Cloud-based method for controlling charging / discharging of vehicle and method for controlling charging / discharging of vehicle

Abstract

This application relates to a cloud-based method for controlling charging / discharging of a vehicle, the method comprising: predicting an estimated charging setting parameters of vehicle (1) during each charging period based on a user behaviour data; planning a charge / discharge schedule of the vehicle (1) during each charging period based on at least the predicted estimated charging setting parameters, a power supply-related information and a power consumption / generation information of a building system (5) in order to optimise an overall electricity consumption cost of the building system (5) and the vehicle (1), wherein the building system (5) and the vehicle (1) are able to supply electrical power to each other; and determining a charge / discharge control parameters of the vehicle (1) during each charging period based on the planned charge / discharge schedule, and sending the determined charge / discharge control parameters to the vehicle (1) and / or a charging apparatus (4) used to charge the vehicle (1). According to this application, making full use of the building system and the vehicle to mutually supply electrical power can reduce the overall electricity consumption cost of the building system and the vehicle as much as possible.

Description

[0001] Mercedes-Benz Group AG

[0002] Cloud-based method for controlling charging I discharging of vehicle and method for controlling charging / discharging of vehicle

[0003] This application relates to the field of electric vehicle charging technology, and specifically to a cloud-based method for controlling charging I discharging of a vehicle, a Cloud server, a method for controlling the vehicle charge I discharge, a vehicle, a charging apparatus, and a computer program product, which is used at least to assist in implement the steps of the method in accordance with this application.

[0004] With the development and popularisation of electric vehicle charging technologies, users can charge their electric vehicle using a charging point installed in the garage at home or in their office building; the user’s home or office building can also be provided with a power supply with solar panels or other power generation apparatus used to power the building system. After connecting to the charging point, the electric vehicle begins the charging process, and this stops automatically once the battery is fully charged. However, on the one hand, the electric vehicle is unable to fully utilise the electrical power produced by the building system to charge the vehicle battery, and on the other, when time-of-use pricing is used on the power supply network, the vehicle is also unable to fully utilise off-peak electricity price periods to charge the vehicle battery, and it is equally unable to utilise the vehicle battery to supply power to the building system during peak electricity price periods, which results in high electricity costs for both the vehicle charging and building systems.

[0005] Therefore, finding ways to optimise the electricity costs of vehicle charging and building systems has become a technological issue to be resolved.

[0006] The purpose of this application is to provide a cloud-based method for controlling charging I discharging of a vehicle, a Cloud server, a method for controlling the vehicle charge I discharge, a vehicle, a charging apparatus, and a computer program product, in order to at least partly resolve the issues in the prior art.

[0007] In accordance with a first aspect of this application, a cloud-based control method for use in charging / discharging a vehicle, the method comprising:predicting an estimated charging setting parameters of vehicle during each charging period based on a user behaviour data;

[0008] planning a charge I discharge schedule of the vehicle during each charging period based on at least the predicted estimated charging setting parameters, a power supply-related information and a power consumption I generation information of a building system in order to optimise an overall electricity consumption cost of the building system and the vehicle, wherein the building system and the vehicle are able to supply electrical power to each other; and

[0009] determining a charge I discharge control parameters of the vehicle during each charging period based on the planned charge I discharge schedule, and sending the determined charge I discharge control parameters to the vehicle and / or a charging apparatus used to charge the vehicle

[0010] The core concept of this application is that: in application scenarios using charging apparatus with fixed access rights installed in the building system to charge the vehicle, it is possible to automatically plan the vehicle’s charge I discharge schedule during each charging period based on user behaviour data, power supply-related information and the building system’s power consumption I generation information and set corresponding charge I discharge control parameters, such that when charging of the vehicle is completed, the battery is able to reach a final state of charge in line with the user’s driving habits, and fully utilise the capability of the building system and the vehicle to supply electrical power to each other to minimise the overall electricity consumption cost of the building system and the vehicle.

[0011] In accordance with an optional embodiment of this application, when planning the charge I discharge schedule of the vehicle during each charging period based on at least the predicted estimated charging setting parameters, the power supply-related information and the power consumption information and the power generation information of the building system, predefined battery health maintenance rules are additionally introduced as influencing factors for planning the charge I discharge schedule, in order to optimise the battery health of the vehicle.

[0012] In accordance with another optional embodiment of this application, the user behaviour data may comprise a user driving behaviour data and / or a user charging behaviour data, the user driving behaviour data includes a historical vehicle departure time data and / or a historical vehicle driving distance data and / or a user future route planning information, and the user charging behaviour data includes a historical charging start time data and I or historical data on a final state of charge of the battery when the vehicle completes charging and / or a historical data on charging power set by the user.In accordance with another optional embodiment of this application, the estimated charging setting parameters may include a charging end time of one or more future charge I discharge cycles and a final state of charge of the battery when the vehicle completes charging.

[0013] In accordance with another optional embodiment of this application, based on the pre-defined battery health maintenance rules, the final state of charge of the battery when the vehicle completes charging is set to be no higher than a pre-defined charge state threshold, and I or an idle time between a time at which the battery reaches the final state of charge and a charging end time is shortened, and / or a battery charging power is reduced on a premise that a set final state of charge can be reached when charging ends.

[0014] In accordance with another optional embodiment of this application, the power supply-related information includes a time-of-use pricing information, the charge I discharge schedule of the vehicle during each charging period is planned based on at least the predicted estimated charging setting parameters, the time-of-use pricing information and the power consumption I generation information of the building system, and the charge I discharge control parameters of the vehicle are determined based on the planned charge I discharge schedule, wherein the charge I discharge control parameters include the battery charging power and I or the battery discharging power in the battery charging process, and I or the start and I or stop of the battery charging process, wherein the time-of-use pricing information changes based on the time and I or is predicted based on information on changes in weather and I or in demand for electrical power.

[0015] In accordance with another optional embodiment of this application, when a power generation capacity of the building system exceeds a power consumption capacity, an electrical power produced by the building system can be used to charge the battery of the vehicle.

[0016] In accordance with another optional embodiment of this application, when the time-of-use pricing exceeds a pre-set electricity price threshold, the battery of the vehicle can be controlled to discharge in order to supply power to the building system and I or output electrical power to a power supply network.

[0017] In accordance with another optional embodiment of this application, the overall power consumption cost of the building system and the vehicle and a revenue from electricity sales obtained from outputting electrical power from the vehicle and I or the building system to the power supply network can be calculated based on the changes over time in the time-of-use pricing information, the power consumption I generation information of the building system and the battery charging power and the battery discharging power of the vehicle.

[0018] In accordance with another optional embodiment of this application, the power supply-relatedinformation may include a peak shaving request information and / or a valley filling request information, wherein the charge I discharge schedule of the vehicle during each charging period is planned based on at least the predicted estimated charging setting parameters, the power consumption I generation information of the building system and the peak shaving request information and I or the valley filling request information, and the charge I discharge control parameters of the vehicle are determined based on the planned charge I discharge schedule, wherein the charge I discharge control parameters include the battery discharging power in the battery charging process, and I or the start and I or stop of the battery charging process, wherein the income from compensation obtained by the vehicle from peak shaving support services and I or valley filling support services is calculated based on the changes in the battery charging power of the vehicle over time and the peak shaving request information and I or valley filling request information.

[0019] In accordance with another optional embodiment of this application, the overall electricity consumption cost of the building system and the vehicle can be calculated based on the calculated overall power consumption cost of the building system and the vehicle, the revenue from electricity sales and I or the income from compensation, and the overall electricity consumption cost of the building system and the vehicle is optimised on the premise that the set final state of charge can be reached when charging ends.

[0020] In accordance with another optional embodiment of this application, the power consumption I generation information of the building system may include information on changes in power consumption capacity of the building system, and I or historical power consumption capacity data for the building system, and I or information on changes in power generation capacity for the building system, and I or power generation capacity forecast information for the building system, wherein the power generation capacity forecast information of the building system is predicted in particular based on information on changes in weather and I or the power generation apparatus parameters of the building system.

[0021] In accordance with another optional embodiment of this application, a prediction model can be used to predict the estimated charging setting parameters of the vehicle during each charging period based on user behaviour data, wherein the prediction model for example includes machine learning models, linear and logistic regression models and I or neural network model.

[0022] In accordance with another optional embodiment of this application, an actual charging setting parameter of the vehicle is obtained for a corresponding charging period, and the prediction model is optimised, for example using a self-learning algorithm, based on a deviation between the estimated charging setting parameters and the actual charging setting parameters.In accordance with a second aspect of this application, a cloud server is provided, and this is configured to execute the cloud-based control method for use in charging I discharging a vehicle in accordance with this application.

[0023] In accordance with a third aspect of this application, a method for controlling a vehicle charging I discharging of a vehicle is provided; the method may include:

[0024] in response to charge I discharge control parameters received from the cloud server in accordance with present application, a charge I discharge process of the vehicle can be controlled at least based on the received charge I discharge control parameters.

[0025] In accordance with a fourth aspect of this application, a vehicle is provided, comprising:

[0026] a vehicle-mounted communication unit configured to receive charge I discharge control parameters from the cloud server in accordance with the present application; and

[0027] a vehicle-mounted control unit configured to execute the method in accordance with the present application.

[0028] In accordance with a fifth aspect of this application, a charging apparatus is provided, comprising:

[0029] a charging point-side communication unit configured to receive charge I discharge control parameters from the cloud server in accordance with the present application; and

[0030] a charging point-side control unit configured for use in the method in accordance with the present application.

[0031] In accordance with a sixth aspect of this application, a computer program product, such as computer-readable program medium, is provided, comprising or storing computer program instructions which, when executed by a processor, at least assist in executing the steps of the method in accordance with the present application.

[0032] The principles, features and advantages of this application can be more clearly understood by referring to the drawings below. The drawings show:

[0033] Figure 1 shows a working flowchart of an exemplary embodiment of the Cloud-based control method for use in charging / discharging a vehicle in accordance with this application;

[0034] Figure 2 is a schematic of a charging scenario in an exemplary embodiment in accordance with this application;Figure 3 shows a curve of the change in the battery charge state over time during the vehicle charging process in an exemplary embodiment in accordance with this application; and

[0035] Figure 4 shows an exemplary embodiment in accordance with this application of the method for controlling the vehicle charge I discharge.

[0036] In order to clarify the technology problems to be resolved, the technology solutions and the beneficial technology effects in this application, a more detailed explanation of this application is provided below, in conjunction with the accompanying drawings and several exemplary embodiments. It should of course be understood that the specific embodiments described here are merely used to explain this application, and are not intended to limit the scope of protection of this application.

[0037] Figure 1 shows a working flowchart of an exemplary embodiment of the Cloud-based control method for use in charging I discharging a vehicle in accordance with this application. The following exemplary embodiments provide a more detailed explanation of the method in accordance with this application.

[0038] As shown in Figure 1, the Cloud-based control method for use in charging I discharging a vehicle may include steps S1 to S3. In step S1, the vehicle’s estimated charging setting parameters during each charging period can be predicted based on user behaviour data; The Cloud-based control method used for vehicle charging in accordance with this application is executed on the vehicle manufacturer’s Cloud server 2, and is particularly suitable for use in application scenarios where the electric vehicle is charged using charging apparatus 4 with fixed access rights installed in a garage at home or the parking area of an office building, i.e., said charging apparatus 4 is reserved for the exclusive use of one user or one user group (such as family members, company employees, etc.). As shown in Figure 2, a schematic of a charging scenario in an exemplary embodiment in accordance with this application, when vehicle 1 is electrically connected to, for example, charging apparatus 4 with fixed access rights installed in a garage at home or the parking area of an office building, the battery of vehicle 1 can be charged using charging apparatus 4, and said charging apparatus 4 can draw electrical power from power supply network 3, and it can also draw electrical power from building system 5.

[0039] In accordance with the regulatory requirements for electric vehicles, battery information, vehicle status information, vehicle position information, energy consumption data and I or charging data and other real-time monitoring data - i.e., RTM data - must be collected using a vehicle-mounted TBOX apparatus when vehicle 1 is in operation, and is then encrypted and transmitted via a wireless communications network to the vehicle manufacturer’s Cloud server2. Here, the behaviour data may include data on the user’s driving behaviour data - such as historical data on the vehicle’s departure time and I or historical vehicle driving distance data, inter alia, and this data can reflect the user’s driving habits in vehicle 1. Herein, the charging end time of vehicle 1 in one or more future charge I discharge cycles can be predicted based on the historical data on the vehicle’s departure time - i.e. , the battery must be charged to the set final state of charge before vehicle 1 departs. The amount of power needed by vehicle 1 for daily driving can be predicted based on historical vehicle driving distance data, and the final state of charge of the battery when the vehicle completes charging can therefore be set in accordance with the amount of power needed. In addition, the user’s driving behaviour data may also include the user’s future route planning information, which may for example be obtained from the user’s mobile terminal or social network accounts, inter alia, and the prediction accuracy of the vehicle’s future driving distance can be further enhanced based on said route planning information, thereby enhancing the prediction accuracy of the set final state of charge.

[0040] The user behaviour data may also include the user’s charging behaviour data, such as historical charging start time data, and I or historical data on the final state of charge of the battery when the vehicle completes charging, and I or historical data on charging power set by the user, inter alia. This data can reflect the user’s habits regarding the charging of vehicle 1 , wherein, the charging start time of vehicle 1 in one or more future charge I discharge cycles can be predicted based on historical charging start time data, the final state of charge of the battery when the vehicle completes charging (i.e., the vehicle battery charge) can be predicted based on historical data on the final state of charge of the battery when the vehicle completes charging, and charging power which matches the user’s habits can be predicted based on historical data on charging power set by the user.

[0041] The user behaviour data can be input into a prediction model, and the estimated charging setting parameters for vehicle 1 during each charging period can be predicted using the prediction model based on user behaviour data, including in particular the charging end time and final state of charge of the battery when the vehicle completes charging for one or more future charge I discharge cycles. For example purposes, the prediction model may include machine learning models, linear and logistic regression models and I or neural network models, inter alia. In order to enhance the precision of the prediction model, the actual charging setting parameters for vehicle 1 can be obtained for a corresponding charging period, and the prediction model can then be optimised, for example using a self-learning algorithm, based on the deviation between the estimated charging setting parameters and the actual charging setting parameters. It is understood that as the precision of the prediction model gradually improves, the predicted estimated charging setting parameters will become increasingly similarto the actual charging setting parameters for the corresponding period.

[0042] In step 2, vehicle 1’s charge I discharge schedule during each charging period can be planned based on at least the predicted estimated charging setting parameters, power supply-related information and building system 5’s power consumption I generation information in order to optimise the overall electricity consumption cost of building system 5 and vehicle 1, wherein the building system 5 and the vehicle 1 are able to supply electrical power to each other. In this application, building system 5 can be a detached house, office building or other operating entity that can be billed for electricity independently, and charging apparatus 4 is installed in building system 5. As shown by the thick lines with arrows in Figure 2 indicating the direction of flow of electrical power, building system 5 can draw electrical power from power supply network 3 in order to supply power to the electrical apparatus (including charging apparatus 4) in building system 5. Power generation apparatus 51 such as photovoltaic panels can also be installed in building system 5. The electrical power generated by power generation apparatus 51 can be used to supply power to the electrical apparatus in building system 5 (including charging apparatus 4), and, when the power generation capacity of power generation apparatus 51 exceeds the total power consumption of building system 5, this can also be fed to power supply network 3 to generate corresponding revenue from the sale of electricity. When the power generation capacity of power generation apparatus 51 is lower than the total power consumption of building system 5, particularly during peak periods when electricity prices are relatively higher, the electrical power stored in vehicle 1’s battery can also be used to supply power to the electrical apparatus in building system 5, to reduce the electrical power drawn by building system 5 from power supply network 3 during peak periods. Therefore, when vehicle 1 is charged using charging apparatus 4 installed in building system 5, the electricity consumption costs of building system 5 and vehicle 1 can be optimised as a whole.

[0043] Cloud server 2 can obtain power consumption I generation information for building system 5 from the building system 5’s back-office server, which may for example include information on changes in power consumption capacity for the building system, and I or historical power consumption capacity data for the building system, and I or information on changes in power generation capacity for the building system, and I or power generation capacity forecast information for the building system, inter alia, wherein the power generation capacity forecast information for the building system 5 is predicted in particular based on information on changes in weather and I or the power generation apparatus parameters of the building system (such as the installed capacity of the power generation apparatus). When the power generation capacity of the building system 5 exceeds the power consumption capacity, the electrical power produced by the building system can be used to charge the vehicle 1’s battery.

[0044] As shown in Figure 2, Cloud server 2 can obtain the power supply-related data from grid server31, particularly including time-of-use pricing information. The time-of-use pricing information varies according to time periods, such that for example, different time periods (e.g., peak and off-peak periods, etc.) have different electricity prices. Because electricity prices at peak times are higher than at off-peak times, provided that the vehicle is able to reach the set final state of charge when charging ends, vehicle 1’s battery should as far as possible be charged during off-peak times. When power supply network 3 uses dynamic electricity prices coupled with the electricity market, the time-of-use pricing information can also be predicted based on information on changes in weather and I or on changes in electricity demand, and, provided that the vehicle is able to reach the set final state of charge when charging ends, vehicle 1’s battery should as far as possible be charged during off-peak times. When time-of-use pricing exceeds a pre-set electricity price threshold, particularly at peak times, the vehicle 1’s battery can be controlled to discharge in order to supply power to the building system 5, and I or output electrical power to power supply network 5 to generate corresponding revenue from electricity sales. The overall power consumption cost of building system 5 and vehicle 1 , and the revenue from electricity sales obtained from outputting electrical power from the vehicle 1 and I or the building system 5 to the power supply network can be calculated based on the changes over time in the time-of-use pricing information, the building system’s 5 power consumption I generation information and the vehicle 1’s battery charging power and battery discharging power.

[0045] When vehicle 1 and power supply network 3 sign a peak shaving I valley filling support service agreement, the power supply-related information may also include peak shaving request information and I or valley filling request information obtained from grid server 31, such that when charging, vehicle 1 is controlled to participate in grid peak shaving support services and I or valley filling support services based on instructions from grid server 31. Specifically, during peak load periods, it is possible to control a stop to the battery charging process and I or reduce the battery charging power based on the peak shaving request information received from grid server 31 ; when loads are lower, it is possible to control a start to the battery charging process and I or increase the battery charging power based on the valley filling request information received from grid server 31. Then, it is possible to calculate the income from compensation obtained from peak shaving support services and I or valley filling support services based on the peak shaving request information and I or valley filling request information. For example, in accordance with the Implementation Rules for the Management of Electrical Power Support Services in Eastern China, the compensation standard for adjustable loads participating in peak shaving support services is CNY 0.8 I kWh, and the compensation standard for participating in valley filling support services is CNY 0.241 kWh. If vehicle 1 participates in peak shaving support services during peak load periods, the income from compensation obtained per kWh is higher compared to the peak / off-peak difference in time-of-use pricing; if vehicle1 participates in valley filling support services during off-peak load periods, vehicle 1 can obtain income from compensation for valley filling support services while also using off-peak electricity prices.

[0046] Next, the overall electricity consumption cost of the building system and the vehicle can be calculated based on the calculated overall power consumption cost of building system 5 and vehicle 1, the revenue from electricity sales and I or the income from compensation, and the overall electricity consumption cost of building system 5 and vehicle 1 is optimised provided that the vehicle is able to reach the set final state of charge when charging ends. Here, the charging cost is the calculated overall power consumption cost minus the calculated revenue from electricity sales and I or income from compensation. The charge I discharge schedule for vehicle 1 during each charging period can be defined with the goal of minimising the overall electricity consumption cost.

[0047] In step S3, vehicle 1’s charge I discharge control parameters during each charging period can be determined based on the planned charge I discharge schedule, and the determined charge I discharge control parameters are sent to vehicle 1 and I or charging apparatus 4 used to charge vehicle 1. Here, the charge I discharge control parameters may for example include the battery charging power and I or battery discharging power during the battery charging process, and the start and I or end of the battery charging process, inter alia. For example purposes, the charge I discharge schedule for vehicle 1 during each charging period can be planned based on at least the predicted estimated charging setting parameters, the time-of-use pricing information and the power consumption I generation information of the building system 5, and the battery charging power and I or battery discharging power of vehicle 1’s battery charging process, and I or the start and I or end of the battery charging process, inter alia, can be determined based on the planned charge I discharge schedule. Provided that the vehicle is able to reach the set final state of charge when charging ends, this on the one hand controls vehicle 1’s battery to charge as much power as possible using the surplus electrical power produced by building system 5 and I or electrical power during low electricity price periods, and on the other controls vehicle 1’s battery to supply as much power as possible to building system 5 and I or power supply network 3 during high electricity price periods, thus reducing the overall electricity costs of building system 5 and vehicle 1 while also enhancing vehicle 1’s revenue from electricity sales.

[0048] For example purposes, the charging schedule for vehicle 1 during each charging period can also be planned based on the peak shaving request information and I or valley filling request information, and the battery charging power during battery charging process and I or the start and I or end of the battery charging process, inter alia, can be determined based on the planned charging schedule. This thus controls vehicle 1 to participate in the grid’s peak shaving supportservices and I or valley filling support services during the charging process and obtain corresponding income from compensation. The charging control parameters determined on Cloud server 2 can be sent to vehicle 1 and I or charging apparatus 4, enabling vehiclemounted control unit 12 and I or charging point-side control unit 42 to control vehicle 1’s battery to execute the planned charging schedule based on the received charging control parameters.

[0049] For example, on the curve of the change in the battery charge state during the vehicle charging process in an exemplary embodiment in accordance with this application shown in Figure 3, at time t1 , the user drives vehicle 1 to the garage at home or the office building and connects the vehicle to charging apparatus 4, thereby starting the charging process. Because vehicle 1 has just completed its journey, battery charge state SOCO is relatively low at time t1. Even at peak hours, vehicle 1 is charged in order to ensure that vehicle 1 has a sufficient power charge for emergency needs, until a pre-set first charge state threshold SOC1 (e.g., 30%) is reached at time t2, and the battery charging process can then be paused. Awaiting period starts from time t2 onwards, for example until time t3 (i.e., the end of the peak period and the start of the off-peak period) when the battery charging process can be controlled to start again, such that vehicle 1’s battery resumes charging from time t3. For example, at time t4, Cloud server 2 receives a valley filling service request from grid server 31, such that during the time period from t4 to t5, while using off-peak electricity prices, it is also possible to obtain compensation for valley filling support services, until a pre-set second charge state threshold SOC2 (e.g., 60%) is reached at time t5. Based on the received time-of-use pricing information, electricity prices are higher from time t5 onwards, and vehicle 1’s battery can be controlled to supply power to power supply network 3 and obtain corresponding revenue from electricity sales. At time t6, because the power generation capacity of building system 5 is much lower than its power consumption capacity, in order to avoid building system 5 drawing too much electrical power from power supply network 3 during high electricity price periods, it is possible to control vehicle 1’s battery to supply power to building system 5.

[0050] Optionally, when planning vehicle 1’s charge / discharge schedule during each charging period based on at least the predicted estimated charging setting parameters, power supply-related information and building system 5’s power consumption information and power generation information, pre-defined battery health maintenance rules can additionally be introduced as influencing factors for planning the charge I discharge schedule, in order to optimise the health of vehicle 1’s battery. The final state of charge of the battery when the vehicle completes charging can be set to be no higher than a pre-defined charge state threshold (e.g., 80%) based on pre-defined battery health maintenance rules in order to avoid vehicle 1’s battery being charged to an excessively high charge state; it is also possible to minimise the idle time between the time at which the battery reaches the final state of charge and the time at whichthe vehicle finishes charging (i.e., the time at which the user drives the vehicle out), thereby avoiding as much as possible prolonged periods during which vehicle 1’s battery is in a high-charge state; it is also possible to minimise battery charging power while ensuring that the set final state of charge is reached when the vehicle finishes charging, which takes into account that slow charging can effectively extend the battery’s life span.

[0051] For example, on the curve shown in Figure 3, because it is predicted that the user will drive vehicle 1 out at time t8, in order to avoid as much as possible prolonged periods during which vehicle 1’s battery is in a high-charge state, as well as ensure that the vehicle can reach the set final state of charge SOC4 (e.g., 80%) when the vehicle finishes charging, vehicle 1’s battery stops discharging when the battery charge reaches SOC3 at time t7, and from time t7 onward, charging of vehicle 1’s battery resumes using power supply network 3 until time t8, when the battery charge reaches the final state of charge SOC4 predicted based on user behaviour data. The user drives vehicle 1 out at time t8, therefore vehicle 1’s battery charge state starts to gradually drop after time t8, thus completing a battery charge I discharge cycle.

[0052] Taking into consideration the differences in every user’s car usage and charging habits, where frequent car users may for example need to charge once a day, while less frequent users may only charge once every five days, as well as that usage differs on working days and rest days, it is possible to define a charging schedule for charge I discharge cycles based on user behaviour data, where the number of days comprising said charging cycle can be adjusted based on user behaviour. In addition, as the precision of the prediction model gradually improves, the predicted estimated charging setting parameters will become increasingly similar to the actual charging setting parameters for the corresponding period, it is possible to define multiple charging schedules for charge I discharge cycles, such as charging schedules for more than ten days in the future.

[0053] Based on the embodiments in this application, in application scenarios using charging apparatus with fixed access rights installed in the building system to charge the vehicle, it is possible to automatically plan the vehicle’s charge I discharge schedule during each charging period based on user behaviour data, power supply-related information and the building system’s power consumption I generation information and set corresponding charge I discharge control parameters, such that when charging of the vehicle is completed, the battery is able to reach a final state of charge in line with the user’s driving habits, and fully utilise the capability of the building system and the vehicle to supply electrical power to each other to minimise the overall electricity consumption cost of the building system and the vehicle; in addition, it is also possible to optimise the health of the vehicle battery, and extend the battery life span as long as possible.The schematic block diagram of a charging scenario in Figure 2 shows a block diagram of the vehicle manufacturer’s Cloud server 2. Said Cloud server 2 is configured to execute the Cloudbased control method for use in charging I discharging a vehicle in accordance with this application.

[0054] The above describes a Cloud-based control method for use in charging I discharging a vehicle executed on Cloud server 2, where the charge I discharge control parameters determined in said method are sent to vehicle 1 and I or charging apparatus 4. Once vehicle 1 and I or charging apparatus 4 receives the charge I discharge control parameters, the method for controlling the vehicle charge I discharge is executed on vehicle 1 and I or charging apparatus 4, to complete vehicle 1’s battery charging process.

[0055] Figure 4 shows a working flowchart of an exemplary embodiment of the method for controlling the vehicle charge I discharge in accordance with this application. As shown in Figure 4, the method may include step ST. In step ST, in response to charge / discharge control parameters received from Cloud server 2 in accordance with this application, vehicle 1 ’s charge I discharge process can be controlled at least based on the received charge I discharge control parameters. Here, the charge I discharge control parameters may for example include the battery charging power and I or battery discharging power during the battery charging process, and the start and I or end of the battery charging process, inter alia. In certain charging architecture designs, the vehicle-mounted control unit 12 of vehicle 1 can control vehicle 1’s battery to charge I discharge in accordance with the planned charge I discharge schedule based on the received charge I discharge control parameters; in certain other charging architecture designs, charging point-side control unit 42 of charging apparatus 4 can also control vehicle 1’s battery to charge I discharge in accordance with the planned charge I discharge schedule based on the received charge I discharge control parameters; in certain other charging architecture designs, vehicle-mounted control unit 12 of vehicle 1 and charging point-side control unit 42 of charging apparatus 4 can also cooperate with each other to control vehicle 1’s battery to charge I discharge in accordance with the planned charge I discharge schedule based on the received charge I discharge control parameters.

[0056] In addition, it should be noted that the numbering of the steps described herein does not necessarily represent any sequential order, but is merely numbering for reference. Depending on the specific circumstances, this sequence may change, provided that the technical objectives of this application can be implemented.

[0057] The schematic block diagram of a charging scenario in Figure 2 also shows a block diagram of vehicle 1; the vehicle 1 may include the following components:A vehicle-mounted communication unit 11, which is configured to receive charge I discharge control parameters from a Cloud server 2 in accordance with this application; and

[0058] A vehicle-mounted control unit 12, which is configured to execute the method for controlling the vehicle charge I discharge in accordance with this application.

[0059] The schematic block diagram of a charging scenario in Figure 2 also shows a block diagram of charging apparatus 4; the charging apparatus 4 may include the following components:

[0060] A charging point-side communication unit 41, which is configured to receive charge I discharge control parameters from Cloud server 2 in accordance with this application; and

[0061] A charging point-side control unit 42, which is configured for use with a method for controlling the vehicle charge I discharge in accordance with this application.

[0062] It should be understood that in this document, the terms “first”, “second” and “third”, etc., are used for descriptive purposes only, and this should not be construed to indicate or imply any relative importance, nor should they be construed to implicitly specify any number of the technical features indicated.

[0063] If an embodiment includes an “and I or” relationship between a first feature and a second feature, this should be interpreted as follows: in accordance with one embodiment, said embodiment has not only the first feature but also the second feature, while in accordance with another embodiment, said embodiment has only the first feature or only the second feature.

[0064] Although specific embodiments are described in the document above, these embodiments by no means limit the scope of this application, even if a particular feature is only described in a single embodiment. The featured examples provided in this application are intended for illustrative purposes, and not for limitation, except where otherwise stated. In specific implementations, multiple features may be combined as required and where technically feasible. Various substitutions, modifications and alterations may also be conceived without departing from the spirit and scope of this application.

Claims

Mercedes-Benz Group AGClaims1. A cloud-based method for controlling charging I discharging of a vehicle, the method comprising:predicting an estimated charging setting parameters of vehicle (1) during each charging period based on a user behaviour data;planning a charge I discharge schedule of the vehicle (1) during each charging period based on at least the predicted estimated charging setting parameters, a power supply- related information and a power consumption I generation information of a building system (5) in order to optimise an overall electricity consumption cost of the building system (5) and the vehicle (1), wherein the building system (5) and the vehicle (1) are able to supply electrical power to each other; anddetermining a charge I discharge control parameters of the vehicle (1) during each charging period based on the planned charge I discharge schedule, and sending the determined charge I discharge control parameters to the vehicle (1) and / or a charging apparatus (4) used to charge the vehicle (1).

2. The method according to Claim 1, wherein when planning the charge I discharge schedule of the vehicle (1) during each charging period based on at least the predicted estimated charging setting parameters, the power supply-related information and the power consumption information and the power generation information of the building system (5), pre-defined battery health maintenance rules are additionally introduced as influencing factors for planning the charge I discharge schedule, in order to optimise the battery health of the vehicle (1).

3. The method according to Claim 1, wherein the user behaviour data comprises a user driving behaviour data and / or a user charging behaviour data, the user driving behaviour data includes a historical vehicle departure time data and / or a historical vehicle driving distance data and / or a user future route planning information, and the user charging behaviour data includes a historical charging start time data and / orhistorical data on a final state of charge of the battery when the vehicle completes charging and / or a historical data on charging power set by the user.

4. The method according to any of Claims 1 - 3, wherein the estimated charging setting parameters include a charging end time of one or more future charge I discharge cycles and a final state of charge of the battery when the vehicle completes charging.

5. The method according to Claim 2, wherein based on the pre-defined battery health maintenance rules, the final state of charge of the battery when the vehicle completes charging is set to be no higher than a pre-defined charge state threshold, and I or an idle time between a time at which the battery reaches the final state of charge and a charging end time is shortened, and / or a battery charging power is reduced on a premise that a set final state of charge can be reached when charging ends.

6. The method according to any of Claims 1 - 5, wherein the power supply-related information includes a time-of-use pricing information, the charge I discharge schedule of the vehicle (1) during each charging period is planned based on at least the predicted estimated charging setting parameters, the time-of-use pricing information and the power consumption I generation information of the building system (5), and the charge I discharge control parameters of the vehicle (1) are determined based on the planned charge I discharge schedule, wherein the charge I discharge control parameters include the battery charging power and I or the battery discharging power in the battery charging process, and I or the start and I or stop of the battery charging process, wherein the time-of-use pricing information changes based on the time and I or is predicted based on information on changes in weather and I or in demand for electrical power.

7. The method according to Claim 6, wherein when a power generation capacity of the building system (5) exceeds a power consumption capacity, an electrical power produced by the building system (5) is used to charge the battery of the vehicle (1), and I orwhen the time-of-use pricing exceeds a pre-set electricity price threshold, the battery of the vehicle is controlled to discharge in order to supply power to the building system (5) and I or output electrical power to a power supply network (3), and I orthe overall power consumption cost of the building system (5) and the vehicle (1), and a revenue from electricity sales obtained from outputting electrical power from the vehicle (1) and I or the building system (5) to the power supply network is calculated based on the changes over time in the time-of-use pricing information, the powerconsumption I generation information of the building system (5) and the battery charging power and the battery discharging power of the vehicle (1).

8. The method according to Claim 7, wherein the power supply-related information includes a peak shaving request information and / or a valley filling request information, wherein the charge I discharge schedule of the vehicle (1) during each charging period is planned based on at least the predicted estimated charging setting parameters, the power consumption I generation information of the building system (5) and the peak shaving request information and I or the valley filling request information, and the charge I discharge control parameters of the vehicle (1) are determined based on the planned charge I discharge schedule, wherein the charge I discharge control parameters include the battery discharging power in the battery charging process, and I or the start and I or stop of the battery charging process, wherein the income from compensation obtained by the vehicle (1) from peak shaving support services and I or valley filling support services is calculated based on the changes in the battery charging power of the vehicle (1) over time and the peak shaving request information and I or valley filling request information.

9. The method according to Claim 8, wherein the overall electricity consumption cost of the building system (5) and the vehicle (1) can be calculated based on the calculated overall power consumption cost of the building system (5) and the vehicle (1), the revenue from electricity sales and I or the income from compensation, and the overall electricity consumption cost of the building system (5) and the vehicle (1) is optimised on the premise that the set final state of charge can be reached when charging ends.

10. The method according to any of Claims 1 - 9, wherein the power consumption I generation information of the building system (5) includes information on changes in power consumption capacity of the building system (5), and I or historical power consumption capacity data for the building system (5), and I or information on changes in power generation capacity for the building system (5), and I or power generation capacity forecast information for the building system (5), wherein the power generation capacity forecast information of the building system (5) is predicted in particular based on information on changes in weather and I or the power generation apparatus parameters of the building system (5).

11. The method according to any of Claims 1 - 10, wherein a prediction model is used to predict the estimated charging setting parameters of the vehicle (1) during each charging period based on user behaviour data, wherein the prediction model for example includes machine learning models, linear and logistic regression models andI or neural network models; and / oran actual charging setting parameter of the vehicle (1) is obtained for a corresponding charging period, and the prediction model is optimised, for example using a selflearning algorithm, based on a deviation between the estimated charging setting parameters and the actual charging setting parameters.

12. A cloud server (2) configured to execute the method in accordance with any of Claims 1 - 11.

13. A method for controlling charging I discharging of a vehicle, the method comprising:in response to charge I discharge control parameters received from the cloud server (2) in accordance with Claim 12, a charge I discharge process of the vehicle (1) is controlled at least based on the received charge I discharge control parameters.

14. A vehicle (1) comprising:a vehicle-mounted communication unit (11) configured to receive charge I discharge control parameters from the cloud server (2) in accordance with Claim 12; anda vehicle-mounted control unit (12) configured to execute the method in accordance with Claim 13.

15. A charging apparatus (4) comprising:a charging point-side communication unit (41) configured to receive charge / discharge control parameters from the cloud server (2) in accordance with Claim 12; anda charging point-side control unit (42) configured for use in the method in accordance with Claim 13.

16. A computer program product, such as computer-readable program medium, comprising or storing computer program instructions which, when executed by a processor, at least assist in executing the steps of the method in accordance with any of Claims 1 - 11 and

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