Vehicle charging and discharging cloud control method and vehicle charging and discharging control method

Abstract

The invention relates to a cloud control method for vehicle charging and discharging. The method comprises the following steps: predicting estimated charging setting parameters of a vehicle (1) in each charging time period based on behavior habit data of a user; planning a charging and discharging plan of the vehicle in each charging time period at least based on the predicted estimated charging setting parameter, the power supply related information and the power consumption / power generation information of the building system (5), so as to optimize the overall power consumption cost of the building system and the vehicle, the building system and the vehicle being capable of supplying electric energy to each other; and determining charging and discharging control parameters of the vehicle in each charging time period based on the planned charging and discharging plan, and sending the determined charging and discharging control parameters to the vehicle and / or a charging device (4) for charging the vehicle. According to the invention, the characteristic that the building system and the vehicle can supply electric energy to each other is fully utilized, so that the overall electricity cost of the building system and the vehicle is reduced as much as possible.

Description

Technical Field

[0001] The present application relates to the technical field of electric vehicle charging, and in particular to a method for cloud-based control of vehicle charging and discharging, a cloud server, a method for controlling vehicle charging and discharging, a vehicle, a charging device, and a computer program product for at least assisting in implementing the steps of the method described in the present application. Background Art

[0002] With the development and popularization of electric vehicle charging technology, users can charge their electric vehicles using charging piles installed in home garages or office buildings. Users' houses or office buildings may also be equipped with power generation equipment such as solar panels to power the building system. After connecting to the charging pile, the electric vehicle will start the charging process until the battery is fully charged and the charging process automatically stops. However, on the one hand, electric vehicles cannot fully utilize the electricity generated by the building system to charge the vehicle battery. On the other hand, when the power supply network adopts time-of-use electricity prices, it is also impossible to fully utilize the valley electricity price period to charge the vehicle battery, and it is also impossible to use the vehicle battery to power the building system during the peak electricity price period, which leads to high electricity costs for vehicle charging and building systems.

[0003] Therefore, how to optimize the electricity cost of vehicle charging and building systems has become a technical problem that needs to be solved. Summary of the invention

[0004] The purpose of the present application is to provide a method for cloud-based control of vehicle charging and discharging, a cloud server, a method for controlling vehicle charging and discharging, a vehicle, a charging device, and a computer program product to at least partially solve the problems in the prior art.

[0005] According to a first aspect of the present application, a method for cloud-based control of vehicle charging and discharging is provided, and the method may include:

[0006] - Predict the estimated charging setting parameters of the vehicle in each charging time period based on the user's behavior habit data;

[0007] - planning a charging and discharging plan for the vehicle in each charging time period based at least on the predicted estimated charging setting parameters, the power supply related information and the power consumption / generation information of the building system, so as to optimize the overall power cost of the building system and the vehicle, wherein the building system and the vehicle can supply power to each other; and

[0008] - Determining charging and discharging control parameters of the vehicle in each charging time period based on the planned charging and discharging plan, and sending the determined charging and discharging control parameters to the vehicle and / or a charging device for charging the vehicle.

[0009] The core concept of the present application is that in the application scenario of charging a vehicle using a charging device with fixed usage rights installed in a building system, the charging and discharging plan of the vehicle in each charging time period can be automatically planned and corresponding charging and discharging control parameters can be set based on the user's behavioral habit data, power supply related information and the building system's power consumption / generation information, so that while ensuring that the battery power reaches the final charge state that meets the user's vehicle usage habits when the vehicle finishes charging, the characteristic that the building system and the vehicle can supply electricity to each other can be fully utilized to reduce the overall electricity cost of the building system and the vehicle as much as possible.

[0010] According to an optional embodiment of the present application, when planning the charging and discharging plan of the vehicle in each charging time period based at least on the predicted estimated charging setting parameters, power supply related information, and power consumption information and power generation information of the building system, a predetermined battery health maintenance principle can be additionally introduced as an influencing factor for planning the charging and discharging plan to optimize the battery health status of the vehicle.

[0011] According to another optional embodiment of the present application, the user's behavioral habit data may include the user's driving behavior data and / or the user's charging behavior data, wherein the user's driving behavior data includes historical data on the vehicle's departure time, and / or historical data on the vehicle's driving distance, and / or the user's itinerary planning information for a future time period, etc., and the user's charging behavior data includes historical data on the charging start time, and / or historical data on the final state of charge of the battery when the vehicle finishes charging, and / or historical data on the charging power set by the user, etc.

[0012] According to another optional embodiment of the present application, the estimated charging setting parameters may include the charging end time of one or more future charging and discharging cycles and the final charge state of the battery when the vehicle finishes charging.

[0013] According to another optional embodiment of the present application, based on a predetermined battery health maintenance principle, the final state of charge of the battery when the vehicle finishes charging is set to be no higher than a predetermined state of charge threshold, and / or the idle time period from the moment the battery reaches the final state of charge to the moment charging ends is reduced, and / or the battery charging power is reduced on the premise that the vehicle can reach the set final state of charge when charging ends, and so on.

[0014] According to another optional embodiment of the present application, the power supply related information may include time-of-use electricity price information, wherein the vehicle's charging and discharging plan in each charging time period can be planned at least based on the predicted estimated charging setting parameters, the time-of-use electricity price information and the power consumption / generation information of the building system, and the vehicle's charging and discharging control parameters can be determined based on the planned charging and discharging plan, wherein the charging and discharging control parameters include the battery charging power and / or battery discharging power in the battery charging process, and / or the start and / or termination of the battery charging process, wherein the time-of-use electricity price information is changed according to the time period and / or is predicted based on weather change information and / or power demand change information.

[0015] According to another optional embodiment of the present application, when the power generation of the building system is greater than the power consumption, the electric energy generated by the building system can be used to charge the battery of the vehicle.

[0016] According to another optional embodiment of the present application, when the time-of-use electricity price exceeds a preset electricity price threshold, the battery of the vehicle can be controlled to discharge to supply power to the building system and / or output electrical energy to the power supply network.

[0017] According to another optional embodiment of the present application, the overall power consumption cost of the building system and the vehicle, as well as the electricity sales revenue obtained by the vehicle and / or the building system from outputting electricity to the power supply network can be calculated based on the time-of-use electricity price information, the power consumption / power generation information of the building system, and the changes in the battery charging power and battery discharging power of the vehicle over time.

[0018] According to another optional embodiment of the present application, the power supply related information may include peak shaving request information and / or valley filling request information, wherein the charging and discharging plan of the vehicle in each charging time period is planned at least based on the predicted estimated charging setting parameters, the power consumption / generation information of the building system and the peak shaving request information and / or valley filling request information, and the charging and discharging control parameters of the vehicle are determined based on the planned charging and discharging plan, wherein the charging and discharging control parameters may include the battery charging power in the battery charging process, and / or the start and / or termination of the battery charging process, etc., wherein the compensation income obtained by the vehicle through the peak shaving auxiliary service and / or valley filling auxiliary service is calculated based on the change process of the battery charging power of the vehicle over time and the peak shaving request information and / or valley filling request information.

[0019] According to another optional embodiment of the present application, the overall electricity cost of the building system and the vehicle can be calculated based on the calculated overall electricity consumption cost of the building system and the vehicle, the electricity sales income and / or the compensation income, and the overall electricity cost of the building system and the vehicle can be optimized on the premise that the set final charge state can be reached when the vehicle finishes charging.

[0020] According to another optional embodiment of the present application, the power consumption / power generation information of the building system may include the power consumption change information of the building system, and / or the power consumption historical data of the building system, and / or the power generation change information of the building system, and / or the power generation prediction information of the building system, etc., wherein the power generation prediction information of the building system is especially based on weather change information and / or the power generation equipment parameter prediction of the building system.

[0021] According to another optional embodiment of the present application, the estimated charging setting parameters of the vehicle in each charging time period can be predicted by a prediction model based on the user's behavioral habit data, wherein the prediction model includes, for example, a machine learning model, a linear and logistic regression model and / or a neural network model.

[0022] According to another optional embodiment of the present application, actual charging setting parameters of the vehicle are obtained in a corresponding charging time period, and the prediction model is optimized based on the deviation between the estimated charging setting parameters and the actual charging setting parameters, for example, through a self-learning algorithm.

[0023] According to a second aspect of the present application, a cloud server is provided, which is configured to execute the method for cloud-based control of vehicle charging and discharging according to the present application.

[0024] According to a third aspect of the present application, a method for controlling vehicle charging and discharging is provided, and the method may include:

[0025] - In response to the charge and discharge control parameters received from the cloud server according to the present application, the charge and discharge process of the vehicle can be controlled based at least on the received charge and discharge control parameters.

[0026] According to a fourth aspect of the present application, a vehicle is provided, which may include the following components:

[0027] - an on-board communication unit configured to receive charging and discharging control parameters from a cloud server according to the present application; and

[0028] - An on-board control unit, which is configured to execute the method for controlling vehicle charging and discharging according to the present application.

[0029] According to a fifth aspect of the present application, a charging device is provided, and the charging device may include the following components:

[0030] - a pile-end communication unit, which is configured to receive charging and discharging control parameters from a cloud server according to the present application; and

[0031] A pile end control unit, which is configured to be used in the method for controlling vehicle charging and discharging according to the present application.

[0032] According to a sixth aspect of the present application, a computer program product, such as a computer-readable program carrier, is provided, which contains or stores computer program instructions, and when the computer program instructions are executed by a processor, they at least assist in implementing the steps of the method described in the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The principles, features and advantages of the present application may be better understood by describing the present application in more detail below with reference to the accompanying drawings. The accompanying drawings show:

[0034] Figure 1 A flowchart showing a method for cloud-based control of vehicle charging and discharging according to an exemplary embodiment of the present application is shown;

[0035] Figure 2 A schematic diagram of a charging scenario according to an exemplary embodiment of the present application is shown;

[0036] Figure 3 A schematic diagram showing a curve of battery state of charge changing over time during a vehicle charging process according to an exemplary embodiment of the present application; and

[0037] Figure 4 A method for controlling charging and discharging of a vehicle according to an exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0038] In order to make the technical problems, technical solutions and beneficial technical effects to be solved by the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and multiple exemplary embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the scope of protection of the present application.

[0039] Figure 1 A flowchart of a method for cloud-based control of vehicle charging and discharging according to an exemplary embodiment of the present application is shown. The following exemplary embodiments describe the method according to the present application in more detail.

[0040] like Figure 1As shown, the method for cloud-based control of vehicle charging and discharging may include steps S1 to S3. In step S1, the estimated charging setting parameters of vehicle 1 in each charging time period may be predicted based on the user's behavioral habit data. The method for cloud-based control of vehicle charging according to the present application is executed in the cloud server 2 of the vehicle manufacturer, and is particularly suitable for application scenarios in which electric vehicles are charged in a charging device 4 with fixed usage rights installed in a home garage or office building parking lot, that is, the charging device 4 is dedicated to a user or a user group (such as family members, company members, etc.). As Figure 2 A schematic diagram of a charging scenario according to an exemplary embodiment of the present application is shown. After the vehicle 1 is electrically connected to a charging device 4 with fixed usage rights installed in, for example, a home garage or an office building parking lot, the battery of the vehicle 1 can be charged by the charging device 4, and the charging device 4 can absorb electrical energy from the power supply network 3 or from the building system 5.

[0041] According to the regulatory requirements for electric vehicles, during the operation of the vehicle 1, the vehicle-mounted TBOX device must collect real-time monitoring data such as battery information, vehicle status information, vehicle location information, energy consumption data and / or charging data, namely RTM data, and transmit it to the cloud server 2 of the vehicle manufacturer through a wireless communication network after encryption. Here, the behavioral habit data may include the user's driving behavior data, such as historical data on the vehicle departure time and / or historical data on the vehicle's driving distance, which can reflect the user's vehicle usage habits for the vehicle 1, wherein, based on the historical data on the vehicle departure time, the charging end time of the vehicle 1 in one or more future charging and discharging cycles can be predicted, that is, the battery needs to be charged to the set final state of charge before the vehicle 1 departs, and based on the historical data on the vehicle's driving distance, the amount of electricity required for the daily driving of the vehicle 1 can be predicted, thereby setting the final state of charge of the battery when the vehicle ends charging according to the required electricity. In addition, the user's driving behavior data may also include the user's itinerary planning information for the future time period, which is obtained, for example, from the user's mobile terminal or social network account, etc. Based on the itinerary planning information, the prediction accuracy of the vehicle's driving distance in the future time period can be further improved, thereby improving the prediction accuracy of the set final state of charge.

[0042] The user's behavioral habit data may also include the user's charging behavior data - for example, historical data about the charging start time, and / or historical data about the final state of charge of the battery when the vehicle finishes charging, and / or historical data about the charging power set by the user, etc. These data can reflect the user's charging habits for the vehicle 1, wherein the charging start time of the vehicle 1 in one or more future charging and discharging cycles can be predicted based on the historical data about the charging start time, the final state of charge of the battery when the vehicle finishes charging, that is, the charge amount of the vehicle battery, can be predicted based on the historical data about the final state of charge of the battery when the vehicle finishes charging, and the charging power set by the user can be predicted based on the historical data about the charging power that meets the user's habits.

[0043] The user's behavior habit data can be input into the prediction model, and the prediction model can predict the estimated charging setting parameters of the vehicle 1 in each charging time period based on the user's behavior habit data, especially including the charging end time of one or more future charging and discharging cycles and the final charge state of the battery when the vehicle ends charging. Exemplarily, the prediction model may include a machine learning model, a linear and logistic regression model, and / or a neural network model, etc. In order to improve the prediction accuracy of the prediction model, the actual charging setting parameters of the vehicle 1 can be obtained in the corresponding charging time period, and the prediction model can be optimized based on the deviation between the estimated charging setting parameters and the actual charging setting parameters, for example, through a self-learning algorithm. It can be understood that as the prediction accuracy of the prediction model gradually improves, the predicted estimated charging setting parameters will become closer and closer to the actual charging setting parameters of the corresponding time period.

[0044] In step S2, the charging and discharging plan of the vehicle 1 in each charging time period can be planned based on at least the predicted estimated charging setting parameters, power supply related information and power consumption / generation information of the building system 5, so as to optimize the overall electricity cost of the building system 5 and the vehicle 1, wherein the building system 5 and the vehicle 1 can supply electricity to each other. In the meaning of the present application, the building system 5 can be an operating entity such as an independent house, an office building, etc. that can perform independent electricity bill settlement, and the charging device 4 is installed in the building system 5. Figure 2The direction of electric energy flow is shown by the thick line with arrows. The building system 5 can absorb electric energy from the power supply network 3 to power the electric devices (including the charging device 4) in the building system 5. A power generation device 51 such as a photovoltaic panel can also be installed in the building system 5. The electric energy generated by the power generation device 51 can not only be used to power the electric devices in the building system 5, including the charging device 4, but also can be transmitted to the power supply network 3 and obtain corresponding electricity sales income when the power generation power of the power generation device 51 exceeds the total power consumption of the building system 5. When the power generation power of the power generation device 51 is lower than the total power consumption of the building system 5, especially during the peak power period when the electricity price is high, the electric energy stored in the battery of the vehicle 1 can also be used to power the electric devices in the building system 5 to reduce the electric energy absorbed by the building system 5 from the power supply network 3 during the peak power period. Therefore, when the vehicle 1 is charged by the charging device 4 installed in the building system 5, the electricity cost of the building system 5 and the vehicle 1 as a whole can be optimized.

[0045] The cloud server 2 can obtain the power consumption / generation information of the building system 5 from the background server of the building system 5, which includes, for example, the power consumption change information of the building system 5, and / or the power consumption history data of the building system 5, and / or the power generation change information of the building system 5, and / or the power generation prediction information of the building system 5, etc., wherein the power generation prediction information of the building system 5 is especially predicted based on weather change information and / or the power generation equipment parameters (such as the installed power of the power generation equipment) of the building system 5. In the case that the power generation of the building system 5 is greater than the power consumption, the electric energy generated by the building system 5 can be used to charge the battery of the vehicle 1.

[0046] like Figure 2As shown, the cloud server 2 can obtain the power supply related data from the power grid server 31, which particularly includes time-sharing electricity price information, which changes according to the time period, for example, different electricity prices are divided according to different time periods (such as peak power period, valley power period, etc.). Since the electricity price in the peak power period is higher than the electricity price in the valley power period, the battery of the vehicle 1 is charged as much as possible in the valley power period on the premise that the vehicle can reach the set final state of charge when the charging is finished. In the case where the power supply network 3 adopts a dynamic electricity price coupled with the power market, the time-sharing electricity price information can also be predicted based on weather change information and / or power demand change information, so that the battery of the vehicle 1 can be charged as much as possible in the period of lower electricity price on the premise that the vehicle can reach the set final state of charge when the charging is finished. In the case where the time-sharing electricity price exceeds the preset electricity price threshold, especially in the peak power period, the battery of the vehicle 1 can also be controlled to discharge to supply power to the building system 5, and / or output electric energy to the power supply network 5 and obtain corresponding electricity sales income. Based on the time-of-use electricity price information, the power consumption / generation information of the building system 5, and the changes in the battery charging power and battery discharging power of the vehicle 1 over time, the overall power consumption cost of the building system 5 and the vehicle 1 and the electricity sales revenue obtained by the vehicle 1 and / or the building system 5 outputting electricity to the power supply network 5 can be calculated.

[0047] In the case where the vehicle 1 signs a peak shaving and valley filling auxiliary service agreement with the power supply network 3, the power supply related information may also include peak shaving request information and / or valley filling request information obtained from the power grid server 31, so as to control the vehicle 1 to participate in the peak shaving auxiliary service and / or valley filling auxiliary service of the power grid based on the instructions of the power grid server 31 during the charging process. Specifically, during the peak load period, the battery charging process can be stopped and / or the battery charging power can be reduced based on the peak shaving request information received from the power grid server 31; during the valley load period, the battery charging process can be started and / or the battery charging power can be increased based on the valley filling request information received from the power grid server 31. Then, the compensation income obtained through the peak shaving auxiliary service and / or valley filling auxiliary service can be calculated based on the peak shaving request information and / or valley filling request information. For example, according to the "Implementation Rules for the Management of Electric Power Auxiliary Services in East China", the compensation standard for adjustable loads participating in peak-shaving auxiliary services is 0.8 yuan / kWh, and the compensation standard for participating in valley-filling auxiliary services is 0.24 yuan / kWh. If vehicle 1 participates in peak-shaving auxiliary services during peak load periods, the compensation income per kilowatt-hour will be higher than the peak-valley electricity price difference of time-of-use electricity prices; if vehicle 1 participates in valley-filling auxiliary services during low load periods, vehicle 1 can obtain compensation income from valley-filling auxiliary services while using the electricity price during the valley electricity period.

[0048] Next, the overall electricity cost of the building system 5 and the vehicle 1 can be calculated based on the calculated overall electricity consumption cost, electricity sales income and / or compensation income of the building system 5 and the vehicle 1, and the overall electricity cost of the building system 5 and the vehicle 1 can be optimized on the premise that the set final charge state can be reached when the vehicle finishes charging. Here, the charging cost is the calculated overall electricity cost minus the calculated electricity sales income and / or compensation income, and the charging and discharging plan of the vehicle 1 in each charging time period can be formulated with minimizing the overall electricity cost as the objective function.

[0049] In step S3, the charge and discharge control parameters of the vehicle 1 in each charging time period may be determined based on the planned charge and discharge plan, and the determined charge and discharge control parameters may be sent to the vehicle 1 and / or the charging device 4 for charging the vehicle 1. Here, the charge and discharge control parameters may include, for example, the battery charging power and / or battery discharging power in the battery charging process, the start and / or termination of the battery charging process, etc. Exemplarily, the charging and discharging plan of the vehicle 1 in each charging time period can be planned at least based on the predicted estimated charging setting parameters, the time-of-use electricity price information and the power consumption / generation information of the building system 5, and the battery charging power and / or battery discharging power in the battery charging process of the vehicle 1, and / or the start and / or termination of the battery charging process, etc. can be determined based on the planned charging and discharging plan, so that the battery of the vehicle 1 can be controlled to charge as much electricity as possible using the surplus electricity generated by the building system 5 and / or the electricity in the low electricity price period on the premise that the vehicle can reach the set final charge state when the charging is finished, and the battery of the vehicle 1 can be controlled to provide as much electricity as possible to the building system 5 and / or the power supply network 3 in the high electricity price period, thereby reducing the overall electricity consumption cost of the building system 5 and the vehicle 1 while increasing the electricity sales revenue of the vehicle 1.

[0050] For example, the charging plan of the vehicle 1 in each charging time period can also be planned based on the peak shaving request information and / or valley filling request information, and the battery charging power and / or the start and / or termination of the battery charging process in the battery charging process can be determined based on the planned charging plan, so as to control the vehicle 1 to participate in the peak shaving auxiliary service and / or valley filling auxiliary service of the power grid during the charging process and obtain corresponding compensation benefits. The charging control parameters determined in the cloud server 2 can be sent to the vehicle 1 and / or the charging device 4, so that the on-board control unit 12 and / or the pile end control unit 42 can control the battery of the vehicle 1 to execute the planned charging plan based on the received charging control parameters.

[0051] For example, according to Figure 3The curve diagram of the battery state of charge changing with time during the vehicle charging process according to an exemplary embodiment of the present application is shown. At time t1, the user drives the vehicle 1 to the home garage or office building and connects the vehicle to the charging device 4, thereby starting the charging process. Since the vehicle 1 has just finished the journey, the battery state of charge SOC0 at time t1 is at a low level. Although it is currently in the peak power period, in order to ensure that the vehicle 1 has a certain amount of power stored to cope with emergency needs, the vehicle 1 is still charged until the preset first state of charge threshold SOC1 (for example, 30%) is reached at time t2, and the battery charging process can be controlled to be suspended. Waiting starts from time t2, for example, until time t3 (i.e., the peak power period ends and the valley power period begins), the battery charging process can be controlled to restart, thereby restarting the charging of the battery of vehicle 1 from time t3, for example, at time t4, the cloud server 2 receives the valley filling service request from the power grid server 31, thereby obtaining compensation for valley filling auxiliary services while using the valley power period electricity price during the time period from time t4 to t5, until the preset second state of charge threshold SOC2 (e.g., 60%) is reached at time t5. According to the received time-of-use electricity price information, the electricity price from time t5 is higher, and the battery of vehicle 1 can be controlled to transmit electricity to the power supply network 3 and obtain corresponding electricity sales income. At time t6, since the power generation power of the building system 5 is much smaller than the power consumption power, in order to avoid the building system 5 absorbing too much electricity from the power supply network 3 during the high electricity price period, the battery of vehicle 1 can be controlled to supply power to the building system 5.

[0052] Optionally, when planning the charging and discharging plan of the vehicle 1 in each charging time period based at least on the predicted estimated charging setting parameters, power supply related information, and power consumption information and power generation information of the building system 5, a predetermined battery health maintenance principle can be additionally introduced as an influencing factor for planning the charging and discharging plan to optimize the battery health state of the vehicle 1. Based on the predetermined battery health maintenance principle, the final state of charge of the battery when the vehicle ends charging can be set to not higher than a predetermined state of charge threshold (e.g., 80%) to prevent the battery of the vehicle 1 from being charged to an excessively high state of charge; the idle time between the moment when the battery reaches the final state of charge and the moment when the vehicle ends charging (i.e., the moment when the user drives the vehicle to depart) can be reduced as much as possible, thereby preventing the battery of the vehicle 1 from being in a high state of charge for a long time as much as possible; the battery charging power can also be reduced as much as possible while ensuring that the vehicle reaches the set final state of charge when charging ends, considering that the battery life can be effectively extended by slow charging.

[0053] For example, according to Figure 3The curve diagram shown shows that, since it is predicted according to the user's behavior habit data that the user will drive the vehicle 1 to start at time t8, in order to avoid the battery of the vehicle 1 being in a high state of charge for a long time as much as possible, and to ensure that the set final state of charge SOC4 (e.g. 80%) can be reached when the vehicle is finished charging, the battery discharge of the vehicle 1 is stopped after the battery power reaches SOC3 at time t7, and the battery of the vehicle 1 is recharged through the power supply network 3 from time t7 until the battery power reaches the final state of charge SOC4 predicted according to the user's behavior habit data at time t8. At time t8, the user drives the vehicle 1 to start, so the battery state of charge of the vehicle 1 begins to gradually decrease after time t8, thereby completing a battery charge and discharge cycle.

[0054] Considering that each user has different car usage frequency and charging habits, for example, users who use the car frequently need to charge once a day, while users who use the car less frequently may charge once every five days, and the frequency of users' car usage on weekdays and weekends is also different, a charging plan for a charging and discharging cycle can be formulated based on the user's behavioral habit data, and the number of days included in the charging cycle can be adjusted according to the user's behavioral habits. In addition, as the prediction accuracy of the prediction model gradually improves, the predicted estimated charging setting parameters will be closer and closer to the actual charging setting parameters of the corresponding time period, and charging plans for multiple charging and discharging cycles can be formulated, such as charging plans for the next few dozen days.

[0055] According to an embodiment of the present application, in an application scenario where a charging device with fixed usage rights installed in a building system is used to charge a vehicle, the charging and discharging plan of the vehicle in each charging time period can be automatically planned and corresponding charging and discharging control parameters can be set based on the user's behavioral habit data, power supply related information, and the power consumption / generation information of the building system. This ensures that the battery power reaches a final charge state that meets the user's vehicle usage habits when the vehicle finishes charging. This makes full use of the characteristic that the building system and the vehicle can supply electricity to each other, thereby reducing the overall electricity cost of the building system and the vehicle as much as possible. In addition, it can also optimize the health of the vehicle battery and extend the battery life as much as possible.

[0056] exist Figure 2 The schematic diagram of the charging scenario also shows a schematic block diagram of a cloud server 2 of a vehicle manufacturer, where the cloud server 2 is configured to execute the method for cloud-based control of vehicle charging and discharging according to the present application.

[0057] The above describes a method for cloud control of vehicle charging and discharging executed in the cloud server 2, in which the determined charging and discharging control parameters are sent to the vehicle 1 and / or the charging device 4. After the vehicle 1 and / or the charging device 4 receive the charging and discharging control parameters, the method for controlling vehicle charging and discharging is executed in the vehicle 1 and / or the charging device 4 to complete the battery charging process of the vehicle 1.

[0058] Figure 4 FIG. 2 shows a flowchart of a method for controlling vehicle charging and discharging according to an exemplary embodiment of the present application. Figure 4 As shown, the method may include step S1'. In step S1', in response to the charge and discharge control parameters received from the cloud server 2 according to the present application, the charge and discharge process of the vehicle 1 may be controlled at least based on the received charge and discharge control parameters. Here, the charge and discharge control parameters may include, for example, the battery charging power and / or battery discharging power in the battery charging process, the start and / or termination of the battery charging process, etc. In some charging design architectures, the on-board control unit 12 of the vehicle 1 may control the battery of the vehicle 1 to charge and discharge according to the planned charge and discharge plan based on the received charge and discharge control parameters; in other charging design architectures, the pile end control unit 42 of the charging device 4 may also control the battery of the vehicle 1 to charge and discharge according to the planned charge and discharge plan based on the received charge and discharge control parameters; in other charging design architectures, the on-board control unit 12 of the vehicle 1 and the pile end control unit 42 of the charging device 4 may also control the battery of the vehicle 1 to charge and discharge according to the planned charge and discharge plan in cooperation with each other based on the received charge and discharge control parameters.

[0059] In addition, it should be noted that the step numbers described herein do not necessarily represent a chronological order, but are merely a figure mark. The order can be changed according to specific circumstances as long as the technical purpose of the present application can be achieved.

[0060] exist Figure 2 The schematic diagram of the charging scenario also shows a schematic block diagram of a vehicle 1, and the vehicle 1 may include the following components:

[0061] - an on-board communication unit 11 configured to receive charging and discharging control parameters from a cloud server 2 according to the present application; and

[0062] An on-board control unit 12 configured to execute the method for controlling vehicle charging and discharging according to the present application.

[0063] exist Figure 2 The schematic diagram of the charging scenario also shows a schematic block diagram of a charging device 4, and the charging device 4 may include the following components:

[0064] - a terminal communication unit 41, which is configured to receive charging and discharging control parameters from the cloud server 2 according to the present application; and

[0065] A pile end control unit 42, which is configured to be used in the method for controlling vehicle charging and discharging according to the present application.

[0066] It should be understood that, in this document, the expressions "first", "second", "third", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance, nor should they be understood as implicitly indicating the number of the indicated technical features.

[0067] If an embodiment includes an “and / or” relationship between a first feature and a second feature, it should be interpreted as follows: according to one embodiment, the embodiment has both the first feature and the second feature, and according to another embodiment, the embodiment has either only the first feature or only the second feature.

[0068] Although specific embodiments have been described above, these embodiments are not intended to limit the scope of the present disclosure, even when only a single embodiment is described with respect to specific features. The feature examples provided in the present disclosure are intended to be illustrative, not restrictive, unless otherwise stated. In specific implementations, multiple features may be combined with each other, where technically feasible, according to actual needs. Various substitutions, changes, and modifications may also be conceived without departing from the spirit and scope of the present application.

Claims

1. A method for cloud control of vehicle charging and discharging, the method comprising: Predicting estimated charging setting parameters of the vehicle (1) in each charging time period based on the user's behavior habit data; Planning the charging and discharging plan of the vehicle (1) in each charging time period based at least on the predicted estimated charging setting parameters, the power supply related information and the power consumption / generation information of the building system (5) to optimize the overall power consumption cost of the building system (5) and the vehicle (1), wherein the building system (5) and the vehicle (1) can supply power to each other; as well as Based on the planned charging and discharging plan, the charging and discharging control parameters of the vehicle (1) in each charging time period are determined, and the determined charging and discharging control parameters are sent to the vehicle (1) and / or a charging device (4) for charging the vehicle (1).

2. The method according to claim 1, wherein: When planning the charging and discharging plan of the vehicle (1) in each charging time period based at least on the predicted estimated charging setting parameters, power supply related information, and power consumption information and power generation information of the building system (5), a predetermined battery health maintenance principle is additionally introduced as an influencing factor for planning the charging and discharging plan to optimize the battery health status of the vehicle (1).

3. The method according to claim 1, wherein: The user's behavior habit data includes the user's driving behavior data and / or the user's charging behavior data, wherein the user's driving behavior data includes historical data on the vehicle's departure time, and / or historical data on the vehicle's driving distance, and / or the user's itinerary planning information for a future time period, and the user's charging behavior data includes historical data on the charging start time, and / or historical data on the final state of charge of the battery when the vehicle finishes charging, and / or historical data on the charging power set by the user.

4. The method according to any one of claims 1 to 3, wherein: The estimated charging setting parameters include the charging end time of one or more future charging and discharging cycles and the final state of charge of the battery when the vehicle finishes charging.

5. The method according to claim 2, wherein: Based on a predetermined battery health maintenance principle, the final state of charge of the battery when the vehicle finishes charging is set to be no higher than a predetermined state of charge threshold, and / or the idle time period from the time when the battery reaches the final state of charge to the time when charging ends is reduced, and / or the battery charging power is reduced under the premise that the set final state of charge can be reached when the vehicle finishes charging.

6. The method according to any one of claims 1 to 5, wherein: The power supply related information includes time-of-use electricity price information, wherein the charging and discharging plan of the vehicle (1) in each charging time period is planned at least based on the predicted estimated charging setting parameters, the time-of-use electricity price information and the power consumption / generation information of the building system (5), and the charging and discharging control parameters of the vehicle (1) are determined based on the planned charging and discharging plan, wherein the charging and discharging control parameters include the battery charging power and / or battery discharging power in the battery charging process, and / or the start and / or termination of the battery charging process, wherein the time-of-use electricity price information is changed according to the time period and / or is predicted based on weather change information and / or power demand change information.

7. The method according to claim 6, wherein: When the power generated by the building system (5) is greater than the power consumed, the electric energy generated by the building system (5) is used to charge the battery of the vehicle (1); and / or When the time-of-use electricity price exceeds a preset electricity price threshold, controlling the battery of the vehicle (1) to discharge, so as to supply power to the building system (5) and / or output electric energy to the power supply network (3); and / or Based on the time-of-use electricity price information, the power consumption / generation information of the building system (5), and the change process of the battery charging power and battery discharging power of the vehicle (1) over time, the overall power consumption cost of the building system (5) and the vehicle (1) is calculated, as well as the power sales revenue obtained by the vehicle (1) and / or the building system (5) outputting electric energy to the power supply network (3).

8. The method according to claim 7, wherein: The power supply related information includes peak shaving request information and / or valley filling request information, wherein the charging and discharging plan of the vehicle (1) in each charging time period is planned at least based on the predicted estimated charging setting parameters, the power consumption / generation information of the building system (5) and the peak shaving request information and / or valley filling request information, and the charging and discharging control parameters of the vehicle (1) are determined based on the planned charging and discharging plan, wherein the charging and discharging control parameters include the battery charging power in the battery charging process, and / or the start and / or termination of the battery charging process, wherein the compensation income obtained by the vehicle (1) through the peak shaving auxiliary service and / or valley filling auxiliary service is calculated based on the change process of the battery charging power of the vehicle (1) over time and the peak shaving request information and / or valley filling request information.

9. The method according to claim 8, wherein: The overall electricity cost of the building system (5) and the vehicle (1) is calculated based on the calculated overall electricity consumption cost, electricity sales income and / or compensation income of the building system (5) and the vehicle (1), and the overall electricity cost of the building system (5) and the vehicle (1) is optimized on the premise that the vehicle can reach the set final charge state when charging is completed.

10. The method according to any one of claims 1 to 9, wherein: The power consumption / power generation information of the building system (5) includes power consumption change information of the building system (5), and / or power consumption historical data of the building system (5), and / or power generation change information of the building system (5), and / or power generation prediction information of the building system (5), wherein the power generation prediction information of the building system (5) is particularly based on weather change information and / or power generation equipment parameter prediction of the building system (5).

11. The method according to any one of claims 1 to 10, wherein: Predicting estimated charging setting parameters of the vehicle (1) in each charging time period based on the user's behavior habit data through a prediction model, wherein the prediction model includes, for example, a machine learning model, a linear and logistic regression model, and / or a neural network model; and / or The actual charging setting parameters of the vehicle (1) are obtained during the corresponding charging time period, and the prediction model is optimized based on the deviation between the estimated charging setting parameters and the actual charging setting parameters, for example, by a self-learning algorithm.

12. A cloud server (2) configured to execute the method according to any one of claims 1 to 11.

13. A method for controlling vehicle charging and discharging, the method comprising: In response to the charge and discharge control parameters received from the cloud server (2) according to claim 12, the charge and discharge process of the vehicle (1) is controlled based at least on the received charge and discharge control parameters.

14. A vehicle (1), comprising the following components: an on-vehicle communication unit (11) configured to receive a charge and discharge control parameter from the cloud server (2) according to claim 12; and An on-board control unit (12) is configured to execute the method according to claim 13.

15. A charging device (4), comprising the following components: A terminal communication unit (41) configured to receive a charge and discharge control parameter from the cloud server (2) according to claim 12; and A pile end control unit (42) configured for use in the method according to claim 13. 16 . A computer program product, such as a computer-readable program carrier, comprising or storing computer program instructions, which, when executed by a processor, at least assist in implementing the steps of the method according to claim 1 .

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