Methods, devices, systems, vehicles and equipment for coordinated control of discharge and thermal management

Abstract

This application relates to a method, apparatus, system, vehicle, and device for coordinated control of discharge and thermal management. The method includes: determining a predicted thermal management strategy based on sensing data while allowing a target vehicle to discharge; wherein the sensing data includes at least one of grid data, user data, and vehicle data; predicting a discharge strategy for the target vehicle based on the sensing data and the predicted thermal management strategy to obtain a predicted discharge strategy; controlling the target vehicle to discharge according to the predicted discharge strategy, and during the discharge process, predicting the vehicle battery temperature at a preset future time based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle to obtain a predicted battery temperature; and performing coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature. This method can ensure battery life and safety.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a method, apparatus, system, vehicle, and equipment for coordinated control of discharge and thermal management. Background Technology

[0002] With the increasing popularity of electric vehicles, Vehicle-to-Grid (V2G) technology is becoming increasingly important as a key technology for realizing vehicle-grid interaction, peak shaving and valley filling, and improving the utilization rate of renewable energy. V2G technology uses electric vehicle batteries as distributed energy storage units through bidirectional charging and discharging, discharging during peak grid load and charging during off-peak load, thereby optimizing grid operation.

[0003] However, the V2G discharge process generates a lot of heat, which affects the lifespan and safety of vehicle batteries. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, device, system, vehicle, and equipment for coordinated control of discharge and thermal management that can ensure battery life and safety, addressing the aforementioned technical problems.

[0005] In a first aspect, this application provides a method for coordinated control of discharge and thermal management, including:

[0006] If the target vehicle is allowed to discharge, a predictive thermal management strategy is determined based on sensing data; wherein the sensing data includes at least one of grid data, user data, and vehicle data.

[0007] Based on the sensing data and the predicted thermal management strategy, the discharge strategy of the target vehicle is predicted to obtain the predicted discharge strategy.

[0008] The target vehicle is controlled to discharge according to the predicted discharge strategy. During the discharge process, the vehicle battery temperature at a preset future time is predicted based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle, so as to obtain the predicted battery temperature.

[0009] Based on the current battery temperature and the predicted battery temperature, the target vehicle is subjected to coordinated control of discharge and thermal management.

[0010] In one embodiment, the coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature includes: determining a target thermal management strategy based on the current battery temperature and the predicted battery temperature; determining a target discharge strategy based on the sensing data and the target thermal management strategy; and performing coordinated control of discharge and thermal management of the target vehicle based on the target thermal management strategy and the target discharge strategy.

[0011] In one embodiment, the target thermal management strategy includes a target thermal management mode and a target thermal management level under the target thermal management mode; determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature includes: determining the target thermal management mode based on the current battery temperature; and determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature.

[0012] In one embodiment, the current battery temperature is the highest among multiple measured battery temperatures; determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature includes: when the target thermal management mode is a cooling mode, determining the temperature rise rate based on the highest temperature and the predicted battery temperature; when the temperature rise rate is greater than a first preset rate and less than or equal to a second preset rate, or when the highest temperature is greater than a first preset temperature and less than or equal to a second preset temperature, determining a preset first cooling level as the target thermal management level; when the temperature rise rate is greater than a second preset rate and less than or equal to a third preset rate, or when the highest temperature is greater than a second preset temperature and less than or equal to a third preset temperature, determining a preset second cooling level as the target thermal management level; when the temperature rise rate is greater than a third preset rate, or when the highest temperature is greater than a third preset temperature, determining a preset third cooling level as the target thermal management level; wherein, under the first cooling level, the second cooling level, and the third cooling level, the flow rate of the cooling medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature decreases sequentially.

[0013] In one embodiment, the current battery temperature is the lowest among multiple measured battery temperatures; determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature includes: when the target thermal management mode is a heating mode, determining a target temperature difference based on the lowest temperature and the predicted battery temperature; when the target temperature difference is less than a first preset temperature difference, or when the lowest temperature is less than or equal to a fourth preset temperature and greater than a fifth preset temperature, determining a preset first heating level as the target thermal management level; when the target temperature difference is greater than or equal to the first preset temperature difference and less than a second preset temperature difference, or when the lowest temperature is less than or equal to a fifth preset temperature and greater than a sixth preset temperature, determining a preset second heating level as the target thermal management level; when the target temperature difference is greater than or equal to the second preset temperature difference and less than a third preset temperature difference, or when the lowest temperature is less than or equal to a sixth preset temperature, determining a preset third heating level as the target thermal management level; wherein, under the first heating level, the second heating level, and the third heating level, the flow rate of the heating medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature increases sequentially.

[0014] In one embodiment, the method further includes: during the coordinated control process, determining a current battery temperature difference based on the highest and lowest temperatures among multiple measured battery temperatures; if the current battery temperature difference is greater than a preset self-circulation activation temperature difference, exiting the target thermal management strategy and controlling the vehicle battery to enter self-circulation mode; if the current battery temperature difference is less than a preset self-circulation exit temperature difference, controlling the vehicle battery to exit the self-circulation mode and re-executing the step of determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature; wherein the preset self-circulation exit temperature difference is less than the preset self-circulation activation temperature difference; or, during the coordinated control process, exiting the target thermal management strategy when the current battery temperature reaches a thermal management temperature threshold.

[0015] In one embodiment, the predicted discharge strategy includes discharge power and discharge start time; the step of predicting the discharge strategy of the target vehicle based on the sensing data and the predicted thermal management strategy to obtain the predicted discharge strategy includes: inputting the sensing data and the predicted thermal management strategy into a pre-constructed multi-objective optimization model, performing multi-objective optimization on the discharge strategy to obtain the discharge power; the multi-objective optimization model aims to minimize the peak-valley difference of the grid load, maximize user benefits, and minimize battery degradation; and determining the discharge start time based on the sensing data, the predicted thermal management strategy, and the discharge power.

[0016] In one embodiment, the method further includes: during the collaborative control process, acquiring the measured battery temperature at preset time intervals; determining the temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time; and if the temperature deviation exceeds a preset deviation threshold, using a rolling time-domain optimization method to return to the step of determining the predicted thermal management strategy based on the sensing data.

[0017] Secondly, this application also provides a discharge and thermal management coordinated control device, comprising:

[0018] The first prediction module is used to determine a predictive thermal management strategy based on sensing data, provided that the target vehicle is allowed to discharge; wherein the sensing data includes at least one of power grid data, user data, and vehicle data.

[0019] The second prediction module is used to predict the discharge strategy of the target vehicle based on the sensing data and the predicted thermal management strategy, so as to obtain the predicted discharge strategy.

[0020] The third prediction module is used to control the target vehicle to discharge according to the prediction discharge strategy, and during the discharge process, it predicts the vehicle battery temperature at a preset future time based on the current ambient temperature, the prediction discharge strategy and the current battery temperature of the target vehicle, so as to obtain the predicted battery temperature.

[0021] The first control module is used to perform coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature.

[0022] Thirdly, this application also provides a discharge and thermal management coordinated control system, the system comprising: a data acquisition module for acquiring sensing data; and a coordinated control module, the coordinated control module being communicatively connected to the data acquisition module, the coordinated control module being used to execute the discharge and thermal management coordinated control method provided in the first aspect of this application.

[0023] Fourthly, this application also provides a vehicle that includes the system provided in the third aspect of this application.

[0024] Fifthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the discharge and thermal management coordinated control method provided in the first aspect of this application.

[0025] Sixthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the discharge and thermal management coordinated control method provided in the first aspect of this application.

[0026] In a seventh aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the discharge and thermal management coordinated control method provided in the first aspect of this application.

[0027] The aforementioned discharge and thermal management coordinated control method, device, system, vehicle, computer equipment, computer-readable storage medium, and computer program product, when allowing the target vehicle to discharge, determine a predictive thermal management strategy based on sensing data; predict the discharge strategy of the target vehicle based on the sensing data and the predicted thermal management strategy to obtain a predicted discharge strategy; control the target vehicle to discharge according to the predicted discharge strategy, and during the discharge process, predict the vehicle battery temperature at a preset future time based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle to obtain a predicted battery temperature; and perform coordinated control of discharge and thermal management on the target vehicle based on the current battery temperature and the predicted battery temperature. As can be seen, this application first determines a predictive thermal management strategy while allowing the target vehicle to discharge, enabling advance prediction of thermal management needs during the discharge process. Secondly, based on sensing data and the predicted thermal management strategy, a predictive discharge strategy is derived, taking into account thermal management needs during discharge, thus avoiding conflicts between the discharge strategy and thermal management and improving discharge safety. Finally, during the discharge process controlled by the predictive discharge strategy, the vehicle's battery temperature at a preset future time is predicted based on the current ambient temperature, the predicted discharge strategy, and the target vehicle's current battery temperature. Based on the current and predicted battery temperatures, coordinated control of discharge and thermal management of the target vehicle is implemented, further reducing or avoiding the impact of the large amount of heat generated during discharge on battery life and safety. Therefore, this application can achieve V2G discharge and optimize grid operation while ensuring battery life and discharge safety. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is an application environment diagram of the discharge and thermal management coordinated control method in one embodiment;

[0030] Figure 2 This is a flowchart illustrating the coordinated control method for discharge and thermal management in one embodiment;

[0031] Figure 3This is a schematic diagram of the process of coordinated control after V2G discharge is triggered in one embodiment;

[0032] Figure 4 This is a schematic diagram of the input and output of a discharge prediction model in one embodiment;

[0033] Figure 5 This is a schematic diagram of the input and output of a temperature prediction model in one embodiment;

[0034] Figure 6 This is a flowchart illustrating step 204 in one embodiment;

[0035] Figure 7 This is a schematic diagram of the process for determining the cooling level in a cooling mode in one embodiment;

[0036] Figure 8 This is a schematic diagram of the process for determining the heating level in a heating mode in one embodiment;

[0037] Figure 9 This is a flowchart illustrating the RTO strategy in one embodiment;

[0038] Figure 10 This is a structural block diagram of a discharge and thermal management coordinated control device in one embodiment;

[0039] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0041] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0042] In related technologies, the following problems exist when a vehicle performs V2G discharge:

[0043] The generation of a large amount of heat affects the life and safety of vehicle batteries: Discharge control mainly focuses on discharge power and time, without considering vehicle thermal management, and cannot realize discharge strategy adjustment based on temperature prediction, thus failing to guarantee battery life and safety.

[0044] The discharge strategy has a single objective: it is mostly based on fixed rules or simple optimization algorithms, and fails to fully combine multi-dimensional dynamic information such as user travel needs, real-time grid load, and battery health status to make intelligent decisions, resulting in the discharge strategy not meeting user needs, grid load, and battery status.

[0045] Lack of a full lifecycle collaborative optimization model: The absence of a unified model that can simultaneously optimize grid load, user benefits, and battery health may lead to conflicts between the various objectives during discharge.

[0046] Therefore, there is an urgent need for a vehicle-side V2G control scheme that can deeply integrate discharge control and thermal management control to achieve multi-objective collaborative optimization.

[0047] To address this, this application proposes a collaborative control method for discharge and thermal management. Through multi-objective collaborative optimization, deep integration of discharge control and thermal management control, and dynamic closed-loop optimization, it achieves collaborative control of V2G discharge and thermal management involving perception, decision-making, execution, and feedback. This represents a leap from single-objective optimization to multi-objective collaboration, from static planning to dynamic closed-loop control, and from isolated control to collaborative control, providing crucial technical support for the large-scale and safe application of vehicle-side V2G discharge technology.

[0048] The discharge and thermal management coordinated control method provided in this application embodiment can be applied to, for example... Figure 1 The application environment is shown. The target vehicle includes a discharge and thermal management coordinated control system, which comprises a data acquisition module 101 and a coordinated control module 102. The data acquisition module 101 collects sensing data from the power grid, the user terminal, and the vehicle, and sends the sensing data to the coordinated control module 102. The coordinated control module 102 is communicatively connected to the data acquisition module 101 and executes the discharge and thermal management coordinated control method. This method controls the vehicle battery and the vehicle thermal management system to perform coordinated discharge and thermal management based on the sensing data. It issues coordinated control commands (discharge commands to the battery and thermal management commands to the thermal management system) to the battery management system and the thermal management system in the target vehicle. This allows the battery management system to control the flow of electrical energy from the power battery to the power grid via a bidirectional charging / discharging pile according to the discharge commands, while the thermal management system performs thermal management on the power battery during the discharge process according to the thermal management commands.

[0049] The following describes the specific implementation of the discharge and thermal management coordinated control method.

[0050] In one exemplary embodiment, such as Figure 2 As shown, a method for coordinated control of discharge and thermal management is provided, which is applied to... Figure 1 The following explanation uses the collaborative control module 102 as an example, including the following steps 201 to 204:

[0051] Step 201: Determine a predictive thermal management strategy based on the sensing data, while allowing the target vehicle to discharge.

[0052] The sensing data includes at least one of the following: grid data, user data, and vehicle data. Grid data includes at least one of the following: real-time electricity price, peak and off-peak hours, grid frequency, voltage, transformer load rate, and short-term load forecast. User data includes at least one of the following: historical travel data, current location, destination, planned departure time, and expected driving range. Vehicle data includes: battery state of charge (SOC), state of health (SOH), temperature, battery capacity limit, grid voltage and frequency, charging station capacity, charging / discharging port status, and bidirectional charging / discharging station status. Sensing data also includes environmental data (such as current ambient temperature).

[0053] For example, such as Figure 3 As shown, the collaborative control module 102 monitors the target vehicle's status in real time. When it detects that V2G discharge has been triggered (e.g., the vehicle is connected to a bidirectional charging / discharging station, or the V2G button is activated), it obtains the route that the user will take after the discharge is completed (e.g., the route between the company and home). Based on the route information and perception data, it determines whether V2G discharge is allowed (i.e., whether the conditions for V2G discharge are met). If so, it predicts the thermal management strategy for the vehicle battery in the future based on the perception data, and obtains the predicted thermal management strategy for subsequent discharge preheating management collaborative control. If not, it does not control the vehicle to enter V2G discharge mode.

[0054] Optionally, after receiving a discharge permission command input by the user through the vehicle-mounted interface, it is determined that V2G discharge is permitted.

[0055] Predictive thermal management strategies are used to characterize the thermal management needs of vehicle batteries during discharge, such as the need for cooling, heating, and self-circulation. Optionally, the predictive thermal management strategy includes predictive thermal management modes and predictive thermal management levels within these modes. The predictive thermal management modes include predictive cooling modes and predictive heating modes, with multiple cooling levels in the predictive cooling mode and multiple heating levels in the predictive heating mode. Thermal management parameters corresponding to the predictive thermal management levels include, but are not limited to, compressor speed, cooling / heating circuit flow rate, inlet temperature, and outlet temperature.

[0056] To improve the accuracy of thermal management prediction, one possible implementation involves predicting a pre-defined thermal management strategy for a future period based on the current ambient temperature and battery state data from vehicle data. This results in a predicted thermal management strategy, also known as a predicted thermal management mode and its corresponding predicted thermal management level. Battery state data includes battery SOC, SOH, and current battery temperature. Another possible implementation involves inputting the current ambient temperature, battery SOC, SOH, current battery temperature, real-time grid electricity price, peak and off-peak hours, and user travel plans into a pre-built thermal management prediction model to perform thermal management prediction and obtain a predicted thermal management strategy. This thermal management prediction model is obtained through machine learning.

[0057] Step 202: Based on the sensing data and the predicted thermal management strategy, predict the discharge strategy of the target vehicle to obtain the predicted discharge strategy.

[0058] For example, the cooperative control module 102 first determines the predicted thermal management power consumption (i.e., how much power is required to implement the predicted thermal management strategy) based on the predicted thermal management strategy. Then, based on environmental data, vehicle data, and thermal management power consumption, it predicts the discharge strategy of the target vehicle in a preset future time period to obtain the predicted discharge strategy. To optimize the obtained discharge strategy, in one possible implementation, such as... Figure 4 As shown, the current ambient temperature, battery SOC, SOH, battery voltage, current battery temperature, battery capacity limit, bidirectional charging / discharging motor capability, grid voltage and frequency, discharge pile capability, and thermal management power consumption are input into the discharge prediction model to predict the discharge strategy of the target vehicle in a preset future time period (e.g., the next M hours), thus obtaining the predicted discharge strategy. The predicted discharge strategy includes discharge power, discharge start time, and discharge amount. The discharge prediction model can be obtained through deep reinforcement learning.

[0059] Step 203: Control the target vehicle to discharge according to the predicted discharge strategy, and during the discharge process, predict the vehicle battery temperature at a preset future time based on the current ambient temperature, the predicted discharge strategy and the current battery temperature of the target vehicle, to obtain the predicted battery temperature.

[0060] For example, after obtaining the predicted discharge strategy, the cooperative control module 102 controls the vehicle battery to discharge according to the strategy. During the discharge process, it predicts the battery temperature at preset intervals (e.g., N minutes). Based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle, it predicts the vehicle battery temperature at a preset future time (e.g., N minutes later), thus obtaining the predicted battery temperature at the preset future time. To improve the accuracy of temperature prediction, in one possible implementation, such as... Figure 5As shown, the current ambient temperature, predicted discharge power, and current battery temperature are input into a pre-built temperature prediction model to predict the vehicle battery temperature at a preset future time (e.g., N minutes later), thus obtaining the predicted battery temperature at the preset future time.

[0061] Step 204: Based on the current battery temperature and the predicted battery temperature, perform coordinated control of discharge and thermal management on the target vehicle.

[0062] For example, when the cooperative control module 102 obtains the predicted battery temperature for a preset future period at the current moment, it first determines whether the predicted battery temperature exceeds the safe range. If the predicted battery temperature exceeds the safe range, an early warning is triggered, cooperative control is not performed, and the discharge ends. If the predicted battery temperature does not exceed the safe range, the target thermal management strategy and target discharge strategy are jointly determined based on the current battery temperature and the predicted battery temperature for the preset future period. Thermal management instructions and discharge instructions are generated according to these two strategies and sent to the thermal management system and the battery management system, respectively. The thermal management system and the battery management system execute corresponding actions according to the instructions to achieve cooperative thermal management and discharge of the vehicle's power battery.

[0063] During the collaborative control process, the battery status, grid status, and discharge process are monitored in real time. The discharge power is dynamically adjusted based on the feedback data to ensure that the grid and user objectives are optimized as much as possible while meeting thermal management requirements, thereby achieving closed-loop dynamic optimization.

[0064] In the above-mentioned coordinated control method for discharge and thermal management, when the target vehicle is allowed to discharge, a predicted thermal management strategy is determined based on sensing data; based on the sensing data and the predicted thermal management strategy, the discharge strategy of the target vehicle is predicted to obtain a predicted discharge strategy; the target vehicle is controlled to discharge according to the predicted discharge strategy, and during the discharge process, the vehicle battery temperature at a preset future time is predicted based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle to obtain a predicted battery temperature; and the target vehicle is subjected to coordinated control of discharge and thermal management based on the current battery temperature and the predicted battery temperature. As can be seen, this application first determines a predictive thermal management strategy while allowing the target vehicle to discharge, enabling advance prediction of thermal management needs during the discharge process. Secondly, based on sensing data and the predicted thermal management strategy, a predictive discharge strategy is derived, taking into account thermal management needs during discharge, thus avoiding conflicts between the discharge strategy and thermal management and improving discharge safety. Finally, during the discharge process controlled by the predictive discharge strategy, the vehicle's battery temperature at a preset future time is predicted based on the current ambient temperature, the predicted discharge strategy, and the target vehicle's current battery temperature. Based on the current and predicted battery temperatures, coordinated control of discharge and thermal management of the target vehicle is implemented, further reducing or avoiding the impact of the large amount of heat generated during discharge on battery life and safety. Therefore, this application can achieve V2G discharge and optimize grid operation while ensuring battery life and discharge safety.

[0065] In one exemplary embodiment, such as Figure 6 As shown, step 204 includes steps 601 to 603. Wherein:

[0066] Step 601: Determine the target thermal management strategy based on the current battery temperature and the predicted battery temperature.

[0067] The current battery temperature includes multiple measured battery temperatures.

[0068] For example, during the process of controlling the vehicle battery to discharge according to the predicted discharge strategy, the cooperative control module 102 determines the average temperature of multiple measured battery temperatures and compares the average temperature with the predicted battery temperature. In one possible implementation, if the predicted battery temperature is greater than the average temperature, it is determined that a cooling mode needs to be activated, i.e., the target thermal management strategy is a cooling mode; if the predicted battery temperature is less than or equal to the average temperature, it is determined that a heating mode needs to be activated, i.e., the target thermal management strategy is a heating mode. In another possible implementation, if the predicted battery temperature is greater than the average temperature, and the difference between the predicted battery temperature and the average temperature reaches the upper limit of the safety range, it is determined that a cooling mode needs to be activated, i.e., the target thermal management strategy is a cooling mode; if the predicted battery temperature is less than or equal to the average temperature, and the difference between the average temperature and the predicted battery temperature is lower than the lower limit of the safety range, it is determined that a heating mode needs to be activated, i.e., the target thermal management strategy is a heating mode; if the difference between the predicted temperature and the average temperature is within the safety range, it is determined that neither cooling nor heating needs to be activated, i.e., the target thermal management strategy is a standby mode.

[0069] Step 602: Determine the target discharge strategy based on the sensing data and the target thermal management strategy.

[0070] For example, the cooperative control module 102 determines the target thermal management power consumption corresponding to the target thermal management strategy, and then uses the target thermal management power consumption as a constraint to determine the discharge strategy. Based on this constraint, grid data, user data, vehicle data, and the target thermal management strategy, the predicted discharge strategy is adjusted to obtain the target discharge strategy. The target discharge strategy includes a target discharge power and a discharge start time. For example, when the target thermal management strategy is in cooling mode, if the target thermal management power consumption is higher than the preset power consumption, the discharge power of the predicted discharge strategy can be reduced to obtain the target discharge power; if the target thermal management power consumption is lower than the preset power consumption, the discharge power of the predicted discharge strategy can be increased to obtain the target discharge power.

[0071] Step 603: Based on the target thermal management strategy and the target discharge strategy, perform coordinated control of discharge and thermal management on the target vehicle.

[0072] For example, the collaborative control module 102 generates a thermal management instruction based on the target thermal management strategy and sends it to the thermal management system; simultaneously, it generates a discharge instruction based on the target discharge strategy and sends it to the battery management system. The thermal management system and the battery management system execute corresponding actions according to the instructions, so that the power battery performs V2G discharge while performing thermal management. The discharge action and the thermal management action are executed synchronously within the same discharge cycle.

[0073] Therefore, in this embodiment, the target thermal management strategy is determined based on the current battery temperature and the predicted battery temperature. This allows for advance decision-making on the thermal management strategy. The target discharge strategy is then determined in conjunction with the target thermal management strategy, ensuring that the thermal management strategy and the discharge strategy are compatible with each other. This enables V2G discharge while ensuring the lifespan and safety of the power battery.

[0074] In an exemplary embodiment, the target thermal management strategy includes a target thermal management mode and a target thermal management level under the target thermal management mode. Step 601 includes: determining the target thermal management mode based on the current battery temperature; and determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature.

[0075] The target thermal management mode includes cooling mode and heating mode. The current battery temperature includes multiple measured battery temperatures. Different thermal management levels have different thermal management parameters, such as cooling / heating medium flow rate and inlet water temperature.

[0076] For example, in one possible implementation, the target thermal management mode is determined to be either a heating mode or a cooling mode based on the average temperature of multiple measured battery temperatures, and / or the temperature difference between the highest and lowest temperatures among the multiple measured battery temperatures. In heating mode, the heating mode level is determined based on the lowest temperature and the predicted battery temperature. Alternatively, in cooling mode, the cooling mode level is determined based on the highest temperature and the predicted battery temperature.

[0077] In another possible implementation, when the highest temperature is above the first cooling temperature threshold T up Cooling mode is activated when the battery's highest temperature is below the first cooling temperature threshold T1; otherwise, the cooling mode is deactivated. up It does not enter cooling mode and remains in standby mode; when the lowest temperature is below the first heating temperature threshold T... low Heating is activated when the minimum temperature is above the second cooling temperature threshold T2, and then deactivated. If the minimum temperature is between T2 and T... low It does not enter heating mode and is in standby mode at times. The heating and cooling strategies are also divided into different levels. Based on the different levels, the flow rate and temperature of the cooling medium in the cooling circuit can be adjusted accordingly to reduce energy consumption. Here, different thermal management levels are obtained by predicting the battery temperature N minutes later based on the current battery temperature, V2G discharge power, ambient temperature, and the current thermal management strategy level. The predicted thermal management level is then adjusted based on the change in the power battery temperature N minutes later.

[0078] Therefore, this embodiment determines the target thermal management mode based on the current battery temperature, which can ensure the effectiveness of the target thermal management mode. Furthermore, by combining the current battery temperature and the predicted battery temperature, it determines the target thermal management level, which can ensure the reliability of the target thermal management level.

[0079] In one exemplary embodiment, when determining the target thermal management level, the current battery temperature is the highest among multiple measured battery temperatures. Determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature includes: if the target thermal management mode is a cooling mode, determining the temperature rise rate based on the highest temperature and the predicted battery temperature; and determining the cooling level based on either the temperature rise rate or the highest temperature. Specifically:

[0080] If the rate of temperature rise is greater than the first preset rate a1 and less than or equal to the second preset rate a2, or the highest temperature is greater than the first preset temperature b1 and less than or equal to the second preset temperature b2, the preset first cooling level will be determined as the target thermal management level.

[0081] If the temperature rise rate is greater than the second preset rate a2 and less than or equal to the third preset rate a3, or the maximum temperature is greater than the second preset temperature b2 and less than or equal to the third preset temperature b3, the preset second cooling level will be determined as the target thermal management level.

[0082] If the rate of temperature rise is greater than the third preset rate a3, or the maximum temperature is greater than the third preset temperature b3, the preset third cooling level will be determined as the target thermal management level.

[0083] Specifically, in the first, second, and third refrigeration levels, the flow rate of the cooling medium in the vehicle's thermal management system increases sequentially, while the target inlet water temperature decreases sequentially. a1, a2, and a3 increase sequentially, as do b1, b2, and b3.

[0084] For example, such as Figure 7 As shown, taking the temperature rise rate as an example, first, it is determined whether the temperature rise rate is greater than a3. If yes, the cooling level is determined to be the third cooling level. If not, it is determined whether the temperature rise rate is less than or equal to a3 and greater than a2. If yes, the cooling level is determined to be the second cooling level. If not, it is determined whether the temperature rise rate is less than or equal to a2 and greater than a1. If yes, the cooling level is determined to be the first cooling level. Taking the highest temperature as an example, first, it is determined whether the highest temperature is greater than b3. If yes, the cooling level is determined to be the third cooling level. If not, it is determined whether the highest temperature is less than or equal to b3 and greater than b2. If yes, the cooling level is determined to be the second cooling level. If not, it is determined whether the highest temperature is less than or equal to b2 and greater than b1. If yes, the cooling level is determined to be the first cooling level.

[0085] It should be noted that if the temperature rise rate determination conflicts with the maximum temperature determination, the temperature rise rate takes precedence over the temperature determination. Within each cooling level, if either the temperature rise rate or the maximum temperature reaches the temperature requirements of another cooling level, the system will switch to that other cooling level.

[0086] Therefore, in this embodiment, the temperature rise rate is determined based on the measured maximum temperature and the predicted temperature of the battery in cooling mode, and the cooling level is determined based on the temperature rise rate or the maximum temperature, which can ensure the reliability of the cooling level.

[0087] In one exemplary embodiment, when determining the target thermal management level, the current battery temperature is the lowest among multiple measured battery temperatures. The target thermal management level is determined based on the target thermal management mode, the current battery temperature, and the predicted battery temperature, including:

[0088] When the target thermal management mode is heating mode, the target temperature difference is determined based on the minimum temperature and the predicted battery temperature.

[0089] If the target temperature difference is less than the first preset temperature difference c1, or the minimum temperature is less than or equal to the fourth preset temperature d1 and greater than the fifth preset temperature d2, the preset first heating level will be determined as the target thermal management level.

[0090] If the target temperature difference is greater than or equal to the first preset temperature difference c1 and less than the second preset temperature difference c2, or if the minimum temperature is less than or equal to the fifth preset temperature d2 and greater than the sixth preset temperature d3, the preset second heating level will be determined as the target thermal management level.

[0091] If the target temperature difference is greater than or equal to the second preset temperature difference c2 and less than the third preset temperature difference c3, or if the minimum temperature is less than or equal to the sixth preset temperature d3, the preset third heating level will be determined as the target thermal management level.

[0092] Specifically, under the first, second, and third heating levels, the flow rate of the heating medium in the vehicle's thermal management system increases sequentially, and the target inlet water temperature also increases sequentially. c1, c2, and c3 increase sequentially, while d1, d2, and d3 decrease sequentially.

[0093] For example, such as Figure 8As shown, taking the target temperature difference as an example, firstly, it is determined whether the target temperature difference is greater than or equal to c2 and less than c3. If yes, the heating level is determined to be the third heating level. If not, it is determined whether the target temperature difference is greater than or equal to c1 and less than c2. If yes, the heating level is determined to be the second heating level. If not, it is determined whether the target temperature difference is less than c1. If yes, the heating level is determined to be the first heating level. Taking the lowest temperature as an example, firstly, it is determined whether the lowest temperature is less than or equal to d3. If yes, the heating level is determined to be the third heating level. If not, it is determined whether the highest temperature is less than or equal to d2 and greater than d3. If yes, the heating level is determined to be the second heating level. If not, it is determined whether the highest temperature is less than or equal to d1 and greater than d2. If yes, the heating level is determined to be the first heating level.

[0094] It should be noted that if the target temperature difference determination conflicts with the minimum temperature determination, the target temperature difference takes precedence over the temperature determination. Within each heating level, if either the target temperature difference or the minimum temperature reaches the temperature conditions of other heating levels, the system switches to that other heating level.

[0095] Therefore, in this embodiment, the target temperature difference is determined based on the measured minimum temperature and the predicted temperature of the battery in the heating mode, and the heating level is determined based on the target temperature difference or the minimum temperature, which can ensure the reliability of the heating level.

[0096] In an exemplary embodiment, the method further includes: during the coordinated control process, determining the current battery temperature difference based on the highest and lowest temperatures among multiple measured battery temperatures; if the current battery temperature difference is greater than a preset self-circulation activation temperature difference, exiting the target thermal management strategy and controlling the vehicle battery to enter self-circulation mode; if the current battery temperature difference is less than a preset self-circulation exit temperature difference, controlling the vehicle battery to exit self-circulation mode and re-executing the step of determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature; wherein the preset self-circulation exit temperature difference is less than the preset self-circulation activation temperature difference; or, during the coordinated control process, exiting the target thermal management strategy when the current battery temperature reaches a thermal management temperature threshold.

[0097] The preset self-circulation start temperature difference and preset self-circulation exit temperature difference refer to the battery temperature differences that are preset to control the start and stop of the vehicle battery's self-circulation mode. The specific values ​​can be determined based on actual needs and historical experience; this application embodiment does not impose any restrictions on this. The preset self-circulation start temperature difference is the battery temperature difference value that triggers the self-circulation mode. When the current battery temperature difference between the vehicle battery's highest and lowest temperatures exceeds this value, it is determined that the battery temperature difference is too large, and the thermal management strategy needs to be exited and self-circulation forced to equalize the temperature. The preset self-circulation exit temperature difference is the battery temperature difference value that terminates the self-circulation mode. During the self-circulation process, when the current battery temperature difference decreases and falls below this value, it indicates that the battery temperature has been equalized, and therefore the self-circulation mode is exited and the thermal management strategy is restored.

[0098] The thermal management temperature threshold refers to a pre-set critical battery temperature value used to determine whether thermal management has reached its target (i.e., whether the current battery temperature has reached a certain target). The specific value can be determined based on actual needs, historical experience, etc., and this application embodiment does not impose any limitations on this. During the coordinated control process, as the vehicle battery undergoes thermal management (i.e., cooling or heating), when the current battery temperature rises or falls back to the thermal management temperature threshold, it indicates that the current battery temperature has been controlled within a suitable or target range through thermal management. This avoids energy waste caused by excessive cooling or heating, and thermal management is then discontinued.

[0099] It should be noted that the preset self-circulation start temperature difference, preset self-circulation stop temperature difference, and thermal management temperature threshold can be the same or different under different thermal management modes (cooling mode or heating mode). The following examples illustrate these differences:

[0100] For example, in the coordinated control process of discharge and thermal management, the current battery temperature difference is obtained by calculating the difference between the battery's highest and lowest temperatures. (Refer to...) Figure 7 If the thermal management mode is cooling mode, and the current battery temperature difference is greater than the first preset self-circulation start temperature difference g1, the cooling mode is exited and the self-circulation mode is entered until the current battery temperature difference is less than the first preset self-circulation exit temperature difference h1. Then, the self-circulation mode is exited and step 601 is executed again. Alternatively, in the coordinated control process of discharge and thermal management, if the thermal management mode is cooling mode, the cooling mode is exited when the highest temperature drops below the first thermal management temperature threshold f1. (Refer to...) Figure 8 If the thermal management mode is heating mode, and the current battery temperature difference is greater than the second preset self-circulation start temperature difference g2, the heating mode is exited and the self-circulation mode is entered until the current battery temperature difference is less than the second preset self-circulation exit temperature difference h2. Then, the self-circulation mode is exited and step 601 is executed again. Alternatively, in the coordinated control process of discharge and thermal management, if the thermal management mode is heating mode, the heating mode is exited when the minimum temperature rises to a level greater than or equal to the second thermal management temperature threshold f2.

[0101] Among them, g1 and g2 are different, h1 and h2 are different, and f1 and f2 are different.

[0102] Therefore, this embodiment, through a temperature difference-triggered self-circulation mode and a temperature-triggered thermal management exit mechanism, can balance the battery temperature with low-power self-circulation when the temperature difference exceeds the standard, resume active thermal management when the temperature difference drops, and completely exit thermal management when the temperature is safe to avoid ineffective energy consumption. Thus, while ensuring the safety of battery temperature, it reduces the thermal management power consumption during V2G discharge.

[0103] In an exemplary embodiment, the predicted discharge strategy includes discharge power and discharge start time. Step 203 includes: inputting the sensing data and the predicted thermal management strategy into a pre-built multi-objective optimization model to perform multi-objective optimization on the discharge strategy to obtain the discharge power; the multi-objective optimization model aims to minimize the peak-valley difference of grid load, maximize user benefits, and minimize battery degradation; and determining the discharge start time based on the sensing data, the predicted thermal management strategy, and the discharge power.

[0104] Among them, the peak-valley difference of grid load refers to the difference between the maximum and minimum values ​​of the total grid load during the vehicle discharge cycle. The larger the value, the greater the fluctuation of grid load; the smaller the value, the more stable the grid load fluctuation. User revenue is the economic benefit obtained by the vehicle owner from V2G discharge, which can be obtained by calculating the difference between discharge revenue and charging cost. Battery degradation refers to the irreversible decrease (e.g., percentage decrease) in the maximum usable capacity or allowable output power of the vehicle battery caused by V2G discharge and thermal management. It is usually quantified by the decrease in the state of battery health (SOH), which can be calculated based on the parameters corresponding to the discharge strategy and thermal management strategy. Specifically, a semi-empirical lifetime model based on the Arrhenius equation can be used to calculate battery degradation.

[0105] It should be noted that, to ensure maximum user benefit from V2G while minimizing battery degradation and meeting user needs under all weather conditions (different humidity, temperature, etc.), road conditions, and battery states (SOC, SOH, etc.), this embodiment uses real user driving data and deep learning to study user driving habits. Based on user choices, it maximizes V2G benefits for users while ensuring battery health. First, a multi-objective optimization model is constructed using deep reinforcement learning algorithms to address the lack of multi-objective collaborative optimization models in existing V2G technologies. The multi-objective optimization model's environment includes dynamic sensing data from multiple dimensions, such as real-time grid load conditions, user travel needs, and battery health. The model aims to simultaneously optimize grid load differences, user benefits, and battery health by balancing minimizing grid load peak-valley differences, maximizing user benefits, and minimizing battery degradation. Minimizing grid load peak-valley differences helps stabilize grid operation and smooths the load curve; maximizing user benefits involves rationally scheduling charging and discharging times and power, leveraging electricity price differences to allow users to gain more economic benefits; minimizing battery degradation extends battery life and reduces user battery replacement costs. The model input includes multi-dimensional sensing data such as real-time grid load data, user travel plans, current battery charge, and health status. Through deep reinforcement learning algorithms, it continuously learns and adjusts its strategies to output the optimal predicted discharge power strategy.

[0106] For example, a multi-objective optimization model is first obtained through reinforcement learning training. Then, the sensing data and the thermal management power consumption corresponding to the predicted thermal management strategy are input into the multi-objective optimization model to perform multi-objective optimization on the discharge strategy for a preset future period. This yields the predicted discharge power that achieves the optimal balance between grid demand, user benefits, and battery degradation. The discharge start time is then determined based on the sensing data, the thermal management power consumption corresponding to the predicted thermal management strategy, and the discharge power. This allows the discharge behavior to fully utilize the peak-valley electricity price difference, thereby maximizing the comprehensive economic benefits of V2G discharge while ensuring battery health. This achieves joint optimization of the electricity, heat, and grid.

[0107] Therefore, this embodiment aims to simultaneously optimize the grid load, user benefits, and battery health status to obtain a predictive discharge strategy. Under this predictive discharge strategy, the optimal balance between the grid, users, and batteries can be achieved, thus improving the reliability of the predictive discharge strategy.

[0108] In an exemplary embodiment, the method further includes: during the collaborative control process, acquiring the measured battery temperature at preset time intervals; determining the temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time; and if the temperature deviation exceeds a preset deviation threshold, using a rolling time-domain optimization method to return to the step of determining the predicted thermal management strategy based on the sensing data.

[0109] For example, during the discharge process, the measured battery temperature is collected at preset time intervals. If the temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time (predicted before the preset time interval) exceeds a preset deviation threshold, the Receding Horizon Optimization (RTO) method is triggered to readjust the predicted thermal management strategy and the predicted discharge strategy, and then the subsequent steps are executed.

[0110] Specifically, real-time operational data is collected periodically (e.g., every 15 minutes), including battery status (SOC, SOH, temperature), grid status (real-time electricity price, load), and changes in user demand. This real-time data serves as feedback to update the model state. A rolling window mechanism is used: the optimization timeframe is not fixed but rather acts like a window, continuously rolling forward over time. For example, the current optimization focuses on the discharge strategy for the next hour, while the next optimization cycle focuses on the strategy for the next hour, and so on. Each optimization executes only the first few control commands within the current window (e.g., the charge / discharge power for the current hour), and subsequent control commands are recalculated in the next optimization cycle based on the latest system state.

[0111] like Figure 9As shown, the measured battery temperature is continuously compared with the predicted battery temperature. If the deviation between the two exceeds a preset threshold (e.g., 10%), the rolling time-domain optimization (RTO) mechanism is immediately triggered to adjust the thermal management strategy and discharge strategy. That is, it will not wait until the end of the original planned optimization cycle to make adjustments, but can quickly respond to emergencies, such as large errors in grid load forecasting or users temporarily changing their travel plans.

[0112] Therefore, this embodiment ensures that the discharge power and thermal management strategy are always adapted through dynamic correction. When the prediction is not accurate enough, the discharge power and thermal management strategy can be adjusted immediately to ensure that the battery always operates within a safe temperature range.

[0113] The collaborative control method of this application is described below through a detailed embodiment.

[0114] The method for coordinated control of discharge and thermal management includes the following steps:

[0115] S1, under the condition that the target vehicle is allowed to discharge, acquire sensing data and perform cleaning, normalization and vectorization processing on the sensing data, etc. The sensing data includes at least one of power grid data, user data and vehicle data.

[0116] S2, the sensing data and predicted thermal management strategy are input into the pre-built multi-objective optimization model to perform multi-objective optimization on the discharge strategy and obtain the discharge power; the multi-objective optimization model aims to minimize the peak-valley difference of grid load, maximize user benefits and minimize battery degradation;

[0117] S3, determine the discharge start time based on sensing data, predicted thermal management strategy, and discharge power; the predicted discharge strategy includes discharge power and discharge start time;

[0118] S4, control the target vehicle to discharge according to the predicted discharge strategy, and during the discharge process, predict the vehicle battery temperature at a preset future time based on the current ambient temperature, the predicted discharge strategy and the current battery temperature of the target vehicle, and obtain the predicted battery temperature.

[0119] S5 determines the target thermal management mode based on the current battery temperature;

[0120] S6, determine the target thermal management level based on the target thermal management mode, current battery temperature, and predicted battery temperature;

[0121] S7, determine the target discharge strategy based on the sensing data and the target thermal management strategy;

[0122] S8, based on the target thermal management strategy and the target discharge strategy, performs coordinated control of discharge and thermal management on the target vehicle;

[0123] S9 acquires the measured battery temperature at preset time intervals during the collaborative control process;

[0124] S10, determine the temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time, and if the temperature deviation exceeds the preset deviation threshold, use the rolling time domain optimization method and return to execute S1;

[0125] S11, during the collaborative control process, the current battery temperature difference is determined based on the highest and lowest temperatures among multiple measured battery temperatures. If the current battery temperature difference is greater than the preset self-circulation start temperature difference, the target thermal management strategy is exited and the vehicle battery is controlled to enter the self-circulation mode.

[0126] S12, if the current battery temperature difference is less than the preset self-circulation exit temperature difference, control the vehicle battery to exit the self-circulation mode and return to S5; wherein, the preset self-circulation exit temperature difference is less than the preset self-circulation start temperature difference.

[0127] S13, during the collaborative control process, if the current battery temperature reaches the thermal management temperature threshold, exit the target thermal management strategy.

[0128] In summary, the embodiments of this application, through multi-objective optimization, enable the discharge strategy to meet user needs, grid load, and battery status, achieving optimal balance among these three factors. By linking discharge with thermal management strategies, proactive discharge control based on temperature prediction can improve system safety and battery life. It exhibits strong dynamic adaptability: through real-time data feedback and rolling optimization, it can quickly respond to changes in grid and user demands, demonstrating strong robustness. Furthermore, it offers significant economic benefits: by optimizing discharge time and power, it can increase user V2G discharge revenue.

[0129] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0130] Based on the same inventive concept, this application also provides a discharge and thermal management coordinated control device for implementing the discharge and thermal management coordinated control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more discharge and thermal management coordinated control device embodiments provided below can be found in the limitations of the discharge and thermal management coordinated control method described above, and will not be repeated here.

[0131] In one exemplary embodiment, such as Figure 10 As shown, a discharge and thermal management coordinated control device is provided, comprising: a first prediction module 1001, a second prediction module 1002, a third prediction module 1003, and a first control module 1004, wherein:

[0132] The first prediction module 1001 is used to determine a predictive thermal management strategy based on sensing data, provided that the target vehicle is allowed to discharge; wherein the sensing data includes at least one of grid data, user data, and vehicle data.

[0133] The second prediction module 1002 is used to predict the discharge strategy of the target vehicle based on the sensing data and the predicted thermal management strategy, and obtain the predicted discharge strategy.

[0134] The third prediction module 1003 is used to control the target vehicle to discharge according to the predicted discharge strategy, and during the discharge process, it predicts the vehicle battery temperature at a preset future time based on the current ambient temperature, the predicted discharge strategy and the current battery temperature of the target vehicle, so as to obtain the predicted battery temperature.

[0135] The first control module 1004 is used to perform coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature.

[0136] In one embodiment, the first control module 1004 includes:

[0137] The first determining unit is used to determine the target thermal management strategy based on the current battery temperature and the predicted battery temperature.

[0138] The second determining unit is used to determine the target discharge strategy based on the sensing data and the target thermal management strategy;

[0139] The control unit is used to perform coordinated control of discharge and thermal management of the target vehicle according to the target thermal management strategy and the target discharge strategy.

[0140] In one embodiment, the target thermal management strategy includes a target thermal management mode and a target thermal management level under the target thermal management mode; the first determining unit is specifically used to: determine the target thermal management mode based on the current battery temperature; and determine the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature.

[0141] In one embodiment, the current battery temperature is the highest among multiple measured battery temperatures; the first determining unit is specifically used to determine the target thermal management level as follows:

[0142] When the target thermal management mode is cooling mode, the temperature rise rate is determined based on the highest temperature and the predicted battery temperature.

[0143] If the temperature rise rate is greater than the first preset rate and less than or equal to the second preset rate, or if the maximum temperature is greater than the first preset temperature and less than or equal to the second preset temperature, the preset first cooling level will be determined as the target thermal management level.

[0144] If the temperature rise rate is greater than the second preset rate and less than or equal to the third preset rate, or if the maximum temperature is greater than the second preset temperature and less than or equal to the third preset temperature, the preset second cooling level will be determined as the target thermal management level.

[0145] If the rate of temperature rise is greater than the third preset rate, or the maximum temperature is greater than the third preset temperature, the preset third cooling level will be determined as the target thermal management level.

[0146] Among them, under the first, second and third refrigeration levels, the flow rate of the cooling medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature decreases sequentially.

[0147] In one embodiment, the current battery temperature is the lowest among multiple measured battery temperatures; the first determining unit is specifically used to determine the target thermal management level as follows:

[0148] When the target thermal management mode is heating mode, the target temperature difference is determined based on the minimum temperature and the predicted battery temperature.

[0149] If the target temperature difference is less than the first preset temperature difference, or if the minimum temperature is less than or equal to the fourth preset temperature and greater than the fifth preset temperature, the preset first heating level will be determined as the target thermal management level.

[0150] If the target temperature difference is greater than or equal to the first preset temperature difference and less than the second preset temperature difference, or if the minimum temperature is less than or equal to the fifth preset temperature and greater than the sixth preset temperature, the preset second heating level will be determined as the target thermal management level.

[0151] If the target temperature difference is greater than or equal to the second preset temperature difference and less than the third preset temperature difference, or if the minimum temperature is less than or equal to the sixth preset temperature, the preset third heating level will be determined as the target thermal management level.

[0152] Among them, under the first heating level, the second heating level and the third heating level, the flow rate of the heating medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature also increases sequentially.

[0153] In one embodiment, the apparatus further includes:

[0154] The second control module is used to determine the current battery temperature difference based on the highest and lowest temperatures among multiple measured battery temperatures during the collaborative control process. If the current battery temperature difference is greater than the preset self-circulation start temperature difference, the target thermal management strategy is exited and the vehicle battery is controlled to enter the self-circulation mode.

[0155] The third control module is used to control the vehicle battery to exit the self-circulation mode when the current battery temperature difference is less than the preset self-circulation exit temperature difference, and to re-execute the step of determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature; wherein, the preset self-circulation exit temperature difference is less than the preset self-circulation start temperature difference.

[0156] Alternatively, the fourth control module is used to exit the target thermal management strategy when the current battery temperature reaches the thermal management temperature threshold during the collaborative control process.

[0157] In one embodiment, the predictive discharge strategy includes discharge power and discharge start time;

[0158] The second prediction module 1002 is specifically used to: input the sensing data and the predicted thermal management strategy into a pre-built multi-objective optimization model, perform multi-objective optimization on the discharge strategy, and obtain the discharge power; the multi-objective optimization model aims to minimize the peak-valley difference of the grid load, maximize user benefits, and minimize battery degradation; and determine the discharge start time based on the sensing data, the predicted thermal management strategy, and the discharge power.

[0159] In one embodiment, the device further includes: an acquisition module, configured to acquire the measured battery temperature at preset time intervals during the collaborative control process; and an optimization module, configured to determine the temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time, and, if the temperature deviation exceeds a preset deviation threshold, to return to the step of determining the predicted thermal management strategy based on the sensing data using a rolling time-domain optimization method.

[0160] Each module in the aforementioned discharge and thermal management coordinated control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0161] In one exemplary embodiment, a discharge and thermal management coordinated control system is provided, referring to... Figure 1 The system includes a data acquisition module 101 and a collaborative control module 102. The data acquisition module 101 is used to acquire sensing data; the collaborative control module 102 is communicatively connected to the data acquisition module 101, and the collaborative control module 101 is used to execute the discharge and thermal management collaborative control method of the above embodiment.

[0162] In one exemplary embodiment, a vehicle is provided that includes the discharge and thermal management coordinated control system described above.

[0163] In one exemplary embodiment, an in-vehicle device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement coordinated control of discharge and thermal management.

[0164] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 11 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores discharge and thermal management coordinated control data. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a discharge and thermal management coordinated control method.

[0165] Those skilled in the art will understand that Figure 11The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0166] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements a method for coordinated control of discharge and thermal management.

[0167] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements a method for coordinated control of discharge and thermal management.

[0168] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0169] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0170] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for coordinated control of discharge and thermal management, characterized in that, The method includes: If the target vehicle is allowed to discharge, a predictive thermal management strategy is determined based on sensing data; wherein the sensing data includes at least one of grid data, user data, and vehicle data. Based on the sensing data and the predicted thermal management strategy, the discharge strategy of the target vehicle is predicted to obtain the predicted discharge strategy. The target vehicle is controlled to discharge according to the predicted discharge strategy. During the discharge process, the vehicle battery temperature at a preset future time is predicted based on the current ambient temperature, the predicted discharge strategy, and the current battery temperature of the target vehicle, so as to obtain the predicted battery temperature. Based on the current battery temperature and the predicted battery temperature, the target vehicle is subjected to coordinated control of discharge and thermal management.

2. The method according to claim 1, characterized in that, The coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature includes: Based on the current battery temperature and the predicted battery temperature, determine the target thermal management strategy; Based on the sensed data and the target thermal management strategy, a target discharge strategy is determined; Based on the target thermal management strategy and the target discharge strategy, the target vehicle is subjected to coordinated control of discharge and thermal management.

3. The method according to claim 2, characterized in that, The target thermal management strategy includes a target thermal management mode and a target thermal management level under the target thermal management mode; The step of determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature includes: Determine the target thermal management mode based on the current battery temperature; The target thermal management level is determined based on the target thermal management mode, the current battery temperature, and the predicted battery temperature.

4. The method according to claim 3, characterized in that, The current battery temperature is the highest among multiple measured battery temperatures. The step of determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature includes: When the target thermal management mode is cooling mode, the temperature rise rate is determined based on the highest temperature and the predicted battery temperature. If the temperature rise rate is greater than the first preset rate and less than or equal to the second preset rate, or if the highest temperature is greater than the first preset temperature and less than or equal to the second preset temperature, the preset first cooling level is determined as the target thermal management level. If the temperature rise rate is greater than the second preset rate and less than or equal to the third preset rate, or if the highest temperature is greater than the second preset temperature and less than or equal to the third preset temperature, the preset second cooling level is determined as the target thermal management level. If the temperature rise rate is greater than the third preset rate, or the maximum temperature is greater than the third preset temperature, the preset third cooling level will be determined as the target thermal management level. Specifically, under the first refrigeration level, the second refrigeration level, and the third refrigeration level, the flow rate of the cooling medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature decreases sequentially.

5. The method according to claim 3, characterized in that, The current battery temperature is the lowest among multiple measured battery temperatures. Determining the target thermal management level based on the target thermal management mode, the current battery temperature, and the predicted battery temperature includes: When the target thermal management mode is heating mode, the target temperature difference is determined based on the minimum temperature and the predicted battery temperature; If the target temperature difference is less than the first preset temperature difference, or if the minimum temperature is less than or equal to the fourth preset temperature and greater than the fifth preset temperature, the preset first heating level is determined as the target thermal management level. If the target temperature difference is greater than or equal to the first preset temperature difference and less than the second preset temperature difference, or if the minimum temperature is less than or equal to the fifth preset temperature and greater than the sixth preset temperature, the preset second heating level is determined as the target thermal management level. If the target temperature difference is greater than or equal to the second preset temperature difference and less than the third preset temperature difference, or if the minimum temperature is less than or equal to the sixth preset temperature, the preset third heating level is determined as the target thermal management level. Specifically, under the first heating level, the second heating level, and the third heating level, the flow rate of the heating medium in the vehicle thermal management system increases sequentially, and the target inlet water temperature increases sequentially.

6. The method according to claim 2, characterized in that, The method further includes: During the collaborative control process, the current battery temperature difference is determined based on the highest and lowest temperatures among multiple measured battery temperatures. If the current battery temperature difference is greater than the preset self-circulation activation temperature difference, the target thermal management strategy is exited, and the vehicle battery is controlled to enter the self-circulation mode. If the current battery temperature difference is less than the preset self-circulation exit temperature difference, the vehicle battery is controlled to exit the self-circulation mode, and the step of determining the target thermal management strategy based on the current battery temperature and the predicted battery temperature is re-executed; wherein, the preset self-circulation exit temperature difference is less than the preset self-circulation start temperature difference; Alternatively, during the collaborative control process, if the current battery temperature reaches the thermal management temperature threshold, the target thermal management strategy may be terminated.

7. The method according to any one of claims 1-6, characterized in that, The predictive discharge strategy includes discharge power and discharge start time; The step of predicting the discharge strategy of the target vehicle based on the sensed data and the predicted thermal management strategy to obtain the predicted discharge strategy includes: The sensed data and the predicted thermal management strategy are input into a pre-built multi-objective optimization model to perform multi-objective optimization on the discharge strategy and obtain the discharge power. The multi-objective optimization model aims to minimize the peak-valley difference of the grid load, maximize user benefits, and minimize battery degradation. The discharge start time is determined based on the sensed data, the predicted thermal management strategy, and the discharge power.

8. The method according to any one of claims 1-6, characterized in that, The method further includes: During the coordinated control process, the measured battery temperature is acquired at preset time intervals; The temperature deviation between the measured battery temperature and the predicted battery temperature at the corresponding time is determined. If the temperature deviation exceeds a preset deviation threshold, a rolling time-domain optimization method is used to return to the step of determining the predicted thermal management strategy based on the sensing data.

9. A discharge and thermal management coordinated control device, characterized in that, The device includes: The first prediction module is used to determine a predictive thermal management strategy based on sensing data, provided that the target vehicle is allowed to discharge; wherein the sensing data includes at least one of power grid data, user data, and vehicle data. The second prediction module is used to predict the discharge strategy of the target vehicle based on the sensing data and the predicted thermal management strategy, so as to obtain the predicted discharge strategy. The third prediction module is used to control the target vehicle to discharge according to the prediction discharge strategy, and during the discharge process, it predicts the vehicle battery temperature at a preset future time based on the current ambient temperature, the prediction discharge strategy and the current battery temperature of the target vehicle, so as to obtain the predicted battery temperature. The first control module is used to perform coordinated control of discharge and thermal management of the target vehicle based on the current battery temperature and the predicted battery temperature.

10. A discharge and thermal management coordinated control system, characterized in that, The system includes: The data acquisition module is used to collect sensor data; A collaborative control module, which is communicatively connected to the data acquisition module, is used to execute the method as described in any one of claims 1 to 8.

11. A vehicle, characterized in that, This includes the discharge and thermal management coordinated control system as described in claim 10.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

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