A method and system for predicting remaining charging time for electric vehicles

Abstract

This application provides a method and system for predicting the remaining charging time of an electric vehicle. Based on a comprehensive consideration of various factors affecting the accuracy of remaining charging time estimation in different working modes and scenarios, this invention provides a processing method that further improves the accuracy of remaining charging time estimation. By matching real-time reference information of the electric vehicle's charging battery during the charging process with historical reference information of the vehicle's charging battery stored in the cloud or obtained from cloud storage, the displayed charging time is corrected. An adaptive following strategy for remaining charging time is also provided, which can adaptively correct the displayed value of remaining charging time based on differences, solving the shortcomings of low accuracy caused by the vehicle relying solely on local calculations and the inability to continuously optimize based on actual vehicle conditions.

Description

Technical Field

[0001] This application relates to the field of electric vehicle charging technology, specifically to a method and system for predicting the remaining charging time of an electric vehicle. Background Technology

[0002] With the rapid development of my country's new energy vehicle industry, electric vehicles are gaining wider acceptance among users. The estimation of remaining charging time is directly related to user experience. Current technologies for estimating remaining charging time primarily rely on the Battery Management System (BMS). This system compares and looks up the collected battery parameters with charging parameter tables, then uses its own controller to calculate the estimated remaining charging time. Remaining charging time is a crucial parameter that users pay close attention to during electric vehicle charging. However, current technologies display data locally based on simulation, experimental, or calibration data, making it impossible to accurately estimate and calibrate the remaining charging time based on the actual vehicle's operating environment and historical vehicle data. Summary of the Invention

[0003] In view of the above-mentioned defects or deficiencies in the prior art, this application aims to provide a method and system for predicting the remaining charging time of electric vehicles. By continuously improving the cloud computing model through the charging history data of vehicles in the market, the remaining charging time of the vehicle is calibrated and corrected, which solves the shortcomings of low accuracy caused by the vehicle relying only on local calculation and the inability to continuously optimize according to the actual vehicle conditions.

[0004] Therefore, the technical solution of the present invention is as follows:

[0005] On the one hand, this invention provides a method for predicting the remaining charging time of electric vehicles. This method can guide the remaining charging time process in the current charging scenario through historical big data in the cloud, avoiding the inaccuracy problem of relying solely on the remaining charging time calculated by the on-board battery management system. The battery reference information uploaded to the cloud in the current charging scenario can be used to match and obtain the reference remaining charging time output by the cloud, or it can be stored in the cloud database as further improvement of the cloud big data.

[0006] The specific steps of this method are as follows:

[0007] S110. Obtain the battery reference information of the target vehicle's charging battery at the current moment, and send the battery reference information to the cloud to obtain the reference remaining charging time at the current moment determined by the cloud based on the battery reference information.

[0008] The acquisition of the target vehicle's battery reference information at the current moment includes:

[0009] Acquire battery temperature, cell voltage, ambient temperature, initial SOC (State of Charge), final SOC, charging type, geographic location, real-time current, and real-time voltage.

[0010] The charging types include DC charging and AC charging, and the geographical location is used to identify and distinguish different charging stations.

[0011] Furthermore, the reference remaining charging time is determined by the cloud based on the acquired battery reference information and historical vehicle reference information; the historical vehicle reference information is battery reference information of other electric vehicles stored or acquired in the cloud.

[0012] S120. Obtain the local remaining charging time at the current moment as determined by the battery management system of the target vehicle for the charging battery;

[0013] S130. Based on the reference remaining charging time and local remaining charging time at the current moment, adjust the local remaining charging time at the next moment.

[0014] Furthermore, S130 includes:

[0015] The target remaining charging time at the current moment is determined based on the reference remaining charging time and the local remaining charging time at the current moment, and the local remaining charging time at the next moment is determined based on the target remaining charging time at the current moment.

[0016] Furthermore, the determination of the target remaining charging time is specifically as follows:

[0017] Determine whether the cloud matching described in S110 was successful;

[0018] If the match is successful, take T. target =T cloud If the match fails, take T. target =T Dis ;

[0019] Among them, T target For the target remaining charging time, T cloud T represents the reference remaining charging time at the current moment. Dis The remaining local charging time at the current moment.

[0020] Furthermore, if the cloud-based matching is successful, then the remaining local charging time T at the current moment will be used as the basis for the calculation. Dis With the target remaining charging time T target Calculate the following rate α and the waiting rate β; adjust the local remaining charging time displayed by the charging battery at the next moment based on the following rate α and the waiting rate β.

[0021] Furthermore, if the current displayed time T Dis With the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0022] If the current displayed time is T Dis Greater than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0023] If the current displayed time is T Dis Less than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0024] Among them, T Dis+1 T represents the remaining local charging time at the next moment. integral Let t represent the time integral, where t represents time.

[0025] To avoid failing to follow the target's remaining charging time, the minimum following rate is set to 1.1, and the maximum waiting rate is set to 0.9. Specifically, if 1.1 > α > 1, the following rate α is set to 1.1; if α ≥ 1.1, then α itself is used; if 0.9 < β < 1, then the waiting rate β is set to 0.9; if β ≤ 0.9, then β itself is used.

[0026] On the other hand, the present invention provides an electric vehicle charging remaining time prediction system, the system comprising a vehicle-side terminal and a cloud-based terminal; wherein, the vehicle-side terminal is used to acquire battery reference information at the current moment, send the battery reference information to the cloud-based terminal, acquire a reference charging time at the current moment determined by the cloud-based terminal based on the battery reference information; acquire the local remaining charging time at the current moment determined by the electric vehicle's battery management system for the charging battery; determine a target remaining charging time at the current moment based on the reference remaining charging time and the local remaining charging time; and determine and display the local remaining charging time at the next moment based on the target remaining charging time; the cloud-based terminal is used to receive the battery reference information sent by the vehicle-side terminal, match and determine the reference remaining charging time at the current moment corresponding to the battery reference information, and feed back the reference remaining charging time at the current moment to the vehicle-side terminal.

[0027] The system may further include a real-time calibration device and a display device. The real-time calibration device is used to receive the local remaining charging time at the current moment sent by the vehicle terminal and the reference remaining charging time at the current moment sent by the cloud, and calculate the local remaining charging time at the next moment based on the local remaining charging time at the current moment and the reference remaining charging time using a correction algorithm. The display device is a device with data transmission and display functions. This module is used to receive and display the local remaining charging time at the current moment sent by the vehicle terminal, the reference remaining charging time at the current moment sent by the cloud, and the local remaining charging time at the next moment sent by the vehicle terminal or the real-time calibration device.

[0028] The real-time calibration device can be any electronic device with computing capabilities, including but not limited to those that can be activated based on real-time calibration requirements and the vehicle's computing power. The display device can be any device with display capabilities other than the vehicle's own display, including but not limited to tablets and mobile phones; this module allows for remote viewing of remaining charging time.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] (1) By acquiring and matching the reference information of the car charging battery in real time, and combining it with the reference remaining charging time obtained based on historical reference information, the problem of low accuracy caused by electric vehicles relying solely on the local system to calculate the remaining charging time is avoided.

[0031] (2) By fully considering the various factors that affect the accuracy of the remaining charging time estimation in different working modes and different working scenarios, the accuracy of the remaining charging time estimation has been further improved.

[0032] (3) An adaptive following strategy for the remaining charging time is provided, which can adaptively correct the displayed value of the remaining charging time in real time according to the difference, so as to achieve smooth following of the remaining charging time to the target value. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 A flowchart of a method for predicting the remaining charging time of an electric vehicle provided in this application;

[0035] Figure 2 A schematic diagram of vehicle-to-cloud interaction provided in an embodiment of this application;

[0036] Figure 3 A flowchart of vehicle-cloud collaboration provided in this application embodiment;

[0037] Figure 4 This is a schematic diagram of cloud data collection and matching provided for an embodiment of this application. Detailed Implementation

[0038] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0039] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0040] As mentioned in the background section, this application proposes a method for predicting the remaining charging time of electric vehicles to address the problems in the existing technology. Figure 1 A flowchart of a method for predicting the remaining charging time of an electric vehicle provided in this application is attached. Figure 1 The method for predicting the remaining charging time of an electric vehicle is as follows:

[0041] S110. Obtain the battery reference information of the target vehicle's charging battery at the current moment, and send the battery reference information to the cloud to obtain the reference remaining charging time at the current moment determined by the cloud based on the battery reference information.

[0042] S120. Obtain the remaining local charging time for the target vehicle's battery management system at the current moment, as determined by the battery management system for the charging battery.

[0043] S130. Based on the reference remaining charging time and the local remaining charging time at the current moment, adjust the local remaining charging time at the next moment.

[0044] Figure 2 This is a schematic diagram of vehicle-to-cloud interaction provided in an embodiment of this application. See attached diagram. Figure 2 The specific steps of this method for predicting the remaining charging time of electric vehicles are as follows:

[0045] S110. Obtain the battery reference information of the target vehicle's charging battery at the current moment, and send the battery reference information to the cloud to obtain the reference remaining charging time at the current moment determined by the cloud based on the battery reference information.

[0046] Obtain the battery reference information of the target vehicle's charging battery at the current moment, including:

[0047] Acquire battery temperature, cell voltage, ambient temperature, initial SOC (State of Charge), final SOC, charging type, geographic location, real-time current, and real-time voltage.

[0048] Charging types include DC charging and AC charging, and geographical location is used to identify and distinguish different charging stations.

[0049] Furthermore, the cloud determines the remaining charging time based on the acquired battery reference information and historical vehicle reference information; the historical vehicle reference information is the battery reference information of other electric vehicles stored or acquired in the cloud.

[0050] Figure 4 This is a schematic diagram of cloud data collection and matching provided in an embodiment of this application.

[0051] In one specific implementation, the cloud is a deep learning model, and the historical battery reference information package and the remaining charging time corresponding to each package constitute the dataset used to train the model; the historical battery reference information package and the remaining charging time corresponding to each package are data sent to the cloud or reference information database during the charging process of other vehicles, wherein the reference information package includes, but is not limited to, battery temperature, cell voltage, ambient temperature, initial SOC, end SOC, charging type, geographical location, real-time current, and real-time voltage, and the time corresponding to each reference information package is the real-time remaining charging time displayed under each reference state during the charging process of historical vehicles.

[0052] Optionally, the input data used for training the deep learning model can be either all or part of the parameter types in the reference information packet.

[0053] Furthermore, this deep learning model can be used simultaneously for matching predictions and further training of the model.

[0054] Optionally, the battery reference information uploaded in real time by the vehicle can be used to obtain the reference remaining charging time through cloud matching, or it can be added to the dataset for further training of the deep learning model.

[0055] In one specific implementation, the cloud is a clustering model that can output a reference remaining charging time based on the input battery reference information. The model can perform clustering processing on historical battery reference information and map each cluster to the class charging time corresponding to its class. The model determines the target cluster in each cluster based on the battery reference information uploaded in real time from the vehicle and uses the class charging time corresponding to the target cluster as the reference remaining charging time.

[0056] In one specific implementation, the cloud is a numerical comparison model that stores all historical reference data packets uploaded to the cloud and the remaining charging time corresponding to each data packet. When the model receives real-time battery reference information uploaded from the vehicle, it compares the real-time battery reference information with the data of the historical reference data packets and takes the remaining charging time corresponding to the historical reference data packet with the smallest difference as the reference remaining charging time.

[0057] S120. Obtain the remaining local charging time for the target vehicle's battery management system at the current moment, as determined by the battery management system for the charging battery.

[0058] S130. Based on the reference remaining charging time and the local remaining charging time at the current moment, adjust the local remaining charging time at the next moment.

[0059] It should be noted that the vehicle-cloud collaborative electric vehicle charging remaining time prediction method provided by this invention predicts the remaining charging time as a continuous and cyclical process, that is, whether the cloud matching is successful or not, and further, whether the currently displayed remaining charging time is corrected based on the cloud matching result. The instrument or App used to display the remaining charging time can realize the display of the remaining charging time under the prediction result of this method.

[0060] Furthermore, the prediction frequency of the vehicle-cloud collaborative electric vehicle charging remaining time prediction method provided by the present invention can be flexibly set according to actual calibration needs or the computing power of the vehicle-side or peripheral data processing terminal with computing functions.

[0061] Figure 3 This is a flowchart of a vehicle-cloud collaboration process provided in an embodiment of this application. Based on the above implementation method, the vehicle determines whether the displayed value needs to be corrected based on the matching result from the cloud. If correction is needed, a correction value is obtained through a correction algorithm. See appendix. Figure 3 The method for predicting remaining charging time specifically includes:

[0062] S210, Vehicle Data Collection: Obtain the battery reference information of the target vehicle's charging battery at the current moment and send the battery reference information to the cloud;

[0063] S220, Cloud Matching: Obtain the reference remaining charging time at the current moment as determined by cloud matching based on battery reference information.

[0064] S221. Determine whether the cloud matching in S220 was successful.

[0065] S230, Real-time vehicle-side calculation: Obtain the remaining local charging time for the target vehicle's battery management system at the current moment, as determined by the battery management system for the charging battery.

[0066] S231, If ​​S221 is successfully matched in the cloud, take T. target =T cloud Accordingly, in this case, the remaining charging time needs to be adjusted; if matching fails, take T. target =T Dis Accordingly, in this case, there is no need to adjust the remaining charging time;

[0067] Among them, T target For the target remaining charging time, T cloud T represents the reference remaining charging time at the current moment. Dis The remaining local charging time at the current moment.

[0068] S232, If cloud matching is successful in S221, then based on the remaining local charging time T at the current moment... Dis With the target remaining charging time T target Calculate the following rate α and the waiting rate β; adjust the local remaining charging time displayed by the charging battery at the next moment based on the following rate α and the waiting rate β.

[0069] Furthermore, if the current displayed time T Dis With the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0070] If the current displayed time is T Dis Greater than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0071] If the current displayed time is T Dis Less than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0072] Among them, T Dis+1 T represents the remaining local charging time at the next moment. integral Let t represent the time integral, where t represents time.

[0073] S233. Display the local charging time for the next moment on the instrument panel or App interface.

[0074] It should be noted that the above-mentioned remaining charging time prediction algorithm based on the following rate α, waiting rate β and time integration can achieve a smooth display of the remaining charging time. This avoids the numerical jump caused by using the reference value as the display value at the next moment when there is a large difference between the reference result obtained by the cloud matching at the current moment and the local display value. This smooth transition process enhances the user experience.

[0075] Optionally, since in reality, the calculated following rate α and waiting rate β may fall within an unreasonable range, which may cause the displayed local remaining charging time before the end of charging to fail to follow the target remaining charging time, the minimum following rate is set to 1.1 and the maximum waiting rate to 0.9. Specifically, if 1.1 > α > 1, the following rate α is set to 1.1; if α ≥ 1.1, α itself is used; if 0.9 < β < 1, the waiting rate β is set to 0.9; if β ≤ 0.9, β itself is used.

[0076] Optionally, in one specific implementation, S233 includes: displaying the reference remaining charging time as the local remaining charging time at the next moment.

[0077] Optionally, in one specific implementation, S233 includes: displaying the average of the reference remaining charging time and the local remaining charging time as the local remaining charging time at the next moment.

[0078] This invention also provides an electric vehicle charging remaining time prediction system, the system comprising a vehicle-side component and a cloud-based component; wherein, the vehicle-side component is used to acquire battery reference information at the current moment, send the battery reference information to the cloud-based component, acquire a reference charging time at the current moment determined by the cloud-based component based on the battery reference information; acquire the local remaining charging time at the current moment determined by the electric vehicle's battery management system for the charging battery; determine a target remaining charging time at the current moment based on the reference remaining charging time and the local remaining charging time; and determine and display the local remaining charging time at the next moment based on the target remaining charging time; the cloud-based component is used to receive the battery reference information sent by the vehicle-side component, match and determine the reference remaining charging time at the current moment corresponding to the battery reference information, and feed back the reference remaining charging time at the current moment to the vehicle-side component.

[0079] Optionally, the system further includes a real-time calibration device and a display device; the real-time calibration device is used to receive the local remaining charging time at the current moment sent by the vehicle and the reference remaining charging time at the current moment sent by the cloud, and calculate the local remaining charging time at the next moment based on the local remaining charging time at the current moment and the reference remaining charging time through a correction algorithm; the display device is a device with data transmission and display functions, and this module is used to receive and display the local remaining charging time at the current moment sent by the vehicle, the reference remaining charging time at the current moment sent by the cloud, and the local remaining charging time at the next moment sent by the vehicle or the real-time calibration device.

[0080] The real-time calibration device can be any electronic device with computing capabilities, including but not limited to devices that can be activated based on real-time calibration requirements and the vehicle's computing power. The display device can be any device with display capabilities other than the vehicle's own display, including but not limited to tablets and mobile phones. This module allows for remote viewing of remaining charging time. Furthermore, the display device can be used to integrate applications related to remaining charging time.

[0081] Optionally, the vehicle-side can also be used for:

[0082] Acquire battery temperature, cell voltage, ambient temperature, initial SOC, final SOC, charging type, geographic location, real-time current, and real-time voltage.

[0083] The target remaining charging time at the current moment is determined based on the reference remaining charging time and the local remaining charging time at the current moment, and the local remaining charging time at the next moment is determined based on the target remaining charging time at the current moment.

[0084] Determine if the cloud matching was successful:

[0085] If the match is successful, take T. target =T cloud If the match fails, take T. target =T Dis ;

[0086] Among them, T target For the target remaining charging time, T cloud T represents the reference remaining charging time at the current moment. Dis The remaining local charging time at the current moment.

[0087] Furthermore, if the cloud matching is successful, the remaining local charging time T at the current moment will be used as the basis for the calculation. Dis With the target remaining charging time T target Calculate the following rate α and the waiting rate β; adjust the local remaining charging time displayed by the charging battery at the next moment based on the following rate α and the waiting rate β.

[0088] Furthermore, if the current displayed time T Dis With the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0089] If the current displayed time is T Dis Greater than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0090] If the current displayed time is T Dis Less than the target remaining charging time T target If there is no difference, the remaining local charging time displayed at the next moment will be:

[0091] Among them, T Dis+1 T represents the remaining local charging time at the next moment. integral Let t represent the time integral, where t represents time.

[0092] To avoid failing to follow the target's remaining charging time, the minimum following rate is set to 1.1, and the maximum waiting rate is set to 0.9. Specifically, if 1.1 > α > 1, the following rate α is set to 1.1; if α ≥ 1.1, then α itself is used; if 0.9 < β < 1, then the waiting rate β is set to 0.9; if β ≤ 0.9, then β itself is used.

[0093] It should be noted that the terminology used in this application is for the purpose of describing specific embodiments only and is not intended to limit the scope of this application. As shown in the specification and claims of this application, unless the context clearly indicates otherwise, words such as "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, or apparatus. Without further limitations, an element defined by the phrase "comprising an..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element.

[0094] It should also be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," "linked," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0095] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A method for predicting the remaining charging time of an electric vehicle, characterized in that, Includes the following steps: Obtain the battery reference information of the target vehicle's charging battery at the current moment, and send the battery reference information to the cloud to obtain the reference remaining charging time at the current moment determined by the cloud based on the battery reference information; Obtain the local remaining charging time at the current moment as determined by the battery management system of the target vehicle for the charging battery; The target remaining charging time at the current moment is determined based on the reference remaining charging time and the local remaining charging time at the current moment. If the current displayed time is T Dis Equal to the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; If the current displayed time is T Dis Greater than the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; If the current displayed time is T Dis Less than the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; in, T represents the remaining local charging time at the next moment. integral This represents the time integral, where t represents time; the following rate α and the waiting rate β; the minimum following rate is set to 1.1, and the maximum waiting rate is 0.9, to avoid failing to follow the target for the remaining charging time; specifically: If 1.1 > α > 1, then the following speed α is 1.1; if α ≥ 1.1, then α itself is used. If 0.9 < β < 1, then the waiting rate β is 0.9; if β ≤ 0.9, then β itself is used.

2. The method for predicting the remaining charging time of an electric vehicle according to claim 1, characterized in that: The battery reference information includes one or more of the following: Battery temperature, cell voltage, ambient temperature, initial SOC, final SOC, charging type, geographical location, real-time charging current, and real-time charging voltage.

3. The method for predicting the remaining charging time of an electric vehicle according to claim 1, characterized in that: The reference remaining charging time is determined by the cloud based on the acquired battery reference information and historical vehicle reference information; the historical vehicle reference information is battery reference information of other electric vehicles stored or acquired in the cloud.

4. The method for predicting the remaining charging time of an electric vehicle according to claim 1, characterized in that: Determining the target remaining charging time at the current moment based on the reference remaining charging time and the local remaining charging time includes: Determine whether the cloud determines the reference remaining charging time up to the current moment based on the battery reference information; If the reference remaining charging time at the current moment is determined by matching, take T. target =T cloud If no matching reference remaining charging time is determined at the current time, then T is taken. target =T Dis ; Among them, T target T represents the remaining charging time for the target. cloud T is the reference remaining charging time at the current moment. Dis The remaining local charging time at the current moment.

5. An electric vehicle charging remaining time prediction system, the system comprising a vehicle-side terminal and a cloud-based terminal; wherein, The vehicle-mounted device is used to obtain the battery reference information at the current moment, send the battery reference information to the cloud, and obtain the reference charging time at the current moment determined by the cloud based on the battery reference information; Obtain the local remaining charging time for the electric vehicle at the current moment, as determined by the battery management system for the charging battery. The target remaining charging time at the current moment is determined based on the reference remaining charging time and the local remaining charging time at the current moment; The local remaining charging time at the next moment is determined and displayed based on the target remaining charging time at the current moment. The target remaining charging time at the current moment is determined based on the reference remaining charging time and the local remaining charging time at the current moment. If the current displayed time is T Dis Equal to the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; If the current displayed time is T Dis Greater than the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; If the current displayed time is T Dis Less than the target remaining charging time T target Then the remaining local charging time displayed at the next moment will be: ; in, T represents the remaining local charging time at the next moment. integral This represents the time integral, where t represents time; the following rate α and the waiting rate β; the minimum following rate is set to 1.1, and the maximum waiting rate is 0.9, to avoid failing to follow the target for the remaining charging time; specifically: If 1.1 > α > 1, then the following speed α is 1.1; if α ≥ 1.1, then α itself is used. If 0.9 < β < 1, then the waiting rate β is 0.9; if β ≤ 0.9, then β itself is used. The cloud is used to receive battery reference information sent by the vehicle, determine the reference remaining charging time at the current moment based on the battery reference information, and feed back the reference remaining charging time at the current moment to the vehicle.

6. The electric vehicle charging remaining time prediction system according to claim 5, characterized in that: The system also includes real-time calibration equipment and display equipment; The real-time calibration device is used to receive the local remaining charging time at the current moment sent by the vehicle and the reference remaining charging time at the current moment sent by the cloud, and calculate the local remaining charging time at the next moment based on the local remaining charging time at the current moment and the reference remaining charging time through a calibration algorithm. The display device is used to receive and display the local remaining charging time at the current moment sent by the vehicle, the reference remaining charging time at the current moment sent by the cloud, and the local remaining charging time at the next moment sent by the vehicle or a real-time calibration device.

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