Forced air-cooled heat management system for lithium ion battery pack based on foamed aluminum filling reinforcement

Abstract

The construction and parameter calibration of the thermal management system of the lithium ion battery pack are carried out by adopting gradient pore foamed aluminum, and the method comprises a gradient foamed aluminum heat dissipation partition system with the non-uniform heating characteristic of the lithium ion battery pack and completion of structure preparation and flow resistance characteristic calibration of the gradient foamed aluminum heat dissipation system. Therefore, a hardware basis is provided for directional distribution of the intelligent wind field, the establishment and the method of the intelligent self-adaptive wind field regulation and control system are finally formed, and the'perception-control-execution 'integrated intelligent wind field regulation and control system is established. The thermal management efficiency of the lithium ion battery pack under the forced air cooling condition is remarkably improved, the intelligent self-adaptive wind field regulation and control system can respond to the temperature change in the battery pack in real time, the temperature uniformity of all areas is ensured, the local overheating phenomenon is effectively prevented, the service life of the battery is prolonged, and the overall safety is improved. In addition, the establishment of a data storage and management module provides powerful support for the optimization of a subsequent regulation and control method and the reuse of a similar battery pack scheme.

Description

Technical Field

[0001] This invention relates to the field of data optimization technology, specifically to a forced air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement. Background Technology

[0002] With the rapid development of new energy electric vehicles, the thermal safety of lithium-ion batteries, as a core energy storage component, has become a major concern. Lithium-ion batteries generate a significant amount of heat during charging and discharging (especially at high rates). If this heat cannot be dissipated in time, it can lead to excessively high battery temperatures or uneven temperature distribution within the module, resulting in capacity decay, shortened lifespan, and even thermal runaway and other safety incidents.

[0003] According to patent document CN102355022A, a lithium-ion battery pack management system includes: a data acquisition module, a microcontroller, and a balancing management module. The data acquisition module collects voltage, current, and temperature data of each individual lithium-ion battery in the lithium-ion battery pack. The microcontroller calculates the number of charge-discharge cycles for each individual lithium-ion battery based on the voltage and current data collected by the data acquisition module, and estimates the state of charge (SOC) of each individual lithium-ion battery based on the voltage, current, and temperature data and the number of charge-discharge cycles. The balancing management module balances the charge levels of each individual lithium-ion battery in the lithium-ion battery pack. Applying the lithium-ion battery pack management system provided by this invention avoids the problem of individual lithium-ion batteries being overcharged or over-discharged, improves the efficiency of the lithium-ion battery pack, and extends the service life of the lithium-ion battery pack.

[0004] Currently, mainstream battery thermal management methods include air cooling, liquid cooling, and phase change material cooling. Among them, air cooling is widely used due to its simple structure, low cost, and no risk of leakage. However, traditional air cooling technology has obvious shortcomings: air has a low specific heat capacity and thermal conductivity, resulting in low heat exchange efficiency; and in the battery module, the temperature rise along the air flow path will cause the downstream battery temperature to be significantly higher than the upstream temperature, resulting in a huge temperature gradient inside the module. Summary of the Invention

[0005] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement, characterized by comprising the following steps: Step 1: Construction and parameter calibration of gradient porous aluminum foam heat dissipation zoning system. Construct a gradient porous aluminum foam heat dissipation zoning system adapted to the non-uniform heating characteristics of lithium-ion battery packs, complete the structural preparation and flow resistance characteristic calibration, and provide a hardware foundation for intelligent wind field directional distribution. Step 2: Building and implementing the intelligent adaptive wind field control system, constructing an integrated intelligent wind field control system that combines "sensing-control-execution", and implementing a collaborative control method based on temperature thresholds to achieve dynamic adaptation of wind field parameters; Step 3: Gradient foam aluminum-intelligent wind farm collaborative debugging and parameter calibration. Through no-load and load linkage debugging, the parameter thresholds of the control method are optimized to improve the accuracy of system collaborative adaptation. Step 4: Full-condition functional verification and method iteration optimization. Through normal and extreme condition tests, verify the effectiveness of the core functions and iteratively optimize the system structure parameters and control method logic.

[0007] As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, wherein: in step one, the construction and parameter calibration of the gradient pore aluminum foam heat dissipation zoning system specifically includes the ANSYS Icepak simulation system to simulate the temperature field distribution under 1C-5C charge and discharge conditions, determine the difference in heat intensity between the "central 2x2 array high heat generation zone" and the "edge array low heat generation zone", and the temperature rise gradient law of the "inlet section-middle section-outlet section" in the airflow direction; Modeling and Parameter Definition for Heat Dissipation Zone Requirements: For the target lithium-ion battery pack, the temperature field distribution under 1C-5C charge-discharge conditions was simulated using the ANSYS Icepak simulation system to determine the difference in heat intensity between the "central 2x2 array high-heat zone" and the "edge array low-heat zone," as well as the temperature rise gradient law of the "inlet section-middle section-outlet section" in the airflow direction. Based on the simulation results, the core parameters were defined as follows: Along the airflow direction, the porosity of the inlet section module is 85%, and the pore density is 8 PPI; the porosity of the middle section module is 90%, and the pore density is 6 PPI; the porosity of the outlet section module is 95%, and the pore density is 4 PPI. Along the radial direction of the battery, the porosity of the central high-heat zone module is 85%-88%, and the pore density is 8 PPI; the porosity of the edge low-heat zone module is 92%-95%, and the pore density is 4-6 PPI. The dimensions of each module are customized according to the battery pack gap. As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, in step one, gradient aluminum foam is prepared into each partition module using a selective foaming + modular processing technology, and each module is spliced ​​together according to a preset layout to form an integrated gradient aluminum foam heat dissipation system, and sensor mounting holes and wiring grooves are processed at preset positions. Gradient aluminum foam module preparation and integration: Selective foaming + modular processing technology is used to prepare each zone module. TiH2 is selected as the foaming agent. The porosity is controlled by adjusting the amount of foaming agent (1.5%-2.5%) in an environment of 620-650℃. The modules are spliced ​​according to the preset layout and the joints are sealed by 1500W fiber laser welding (welding speed 3mm / s) to form an integrated gradient aluminum foam heat dissipation system. After welding, the surface is polished to ensure that the flatness is ≤0.2mm. Sensor mounting holes and wiring grooves are processed in preset positions. As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, wherein: in step one, the intelligent wind field includes a wind tunnel testing system, gradient aluminum foam is placed in the wind tunnel testing system, flow resistance and pressure drop data are tested, and a "wind speed-zone flow resistance" database is established as the parameter input basis for the intelligent wind field control method; Flow resistance characteristic calibration: The integrated gradient aluminum foam heat dissipation system was placed in a wind tunnel testing system to test the flow resistance pressure drop data of each zone within the wind speed range of 0.3m / s-6m / s, and a "wind speed-zone flow resistance" database was established as the parameter input basis for the intelligent wind field control method.

[0008] As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, wherein: step two, the construction and implementation of the intelligent adaptive wind field control system specifically includes: (1) Construction and deployment of multi-zone temperature sensing system: NTC temperature sensor with an accuracy of ±0.5℃ is selected and a sensing system is constructed by combining signal amplification module and A / D conversion module; according to the layout of "1 inlet section, 1 middle section, 1 outlet section, 2 central high heat generation zones, and 2 edge low heat generation zones", the sensor is embedded in the reserved mounting holes of the gradient foam aluminum system. The probe is attached to the inner wall of the foam aluminum through thermally conductive silicone (thermal conductivity ≥2W / (m·K)). The lead wire is led out through the wiring channel and connected to the control module. (2) Construction and installation of the wind farm execution system: The execution system is constructed using a "variable frequency centrifugal fan + zoned electric louvers", wherein the variable frequency fan speed adjustment range is 1000-5000 rpm and the maximum air volume is ≥120 m³ / h. 3 / h, the electric louvers are divided into 3 groups according to the heat dissipation zone (the group corresponding to the central zone, the group corresponding to the inlet-middle section, and the group corresponding to the outlet section), with an opening adjustment range of 0-100% and a response time of ≤0.5s; the variable frequency fan is fixed to the air inlet of the battery box through a flange seal, and the electric louvers are installed in the corresponding air outlet zone position, and the control terminal is connected to the PWM interface of the control module. (3) Control module construction and regulation method implementation: The STM32F103 MCU is selected as the core, integrating an A / D conversion module, a PWM drive module, and a power management module (12V output power supply); the "gradient zoning - temperature threshold - wind field parameters" collaborative regulation method is implemented, and the core logic includes: ①Basic control rules: When T_avg < 25℃, the fan speed is 1000-2000 rpm and the louver opening is 50%; when 25℃ ≤ T_avg ≤ 40℃, the fan speed is 2000-3500 rpm and the louver opening is 80%. ② Extreme operating condition lag compensation rule: When T_center > 40℃ or any zone temperature difference ΔT > 3℃, enhanced regulation is triggered, the fan speed is increased to 3500-5000rpm, the louver opening in the central zone is 100%, the inlet-middle section is 80%, and the outlet section is 70%; ③ Flow resistance adaptation correction: Incorporate gradient aluminum foam flow resistance characteristic data to correct wind speed parameters and avoid airflow short circuit.

[0009] As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, wherein step three, the gradient aluminum foam-intelligent wind field collaborative debugging and parameter calibration specifically includes: (1) No-load coordinated debugging: Start the control module and control the fan to run at three speeds of 1000rpm, 3000rpm and 5000rpm. Use an oscilloscope to detect the louver response time and opening accuracy to ensure that the opening error is ≤2% and the response delay is ≤0.5s. Simulate temperature signals of different zones to verify the accuracy of the extreme working condition triggering logic of the control method. (2) Load Coordination Debugging and Parameter Calibration: The gradient foam aluminum system, sensing system, execution system and control module are integrated into the battery box, the target battery pack is placed in it and attached by thermally conductive silicone pads; discharge tests are conducted at 2C, 3C and 5C rates respectively, and the temperature and wind field parameters of each zone are collected in real time; the temperature threshold and wind field parameters of the control method are corrected according to the test data to ensure that the temperature of the central area rises from 35℃ to 42℃ within 0.5s during 5C discharge, the fan speed is accurately increased from 3000rpm to 4500rpm, and the louvers in the central area are fully opened synchronously.

[0010] As a preferred embodiment of the forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement described in this invention, step four, specifically includes: full-condition functional verification and method iterative optimization. (1) Verification under normal operating conditions: The system was operated under 1C-3C charging and discharging conditions. The temperature and wind field parameters of each zone were monitored to verify the effect of gradient aluminum foam heat dissipation zone (temperature difference between the central zone and the edge zone ≤ 3℃) and the adaptability of the basic rules of the control method. (2) Core function verification under extreme conditions: A comparative test was conducted under the condition of instantaneous high-rate discharge at 5C (lasting for 30 minutes). When the intelligent wind field was turned off, the temperature baseline value (≥48℃) and the rate of rapid rise (≥2℃ / min) of the central area were recorded. After the entire system was turned on, the temperature peak value was ensured to be 5-8℃ lower than the baseline value (≤42℃), and the rate of rapid rise was reduced to ≤0.8℃ / min. This verified the effect of the intelligent wind field on compensating for the heat transfer lag of the gradient foam aluminum. (3) Iterative optimization: Based on the verification data, fine-tune the porosity parameters of the gradient aluminum foam edge region, optimize the control algorithm response threshold, and add the logic of "temperature rise rate prediction" (when the temperature rise rate is ≥1.5℃ / min, increase the fan speed to 3500rpm in advance) to ensure the coordinated effect under all working conditions.

[0011] A forced-air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement, comprising: a gradient porosity aluminum foam heat dissipation zoning system, an intelligent adaptive wind field control system, and a data storage and management module; Gradient porous aluminum foam heat dissipation zoning system: includes gradient aluminum foam modules designed according to "inlet section-middle section-outlet section" and "central area-edge area". The modules are integrated and sealed by laser welding. Pre-set sensor mounting holes and wiring channels are used to construct precise heat dissipation zoning and provide a basis for directional distribution of airflow. The intelligent adaptive wind field control system includes a multi-zone temperature sensing module, a control module, and a wind field execution module. The multi-zone temperature sensing module consists of an NTC temperature sensor, a signal amplification module, and an A / D conversion module, used to collect temperature data of each zone in real time. The control module is based on an STM32F103 MCU, integrating a PWM drive module and a power management module, and has a built-in "gradient zoning-temperature threshold-wind field parameter" collaborative control algorithm. The wind field execution module consists of a variable frequency centrifugal fan and three groups of zonal electric louvers, used to realize dynamic adjustment of wind field parameters. Data storage and management module: It uses encryption algorithms to store temperature data, wind field parameters, flow resistance characteristics data and optimization iteration records of each zone, and establishes a "temperature-wind field parameter" mapping database for the optimization of control methods and reuse of subsequent similar battery pack solutions.

[0012] A forced air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement includes: each module of the gradient porosity aluminum foam heat dissipation partition system is prepared by selective foaming process, the foaming agent is TiH2, the foaming temperature is 620-650℃, and the porosity and pore density parameters of each partition are precisely controlled by adjusting the amount of foaming agent added (1.5%-2.5%).

[0013] A forced-air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement, which stores a computer program, wherein: the control module of the intelligent adaptive wind field regulation system has built-in extreme condition lag compensation logic. When the temperature in the central area is detected to be >40℃ or the temperature difference ΔT in any zone is >3℃, the wind field enhancement regulation can be triggered within 0.5s to directionally distribute the wind field energy to the high-heat area.

[0014] The beneficial effects of this invention are as follows: By adopting a gradient porous aluminum foam heat dissipation zoning system, this invention significantly improves the thermal management efficiency of lithium-ion battery packs under forced air cooling conditions. The intelligent adaptive wind field control system can respond to changes in the internal temperature of the battery pack in real time, ensuring temperature uniformity in each area and effectively preventing local overheating, thereby extending battery life and improving overall safety. In addition, the establishment of the data storage and management module provides strong support for subsequent optimization of control methods and reuse of similar battery pack solutions. The beneficial effects of this invention are as follows: Compared with traditional thermal management systems, this invention achieves a qualitative leap in heat dissipation performance. The gradient porosity foam aluminum heat dissipation zoning system, with its unique structural advantages, not only increases the heat dissipation area but also achieves personalized customization of heat dissipation efficiency by precisely controlling the porosity and pore density parameters of each zone. The introduction of the intelligent adaptive airflow control system further elevates the level of intelligent thermal management to a new height. It can quickly adjust the airflow distribution based on real-time temperature data inside the battery pack, ensuring that each area receives adequate cooling, thereby avoiding performance degradation and safety hazards caused by uneven temperature. Simultaneously, the addition of a data storage and management module allows for long-term storage and in-depth analysis of the entire system's operating data, providing valuable reference for subsequent optimization and improvement, and the design of similar products. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the process of the present invention.

[0017] Figure 2 This is a system architecture diagram of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. 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 protection scope of the present invention.

[0019] Example 1, referring to Figure 1 As an embodiment of the present invention, a forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement is provided, comprising: Step 1: Construction and parameter calibration of a gradient porous aluminum foam heat dissipation zoning system. A gradient porous aluminum foam heat dissipation zoning system adapted to the non-uniform heating characteristics of lithium-ion battery packs is constructed. The structure is fabricated and its flow resistance characteristics are calibrated, providing a hardware foundation for intelligent wind field directional distribution. For a 3x3 18650 lithium-ion battery pack, ANSYS is used... The Icepak simulation system simulates the temperature field distribution under 1C-5C charge-discharge conditions, determining the difference in heat intensity between the "central 2x2 array high-heat zone" and the "edge array low-heat zone," as well as the temperature rise gradient from the inlet section to the middle section to the outlet section along the airflow direction. Based on the simulation results, the core parameters of the gradient aluminum foam heat dissipation partition system are defined as follows: along the airflow direction, the inlet section module has a porosity of 85% and a pore density of 8 PPI, the middle section module has a porosity of 90% and a pore density of 6 PPI, and the outlet section module has a porosity of 95% and a pore density of 4 PPI; along the radial direction of the battery, the central high-heat zone module has a porosity of 85%-88% and a pore density of 8 PPI, and the edge low-heat zone module has a porosity of 92%-95% and a pore density of 4-6 PPI. The dimensions of each module are customized according to the battery pack gap to ensure no airflow gap after assembly. Selective foaming + modular processing technology is used to prepare each partition module, with TiH2 selected as the foaming agent. The foaming agent is adjusted at 620-650℃. The porosity of each module is precisely controlled by adding 1.5%-2.5% of the material. The prepared modules are cut and beveled to ensure that the edge fit of the modules is ≤0.1mm. The modules of each zone are spliced ​​according to the preset layout of "center zone-edge zone" and "inlet section-middle section-outlet section". The joints are sealed by 1500W fiber laser welding (welding speed 3mm / s) to form an integrated gradient aluminum foam heat dissipation system. After welding, the surface of the components is polished to ensure that the surface flatness is ≤0.2mm. Sensor mounting holes (hole diameter 2mm) and wiring grooves are processed at the preset positions of the components to reserve interfaces for the subsequent integration of the wind field control system. The integrated gradient aluminum foam heat dissipation system is placed in the wind tunnel test system to build a "wind speed-zone flow resistance" test platform. The flow resistance pressure drop data of the inlet section, middle section, outlet section and center zone and edge zone are tested within the wind speed range of 0.3m / s-6m / s. The flow resistance characteristic database is established as the core parameter input basis for the intelligent wind field control method. Step Two: Construction and Methodology of Intelligent Adaptive Wind Field Control System. An integrated intelligent wind field control system encompassing "sensing-control-execution" is established. A temperature threshold-based collaborative control method is implemented to achieve dynamic adaptation of wind field parameters. The construction and deployment of a multi-zone temperature sensing system are also undertaken. NTC temperature sensors with an accuracy of ±0.5℃ are selected as sensing elements, paired with signal amplification and A / D conversion modules to construct a multi-zone temperature sensing system. The seven temperature sensors are arranged as follows: one at the inlet, one in the middle, one at the outlet, and two in the central high-heat zone. The sensor probes are arranged in a "two low-heat-generating zones at the edge" layout, embedded in the pre-reserved mounting holes of the gradient aluminum foam system. The probes are tightly bonded to the inner wall of the aluminum foam using thermally conductive silicone (thermal conductivity ≥2W / (m·K)). Lead wires are routed out through wiring channels to avoid obstructing the airflow channel. The signal output of the sensing system interfaces with the subsequent control module, using a "variable frequency centrifugal fan + zoned electric louvers" as the actuator to construct a directional airflow distribution system. The variable frequency fan has a speed adjustment range of 1000-5000 rpm and a maximum airflow ≥120 m³ / h. 3 The electric louvers, model / h, are divided into three groups according to heat dissipation zones (center zone, inlet-middle section, and outlet section). The opening range is 0-100%, and the response time is ≤0.5s. The variable frequency fan is fixed to the outside of the battery box air inlet using a flange seal. The fan outlet and inlet are connected by a rubber gasket to prevent airflow leakage. The three groups of electric louvers are installed at the corresponding zones of the battery box air outlet. The control terminal interfaces with the PWM drive interface of the control module. An STM32F103 MCU is selected as the core, integrating an A / D conversion module, a PWM drive module, and a power management module to construct an intelligent wind farm control core system. The power module outputs 12V to power the sensing system, execution system, and control module. The "gradient zoning-temperature threshold-wind field parameter" collaborative control method is embedded in the control module. The core logic includes: (1) Basic control rules: When the average battery temperature T_avg < 25℃, control the fan speed to 1000-2000rpm and the opening of all louvers to 50%; when 25℃≤T_avg≤40℃, control the fan speed to 2000-3500rpm and the opening of all louvers to 80%; (2) Extreme operating condition lag compensation rule: When the temperature of the central area T_center>40℃, or the temperature difference of any zone ΔT>3℃, it is judged as an extreme operating condition (such as instantaneous high-rate discharge), and the enhanced regulation is immediately triggered: the fan speed is increased to 3500-5000rpm, the louver opening of the central area is 100%, the louver opening of the inlet-middle section is 80%, the louver opening of the outlet section is 70%, and the wind field energy is directionally distributed to the high temperature area; (3) Flow resistance adaptation correction: The flow resistance characteristic data of the gradient aluminum foam system is incorporated into the control algorithm, and the wind speed output parameters are corrected according to the flow resistance difference of different zones to avoid airflow short circuit; Step 3: Gradient foam aluminum-intelligent wind farm collaborative debugging and parameter calibration. Through no-load and load linkage debugging, the parameter thresholds of the control method are optimized to improve the system's collaborative adaptation accuracy. The control module is started, and the fan is controlled to run at three speeds: 1000rpm, 3000rpm, and 5000rpm. The response time and opening accuracy of the three sets of electric louvers are detected by oscilloscope to ensure that the opening error is ≤2% and the response delay is ≤0.5s. The temperature signals of different zones are simulated by the control module (e.g., 42℃ in the central zone and 38℃ in the outlet section) to verify the triggering logic of the control method: ensuring that the extreme working condition rules can be triggered accurately and that the wind farm parameters are adjusted according to the preset rules. The gradient foam aluminum system, sensing system, execution system, and control module are integrated into the battery box and placed in a 4x4 The 18650 lithium-ion battery pack is bonded to the aluminum foam system via thermally conductive silicone pads, completing the entire system assembly. Discharge tests were conducted on the battery pack at 2C, 3C, and 5C rates. A sensing system collected real-time temperature data from each zone, recording the wind field parameter response curves of the control system. Based on the test data, the temperature threshold and wind field parameters in the control method were adjusted to ensure that during 5C discharge, the fan speed could precisely increase from 3000rpm to 4500rpm within 0.5 seconds when the central area temperature rapidly increased from 35℃ to 42℃, with the central area louvers opening simultaneously and fully, achieving directional energy distribution in the wind field and compensating for the heat transfer lag of the gradient aluminum foam. The calculation formula is as follows:

[0020] In this formula when When ∈(0.2,1): This zone is a high-priority control area, corresponding to high-heat areas under extreme operating conditions (such as central area temperature > 40℃). At this time, the wind field control system will prioritize the allocation of wind field energy to this area, triggering high-speed operation of the fan and full opening of the corresponding louvers. When ∈(0.05,0.2]: This zone is a normal priority control area, corresponding to normal charging and discharging conditions (25℃≤T≤40℃). The wind field control operates according to basic rules to ensure temperature stability in this area. : The hierarchical attention weight of the k-th sensing partition, which represents the influence weight of the temperature signal of the partition on wind field regulation. The value range is (0,1). The sum of the weights of all partitions is 1. Perception zone numbering, k=1 (inlet section), 2 (middle section), 3 (outlet section), 4 (central high fever zone 1), 5 (central high fever zone 2), 6 (edge ​​low fever zone 1), 7 (edge ​​low fever zone 2), a total of 7 zones; : Normalization factor; ensures that the sum of attention weights for all partitions is 1, with a range of (0, +∞); : No. Partition at time Temperature deviation, , For the first Measured temperatures in each zone The average temperature of the battery pack, with a range of (-15, 25)℃; : No. Partition at time The rate of temperature change characterizes how fast the temperature changes, with a value range of (-0.5, 2.5)℃ / s. Positive values ​​indicate heating, and negative values ​​indicate cooling. : No. Partitioning from the initial time up to the current moment The integral term representing the temperature deviation-rate of change characterizes the combined effect of the cumulative temperature deviation and the trend of change in this region, with a value range of (-100, 200)℃. 2 ; : Flow resistance correction weight coefficient, which adjusts the degree of influence of flow resistance characteristics on attention weight. After debugging and optimization, the value is set to 0.3 (dimensionless). Reference flow resistance voltage drop, taken as the average value of the flow resistance voltage drop of all zones, with a value range of (50, 300) Pa; : The actual flow resistance pressure drop of the k-th partition, which characterizes the magnitude of the airflow resistance in that partition, with a value range of (30, 350) Pa; Temperature fluctuation characteristic parameter, reflecting the dispersion of battery pack temperature distribution, is calibrated to a value of 2.8 (dimensionless) through experiments. The cumulative distribution function of the standard normal distribution. Range: (0,1) (dimensionless); Temperature threshold of the k-th partition, central high-heat zone Other partitions Value range: (35, 45)℃; The cumulative function of the normal distribution in The derivative at that point (i.e., the probability density function) enables smooth triggering of the temperature threshold. near As the value increases, the weight of this partition is strengthened; the value range is (0, 0.4) (1 / ℃). Step Four: Full-condition functional verification and method iteration optimization. Through normal and extreme condition tests, verify the effectiveness of core functions, iteratively optimize system structural parameters and control method logic, run the entire system under normal 1C-3C charge / discharge conditions, continuously monitor the temperature and airflow parameters of each zone, verify the heat dissipation zoning effect of the gradient aluminum foam system, and ensure that the temperature difference between the central and edge zones is ≤3℃; verify the basic rules of the control method, ensuring that airflow parameters dynamically adapt to temperature without airflow dead zones, and conduct comparative tests under a 5C instantaneous high-rate discharge condition (lasting 30 minutes). (1) Turn off the intelligent wind field control system and turn on only the gradient aluminum foam system. Record the temperature (baseline value, usually ≥48℃) and the rate of temperature rise (≥2℃ / min) in the central area after 10 minutes. (2) Start the whole system (gradient foam aluminum + intelligent wind field control), and record the temperature in the central area under the same working conditions: ensure that the temperature peak is reduced by 5-8℃ (≤42℃) compared with the reference value, and the temperature rise rate is reduced to ≤0.8℃ / min, to verify that the intelligent wind field control method can effectively make up for the heat exchange response lag problem of gradient foam aluminum. Based on verification data from both normal and extreme operating conditions, further optimizations were made: (1) System level: Fine-tune the porosity parameters of the edge zone of gradient aluminum foam (e.g., from 95% to 93%) to improve adaptability to the wind field; (2) Method level: Optimize the response threshold of the control algorithm and add the logic of "temperature rise rate prediction" (such as when the temperature rise rate is ≥1.5℃ / min, increase the fan speed to 3500rpm in advance) to further improve the timeliness of lag compensation; finally achieve the synergistic effect of "precise partition heat dissipation + dynamic wind field adaptation" under all working conditions and complete the implementation of the patented technology.

[0021] On the other hand, this embodiment also provides a forced air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement, which includes: a gradient pore aluminum foam heat dissipation zoning system, an intelligent adaptive wind field control system, and a data storage and management module. Gradient porous aluminum foam heat dissipation zoning system: includes gradient aluminum foam modules designed according to "inlet section-middle section-outlet section" and "central area-edge area". The modules are integrated and sealed by laser welding. Pre-set sensor mounting holes and wiring channels are used to construct precise heat dissipation zoning and provide a basis for directional distribution of airflow. The intelligent adaptive wind field control system includes a multi-zone temperature sensing module, a control module, and a wind field execution module. The multi-zone temperature sensing module consists of an NTC temperature sensor, a signal amplification module, and an A / D conversion module, used to collect temperature data of each zone in real time. The control module is based on an STM32F103 MCU, integrating a PWM drive module and a power management module, and has a built-in "gradient zoning-temperature threshold-wind field parameter" collaborative control algorithm. The wind field execution module consists of a variable frequency centrifugal fan and three groups of zonal electric louvers, used to realize dynamic adjustment of wind field parameters. Data storage and management module: It uses encryption algorithms to store temperature data, wind field parameters, flow resistance characteristics data and optimization iteration records of each zone, and establishes a "temperature-wind field parameter" mapping database for the optimization of control methods and reuse of subsequent similar battery pack solutions; In summary, the forced air cooling thermal management system and method for lithium-ion battery packs based on aluminum foam reinforcement proposed in this embodiment achieves efficient thermal management of lithium-ion battery packs under complex operating conditions through an innovative gradient porosity aluminum foam heat dissipation zoning system design combined with an intelligent adaptive wind field control system. This system not only effectively solves the problems of uneven heat dissipation and response lag in traditional heat dissipation methods, but also provides data support for continuous system optimization and iteration through the introduction of a data storage and management module. In practical applications, this system can significantly improve the working stability and safety of lithium-ion battery packs, extend battery life, and reduce maintenance costs, which is of great significance for promoting the rapid development of new energy vehicles, energy storage systems, and other fields. At the same time, the technical solution provided in this embodiment has high versatility and scalability, and can be customized for different types and specifications of lithium-ion battery packs to meet the thermal management needs of different application scenarios.

[0022] Example 2, an embodiment of the present invention, provides a forced air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement: I. Experiment Preparation and Implementation Process This embodiment uses a 3×3 array of 18650 lithium-ion battery packs (single cell capacity 2200mAh, nominal voltage 3.7V, maximum discharge current 11A) as the test object to verify the effectiveness of the forced air cooling thermal management method and system based on gradient aluminum foam filling reinforcement and intelligent adaptive wind field regulation. Before the experiment, a comprehensive test platform including a battery test bench, data acquisition system, and environmental simulation chamber was constructed. The environmental simulation chamber maintained a constant temperature of 25℃ and humidity of 50%RH to eliminate interference from the external environment on the test results. Two comparative groups were set up simultaneously: Comparative group 1 was a thermal management system of "traditional uniform porous aluminum foam + fixed air field" (existing conventional technology, with a uniform aluminum foam porosity of 85%, a pore density of 8 PPI, a fixed fan speed of 3000 rpm, and a fixed louver opening of 80%); Comparative group 2 was a thermal management system of "gradient porous aluminum foam + single air field" (existing improved technology, with aluminum foam parameters consistent with the present invention, but without intelligent adaptive control, a fixed fan speed of 4000 rpm, and a uniform louver opening of 100%); the present invention group is the complete system and method described in claims 1-10; The implementation process strictly followed the four-step core procedure of the invention, with specific details as follows: Step 1: Construction and parameter calibration of the gradient porous aluminum foam heat dissipation zoning system. First, the ANSYS Icepak simulation system was used to simulate the temperature field distribution of the battery pack under 1C, 3C, and 5C charge-discharge conditions. The simulation results showed that the maximum heat intensity difference between the high-heat-generating area in the central 2×2 array and the edge area reached 12W, and the temperature rise gradient in the airflow direction from the inlet section to the middle section to the outlet section was 3℃-5℃. Based on this, the gradient aluminum foam parameters were determined as follows: along the airflow direction, the porosity of the inlet section was 85%, and the pore density was 8 PPI; the porosity of the middle section was 90%, and the pore density was 6 PPI; the porosity of the outlet section was 95%, and the pore density was 4 PPI. Radially, the porosity of the central high-heat-generating area was 86%, and the pore density was 8 PPI; the porosity of the edge area was 93%, and the pore density was 5 PPI. Selective foaming was used to prepare the modules for each zone, with TiH2 as the foaming agent and a foaming temperature of 630℃. The porosity was precisely controlled by adjusting the amount of foaming agent added (1.8%-2.3%). The modules were assembled according to a preset layout and sealed using 1500W fiber laser welding (welding speed 3mm / s). After grinding, the surface flatness was 0.15mm. 2mm diameter sensor mounting holes and 3mm wide wiring grooves were machined at preset positions. The system was then placed in a wind tunnel testing system to test the flow resistance pressure drop data of each zone at wind speeds of 0.3m / s-6m / s, establishing a "wind speed-zone flow resistance" database. The flow resistance pressure drop in the central zone was 180Pa at a wind speed of 3m / s, and in the outlet zone it was 120Pa. The reference flow resistance pressure drop ΔP_ref=156Pa. The second step involves the construction and implementation of the intelligent adaptive wind farm control system. A multi-zone temperature sensing system is constructed, using NTC temperature sensors (model NTC 10K) with an accuracy of ±0.5℃, paired with an LM324 signal amplification module and an ADS1115 A / D conversion module. The sensors are embedded in mounting holes according to a layout of "one sensor at the inlet (k=1), one in the middle (k=2), one at the outlet (k=3), two in the central high-heat zone (k=4, k=5), and two in the edge low-heat zone (k=6, k=7)". The probes are bonded to the inner wall of the aluminum foam using thermally conductive silicone (thermal conductivity 2.5W / (m·K)), and the leads are led out through a wiring channel and connected to the control module. The wind farm execution system is then constructed, using a variable frequency centrifugal fan (model DF-12032, speed adjustment range 1000-5000rpm, maximum air volume 125m³ / h). 3 The air inlet of the battery box is sealed with a flange and equipped with three sets of electric louvers (model EB-01, opening adjustment range 0-100%, response time 0.3s), corresponding to the central area, inlet-middle section, and outlet section respectively. The control terminal is connected to the PWM interface of an STM32F103 MCU. A control module is constructed, integrating A / D conversion, PWM drive, and 12V power management modules. A "gradient zoning-temperature threshold-wind field parameter" collaborative control method is implemented, with preset basic control rules and extreme condition lag compensation rules. The flow resistance data obtained from wind tunnel testing is incorporated into the algorithm to complete parameter initialization. The third step is the coordinated commissioning and parameter calibration of the gradient aluminum foam-intelligent wind farm. First, no-load commissioning is performed: the control module is started, and the fan is controlled at three speeds: 1000rpm, 3000rpm, and 5000rpm. The louver response time is measured using an oscilloscope, and the opening error is ≤1.5%. A simulated temperature of 42℃ in the central area and 38℃ at the outlet is used. The control system accurately triggers the extreme operating condition rules, increasing the fan speed to 4500rpm. The louvers in the central area are fully open, the inlet-middle section opening is 80%, and the outlet section opening is 70%, demonstrating accurate triggering logic. Next, load testing was performed: The gradient aluminum foam system, sensing system, execution system, and control module were integrated into the battery box, and a 4×4 18650 battery pack was placed inside. The battery pack and the aluminum foam system were assembled by attaching them together with a thermally conductive silicone pad (0.3mm thick). The battery was discharged at 2C, 3C, and 5C rates, and the temperature and wind field parameters of each zone were collected in real time. The control threshold was adjusted based on the test data. Finally, it was determined that when the temperature rise rate of the central zone was ≥1.5℃ / min, the fan speed was pre-increased to 3500rpm in advance to ensure that the fan speed accurately reached 4500rpm within 0.5s when the temperature of the central zone rose from 35℃ to 42℃ during 5C discharge. The fourth step is full-condition functional verification and method iteration optimization. Three sets of systems were subjected to 1C (normal operating conditions), 3C (medium-high load operating conditions), and 5C (extreme operating conditions) charge-discharge cycle tests. Each operating condition was repeated three times, and the average value was taken. Key parameters such as the battery pack's highest temperature, center-edge temperature difference, heat exchange response time, and energy consumption were recorded using a data acquisition system. Based on the test results, the threshold of the control algorithm for the system of this invention was fine-tuned, completing the final optimization.

[0023] II. Test Data Recording Table Table 1. Comparison of Maximum Battery Pack Temperatures under Different Operating Conditions (Unit: °C)

[0024] Table 2 Comparison of temperature difference between the center and edge of the battery pack under different operating conditions (unit: °C)

[0025] Table 3 Comparison of key performance parameters under extreme operating conditions (5C discharge)

[0026] III. Analysis of Experimental Data and Explanation of the Beneficial Effects of the Invention Based on the data in the three sets of tables above, it can be seen that the overall performance of the invention group under various working conditions is significantly better than that of the two comparative groups, fully verifying the invention's innovativeness, novelty, and beneficial effects. A detailed analysis follows: Table 1 shows the highest battery pack temperatures under different operating conditions. The highest temperatures of this invention's pack under 1C, 3C, and 5C conditions are 32.5℃, 40.1℃, and 46.5℃, respectively. Compared to Comparison Group 1 (traditional technology), these temperatures represent reductions of 11.7%, 17.3%, and 21.5%, respectively. Compared to Comparison Group 2 (existing gradient foamed aluminum technology), these reductions are 5.0%, 9.5%, and 13.6%, respectively. Furthermore, the highest temperature under extreme conditions is controlled below 47℃, far below the 55℃ safety critical temperature for lithium-ion batteries. This advantage stems from the deep integration of precise zoned heat dissipation of gradient porous foamed aluminum with intelligent adaptive wind field control: the gradient foamed aluminum, through differentiated porosity and pore density design, matches the non-uniform heating characteristics of the battery pack, providing a basis for directional wind field distribution; while the intelligent wind field, based on multi-regional temperature sensing, dynamically adjusts the fan speed and louver opening, avoiding the problems of Comparison Group 1's fixed wind field being unable to adapt to different load conditions and Comparison Group 2's single wind field energy distribution imbalance, thus achieving efficient heat removal. Table 2 shows the center-edge temperature difference data, further demonstrating the precise temperature control advantages of this invention. The temperature difference in this invention group was controlled within 3.2℃ under all operating conditions, with a maximum reduction of 62.4% compared to control group 1 and 49.2% compared to control group 2. Control group 1, due to its use of uniformly porous aluminum foam, could not adapt to the heating difference between the center and the edge, resulting in a large temperature difference. While control group 2 used gradient aluminum foam, the single airflow could not achieve directional energy distribution, limiting temperature difference optimization. In contrast, this invention, through a layered attention weighting control mechanism, directionally distributes airflow energy to the high-heat-generating central region while maintaining temperature stability in the edge region, significantly reducing the internal temperature difference of the battery pack and effectively avoiding the impact of localized overheating on battery performance. This represents a creative breakthrough in addressing the pain point of "lack of synergy between structure and airflow" in existing technologies. Table 3 compares key performance parameters under extreme conditions, further highlighting the core innovative value of this invention. Regarding heat exchange response time, the present invention group only needs 0.5 seconds to complete the response control of the central area temperature rising from 35℃ to 42℃, which is 58.3% shorter than comparison group 1 and 44.4% shorter than comparison group 2. This verifies the effectiveness of the extreme condition lag compensation logic in the invention—by rapidly triggering wind field enhancement control within 0.5 seconds, it accurately compensates for the heat exchange response lag problem of gradient aluminum foam under instantaneous high-rate discharge. In contrast, comparison group 1 has a fixed wind field response lag, and comparison group 2 lacks adaptive control logic, both of which cannot cope with the sudden temperature rise under extreme conditions. Regarding system energy consumption, the present invention group reduces energy consumption by 18.3% compared to comparison group 1 and by 34.8% compared to comparison group 2. This is because the dynamic adjustment of the intelligent wind field avoids the energy waste of comparison group 2's "high-speed operation throughout," achieving a balance between energy saving and efficient heat exchange. Regarding the impact on battery cycle life, the capacity retention rate of this invention group after 500 cycles reached 91.3%, which is 16.7% higher than that of the control group 1 and 9.3% higher than that of the control group 2. This is because the invention reduces the occurrence of internal side reactions of the battery by precisely controlling the temperature and reducing the temperature difference, thus delaying the capacity decay and improving the service life and safety of the battery pack.

[0027] In summary, this invention, through the synergistic design of "precise filling of gradient porous aluminum foam + intelligent adaptive wind field control", overcomes the three major technical bottlenecks in the prior art: "uniform structure with uneven heat transfer", "lack of coordination between gradient structure and wind field", and "lag in response to extreme conditions". It achieves comprehensive benefits such as "precise zoned heat dissipation, dynamic wind field adaptation, high efficiency and energy saving, and long lifespan guarantee", and has significant innovation and application advantages compared with the prior art.

[0028] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement, characterized in that, Includes the following steps: Step 1: Construction and parameter calibration of gradient porous aluminum foam heat dissipation zoning system. Construct a gradient porous aluminum foam heat dissipation zoning system adapted to the non-uniform heating characteristics of lithium-ion battery packs, complete the structural preparation and flow resistance characteristic calibration, and provide a hardware foundation for intelligent wind field directional distribution. Step 2: Building and implementing the intelligent adaptive wind field control system, constructing an integrated intelligent wind field control system that combines "sensing, control, and execution", and implementing a collaborative control method based on temperature thresholds to achieve dynamic adaptation of wind field parameters; Step 3: Gradient foam aluminum-intelligent wind farm collaborative debugging and parameter calibration. Through no-load and load linkage debugging, the parameter thresholds of the control method are optimized to improve the accuracy of system collaborative adaptation. Step 4: Full-condition functional verification and method iteration optimization. Through normal and extreme condition tests, verify the effectiveness of the core functions and iteratively optimize the system structure parameters and control method logic.

2. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step one, the construction and parameter calibration of the gradient porous aluminum foam heat dissipation partition system specifically includes the ANSYS Icepak simulation system to simulate the temperature field distribution under 1C-5C charging and discharging conditions, determine the difference in heating intensity between the "central 2x2 array high heating zone" and the "edge array low heating zone", and the temperature rise gradient law of the "inlet section-middle section-outlet section" in the airflow direction.

3. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step one, gradient aluminum foam is prepared into modules for each zone using a selective foaming + modular processing technology. The modules are then spliced ​​together according to a preset layout to form an integrated gradient aluminum foam heat dissipation system. Sensor mounting holes and wiring channels are then processed at preset positions.

4. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step one, to calibrate the parameters for intelligent wind field directional allocation, gradient aluminum foam is placed in a wind tunnel testing system to test flow resistance and pressure drop data, and a 'wind speed-zone flow resistance' database is established as the parameter input basis for the intelligent wind field control method.

5. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step two, the construction and implementation of the intelligent adaptive wind field control system specifically includes the construction and deployment of a multi-zone temperature sensing system. Temperature sensors are selected and paired with signal amplification and A / D conversion modules to form the sensing system. Following a layout of "one inlet section, one middle section, one outlet section, two central high-heat zones, and two edge low-heat zones," the sensors are embedded in the pre-reserved mounting holes of the gradient aluminum foam system. The probes are attached to the inner wall of the aluminum foam using thermally conductive silicone. Lead wires are routed through wiring channels and connected to the control module. An execution system is constructed using a "variable frequency centrifugal fan + zoned electric louvers." The electric louvers are divided into three groups according to heat dissipation zones (corresponding to the central zone, the inlet-middle section, and the outlet section). The variable frequency fan is sealed and fixed to the air inlet of the battery box using a flange. The electric louvers are installed at the corresponding air outlet zones. The control terminal is connected to the PWM interface of the control module.

6. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step three, the gradient aluminum foam-intelligent wind field collaborative debugging and parameter calibration specifically includes no-load collaborative debugging, verifying the accuracy of the extreme working condition triggering logic of the control method, integrating the gradient aluminum foam system, sensing system, execution system and control module into the battery box, placing it into the target battery pack and attaching it with a thermally conductive silicone pad.

7. The forced air cooling thermal management method for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 1, characterized in that: In step four, the full-condition functional verification and method iterative optimization specifically includes verification under normal operating conditions, core functional verification and iterative optimization under extreme operating conditions, to ensure the collaborative effect under all operating conditions.

8. A forced-air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement, characterized in that: A forced air cooling thermal management method for lithium-ion battery pack based on aluminum foam filling reinforcement according to any one of claims 1-7 includes a gradient pore aluminum foam heat dissipation zoning system, an intelligent adaptive wind field control system, and a data storage and management module. Gradient porous aluminum foam heat dissipation zoning system: includes gradient aluminum foam modules designed according to "inlet section-middle section-outlet section" and "center area-edge area". The modules are integrated by laser welding and sealed. Pre-set sensor mounting holes and wiring channels are used to construct precise heat dissipation zoning and provide a basis for directional airflow distribution. Intelligent adaptive wind field control system: includes a multi-zone temperature sensing module, a control module and a wind field execution module; the multi-zone temperature sensing module consists of an NTC temperature sensor, a signal amplification module and an A / D conversion module, used to collect temperature data of each zone in real time; Data storage and management module: It uses encryption algorithms to store temperature data, wind field parameters, flow resistance characteristics data and optimization iteration records of each zone, and establishes a "temperature-wind field parameter" mapping database for the optimization of control methods and reuse of subsequent similar battery pack solutions.

9. A forced-air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 8, characterized in that: Each module of the gradient porous aluminum foam heat dissipation partition system is prepared using a selective foaming process, and the porosity and pore density parameters of each partition are precisely controlled by adjusting the amount of foaming agent added.

10. A forced-air cooling thermal management system for lithium-ion battery packs based on aluminum foam filling reinforcement as described in claim 8, characterized in that: The control module of the intelligent adaptive wind field regulation system has built-in extreme condition lag compensation logic. When the temperature in the central area is detected to be >40℃ or the temperature difference ΔT between any two zones is >3℃, the wind field enhancement regulation can be triggered within 0.5s to directionally distribute wind field energy to the high-heat area.

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