of a target vehicle's battery is less than a health threshold, indicates that multiple instances of improper charging may have occurred, significantly reducing the actual health of the target vehicle's battery. The method obtains the optimization count corresponding to the health interval to which the actual health belongs. If the optimization count is less than the threshold, an activation charging curve is generated with reversible capacity loss activation as the optimization objective. The activation charging curve is then used as the actual optimized charging curve. Subsequently, at least one theoretical charging location that meets the theoretical charging configuration information is selected from the target vehicle's historical charging locations. The theoretical charging location includes any one of the historical charging locations. A charging instruction message containing the actual optimized charging curve and the theoretical charging location is sent to the target vehicle. The charging instruction message is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging location. Because the actual optimized charging curve better matches the target vehicle's battery, charging according to the actual optimized charging curve can slow the rate of decline in the battery's actual health, thereby enabling real-time management of each vehicle's battery life and preventing significant reduction in battery life due to multiple instances of improper charging.

[0078] In some possible implementation examples, combined with Figure 4 ,like Figure 5 As shown, the charging method provided in the embodiment of the present disclosure also includes S19 and S20.

[0079] S19: When the number of optimizations is greater than or equal to the number threshold, an extended charging curve is generated with extending the battery life as the optimization goal.

[0080] In some examples, the cloud server pre-stores a correspondence between activation charging curves corresponding to different optimization objectives. When the cloud server determines that the optimization objective is to extend battery life, it queries the correspondence to determine the activation charging curve corresponding to the extended battery life.

[0081] When multiple activation charging curves are available, the target vehicle's battery's current remaining SOC can be used to calculate the time required to charge the battery to 100% SOC using different theoretically optimized charging curves. The corresponding charging cost is then calculated by multiplying the charging time and the charging price. The activation charging curve with the lowest charging cost is then used as the actual optimized charging curve.

[0082] S20: Extending the charging curve as the actual optimized charging curve.

[0083] As can be seen from the foregoing, the charging method provided by the disclosed embodiments, when the actual health of a target vehicle's battery is less than a health threshold, indicates that multiple instances of improper charging may have occurred, significantly reducing the actual health of the target vehicle's battery. When the number of optimization attempts is greater than or equal to the threshold, an extended charging curve is generated with battery life as the optimization objective, and the extended charging curve is used as the actual optimized charging curve. Subsequently, at least one theoretical charging position that satisfies the theoretical charging configuration information is selected from the target vehicle's historical charging positions; the theoretical charging position includes any of the historical charging positions. Charging instruction information containing the actual optimized charging curve and the theoretical charging position is sent to the target vehicle. The charging instruction information is used to determine whether to use the actual optimized charging curve for charging after the target vehicle is powered off, based on the actual charging information and the theoretical charging position. Because the actual optimized charging curve better matches the target vehicle's battery, charging according to the actual optimized charging curve can slow the decline in the battery's actual health, thereby enabling real-time management of each vehicle's battery life, preventing significant reduction in battery life due to multiple instances of improper charging.

[0084] Example 2

[0085] Figure 6 A schematic flow chart of a charging method is shown in FIG. 1 , and the execution subject of this example may be a vehicle controller, such as Figure 6 As shown, the method includes:

[0086] S30. Receive charging instruction information sent by the cloud server, which carries the actual optimized charging curve and the theoretical charging position; wherein the charging instruction information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after the target vehicle is powered off.

[0087] S31. After the target vehicle is powered off, the current actual charging position and the battery state of charge are obtained.

[0088] S32: When the actual distance between the theoretical charging position and the actual charging position is less than or equal to the distance threshold, and the state of charge is less than the charge threshold, generate first prompt information including charging using the actual optimized charging curve.

[0089] In some examples, the actual charging position corresponds to an actual position coordinate, and the theoretical charging position corresponds to a theoretical position coordinate, and then the distance between the actual position coordinate and the theoretical position coordinate is calculated as the actual distance between the theoretical charging position and the actual charging position.

[0090] S33: In response to the selection operation of the charging function, charging is performed according to the actual optimized charging curve.

[0091] In some examples, when the target vehicle's battery is charged according to the actual optimized charging curve and the vehicle's SOC is charged to 100%, the target vehicle initiates a completion response message to the cloud indicating that charging is complete using the actual optimized charging curve. Alternatively, when the target vehicle's battery is charged according to the actual optimized charging curve and the vehicle's SOC is not charged to 100%, the target vehicle initiates a non-completion response message to the cloud indicating that charging is complete using the actual optimized charging curve. The cloud server then calculates the number of optimizations based on the received response message. For example, when the cloud server sends a charging instruction message and receives a response message in response to the charging instruction message, the optimization number is incremented by 1.

[0092] As can be seen from the above, in the charging method provided by the embodiment of the present disclosure, the target vehicle receives charging instruction information sent by the cloud server, which carries the actual optimized charging curve and the theoretical charging position; after the target vehicle is powered off, the current actual charging position and the battery's state of charge are obtained; when the actual distance between the theoretical charging position and the actual charging position is less than or equal to the distance threshold, and the state of charge is less than the charge threshold, a first prompt information including charging using the actual optimized charging curve is generated; in response to the selection operation of the charging function, charging is performed according to the actual optimized charging curve. Since the actual optimized charging curve is more consistent with the battery of the target vehicle, when the battery is charged according to the actual optimized charging curve, the rate of decline of the actual health of the battery can be slowed down, so that the battery life of each vehicle can be managed in real time, avoiding the situation where the battery life of the vehicle is greatly reduced due to multiple failures to charge normally.

[0093] In some possible implementation examples, combined with Figure 6 ,like Figure 7 As shown, the charging method provided in the embodiment of the present disclosure further includes S34 and S35.

[0094] S34. When the actual distance is greater than the distance threshold and the state of charge is less than the charge threshold, generate second prompt information for prompting whether to execute the target information; wherein the target information includes that the duration of AC charging is greater than a preset time.

[0095] In some examples, the second prompt information includes text prompting the user to use a specific charging request, such as: the specific charging request is to use AC charging for a duration greater than a preset time.

[0096] S35 . In response to the selection operation of the execution target information and the reception of the selection operation of the charging function, charging is performed according to the actual optimized charging curve.

[0097] As can be seen from the above, in the charging method provided by the embodiment of the present disclosure, the target vehicle receives charging instruction information sent by the cloud server, which carries the actual optimized charging curve and the theoretical charging position; after the target vehicle is powered off, the current actual charging position and the battery's state of charge are obtained; when the actual distance is greater than the distance threshold and the state of charge is less than the charge threshold, a second prompt information is generated to prompt whether to execute the target information; in response to the selection operation of executing the target information and receiving the selection operation of the charging function, charging is performed according to the actual optimized charging curve. Since the actual optimized charging curve is more consistent with the battery of the target vehicle, when the battery is charged according to the actual optimized charging curve, the rate of decline of the actual health of the battery can be slowed down, so that the battery life of each vehicle can be managed in real time, avoiding the situation where the battery life of the vehicle is greatly reduced due to multiple failures to charge normally.

[0098] In some possible implementations, combining Figure 7 ,like Figure 8 As shown, the charging method provided by the embodiment of the present disclosure also includes S36.

[0099] S36. In response to executing the selection operation of the target information and without receiving the selection operation of the charging function, generate a third prompt message; wherein the third prompt message is used to prompt one or more of the battery health information and charging suggestions of the battery, and the battery health information includes the actual health.

[0100] As can be seen from the above, the charging method provided by the disclosed embodiments involves the target vehicle receiving charging instruction information from a cloud server containing the actual optimized charging curve and theoretical charging position. After the target vehicle is powered off, the target vehicle obtains the current actual charging position and battery state of charge. In response to executing a target information selection operation and failing to receive a charging function selection operation, a third prompt message is generated. At this point, the user can decide whether to charge and how to charge based on the third prompt message, thereby allowing the user to use a more reasonable charging method to charge the target vehicle's battery, avoiding situations where the vehicle's battery life is significantly reduced due to repeated improper charging.

[0101] In some possible implementations, combining Figure 8 ,like Figure 9 As shown, the charging method provided by the embodiment of the present disclosure also includes S37.

[0102] S37 . In response to not executing the target information selection operation and receiving the charging function selection operation, charging is performed according to a pre-configured charging curve; wherein the pre-configured charging curve is different from the actual optimized charging curve.

[0103] In some examples, the preconfigured charging curve can be a charging curve preconfigured when the target vehicle leaves the factory, or after the target vehicle is connected to the charging device, the charging time required to charge the battery's SOC to 100% is calculated based on the actual configuration information of the charging device and the current remaining SOC of the target vehicle's battery using multiple preconfigured charging curves pre-stored in the target vehicle's database. The corresponding charging cost is then calculated by multiplying the charging time by the charging price. The battery is then charged according to the preconfigured charging curve corresponding to the minimum charging cost.

[0104] From the above, it can be seen that in the charging method provided by the embodiment of the present disclosure, the target vehicle receives charging indication information carrying the actual optimized charging curve and theoretical charging position sent by the cloud server; after the target vehicle is powered off, the current actual charging position and the battery charge state are obtained; in response to the selection operation of not executing the target information and receiving the selection operation of the charging function, charging is performed according to the pre-configured charging curve, so that the charging device can continue to charge the battery of the target vehicle to ensure the normal operation of the target vehicle.

[0105] Example 3

[0106] Figure 10 The schematic diagram of the structure of the cloud server provided in the third embodiment of the present application is shown in FIG. Figure 10 As shown, the cloud server includes: a transceiver module 81 and a processing module 82.

[0107] The processing module 81 is configured to determine an actual optimized charging curve based on the actual health of the battery of the target vehicle when the actual health of the battery is less than a health threshold; wherein one actual optimized charging curve corresponds to one theoretical charging configuration information;

[0108] The processing module 81 is further configured to select at least one theoretical charging position that satisfies the theoretical charging configuration information from the historical charging positions of the target vehicle; wherein the theoretical charging position includes any one of the historical charging positions;

[0109] The processing module 81 is also used to control the transceiver module 82 to send charging instruction information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle; wherein, the charging instruction information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging information and the theoretical charging position after the target vehicle is powered off.

[0110] In some feasible examples, the theoretical charging configuration information includes charging time and / or charging price; the processing module 81 is specifically used to determine the actual optimized charging curve based on the charging time and charging price when the actual health of the battery of the target vehicle is less than the health threshold and the actual health is less than or equal to the aging threshold.

[0111] In some feasible examples, the processing module 81 is also used to obtain the historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment when the actual health of the battery of the target vehicle is less than the health threshold, the actual health is greater than the aging threshold, and the actual health is greater than the activation reversible capacity damage threshold corresponding to each health interval; the processing module is also used to use the historical charging curve as the actual optimized charging curve.

[0112] In some feasible examples, the processing module 81 is also used to obtain the optimization number corresponding to the health interval to which the actual health belongs when the actual health of the battery of the target vehicle is less than the health threshold, and the actual health is greater than the aging threshold, and the actual health is lower than one or more activation reversible capacity damage thresholds; wherein the optimization number includes the total number of times the battery has been charged using the actual optimized charging curve in history; the processing module is also used to generate an activation charging curve with reversible capacity loss activation as the optimization target when the optimization number is less than the number threshold; the processing module 81 is also used to use the activation charging curve as the actual optimized charging curve.

[0113] In some feasible examples, the processing module 81 is further used to generate an extended charging curve with extending battery life as the optimization goal when the number of optimization times is greater than or equal to a threshold number; the processing module is also used to use the extended charging curve as the actual optimized charging curve.

[0114] Among them, all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, and its role will not be repeated here.

[0115] Of course, the cloud server provided by the embodiment of the present invention includes but is not limited to the above modules. For example, the cloud server may further include a storage module 83. The storage module 83 may be used to store the program code of the cloud server and may also be used to store data generated during the operation of the cloud server, such as diagnostic data.

[0116] Figure 11 A schematic diagram of the structure of a cloud server provided by an embodiment of the present invention is shown in FIG. Figure 11 As shown, the cloud server may include: at least one processor 51 , a memory 52 , a communication interface 53 and a communication bus 54 .

[0117] The following combination Figure 11 A detailed introduction to the various components of the cloud server:

[0118] Processor 51 is the control center of the cloud server and can be a single processor or a collective term for multiple processing elements. For example, processor 51 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more DSPs or one or more field programmable gate arrays (FPGAs).

[0119] In a specific implementation, as an embodiment, the processor 51 may include one or more CPUs, such as Figure 11 Also, as an embodiment, the cloud server may include multiple processors, such as Figure 11 , processor 51 and processor 55 are shown. Each of these processors can be a single-core processor (Single-CPU) or a multi-core processor (Multi-CPU). The processor here can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0120] The memory 52 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer. The memory 52 may be independent and connected to the processor 51 via a communication bus 54. The memory 52 may also be integrated with the processor 51.

[0121] In a specific implementation, the memory 52 is used to store the data of the present invention and execute the software program of the present invention. The processor 51 can execute various functions of the air conditioner by running or executing the software program stored in the memory 52 and calling the data stored in the memory 52.

[0122] Communication interface 53 , using any transceiver or other device, is used to communicate with other devices or communication networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a terminal, or the cloud. Communication interface 53 may include a transceiver module to implement the acquisition function.

[0123] The communication bus 54 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 11 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0124] As an example, combining Figure 10The functions implemented by the transceiver module 81 of the cloud server are similar to Figure 11 The function of the communication interface 53 in the cloud server is the same as that of the processing module 82 in the cloud server. Figure 11 The functions of the processor 51 in the cloud server are the same as those of the storage module 83 in the cloud server. Figure 11 The function of the memory 52 in is the same.

[0125] Example 4

[0126] Figure 12 The structural diagram of the vehicle controller provided by the fourth embodiment of the present application is shown in FIG. Figure 12 As shown, the vehicle controller includes: a transceiver module 91 and a processing module 92.

[0127] The transceiver module 91 is used to receive charging indication information carrying the actual optimized charging curve and the theoretical charging position sent by the cloud server; wherein the charging indication information is used to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after the target vehicle is powered off; the transceiver module 91 is also used to obtain the current actual charging position and the battery state of charge after the target vehicle is powered off; the processing module 92 is used to generate a first prompt information including the use of the actual optimized charging curve for charging when the actual distance between the theoretical charging position obtained by the transceiver module 91 and the actual charging position is less than or equal to the distance threshold and the charge state is less than the charge threshold; the processing module is also used to charge according to the actual optimized charging curve in response to the selection operation of the charging function.

[0128] In some applicable examples, the processing module 92 is further used to generate a second prompt message for prompting whether to execute the target information when the actual distance is greater than the distance threshold and the charge state is less than the charge threshold; wherein the target information includes the duration of AC charging being greater than a preset time; the processing module 92 is also used to respond to a selection operation for executing the target information and receive a selection operation for the charging function, and charge according to the actual optimized charging curve.

[0129] In some applicable examples, the processing module 92 is also used to generate a third prompt message in response to an operation of selecting the execution target information and without receiving an operation of selecting the charging function; wherein the third prompt message is used to prompt one or more of the battery health information and charging recommendations of the battery, and the battery health information includes the actual health.

[0130] In some feasible examples, the processing module 92 is further configured to, in response to not executing a selection operation of target information and receiving a selection operation of a charging function, charge according to a preconfigured charging curve; wherein the preconfigured charging curve is different from the actual optimized charging curve.

[0131] Among them, all relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module, and its role will not be repeated here.

[0132] Of course, the vehicle controller provided by the embodiment of the present invention includes but is not limited to the above modules. For example, the vehicle controller may also include a storage module 93. The storage module 93 may be used to store the program code of the vehicle controller and may also be used to store data generated during the operation of the vehicle controller, such as diagnostic data.

[0133] Figure 13 A schematic diagram of the structure of a vehicle controller provided by an embodiment of the present invention is shown in FIG. Figure 13 As shown, the vehicle controller may include at least one processor 61 , a memory 62 , a communication interface 63 and a communication bus 64 .

[0134] The following combination Figure 13 A detailed introduction to the various components of the vehicle controller:

[0135] Processor 61 is the control center of the vehicle controller and can be a single processor or a collective term for multiple processing elements. For example, processor 61 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more DSPs or one or more field programmable gate arrays (FPGAs).

[0136] In a specific implementation, as an embodiment, the processor 61 may include one or more CPUs, such as Figure 13 Also, as an embodiment, the vehicle controller may include multiple processors, such as Figure 13 61 and processor 65 are shown in FIG. Each of these processors can be a single-core processor (Single-CPU) or a multi-core processor (Multi-CPU). A processor here can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0137] The memory 62 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer. The memory 62 may be independent and connected to the processor 61 via a communication bus 64. The memory 62 may also be integrated with the processor 61.

[0138] In a specific implementation, the memory 62 is used to store the data of the present invention and execute the software program of the present invention. The processor 61 can execute various functions of the air conditioner by running or executing the software program stored in the memory 62 and calling the data stored in the memory 62.

[0139] Communication interface 63 , using any transceiver or other device, is used to communicate with other devices or communication networks, such as radio access networks (RANs), wireless local area networks (WLANs), terminals, and the cloud. Communication interface 63 may include a transceiver module to implement acquisition and reception functions.

[0140] The communication bus 64 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 13 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0141] As an example, combining Figure 12 The functions implemented by the transceiver module 91 of the vehicle controller are similar to Figure 13 The function of the communication interface 53 in the vehicle controller is the same as that of the processing module 92 in the vehicle controller. Figure 13 The functions of the processor 61 in the vehicle controller are the same as those of the storage module 93 in the vehicle controller. Figure 13 The function of the memory 62 in is the same.

[0142] An embodiment of the present application also provides a vehicle, which may include the vehicle controller in any embodiment.

[0143] An embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method in any embodiment.

[0144] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A charging method, applied to a cloud server, characterized in that: include: When the actual health of the battery of the target vehicle is less than a health threshold, determining an actual optimized charging curve based on the actual health; wherein one actual optimized charging curve corresponds to one piece of theoretical charging configuration information; Screening at least one theoretical charging position that satisfies the theoretical charging configuration information from the historical charging positions of the target vehicle; wherein the theoretical charging position includes any one of the historical charging positions; Sending charging instruction information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle; wherein the charging instruction information is used to enable the target vehicle to determine whether to use the actual optimized charging curve for charging based on the actual charging information and the theoretical charging position after powering off.

2. The charging method according to claim 1, wherein: The theoretical charging configuration information includes charging time and / or charging price; The step of determining an actual optimized charging curve based on the actual health of the battery of the target vehicle when the actual health of the battery is less than a health threshold includes: When the actual health of the battery of the target vehicle is less than a health threshold and the actual health is less than or equal to an aging threshold, an actual optimized charging curve is determined based on the charging time and the charging price.

3. The charging method according to claim 2, wherein: The method further comprises: When the actual health of the battery of the target vehicle is less than the health threshold, the actual health is greater than the aging threshold, and the actual health is greater than the activation reversible capacity damage threshold corresponding to each health interval, obtaining a historical optimized charging curve corresponding to the historical moment with the smallest difference from the current moment; The historical charging curve is used as the actual optimized charging curve.

4. The charging method according to claim 3, characterized in that: The method further comprises: When the actual health of the battery of the target vehicle is less than the health threshold, the actual health is greater than the aging threshold, and the actual health is lower than one or more activation reversible capacity damage thresholds, obtaining the number of optimizations corresponding to the health interval to which the actual health belongs; wherein the number of optimizations includes the total number of times the battery has been charged using the actual optimized charging curve in history; When the optimization times are less than the times threshold, reversible capacity loss activation is used as the optimization target to generate an activation charging curve; The activation charging curve is used as the actual optimized charging curve.

5. The charging method according to claim 4, characterized in that: The method further comprises: When the optimization number is greater than or equal to the number threshold, generating an extended charging curve with extending battery life as the optimization goal; The extended charging curve is used as the actual optimized charging curve.

6. A charging method, applied to a vehicle controller, characterized in that: include: Receiving charging instruction information sent by a cloud server and carrying an actual optimized charging curve and a theoretical charging position; wherein the charging instruction information is used to enable the target vehicle to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after being powered off; After the target vehicle is powered off, the current actual charging position and battery state of charge are obtained; generating, when the actual distance between the theoretical charging position and the actual charging position is less than or equal to a distance threshold and the state of charge is less than a charge threshold, a first prompt message including charging using the actual optimized charging curve; In response to the selection operation of the charging function, charging is performed according to the actual optimized charging curve.

7. The charging method according to claim 6, characterized in that: The method further comprises: If the actual distance is greater than the distance threshold and the state of charge is less than the charge threshold, generating a second prompt message for prompting whether to execute the target information; wherein the target information includes that the duration of AC charging is greater than a preset time; In response to executing the operation of selecting the target information and receiving the operation of selecting a charging function, charging is performed according to the actual optimized charging curve.

8. The charging method according to claim 7, characterized in that: The method further comprises: In response to executing the selection operation of the target information and without receiving the selection operation of the charging function, a third prompt information is generated; wherein, the third prompt information is used to prompt one or more of the battery health information and charging suggestions of the battery, and the battery health information includes the actual health.

9. The charging method according to claim 7, wherein: The method further comprises: In response to not performing the target information selection operation and receiving a charging function selection operation, charging is performed according to a preconfigured charging curve; wherein the preconfigured charging curve is different from the actual optimized charging curve.

10. A cloud server, characterized in that: include: a processing module, configured to determine, when the actual health of the battery of the target vehicle is less than a health threshold, an actual optimized charging curve based on the actual health; wherein one actual optimized charging curve corresponds to one piece of theoretical charging configuration information; The processing module is further configured to screen at least one theoretical charging position that satisfies the theoretical charging configuration information from the historical charging positions of the target vehicle; wherein the theoretical charging position includes any one of the historical charging positions; The processing module is further used to control the transceiver module to send charging instruction information carrying the actual optimized charging curve and the theoretical charging position to the target vehicle; wherein, the charging instruction information is used to enable the target vehicle to determine whether to use the actual optimized charging curve for charging based on the actual charging information and the theoretical charging position after power is turned off.

11. A vehicle controller, characterized in that: include: a transceiver module, configured to receive charging instruction information sent by a cloud server and including an actual optimized charging curve and a theoretical charging position; wherein the charging instruction information is used to enable the target vehicle to determine whether to use the actual optimized charging curve for charging based on the actual charging position and the theoretical charging position after power is turned off; The transceiver module is further used to obtain the current actual charging position and battery charge state of the target vehicle after the target vehicle is powered off; a processing module, configured to generate a first prompt message including charging using the actual optimized charging curve, if the actual distance between the theoretical charging position obtained by the transceiver module and the actual charging position is less than or equal to a distance threshold, and the state of charge is less than a charge threshold; The processing module is further configured to, in response to a selection operation of a charging function, perform charging according to the actual optimized charging curve.

12. A vehicle, characterized in that: Comprising the vehicle controller of claim 11.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the charging method according to any one of claims 1 to 5, or which, when executed by a processor, are used to implement the charging method according to any one of claims 6 to 9.

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