Vehicle, charging and discharging power scheduling method and computer readable storage medium

Abstract

The embodiment of the invention provides a vehicle, a charging and discharging power scheduling method and a computer readable storage medium, and the method applied to the vehicle comprises the steps: obtaining the power demand of the vehicle and the battery data of a battery in the vehicle in the current time period under the condition that the vehicle is connected to a power grid, and receiving the demand power of the current time period issued by the power grid; based on the required power and the battery data, initial response power for the required power is obtained; based on the battery data, predicting the temperature of the vehicle after executing the initial response power to obtain a predicted temperature; and adjusting the initial response power for at least one time based on the power demand, the battery data and the predicted temperature to obtain target response power. According to the invention, the technical problem that the flexibility of the charging and discharging power scheduling of the vehicle is poor in the related technology is solved.

Description

Technical Field

[0001] This application relates to the fields of vehicles and scheduling, and more specifically, to a method for scheduling vehicles and their charging and discharging power, and a computer-readable storage medium. Background Technology

[0002] With the increasing prevalence of vehicles equipped with power batteries, vehicles can participate in grid peak shaving and valley filling as a form of energy storage.

[0003] In related technologies, vehicles typically use an open-loop scheduling method to receive dispatch instructions from the power grid, which means they directly execute the charging and discharging power corresponding to the dispatch instructions. However, since batteries are greatly affected by the environment, using open-loop scheduling may result in poor flexibility in scheduling the charging and discharging power of vehicles.

[0004] There is currently no good solution to the above problems. Summary of the Invention

[0005] This application provides a method for scheduling vehicles and charging / discharging power, as well as a computer-readable storage medium, to at least solve the technical problem of poor flexibility in scheduling vehicle charging / discharging power in related technologies.

[0006] According to one aspect of the embodiments of this application, a method for scheduling the charging and discharging power of a vehicle is provided, applied to a vehicle, comprising: when the vehicle is connected to the power grid, acquiring the vehicle's power demand and battery data of the vehicle's battery in the current time period, and receiving the power demand for the current time period issued by the power grid; obtaining an initial response power for the power demand based on the power demand and the battery data; predicting the temperature of the vehicle after executing the initial response power based on the battery data, and obtaining a predicted temperature; and adjusting the initial response power at least once based on the power demand, battery data, and predicted temperature to obtain a target response power, wherein the adjustment is used to adjust the initial response power according to different battery parameters, and the target response power is used to control the charging and discharging of the vehicle.

[0007] Optionally, based on the demand power and battery data, an initial response power is obtained for the demand power, including: determining the vehicle's thermal power based on the battery data; and obtaining the initial response power based on the thermal power and the demand power.

[0008] Optionally, the battery data includes the battery temperature. Based on the battery data, the predicted temperature is obtained after the vehicle performs the initial response power. This includes: determining the battery temperature change value based on the battery data and the initial response power; and obtaining the predicted temperature based on the sum of the battery temperature and the temperature change value.

[0009] Optionally, the battery data also includes battery mass and specific heat capacity. Based on the battery data and initial response power, the temperature change value of the battery is determined, including: calculating the heat generation and heat dissipation of the battery based on the battery data and initial response power; obtaining a heat difference based on the difference between heat generation and heat dissipation; obtaining a first product based on the product of the heat difference and the time period corresponding to the current time period, and obtaining a second product based on the product of battery mass and specific heat capacity; and obtaining the temperature change value based on the first product and the second product.

[0010] Optionally, the initial response power is adjusted at least once based on power demand, battery data, and predicted temperature to obtain a target response power, including: adjusting the initial response power based on the physical constraints of the battery to obtain a first adjusted power; adjusting the first adjusted power based on the predicted temperature to obtain a second adjusted power; and adjusting the second adjusted power based on power demand and battery data to obtain the target response power.

[0011] Optionally, adjusting the first adjustment power based on the predicted temperature to obtain the second adjustment power includes: determining the first adjustment power as the second adjustment power when the predicted temperature is less than or equal to a preset safe temperature; and repeatedly executing the steps of determining a new first adjustment power based on the attenuation coefficient, predicting the temperature of the vehicle after implementing the new first adjustment power in the current time period based on battery data, obtaining a new predicted temperature, and reducing the attenuation coefficient until the new predicted temperature is less than or equal to the preset safe temperature, or the attenuation coefficient is less than the preset coefficient, and then determining the new first adjustment power as the second adjustment power.

[0012] Optionally, the second adjustment power is adjusted based on power demand and battery data to obtain the target response power, including: determining the required energy based on power demand and battery data, and predicting the vehicle's remaining charging energy in the future based on battery data; determining the second adjustment power as the target response power when the remaining charging energy is greater than or equal to the required energy; and determining the target response power based on the required energy, charging efficiency, and thermal power when the remaining charging energy is less than the required energy.

[0013] Optionally, based on battery data, predicting the vehicle's remaining charging energy in future time periods includes: determining the safe response power based on battery data; determining the remaining charging energy based on the product of battery charging efficiency, safe response power, and remaining time; preferably, determining the target response power based on demand energy, charging efficiency, and thermal power includes: determining a third product based on the product of charging efficiency and remaining time; determining the average power based on the demand energy and the third product; determining the actual power based on the sum of thermal power and average power; and determining the minimum value between the vehicle's maximum safe power and the actual power as the target response power.

[0014] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0015] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0016] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0018] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0019] In this embodiment, when a vehicle is connected to the power grid, the vehicle's power demand and battery data for the current time period are acquired. The power demand for the current time period is received from the power grid. Then, based on the power demand and battery data, an initial response power is obtained for the required power. Based on the battery data, the vehicle's temperature after executing the initial response power is predicted, resulting in a predicted temperature. Therefore, based on the power demand, battery data, and predicted temperature, the initial response power is adjusted at least once to obtain a target response power. This application fully considers the vehicle's actual power demand and battery temperature response when scheduling vehicle charging and discharging power. Specifically, after the vehicle is connected to the power grid, the initial response power is calculated promptly using the power demand of the power grid and the vehicle's battery data. The actual power demand of the vehicle and the predicted temperature after executing the initial response power are considered to adjust the initial response power, obtaining a target response power that satisfies both the vehicle's energy needs and ensures vehicle safety. This achieves the goal of flexibly scheduling the vehicle's charging and discharging power, thus realizing the technical effect of flexible vehicle charging and discharging power scheduling and solving the technical problem of poor flexibility in vehicle charging and discharging power scheduling in related technologies. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0021] Figure 1 This is a schematic diagram of a method for scheduling the charging and discharging power of a vehicle according to an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of an optional predicted target response power according to an embodiment of this application;

[0023] Figure 3 This is a schematic diagram of an optional power scheduling method according to an embodiment of this application;

[0024] Figure 4 This is a schematic diagram of a vehicle charging and discharging power scheduling device according to an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] According to an embodiment of this application, a method embodiment for scheduling vehicle charging and discharging power is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] This embodiment provides a method for scheduling the charging and discharging power of a vehicle, which is applied to vehicles. Figure 1 This is a flowchart of a vehicle charging and discharging power scheduling method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0029] Step S102: When the vehicle is connected to the power grid, obtain the vehicle's power demand and the battery data of the vehicle's battery in the current time period, and receive the power demand for the current time period sent by the power grid.

[0030] The vehicles mentioned above can refer to electric vehicles (EVs). In vehicle-to-grid (V2G) scenarios, vehicles can serve as mobile energy storage devices. EV batteries can store electrical energy during off-peak hours and release it back to the grid when needed, thus achieving bidirectional energy flow. EVs can not only draw power from the grid for their own propulsion but also act as an auxiliary resource for the grid, discharging into the grid during peak hours or charging from the grid during off-peak hours to balance power load and improve the overall efficiency and stability of the grid.

[0031] The aforementioned electricity demand refers to the power requirements of a vehicle at a specific moment or within a specific time period. The primary function of an EV is driving, which consumes the electrical energy stored in its battery. Therefore, the vehicle's electricity demand can include, but is not limited to, the energy consumption estimate for the vehicle's expected journey. This means predicting the amount of electricity required to complete a specific journey based on factors such as the vehicle's driving mode, road conditions, speed, and load, as well as the electricity required for entertainment systems, such as audio systems.

[0032] The battery data mentioned above refers to data related to the vehicle's battery. Battery data can be performance data or state-of-charge (SOC) data. SOC data may include, but is not limited to, battery SOC (State of Charge), battery temperature, rated capacity, internal resistance, and the ambient temperature of the battery. Furthermore, performance data may include, but is not limited to, the battery's physical properties, such as specific heat capacity and mass, as well as safe operating thresholds, such as upper temperature limits. By monitoring and analyzing battery data, it is possible to ensure that battery health is not compromised while responding to grid commands, avoiding safety issues caused by overheating or overcooling, and extending battery life.

[0033] The aforementioned power demand is part of the grid dispatch instruction, indicating the amount of electricity vehicles should supply to or absorb from the grid during a specific time period. Power demand reflects the grid's real-time demand for power supply and demand balance. It guides the immediate direction and intensity of electric vehicle charging and discharging, and is a key instruction for achieving peak shaving and valley filling in V2G aggregation dispatch.

[0034] In one optional embodiment, once the vehicle is connected to the power grid, it can participate in peak shaving and valley filling as a distributed energy storage unit. To enable grid dispatch, the vehicle can acquire actual electricity demand and real-time battery data, and receive power demand directly from the grid or relayed through charging stations. Electricity demand can be user-indicated or determined based on historical vehicle usage data. Battery data can be obtained from the battery management system.

[0035] In another optional embodiment, an event listening mechanism is designed. After the vehicle establishes a connection with the power grid, a request is triggered to obtain power demand and battery data, and the required power is parsed from the data sent by the power grid. For example, after confirming the connection with the power grid through the vehicle's onboard communication unit, a request is promptly generated and sent to the vehicle to instruct the acquisition of relevant data for power scheduling.

[0036] Step S104: Based on the power demand and battery data, obtain the initial response power for the power demand.

[0037] The initial response power mentioned above is a dispatch power calculated based on the grid demand power and the vehicle's current battery state. The initial response power takes into account the full constraints of thermal management and user demand. It provides a benchmark for further calculations and dynamic adjustments. Through multiple iterations and corrections of the initial response power, an optimal discharge power that satisfies both grid demand and battery safety can be gradually found.

[0038] In one alternative embodiment, a preset rule base can be used to determine the initial response power. This preset rule base is established based on the battery's physical characteristics, the actual demands of the power grid, and the vehicle's actual power consumption. For example, if the power grid demand is charging and the battery temperature is within a safe range, the initial response power can be set to the demanded power minus the vehicle's basic power consumption. If the battery temperature is close to a critical value, the rule might be to reduce the demanded power to avoid overheating.

[0039] In another alternative embodiment, a machine learning model, such as a support vector machine or a time series forecasting model, can be used to predict the initial response power. The model can be pre-trained based on historical data, and the initial response power is determined by analyzing the correspondence between battery data, power demand, and initial response power.

[0040] Step S106: Based on battery data, predict the temperature of the vehicle after executing the initial response power to obtain the predicted temperature.

[0041] The predicted temperature mentioned above is a comprehensive determination of the battery temperature based on current battery data, the thermal effects generated after performing charge / discharge operations corresponding to the initial response power, the battery's heat dissipation capacity, and external environmental conditions. The predicted temperature can be used to assess the impact of charge / discharge operations on battery temperature, thereby preventing excessively high battery temperatures from jeopardizing battery performance and safety. The predicted temperature is an important reference for adjusting charge / discharge power and activating or deactivating thermal management measures.

[0042] In one alternative embodiment, a thermodynamic model can be used to analyze the battery's thermodynamic parameters and thermal boundary conditions to predict the temperature after the initial response power is applied. The thermodynamic model is constructed using battery data and the initial response power, and then solved using the finite difference or finite element method to obtain the predicted temperature.

[0043] In another alternative embodiment, a multilayer perceptron or convolutional neural network can be used to learn the nonlinear relationship between battery data, initial response power, and predicted temperature. This allows for timely prediction of the predicted temperature after obtaining battery data and calculating the initial response power.

[0044] Step S108: Based on power demand, battery data, and predicted temperature, adjust the initial response power at least once to obtain the target response power.

[0045] The adjustment is used to adjust the initial response power according to different battery parameters, while the target response power is used to control the charging and discharging of the vehicle.

[0046] The aforementioned adjustments can be a dynamic process. This process modifies the initially calculated response power to ensure battery health and safety, as well as the achievement of user charging goals, while simultaneously meeting grid demands. The adjustment strategy considers factors such as real-time grid demand, battery status, and vehicle charging / discharging preferences. The goal of the adjustment is to find a charging / discharging power that satisfies grid dispatch instructions while adhering to battery safety operating rules.

[0047] The target response power mentioned above is a charging and discharging power suitable for the current vehicle condition, obtained after comprehensively considering changes in battery temperature, the vehicle's actual power demand, and changes in battery state. Utilizing the target response power ensures that charging and discharging operations can effectively support the grid's peak shaving and valley filling tasks without sacrificing battery health and user experience.

[0048] In one alternative embodiment, an adjustment rule can be pre-defined to adjust the initial response power to obtain the target response power. For example, the adjustment rule could be "if the predicted battery temperature exceeds 42°C, reduce the initial response power by 20%". The adjustment rule can be determined by analyzing power demand, battery data, and the impact of predicted temperature on the initial response power. The adjustment rule can be constructed through manual analysis or determined through simulation experiments.

[0049] In another alternative embodiment, battery performance is affected by various parameters. Therefore, changes in power demand and predicted temperature can impact battery performance. For example, the chemical reaction rate and internal resistance of a battery change under different states of charge and temperatures, directly affecting the thermal effects during charging and discharging. Therefore, the impact of response power on the battery needs to be considered to adjust the initial response power to obtain the target response power. Deep reinforcement learning can be used to learn how to adjust the response power while satisfying constraints. An environmental model can be built using power demand, battery data, and predicted temperature, and a reward function can be designed to find the target response power that satisfies each constraint.

[0050] In this embodiment, when a vehicle is connected to the power grid, the vehicle's power demand and battery data for the current time period are acquired. The power demand for the current time period is received from the power grid. Then, based on the power demand and battery data, an initial response power is obtained for the required power. Based on the battery data, the vehicle's temperature after executing the initial response power is predicted, resulting in a predicted temperature. Therefore, based on the power demand, battery data, and predicted temperature, the initial response power is adjusted at least once to obtain a target response power. This application fully considers the vehicle's actual power demand and battery temperature response when scheduling vehicle charging and discharging power. Specifically, after the vehicle is connected to the power grid, the initial response power is calculated promptly using the power demand of the power grid and the vehicle's battery data. The actual power demand of the vehicle and the predicted temperature after executing the initial response power are considered to adjust the initial response power, obtaining a target response power that satisfies both the vehicle's energy needs and ensures vehicle safety. This achieves the goal of flexibly scheduling the vehicle's charging and discharging power, thus realizing the technical effect of flexible vehicle charging and discharging power scheduling and solving the technical problem of poor flexibility in vehicle charging and discharging power scheduling in related technologies.

[0051] Optionally, based on the demand power and battery data, an initial response power is obtained for the demand power, including: determining the vehicle's thermal power based on the battery data; and obtaining the initial response power based on the thermal power and the demand power.

[0052] The aforementioned thermal power refers to the self-consumption of battery thermal management, i.e., the electricity consumed by the vehicle regardless of whether charging or discharging is in progress. In other words, thermal power is the system's self-consumption independent of the battery's charging / discharging state. Even when the battery is charging or discharging, if the battery temperature reaches the condition for activating the cooling system, additional energy is required to drive the liquid cooling system to achieve stable battery temperature control. This additional energy requirement needs to be considered when calculating the overall battery energy balance and charging / discharging strategy to ensure the battery operates within a safe temperature range while accurately calculating energy efficiency.

[0053] In one alternative embodiment, the thermal power can be specifically determined from battery data. For example, the thermal power can be related to both the battery temperature and the ambient temperature. If the battery temperature is significantly higher than the ambient temperature, the thermal power may be higher. Alternatively, a thermal power consumption model can be established to calculate the thermal power based on the battery data. This thermal power consumption model can be built based on the cooling system and the battery's thermal characteristics.

[0054] Then, the initial response power can be obtained based on the thermal power and the demanded power. That is, the initial response power is the vehicle's preliminary response value to the grid's power demand, taking into account the battery's thermal power; it represents the actual charging and discharging power the vehicle can provide. Because of the influence of thermal power, the initial response power can satisfy both the grid's power demand and the vehicle's actual power consumption.

[0055] Optionally, the battery data includes the battery temperature. Based on the battery data, the predicted temperature is obtained after the vehicle performs the initial response power. This includes: determining the battery temperature change value based on the battery data and the initial response power; and obtaining the predicted temperature based on the sum of the battery temperature and the temperature change value.

[0056] In one alternative embodiment, the battery temperature trend is predicted by analyzing current battery data and initial charge / discharge power. Thermodynamic models, machine learning models, etc., can be used to calculate the battery temperature change after power is applied. By evaluating the battery temperature change during a specific charge / discharge task, battery damage due to overheating can be prevented. Furthermore, predicting the temperature change helps determine the final predicted temperature, thereby dynamically adjusting the charge / discharge power to ensure the battery operates within a safe temperature range. That is, the predicted temperature is obtained by summing the battery temperature and the temperature change value.

[0057] Therefore, predicting the temperature reflects the expected thermal state of the battery after executing a charge / discharge plan, which directly reflects the battery's health and safety level. The predicted temperature value is crucial for developing thermal management and charge / discharge strategies. Predicted temperature can be used to dynamically adjust charge / discharge power to balance grid demand, user demand, and battery health, thereby achieving multi-objective constraints.

[0058] Optionally, the battery data also includes battery mass and specific heat capacity. Based on the battery data and initial response power, the temperature change value of the battery is determined, including: calculating the heat generation and heat dissipation of the battery based on the battery data and initial response power; obtaining a heat difference based on the difference between heat generation and heat dissipation; obtaining a first product based on the product of the heat difference and the time period corresponding to the current time period, and obtaining a second product based on the product of battery mass and specific heat capacity; and obtaining the temperature change value based on the first product and the second product.

[0059] In one alternative embodiment, to comprehensively assess the temperature changes of the battery during a specific charge-discharge schedule, heat generation and dissipation can be considered. Specifically, battery data and initial response power are used to estimate the heat generated by the battery under that power and the heat it can dissipate under current environmental conditions. Heat generation can be calculated through internal chemical reactions and resistive losses during charge-discharge, while heat dissipation can be determined based on the heat exchange mechanism between the battery and its surroundings. The initial response power can be used to infer the current in the battery circuitry. The terminal voltage used to calculate heat generation can be determined by looking up a table and considering the battery's internal resistance. By calculating heat generation and dissipation, the specific thermal load faced by the battery can be directly assessed, i.e., the heat difference can be determined, reflecting the thermal state evolution of the battery during charge-discharge operations, reflecting the difference between the heat generated and the heat dissipated within a certain time interval. In other words, the heat difference reflects the net thermal effect of battery temperature rise and fall.

[0060] After determining the heat difference, the actual change in battery temperature can be calculated to determine whether the battery will overheat or overcool under a given charge / discharge power. Specifically, the first product can be obtained by multiplying the heat difference by the duration of the time period corresponding to the current time window. This first product represents the total energy level of the battery's net thermal effect within that time window. The second product, calculated by multiplying the battery mass by its specific heat capacity, converts the heat difference into the physical parameters required for temperature change. The second product is essentially a coefficient for converting battery thermal energy into temperature change, determining the sensitivity of the battery temperature to changes in thermal energy. It reflects the thermal characteristics of the battery materials. Therefore, based on the first and second products, the thermal effect can be converted into a specific temperature change to indicate the battery's temperature variation.

[0061] Optionally, the initial response power is adjusted at least once based on power demand, battery data, and predicted temperature to obtain a target response power, including: adjusting the initial response power based on the physical constraints of the battery to obtain a first adjusted power; adjusting the first adjusted power based on the predicted temperature to obtain a second adjusted power; and adjusting the second adjusted power based on power demand and battery data to obtain the target response power.

[0062] In one alternative embodiment, the target response power is ultimately determined by taking into account multiple factors such as battery safety, health, and user and grid needs, which ensures both the effective use of the battery and meets the diverse needs of grid stability and user electricity consumption.

[0063] Specifically, the physical characteristics of the battery can be considered, including but not limited to charging power, discharging power, and upper and lower limits of state of charge, in order to adjust the initial response power and avoid affecting the battery health due to power exceeding the limit.

[0064] Then, the first adjustment power is further adjusted using the predicted battery temperature to ensure that it remains within a safe range after the first adjustment. Further power adjustments, while meeting physical constraints, ensure that battery temperature changes do not affect battery health.

[0065] Finally, the power is adjusted again based on the vehicle's actual power demand to ensure that the second adjusted power can also meet the user's actual needs. For example, the battery's state of charge and remaining available capacity can be combined to determine whether the second adjusted power can meet the vehicle's power demand while satisfying grid dispatch, and the power can be adjusted in a timely manner to determine the actual available target response power.

[0066] Optionally, adjusting the first adjustment power based on the predicted temperature to obtain the second adjustment power includes: determining the first adjustment power as the second adjustment power when the predicted temperature is less than or equal to a preset safe temperature; and repeatedly executing the steps of determining a new first adjustment power based on the attenuation coefficient, predicting the temperature of the vehicle after implementing the new first adjustment power in the current time period based on battery data, obtaining a new predicted temperature, and reducing the attenuation coefficient until the new predicted temperature is less than or equal to the preset safe temperature, or the attenuation coefficient is less than the preset coefficient, and then determining the new first adjustment power as the second adjustment power.

[0067] In one optional embodiment, after receiving the first adjustment power adjusted based on battery physical constraints, it can be determined whether the predicted temperature is less than or equal to a preset safe temperature. The preset safe temperature can be the highest temperature at which the battery can operate safely, such as 45°C, 46°C, or 47°C. This confirms whether the first adjustment power will place the battery within a safe operating temperature range, avoiding safety hazards and performance degradation caused by battery overheating. If the predicted temperature meets the condition, the first adjustment power will not require additional modification and will be directly used as the second adjustment power to guide the battery's charging and discharging operations.

[0068] If the predicted temperature exceeds the preset safe temperature, power attenuation adjustment is required. Specifically, this can be achieved by introducing an attenuation coefficient, such as 0.9, to reduce the initial adjustment power, thereby generating a new initial adjustment power. Then, based on this new power, the temperature is re-predicted, and adjustments are made continuously until the predicted temperature drops to the preset safe temperature or the attenuation coefficient reaches a preset minimum value, such as 0.1. Dynamic power adjustment prevents the battery temperature from exceeding the limit, ensuring that the battery is not damaged by excessive temperature during charging and discharging tasks, while meeting the initial charging and discharging power requirements as much as possible. Even if the charging and discharging efficiency decreases, it is essential to ensure that the battery does not overheat, thus ensuring safe battery operation.

[0069] Optionally, the second adjustment power is adjusted based on power demand and battery data to obtain the target response power, including: determining the required energy based on power demand and battery data, and predicting the vehicle's remaining charging energy in the future based on battery data; determining the second adjustment power as the target response power when the remaining charging energy is greater than or equal to the required energy; and determining the target response power based on the required energy, charging efficiency, and thermal power when the remaining charging energy is less than the required energy.

[0070] In one optional embodiment, while meeting the power demand of the power grid, it is still necessary to consider the user's immediate power demand to ensure that the vehicle can still be charged with the required energy in the future. This means that the energy demand represents the actual energy required by the user. For example, the power demand can be converted into a specific energy demand for easier quantitative analysis; that is, the required energy can be determined based on the power demand and battery data. Furthermore, the future charging capacity of the battery can be predicted based on current battery data to determine whether the battery has sufficient energy receiving capacity to meet the set power demand in the future.

[0071] Specifically, by comparing the remaining charging energy with the required energy, if the remaining charging energy can meet the required energy, a second power adjustment can be implemented. If the remaining charging energy is insufficient to meet the required energy, it indicates that the battery cannot charge enough energy to meet the demand in the future at the current second power adjustment. In this case, the target response power needs to be recalculated, which can be determined based on the required energy, charging efficiency, and thermal power. By adjusting the second power adjustment, it is ensured that the battery can charge or discharge enough energy to meet the predetermined power demand. Considering charging efficiency, dynamically adjusting the second power adjustment ensures that the battery meets the power demand while operating safely.

[0072] Optionally, based on battery data, the remaining charging energy of the vehicle in future time periods can be predicted, including: determining the safe response power based on battery data; and determining the remaining charging energy based on the product of battery charging efficiency, safe response power, and remaining time.

[0073] In one alternative embodiment, battery operation must remain within a reasonable safety range to avoid overcharging, over-discharging, or excessively high / low temperatures, thereby protecting the battery from damage. Therefore, when predicting remaining charging energy, the vehicle's safe response power can be determined based on battery data to ensure safe operation. The safe response power can be the maximum charging power corresponding to the current battery temperature, ensuring that even under urgent grid demands or special user requirements, the battery will not operate beyond its safety margin.

[0074] Then, combining the battery's charging efficiency (the ratio of energy charged into the battery to the total input energy, which may be less than 1 due to energy loss) and the remaining time (the time remaining before the vehicle leaves the grid again), the total energy the battery can receive and effectively store during that remaining time is calculated. This remaining charging energy, or the vehicle's rechargeable energy calculated using the maximum allowable charging power at the current temperature, provides an energy-level basis for V2G scheduling decisions, helping to balance grid demand and vehicle charging capacity. Expressing the battery's charging capacity explicitly in terms of energy facilitates subsequent charging and discharging scheduling decisions. Accurate assessment and prediction of the battery's energy receiving capacity enables precise scheduling and efficient resource allocation.

[0075] Preferably, the target response power is determined based on the energy demand, charging efficiency, and thermal power, including: determining a third product based on the product of charging efficiency and remaining time; determining the average power based on the energy demand and the third product; determining the actual power based on the sum of thermal power and average power; and determining the minimum value between the vehicle's maximum safe power and the actual power as the target response power.

[0076] In one alternative embodiment, a third product is calculated based on the battery's charging efficiency and the remaining estimated parking time of the vehicle. The remaining time can be the entire estimated parking cycle or divided into multiple time segments, each corresponding to a time period in a scheduling plan. The third product represents the energy efficiency that the battery can theoretically receive and effectively store during the remaining parking time, used to accurately predict the actual energy the battery can charge in the following parking cycles. By considering energy losses during battery charging, it provides more realistic basic data for subsequent power planning.

[0077] Then, based on the demanded energy and the third product, the average power is determined, that is, the average charging or discharging power required by the battery throughout the remaining parking time to meet the demanded energy is calculated. Preferably, this average power can be calculated by dividing the demanded energy by the third product. Determining an average power level ensures that the battery can charge or discharge sufficient energy as needed during future parking periods to achieve the charging and discharging goals of the user or the power grid. Furthermore, considering that the battery may generate additional heat during charging and discharging, thus consuming a certain amount of thermal power, the actual power determination needs to meet the average power requirement while also requiring additional thermal power to support the operation of the thermal management system.

[0078] Therefore, the maximum safe power calculated based on the current battery state can be compared with the actual power, and the smaller value between the two can be selected as the target response power. This means that the final target response power will not exceed the battery's maximum safe operating range, ensuring the user's actual power needs. This ensures that when the vehicle participates in V2G dispatch, the charging and discharging plan can effectively meet both the grid demand and the user's vehicle needs, while also ensuring that the battery operates in a safe and healthy state.

[0079] The technical solution proposed in this application is described below with reference to an optional embodiment. This application proposes a V2G aggregation scheduling method for electric vehicles based on thermal-electric coupling constraints. This method can address the problems of neglecting battery thermal management, insufficient user demand guarantee, and lack of dynamic adjustment capabilities, and achieve multi-objective coordination of grid demand, battery safety, and user satisfaction.

[0080] Existing V2G dispatch strategies generally neglect thermal effects. Frequent or high-power charging and discharging significantly increase battery heat generation. If left unmanaged, this can lead to excessively high battery temperatures, accelerated aging, and even safety risks. Furthermore, they fail to adequately guarantee user demand; dispatch plans often struggle to accurately ensure the user's set state of charge (SOC) target at the time of disconnection while simultaneously meeting grid power requirements. Moreover, most solutions employ static dispatching methods such as open-loop scheduling, failing to dynamically adjust based on real-time battery temperature, SOC changes, and grid demand fluctuations during vehicle parking, resulting in significant deviations in plan execution.

[0081] The method in this embodiment can deeply integrate battery thermal management models, user charging needs and grid dispatch instructions, and is a V2G aggregation dispatch method with online dynamic adjustment capabilities.

[0082] Specifically, this method includes initialization and data acquisition. A day can be divided into 144 10-minute planning segments, and then the power demand instructions for each planning segment for the next 24 hours issued by the power grid are obtained. During charging, When the value is negative, during discharge, The value is positive. It also retrieves the initial information of electric vehicles participating in V2G within the aggregation region.

[0083] Initial information may include, but is not limited to, the vehicle's current SOC, total battery pack capacity, parking start and end times, and the user-defined target SOC for the off-grid time. Current battery temperature and ambient temperature Then, the power is dynamically adjusted. This step uses input data for each vehicle at each time period t to predict the target response power. This refers to the net power (W) actually generated by the vehicle during time period t, which includes thermal management power consumption. Input data may include, but is not limited to, the grid's dispatch instructions during time period t. Negative values ​​indicate the need for charging, while positive values ​​indicate the need for discharging; the battery's state of charge at the start of the current time period. Battery temperature at the start of the current time period ; Estimated time of vehicle disconnection It can be represented by the segment number; the user-defined target SOC for disconnection. Battery rated capacity Rated capacity is measured in Wh; the maximum allowable charging / minimum discharging power of the battery at the current temperature. Maximum safe operating temperature threshold for batteries , It can be 45℃; the length of a single planned segment , It can be .

[0084] Specifically, predicting the target response power can be achieved using methods such as... Figure 2 The method shown is as follows. The method for predicting the target response power includes: calculating the thermal management baseline power consumption, generating the initial response power, temperature safety verification, and user requirement feasibility verification, thereby determining the execution power.

[0085] Specifically, calculate the thermal management base power consumption, i.e., thermal management power consumption. . The system consumes its own power and requires additional power for both charging and discharging. This can be adjusted based on the current battery temperature. And implemented with preset thermal management strategies (such as liquid cooling start / stop logic). If Start the cooling system and calculate the power consumption required to maintain temperature control. If the temperature has not reached the temperature required to activate the cooling system. ,make .

[0086] Generate initial response power The handling can be differentiated based on the nature of the power grid command. For example, during peak shaving or vehicle charging, the charging power... In this case, it is possible to make When filling a valley or when a vehicle is discharging electricity, In this case, it is possible to make This means that the battery needs to discharge more to supply the vehicle's thermal management system.

[0087] And on Hard limiting is performed using the following formula:

[0088] ;

[0089] in, For the initial response power, Minimum discharge power, Maximum charging power, This is a function that limits input values ​​to between specified upper and lower limits.

[0090] Temperature safety verification can be performed by using a thermo-electric coupling model to predict the temperature at the next moment after the initial response power is executed.

[0091] Specifically, the following formula is used based on the initial response power. Reverse current calculation:

[0092] ;

[0093] in, For current, The initial response power, The voltage drop can be estimated by referring to the data table of the SOC and taking into account the internal resistance. The data table can reflect the relationship between open circuit voltage and state of charge.

[0094] Then, the heat generation is calculated using the following formula. :

[0095] ;

[0096] Among them, the heat generated by the battery within the planned segment t , For current, Terminal voltage, Open circuit voltage, This is based on experimental calibration and varies with SOC and temperature, under the state of charge of... The temperature is Battery internal resistance under certain conditions.

[0097] And based on the current battery temperature The following formula is used to calculate heat dissipation based on ambient temperature and cooling conditions. :

[0098] ;

[0099] in, This represents the heat dissipation of the battery within the planned segment t. The heat transfer coefficient between the battery and the environment. The heat transfer coefficient of the liquid cooling system. This refers to the coolant temperature. For battery temperature, The ambient temperature.

[0100] Furthermore, based on the law of energy conservation, the battery temperature at the end of the current planned segment can be predicted:

[0101] ;

[0102] in, To predict temperature, This represents the heat dissipation of the battery within the planned segment t. The heat generated by the battery within the planned segment t, For battery quality, For specific heat capacity, This is for a planned period of time.

[0103] And determine whether the predicted temperature is close to the safe temperature. ,like After verification, it can be made .like Then power needs to be reduced. This can be done by setting an initial value for the attenuation coefficient. ,like It can be 0.9, then, iterate: Let Re-predict If the temperature still exceeds the limit, then proceed in sequence... Decrease by 0.1 until... or You can get .

[0104] Conducting a feasibility check of user needs can be done by checking whether, even if charging is subsequently performed at the maximum safe power, the device can be charged from the current SOC to [a higher capacity] within the remaining time. accomplish.

[0105] Specifically, calculate the number of remaining plan segments. And the energy required to be charged is calculated using the following formula. ;

[0106] ;

[0107] in, For the required energy, This represents the battery's state of charge for the current time period. For the target state of charge, This refers to the battery's rated capacity.

[0108] Furthermore, to estimate the maximum chargeable energy for the remaining time period, we can assume that each future period will use the maximum allowable charging power at the current temperature. And deduct thermal management power consumption And considering charging efficiency The maximum rechargeable energy for the remaining time period can be calculated using the following formula. :

[0109] ;

[0110] in, This represents the maximum rechargeable energy for the remaining time period. The remaining number of planned segments, For charging efficiency, The duration of each segment can be 600 seconds. Let be the temperature in the (t+k)th time interval. The temperature in the time interval t+k Maximum charging power at the specified level Let be the heat dissipation at temperature t during the (t+k)th time interval.

[0111] To simplify the calculation, the maximum rechargeable energy for the remaining time period can also be calculated using the following formula. :

[0112] ;

[0113] in, This represents the maximum rechargeable energy for the remaining time period. The remaining number of planned segments, For charging efficiency, The duration of each segment can be 600 seconds. This is the maximum charging power, and ,in, For temperature Maximum charging power at the specified level This refers to thermal power consumption.

[0114] Then, determine the maximum chargeable energy for the remaining time period. Energy required by the vehicle ,like This indicates that the user's needs can be met, and the account can be retained. .like This indicates that the State of Charge (SOC) is prioritized. In this case, tracking the grid command is abandoned, and the system switches to "SOC protection mode," meaning the energy required to meet the SOC requirement is calculated using the following formula. Required average power:

[0115] ;

[0116] in, for, For the required energy, The remaining number of planned segments, For charging efficiency, The duration of each segment can be 600 seconds.

[0117] Then, the actual power can be calculated using the following formula, which satisfies long-term energy requirements without exceeding instantaneous power and temperature limits:

[0118] ;

[0119] in, The actual power in time period t. The maximum charging power is the battery temperature at the current time period t. For battery temperature, Average power, Let be the heat consumption during the current time period t, and min is the minimum value.

[0120] Simultaneously record the updated state of battery charge after the current time period ends. and the temperature at the end of the current period. That is, predicting temperature The initial state of charge for the next time period. The following formula can be used for calculation:

[0121] ;

[0122] in, State of charge for the next time period , The rated capacity of the battery. For charging efficiency, The duration of each segment can be 600 seconds. The net power at the battery terminal during time period t. , The actual power in time period t. Let t be the thermal power consumption during time period t.

[0123] like Figure 3As shown, an optional power scheduling method is illustrated. This method includes: dividing time periods, setting charging targets and energy allocation, calculating power based on operating conditions, accurately predicting battery temperature, and dynamically adjusting power.

[0124] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0125] According to an embodiment of this application, a device embodiment for scheduling vehicle charging and discharging power is provided. It should be noted that the device can be used to execute the above-described vehicle charging and discharging power scheduling method.

[0126] Figure 4 This is a schematic diagram of a vehicle charging and discharging power scheduling device according to an embodiment of this application, such as... Figure 4 As shown, the device includes:

[0127] The acquisition module 40 is used to acquire the vehicle's power demand and the battery data of the vehicle's battery in the current period when the vehicle is connected to the power grid, and to receive the power demand for the current period from the power grid.

[0128] The calculation module 42 is used to obtain the initial response power for the demand power based on the demand power and battery data.

[0129] The prediction module 44 is used to predict the temperature of the vehicle after the initial response power is executed, based on battery data, and obtain the predicted temperature.

[0130] The adjustment module 46 is used to adjust the initial response power at least once based on power demand, battery data and predicted temperature to obtain the target response power. The adjustment is used to adjust the initial response power according to different battery parameters, and the target response power is used to control the charging and discharging of the vehicle.

[0131] Optionally, the calculation module is also used to determine the vehicle's thermal power based on battery data; and to obtain the initial response power based on the thermal power and the demand power.

[0132] Optionally, the battery data includes battery temperature. The prediction module is also used to determine the battery temperature change value based on the battery data and the initial response power; and to obtain the predicted temperature based on the sum of the battery temperature and the temperature change value.

[0133] Optionally, the battery data also includes battery mass and specific heat capacity. The prediction module is also used to calculate the heat generation and heat dissipation of the battery based on the battery data and initial response power; obtain a heat difference based on the difference between heat generation and heat dissipation; obtain a first product based on the product of the heat difference and the time period corresponding to the current time period, and obtain a second product based on the product of battery mass and specific heat capacity; obtain the temperature change value based on the first product and the second product.

[0134] Optionally, the adjustment module is also used to adjust the initial response power based on the physical constraints of the battery to obtain a first adjusted power; adjust the first adjusted power based on the predicted temperature to obtain a second adjusted power; and adjust the second adjusted power based on power demand and battery data to obtain a target response power.

[0135] Optionally, the adjustment module is further configured to: determine the first adjustment power as the second adjustment power when the predicted temperature is less than or equal to the preset safe temperature; and repeatedly execute the steps of determining a new first adjustment power based on the attenuation coefficient, predicting the temperature of the vehicle after implementing the new first adjustment power in the current period based on battery data, obtaining a new predicted temperature, and reducing the attenuation coefficient, until the new predicted temperature is less than or equal to the preset safe temperature, or the attenuation coefficient is less than the preset coefficient, and then determine the new first adjustment power as the second adjustment power.

[0136] Optionally, the adjustment module is also used to determine the required energy based on power demand and battery data, and to predict the vehicle's remaining charging energy in future periods based on battery data; if the remaining charging energy is greater than or equal to the required energy, the second adjustment power is determined as the target response power; if the remaining charging energy is less than the required energy, the target response power is determined based on the required energy, charging efficiency, and thermal power.

[0137] Optionally, the adjustment module is further configured to determine the safe response power based on battery data; determine the remaining charging energy based on the product of the battery's charging efficiency, safe response power, and remaining time; preferably, the adjustment module is further configured to determine a third product based on the product of charging efficiency and remaining time; determine the average power based on the demand energy and the third product; determine the actual power based on the sum of thermal power and average power; and determine the minimum value between the vehicle's maximum safe power and the actual power as the target response power.

[0138] Embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application when it runs.

[0139] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0140] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0141] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0142] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0143] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0145] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0147] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0148] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for scheduling vehicle charging and discharging power, characterized in that, Applied to vehicles, including: When the vehicle is connected to the power grid, the power demand of the vehicle and the battery data of the vehicle in the current time period are obtained, and the power demand for the current time period is received from the power grid. Based on the required power and the battery data, the initial response power for the required power is obtained; Based on the battery data, the temperature of the vehicle after executing the initial response power is predicted, and the predicted temperature is obtained. Based on the power demand, the battery data, and the predicted temperature, the initial response power is adjusted at least once to obtain a target response power. The adjustment is used to adjust the initial response power according to different battery parameters, and the target response power is used to control the charging and discharging of the vehicle.

2. The method according to claim 1, characterized in that, Based on the required power and the battery data, an initial response power is obtained for the required power, including: Based on the battery data, the thermal power of the vehicle is determined; The initial response power is obtained based on the thermal power and the required power.

3. The method according to claim 1, characterized in that, The battery data includes battery temperature. Based on the battery data, the temperature of the vehicle after executing the initial response power is predicted, resulting in the predicted temperature, including: Based on the battery data and the initial response power, the temperature change value of the battery is determined; The predicted temperature is obtained based on the sum of the battery temperature and the temperature change value.

4. The method according to claim 3, characterized in that, The battery data also includes battery mass and specific heat capacity. Based on the battery data and the initial response power, the temperature change value of the battery is determined, including: Based on the battery data and the initial response power, calculate the heat generation and heat dissipation of the battery; The heat difference is obtained based on the difference between the heat generated and the heat dissipated. A first product is obtained by multiplying the heat difference with the time period corresponding to the current time period, and a second product is obtained by multiplying the battery mass and the specific heat capacity. The temperature change value is obtained based on the first product and the second product.

5. The method according to claim 1, characterized in that, Based on the power demand, the battery data, and the predicted temperature, the initial response power is adjusted at least once to obtain the target response power, including: The initial response power is adjusted based on the physical constraints of the battery to obtain a first adjusted power; The first adjustment power is adjusted based on the predicted temperature to obtain the second adjustment power; The second adjustment power is adjusted based on the power demand and the battery data to obtain the target response power.

6. The method according to claim 5, characterized in that, The first adjustment power is adjusted based on the predicted temperature to obtain the second adjustment power, including: If the predicted temperature is less than or equal to the preset safe temperature, the first adjustment power is determined as the second adjustment power; If the predicted temperature is greater than the preset safe temperature, the steps of determining a new first adjustment power based on the attenuation coefficient, predicting the temperature of the vehicle after the new first adjustment power is applied in the current time period based on the battery data, obtaining a new predicted temperature, and reducing the attenuation coefficient are repeated until the new predicted temperature is less than or equal to the preset safe temperature, or the attenuation coefficient is less than the preset coefficient, and the new first adjustment power is determined as the second adjustment power.

7. The method according to claim 5, characterized in that, The second adjustment power is adjusted based on the power demand and the battery data to obtain the target response power, including: Based on the electricity demand and the battery data, the required energy is determined, and based on the battery data, the remaining charging energy of the vehicle in future periods is predicted. If the remaining charging energy is greater than or equal to the required energy, the second adjustment power is determined as the target response power; If the remaining charging energy is less than the required energy, the target response power is determined based on the required energy, charging efficiency, and thermal power.

8. The method according to claim 7, characterized in that, Based on the battery data, predict the vehicle's remaining charging energy in future time periods, including: Based on the battery data, determine the safe response power; The remaining charging energy is determined based on the product of the battery's charging efficiency, the safety response power, and the remaining time. Preferably, determining the target response power based on the required energy, charging efficiency, and thermal power includes: The third product is determined based on the product of the charging efficiency and the remaining time; The average power is determined based on the energy demand and the third product. The actual power is determined based on the sum of the thermal power and the average power; The minimum value between the vehicle's maximum safe power and its actual power is determined as the target response power.

9. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 8.

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