New energy automobile battery thermal management intelligent control system

Abstract

The invention discloses a new energy automobile battery thermal management intelligent control system, and relates to the technical field of electric automobile energy storage device manufacturing, the new energy automobile battery thermal management intelligent control system comprises a temperature acquisition module, a data processing module, an intelligent control module and a heat exchange execution module, the data processing module adopts a weighted average method to calculate temperature distribution parameters, the intelligent control module prejudges the temperature change trend in advance and generates a heat management control instruction based on a temperature prediction algorithm, and the heat exchange execution module comprises a liquid cooling loop and an air cooling loop and flexibly selects a cooling mode according to the temperature state. Active thermal management control is achieved, temperature control precision is improved, system energy consumption is reduced, safe and efficient operation of the battery is ensured, and the method is suitable for the field of battery thermal management of motor vehicles such as electric automobiles.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle energy storage device manufacturing technology, specifically to an intelligent control system for thermal management of new energy vehicle batteries. Background Technology

[0002] The power batteries of new energy vehicles generate a lot of heat during charging and discharging. Excessive battery temperature can lead to decreased battery performance, shortened lifespan, and even safety accidents. Conversely, excessively low battery temperature can affect the charging and discharging efficiency and power output capability of the battery. Therefore, the battery thermal management system is one of the key technologies for new energy vehicles. Existing battery thermal management systems typically employ passive temperature control strategies, relying on feedback control based on real-time temperature measurements. This control method suffers from response lag, meaning that the battery may already be damaged when an abnormal temperature is detected. Furthermore, existing systems often employ a single cooling method, resulting in poor adaptability to different operating conditions and high energy consumption. In addition, existing temperature acquisition technologies often only place sensors in a few locations, which cannot accurately reflect the temperature distribution inside the battery pack, making it difficult to detect and deal with local overheating problems in a timely manner. Therefore, there is a need for an intelligent thermal management and control system that can predict temperature change trends, adaptively adjust cooling strategies, and accurately monitor temperature distribution. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent control system for thermal management of new energy vehicle batteries, so as to solve the technical problems of delayed thermal management response, single cooling method, and inaccurate temperature monitoring in the prior art.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A smart control system for thermal management of new energy vehicle batteries includes a smart control system comprising: Temperature acquisition modules are installed at multiple monitoring locations on the battery pack to collect temperature data of individual battery cells. The data processing module is electrically connected to the temperature acquisition module and is used to receive and process temperature data and calculate the temperature distribution parameters of the battery pack. The intelligent control module is electrically connected to the data processing module and generates thermal management control commands based on temperature distribution parameters. The heat exchange execution module is electrically connected to the intelligent control module and adjusts the temperature of the battery pack according to control commands. The intelligent control module uses a temperature prediction algorithm to predict the battery temperature change trend in the future based on the current temperature data, vehicle driving conditions and battery charging and discharging status, and adjust the thermal management strategy in advance. The heat exchange execution module includes a liquid cooling circuit and an air cooling circuit. The liquid cooling circuit is located at the bottom of the battery pack, and the air cooling circuit is located on the side of the battery pack. The liquid cooling circuit and the air cooling circuit can be controlled independently and can work together.

[0005] Furthermore, the temperature acquisition module includes a distributed temperature sensor array, with each sensor monitoring the temperature of 3 to 5 individual battery cells, and the sensor sampling frequency is 0.5Hz to 2Hz.

[0006] Furthermore, when the data processing module calculates the temperature distribution parameters, it uses a weighted average method, assigning a weight coefficient of 0.4 to the temperature data in the central area of ​​the battery pack, a weight coefficient of 0.3 to the temperature data in the edge area, and a weight coefficient of 0.3 to the temperature data in the corner area.

[0007] Furthermore, the temperature prediction algorithm of the intelligent control module includes: A battery thermal model is established, which calculates the rate of temperature change based on the battery's heat generation and heat dissipation power. Calculate the heat generation power based on the current charging and discharging current and internal resistance parameters; Calculate the heat dissipation power based on the current cooling medium flow rate and temperature difference; Predict the battery temperature value within the next 5 to 15 minutes based on the rate of temperature change.

[0008] Furthermore, the intelligent control module sets the temperature control threshold as follows: The normal operating temperature range is 20℃ to 35℃; The upper limit of the warning temperature is 40℃; The maximum protection temperature is 45℃; The lower limit of the warning temperature is 5℃; The lower limit of the protection temperature is 0℃.

[0009] Furthermore, the liquid cooling circuit includes a coolant pump, coolant pipes, and a cooling plate. The cooling plate has a flow channel, in which the coolant flows to remove heat. The flow rate of the coolant pump is adjustable from 3L / min to 15L / min.

[0010] Furthermore, the air-cooling circuit includes a fan assembly and an air guide channel. The fan assembly has an adjustable speed, ranging from 1000 rpm to 3000 rpm, and the air guide channel guides the airflow along the side of the battery pack.

[0011] Furthermore, the intelligent control module selects the thermal management operating mode based on the battery temperature and temperature change trend: When the battery temperature is below 20°C and the temperature is rising, the heat exchange execution module is shut down. When the battery temperature is between 20°C and 35°C, activate the air cooling circuit. When the battery temperature is above 35°C, both the liquid cooling circuit and the air cooling circuit are activated simultaneously.

[0012] Furthermore, the intelligent control system also includes a safety protection module. When the battery temperature is detected to exceed the protection threshold, the safety protection module triggers protection measures to limit the battery charging and discharging power and adjust the heat exchange execution module to the power output state.

[0013] Compared with the prior art, the beneficial effects of the present invention by adopting the above technical solution are as follows: 1. Through temperature prediction algorithms, the battery temperature change trend can be predicted in advance, realizing active thermal management control and avoiding damage to the battery caused by abnormal temperature. 2. It adopts a heat exchange method that combines liquid cooling and air cooling, and the cooling mode can be flexibly selected according to actual needs, so as to ensure the cooling effect and reduce energy consumption. 3. By using a distributed temperature sensor array, the internal temperature distribution of the battery pack can be accurately obtained, and local overheating problems can be detected in a timely manner; 4. Employ a weighted temperature calculation method, focusing on high-temperature areas, to improve the accuracy and effectiveness of temperature monitoring; 5. Set multiple temperature protection thresholds and take corresponding measures under different temperature conditions to ensure safe battery operation; 6. The system has a reasonable structure and a high degree of intelligence in its control strategy, making it suitable for practical application scenarios of electric vehicles. Attached Figure Description

[0014] Figure 1 This is a block diagram of the overall structure of the system of the present invention; Figure 2 This is a schematic diagram of the layout of the temperature acquisition module of the present invention; Figure 3 This is a schematic diagram of the liquid cooling circuit of the present invention; Figure 4 This is a flowchart of the intelligent control process of the present invention; Figure 5 This is a flowchart of the temperature prediction algorithm of the present invention. Detailed Implementation

[0015] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0016] Example 1 like Figure 1 As shown in the figure, this embodiment provides an intelligent control system for thermal management of new energy vehicle batteries, including a temperature acquisition module, a data processing module, an intelligent control module, a heat exchange execution module, and a safety protection module.

[0017] Temperature acquisition modules are installed at multiple monitoring locations within the battery pack to collect temperature data from individual battery cells, such as... Figure 2 As shown, the temperature acquisition module includes a distributed temperature sensor array. The sensors are arranged in the central, edge, and corner areas of the battery pack. Each sensor monitors the temperature of 3 to 5 individual battery cells, ensuring comprehensive monitoring of the internal temperature distribution of the battery pack. The sensor sampling frequency is set to 0.5Hz to 2Hz to ensure real-time monitoring while avoiding excessive data processing burden.

[0018] In practice, 24 temperature sensors are arranged in a battery pack containing 96 battery cells. Each sensor monitors the temperature of 4 battery cells. The sensors are NTC thermistors with a temperature range of -40℃ to 125℃ and a measurement accuracy of ±0.5℃. The sensors transmit temperature data to the data processing module via a CAN bus.

[0019] The data processing module is electrically connected to the temperature acquisition module and is used to receive and process temperature data and calculate the temperature distribution parameters of the battery pack. The data processing module uses a weighted average method to calculate the overall temperature parameters, assigning a weighting coefficient of 0.4 to the temperature data collected by the 8 sensors in the central area of ​​the battery pack, a weighting coefficient of 0.3 to the temperature data collected by the 12 sensors in the edge area, and a weighting coefficient of 0.3 to the temperature data collected by the 4 sensors in the corner area.

[0020] The weighted average temperature is calculated as follows: ; in: This is a weighted average temperature, in °C. This represents the average temperature of the central region, in °C. This represents the average temperature of the edge region, in °C. This represents the average temperature of the corner area, in °C. In addition, the data processing module also calculates temperature difference parameters, reflecting the temperature uniformity inside the battery pack: ; in: This is a temperature difference parameter, in °C. The temperature values ​​are from all sensors, in °C. The values ​​are the temperature values ​​from all sensors, in °C.

[0021] The intelligent control module is electrically connected to the data processing module. It generates thermal management control commands based on temperature distribution parameters. The intelligent control module sets the temperature control threshold as follows: The normal operating temperature range is 20℃ to 35℃; The upper limit of the warning temperature is 40℃; The maximum protection temperature is 45℃; The lower limit of the warning temperature is 5℃; The lower limit of the protection temperature is 0℃.

[0022] like Figure 5 As shown, the intelligent control module uses a temperature prediction algorithm to predict the future trend of battery temperature changes based on current temperature data, vehicle driving conditions, and battery charging / discharging status. The temperature prediction algorithm includes the following steps: Step S1: Establish a battery thermal model. The thermal model calculates the rate of temperature change based on the battery's heat generation and heat dissipation power.

[0023] The formula for calculating the battery temperature change rate is: ; in: This is the rate of temperature change, expressed in °C / s. Heat generation power, measured in W; Heat dissipation power, measured in watts (W). Battery pack mass, in kg; This refers to the specific heat capacity of the battery pack, expressed in J / (kg·℃).

[0024] Step S2: Calculate the heat generation power based on the current charging / discharging current and internal resistance parameters.

[0025] The formula for calculating heat generation power is: ; in: This is the charging and discharging current, measured in amperes (A). This represents the battery's internal resistance, measured in Ω.

[0026] Step S3: Calculate the heat dissipation power based on the current cooling medium flow rate and temperature difference.

[0027] For liquid cooling circuits, the formula for calculating heat dissipation power is: ; in: This refers to the liquid cooling power, measured in watts (W). This refers to the density of the coolant, expressed in kg / L. This refers to the coolant flow rate, expressed in L / min. This refers to the specific heat capacity of the coolant, expressed in J / (kg·℃). Battery temperature, in °C; This refers to the coolant temperature, expressed in °C.

[0028] For air-cooled circuits, the formula for calculating heat dissipation power is: ; in: This refers to the air-cooled heat dissipation power, measured in watts (W). The convective heat transfer coefficient is expressed in W / (m²). 2 ·℃); The heat dissipation area is expressed in meters (m²). 2 ; The air temperature is expressed in °C.

[0029] Step S4: Predict the battery temperature value within the next 5 to 15 minutes based on the temperature change rate.

[0030] The formula for predicting temperature is: ; in: Temperature is predicted, and the unit is °C. The current temperature is in °C. The prediction time interval is in seconds and ranges from 300s to 900s.

[0031] like Figure 4 As shown, the intelligent control module selects the thermal management operating mode based on the battery temperature and temperature change trend. The specific control strategy is as follows: Mode 1: When the battery temperature is below 20°C and the temperature is rising, the heat exchange execution module is turned off, and the temperature is raised by the battery itself. Mode 2: When the battery temperature is between 20°C and 35°C, the air-cooling circuit is activated to provide moderate cooling through natural convection and forced convection. Mode 3: When the battery temperature is higher than 35°C, the liquid cooling circuit and the air cooling circuit are activated simultaneously to quickly cool down the battery through a combination of liquid cooling and air cooling. Mode 4: When the predicted temperature exceeds the warning threshold of 40℃, the cooling system will be activated in advance to prevent the temperature from reaching a dangerous level; Mode 5: When the temperature exceeds the protection threshold of 45℃, the safety protection module is triggered to limit the battery charging and discharging power.

[0032] The heat exchange execution module is electrically connected to the intelligent control module and adjusts the temperature of the battery pack according to control commands. The heat exchange execution module includes a liquid cooling circuit and an air cooling circuit.

[0033] like Figure 3 As shown, the liquid cooling circuit includes a coolant pump, coolant pipes, and a cooling plate. The cooling plate is located at the bottom of the battery pack and is in direct contact with the individual battery cells. A serpentine flow channel is set inside the cooling plate, and the coolant flows in the channel to remove heat. The flow rate of the coolant pump is adjustable from 3L / min to 15L / min. The flow rate is controlled by adjusting the pump speed. The coolant is an aqueous solution of ethylene glycol with a concentration of 50%, a freezing point of -37℃, and a boiling point of 107℃.

[0034] The working process of the liquid cooling circuit is as follows: the coolant pump draws coolant from the storage tank, delivers it to the cooling plate through the coolant pipeline, the coolant flows in the flow channel of the cooling plate, absorbs the heat generated by the battery and the temperature rises, the heated coolant flows out of the cooling plate, is cooled by the radiator, and then returns to the storage tank to form a cycle.

[0035] The air-cooled circuit includes a fan assembly and an air duct. The fan assembly is located on the side of the battery pack and includes two axial fans, each with a diameter of 120mm. The fan assembly speed is adjustable, with a speed adjustment range of 1000rpm to 3000rpm. The air duct guides the airflow along the side of the battery pack to ensure that the airflow is evenly distributed on the surface of the battery cells.

[0036] The working process of the air-cooled circuit is as follows: the fan assembly draws in external air, the air is distributed to the side of the battery pack through the air guide channel, the air flows over the surface of the battery cell, and the heat is dissipated through the convection heat exchanger. The heated air is then discharged from the other side of the battery pack.

[0037] The safety protection module is electrically connected to the intelligent control module. When the battery temperature exceeds the protection threshold, the safety protection module triggers protective measures. (1) Limiting battery charging and discharging power: By sending a power limiting command to the battery management system, the charging power is reduced to 50% of the rated power and the discharging power is reduced to 60% of the rated power; (2) Adjust the heat exchange execution module to power output state: adjust the coolant pump flow rate of the liquid cooling circuit to 15L / min, and adjust the fan speed of the air cooling circuit to 3000rpm; (3) Issue a warning message to the driver: Display an abnormal temperature warning on the instrument panel to alert the driver; (4) Record fault information: Record abnormal temperature events in the fault log for easy subsequent analysis.

[0038] Example 2 Based on Example 1, this embodiment optimizes the temperature prediction algorithm. The intelligent control module incorporates vehicle driving condition parameters and historical temperature data to improve the accuracy of temperature prediction.

[0039] Vehicle operating parameters include: vehicle speed, acceleration, and road gradient. The intelligent control module uses these parameters to determine the vehicle's operating status. (1) Low load condition: vehicle speed below 40km / h, acceleration at -0.5m / s² 2 up to 0.5m / s 2 Between these points, the road gradient ranges from -3% to 3%. (2) Medium load condition: vehicle speed between 40km / h and 80km / h, acceleration between -1m / s² 2 Up to 1m / s 2 Between these points, the road gradient ranges from -5% to 5%. (3) High-load operating conditions: vehicle speed exceeds 80km / h, and acceleration exceeds 1m / s². 2 The road gradient exceeds 5%.

[0040] The heat generation power of the battery varies under different operating conditions. The intelligent control module adjusts the calculation of heat generation power based on the operating condition parameters. ; in: The corrected heat generation power is expressed in W. This is the load correction factor, which is dimensionless.

[0041] The load correction factor is set to: Low load conditions: =0.8$; Medium load condition: =1.0$; High-load operating conditions: =1.3$; The intelligent control module also incorporates historical temperature data to establish a temperature change trend model. By analyzing temperature data from the past 30 minutes, it calculates the slope of temperature change and predicts future temperature trends.

[0042] The formula for calculating the slope of temperature change is: ; in: The slope of the temperature change is expressed in °C / min. The temperature at the current moment, in °C; The temperature at the previous moment, in °C; The time interval is expressed in minutes.

[0043] Based on the slope of temperature change, the formula for predicting temperature is revised as follows: ; in: The optimized predicted temperature is in °C. The predicted time duration is in minutes.

[0044] By incorporating operating parameters and historical data, the temperature prediction accuracy of this embodiment is improved by 15% to 20%, enabling more accurate prediction of temperature change trends and achieving more effective active thermal management control.

[0045] Example 3 Based on Example 1, this embodiment optimizes the control strategy of the heat exchange execution module. The intelligent control module adopts a fuzzy control algorithm to dynamically adjust the coolant flow rate of the liquid cooling circuit and the fan speed of the air cooling circuit according to the temperature deviation and the rate of temperature change. The temperature deviation is defined as: ; in: Temperature deviation, in °C; The target temperature is set at 27.5℃ (the midpoint of the normal operating temperature range). The current temperature is in °C.

[0046] Define the rate of temperature change as: ; This represents the rate of temperature change, expressed in °C / s.

[0047] Based on temperature deviation and rate of temperature change, the system state is divided into 9 cases: Temperature deviation: negative large ( <-10℃), negative small (-10℃≤ <-3℃), zero (-3℃≤ ≤3℃), positive small (3℃< ≤10℃), Zhengda ( >10℃); Temperature change rate: negative ( <-0.1℃ / s), zero (-0.1℃ / s≤ ≤0.1℃ / s), positive ( >0.1℃ / s).

[0048] For liquid cooling circuits, the control rules for coolant flow rate are as follows: (1) When the temperature deviation is negative and the temperature change rate is negative, the coolant flow rate is set to 3L / min; (2) When the temperature deviation is negative and the rate of temperature change is zero, the coolant flow rate is set to 5 L / min; (3) When the temperature deviation is zero and the rate of temperature change is zero, the coolant flow rate is set to 7 L / min; (4) When the temperature deviation is small and the temperature change rate is positive, the coolant flow rate is set to 10 L / min; (5) When the temperature deviation is positive and the temperature change rate is positive, the coolant flow rate is set to 15L / min.

[0049] For air-cooled circuits, the fan speed control rules are as follows: (1) When the temperature deviation is negative and the temperature change rate is negative, the fan speed is set to 1000 rpm; (2) When the temperature deviation is negative and the temperature change rate is zero, the fan speed is set to 1500 rpm; (3) When the temperature deviation is zero and the rate of temperature change is zero, the fan speed is set to 2000 rpm; (4) When the temperature deviation is small and the temperature change rate is positive, the fan speed is set to 2500 rpm; (5) When the temperature deviation is positive and the temperature change rate is positive, the fan speed is set to 3000 rpm.

[0050] Through fuzzy control algorithm, this embodiment can dynamically adjust the cooling intensity according to the temperature state, avoid energy waste caused by excessive cooling, and ensure the stability and speed of temperature control.

[0051] Example 4 This embodiment provides a system application scenario, applying the intelligent control system for thermal management of new energy vehicle batteries of the present invention to a pure electric passenger vehicle. The vehicle is equipped with a 60kWh ternary lithium battery pack, which contains 96 battery cells, each with a capacity of 50Ah and a nominal voltage of 3.7V.

[0052] The system installation steps are as follows: Step 1: Arrange 24 temperature sensors inside the battery pack, the sensor positions are based on... Figure 2 The layout scheme shown has been determined; Step 2: Install a cooling plate at the bottom of the battery pack. The cooling plate has dimensions of 1200mm × 800mm × 15mm, a flow channel width of 5mm, and a flow channel depth of 8mm. Step 3: Install the fan assembly and air duct on the side of the battery pack. The cross-sectional dimensions of the air duct are 100mm × 50mm. Step 4: Install the coolant pump, coolant piping, and radiator. The total coolant capacity is 8L. Step 5: Integrate the temperature acquisition module, data processing module, intelligent control module, and safety protection module onto the main control board of the battery management system.

[0053] Step 6: Connect the electrical and communication lines between the modules and perform system debugging.

[0054] System operation test: Test condition 1: Urban road driving, ambient temperature 25℃, driving distance 50km. During the test, the battery temperature was maintained between 22℃ and 32℃, and the temperature control was stable. The system mainly adopted the air cooling mode, and the fan speed was adjusted between 1500rpm and 2000rpm. The average energy consumption was 80W.

[0055] Test Condition 2: Highway driving, ambient temperature 35℃, driving distance 100km. During the test, the battery temperature was maintained between 28℃ and 38℃. The system adopted a hybrid liquid cooling and air cooling mode. The coolant flow rate was adjusted between 8L / min and 12L / min, and the fan speed was adjusted between 2000rpm and 2500rpm. The average energy consumption was 350W.

[0056] Test Condition 3: Fast charging, ambient temperature 30℃, charging power 60kW. During the test, the battery temperature rose from 25℃ to 42℃. The system started the liquid cooling circuit 5 minutes in advance to prevent the temperature from exceeding the warning threshold. During the charging process, the coolant flow rate was maintained at 15L / min and the fan speed was maintained at 3000rpm, and the temperature rise rate was effectively controlled.

[0057] Test results show that the system of the present invention can effectively control the battery temperature under different operating conditions, ensure that the battery operates within the normal operating temperature range, extend the battery life, and improve vehicle safety.

[0058] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A smart control system for thermal management of new energy vehicle batteries, comprising a smart control system, characterized in that: The intelligent control system includes: Temperature acquisition modules are installed at multiple monitoring locations on the battery pack to collect temperature data of individual battery cells. The data processing module is electrically connected to the temperature acquisition module and is used to receive and process temperature data and calculate the temperature distribution parameters of the battery pack. The intelligent control module is electrically connected to the data processing module and generates thermal management control commands based on temperature distribution parameters. The heat exchange execution module is electrically connected to the intelligent control module and adjusts the temperature of the battery pack according to control commands. The intelligent control module uses a temperature prediction algorithm to predict the battery temperature change trend in the future based on the current temperature data, vehicle driving conditions and battery charging and discharging status, and adjust the thermal management strategy in advance. The heat exchange execution module includes a liquid cooling circuit and an air cooling circuit. The liquid cooling circuit is located at the bottom of the battery pack, and the air cooling circuit is located on the side of the battery pack. The liquid cooling circuit and the air cooling circuit can be controlled independently and can work together.

2. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The temperature acquisition module includes a distributed temperature sensor array, with each sensor monitoring the temperature of 3 to 5 individual battery cells. The sensor sampling frequency is 0.5 Hz to 2 Hz.

3. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: When calculating the temperature distribution parameters, the data processing module uses a weighted average method, assigning a weight coefficient of 0.4 to the temperature data in the central area of ​​the battery pack, a weight coefficient of 0.3 to the temperature data in the edge area, and a weight coefficient of 0.3 to the temperature data in the corner area.

4. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The temperature prediction algorithm of the intelligent control module includes: A battery thermal model is established, which calculates the rate of temperature change based on the battery's heat generation and heat dissipation power. Calculate the heat generation power based on the current charging and discharging current and internal resistance parameters; Calculate the heat dissipation power based on the current cooling medium flow rate and temperature difference; Predict the battery temperature value within the next 5 to 15 minutes based on the rate of temperature change.

5. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The intelligent control module sets the temperature control threshold as follows: The normal operating temperature range is 20℃ to 35℃; The upper limit of the warning temperature is 40℃; The maximum protection temperature is 45℃; The lower limit of the warning temperature is 5℃; The lower limit of the protection temperature is 0℃.

6. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The liquid cooling circuit includes a coolant pump, coolant pipes, and a cooling plate. The cooling plate has a flow channel in which the coolant flows to remove heat. The flow rate of the coolant pump is adjustable from 3L / min to 15L / min.

7. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The air-cooling circuit includes a fan assembly and an air guide channel. The fan assembly has an adjustable speed, ranging from 1000 rpm to 3000 rpm. The air guide channel directs airflow along the side of the battery pack.

8. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The intelligent control module selects the thermal management operating mode based on the battery temperature and temperature change trend: When the battery temperature is below 20°C and the temperature is rising, the heat exchange execution module is shut down. When the battery temperature is between 20°C and 35°C, activate the air cooling circuit. When the battery temperature is above 35°C, both the liquid cooling circuit and the air cooling circuit are activated simultaneously.

9. The intelligent control system for thermal management of new energy vehicle batteries according to claim 1, characterized in that: The intelligent control system also includes a safety protection module. When the battery temperature is detected to exceed the protection threshold, the safety protection module triggers protection measures, limits the battery charging and discharging power, and adjusts the heat exchange execution module to the power output state.

Images