Temperature adjusting method and system based on embedded lithium battery

Abstract

The invention relates to the technical field of lithium battery temperature regulation and control, in particular to a temperature regulation method and system based on an embedded lithium battery. According to the invention, accurate real-time monitoring and dynamic regulation and control of the temperature of the lithium battery are realized by constructing the temperature regulation and control sensing model and the self-adaptive power management system. And a temperature propagation model, a dynamic battery model and a compensation factor are introduced, so that the temperature prediction precision and the system response capability are improved. A comprehensive thermal state evaluation function and an innovative temperature adjusting method are adopted, and comprehensive thermal state evaluation and flexible temperature control are achieved. And the multi-level temperature risk management ensures the safety of the system. The multi-layer and multi-angle temperature control strategy obviously prolongs the service life, safety and performance of the battery, and provides a reliable and efficient energy solution for equipment such as electric automobiles.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery temperature control, and in particular to a temperature control method and system based on an embedded lithium battery. Background Art

[0002] With the rapid development of the electric vehicle industry, lithium-ion batteries as its core power source have received increasing attention. Lithium-ion batteries generate a lot of heat during high-power charging and discharging, and the control and management of battery temperature have become a key factor affecting their performance and safety. In recent years, embedded temperature sensing and intelligent thermal management technologies have been gradually applied to battery systems, which monitor the battery temperature distribution in real time and dynamically adjust the charging and discharging power to maintain the battery operating within the ideal temperature range. At the same time, battery temperature prediction methods based on electrochemical-thermal coupling models have also made significant progress, providing a theoretical basis for precise temperature control. In addition, the application of new thermal management materials such as phase change materials (PCM) has further improved the heat dissipation efficiency and temperature uniformity of battery packs. The performance of electric vehicles depends largely on the performance of their battery packs. Lithium-ion batteries generate a lot of heat during high-power discharge, which in some cases can shorten the battery life or cause safety hazards. This poses a challenge to manufacturing efficient and reliable battery packs for electric vehicles.

[0003] However, the existing lithium battery temperature regulation technology still has many shortcomings. First, most temperature sensing systems use discrete sensor arrangements, which makes it difficult to accurately describe the temperature field inside the battery, resulting in limitations in the formulation of temperature control strategies. Secondly, traditional power management algorithms are often based on simplified thermal models, which fail to fully consider the complex heat conduction mechanism inside the battery and the impact of electrochemical reactions on temperature distribution, reducing the accuracy and real-time performance of temperature control. Furthermore, most existing thermal management systems are passively regulated, making it difficult to adaptively regulate according to the dynamic working state of the battery and environmental changes, and unable to achieve the optimal balance between battery performance and safety. Finally, the lack of in-depth research on the evolution of temperature characteristics throughout the battery life cycle makes it difficult to optimize the temperature management strategy in long-term operation for the battery aging process. In order to obtain the best performance from the battery pack, the thermal management system needs to: adjust the battery to operate within the required temperature range; and reduce the uneven temperature distribution of lithium, which must be used. In order to quantify the impact of temperature on battery performance and thus on electric vehicles, a temperature-dependent battery performance model is required.

[0004] Therefore, there is an urgent need to develop an embedded lithium battery temperature regulation system that integrates intelligent temperature sensing, adaptive power management and closed-loop thermal control to achieve precise control of battery temperature, extend service life and improve safety performance. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is how to solve the problem of regulating the battery to operate within a desired temperature range; and how to solve the problem of uneven temperature distribution of lithium.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a temperature regulation method based on an embedded lithium battery, which includes collecting battery data, building a temperature regulation perception model, and monitoring battery temperature changes in real time through the temperature regulation perception model;

[0009] Adaptive power management is built based on battery temperature changes. The output of the temperature control perception model is used as the input of adaptive power management to dynamically adjust the battery charging and discharging power and optimize battery performance.

[0010] An integrated thermal management system is established by combining the temperature control perception model and adaptive power management. The battery temperature is judged by the threshold output by the temperature control perception model and adaptive power management. The integrated thermal management system prevents battery overheating and accurately controls the battery temperature.

[0011] As a preferred solution of the temperature regulation method based on embedded lithium battery of the present invention, wherein: the battery data is collected, and the battery data includes the temperature of each point inside the battery, the ambient temperature, the battery working state, the battery health state, and other related parameters;

[0012] Battery internal temperature: battery core temperature, battery surface temperature, and temperature distribution at different locations;

[0013] Ambient temperature: the ambient temperature around the battery and the temperature of the cooling system;

[0014] Battery working status: charging current, discharging current, battery voltage;

[0015] Time-related data: temperature change rate, historical temperature data;

[0016] Battery health status: battery cycle times, battery capacity attenuation;

[0017] Other relevant parameters: ambient humidity, vibration data or shock data.

[0018] As a preferred solution of the temperature regulation method based on embedded lithium battery of the present invention, wherein: the battery data is collected, a temperature regulation perception model is constructed, and the battery temperature change is monitored in real time through the temperature regulation perception model; the temperature regulation perception model includes a temperature propagation model, a dynamic battery model and a temperature regulation strategy, and a temperature propagation model is constructed according to the temperature at different positions inside the battery, taking into account the influence of the environment and the heat dissipation system, and the following expression is used:

[0019]

[0020] where Θ(x,t) is the predicted temperature at location x at time t; T env is the ambient temperature; T i is the battery temperature measured by the i-th sensor; x i is the position of the i-th sensor; k i is the attenuation coefficient at position i, indicating how the heat is spread from that point to the rest of the battery; T cool is the temperature of the cooling system; f cool is the contribution of the cooling system temperature to the total temperature, which is a function of time to take into account the change of cooling efficiency over time;

[0021] According to the temperature of different positions inside the battery, including the influence of the battery working state on the battery temperature, a dynamic battery model can be constructed, which uses the following expression:

[0022]

[0023] Where Q(t) is the heat generation at time t; η is the thermal efficiency coefficient; I charge and I discharge are the charge and discharge currents respectively; R(T) is

[0024] The internal resistance of the battery at temperature T depends on the internal temperature and can be estimated using a weighted average;

[0025] The working state of the battery is adjusted by combining the output of the temperature propagation model and the dynamic battery model to achieve real-time adjustment of the charge and discharge current, self-adjustment based on instant temperature feedback, and use integral control to compensate for the previous temperature error, thereby controlling the battery temperature to maintain the temperature within a safe range, extend the battery life and ensure safe operation. The following expression is used:

[0026]

[0027] Among them, I adj (t) is the adjusted charge or discharge current; K p , K i are proportional and integral gains, T targetIt is used for PID controller; is the target temperature; is the average temperature of the battery.

[0028] As a preferred solution of the temperature regulation method based on embedded lithium battery of the present invention, wherein: the adaptive power management is constructed according to the battery temperature change, the output of the temperature control perception model is used as the input of the adaptive power management, the battery charging and discharging power is dynamically adjusted, and the battery performance is optimized;

[0029] The adaptive power management includes acquiring temperature data from a temperature control model, constructing a power adjustment model according to the acquired temperature data, further optimizing the power adjustment model by introducing temperature impact compensation, and combining the basic power adjustment model and temperature impact compensation to obtain the final charge and discharge power;

[0030] Get temperature data from the temperature control model. First, use the average temperature of the battery in the previously defined temperature control model as the basic input of this model. By obtaining the real-time temperature information of the battery as the basis for dynamically adjusting the power, the charging and discharging power is dynamically adjusted according to the battery temperature to build a power adjustment model.

[0031] Use the following expression:

[0032]

[0033] Where P(t) is the charge and discharge power at time t, P0 is the base power, which is the maximum charge and discharge power of the battery under standard operating conditions; T target is the target temperature, is the average battery temperature obtained from the temperature control model, τ is the temperature response constant, which is used to adjust the sensitivity of the power response;

[0034] Base power adjustment: Use an exponential decay function to adjust the base power, ensuring that the relationship between power adjustment and battery temperature is nonlinear to accommodate the high sensitivity of battery temperature to performance;

[0035] The power adjustment model is further optimized by introducing temperature impact compensation. The temperature impact compensation includes introducing a compensation factor to cope with the performance fluctuations that may occur when the temperature changes rapidly. The compensation factor is used to smoothly adjust the power transition and reduce the impact caused by the rapid temperature change. It uses the following expression:

[0036]

[0037] Where C(t) is the compensation factor at time t; κ is the compensation coefficient, which is used to adjust the degree of compensation; is the rate of change of battery temperature, obtained from the temperature control model;

[0038] Combining the basic power adjustment and temperature effect compensation, the final charge and discharge power is obtained, and the power output after comprehensive adjustment is: The final power takes into account the basic power adjustment and compensation for temperature changes to ensure that the battery can maintain optimal performance under all operating conditions. It uses the following expression:

[0039] P final (t) = P(t)·(1+C(t))

[0040] Among them, P final (t) is the final adjusted power.

[0041] As a preferred solution of the temperature regulation method based on embedded lithium battery described in the present invention, wherein: the integrated thermal management system is established by combining the temperature regulation perception model and adaptive power management, the battery temperature is judged by the threshold value output by the temperature regulation perception model and adaptive power management, the battery overheating is prevented according to the integrated thermal management system, and the battery temperature is accurately regulated;

[0042] The integrated thermal management system includes defining a comprehensive thermal state evaluation function, a temperature regulation strategy, and a final charge and discharge strategy adjustment;

[0043] The comprehensive thermal state evaluation function evaluates the thermal state of the battery by combining the temperature deviation and the power output, ensuring dynamic adjustment according to the actual performance of the battery, and accurately evaluating the instantaneous thermal environment of the battery. A thermal state evaluation function is defined. The thermal state evaluation function evaluates the thermal state of the battery based on the output of the intelligent temperature perception model and the adaptive power management, and adopts the following expression:

[0044]

[0045] Where Z(t) is the comprehensive thermal state evaluation at time t; T actual (t) is the actual temperature obtained by the temperature control perception model; T target is the target operating temperature of the battery; P final (t) is the power adjustment value obtained from the adaptive power management system; is the adjustment coefficient, and λ, μ, and ν are used to balance the influence of temperature deviation and power output, respectively.

[0046] As a preferred solution of the temperature regulation method based on embedded lithium battery of the present invention, the temperature regulation strategy realizes dynamic adjustment of temperature by combining hyperbolic tangent function and sine function. The hyperbolic tangent function provides a smooth and effective regulation mechanism. The sine function introduces periodic regulation to adapt to the fluctuation of ambient temperature. According to the output of thermal state evaluation function, the regulation strategy of battery temperature is defined, which adopts the following expression:

[0047] Radjust (t)=δ·tanh(Z(t))+∈·sin(ω·t)

[0048] Among them, R adjust (t) is the temperature regulation strategy at time t; δ,∈,

[0049] ω is the regulation coefficient, which is used to adjust the sensitivity of the response and introduce periodic regulation to cope with external temperature fluctuations;

[0050] The final charge and discharge strategy adjustment ensures that the battery can maintain optimal performance and safe operation under various operating conditions by comprehensively considering the effects of power management and temperature regulation. According to the output of the thermal state evaluation function, the battery temperature regulation strategy is defined, which adopts the following expression:

[0051] P updated (t) = P final (t)·(1+R adjust (t))

[0052] Among them, P updated (t) is the final adjusted power after temperature regulation.

[0053] As a preferred solution of the temperature regulation method based on embedded lithium batteries described in the present invention, when the battery temperature is less than the first threshold, the battery temperature risk level is judged to be low risk; the system will monitor the real-time temperature of the battery, and confirm through the intelligent temperature perception model that the temperature is lower than the safety threshold, and it is judged to be a low risk state at this time; at the same time, a regular performance report is sent to the maintenance department, and a low alarm state is displayed through the user interface for routine risk awareness and basic maintenance training.

[0054] When the first threshold is less than the battery temperature and less than the second threshold, the battery temperature risk level is judged to be medium risk; the intelligent temperature perception model detects that the battery temperature is between the first threshold and the second threshold, and the adaptive power management system adjusts the charging and discharging power according to the current temperature; at the same time, an early warning message is sent to the technical support department, and a medium-intensity alarm is generated and displayed through the system interface for risk communication and primary emergency drills. In addition, the early warning response plan is initiated to prepare for corresponding technical interventions;

[0055] When the battery temperature is greater than the second threshold: the battery temperature risk level is judged to be high risk; when the temperature exceeds the second threshold, ITMS immediately conducts an advanced assessment, and the adaptive power management system performs emergency power adjustments to reduce the temperature to a safe range as quickly as possible. At the same time, emergency warning information is sent to all relevant departments and users, and the system interface generates and displays a high-intensity virtual alarm scene for evacuation and rescue strategy formulation. At the same time, the system automatically starts + emergency cooling procedures and other necessary emergency response measures.

[0056] In a second aspect, an embodiment of the present invention provides a temperature regulation system based on an embedded lithium battery, which includes:

[0057] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the temperature regulation method based on the embedded lithium battery as described in the first aspect of the present invention are implemented.

[0058] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the temperature regulation method based on an embedded lithium battery as described in the first aspect of the present invention are implemented.

[0059] The beneficial effect of the present invention is that by collecting battery data and building a temperature control perception model, real-time monitoring of battery temperature changes is achieved. This method not only improves the accuracy of temperature monitoring, but also captures subtle changes in the temperature distribution inside the battery, providing an accurate data basis for subsequent temperature control, thereby greatly improving the response speed and control accuracy of the entire system.

[0060] By using the output of the temperature control perception model as the input of adaptive power management, dynamic adjustment of charging and discharging power is achieved. This closed-loop control mechanism can quickly adjust the working state of the battery according to real-time temperature changes, effectively preventing local overheating and significantly improving the service life and safety of the battery.

[0061] By combining the temperature control perception model and adaptive power management to establish an integrated thermal management system, precise control of battery temperature is achieved. This integrated approach can not only prevent battery overheating, but also maintain the optimal operating temperature of the battery under various complex working conditions, thereby maximizing the performance output of the battery and preventing battery degradation caused by thermal stress.

[0062] By introducing the temperature propagation model and dynamic battery model, the system can more accurately predict the temperature distribution and change trend inside the battery. This method takes into account the heat conduction mechanism inside the battery and the impact of electrochemical reactions on temperature, greatly improving the accuracy of temperature prediction and making it possible to formulate more sophisticated temperature control strategies.

[0063] By introducing compensation factors to optimize the power adjustment model, the system can better cope with rapid temperature changes. This approach improves the system's dynamic response capability and reduces the performance loss and safety risks that may be caused by drastic temperature fluctuations.

[0064] By defining a comprehensive thermal state evaluation function, the system can comprehensively evaluate the thermal state of the battery. This method not only takes into account temperature deviation, but also combines the influence of power output, allowing the system to more comprehensively grasp the working state of the battery and thus formulate a more reasonable temperature control strategy.

[0065] By introducing a combination of hyperbolic tangent function and sine function for temperature regulation, dynamic fine adjustment of temperature is achieved. This innovative regulation method not only ensures the smoothness of regulation, but also adapts to the periodic fluctuations of ambient temperature, greatly improving the flexibility and adaptability of temperature control.

[0066] By setting different temperature thresholds and corresponding risk levels, the system can achieve multi-level temperature risk management. This hierarchical management method not only improves the safety of the system, but also takes corresponding measures according to different risk levels, achieving reasonable allocation of resources and optimization of system response.

[0067] In summary, our solution is based on the temperature regulation method and system of embedded lithium batteries, which realizes the precise regulation of battery temperature through multi-level and multi-angle temperature monitoring and control strategies. It not only improves the service life and safety of the battery, but also optimizes the performance output of the battery, providing a more reliable and efficient energy solution for electric vehicles and other equipment using lithium batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0069] Figure 1 A flow chart of a temperature regulation method based on an embedded lithium battery;

[0070] Figure 2 A diagram of a computer device based on a temperature regulation method for an embedded lithium battery. DETAILED DESCRIPTION

[0071] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0072] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0073] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0074] Example 1

[0075] Reference Figure 1-2 , which is the first embodiment of the present invention, provides a temperature regulation method based on an embedded lithium battery, comprising:

[0076] S100: Collect battery data, build a temperature control perception model, and monitor battery temperature changes in real time through the temperature control perception model;

[0077] S101: collecting battery data, the battery data including the temperature of each point inside the battery, the ambient temperature, the battery working status, the battery health status, and other related parameters;

[0078] Battery internal temperature: battery core temperature, battery surface temperature, and temperature distribution at different locations;

[0079] Ambient temperature: the ambient temperature around the battery and the temperature of the cooling system;

[0080] Battery working status: charging current, discharging current, battery voltage;

[0081] Time-related data: temperature change rate, historical temperature data;

[0082] Battery health status: battery cycle times, battery capacity attenuation;

[0083] Other relevant parameters: ambient humidity, vibration data or shock data.

[0084] S102: The battery data is collected, a temperature control perception model is constructed, and the battery temperature change is monitored in real time through the temperature control perception model; the temperature control perception model includes a temperature propagation model, a dynamic battery model, and a temperature control strategy. According to the temperature at different positions inside the battery, the temperature propagation model is constructed taking into account the influence of the environment and the heat dissipation system, and the following expression is used:

[0085]

[0086] where Θ(x,t) is the predicted temperature at location x at time t; T env is the ambient temperature; T i is the battery temperature measured by the i-th sensor; x iis the position of the i-th sensor; k i is the attenuation coefficient at position i, indicating how the heat is spread from that point to the rest of the battery; T cool is the temperature of the cooling system; f cool is the contribution of the cooling system temperature to the total temperature, which is a function of time to take into account the change of cooling efficiency over time;

[0087] According to the temperature of different positions inside the battery, including the influence of the battery working state on the battery temperature, a dynamic battery model can be constructed, which uses the following expression:

[0088]

[0089] Where Q(t) is the heat generation at time t; η is the thermal efficiency coefficient; I charge and I discharge are the charge and discharge currents, respectively; R(T) is the internal resistance of the battery at temperature T, which depends on the internal temperature and can be estimated using a weighted average;

[0090] The working state of the battery is adjusted by combining the output of the temperature propagation model and the dynamic battery model to achieve real-time adjustment of the charge and discharge current, self-adjustment based on instant temperature feedback, and use integral control to compensate for the previous temperature error, thereby controlling the battery temperature to maintain the temperature within a safe range, extend the battery life and ensure safe operation. The following expression is used:

[0091]

[0092] Among them, I adj (t) is the adjusted charge or discharge current; K p ,

[0093] K i are proportional and integral gains, T target It is used for PID controller; is the target temperature; is the average temperature of the battery. S102: The battery data is collected to build a temperature control perception model, and the battery temperature change is monitored in real time through the temperature control perception model; the temperature control perception model includes a temperature propagation model, a dynamic battery model and a temperature control strategy. According to the temperature of different positions inside the battery, taking into account the influence of the environment and the heat dissipation system, a temperature propagation model is built, which uses the following expression:

[0094]

[0095] where Θ(x,t) is the predicted temperature at location x at time t; T env is the ambient temperature; T i is the battery temperature measured by the i-th sensor; x iis the position of the i-th sensor; k i is the attenuation coefficient at position i, indicating how the heat is spread from that point to the rest of the battery; T cool is the temperature of the cooling system; f cool is the contribution of the cooling system temperature to the total temperature, which is a function of time to take into account the change of cooling efficiency over time;

[0096] According to the temperature of different positions inside the battery, including the influence of the battery working state on the battery temperature, a dynamic battery model can be constructed, which uses the following expression:

[0097]

[0098] Where Q(t) is the heat generation at time t; η is the thermal efficiency coefficient; I charge and I discharge are the charge and discharge currents respectively; R(T) is

[0099] The internal resistance of the battery at temperature T depends on the internal temperature and can be estimated using a weighted average;

[0100] The working state of the battery is adjusted by combining the output of the temperature propagation model and the dynamic battery model to achieve real-time adjustment of the charge and discharge current, self-adjustment based on instant temperature feedback, and use integral control to compensate for the previous temperature error, thereby controlling the battery temperature to maintain the temperature within a safe range, extend the battery life and ensure safe operation. The following expression is used:

[0101]

[0102] Among them, I adj (t) is the adjusted charge or discharge current; K p , K i are proportional and integral gains, T target It is used for PID controller; is the target temperature; is the average temperature of the battery.

[0104] S200: Build adaptive power management based on battery temperature changes, use the output of the temperature control perception model as the input of adaptive power management, dynamically adjust battery charging and discharging power, and optimize battery performance;

[0105] S201: constructing adaptive power management according to battery temperature changes, using the output of the temperature control perception model as input of the adaptive power management, dynamically adjusting the battery charging and discharging power, and optimizing battery performance;

[0106] The adaptive power management includes acquiring temperature data from a temperature control model, constructing a power adjustment model according to the acquired temperature data, further optimizing the power adjustment model by introducing temperature impact compensation, and combining the basic power adjustment model and temperature impact compensation to obtain the final charge and discharge power;

[0107] Get temperature data from the temperature control model. First, use the average temperature of the battery in the previously defined temperature control model as the basic input of this model. Get the real-time temperature information of the battery as the basis for dynamically adjusting the power. Dynamically adjust the charge and discharge power according to the battery temperature. Construct a power adjustment model using the following expression:

[0108]

[0109] Where P(t) is the charge and discharge power at time t, P0 is the base power, which is the maximum charge and discharge power of the battery under standard operating conditions; T target is the target temperature, is the average battery temperature obtained from the temperature control model, τ is the temperature response constant, which is used to adjust the sensitivity of the power response;

[0110] Base power adjustment: Use an exponential decay function to adjust the base power, ensuring that the relationship between power adjustment and battery temperature is nonlinear to accommodate the high sensitivity of battery temperature to performance;

[0111] The power adjustment model is further optimized by introducing temperature impact compensation. The temperature impact compensation includes introducing a compensation factor to cope with the performance fluctuation that may occur when the temperature changes rapidly. The compensation factor is used to smoothly adjust the power transition and reduce the impact caused by the rapid temperature change. It uses the following expression:

[0112]

[0113] Where C(t) is the compensation factor at time t; κ is the compensation coefficient, which is used to adjust the degree of compensation; is the rate of change of battery temperature, obtained from the temperature control model;

[0114] Combining the basic power adjustment and temperature effect compensation, the final charge and discharge power is obtained, and the power output after comprehensive adjustment is: The final power takes into account the basic power adjustment and compensation for temperature changes to ensure that the battery can maintain optimal performance under all operating conditions. It uses the following expression:

[0115] P final (t) = P(t)·(1+C(t))

[0116] Among them, P final (t) is the final adjusted power.

[0117] S300: Establish an integrated thermal management system by combining the temperature control perception model and adaptive power management. Determine the battery temperature by combining the output threshold of the temperature control perception model and adaptive power management. Prevent battery overheating according to the integrated thermal management system and precisely control the battery temperature.

[0118] S301: establishing an integrated thermal management system by combining the temperature control perception model and the adaptive power management, judging the battery temperature by combining the threshold output by the temperature control perception model and the adaptive power management, preventing the battery from overheating according to the integrated thermal management system, and accurately controlling the battery temperature;

[0119] The integrated thermal management system includes defining a comprehensive thermal state evaluation function, a temperature regulation strategy, and a final charge and discharge strategy adjustment;

[0120] The comprehensive thermal state evaluation function evaluates the thermal state of the battery by combining the temperature deviation and the power output, ensuring dynamic adjustment according to the actual performance of the battery, and accurately evaluating the instantaneous thermal environment of the battery. A thermal state evaluation function is defined. The thermal state evaluation function evaluates the thermal state of the battery based on the output of the intelligent temperature perception model and the adaptive power management, and adopts the following expression:

[0121]

[0122] Where Z(t) is the comprehensive thermal state evaluation at time t; T actual (t) is the actual temperature obtained by the temperature control perception model; T target is the target operating temperature of the battery; P final (t) is the power adjustment value obtained from the adaptive power management system; is the adjustment coefficient, and λ, μ, and ν are used to balance the influence of temperature deviation and power output, respectively.

[0123] S302: The temperature regulation strategy uses a combination of a hyperbolic tangent function and a sine function to achieve dynamic temperature adjustment. The hyperbolic tangent function provides a smooth and effective regulation mechanism, and the sine function introduces periodic regulation to adapt to ambient temperature fluctuations. According to the output of the thermal state evaluation function, the battery temperature regulation strategy is defined, which uses the following expression:

[0124] R adjust (t)=δ·tanh(Z(t))+∈·sin(ω·t)

[0125] Among them, R adjust (t) is the temperature regulation strategy at time t;,δ,∈,ω,is the regulation coefficient, which is used to adjust the sensitivity of the response and introduce periodic regulation to cope with external temperature fluctuations;

[0126] The final charge and discharge strategy adjustment ensures that the battery can maintain optimal performance and safe operation under various operating conditions by comprehensively considering the effects of power management and temperature regulation. According to the output of the thermal state evaluation function, the battery temperature regulation strategy is defined, which adopts the following expression:

[0127] P updated (t) = P final (t)·(1+R adjust (t))

[0128] Among them, P updated (t) is the final adjusted power after temperature regulation.

[0129] S303: When the battery temperature is less than the first threshold: the battery temperature risk level is judged to be low risk; the system will monitor the real-time temperature of the battery, and confirm through the intelligent temperature perception model that the temperature is lower than the safety threshold, and it is judged to be a low risk state at this time; at the same time, a regular performance report is sent to the maintenance department, and a low alarm state is displayed through the user interface for routine risk awareness and basic maintenance training.

[0130] When the first threshold is less than the battery temperature and less than the second threshold, the battery temperature risk level is judged to be medium risk; the intelligent temperature perception model detects that the battery temperature is between the first threshold and the second threshold, and the adaptive power management system adjusts the charging and discharging power according to the current temperature; at the same time, an early warning message is sent to the technical support department, and a medium-intensity alarm is generated and displayed through the system interface for risk communication and primary emergency drills. In addition, the early warning response plan is initiated to prepare for corresponding technical interventions;

[0131] When the battery temperature is greater than the second threshold: the battery temperature risk level is judged to be high risk; when the temperature exceeds the second threshold, ITMS immediately conducts an advanced assessment, and the adaptive power management system performs emergency power adjustments to reduce the temperature to a safe range as quickly as possible. At the same time, emergency warning information is sent to all relevant departments and users, and the system interface generates and displays a high-intensity virtual alarm scene for evacuation and rescue strategy formulation. At the same time, the system automatically starts + emergency cooling procedures and other necessary emergency response measures.

[0132] Furthermore, this embodiment also provides a temperature regulation system based on an embedded lithium battery, comprising:

[0133] The acquisition module collects battery data, builds a temperature control perception model, and monitors battery temperature changes in real time through the temperature control perception model;

[0134] Building modules, building adaptive power management according to battery temperature changes, using the output of the temperature control perception model as the input of adaptive power management, dynamically adjusting battery charging and discharging power, and optimizing battery performance;

[0135] The control module establishes an integrated thermal management system by combining the temperature control perception model and adaptive power management. The battery temperature is judged by the threshold output by the temperature control perception model and adaptive power management. The battery overheating is prevented according to the integrated thermal management system, and the battery temperature is precisely controlled.

[0136] This embodiment also provides a computer device, which is suitable for the temperature regulation method based on an embedded lithium battery, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to implement the temperature regulation method based on an embedded lithium battery as proposed in the above embodiment.

[0137] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0138] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the temperature regulation method based on an embedded lithium battery as proposed in the above embodiment is implemented.

[0139] In summary, by collecting battery data and building a temperature control perception model, real-time monitoring of battery temperature changes is achieved. This method not only improves the accuracy of temperature monitoring, but also captures subtle changes in the temperature distribution inside the battery, providing an accurate data basis for subsequent temperature control, thereby greatly improving the response speed and control accuracy of the entire system.

[0140] By using the output of the temperature control perception model as the input of adaptive power management, dynamic adjustment of charging and discharging power is achieved. This closed-loop control mechanism can quickly adjust the working state of the battery according to real-time temperature changes, effectively preventing local overheating and significantly improving the service life and safety of the battery.

[0141] By combining the temperature control perception model and adaptive power management to establish an integrated thermal management system, precise control of battery temperature is achieved. This integrated approach can not only prevent battery overheating, but also maintain the optimal operating temperature of the battery under various complex working conditions, thereby maximizing the performance output of the battery and preventing battery degradation caused by thermal stress.

[0142] By introducing the temperature propagation model and dynamic battery model, the system can more accurately predict the temperature distribution and change trend inside the battery. This method takes into account the heat conduction mechanism inside the battery and the impact of electrochemical reactions on temperature, greatly improving the accuracy of temperature prediction and making it possible to formulate more sophisticated temperature control strategies.

[0143] By introducing compensation factors to optimize the power adjustment model, the system can better cope with rapid temperature changes. This approach improves the system's dynamic response capability and reduces the performance loss and safety risks that may be caused by drastic temperature fluctuations.

[0144] By defining a comprehensive thermal state evaluation function, the system can comprehensively evaluate the thermal state of the battery. This method not only takes into account temperature deviation, but also combines the influence of power output, allowing the system to more comprehensively grasp the working state of the battery and thus formulate a more reasonable temperature control strategy.

[0145] By introducing a combination of hyperbolic tangent function and sine function for temperature regulation, dynamic fine adjustment of temperature is achieved. This innovative regulation method not only ensures the smoothness of regulation, but also adapts to the periodic fluctuations of ambient temperature, greatly improving the flexibility and adaptability of temperature control.

[0146] By setting different temperature thresholds and corresponding risk levels, the system can achieve multi-level temperature risk management. This hierarchical management method not only improves the safety of the system, but also takes corresponding measures according to different risk levels, achieving reasonable allocation of resources and optimization of system response.

[0147] In summary, our solution is based on the temperature regulation method and system of embedded lithium batteries, which realizes the precise regulation of battery temperature through multi-level and multi-angle temperature monitoring and control strategies. It not only improves the service life and safety of the battery, but also optimizes the performance output of the battery, providing a more reliable and efficient energy solution for electric vehicles and other equipment using lithium batteries.

[0148] Example 2

[0149] Reference Figure 1 - Figure 2, which is the second embodiment of the present invention, and this embodiment provides a temperature regulation method based on an embedded lithium battery. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0150] In order to verify the effectiveness of the temperature regulation method based on embedded lithium batteries proposed in the present invention, a large-capacity lithium-ion battery pack for electric vehicles was selected for testing. The battery pack consists of 100 single cells connected in series and parallel, with a total capacity of 100kWh and a rated voltage of 400V. First, 20 high-precision temperature sensors were installed at key positions of the battery pack to monitor the temperature distribution inside the battery in real time. At the same time, ambient temperature sensors and heat dissipation system temperature sensors were installed outside the battery pack. In order to comprehensively evaluate the battery performance, monitoring equipment for parameters such as current, voltage, and number of cycles is also equipped.

[0151] The testing process is divided into three stages: standard operating condition test, extreme operating condition test and long-term cycle test. In the standard operating condition test, the battery pack is charged and discharged at 0.5C, 1C and 2C rates at an ambient temperature of 25°C, and 50 cycles are performed at each rate. The extreme operating condition test includes a -20°C low temperature start test and a 45°C high temperature fast charge test. The long-term cycle test is carried out in a simulated actual use environment, including a combination of different temperatures and different charge and discharge rates, lasting 6 months, with a total of 1,000 complete charge and discharge cycles.

[0152] During the test, the temperature control perception model of the present invention processes the data from each sensor in real time. The temperature propagation model uses formula (1) to predict the temperature distribution inside the battery pack, which takes into account the data of 20 temperature sensors, the ambient temperature and the influence of the cooling system. The dynamic battery model calculates the heat generation according to formula (2), combined with the current charge and discharge state and the internal resistance of the battery. The temperature control strategy adjusts the charge and discharge current in real time through formula (3) to maintain the optimal operating temperature.

[0153] The adaptive power management system uses formula (4) to dynamically adjust the charge and discharge power according to the output of the temperature control perception model. In order to cope with the rapid temperature change, the temperature impact compensation factor is introduced, as shown in formula (5). The final charge and discharge power is determined by formula (6), ensuring that the battery can maintain optimal performance under various working conditions.

[0154] The integrated thermal management system combines the outputs of the temperature control perception model and the adaptive power management. The thermal state evaluation function defined by equation (7) comprehensively evaluates the instantaneous thermal environment of the battery. The temperature regulation strategy adopts an innovative combination of hyperbolic tangent function and sine function, as shown in equation (8), to achieve smooth and flexible temperature regulation. The final charge and discharge strategy is determined by equation (9), which comprehensively considers the effects of power management and temperature regulation.

[0155] In addition, the system also sets up a three-level temperature risk management mechanism. When the temperature is below 35℃, it is judged as low risk; when the temperature is between 35℃ and 45℃, it is judged as medium risk and the early warning mechanism is activated; when the temperature exceeds 45℃, it is judged as high risk and emergency cooling measures are taken immediately.

[0156] The test results are shown in the following table:

[0157]

[0158] By analyzing the above data, we can draw the following conclusions:

[0159] Temperature uniformity is significantly improved: Under standard operating conditions, the method of the present invention reduces the maximum temperature difference inside the battery pack from 8.5°C to 3.2°C, an improvement of 62.4%. This significant improvement is due to the accurate prediction of the temperature propagation model and the dynamic adjustment of the adaptive power management system. The uniformity of temperature distribution is crucial to extending battery life and improving safety, as it can effectively reduce local overheating and overcooling and reduce internal stress of the battery.

[0160] Extreme temperature adaptability is greatly improved: In a low temperature environment of -20°C, the method of the present invention shortens the battery startup time from 180 seconds to 75 seconds, an increase of 58.3%. This is mainly due to the rapid response of the temperature control perception model to the low temperature environment and the intelligent preheating strategy of the adaptive power management system. The fast charging performance in a high temperature environment of 45°C has also been significantly improved, and the time to charge to 80% has been reduced from 45 minutes to 28 minutes, an increase of 37.8%. This excellent performance in extreme temperatures has greatly expanded the applicability of electric vehicles in various climate conditions.

[0161] The cycle life is significantly extended: After 1,000 complete charge and discharge cycles, the battery pack capacity retention rate using the method of the present invention reaches 91%, which is 11 percentage points higher than the traditional method. This result fully proves that the present invention effectively maintains the health of the battery during long-term use. Through precise temperature control and intelligent charge and discharge strategies, the aging speed of the battery is effectively slowed down, providing users with a more lasting use experience.

[0162] Improved charging efficiency: The average charging efficiency increased from 89% to 94%, an increase of 5.6%. This improvement is mainly due to the adaptive power management system's optimized control of the charging process, and the temperature control strategy's effective management of heat generated during the charging process. Higher charging efficiency not only means shorter charging time, but also reduces energy loss during charging and improves overall energy utilization.

[0163] Safety performance is greatly improved: The temperature-related failure rate is reduced from 3.5 times / 1000 cycles to 0.8 times / 1000 cycles, a decrease of 77.1%. This significant improvement is mainly due to the multi-level temperature risk management mechanism and precise temperature control strategy of the present invention. Through real-time monitoring and early warning, the system can take preventive measures before temperature anomalies occur, greatly reducing the probability of safety accidents.

[0164] Both energy density and power density have been improved: energy density has increased from 220Wh / kg to 238Wh / kg, an increase of 8.2%; power density has increased from 2000W / kg to 2350W / kg, an increase of 17.5%. This comprehensive performance improvement proves that the present invention can not only effectively manage battery temperature, but also tap the potential performance of the battery by optimizing the working state. Higher energy density and power density mean that electric vehicles can achieve longer driving range and stronger acceleration performance at the same weight.

[0165] In summary, the temperature regulation method based on embedded lithium batteries proposed in the present invention has shown significant advantages in multiple key indicators. It not only improves the service life and safety of the battery, but also achieves comprehensive improvements in extreme environmental adaptability, charging efficiency and overall performance. This comprehensive improvement provides strong technical support for the development of the electric vehicle industry and is expected to promote the popularization of electric vehicles in a wider range of application scenarios.

[0166] Example 3

[0167] Reference Figure 1 - Figure 2 , which is the third embodiment of the present invention, and this embodiment provides a temperature regulation method based on an embedded lithium battery. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0168] The magnitude of the total heat generation rate from the battery pack under load determines the size and design of the cooling system. In a battery cell, heat is generated by (i) entropy changes from electrochemical reactions and (ii) the Joule effect (or Ohmic heating) caused by the transfer of current across internal resistances. The heat generation rate in a battery can be calculated by:

[0169] q=I(E oc -V)-ITdE oc / dT)

[0170] Where q is the rate of heat generation, I is the current (I>0 for discharge and I<0 for charge), Eoc is the equilibrium cell voltage or open circuit potential, V is the cell voltage, T is the temperature, and dEoc / dT is the temperature coefficient. The first term, I(Eoc-V), is the heat generation due to the ohmic resistance and other internal resistances present in the battery, and the second term, IT[dEoc / dT), is the heat generated or consumed due to the reversible entropy change produced by the battery's electrochemical reactions.

[0171] Different types of lithium-ion batteries have different values ​​of internal resistance and entropy change. Thermal management strategies require accurate determination of these data. Since the internal resistance depends on the temperature and SOC of the battery, it should be measured under various battery operating conditions. The equivalent internal resistance of flat batteries currently used in electric vehicles is proprietary and not available in the open literature. However, this parameter has been measured for commercially available small-sized lithium-ion batteries, which are very similar to flat batteries in structure. In this work, experimentally measured internal resistance data of the cylindrical SONY-US18650

[10] as a function of SOC and temperature are analyzed. These experimental data are used for numerically implemented curve fitting, from which the battery internal resistance calculation formula can be obtained as shown in the following formula:

[0172] R i =2.258×10 -6 SOC -0.3952 T=20℃

[0173] R i =1.857×10 -6 SOC -0.2787 T=30℃

[0174] R i =1.659×10 -6 SOC -0.1692 T=40℃

[0175] According to thermodynamic theory, the entropy change ΔS was obtained by measuring the dependence of the battery open circuit voltage on different SOC temperatures:

[0176]

[0177] The experimental results show that within the temperature range of 20 to 40°C, ΔS is almost independent of temperature, and the change of ΔS with SOC approximately conforms to the following equation:

[0178] ΔS=99.88SOC-76.67 0≤SOC≤0.77

[0179] ΔS=30 0.77<SOC≤87

[0180] ΔS=-20 0.87<SOC≤1

[0181] Taking this into account, the equation can be modified and the internal heat generation rate in the power generation area of ​​a lithium-ion battery during discharge can be expressed as:

[0182]

[0183] Compared with the traditional battery heat dissipation calculation formula, the simplified formula can be calculated only by experimentally measured data. This method simplifies the heat calculation method and reduces the parameter input of the formula. This method helps to achieve accurate embedded thermal management of lithium batteries.

[0184] By fitting the numerical curve with the experimental data, the calculation formula of the battery internal resistance can be obtained;

[0185] In the temperature range of 20 to 40°C, ΔS is almost independent of temperature, and the equation of ΔS changing with SOC can be approximately simplified.

[0186] A simplified equation for calculating the heat generation rate of a battery in experimental analysis mainly includes experimental fitting of a battery internal resistance calculation formula and approximate processing of entropy change ΔS.

[0187] The battery internal resistance calculation formula according to claim 1 is characterized in that the relationship between the battery internal resistance and the battery SOC is obtained by fitting known experimental data.

[0188] The approximate processing of entropy change ΔS according to claim 2 is characterized in that the relationship between ΔS and SOC in the temperature range of 20 to 40°C is obtained through experimental results.

[0189] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A temperature regulation method based on an embedded lithium battery, characterized in that: include, Collect battery data, build a temperature control perception model, and use the temperature control perception model to monitor battery temperature changes in real time; Adaptive power management is built based on battery temperature changes. The output of the temperature control perception model is used as the input of adaptive power management to dynamically adjust the battery charging and discharging power and optimize battery performance. An integrated thermal management system is established by combining the temperature control perception model and adaptive power management. The battery temperature is judged by the threshold output by the temperature control perception model and adaptive power management. The integrated thermal management system prevents battery overheating and accurately controls the battery temperature.

2. The temperature regulation method based on embedded lithium battery according to claim 1, characterized in that: The collected battery data includes the temperature of each point inside the battery, the ambient temperature, the battery working status, the battery health status, and other related parameters; Battery internal temperature: battery core temperature, battery surface temperature, and temperature distribution at different locations; Ambient temperature: the ambient temperature around the battery and the temperature of the cooling system; Battery working status: charging current, discharging current, battery voltage; Time-related data: temperature change rate, historical temperature data; Battery health status: battery cycle times, battery capacity attenuation; Other relevant parameters: ambient humidity, vibration data or shock data.

3. The temperature regulation method based on embedded lithium battery according to claim 2, characterized in that: The battery data is collected, a temperature control perception model is constructed, and the battery temperature change is monitored in real time through the temperature control perception model; the temperature control perception model includes a temperature propagation model, a dynamic battery model and a temperature control strategy. According to the temperature at different positions inside the battery, the temperature propagation model is constructed taking into account the influence of the environment and the heat dissipation system, and the following expression is used: where Θ(x,t) is the predicted temperature at location x at time t; T env is the ambient temperature; T i is the battery temperature measured by the i-th sensor; x i is the position of the i-th sensor; k i is the attenuation coefficient at position i, indicating how the heat is spread from that point to the rest of the battery; T cool is the temperature of the cooling system; f cool is the contribution of the cooling system temperature to the total temperature, which is a function of time to take into account the change of cooling efficiency over time; According to the temperature of different positions inside the battery, including the influence of the battery working state on the battery temperature, a dynamic battery model can be constructed, which uses the following expression: Where Q(t) is the heat generation at time t; η is the thermal efficiency coefficient; I charge and I discharge are the charge and discharge currents respectively; R(T) is The internal resistance of the battery at temperature T depends on the internal temperature and can be estimated using a weighted average; The working state of the battery is adjusted by combining the output of the temperature propagation model and the dynamic battery model to achieve real-time adjustment of the charge and discharge current, self-adjustment based on instant temperature feedback, and use integral control to compensate for the previous temperature error, thereby controlling the battery temperature to maintain the temperature within a safe range, extend the battery life and ensure safe operation. The following expression is used: Among them, I adj (t) is the adjusted charge or discharge current; K p , K i are proportional and integral gains, T target It is used for PID controller; is the target temperature; is the average temperature of the battery.

4. The temperature regulation method based on embedded lithium battery according to claim 3, characterized in that: The adaptive power management is constructed according to the battery temperature change, and the output of the temperature control perception model is used as the input of the adaptive power management to dynamically adjust the battery charging and discharging power and optimize the battery performance; The adaptive power management includes acquiring temperature data from a temperature control model, constructing a power adjustment model according to the acquired temperature data, further optimizing the power adjustment model by introducing temperature impact compensation, and combining the basic power adjustment model and temperature impact compensation to obtain the final charge and discharge power; Get temperature data from the temperature control model. First, use the average temperature of the battery in the previously defined temperature control model as the basic input of this model. Get the real-time temperature information of the battery as the basis for dynamically adjusting the power. Dynamically adjust the charge and discharge power according to the battery temperature. Construct a power adjustment model using the following expression: Among them, P(t) is the charge and discharge power at time t, P0 is Basic power, which is the maximum charge and discharge power of the battery under standard operating conditions; T target yes Target temperature; yes The average battery temperature obtained from the temperature control model; τ temperature response constant, used to adjust the sensitivity of power response; Base power adjustment: Use an exponential decay function to adjust the base power, ensuring that the relationship between power adjustment and battery temperature is nonlinear to accommodate the high sensitivity of battery temperature to performance; The power adjustment model is further optimized by introducing temperature impact compensation, which includes introducing a compensation factor to cope with the performance fluctuations that may occur when the temperature changes rapidly. The compensation factor is used to smooth the transition power adjustment and reduce the impact caused by the rapid temperature change. It uses the following expression: Where C(t) is the compensation factor at time t; κ is the compensation coefficient, which is used to adjust the degree of compensation; is the rate of change of battery temperature, obtained from the temperature control model; Combining the basic power adjustment and temperature effect compensation, the final charge and discharge power is obtained, and the power output after comprehensive adjustment is: The final power takes into account the basic power adjustment and compensation for temperature changes to ensure that the battery can maintain optimal performance under all operating conditions. It uses the following expression: P final (t)=P(t)·(1+C(t)) Among them, P final (t) is the final adjusted power.

5. The temperature regulation method based on embedded lithium battery according to claim 4, characterized in that: The integrated thermal management system is established by combining the temperature control perception model and the adaptive power management, the battery temperature is judged by the threshold value output by the temperature control perception model and the adaptive power management, the battery overheating is prevented according to the integrated thermal management system, and the battery temperature is precisely controlled; The integrated thermal management system includes defining a comprehensive thermal state evaluation function, a temperature regulation strategy, and a final charge and discharge strategy adjustment; The comprehensive thermal state evaluation function evaluates the thermal state of the battery by combining the temperature deviation and the power output, ensuring dynamic adjustment according to the actual performance of the battery, and accurately evaluating the instantaneous thermal environment of the battery. A thermal state evaluation function is defined. The thermal state evaluation function evaluates the thermal state of the battery based on the output of the intelligent temperature perception model and the adaptive power management, and adopts the following expression: Where Z(t) is the comprehensive thermal state evaluation at time t; T actual (t) is the actual temperature obtained by the temperature control perception model; T target is the target operating temperature of the battery; P final (t) is the power adjustment value obtained from the adaptive power management system; is the adjustment coefficient, and λ, μ, and ν are used to balance the influence of temperature deviation and power output, respectively.

6. The temperature regulation method based on embedded lithium battery according to claim 5, characterized in that: The temperature regulation strategy uses a combination of a hyperbolic tangent function and a sine function to achieve dynamic temperature adjustment. The hyperbolic tangent function provides a smooth and effective regulation mechanism, and the sine function introduces periodic regulation to adapt to ambient temperature fluctuations. According to the output of the thermal state evaluation function, the battery temperature regulation strategy is defined, which uses the following expression: R adjust (t)=δ·tanh(Z(t))+∈·sin(ω·t) Among them, R adjust (t) is the temperature regulation strategy at time t; δ,∈, ω is the regulation coefficient, which is used to adjust the sensitivity of the response and introduce periodic regulation to cope with external temperature fluctuations; The final charge and discharge strategy adjustment ensures that the battery can maintain optimal performance and safe operation under various operating conditions by comprehensively considering the effects of power management and temperature regulation. According to the output of the thermal state evaluation function, the battery temperature regulation strategy is defined, which adopts the following expression: P updated (t)=P final (t)·(1+R adjust (t)) Among them, P updated (t) is the final adjusted power after temperature regulation.

7. The temperature regulation method based on embedded lithium battery according to claim 6, characterized in that: When the battery temperature is less than the first threshold, the battery temperature risk level is judged to be low risk. The system will monitor the real-time temperature of the battery and confirm through the intelligent temperature perception model that the temperature is lower than the safety threshold, and it is judged to be a low risk state. At the same time, a regular performance report is sent to the maintenance department, and a low alarm state is displayed through the user interface for routine risk awareness and basic maintenance training. When the first threshold value is less than the battery temperature and less than the second threshold value: the battery temperature risk level is judged to be medium risk; The intelligent temperature sensing model detects that the battery temperature is between a first threshold and a second threshold, and the adaptive power management system adjusts the charging and discharging power according to the current temperature; At the same time, early warning information is sent to the technical support department, and medium-intensity alarms are generated and displayed through the system interface for risk communication and primary emergency drills. In addition, the early warning response plan is activated and corresponding technical interventions are prepared; When the battery temperature is greater than the second threshold: the battery temperature risk level is judged to be high risk; when the temperature exceeds the second threshold, ITMS immediately conducts an advanced assessment, and the adaptive power management system performs emergency power adjustments to reduce the temperature to a safe range as quickly as possible. At the same time, emergency warning information is sent to all relevant departments and users, and the system interface generates and displays a high-intensity virtual alarm scene for evacuation and rescue strategy formulation. At the same time, the system automatically starts + emergency cooling procedures and other necessary emergency response measures.

8. A temperature regulation system based on an embedded lithium battery, based on the temperature regulation method based on an embedded lithium battery according to any one of claims 1 to 7, characterized in that: Also includes, The acquisition module collects battery data, builds a temperature control perception model, and monitors battery temperature changes in real time through the temperature control perception model; Building modules, building adaptive power management according to battery temperature changes, using the output of the temperature control perception model as the input of adaptive power management, dynamically adjusting battery charging and discharging power, and optimizing battery performance; The control module establishes an integrated thermal management system by combining the temperature control perception model and adaptive power management. The battery temperature is judged by the threshold output by the temperature control perception model and adaptive power management. The battery overheating is prevented according to the integrated thermal management system, and the battery temperature is precisely controlled.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the temperature regulation method based on an embedded lithium battery according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the temperature regulation method based on an embedded lithium battery according to any one of claims 1 to 7 are implemented.

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