Temperature adjusting method and device for energy storage equipment in vehicle, processor and vehicle

Abstract

The invention discloses a temperature adjusting method and device for energy storage equipment in a vehicle, a processor and the vehicle. The method comprises the steps that state information of energy storage equipment in a vehicle at the current moment is obtained, and the state information is used for representing the running state of the energy storage equipment at the current moment; based on the state information, the temperature of the energy storage equipment at the future moment is determined, and the future moment is later than the current moment; in response to the fact that the temperature is in the abnormal temperature range, a control strategy of the vehicle is determined, the operation state corresponding to the abnormal temperature range is an abnormal operation state, and the control strategy is used for representing a rule for controlling the vehicle to adjust the temperature; and at the future moment, the vehicle is controlled to adjust the temperature according to the control strategy, the adjusted temperature is in the normal temperature range, and the running state corresponding to the normal temperature range is the normal running state. The technical problem that the temperature adjustment accuracy of the energy storage equipment in the vehicle is low is solved.

Description

Technical Field

[0001] This invention relates to the field of vehicle battery technology, and more specifically, to a method, apparatus, processor, and vehicle for temperature regulation of energy storage devices in a vehicle. Background Technology

[0002] Among related technologies, battery temperature management is one of the key technologies to ensure battery performance and safety. Currently, the industry commonly uses air-cooling or liquid-cooling systems to regulate battery temperature, aiming to prevent the negative impact of high or low temperatures on the battery. However, these traditional temperature control methods have significant drawbacks: they mainly rely on real-time monitoring of battery temperature, immediately initiating cooling or heating measures once the temperature deviates from the ideal operating range. While this approach seems direct and effective, its long response time often prevents it from quickly correcting temperature anomalies, especially under conditions of rapid battery temperature changes. The system's lag in adjustment leads to low accuracy in battery temperature control, affecting battery performance stability and lifespan. Therefore, the technical problem of low temperature regulation accuracy in energy storage devices in vehicles remains.

[0003] There is currently no effective solution to the aforementioned technical problems. Summary of the Invention

[0004] This invention provides a method, apparatus, processor, and vehicle for temperature regulation of energy storage devices in vehicles, to at least solve the technical problem of low accuracy in temperature regulation of energy storage devices in vehicles.

[0005] According to one aspect of the present invention, a method for temperature regulation of an energy storage device in a vehicle is provided. The method includes: acquiring state information of the energy storage device in the vehicle at a current moment, wherein the state information represents the operating state of the energy storage device at the current moment; determining the temperature of the energy storage device at a future moment based on the state information, wherein the future moment is later than the current moment; determining a control strategy for the vehicle in response to the temperature being within an abnormal temperature range, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy represents a rule for controlling the vehicle to regulate the temperature; and controlling the vehicle to regulate the temperature according to the control strategy at a future moment, wherein the regulated temperature is within a normal temperature range, and the operating state corresponding to the normal temperature range is a normal operating state.

[0006] Optionally, in response to the temperature being in an abnormal temperature range, determining a control strategy for the vehicle includes: in response to the temperature being below the normal temperature range, determining that the temperature is in an abnormal temperature range, and determining the control strategy corresponding to the temperature below the normal temperature range as a first control strategy, wherein the first control strategy is used to represent a rule for controlling the vehicle to increase its temperature; in response to the temperature being above the normal temperature range, determining that the temperature is in an abnormal temperature range, and determining the control strategy corresponding to the temperature above the normal temperature range as a second control strategy, wherein the second control strategy is used to represent a rule for controlling the vehicle to decrease its temperature.

[0007] Optionally, the vehicle includes a cooling module and a heating module. In the future, according to a control strategy, the vehicle is controlled to adjust the temperature of the energy storage device, including: in the future, according to a first control strategy, controlling the heating module to perform a heating operation on the energy storage device to increase the temperature; and in the future, according to a second control strategy, controlling the cooling module to perform a cooling operation on the energy storage device to decrease the temperature.

[0008] Optionally, determining the temperature of the energy storage device at future times based on state information includes: inputting the state information into a dynamic thermal model, wherein the dynamic thermal model is trained using an artificial intelligence algorithm based on state information samples and temperature samples; using the dynamic thermal model, determining the temperature change trend of the energy storage device at future times based on the state information, wherein the temperature change trend is used to represent the temperature change over time; and determining the temperature of the energy storage device at future times based on the temperature change trend.

[0009] Optionally, the vehicle includes sensors, and the method further includes: using the sensors to acquire environmental information of the environment in which the energy storage device is located at the current moment, wherein the environmental information is used to influence the operating state; the vehicle includes a central processing unit, the central processing unit includes a dynamic thermal model, and using the dynamic thermal model, based on the state information, to determine the temperature change trend of the energy storage device at future moments, including: controlling the central processing unit to determine the temperature change trend based on the dynamic thermal model, the state information, and the environmental information.

[0010] Optionally, the status information of the energy storage device in the vehicle at the current moment can be obtained, including: obtaining status information in response to activating the vehicle's temperature regulation function.

[0011] Optionally, the vehicle includes an energy storage plate, a cooling module, and a heating module. The method further includes at least one of the following: in response to the vehicle being in a powered-off state or the light intensity of the environment in which the vehicle is located being lower than a light intensity threshold, providing electrical energy to the cooling module and the heating module using the energy storage plate; during the temperature adjustment process, displaying an adjustment status on a graphical user interface associated with the vehicle, wherein the adjustment status is used to indicate the operating status of the components in the vehicle during the temperature adjustment process; and triggering or stopping the temperature adjustment process in response to a control operation triggered by a target object of the vehicle on the graphical user interface.

[0012] According to another aspect of the present invention, a temperature regulation device for an energy storage device in a vehicle is also provided. The device may include: an acquisition unit, configured to acquire state information of the energy storage device in the vehicle at a current moment, wherein the state information represents the operating state of the energy storage device at the current moment; a first determination unit, configured to determine the temperature of the energy storage device at a future moment based on the state information, wherein the future moment is later than the current moment; a second determination unit, configured to determine a control strategy for the vehicle in response to the temperature being within an abnormal temperature range, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy represents the rules for controlling the vehicle to regulate the temperature; and an adjustment unit, configured to control the vehicle to adjust the temperature according to the control strategy at a future moment, wherein the adjusted temperature is within a normal temperature range, and the operating state corresponding to the normal temperature range is a normal operating state.

[0013] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the methods described in the embodiments of the present invention.

[0014] According to another aspect of the present invention, a processor is also provided. This processor is used to run a program, wherein the program executes the methods described above in the embodiments of the present invention during runtime.

[0015] According to another aspect of the present invention, an electronic device is also provided. The electronic device includes a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the methods described in the embodiments of the present invention.

[0016] According to another aspect of the present invention, a computer program product is also provided. This computer program product includes a computer program that, when executed by a processor, implements the methods described above in the embodiments of the present invention.

[0017] According to another aspect of the present invention, a vehicle is also provided. The vehicle includes a memory and a processor. The memory stores an executable program; the processor runs the program, which, when executed, implements the methods described in the embodiments of the present invention.

[0018] In this embodiment of the invention, the status information of the energy storage device in the vehicle at the current moment is obtained, wherein the status information represents the operating status of the energy storage device at the current moment; based on the status information, the temperature of the energy storage device at a future moment is determined, wherein the future moment is later than the current moment; in response to the temperature being in an abnormal temperature range, a control strategy for the vehicle is determined, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy represents the rules for controlling the vehicle to adjust the temperature; at the future moment, according to the control strategy, the vehicle is controlled to adjust the temperature, wherein the adjusted temperature is within the normal temperature range, and the operating state corresponding to the normal temperature range is a normal operating state. In other words, in this embodiment, by acquiring the status information of the energy storage device in real time, the battery temperature at a future moment can be predicted, and it can be determined in advance whether it may enter an abnormal temperature range. Once an anomaly is predicted, a control strategy is formulated and executed, such as adjusting the coolant flow rate or heating power, without waiting for the temperature to actually deviate from the ideal range. The innovation of the above method lies in transforming temperature regulation from a passive response to a prediction-based active management, which significantly improves the system's response speed and control accuracy. This effectively solves the problem of low accuracy in battery temperature regulation in existing technologies, ensures stable and efficient battery operation under various operating conditions, solves the technical problem of low accuracy in temperature regulation of energy storage devices in vehicles, and achieves the technical effect of improving the accuracy of temperature regulation of energy storage devices in vehicles. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0020] Figure 1 This is a flowchart of a temperature regulation method for an energy storage device in a vehicle according to an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of a control system for balancing battery temperature according to an embodiment of the present invention;

[0022] Figure 3 This is a flowchart of a method for controlling the temperature of a balanced battery according to an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram of a temperature regulation device for an energy storage device in a vehicle according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to an embodiment of the present invention, an embodiment of a method for addressing low temperature regulation accuracy of an energy storage device in a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] Figure 1 This is a flowchart illustrating a method for addressing low temperature regulation accuracy of an energy storage device in a vehicle according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0028] Step S102: Obtain the status information of the energy storage device in the vehicle at the current moment.

[0029] In the technical solution provided by step S102 of the present invention, the status information is used to represent the operating status of the energy storage device at the current moment.

[0030] Optionally, energy storage devices can refer to batteries or battery modules in electric vehicles. As the energy source for an electric vehicle, a battery consists of multiple cells connected in series and parallel to form a battery module, which in turn forms the entire battery system. Batteries or battery modules are responsible for storing and releasing electrical energy, and their performance and state directly affect the vehicle's range, power output, and safety performance.

[0031] Optionally, status information can refer to the collection of real-time operating parameters and health status of an energy storage device (such as a battery or battery module) at a specific point in time. This information may include, but is not limited to, battery temperature, voltage, current, state of charge (SOC), state of health (SOH), charge / discharge rate, and internal resistance. By continuously monitoring the above status information, the real-time operating status of the battery can be understood, and it can be determined whether it is within a safe and efficient operating range. For example, temperature is a key parameter in status information, directly related to the battery's chemical reaction rate and energy conversion efficiency; excessively high or low temperatures will adversely affect battery performance.

[0032] In this embodiment, the status information of the energy storage device in the vehicle at the current moment can be obtained.

[0033] Optionally, upon vehicle startup or battery management system startup, all sensors related to the energy storage device, including temperature, voltage, and current sensors, are activated first. To ensure data accuracy, each sensor is calibrated to eliminate potential errors or offsets. The sensors continuously collect real-time operating parameters of the energy storage device, such as temperature, voltage, and current, at a predetermined frequency (e.g., 10 times per second). The battery management system (BMS) aggregates the sensor data to form a set of current-moment status information, including but not limited to the cell's SOC, SOH, cell temperature distribution, system voltage, and total current.

[0034] Optionally, data analysis algorithms can be used to identify and remove outliers or noise from sensor readings to ensure data validity and reliability. The integrated status information is processed to ensure it is up-to-date and reflects the real-time operating status of the energy storage device. The current status information is compared with preset normal operating parameter ranges to check if all key indicators are within safe and efficient operating ranges. For status information outside the normal range, the system can quickly identify and determine whether the energy storage device is in an abnormal operating state, such as overheating, overcooling, overcharging, or over-discharging.

[0035] Optionally, the current status information can be saved to the data storage unit of the battery management system or the vehicle's central processing unit for subsequent analysis and retrieval. As needed, a report on the current status information can be generated and provided to the driver or maintenance personnel to help them understand the health status and operating efficiency of the energy storage device.

[0036] Step S104: Based on the status information, determine the temperature of the energy storage device at a future time.

[0037] In the technical solution provided by step S104 of the present invention, the future time is later than the current time.

[0038] In this embodiment, after obtaining the status information of the energy storage device in the vehicle, the temperature of the energy storage device at a future time can be determined based on the status information.

[0039] Optionally, key parameters such as current battery temperature, voltage, current, state of charge, and health status are read from the battery management system. Simultaneously, external environmental data such as temperature and humidity, as well as vehicle operating condition information (e.g., vehicle speed, motor load, charging status), are collected. Outliers and sensor noise are eliminated to ensure the accuracy and reliability of all input data. The collected status information is standardized to unify data format and units for easier model input. Historical operating data similar to the current conditions is extracted from the data storage unit and used as training input for the prediction algorithm. The trend of battery temperature changes over time, environment, and vehicle status in historical data is analyzed to identify patterns and regularities in temperature changes.

[0040] Optionally, a suitable machine learning algorithm (such as time series analysis, neural network models, etc.) is used to train a temperature prediction model based on historical data. The collected real-time state information and the parameters processed in step 2 are input into the prediction model. The model calculates and outputs the predicted temperature value of the energy storage device at future times. Based on battery performance and safety requirements, an abnormal temperature range (thresholds for excessively high or low temperatures) is set. The predicted future temperature is compared with the set abnormal thresholds to determine if there is a risk of abnormal temperature.

[0041] Step S106: In response to the temperature being in an abnormal temperature range, determine the vehicle's control strategy.

[0042] In the technical solution of step S106 of the present invention, the operating state corresponding to the abnormal temperature range is the abnormal operating state, and the control strategy is used to represent the rules for controlling the vehicle to adjust the temperature.

[0043] Optionally, the abnormal temperature range can refer to the temperature range that exceeds the requirements for safe and efficient battery operation. For lithium batteries, the aforementioned abnormal temperature range can be any range other than the normal operating temperature range of the battery (e.g., 25℃~35℃). For example, if the battery temperature is below 0℃ or above 45℃, battery performance will significantly degrade, and may even lead to safety issues, such as capacity decay at low temperatures or the risk of thermal runaway at high temperatures. In other words, the abnormal temperature range can include all temperatures below 0℃ and above 45℃.

[0044] Optionally, abnormal operating conditions can refer to the state in which the energy storage device operates within an abnormal temperature range, i.e., the battery is in a state detrimental to its performance and safety. These abnormal operating conditions can directly affect the battery's charge / discharge efficiency, cycle life, and safety. At low temperatures, the conductivity of the active materials in lithium-ion batteries decreases, leading to slower charging speeds and reduced discharge capacity; at high temperatures, internal chemical side reactions intensify, potentially causing rapid capacity decay or even thermal runaway. Therefore, when the battery temperature is within an abnormal temperature range, its operating state is defined as an abnormal operating state.

[0045] Optionally, the control strategy can be an adjustment measure based on the current and predicted temperature state of the energy storage device to restore the battery temperature to the normal operating range. The control strategy may include, but is not limited to, heating commands, cooling commands, and dynamic adjustments. Specifically, the heating command may be issued when the predicted temperature is below the lower limit of the normal operating temperature, activating the heating device (such as a graphene heating film, PTC heating element, etc.) to raise the battery temperature to a suitable level. The cooling command may be issued when the predicted temperature is above the upper limit of the normal operating temperature, activating the cooling system (such as a microchannel liquid cooling system), adjusting the coolant flow rate or the speed of the cooling fan to reduce the battery temperature. The dynamic adjustment may require dynamic adjustment of the control strategy according to the vehicle's operating conditions (such as driving, charging, stationary, etc.). For example, during fast charging, the cooling intensity may be increased in advance; during driving in extremely cold environments, heating power may be continuously provided until the battery temperature reaches the normal range.

[0046] In this embodiment, after determining the temperature of the energy storage device at a future time based on the state information, if the temperature is within an abnormal temperature range, the vehicle control strategy can be determined.

[0047] Optionally, the system continuously receives and analyzes temperature data from the Battery Management System (BMS). The current temperature data is compared to preset abnormal temperature ranges (e.g., below 0°C or above 45°C). Once the battery temperature is detected to fall within an abnormal temperature range, an abnormal operating state is confirmed. In addition to temperature data, the system also needs to collect other status information related to temperature regulation, such as battery state of charge (SOC), state of health (SOH), vehicle operating conditions (driving, charging, parking, etc.), and external environmental conditions. The system analyzes how this information affects battery temperature changes and identifies factors that cause abnormal temperatures, such as excessive motor load or prolonged inactivity in low-temperature environments.

[0048] Optionally, based on the specific circumstances of the abnormal temperature and comprehensive status information analysis, the system determines an appropriate control strategy. This may include activating the heating system, enhancing cooling capacity, adjusting charging current, and limiting vehicle power output. When formulating the control strategy, battery safety and overall vehicle performance can be considered to ensure that the selected strategy will not cause further damage to the battery. Based on the selected strategy, specific control commands are generated, specifying the activation time, power level, or specific values ​​for adjusting the charging / discharging rate of the heating / cooling device. The generated control commands are sent to the corresponding execution units (such as the heating module, cooling module, charging management unit, etc.). While executing the control strategy, temperature changes and other status information continue to be monitored to ensure the effective implementation of the strategy and a smooth return of the battery temperature. If the initial control strategy fails to restore the temperature to normal within the expected time, the system prepares a second control scheme and assesses whether emergency shutdown or other safety measures are necessary.

[0049] Optionally, the effectiveness of the control strategy can be continuously evaluated, and the heating / cooling intensity or charging / discharging management strategy can be dynamically adjusted based on the latest status information. An effective feedback mechanism can be established to collect temperature change data after the execution of the control strategy, which can be used to optimize future control strategies and improve the accuracy and efficiency of temperature regulation.

[0050] In step S108, at a future time, the vehicle is controlled to adjust the temperature according to the control strategy.

[0051] In the technical solution of step S108 of the present invention, the adjusted temperature is within the normal temperature range, and the operating state corresponding to the normal temperature range is the normal operating state.

[0052] Optionally, the normal temperature range can refer to the temperature range within which the battery can operate safely and efficiently. For lithium batteries, the above-mentioned normal temperature range can be defined as 25℃~35℃, which is determined based on the optimal activity temperature range of the internal chemical reactions of the battery. Within the normal temperature range, the battery can achieve the best charge and discharge efficiency, the longest cycle life, and the highest safety performance. Excessively high temperatures (such as exceeding 45℃) will accelerate the internal chemical reactions of the battery, increase the battery aging rate, and even trigger thermal runaway; excessively low temperatures (such as below 0℃) will reduce the migration rate of lithium ions, affect the battery's charge and discharge performance, and increase the risk of battery aging.

[0053] Optionally, normal operating condition can refer to the state in which energy storage devices (such as batteries) operate within a normal temperature range, that is, the battery is in a state of optimal performance and safety. Under the above-mentioned normal operating condition, the battery's key performance indicators such as charge and discharge efficiency, energy density, and cycle life are all at their optimal state, while ensuring battery safety and avoiding various failures and safety risks caused by abnormal temperatures. Normal operating condition not only covers the operation of the battery under suitable ambient temperature conditions, but should also include the state in which the battery temperature is actively adjusted by the temperature control system to keep it within the normal temperature range under various vehicle operating conditions (such as high-speed driving, fast charging, long-term idling, etc.).

[0054] In this embodiment, after determining the vehicle's control strategy, the vehicle can be controlled to adjust the temperature in a future time according to the control strategy.

[0055] Optionally, the specific moment given by the temperature prediction model is determined, i.e., the time point at which the system will take adjustment measures. Based on the predicted temperature value, it is determined whether it is within an abnormal temperature range. A thorough understanding of the determined control strategy is achieved, including the specific methods of heating / cooling, the required time, and the target temperature. According to the control strategy, the resources required by the heating / cooling modules, such as energy and material supply, are pre-allocated. As the future moment approaches, the system collects the latest environmental data and vehicle operating status again to verify whether the prediction information is still accurate. Based on the latest information, the control strategy is fine-tuned in a timely manner to ensure that it conforms to the actual situation to the greatest extent possible.

[0056] Optionally, upon reaching a future time, the temperature regulation process is immediately initiated. If the temperature is to rise, the heating device (such as a graphene heating film) is activated; if the temperature is to fall, the cooling system (such as a microchannel liquid cooling system) is activated, and operations are performed according to the parameters set by the strategy (such as heating power, coolant flow rate, etc.). During the execution of the control strategy, changes in battery temperature are continuously monitored and compared with the preset target.

[0057] Optionally, the heating / cooling operation should be stopped when the adjusted temperature reaches or returns to the normal temperature range. Confirm that the battery is in normal operating condition, including charge / discharge efficiency, SOC and SOH recovery status. Based on the data from this adjustment, optimize future temperature prediction and control strategies to improve the accuracy and efficiency of the system response.

[0058] In the embodiments of this application, the above method ensures that when abnormal battery temperature is predicted in the future, timely and effective measures can be taken to restore the battery temperature to the normal range as quickly as possible through precise temperature regulation, thereby ensuring that the battery is in normal operating condition and maintaining the safety and performance of the vehicle. At the same time, through continuous strategy adjustment and optimization, it can better adapt to various operating scenarios and environmental changes, improving the intelligence level and overall efficiency of temperature management.

[0059] In steps S102 to S108 of this application, the status information of the energy storage device in the vehicle at the current moment is obtained, wherein the status information is used to represent the operating status of the energy storage device at the current moment; based on the status information, the temperature of the energy storage device at a future moment is determined, wherein the future moment is later than the current moment; in response to the temperature being in an abnormal temperature range, a control strategy for the vehicle is determined, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy is used to represent the rules for controlling the vehicle to adjust the temperature; at the future moment, according to the control strategy, the vehicle is controlled to adjust the temperature, wherein the adjusted temperature is within the normal temperature range, and the operating state corresponding to the normal temperature range is a normal operating state. In other words, in this embodiment, by obtaining the status information of the energy storage device in real time, the battery temperature at a future moment can be predicted, and it can be determined in advance whether it may enter an abnormal temperature range. Once an anomaly is predicted, a control strategy is formulated and executed, such as adjusting the coolant flow rate or heating power, without waiting for the temperature to actually deviate from the ideal range. The innovation of the above method lies in transforming temperature regulation from a passive response to a prediction-based active management, which significantly improves the system's response speed and control accuracy. This effectively solves the problem of low accuracy in battery temperature regulation in existing technologies, ensures stable and efficient battery operation under various operating conditions, solves the technical problem of low accuracy in temperature regulation of energy storage devices in vehicles, and achieves the technical effect of improving the accuracy of temperature regulation of energy storage devices in vehicles.

[0060] The method described in this embodiment will be further described below.

[0061] As an optional embodiment, step S106, in response to the temperature being in an abnormal temperature range, determines a control strategy for the vehicle, including: in response to the temperature being below the normal temperature range, determining that the temperature is in an abnormal temperature range, and determining the control strategy corresponding to the temperature below the normal temperature range as a first control strategy, wherein the first control strategy is used to represent a rule for controlling the vehicle to increase its temperature; in response to the temperature being above the normal temperature range, determining that the temperature is in an abnormal temperature range, and determining the control strategy corresponding to the temperature above the normal temperature range as a second control strategy, wherein the second control strategy is used to represent a rule for controlling the vehicle to decrease its temperature.

[0062] In this embodiment, during the process of determining the vehicle's control strategy, if the temperature is below the normal temperature range, it can be determined that the temperature is in an abnormal temperature range, and a corresponding first control strategy can be determined. If the temperature is above the normal temperature range, a corresponding second control strategy can be determined.

[0063] Optionally, temperature data from the battery management system and ambient temperature information are continuously collected. The collected temperature data is compared with a preset normal temperature range (e.g., 25℃~35℃). If the battery temperature is detected to be below the lower limit of the normal temperature range (e.g., below 0℃), the system immediately confirms that it is in an abnormal temperature range. After identifying the abnormal operating state, a primary control strategy aimed at improving the battery temperature can be generated. Based on this strategy, a heating system, such as a graphene heating film or a PTC heating element, is activated to quickly increase the battery temperature. The power level of the heating element and the duration of heating are determined to ensure that the battery temperature can safely and efficiently recover to the normal temperature range. Considering safety factors during the heating process, the strategy should include the thermal stability and thermal protection mechanisms of the heating element to prevent overheating.

[0064] Optionally, a control command is sent to the heating module to execute the first control strategy. The battery temperature is continuously monitored after heating to ensure a smooth rise until it reaches the normal temperature range. After the heating operation is completed, the battery temperature, charge / discharge efficiency, and other parameters are analyzed to determine if they have returned to ideal conditions, and secondary adjustments are made if necessary. Similar to the low-temperature response, temperature data is continuously collected and compared with the normal temperature range to detect any temperature anomalies. If the temperature exceeds the upper limit of the normal temperature range (e.g., above 30°C), the system confirms that the battery is in an abnormal temperature range.

[0065] Optionally, a second control strategy can be determined to activate the cooling system (such as a microchannel liquid cooling cycle) to reduce the battery temperature. The coolant flow rate, cooling fan speed, and cooling cycle time are set to ensure that the battery temperature can be rapidly and stably reduced to within the normal temperature range. When designing the cooling strategy, the system must balance cooling efficiency and energy consumption, while also including a thermal protection mechanism to prevent excessive cooling that could degrade battery performance.

[0066] Optionally, a control command is sent to the cooling module to execute a second control strategy. The battery temperature is monitored during the cooling process to ensure it gradually decreases to the normal temperature range. After the cooling operation is complete, the battery temperature, cycle life, and other indicators are checked to ensure they meet the standards; if necessary, secondary adjustments are made to optimize the results.

[0067] Optionally, the control strategy needs to be flexibly adjusted according to the vehicle's driving status (driving, parking, charging, etc.) and external environmental conditions (high temperature, excessive humidity, etc.) to ensure optimal temperature regulation. It can possess predictive capabilities, enabling it to anticipate impending temperature anomalies and proactively activate or adjust heating / cooling strategies for preventative temperature management. By continuously collecting actual performance data from heating / cooling operations, the system should be able to learn and continuously optimize its control strategy, improving the accuracy and efficiency of temperature regulation.

[0068] In this embodiment of the application, the above method can quickly start and execute the corresponding first or second control strategy when an abnormal battery temperature is detected, so as to ensure that the battery temperature quickly returns to the normal temperature range, maintain the optimal operating state of the battery and improve the overall performance of the vehicle, while taking into account the safety and economy of operation.

[0069] As an optional embodiment, the vehicle includes a cooling module and a heating module. In step S108, at a future time, according to a control strategy, the vehicle controls the temperature of the energy storage device to be adjusted, including: at a future time, according to a first control strategy, controlling the heating module to perform a heating operation on the energy storage device to increase the temperature; at a future time, according to a second control strategy, controlling the cooling module to perform a cooling operation on the energy storage device to decrease the temperature.

[0070] In this embodiment, during the temperature adjustment process according to the control strategy, the heating module can be controlled to perform a heating operation on the energy storage device to increase the temperature according to the first control strategy. Alternatively, the cooling module can be controlled to perform a cooling operation on the energy storage device to reduce the temperature according to the second control strategy.

[0071] Optionally, the current temperature of the energy storage device is continuously monitored using a high-precision temperature sensor. When the temperature falls below the lower limit of the normal temperature range (e.g., below 0°C), a heating requirement is identified, indicating an abnormal operating state. According to the first control strategy, the heating module is activated, for example, using a graphene heating film. Utilizing the excellent thermal conductivity and heating properties of graphene, rapid temperature rise is achieved, significantly increasing the temperature within 3 seconds, ensuring the battery quickly returns to the normal temperature range. During heating, the system continuously receives feedback from the temperature sensor to monitor temperature changes. When the temperature approaches the normal range, the heating power is adjusted to achieve a temperature control accuracy of ±0.5°C, preventing the battery temperature from overheating.

[0072] Optionally, the temperature of the energy storage device is continuously monitored and compared with the upper limit of the normal temperature range (e.g., 30°C). When the temperature exceeds the upper limit, a cooling demand is identified, indicating an abnormal operating state. According to a second control strategy, a cooling module, such as a microchannel liquid cooling system, is activated. Through coolant circulation in a 1.2mm serpentine pipe and flow rate control by a variable frequency water pump, a heat dissipation power of up to 5kW is achieved, effectively reducing the battery temperature. During the cooling process, feedback from temperature sensors is continuously received to monitor battery temperature changes. The coolant flow rate is adjusted based on real-time temperature data to optimize the cooling effect and ensure the battery temperature steadily decreases to the normal range.

[0073] Optionally, by combining temperature sensors, environmental sensors, and other data, comprehensive data can be collected, providing a foundation for more accurate temperature prediction and control strategy formulation. Through continuous temperature monitoring and feedback, dynamic adjustments to heating and cooling operations can be achieved, ensuring that the energy storage device is always in the optimal temperature state. The built-in Artificial Intelligence (AI) algorithm can intelligently adjust the parameters of the first or second control strategy based on historical data and real-time information, achieving efficient and safe temperature management.

[0074] Optionally, by precisely controlling battery temperature, the charging and discharging efficiency of the battery can be significantly improved, extending its cycle life. This avoids safety hazards caused by abnormal battery temperatures, such as thermal runaway due to overheating or performance degradation at low temperatures. Using solar energy to power the heating and cooling system reduces dependence on the main battery's power, achieving efficient energy utilization.

[0075] As an optional embodiment, step S104, determining the temperature of the energy storage device at a future time based on the state information, includes: inputting the state information into a dynamic thermal model, wherein the dynamic thermal model is trained using an artificial intelligence algorithm based on state information samples and temperature samples; using the dynamic thermal model, determining the temperature change trend of the energy storage device at a future time based on the state information, wherein the temperature change trend is used to represent the temperature change over time; and determining the temperature of the energy storage device at a future time based on the temperature change trend.

[0076] In this embodiment, during the process of determining the temperature at future times based on state information, the state information can be input into a dynamic thermal model. The dynamic thermal model can then be used to determine the temperature change trend of the energy storage device at future times based on the state information, and the temperature of the energy storage device at future times can be determined based on the temperature change trend.

[0077] Optionally, the status information includes, but is not limited to, battery state of charge (SOC), state of health (SOH), vehicle operating conditions (such as driving, charging, and parking), ambient temperature, wind speed, and humidity. This information is continuously acquired and preprocessed through the vehicle's sensor network, battery management system (BMS), and external environmental monitoring equipment to ensure data quality and real-time performance. Based on the collected status information samples and corresponding temperature samples, a dynamic thermal model is trained using artificial intelligence algorithms (such as deep learning, regression analysis in machine learning, and neural networks). This model can learn and understand the complex relationship between status information and battery temperature, and predict future temperature changes of the energy storage device under different operating conditions.

[0078] Optionally, using the current state information as input, the dynamic thermal model calculates the future temperature change trend of the energy storage device through its internal algorithm. This process utilizes the patterns learned by the model during training to analyze and predict the input data. The temperature change trend specifically manifests as the increase or decrease in temperature over time, which may be linear, nonlinear, or periodic. The trend prediction results help the system anticipate potential temperature fluctuations, thereby preparing appropriate temperature regulation strategies.

[0079] Optionally, based on temperature change trends, the system can predict the precise temperature value of the energy storage device at future moments. This prediction result is crucial for determining whether and how to adjust the temperature. The accuracy of the dynamic thermal model's predictions directly affects the effectiveness of subsequent temperature management strategies. To improve accuracy, the model needs to be updated regularly and retrained using the latest state information and temperature data to adapt to dynamic changes in the environment and operating conditions. The system detects whether the predicted future temperature is within an abnormal range (below the lower limit of the normal temperature range or above the upper limit of the normal temperature range). If an abnormal temperature is detected, action is determined. Based on the predicted temperature change trend, the system generates a corresponding first control strategy (heating) or second control strategy (cooling). The control strategy must clearly define the initiation conditions, operating parameters, and duration of heating / cooling. The generated control strategy is executed, and the actual temperature changes of the energy storage device are monitored to ensure that temperature regulation achieves the expected effect. Simultaneously, the system should have a feedback mechanism to adjust the control strategy based on the actual effect to adapt to unforeseen changes in operating conditions.

[0080] Optionally, during system operation, status information and temperature data are continuously collected for ongoing model optimization. Periodically, or when the system detects a significant deviation between predicted and actual temperatures, the latest dataset is used to retrain the dynamic thermal model, improving its prediction accuracy. By comparing and analyzing the model's predictions with actual temperature changes, the model's performance is evaluated, and algorithm parameters or model structure are adjusted promptly to improve its adaptability and prediction accuracy.

[0081] In this embodiment, the method described above can predict the future temperature change trend of energy storage devices based on dynamic thermal models and state information, and determine specific temperature values ​​accordingly, providing a scientific and accurate basis for temperature regulation. This not only helps improve the operating efficiency and safety of vehicles under various operating conditions, but also reduces energy loss and equipment aging caused by improper temperature management, thereby improving the performance and service life of the entire vehicle system.

[0082] As an optional embodiment, the vehicle includes sensors, and the method further includes: using the sensors to acquire environmental information of the environment in which the energy storage device is located at the current moment, wherein the environmental information is used to influence the operating state; the vehicle includes a central processing unit, the central processing unit includes a dynamic thermal model, and using the dynamic thermal model, based on the state information, determines the temperature change trend of the energy storage device at future moments, including: controlling the central processing unit to determine the temperature change trend based on the dynamic thermal model, the state information, and the environmental information.

[0083] In this embodiment, sensors in the vehicle can be used to acquire environmental information about the current location of the energy storage device. During the process of determining the temperature change trend using a dynamic thermal model based on the state information, the central processing unit can be controlled to determine the temperature change trend using the dynamic thermal model, based on both the state and environmental information.

[0084] Optionally, the sensor array equipped in the vehicle is not limited to measuring the state information of the energy storage device (such as the battery pack) itself, but also includes environmental sensors to monitor the environmental information of the environment in which the energy storage device is located at the current moment. The types of environmental information can be very broad; in this embodiment, the focus is on ambient light information. Ambient light directly affects the photoelectric conversion efficiency of the solar energy storage panel, and thus affects the energy supply of the energy storage device. Under sufficient sunlight, the energy storage panel has high power generation efficiency and can provide sufficient power for the temperature control system; while under insufficient sunlight, the power generation is reduced, and it is necessary to consider how to optimize the energy consumption of the temperature control system to ensure its normal operation.

[0085] Optionally, a dynamic thermal model can be integrated into the central processing unit (CPU). This model, trained through extensive data analysis, understands the impact of state and environmental information on the temperature of the energy storage device. The CPU runs the dynamic thermal model to predict the future temperature trends of the energy storage device based on current state information (battery temperature, state of charge, health status, etc.) and environmental information (especially ambient light). This prediction helps the system plan heating / cooling operations in advance, avoiding performance losses or safety hazards caused by sudden temperature changes.

[0086] Optionally, when forecasts indicate sufficient ambient light in the future, the temperature control system can fully utilize solar energy, reducing reliance on the vehicle's main battery and achieving more efficient temperature regulation. Conversely, if lighting conditions are poor, the temperature control strategy needs to be optimized to ensure stable operation under limited power conditions. This may include activating the energy storage battery pack and adjusting heating / cooling intensity. Based on temperature change trends predicted by the dynamic thermal model, the system automatically generates heating or cooling control strategies, which are coordinated and executed by the central processor to ensure that the temperature of the energy storage device remains within the optimal range in the future. Through intelligent energy scheduling, the system can maximize the use of solar energy, reduce power consumption of the main battery, and improve overall energy efficiency. Combining environmental information with temperature change trend predictions makes heating / cooling operations more precise, reduces temperature fluctuations, and extends the lifespan of the energy storage device. It can provide early warnings and respond to potential temperature anomalies caused by changes in lighting conditions, reducing the risk of thermal runaway and improving vehicle operational safety.

[0087] Optionally, state and environmental information can be continuously collected for retraining of the dynamic thermal model, thereby continuously improving the model's prediction accuracy and sensitivity to environmental changes. As the predictive capabilities of the dynamic thermal model improve, the control strategy library will also be continuously improved, providing more diverse heating / cooling solutions to adapt to temperature regulation needs under different lighting and operating conditions.

[0088] In this embodiment, the above method fully considers the influence of ambient light, achieving more intelligent and precise temperature regulation. This not only improves the performance and safety of energy storage devices but also optimizes the overall energy utilization efficiency of vehicles, providing an efficient and reliable solution for temperature control of pure electric vehicles.

[0089] As an optional embodiment, step S102, obtaining the status information of the energy storage device in the vehicle at the current moment, includes: obtaining the status information in response to activating the vehicle's temperature regulation function.

[0090] In this embodiment, if the vehicle's temperature control function is activated while acquiring the current status information of the energy storage device in the vehicle, the status information can be acquired.

[0091] Optionally, the temperature regulation function can be manually triggered by the user through the vehicle's central control interface, or it can be automatically activated by the system according to pre-set rules (such as detecting that the battery temperature exceeds the normal range). In response to the activation of the temperature regulation function, the system immediately initiates a data acquisition process to obtain temperature-related status information from the vehicle's sensor network. This includes directly reading battery status parameters from the Battery Management System (BMS) and obtaining external environmental conditions from environmental sensors. The sensor network continuously monitors the status information of the energy storage device to ensure the real-time nature and accuracy of the data. This involves the layout of high-precision sensors, as well as the mechanisms for data transmission and processing. The collected status information needs to be preprocessed, including data cleaning, format standardization, and, if necessary, conversion, to ensure the accuracy and efficiency of subsequent analysis.

[0092] Optionally, the status information needs to be updated frequently enough to capture rapid changes in battery status, especially in the early stages when the temperature regulation function is enabled, which may require a higher sampling frequency to monitor temperature changes in real time.

[0093] Optionally, the acquired state information is used as an important input to the dynamic thermal model to predict future temperature trends in the battery. Based on the model prediction results, the central processing unit determines corresponding control strategies, such as activating the heating or cooling system and adjusting energy management parameters, to respond to the current state information and ensure stable battery temperature control. After the temperature regulation function is activated, the various components within the system (such as the heating module, cooling module, and energy storage unit) need to work efficiently and collaboratively according to the acquired state information and control strategies. A user interface should be provided to clearly display the current status and effects of temperature regulation, including battery temperature trends and energy consumption, allowing users to understand the progress of temperature regulation in real time and make manual adjustments when necessary.

[0094] As an optional embodiment, the vehicle includes an energy storage plate, a cooling module, and a heating module. The method further includes at least one of the following: in response to the vehicle being in a powered-off state or the ambient light intensity of the vehicle being in a light intensity threshold, providing electrical energy to the cooling module and the heating module using the energy storage plate; during temperature adjustment, displaying an adjustment status on a graphical user interface associated with the vehicle, wherein the adjustment status indicates the operating status of components in the vehicle during temperature adjustment; and triggering or stopping the temperature adjustment process in response to a control operation triggered by a target object of the vehicle on the graphical user interface.

[0095] In this embodiment, if the vehicle is off, or the ambient light intensity is below a certain threshold, the energy storage plate can provide power to the cooling and heating modules. During temperature adjustment, the adjustment status can be displayed on the graphical user interface associated with the vehicle. If a target object (e.g., a driver or passenger) triggers a control operation on the graphical user interface, the temperature adjustment process can be initiated or stopped.

[0096] Optionally, solar energy storage panels installed on the vehicle body surface, such as flexible cadmium telluride thin-film solar panels, can convert solar energy into electrical energy under sunlight conditions, providing auxiliary energy for the vehicle's cooling module, heating module, and temperature control system. In environments with sufficient sunlight, the energy storage panels can independently supply power to the temperature control system, reducing the burden on the main battery pack and extending the driving range. The energy storage battery pack serves as a backup energy system, taking over power to the temperature control system from the solar energy storage panels when the vehicle is off or in poor lighting conditions, ensuring that temperature regulation is not limited by external conditions and achieving stable temperature control year-round, around the clock.

[0097] Optionally, if the vehicle is turned off, it automatically switches to the energy storage battery pack power supply mode, utilizing previously stored energy to continue operating the temperature control system and ensuring the energy storage device remains within a safe and ideal temperature range. A light intensity threshold is set; when the detected external light intensity is below this threshold, the solar energy storage panel's power generation efficiency is insufficient to support the normal operation of the temperature control system. In this case, the system automatically switches to the energy storage battery pack power supply to compensate for the energy shortfall. The vehicle's central control interface displays the real-time status of the temperature adjustment process through a graphical user interface, including but not limited to the energy generation of the energy storage panel, the remaining charge of the energy storage battery pack, the operating status of the cooling / heating modules, battery temperature values ​​and their trends, etc. Users can intuitively understand the operation of the entire temperature control system through the graphical user interface. The graphical user interface provides user-operable buttons or sliders, allowing users to manually adjust the temperature adjustment strategy according to personal needs or changes in the external environment. For example, one-click activation of deep energy-saving mode, or adjustment of heating / cooling priority within a specific temperature range.

[0098] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0099] Currently, with the booming development of the automotive industry, pure electric vehicles have become mainstream products launched by major automakers. As one of the most crucial components of pure electric vehicles, the safety and lifespan of batteries have received much attention. Battery operation within a suitable temperature range is critical. Research data shows that lithium batteries achieve the highest charging and discharging efficiency and the least cycle life loss when operating within the temperature range of 25℃-35℃. However, when the temperature exceeds 45℃, internal chemical reactions intensify, potentially leading to thermal runaway risks; below 0℃, lithium-ion activity decreases significantly, resulting in battery capacity degradation exceeding 30%. Therefore, ensuring batteries operate at suitable temperatures has become a key focus of industry efforts. By employing advanced temperature control technology, not only can batteries operate in optimal conditions, but vehicle performance can also be effectively improved and lifespan extended, providing users with a safer, more reliable, and more efficient travel experience. This application's embodiments primarily focus on the temperature balance of power batteries, aiming to ensure batteries operate within their optimal temperature range and address safety incidents and range issues caused by abnormal temperatures (excessive heat triggering thermal runaway, excessive cold causing capacity degradation).

[0100] Alternatively, in the current era of rapid development in the pure electric vehicle industry, the performance of the power battery, as the "heart" driving the vehicle, directly determines the overall user experience and market competitiveness. However, industry research data shows that in the past three years, over 65% of electric vehicle safety accidents caused by battery failures worldwide were closely related to abnormal battery temperatures. Meanwhile, the issue of reduced battery range in low-temperature environments has become one of the core concerns for consumers when purchasing a vehicle. These two major pain points severely restrict the popularization of pure electric vehicles.

[0101] From the perspective of battery working principles, lithium-ion batteries involve complex electrochemical reactions and energy conversions during charging and discharging, with temperature being a key variable affecting the reaction rate and the stability of active materials. When the battery temperature exceeds 45°C, the electrolyte decomposition inside the battery intensifies, producing a large amount of flammable gas. If heat dissipation is not timely, it can easily trigger a thermal runaway chain reaction, leading to battery fire or even explosion. In 2022, a well-known brand of electric vehicle spontaneously combusted while driving at high speed in the summer. Investigations confirmed that this was caused by excessively high local temperatures in the battery pack triggering thermal runaway. In extremely cold environments of -20°C, the migration rate of lithium ions inside the battery decreases significantly, leading not only to a battery capacity reduction of over 40%, but also preventing lithium ions from properly intercalating into the negative electrode material during charging, causing lithium plating, accelerating battery aging, and posing a short-circuit risk.

[0102] Although the industry has widely adopted temperature control technologies such as air cooling and liquid cooling, traditional solutions still have limitations such as slow response and high energy consumption. Air cooling systems are greatly affected by ambient temperature, and their heat dissipation efficiency decreases significantly in high-temperature environments; while liquid cooling systems have strong heat dissipation capabilities, the circulation of coolant consumes additional electricity, and it is difficult to achieve precise temperature control of battery modules.

[0103] To address the aforementioned industry challenges, this invention proposes a battery temperature collaborative control method based on a multi-dimensional sensor array and an adaptive intelligent controller. This system deploys high-precision temperature, humidity, and pressure sensors at key locations within the battery module to collect real-time battery operating data, in conjunction with liquid cooling (microchannel piping) and heating (graphene heating film, PTC element) modules. Furthermore, it integrates AI algorithms to establish a dynamic thermal model, accurately predicting battery temperature change trends. When an abnormal temperature is detected, the intelligent controller can respond in milliseconds, coordinating the control of the liquid cooling circulation pump speed, the cooling fan start / stop, and the PTC heating element power, forming a closed-loop management system of "monitoring-analysis-control." Compared to traditional temperature control systems, this method reduces the battery temperature fluctuation range to ±1.5℃, enabling the battery to maintain efficient operation even in extreme environments ranging from -30℃ to 50℃. This provides a revolutionary technical solution for the safe and reliable operation of pure electric vehicles.

[0104] The embodiments of the present invention will be further described below.

[0105] The solar energy storage panel utilizes flexible materials and nano-coating technology, achieving a photoelectric conversion efficiency of 22.5%. It generates electricity stably even in low light conditions, and its self-cleaning coating ensures long-term performance. The generated electricity is optimized by an MPPT controller and stored in a lithium iron phosphate battery pack, providing independent power for the entire temperature control system and eliminating reliance on the vehicle's main battery.

[0106] The intelligent control unit is the core hub, connecting a multi-dimensional sensor array and the execution module. Sensors collect real-time data on battery temperature, ambient light, and stored energy, transmitting this data to the control unit. The control unit incorporates a dynamic thermal model and, combined with an AI temperature control algorithm (including PID regulation logic), analyzes the data and generates commands: when the battery temperature is below 0℃, the graphene heating film is activated, its two-dimensional structure rapidly heating up within 3 seconds with a temperature control accuracy of ±0.5℃; when the temperature exceeds 30℃, the microchannel liquid cooling system is activated, with a 1.2mm serpentine pipe and a variable frequency water pump adjusting the flow rate to achieve a 5kW heat dissipation power.

[0107] The energy storage battery pack acts as an energy buffer, continuously supplying power to the temperature control system when the vehicle is off or in low light conditions, ensuring uninterrupted closed-loop regulation. The central control interface displays the status of each component through visual curves, allowing users to start and stop the vehicle with a single button, and the system automatically issues warnings for any abnormalities.

[0108] This architecture deeply couples power generation, energy storage, and temperature control, enabling the battery to always operate in the 0-30℃ range, maintain a charge and discharge efficiency of over 95%, reduce the main battery's energy consumption, and improve safety and range stability in extreme environments.

[0109] Optionally, the operating logic is optimized for scenarios involving long-term vehicle parking, with all components working together to achieve intelligent temperature control management. The specific operating mechanism is as follows:

[0110] The central processing unit (CPU) acts as the control core, continuously interacting with various modules. When the user activates "Deep Energy Saving Mode" on the central control interface, the CPU receives the command and immediately cuts off the power supply circuits to the heating and cooling modules, retaining only the basic power supply for the battery temperature monitoring function. Simultaneously, it sends a hibernation command to the energy storage battery pack, triggering a low-power management program to control its daily self-discharge rate to within 0.3%.

[0111] If the user does not enable the deep energy-saving mode, the system enters the normal monitoring and control state: the high-precision digital temperature sensor integrated inside the battery (accuracy ±0.1℃) collects cell temperature data 10 times per second and transmits it to the central processor in real time via the CAN bus. After receiving the data, the processor calls the adaptive fuzzy control algorithm for dual-channel processing: on the one hand, it determines whether to trigger the execution command based on the current temperature value—when the temperature is below 0℃, a start signal is sent to the graphene heating film to control it to run at an initial power of 1.2kW, and then reduce it to 0.5kW to maintain the power after the temperature rises to 5℃; when the temperature exceeds 30℃, the natural convection mode of the liquid cooling system is activated first, and if the temperature continues to rise within 5 minutes, the speed of the variable frequency water pump is gradually increased to the maximum power. On the other hand, the algorithm combines the historical temperature curve of the past 3 hours with the current environmental parameters to predict the temperature change trend in the next 15 minutes. For example, if the ambient temperature is detected to be below -10℃ in winter and the battery temperature drops by more than 2℃ every 10 minutes, the heating module is activated in advance for preheating.

[0112] Under different operating conditions, the central processing unit dynamically adjusts the data acquisition dimensions and control strategies: when the vehicle is stationary, it only receives data from the temperature sensor and the energy storage battery, and controls the energy storage battery pack to output 15% of its rated power to ensure the system can operate independently for 72 hours; during driving, it synchronously obtains parameters such as vehicle speed and real-time motor load from the vehicle CAN bus. When the vehicle speed exceeds 80km / h and the motor output power exceeds 80% of the rated value for 5 minutes, it increases the speed of the liquid cooling system water pump to 30% for pre-cooling; during the charging phase, it obtains charging power information through the charging pile data interaction interface. In the 60kW fast charging scenario, it automatically increases the heat dissipation power of the liquid cooling system to 4kW, reducing the battery temperature rise rate by 60%.

[0113] The electricity generated by the solar energy storage panels is optimized by the MPPT controller and continuously replenishes the energy storage battery pack. The central processing unit monitors the battery status in real time. When the battery level is below 20%, solar power is prioritized for the battery pack; when the battery level is above 80%, excess power is used for the operation of the temperature control system. This collaborative mechanism enables the system to achieve an average annual self-sufficiency rate of 92%, ensuring that the temperature control function can operate normally for 48 hours even after a week of continuous cloudy or rainy weather.

[0114] Optionally, the battery temperature control system monitors the cell temperature in real time using a high-precision temperature sensor (sampling frequency 10Hz, accuracy ±0.1℃), and dynamically adjusts the temperature using a fuzzy PID control algorithm.

[0115] Low-temperature heating mode: Utilizing a graphene nano-heating film (heating rate 5℃ / s) combined with a PTC ceramic heating element, along with thermally conductive silicone pads, it achieves 360° uniform heat conduction, preheating the battery to 25℃ within 12 minutes at -30℃. High-temperature cooling mode: Equipped with a microchannel liquid cooling system (channel diameter 0.8mm), linked to a variable frequency water pump (0-3000rpm adjustable) and heat dissipation fins, it can control the battery temperature below 30℃ at 45℃, with a temperature fluctuation ≤±1.5℃. This system, through collaboration between the BMS battery management system and the central processing unit, constructs a "monitoring-decision-execution" closed loop, ensuring the battery is always maintained within the optimal operating range of 25℃±5℃.

[0116] Solar Energy Storage: A flexible cadmium telluride thin-film solar panel is integrated into the roof, paired with a 5kWh lithium iron phosphate battery pack, forming an energy closed loop independent of the main battery. Photovoltaic Conversion Module: Employing MPPT (Maximum Power Point Tracking) technology, it maintains over 70% power generation efficiency even in low-light conditions such as cloudy or rainy days, generating an average of 8-12kWh per day. Energy Management System: A bidirectional DC-DC converter enables intelligent power supply to the battery pack and temperature control system. When solar panel power generation is insufficient, the battery pack can independently support the temperature control system for 72 hours (self-discharge rate <0.5% / day). Zero-Energy Design: 93% of the temperature control system's annual power comes from solar energy. Compared to traditional onboard power solutions, this reduces the battery's energy consumption by 1200kWh annually, equivalent to an increase in driving range of 4800 kilometers.

[0117] All-condition adaptability: The system collects vehicle status data in real time via the CAN bus, enabling dynamic adjustment of temperature control strategies across all scenarios. Driving state: Combining motor load and vehicle speed data, pre-cooling / pre-heating is initiated 15 minutes in advance to prevent battery overheating during rapid acceleration. Charging state: Communicating with the charging pile to obtain charging power, the system dynamically adjusts cooling intensity, ensuring a battery temperature rise of ≤15℃ / h during 60kW fast charging. Stationary state: Entering low-power monitoring mode, the temperature control module is woken up every 10 minutes to maintain stable battery temperature. Extreme conditions: In environments ranging from -40℃ to 60℃, an extreme protection mode is activated, prioritizing the operation of the temperature control system through the energy storage battery. Comprehensive performance improvement: Significant improvements are seen in safety performance, charging efficiency, range, and extreme adaptability.

[0118] Figure 2 This is a schematic diagram of a control system for balancing battery temperature according to an embodiment of the present invention, as shown below. Figure 2As shown, the control system may include a solar energy storage panel 201, a central processing unit 2020, a cooling module 203, and a heating module 204. The solar energy storage panel 201 is installed on the top layer or surface of the vehicle and is made of flexible or more efficient photoelectric conversion materials, such as cadmium telluride thin film, silicon-based solar panels, or perovskite. It can convert solar energy into electrical energy under sunlight conditions, providing auxiliary power for the vehicle's battery temperature control system. This component can have low light response capability, maintaining a certain power generation efficiency even on cloudy or overcast days. It can also be equipped with a self-cleaning coating to ensure that long-term photoelectric conversion efficiency is not affected by dust or dirt. The central processing unit 2020, as the core of the control system, is responsible for processing status information and environmental information, and predicting battery temperature change trends based on dynamic thermal models and AI algorithms, generating and executing corresponding control strategies. The cooling module 203 is used to rapidly cool the battery when the temperature is too high, preventing thermal runaway and maintaining its operation within a safe temperature range. The heating module 204 ensures that the battery can be quickly heated to a suitable operating temperature, avoiding performance degradation caused by low temperatures.

[0119] Figure 3 This is a flowchart of a method for controlling the temperature of a balanced battery according to an embodiment of the present invention, such as... Figure 3 As shown, the method may include the following steps:

[0120] Step S301: Is the function enabled?

[0121] In this embodiment, if the function is enabled, step S302 can be executed; otherwise, the process ends.

[0122] Step S302: Is the temperature < 0℃?

[0123] In this embodiment, if the temperature is <0°C, step S303 can be executed. If the temperature is ≥0°C, step S304 can be executed.

[0124] Step S303: Turn on the heating.

[0125] Step S304: Is the temperature > 30℃?

[0126] In this embodiment, if the temperature is >30°C, step S305 can be executed. If the temperature is ≤30°C, the process can end.

[0127] According to embodiments of the present invention, a temperature regulation device for an energy storage device in a vehicle is also provided. It should be noted that this temperature regulation device for an energy storage device in a vehicle can be used to execute the temperature regulation method for an energy storage device in a vehicle described in the above embodiments.

[0128] Figure 4This is a schematic diagram of a temperature regulation device for an energy storage device in a vehicle according to an embodiment of the present invention, such as... Figure 4 As shown, the temperature regulation device 400 of the energy storage device in the vehicle may include: an acquisition unit 402, a first determination unit 404, a second determination unit 406, and an adjustment unit 408.

[0129] The acquisition unit 402 is used to acquire the status information of the energy storage device in the vehicle at the current moment.

[0130] The first determining unit 404 is used to determine the temperature of the energy storage device at a future time based on the state information.

[0131] The second determining unit 406 is used to determine the vehicle's control strategy in response to the temperature being in an abnormal temperature range.

[0132] The regulating unit 408 is used to control the vehicle to regulate the temperature in the future, according to the control strategy.

[0133] In this embodiment of the invention, the acquisition unit 402 acquires the current state information of the energy storage device in the vehicle. Based on the state information, the first determination unit 404 determines the temperature of the energy storage device at a future time. In response to the temperature being within an abnormal temperature range, the second determination unit 406 determines the vehicle's control strategy. The adjustment unit 408, at a future time, controls the vehicle to adjust the temperature according to the control strategy, thereby solving the technical problem of low accuracy in temperature regulation of the energy storage device in the vehicle and achieving the technical effect of improving the accuracy of temperature regulation of the energy storage device in the vehicle.

[0134] According to embodiments of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein the program executes the methods described in the embodiments of the present invention.

[0135] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the methods described in the embodiments of the present invention during runtime.

[0136] According to another aspect of the present invention, an electronic device is also provided. The electronic device includes a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the methods described in the embodiments of the present invention.

[0137] According to another aspect of the present invention, a computer program product is also provided. This computer program product includes a computer program that, when executed by a processor, implements the methods described above in the embodiments of the present invention.

[0138] According to another aspect of the present invention, a vehicle is also provided. The vehicle includes a memory and a processor. The memory stores an executable program; the processor runs the program, which, when executed, implements the methods described in the embodiments of the present invention.

[0139] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0140] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0141] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0142] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0143] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0144] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for temperature regulation of an energy storage device in a vehicle, characterized in that, include: Obtain the status information of the energy storage device in the vehicle at the current moment, wherein the status information is used to represent the operating status of the energy storage device at the current moment; Based on the state information, the temperature of the energy storage device at a future time is determined, wherein the future time is later than the current time; In response to the temperature being in an abnormal temperature range, a control strategy for the vehicle is determined, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy is used to represent the rules for controlling the vehicle to adjust the temperature. At the future time, according to the control strategy, the vehicle is controlled to adjust the temperature, wherein the adjusted temperature is within the normal temperature range, and the operating state corresponding to the normal temperature range is the normal operating state.

2. The method according to claim 1, characterized in that, In response to the temperature being within an abnormal temperature range, a control strategy for the vehicle is determined, including: In response to the temperature being lower than the normal temperature range, it is determined that the temperature is in the abnormal temperature range, and the control strategy corresponding to the temperature being lower than the normal temperature range is determined to be a first control strategy, wherein the first control strategy is used to represent a rule for controlling the vehicle to increase the temperature; In response to the temperature being higher than the normal temperature range, the temperature is determined to be in the abnormal temperature range, and the control strategy corresponding to the temperature being higher than the normal temperature range is determined to be a second control strategy, wherein the second control strategy is used to represent a rule for controlling the vehicle to reduce the temperature.

3. The method according to claim 2, characterized in that, The vehicle includes a cooling module and a heating module. At the future time, according to the control strategy, the vehicle will control the temperature of the energy storage device to be adjusted, including: At the future time, according to the first control strategy, the heating module is controlled to perform a heating operation on the energy storage device to increase the temperature; At the future time, in accordance with the second control strategy, the cooling module is controlled to perform a cooling operation on the energy storage device to reduce the temperature.

4. The method according to claim 1, characterized in that, Based on the state information, determining the temperature of the energy storage device at a future time includes: The state information is input into the dynamic thermal model, which is trained using an artificial intelligence algorithm based on state information samples and temperature samples. Using the dynamic thermal model, based on the state information, the temperature change trend of the energy storage device at the future time is determined, wherein the temperature change trend is used to represent the temperature change over time; Based on the temperature change trend, the temperature of the energy storage device at the future time is determined.

5. The method according to claim 4, characterized in that, The vehicle includes sensors, and the method further includes: Using the sensor, environmental information of the environment in which the energy storage device is located at the current moment is obtained, wherein the environmental information is used to influence the operating state; The vehicle includes a central processing unit, which includes the dynamic thermal model. Using the dynamic thermal model and based on the state information, the temperature change trend of the energy storage device at a future time is determined, including: The central processing unit is controlled to determine the temperature change trend based on the state information and the environmental information using the dynamic thermal model.

6. The method according to claim 1, characterized in that, Obtain the current status information of the energy storage devices in the vehicle, including: In response to activating the vehicle's temperature control function, the status information is obtained.

7. The method according to any one of claims 1 to 6, characterized in that, The vehicle includes an energy storage plate, a cooling module, and a heating module, and the method further includes at least one of the following: In response to the vehicle being turned off, or the light intensity of the environment where the vehicle is located being lower than the light intensity threshold, the energy storage plate provides electrical energy to the cooling module and the heating module. During the temperature adjustment process, the adjustment status is displayed on the graphical user interface associated with the vehicle, wherein the adjustment status is used to indicate the operating status of the components in the vehicle during the temperature adjustment process; The temperature adjustment process can be triggered or stopped in response to a control operation triggered by the target object of the vehicle on the graphical user interface.

8. A temperature regulation device for an energy storage device in a vehicle, characterized in that, The device includes: An acquisition unit is used to acquire the status information of the energy storage device in the vehicle at the current moment, wherein the status information is used to represent the operating status of the energy storage device at the current moment; The first determining unit is configured to determine the temperature of the energy storage device at a future time based on the state information, wherein the future time is later than the current time; The second determining unit is configured to determine the control strategy of the vehicle in response to the temperature being in an abnormal temperature range, wherein the operating state corresponding to the abnormal temperature range is an abnormal operating state, and the control strategy is used to represent the rules for controlling the vehicle to adjust the temperature. The adjustment unit is used to control the vehicle to adjust the temperature according to the control strategy at the future time, wherein the adjusted temperature is within the normal temperature range, and the operating state corresponding to the normal temperature range is the normal operating state.

9. A processor, characterized in that, The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 7 when it runs.

10. An electronic device, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 7.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1 to 7.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1 to 7.

13. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 7.

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