Charging resource management scheduling method and system, intelligent vehicle and storage medium

Abstract

The invention provides a charging resource management scheduling method and system, an intelligent vehicle and a storage medium, and belongs to the technical field of new energy automobiles, and the method comprises the steps: obtaining the current position and the current driving mileage of the vehicle, and generating a target charging range with the current position as the center and the current driving mileage as the radius; real-time state information of the charging piles in the target charging range is obtained, wherein the real-time state information of the charging piles at least comprises the number of available charging piles and the number of idle charging piles; matching is carried out according to the real-time state information of the charging pile and a multi-stage trigger condition, and a control signal corresponding to a matching result is generated; and executing a corresponding response operation according to the control signal, and terminating execution of the response operation when the real-time state information of the charging pile meets a preset recovery condition. According to the invention, the charging safety is improved while the charging resource use efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle technology, specifically to a charging resource management and scheduling method, system, intelligent vehicle, and storage medium. Background Technology

[0002] With the increasing popularity of new energy vehicles, the demand for charging infrastructure is growing rapidly. Currently, in first- and second-tier cities, the coverage density of charging piles is relatively high, basically meeting daily travel needs. However, in suburban areas and remote mountain villages, the distribution density of charging piles is significantly lower, and the distance between adjacent charging stations is large. Once a charging station is missed, finding the next one often takes a long time. In addition, during holiday travel scenarios on highways, although most service areas are equipped with charging piles, the concentrated travel of vehicles leads to a severe shortage of available charging piles, resulting in widespread queuing for charging and seriously affecting the user's travel experience.

[0003] In existing technologies, vehicles typically trigger charging prompts and recommend nearby charging stations only when the battery level falls below a certain preset threshold. For example, when the vehicle's battery is low, the in-vehicle system will prompt the user to charge promptly via the instrument panel or central control screen, and recommend available charging stations based on the current location. This type of technology mainly relies on a battery level threshold as a trigger condition, combined with charging station location information provided by the navigation module, to help users find charging resources when the battery is low.

[0004] However, existing technology has significant limitations: it only issues a warning when the battery level drops to a threshold, failing to analyze and assess available charging station resources within the current driving range in advance, and lacking a corresponding early warning mechanism. In this situation, when users receive the warning, they often find that nearby charging stations are full, requiring long waits, or that charging stations are malfunctioning, or even unavailable in remote areas. This causes users to miss reasonable charging planning windows, increasing the risk of vehicle breakdowns and impacting their travel safety and convenience. Summary of the Invention

[0005] In view of this, it is necessary to provide a charging resource management and scheduling method, system, intelligent vehicle and storage medium to solve the technical problem in the existing technology that the analysis and early warning of the charging pile resource status within the driving range in advance causes users to miss the reasonable charging planning window or even the vehicle to break down.

[0006] To address the aforementioned technical problems, in a first aspect, the present invention provides a charging resource management and scheduling method, comprising: Obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius; Obtain real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. The real-time status information of the charging pile is matched with multi-level triggering conditions to generate a control signal corresponding to the matching result. The corresponding response operation is executed according to the control signal, and the execution of the response operation is terminated when the real-time status information of the charging pile meets the preset recovery conditions.

[0007] In one possible implementation, after obtaining the current driving range, the following is also included: The vehicle obtains real-time road condition and weather information of its current environment, and corrects the current driving range based on the real-time road condition and weather information to generate a corrected driving range. The target charging range is regenerated with the current location as the center and the corrected driving range as the radius.

[0008] In one possible implementation, after obtaining the real-time status information of the charging piles within the target charging range, the method further includes: Obtain historical occupancy data for each charging pile within the target charging range, including occupancy rates for different time periods and occupancy curves during holidays; Based on the historical occupancy data and the estimated time for vehicles to arrive at each charging station, the predicted occupancy status of each charging station at the time of vehicle arrival is predicted. The charging piles predicted to be occupied are removed from the number of available charging piles and the number of idle charging piles, and the corrected real-time status information of the charging piles is generated.

[0009] In one possible implementation, before generating the control signal corresponding to the matching result, the following steps are also included: The vehicle network communication is used to obtain the driving status information and charging intention information of surrounding vehicles. The surrounding vehicles are those that are traveling in the same direction as the current vehicle and are within a preset distance. Based on the number of surrounding vehicles and the charging intention information, a resource competition coefficient is generated; The multi-level triggering conditions are modified based on the resource competition coefficient; the resource competition coefficient is negatively correlated with the triggering threshold of the multi-level triggering conditions.

[0010] In one possible implementation, the execution of the corresponding response operation also includes: Perform at least one of the following management operations based on the control signal: adjust the coasting energy recovery intensity to the maximum value, limit the vehicle's maximum output power, automatically switch to an economy driving mode, and force engine intervention for hybrid vehicles to conserve battery power.

[0011] In one possible implementation, obtaining real-time status information of charging piles within the target charging range includes: When the vehicle is detected to be in a communication blind spot, it receives charging pile information broadcast by the roadside unit through vehicle-road cooperative communication. The charging pile information includes the location, availability and fault status of the charging pile. The charging pile information broadcast by the roadside unit is used as the real-time status information of the charging pile.

[0012] In one possible implementation, before matching the charging pile's real-time status information with multi-level triggering conditions, the method further includes: Obtain the user's historical charging behavior data, and calculate the user's average remaining battery life at the start of charging based on the historical charging behavior data; The multi-level triggering conditions are corrected based on the average remaining battery life at the start of charging; the average remaining battery life at the start of charging is negatively correlated with the triggering threshold of the multi-level triggering conditions.

[0013] Secondly, the present invention also provides a charging resource management and scheduling system, comprising: The generation module is used to obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius; The acquisition module is used to acquire real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. The processing module is used to match the real-time status information of the charging pile with multi-level triggering conditions and generate a control signal corresponding to the matching result. The control module is used to execute corresponding response operations according to the control signal, and to terminate the execution of the response operation when the real-time status information of the charging pile meets the preset recovery conditions.

[0014] Thirdly, the present invention also provides an intelligent vehicle, including a memory and a processor, wherein, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the charging resource management and scheduling method described in any of the above implementations.

[0015] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps of the charging resource management and scheduling method described in any of the above implementations.

[0016] The beneficial effects of this invention are as follows: The charging resource management and scheduling method provided by this invention firstly proactively analyzes and issues warnings based on the density and status of charging piles within the driving range when the vehicle's remaining range is still sufficient. Users can plan routes and adjust their trips in advance before charging resources are completely depleted, effectively avoiding the risk of vehicle breakdown due to missing the optimal charging window and significantly improving travel safety. Furthermore, after meeting multiple trigger conditions and executing corresponding response operations, the system continuously monitors the status of charging piles and automatically downgrades or terminates response operations when resource conditions improve. This adapts to the dynamic changes in charging resources, avoiding frequent triggering and elimination of alarm signals during brief resource fluctuations, thus improving system stability and user comfort. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic flowchart of an embodiment of the charging resource management and scheduling method provided by the present invention; Figure 2 A schematic flowchart of another embodiment of the charging resource management and scheduling method provided by the present invention; Figure 3 A schematic flowchart of another embodiment of the charging resource management and scheduling method provided by the present invention; Figure 4 A schematic flowchart of another embodiment of the charging resource management and scheduling method provided by the present invention; Figure 5 A schematic diagram of an embodiment of the charging resource management and scheduling system provided by the present invention; Figure 6 A schematic diagram of an embodiment of the intelligent vehicle provided by the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] In the description of the embodiments of the present invention, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0021] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] This invention provides a charging resource management and scheduling method, system, intelligent vehicle, and storage medium, which are described below.

[0024] Figure 1 This is a schematic flowchart of an embodiment of the charging resource management and scheduling method provided by the present invention, as shown below. Figure 1 As shown, the charging resource management and scheduling method includes: S101. Obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius.

[0025] It should be noted that after the vehicle starts, the Vehicle Control Unit (VCU) obtains the remaining driving range information of the vehicle through the vehicle's CAN network. For pure electric vehicles, this driving range is calculated by the Battery Management System (BMS) based on the current battery state of charge (SOC), battery temperature, and historical energy consumption data. For hybrid vehicles, this driving range is the sum of the pure electric driving range and the fuel driving range. Simultaneously, the VCU obtains the vehicle's precise current location coordinates through an onboard positioning module (such as GPS / BeiDou). The VCU sends the above information to the navigation module or onboard communication module, which then delineates a circular area on the map data with the current location as the center and the current driving range as the radius, serving as the target charging range for this operation.

[0026] S102. Obtain the real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles.

[0027] It should be noted that the VCU sends a request to the cloud-based charging service platform via the onboard communication module (T-BOX), requesting the geographical boundary information of the target charging range and the current timestamp. Based on the request, the cloud platform retrieves real-time status data of all charging stations within that range and returns it to the vehicle. The real-time status information of the charging stations includes at least: the total number of available fast charging stations, the total number of available slow charging stations, the number of currently available fast charging stations, the number of currently available slow charging stations, and detailed information such as the detailed location, interface type, real-time occupancy status, and estimated waiting time for each charging station.

[0028] S103. Match the real-time status information of the charging pile with the multi-level triggering conditions to generate a control signal corresponding to the matching result.

[0029] It should be noted that the VCU has pre-stored multiple levels of trigger conditions, which are calibrated based on data such as the maximum adjacent interval distance of charging piles in China and the charging demand characteristics during holidays. In this embodiment, a three-level threshold division is used as an example. The VCU compares the number of available fast charging piles and the number of idle fast charging piles obtained in step S102 with the thresholds at each level. If the number of available fast charging piles is ≥10 and the number of idle fast charging piles is ≥3, it is determined that the charging resources are sufficient, and the VCU does not generate an alarm control signal, or generates a status signal representing "normal". If the number of available fast charging piles is <10 or the number of idle fast charging piles is ≤3, it is determined that the charging resources are scarce, and the VCU generates a level one warning control signal. If the number of available fast charging piles is <6 or the number of idle fast charging piles is ≤1, it is determined that the charging resources are severely insufficient, and the VCU generates a level two warning control signal. If the number of available fast charging piles is <1 and the number of available slow charging piles is <1, it is determined that the charging resources are exhausted, and the VCU generates a level three warning control signal. For hybrid vehicles, the number of gas stations is also included as a supplementary judgment criterion in the above judgment conditions.

[0030] S104. Execute the corresponding response operation according to the control signal, and terminate the execution of the response operation when the real-time status information of the charging pile meets the preset recovery conditions.

[0031] It should be noted that the VCU sends the generated control signals to the instrument panel controller and the smart cockpit controller via the CAN bus. Each controller executes the corresponding response operation according to the signal level. While executing the above response operation, the VCU continuously repeats steps S101 to S103 at preset time intervals (e.g., 30 seconds) to monitor the status changes of charging piles within the target charging range in real time. When the real-time status information of the charging pile is detected to rise above the threshold of the previous warning level, the VCU determines that the recovery conditions are met, generates a downgrade control signal and sends it to the instrument panel and smart cockpit system, thereby terminating the current level of response operation and switching to a lower level or terminating completely.

[0032] In summary, the charging resource management and scheduling method provided by this invention firstly proactively analyzes and issues warnings based on the density and status of charging piles within the vehicle's remaining range when the vehicle still has sufficient remaining range. Users can plan routes and adjust their trips in advance before charging resources are completely depleted, effectively avoiding the risk of vehicle breakdown due to missing the optimal charging window and significantly improving travel safety. Furthermore, after meeting multiple trigger conditions and executing corresponding response operations, the system continuously monitors the charging pile status and automatically downgrades or terminates response operations when resource conditions improve. This adapts to the dynamic changes in charging resources, avoiding frequent triggering and elimination of alarm signals during brief resource fluctuations, thus improving system stability and user comfort.

[0033] In some embodiments of the present invention, after obtaining the current driving range, the method further includes: The vehicle obtains real-time road condition and weather information of its current environment, and corrects the current driving range based on the real-time road condition and weather information to generate a corrected driving range. It should be noted that, based on the aforementioned step S101, the Vehicle Control Unit (VCU) or Domain Controller sends a request to the cloud service platform via the onboard communication module (T-BOX) to obtain real-time traffic and weather information for the vehicle's current location. Real-time traffic information includes, but is not limited to, the length and degree of congestion on the road ahead, road gradient information (such as the length and gradient of uphill sections), road surface conditions (slippery, snow-covered, under construction, etc.), and estimated travel time. Real-time traffic information can be obtained in real-time through the application programming interface (API) of navigation map service providers (such as high-precision maps), or by receiving traffic information broadcast by roadside units through vehicle-to-infrastructure communication. Weather information includes, but is not limited to, the current and forward area's temperature, wind speed, precipitation type and intensity, and snow depth. Weather information can be obtained through onboard meteorological sensors or through a cloud-based meteorological service platform. Based on the obtained real-time traffic and weather information, the VCU calls a preset energy consumption impact model to calculate the comprehensive energy consumption correction coefficient. The energy consumption impact model is established based on vehicle calibration data and reflects the weight of different environmental factors on energy consumption per unit mileage. The process involves calculating a slope impact factor based on road gradient information, a temperature impact factor based on real-time temperature information, and a congestion impact factor based on congestion information. The VCU multiplies or weights these impact factors to generate a comprehensive energy consumption correction coefficient. The formula for the energy consumption correction coefficient is: Energy Consumption Correction Coefficient = First Weighting Coefficient × Slope Impact Factor + Second Weighting Coefficient × Temperature Impact Factor + Third Weighting Coefficient × Congestion Impact Factor. The VCU obtains the original driving range value (calculated by the battery management system or vehicle controller based on the remaining battery power) and divides it by the comprehensive energy consumption correction coefficient to generate the corrected driving range = Original Driving Range / Energy Consumption Correction Coefficient. If the correction coefficient is greater than 1, the corrected driving range is less than the original driving range, indicating that the actual achievable distance is shortened due to environmental factors. If the correction coefficient is less than 1, the corrected driving range is greater than the original driving range, indicating that the actual achievable distance is extended due to environmental factors (such as downhill sections or tailwinds).

[0034] In addition, the VCU can further adjust the correction coefficient based on the vehicle's driving mode (such as Eco, Sport, and Snow modes). When the vehicle is in Eco mode, the energy consumption control strategy is more conservative, and the VCU appropriately reduces the correction coefficient, resulting in a relatively larger corrected driving range. When the vehicle is in Sport mode, energy consumption is higher, and the VCU appropriately increases the correction coefficient, resulting in a relatively smaller corrected driving range.

[0035] The target charging range is regenerated with the current location as the center and the corrected driving range as the radius.

[0036] It should be noted that the VCU uses the corrected driving range as the new radius, with the vehicle's current location as the center, to regenerate the target charging range. This corrected target charging range replaces the original target charging range and is used for subsequent acquisition of charging station status information and early warning judgments. During vehicle operation, the VCU continuously repeats the above correction process at preset time intervals (such as 1 minute or every 5 kilometers traveled), dynamically updating the target charging range to ensure that the range on which early warning judgments are based always remains consistent with the vehicle's actual achievable capability.

[0037] In this embodiment, by acquiring real-time road and weather information, the original driving range is dynamically corrected to ensure a precise match between the target charging range and the actual achievable capability. This avoids misjudgments or missed judgments caused by inflated range claims or sudden environmental changes, significantly improving the accuracy and reliability of the warning. Furthermore, by proactively narrowing the target charging range under adverse conditions and triggering the warning earlier, the risk of missed alarms is effectively reduced, preventing vehicles from breaking down due to inflated range claims. Moreover, under favorable conditions, the warning range is appropriately expanded to avoid premature alarms and user interference, thus improving the user experience.

[0038] In some embodiments of the present invention, such as Figure 2 As shown, after obtaining the real-time status information of charging piles within the target charging range, the method further includes: S201. Obtain historical occupancy data of each charging pile within the target charging range, including occupancy rates for each time period and occupancy curves for holidays; S202. Based on the historical occupancy data and the estimated time for vehicles to arrive at each charging station, predict the predicted occupancy status of each charging station at the time of vehicle arrival. S203. Remove the charging piles whose predicted occupancy status is occupied from the number of available charging piles and the number of idle charging piles, and generate corrected real-time status information of the charging piles.

[0039] It should be noted that after obtaining the real-time status information of charging piles within the target charging range, the Vehicle Control Unit (VCU) or the Onboard Communication Module (T-BOX) sends a request to the cloud-based charging service platform to obtain the historical occupancy data of each charging pile within the target charging range. The cloud service platform retrieves the aforementioned historical data for all charging piles within the range based on the geographical range information sent by the VCU and the current timestamp, and returns it to the vehicle. After obtaining the location information of each charging pile, the VCU, combined with the current vehicle location and the route planning information provided by the navigation module, calculates the estimated time for the vehicle to reach each charging pile. The VCU matches the estimated arrival time of each charging pile with the corresponding historical occupancy data to predict the occupancy status of the charging pile at the time of vehicle arrival. The VCU removes charging piles predicted to be "occupied" from the original number of available and idle charging piles, generating corrected real-time charging pile status information. Specifically, the calculation method is as follows: Corrected number of available charging piles = Original number of available charging piles. Predict the number of charging stations already occupied upon arrival. Corrected number of available charging stations = Original number of available charging stations. Predict the number of charging stations that are already occupied upon arrival.

[0040] In this embodiment, by introducing historical occupancy data and arrival time estimation, the occupancy status of charging piles at the time of vehicle arrival is predicted, false vacant charging piles are identified and removed from the effective resources, avoiding warning failures and user charging failures caused by misjudgment, improving the accuracy of identifying truly available charging pile resources, and recommending the charging route that is actually reachable and has the shortest waiting time to users, thereby improving charging efficiency and user experience.

[0041] In some embodiments of the present invention, such as Figure 3 As shown, before generating the control signal corresponding to the matching result, the process also includes: S301. Obtain the driving status information and charging intention information of surrounding vehicles through vehicle network communication. The surrounding vehicles are vehicles that are traveling in the same direction as the current vehicle and are within a preset distance.

[0042] It should be noted that: The vehicle control unit (VCU) or the onboard communication module (T-BOX) activates the vehicle-to-everything (V2X) communication function, establishing a direct communication link with surrounding vehicles via cellular vehicle-to-everything (C-V2X) or dedicated short-range communication (DSRC) technology. The VCU sends a broadcast request via V2X, requesting information including the current vehicle's direction of travel, location coordinates, and speed. Upon receiving the broadcast, surrounding vehicles determine whether they meet the conditions of "being in the same direction of travel as the current vehicle and within a preset distance." If so, they respond by returning their own driving status information and charging intention information. The driving status information includes, but is not limited to, current location, driving speed, heading angle, remaining range, and current state of charge (SOC).

[0043] S302. Generate a resource competition coefficient based on the number of surrounding vehicles and the charging intention information; S303. The multi-level triggering conditions are modified according to the resource competition coefficient; the resource competition coefficient is negatively correlated with the triggering threshold of the multi-level triggering conditions.

[0044] It should be noted that the VCU generates a resource competition coefficient based on the acquired information about surrounding vehicles. This coefficient quantifies the intensity of competition for charging resources that the current vehicle may face within the target charging range. One formula for calculating the resource competition coefficient is as follows: Resource Competition Coefficient = α × Number of Surrounding Vehicles Factor + β × Percentage of Vehicles with Charging Intent Factor. Of course, surrounding vehicles closer to the current vehicle are assigned higher weights. Another formula for calculating the resource competition coefficient is as follows: Resource Competition Coefficient = Σ(Weight of Vehicle i × Charging Intent Indication Function i), where the weight of vehicle i is inversely proportional to the distance to the current vehicle, calculated using a Gaussian decay function or a linear decay function.

[0045] The VCU dynamically adjusts the trigger thresholds in the preset multi-level triggering conditions based on the generated resource contention coefficient. The resource contention coefficient and the trigger thresholds of the multi-level triggering conditions are negatively correlated. The VCU uses the adjusted multi-level triggering conditions as a new judgment benchmark for subsequent matching of real-time charging pile status information. During vehicle operation, the VCU continuously repeats the above steps at preset time intervals (e.g., 30 seconds), dynamically updating the resource contention coefficient and the adjusted trigger thresholds to ensure that the warning strategy responds in real-time to changes in the surrounding vehicle situation.

[0046] In this embodiment, by acquiring the driving status and charging intentions of surrounding vehicles through vehicle-to-everything (V2X) communication, the true scarcity of charging resources can be comprehensively assessed. Through the calculation of a resource competition coefficient, multi-dimensional information such as the number of surrounding vehicles, their distance, and their charging intentions is quantified into a quantifiable resource competition coefficient. A negative correlation is established between this coefficient and the trigger thresholds of multi-level triggering conditions. When competition is intense, the trigger threshold is proactively lowered, and early warnings are issued, allowing users more time for decision-making and action. This allows for early detection of such competitive situations and triggers warnings, guiding users to choose to exit the highway for charging or adjust their routes, effectively avoiding competition risks.

[0047] In some embodiments of the present invention, the execution of the corresponding response operation also includes: Perform at least one of the following management operations based on the control signal: adjust the coasting energy recovery intensity to the maximum value, limit the vehicle's maximum output power, automatically switch to an economy driving mode, and force engine intervention for hybrid vehicles to conserve battery power.

[0048] It should be noted that when executing the steps of responding to the control signal, the Vehicle Control Unit (VCU) or Domain Controller simultaneously sends the control signal to the Vehicle Energy Management System (EMS) or Powertrain Domain Controller. The Energy Management System, as the core control unit for vehicle energy distribution, is responsible for coordinating and controlling the drive motor, battery, engine (hybrid models), and energy recovery system. The VCU sends a command to the Motor Controller (MCU) to adjust the coasting energy recovery intensity to its maximum value. The VCU also sends a command to the Motor Controller based on the control signal to limit the maximum output power of the drive motor. When the control signal reaches a preset intervention level, the VCU sends a command to the Driving Mode Management Module to automatically switch the vehicle's driving mode to Eco mode. For hybrid models, when the control signal reaches a preset intervention level, the VCU sends commands to the Engine Management System (EMS) and Hybrid Controller (HCU) to force the engine to engage in operation to conserve battery power. For example, during vehicle operation, the VCU continuously monitors changes in the warning level and dynamically adjusts the execution status of energy management operations accordingly: when the warning level drops from level three to level two, the VCU exits the "limit maximum output power" operation, but retains "adjust coasting energy recovery intensity to maximum value" and "automatically switch to economy driving mode". When the warning level drops from level two to level one, the VCU gradually exits various energy management operations, restoring the coasting energy recovery intensity, maximum output power limit, driving mode, etc., to the user-preset or system default states.

[0049] In some embodiments of the present invention, obtaining real-time status information of charging piles within the target charging range includes: When the vehicle is detected to be in a communication blind spot, it receives charging pile information broadcast by the roadside unit through vehicle-road cooperative communication. The charging pile information includes the location, availability and fault status of the charging pile. The charging pile information broadcast by the roadside unit is used as the real-time status information of the charging pile.

[0050] It should be noted that during vehicle operation, the onboard communication module (T-BOX) continuously monitors the signal strength and connection status of the cellular network (4G / 5G). A communication blind spot is defined as an area where the vehicle's location cannot establish a stable data connection with the cloud-based charging service platform via the cellular network. Vehicle-to-everything (V2X) communication is based on Cellular Vehicle-to-Everything (C-V2X) or Dedicated Short Range Communication (DSRC) technology to achieve direct communication between the vehicle and the roadside unit. When the vehicle enters the communication coverage area of ​​the Roadside Unit (RSU) (typically 300-500 meters), the Onboard Unit (OBU) automatically initiates a connection or listens to the RSU's periodic broadcasts. The RSU broadcasts information about nearby charging stations at a fixed frequency (e.g., once per second). After receiving the charging station information broadcast by the RSU, the OBU transmits it to the Vehicle Control Unit (VCU) via the vehicle network. The VCU uses the received information as the real-time status information of charging stations within the current target charging range, replacing the information originally obtained from the cloud. The VCU parses and stores the received charging station information to form a local charging station status list. While the vehicle is in motion, the VCU continuously monitors the broadcast information from RSUs (Roadside Units) along the route and dynamically updates the charging station status list based on the vehicle's location. When the vehicle leaves the coverage area of ​​one RSU and enters the coverage area of ​​another, the VCU integrates information from multiple RSUs to form a continuous charging station status awareness. When the vehicle leaves a communication blind spot and the T-BOX detects that the cellular network signal has returned to normal and a connection with the cloud platform can be established, the VCU automatically retrieves the real-time charging station status information from the cloud again.

[0051] In this embodiment, by introducing vehicle-road cooperative communication, vehicles can still obtain charging station information through roadside unit broadcasts in areas without cellular network coverage, ensuring the continuity of the charging resource early warning function in various geographical environments. By deploying RSUs on key road sections, necessary charging station information support is provided for vehicles entering remote areas, enabling drivers to obtain charging resource status in a timely manner before entering or within blind spots, plan charging routes in advance, avoid the risk of breakdowns due to missing information, and significantly improve the safety of travel in remote areas.

[0052] In some embodiments of the present invention, such as Figure 4 As shown, before matching the real-time status information of the charging pile with the multi-level triggering conditions, the process also includes: S401. Obtain the user's historical charging behavior data, and calculate the user's average remaining battery life at the start of charging based on the historical charging behavior data. S402. The multi-level triggering conditions are corrected based on the average remaining battery life at the start of charging; the average remaining battery life at the start of charging is negatively correlated with the triggering threshold of the multi-level triggering conditions.

[0053] It should be noted that before performing the step of matching the real-time status information of the charging pile with multi-level triggering conditions, the vehicle controller (VCU) or domain controller obtains the user's historical charging behavior data from the on-board storage or cloud-based user profiling platform. This historical charging behavior data includes at least the remaining driving range at the start of charging, the battery percentage (SOC) at the start of charging, the charging triggering method (user-initiated charging, passive charging after a low battery warning, or charging triggered by other reasons), charging scenario markers (such as holidays, long-distance driving, near the destination, etc.), and charging location type (such as highway service areas, urban fast charging stations, residential slow charging piles, charging stations in remote areas, etc.). The VCU extracts the user's starting remaining driving range value for a recent period (such as the past 90 days or the last 30 charging events) from the historical charging behavior data and calculates the user's average starting remaining driving range value according to a preset statistical method. The VCU dynamically adjusts the trigger thresholds in the preset multi-level trigger conditions based on the calculated average remaining battery life at the start of charging (or the average value in a specific scenario). The average remaining battery life at the start of charging is negatively correlated with the trigger thresholds of the multi-level trigger conditions; that is, the larger the average remaining battery life at the start of charging, the smaller the trigger threshold of the trigger conditions.

[0054] In this embodiment, by analyzing users' historical charging behavior, the system identifies users' actual charging habits and enables personalized customization of early warning strategies. This fundamentally solves the problem of the inapplicability of uniform thresholds, improving the system's intelligence and user-friendliness. Furthermore, through scenario-based segmentation, user behavior models are established for different scenarios, allowing early warning strategies to automatically switch according to the current trip type. This effectively reduces the disturbance of invalid warnings to users and improves the user experience.

[0055] To better implement the charging resource management and scheduling method in this embodiment of the invention, based on the charging resource management and scheduling method, correspondingly, as follows: Figure 5 As shown, this embodiment of the invention also provides a charging resource management and scheduling system 500, which includes: The generation module 501 is used to obtain the current location and current driving range of the vehicle, and generate a target charging range with the current location as the center and the current driving range as the radius; The acquisition module 502 is used to acquire real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. Processing module 503 is used to match the real-time status information of the charging pile with multi-level triggering conditions and generate a control signal corresponding to the matching result; The control module 504 is used to execute a corresponding response operation according to the control signal, and to terminate the execution of the response operation when the real-time status information of the charging pile meets the preset recovery conditions.

[0056] The charging resource management and scheduling system 500 provided in the above embodiments can implement the technical solutions described in the above embodiments of the charging resource management and scheduling method. The specific implementation principles of each module or unit can be found in the corresponding content in the above embodiments of the charging resource management and scheduling method, and will not be repeated here.

[0057] like Figure 6 As shown, the present invention also provides an intelligent vehicle 600. The intelligent vehicle 600 includes a processor 601, a memory 602, and a display 603. Figure 6 Only some of the components of the intelligent vehicle 600 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0058] In some embodiments, processor 601 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 602 or process data, such as the charging resource management and scheduling method of the present invention.

[0059] In some embodiments, processor 601 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 601 may be local or remote. In some embodiments, processor 601 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, intranet, multi-cloud, etc., or any combination thereof.

[0060] In some embodiments, memory 602 may be an internal storage unit of the intelligent vehicle 600, such as a hard disk or memory of the intelligent vehicle 600. In other embodiments, memory 602 may also be an external storage device of the intelligent vehicle 600, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the intelligent vehicle 600.

[0061] Furthermore, the memory 602 may include both internal storage units of the intelligent vehicle 600 and external storage devices. The memory 602 is used to store application software and various types of data installed on the intelligent vehicle 600.

[0062] In some embodiments, display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 603 is used to display information from the intelligent vehicle 600 and to display a visual user interface. Components 601-603 of the intelligent vehicle 600 communicate with each other via a system bus.

[0063] In one embodiment, when the processor 601 executes the charging resource management scheduler in the memory 602, the following steps can be implemented: Obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius; Obtain real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. The real-time status information of the charging pile is matched with multi-level triggering conditions to generate a control signal corresponding to the matching result. The corresponding response operation is executed according to the control signal, and the execution of the response operation is terminated when the real-time status information of the charging pile meets the preset recovery conditions.

[0064] It should be understood that when the processor 601 executes the charging resource management scheduler in the memory 602, in addition to the functions mentioned above, it can also perform other functions, as detailed in the description of the corresponding method embodiments above.

[0065] Furthermore, this embodiment of the invention does not specifically limit the type of intelligent vehicle 600 mentioned. Intelligent vehicle 600 can be a portable intelligent vehicle such as a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, or laptop computer. Exemplary embodiments of portable intelligent vehicles include, but are not limited to, portable intelligent vehicles running iOS, Android, Microsoft, or other operating systems. The aforementioned portable intelligent vehicle can also be other portable intelligent vehicles, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the invention, intelligent vehicle 600 may not be a portable intelligent vehicle, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0066] Accordingly, this application also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the programs or instructions are executed by a processor, they can implement the steps or functions of the charging resource management and scheduling methods provided in the above-described method embodiments.

[0067] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0068] The charging resource management and scheduling method, system, equipment, and medium provided by the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A charging resource management and scheduling method, characterized in that, include: Obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius; Obtain real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. The real-time status information of the charging pile is matched with multi-level triggering conditions to generate a control signal corresponding to the matching result. The corresponding response operation is executed according to the control signal, and the execution of the response operation is terminated when the real-time status information of the charging pile meets the preset recovery conditions.

2. The method according to claim 1, characterized in that, After obtaining the current driving range, it also includes: The vehicle obtains real-time road condition and weather information of its current environment, and corrects the current driving range based on the real-time road condition and weather information to generate a corrected driving range. The target charging range is regenerated with the current location as the center and the corrected driving range as the radius.

3. The method according to claim 1, characterized in that, After obtaining the real-time status information of charging piles within the target charging range, the method further includes: Obtain historical occupancy data for each charging pile within the target charging range, including occupancy rates for different time periods and occupancy curves during holidays; Based on the historical occupancy data and the estimated time for vehicles to arrive at each charging station, the predicted occupancy status of each charging station at the time of vehicle arrival is predicted. The charging piles predicted to be occupied are removed from the number of available charging piles and the number of idle charging piles, and the corrected real-time status information of the charging piles is generated.

4. The method according to claim 1, characterized in that, Before generating the control signal corresponding to the matching result, the following steps are also included: The vehicle network communication is used to obtain the driving status information and charging intention information of surrounding vehicles. The surrounding vehicles are those that are traveling in the same direction as the current vehicle and are within a preset distance. Based on the number of surrounding vehicles and the charging intention information, a resource competition coefficient is generated; The multi-level triggering conditions are modified based on the resource competition coefficient; the resource competition coefficient is negatively correlated with the triggering threshold of the multi-level triggering conditions.

5. The method according to claim 1, characterized in that, In addition to executing the corresponding response operation, it also includes: Perform at least one of the following management operations based on the control signal: adjust the coasting energy recovery intensity to the maximum value, limit the vehicle's maximum output power, automatically switch to an economy driving mode, and force engine intervention for hybrid vehicles to conserve battery power.

6. The method according to claim 1, characterized in that, Obtaining real-time status information of charging piles within the target charging range includes: When the vehicle is detected to be in a communication blind spot, it receives charging pile information broadcast by the roadside unit through vehicle-road cooperative communication. The charging pile information includes the location, availability and fault status of the charging pile. The charging pile information broadcast by the roadside unit is used as the real-time status information of the charging pile.

7. The method according to claim 1, characterized in that, Before matching the real-time status information of the charging pile with the multi-level triggering conditions, the process also includes: Obtain the user's historical charging behavior data, and calculate the user's average remaining battery life at the start of charging based on the historical charging behavior data; The multi-level triggering conditions are corrected based on the average remaining battery life at the start of charging; the average remaining battery life at the start of charging is negatively correlated with the triggering threshold of the multi-level triggering conditions.

8. A charging resource management and scheduling system, characterized in that, include: The generation module is used to obtain the vehicle's current location and current driving range, and generate a target charging range with the current location as the center and the current driving range as the radius; The acquisition module is used to acquire real-time status information of charging piles within the target charging range. The real-time status information of charging piles includes at least the number of available charging piles and the number of idle charging piles. The processing module is used to match the real-time status information of the charging pile with multi-level triggering conditions and generate a control signal corresponding to the matching result. The control module is used to execute corresponding response operations according to the control signal, and to terminate the execution of the response operation when the real-time status information of the charging pile meets the preset recovery conditions.

9. An intelligent vehicle, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the charging resource management and scheduling method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the charging resource management and scheduling method according to any one of claims 1 to 7.

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