An intelligent temperature control cooling system for the drive motor of new energy vehicles

Abstract

The present invention proposes an intelligent temperature control and cooling system for a drive motor of a new energy vehicle. The intelligent temperature control and cooling system includes an electronic water pump, a temperature sensor array, and a control unit; wherein, the temperature sensor array is used to collect temperature data of each part of the motor in real time and send the temperature data to the control unit; the control unit is used to dynamically adjust the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of each part of the motor; at the same time, obtain a rotational speed dynamic compensation coefficient and a flow rate dynamic compensation coefficient according to the received temperature data, and adaptively adjust the rotational speed and coolant flow rate of the electronic water pump through the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient; the electronic water pump is used to adjust the rotational speed and coolant flow according to the instructions corresponding to the rotational speed and coolant flow rate given by the control unit, so as to achieve precise adjustment of the motor temperature.

Description

Technical Field

[0001] The present invention provides an intelligent temperature control cooling system for a drive motor of a new energy vehicle, belonging to the technical field of intelligent temperature control cooling. Background Art

[0002] As an important trend for future travel, the working principles of the drive motor and the cooling system, which are the core components of new energy vehicles, are particularly important. The drive motor system, as the power source of new energy vehicles, directly affects the driving efficiency, cruising range and safety of the vehicle. The cooling system is the key to dissipating heat from the drive motor and control system to prevent overheating damage and ensure the stable operation of the motor.

[0003] In the prior art, the cooling system of new energy vehicles usually adopts a traditional mechanical water pump and a fixed temperature sensor configuration. This configuration has the following deficiencies:

[0004] Inflexible water pump control: The rotation speed and coolant flow rate of the mechanical water pump are usually driven by the engine and cannot be dynamically adjusted according to the real-time temperature of the motor, resulting in low cooling efficiency and high energy consumption.

[0005] Limited accuracy of temperature sensors: The acquisition frequency of the fixed temperature sensors may not accurately reflect the temperature changes of each part of the motor. Especially when the motor is running at high speed or the load changes, the temperature distribution may be more complex and higher-precision temperature monitoring is required.

[0006] Lack of intelligent adjustment mechanism: The existing system lacks an intelligent adjustment mechanism for dynamically adjusting the sensor data acquisition frequency, water pump rotation speed and coolant flow rate according to temperature data, resulting in unsatisfactory cooling effect and may affect the service life and performance of the motor. Summary of the Invention

[0007] The present invention provides an intelligent temperature control cooling system for a drive motor of a new energy vehicle to solve the technical problems in the above prior art. The technical solutions adopted are as follows:

[0008] An intelligent temperature control cooling system for a drive motor of a new energy vehicle, the intelligent temperature control cooling system includes an electronic water pump, a temperature sensor array and a control unit; wherein,

[0009] The temperature sensor array is used to collect the temperature data of each part of the motor in real time and send the temperature data to the control unit;

[0010] The control unit is configured to dynamically adjust the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of various parts of the motor; meanwhile, obtain a rotational speed dynamic compensation coefficient and a flow rate dynamic compensation coefficient based on the received temperature data, and adaptively adjust the rotational speed and coolant flow rate of the electronic water pump through the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient;

[0011] The electronic water pump is configured to adjust the rotational speed and coolant flow according to the instructions corresponding to the rotational speed and coolant flow rate given by the control unit, so as to achieve precise regulation of the motor temperature.

[0012] Further, the temperature sensor array includes an ambient temperature sensor, a stator temperature sensor, a rotor surface temperature sensor, and a motor housing temperature sensor;

[0013] The temperature correlation coefficients between the target objects corresponding to the temperature sensors included in the temperature sensor array are as follows:

[0014] The temperature correlation coefficients between the ambient temperature sensor and the stator temperature sensor, the rotor surface temperature sensor, and the motor housing temperature sensor are λ 01 = 0.2, λ 02 = 0.1, and λ 03 = 0.4;

[0015] The temperature correlation coefficients between the stator temperature sensor and the rotor surface temperature sensor, and the motor housing temperature sensor are λ 04 = 0.6 and λ 05 = 0.5;

[0016] The temperature correlation coefficient k 01 λ 04 + k 02 λ 05 between the rotor surface temperature sensor and the motor housing temperature sensor, where k 01 and k 02 respectively represent the temperature influence coefficient between the stator and the rotor and the influence coefficient of the motor housing temperature on the stator temperature, and the specific values of the influence coefficients are obtained through experimental simulation means.

[0017] Further, dynamically adjusting the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of various parts of the motor includes:

[0018] Real-time monitoring of the temperature values obtained by each temperature sensor included in the temperature sensor array;

[0019] Obtaining the temperature change coefficient of the target object corresponding to each temperature sensor according to the temperature data collected by each temperature sensor;

[0020] Compare the temperature change coefficient with a preset temperature change coefficient threshold;

[0021] When any one of the temperature change coefficients exceeds the preset temperature change coefficient threshold, the temperature sensor with the temperature change coefficient exceeding the preset temperature change coefficient threshold is used as the target sensor, and the temperature sensors with temperature change coefficients not exceeding the preset temperature change coefficient threshold are used as associated sensors;

[0022] Adjust the temperature acquisition frequency of the target sensor using the temperature change coefficient of the target sensor;

[0023] Adjust the temperature acquisition frequency of the associated sensors using the temperature change coefficient of the target sensor in combination with the temperature change coefficients of the associated sensors.

[0024] Furthermore, obtaining the temperature change coefficient of the target object monitored by each temperature sensor according to the temperature data collected by each temperature sensor includes:

[0025] Extract the temperature data collected by each temperature sensor n times, and form a temperature vector corresponding to each temperature sensor using the temperature data collected n times; wherein, the structure of the temperature vector is as follows:

[0026]

[0027] wherein, T represents the temperature vector; T1, T2,..., T n respectively represent the temperature data collected n times;

[0028] Perform normalization processing on the temperature vector to obtain a normalized temperature standard vector, wherein the structure of the temperature standard vector is as follows:

[0029]

[0030] wherein, S represents the temperature standard vector, and S = [1 + exp(-T)] -1 ; T represents the temperature vector;

[0031] Obtain the temperature change coefficient of the target object monitored by each temperature sensor using the temperature standard vector corresponding to each temperature sensor;

[0032] wherein, the temperature change coefficient of the target object monitored by each temperature sensor is obtained through the following formula:

[0033]

[0034] wherein, G represents the temperature change coefficient of the target object monitored by each temperature sensor; Dr represents the first-order difference vector of the temperature standard vector, used to capture the temperature change trend; ⊙ represents the dot product operation of the corresponding elements of the vectors; S represents the temperature standard vector; S J represents the mean vector of the temperature standard vector; ΔS represents the second-order difference vector of the temperature standard vector; σ(ΔS) is the standard deviation function corresponding to the second-order difference ΔS of the temperature standard vector; I represents the identity matrix; S smooth represents the smoothed vector after smoothing the temperature standard vector; δ(S) represents the variance corresponding to the temperature standard vector.

[0035] Furthermore, the temperature acquisition frequency of the target sensor is adjusted using the temperature change coefficient of the target sensor, including:

[0036] extracting the temperature change coefficient corresponding to the target sensor and the temperature acquisition frequency of the target sensor;

[0037] obtaining the adjusted temperature acquisition frequency of the target sensor using the temperature change coefficient corresponding to the target sensor;

[0038] wherein, the adjusted temperature acquisition frequency of the target sensor is obtained through the following formula:

[0039]

[0040] wherein, f a represents the adjusted temperature acquisition frequency of the target sensor; f a0 represents the temperature acquisition frequency of the target sensor before adjustment; G m represents the temperature change coefficient of the target object monitored by the target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset non-linear factor, used to further control the smoothness and sensitivity of the adjustment, and its value range is 0.58 - 1.73.

[0041] Furthermore, the temperature acquisition frequency of the associated sensor is adjusted using the temperature change coefficient of the target sensor in combination with the temperature change coefficient of the associated sensor, including:

[0042] extracting the temperature correlation coefficient between the temperature of the target object corresponding to each preset associated sensor and the temperature of the target object corresponding to each target sensor;

[0043] Obtain the temperature acquisition frequency after adjustment corresponding to each associated sensor by combining the temperature change coefficient of the associated sensor and the temperature change coefficient of the target sensor with the temperature correlation coefficient between the temperature of the target object corresponding to each associated sensor and the temperature of the target object corresponding to each target sensor;

[0044] Among them, the temperature acquisition frequency after adjustment corresponding to each associated sensor is obtained through the following formula:

[0045]

[0046] Among them, f b represents the temperature acquisition frequency after adjustment corresponding to the associated sensor; f b0 represents the temperature acquisition frequency before adjustment corresponding to the associated sensor; G mi represents the temperature change coefficient of the target object monitored by the i-th target sensor that has an association relationship with the target object monitored by the associated sensor; G g represents the temperature change coefficient of the target object monitored by the associated sensor; w i represents the temperature correlation coefficient between the target objects monitored by the associated sensor and the i-th target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset non-linear factor, which is used to further control the smoothness and sensitivity of the adjustment, and its value range is 0.58 - 1.73.

[0047] Furthermore, obtain the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient according to the received temperature data, and adaptively adjust the rotational speed and the coolant flow rate of the electronic water pump through the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient, including:

[0048] The control unit receives the temperature data sent by the temperature sensor array in real time;

[0049] Obtain the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient by using the temperature data sent by the temperature sensor array;

[0050] Adaptively adjust the rotational speed of the electronic water pump by using the rotational speed dynamic compensation coefficient, and at the same time, adaptively adjust the coolant flow rate of the electronic water pump by using the flow rate dynamic compensation coefficient.

[0051] Furthermore, obtaining the rotational speed dynamic compensation coefficient by using the temperature data sent by the temperature sensor array includes:

[0052] Extract the temperature data sent by the temperature sensor array;

[0053] Compare the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold;

[0054] When the temperature data collected by any one of the temperature sensors reaches or exceeds its corresponding temperature threshold, obtain the rotational speed dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array;

[0055] Among them, the rotational speed dynamic compensation coefficient is obtained through the following formula:

[0056]

[0057] Among them, B r represents the rotational speed dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data that reaches or exceeds its corresponding temperature threshold; y represents the number of target objects corresponding to the temperature data that is lower than its corresponding temperature threshold; T xi represents the temperature data of the target object corresponding to the i-th temperature data that reaches or exceeds its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object corresponding to the i-th temperature data that is lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; J 01 and J 02 represent the first adjustment coefficient and the second adjustment coefficient;

[0058] Among them, the first adjustment coefficient is obtained through the following formula:

[0059]

[0060] Among them, J 01 represents the first adjustment coefficient; T xmaxi and T xmini represent the maximum temperature and the minimum temperature that occur corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; f xbi represents the standard deviation of the temperature acquisition frequency of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T xbi represents the standard deviation of the temperature data of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold;

[0061] At the same time, the first adjustment coefficient is obtained through the following formula:

[0062]

[0063] Among them, J 02 represents the second adjustment coefficient; T ymaxi and T ymini represent the maximum temperature and the minimum temperature that occur corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; f ybi represents the standard deviation of the temperature acquisition frequency of the target object whose i-th temperature data is lower than its corresponding temperature threshold; T ybi represents the standard deviation of the temperature data of the target object whose i-th temperature data is lower than its corresponding temperature threshold.

[0064] Furthermore, obtaining the flow dynamic compensation coefficient by using the temperature data sent by the temperature sensor array includes:

[0065] Extracting the temperature data sent by the temperature sensor array;

[0066] Comparing the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold;

[0067] When the temperature data collected by any one temperature sensor reaches or exceeds its corresponding temperature threshold, then obtaining the flow dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array;

[0068] Among them, the flow dynamic compensation coefficient is obtained through the following formula:

[0069]

[0070] Among them, B v represents the flow dynamic compensation coefficient; x represents the number of target objects whose temperature data reaches or exceeds its corresponding temperature threshold; y represents the number of target objects whose temperature data is lower than its corresponding temperature threshold; T xi represents the temperature data of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object whose i-th temperature data is lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; f xbp represents the average value of the standard deviation of the temperature acquisition frequency of x target objects whose temperature data reaches or exceeds its corresponding temperature threshold; T xbp represents the average value of the standard deviation of the temperature data of x target objects whose temperature data reaches or exceeds its corresponding temperature threshold; f ybpRepresents the average standard deviation of the temperature acquisition frequency of the target objects whose y temperature data are lower than their corresponding temperature thresholds; T ybp Represents the average standard deviation of the temperature data of the target objects whose y temperature data are lower than their corresponding temperature thresholds.

[0071] Furthermore, the rotation speed of the electronic water pump is adaptively adjusted using the rotation speed dynamic compensation coefficient, and at the same time, the coolant flow rate of the electronic water pump is adaptively adjusted using the flow rate dynamic compensation coefficient, including:

[0072] Compensate and adjust the rotation speed of the electronic water pump using the rotation speed dynamic compensation coefficient to obtain the compensated and adjusted rotation speed;

[0073] Among them, the compensated and adjusted rotation speed is obtained through the following formula:

[0074]

[0075] Among them, R represents the compensated and adjusted rotation speed; R0 represents the rotation speed before compensation adjustment; B r Represents the rotation speed dynamic compensation coefficient; x represents the number of target objects whose temperature data reach or exceed their corresponding temperature thresholds; T xi Represents the temperature data of the i-th target object whose temperature data reach or exceed their corresponding temperature thresholds; T zxi Represents the temperature threshold value corresponding to the i-th target object whose temperature data reach or exceed their corresponding temperature thresholds; η represents the regulation correlation coefficient of the preset temperature and rotation speed regulation; and the regulation correlation coefficient of the temperature and rotation speed regulation is obtained through experiments or simulations, etc.;

[0076] Control the motor of the electronic water pump to operate at the compensated and adjusted rotation speed;

[0077] Compensate and adjust the coolant flow rate of the electronic water pump using the flow rate dynamic compensation coefficient to obtain the compensated and adjusted coolant flow rate;

[0078] Among them, the compensated and adjusted coolant flow rate is obtained through the following formula:

[0079]

[0080] Among them, V represents the compensated and adjusted coolant flow rate; V0 represents the coolant flow rate before compensation adjustment; B v Represents the flow rate dynamic compensation coefficient; ξ represents the regulation correlation coefficient of the preset temperature and coolant flow rate regulation; and the regulation correlation coefficient of the temperature and coolant flow rate regulation is obtained through experiments or simulations, etc.;

[0081] Control the electronic water pump to operate at the compensated and adjusted coolant flow rate.

[0082] Advantages of the present invention:

[0083] An intelligent temperature control cooling system for a driving motor of a new energy vehicle proposed by the present invention can more accurately monitor and adjust the temperature of the motor by dynamically adjusting the data acquisition frequency of temperature sensors, the rotation speed of an electronic water pump, and the coolant flow rate. This not only improves the cooling efficiency but also reduces unnecessary energy consumption. Precise cooling control helps keep the motor operating within the optimal working temperature range, reducing the risk of damage caused by overheating. This helps extend the service life of the motor and reduce maintenance costs. The intelligent temperature control cooling system can adaptively adjust cooling parameters to cope with different working conditions and external environmental changes. This improves the stability of the entire driving system of the new energy vehicle, ensuring the driving safety and reliability of the vehicle. By optimizing the operating efficiency of the cooling system, the intelligent temperature control cooling system helps reduce the energy consumption and emissions of new energy vehicles. This meets the current global requirements for energy conservation, emission reduction, and sustainable development. Description of the drawings

[0084] Figure 1 is the system schematic diagram of the system described in the present invention. Detailed implementation manners

[0085] The following describes the preferred embodiments of the present invention with reference to the drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and are not used to limit the present invention.

[0086] An intelligent temperature control cooling system for a driving motor of a new energy vehicle proposed in an embodiment of the present invention, as Figure 1 shown, the intelligent temperature control cooling system includes an electronic water pump, a temperature sensor array, and a control unit; wherein,

[0087] The temperature sensor array is used to collect temperature data of each part of the motor in real time and send the temperature data to the control unit;

[0088] The control unit is used to dynamically adjust the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of each part of the motor; at the same time, obtain a rotation speed dynamic compensation coefficient and a flow rate dynamic compensation coefficient according to the received temperature data, and adaptively adjust the rotation speed and coolant flow rate of the electronic water pump through the rotation speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient;

[0089] The electronic water pump is used to adjust the rotation speed and coolant flow according to the instructions corresponding to the rotation speed and coolant flow rate given by the control unit, so as to achieve precise adjustment of the motor temperature.

[0090] The working principle of the above technical solution is as follows: The temperature sensor array is arranged at various key parts of the drive motor of a new energy vehicle to collect the temperature data of these parts in real time. These temperature data are converted into electrical signals through the internal circuit of the sensor and sent to the control unit. The control unit receives the temperature data from the temperature sensor array and dynamically adjusts the data acquisition frequency of each temperature sensor according to these data. If the temperature of a certain part changes rapidly or is relatively high, the control unit may increase the data acquisition frequency of the temperature sensor at that part to more accurately monitor the temperature change. The control unit calculates the rotational speed dynamic compensation coefficient and the flow dynamic compensation coefficient through the built-in algorithm based on the received temperature data. The control unit sends the calculated rotational speed and coolant flow commands to the electronic water pump. The electronic water pump adjusts its rotational speed and coolant flow according to these commands to achieve precise regulation of the motor temperature. Throughout the process, the control unit continuously receives the temperature data from the temperature sensor array and continuously adjusts the data acquisition frequency, compensation coefficient, and the adjustment commands of the electronic water pump according to these data. This feedback mechanism ensures that the cooling system can respond to the temperature change of the motor in real time and always maintain the best cooling effect.

[0091] The effects of the above technical solution are as follows: By dynamically adjusting the data acquisition frequency of the temperature sensor and the rotational speed and coolant flow of the electronic water pump, the intelligent temperature control cooling system can more accurately monitor and regulate the temperature of the motor. This not only improves the cooling efficiency but also reduces unnecessary energy consumption. Precise cooling control helps to keep the motor operating within the optimal working temperature range, reducing the risk of damage caused by overheating. This helps to extend the service life of the motor and reduce the maintenance cost. The intelligent temperature control cooling system can adaptively adjust the cooling parameters to cope with different working conditions and external environment changes. This improves the stability of the entire new energy vehicle drive system, ensuring the driving safety and reliability of the vehicle. By optimizing the operating efficiency of the cooling system, the intelligent temperature control cooling system helps to reduce the energy consumption and emissions of new energy vehicles. This meets the current global requirements for energy conservation, emission reduction, and sustainable development.

[0092] In summary, through its unique working principle and advanced technical effects, the intelligent temperature control cooling system provides a more efficient, reliable, and environmentally friendly cooling solution for the drive motor of new energy vehicles.

[0093] In an embodiment of the present invention, the temperature sensor array includes an ambient temperature sensor, a stator temperature sensor, a rotor surface temperature sensor, and a motor housing temperature sensor;

[0094] The temperature correlation coefficients between the target objects corresponding to the temperature sensors included in the temperature sensor array are as follows:

[0095] The temperature correlation coefficients between the ambient temperature sensor and the stator temperature sensor, the rotor surface temperature sensor, and the motor housing temperature sensor are λ 01 = 0.2, λ 02 = 0.1, and λ 03 = 0.4;

[0096] The temperature correlation coefficients between the stator temperature sensor and the rotor surface temperature sensor, and the motor housing temperature sensor are λ 04 = 0.6 and λ 05 = 0.5;

[0097] The temperature correlation coefficient k 01 λ 04 + k 02 λ 05 between the rotor surface temperature sensor and the motor housing temperature sensor, where k 01 and k 02 represent the temperature influence coefficient between the stator and the rotor and the influence coefficient of the motor housing temperature on the stator temperature respectively, and the specific values of the influence coefficients are obtained by means of experimental simulation.

[0098] The working principle of the above technical solution is as follows: Ambient temperature sensor: used to monitor the temperature of the environment where the drive motor of a new energy vehicle is located.

[0099] Stator temperature sensor: placed inside the motor stator to monitor the temperature of the stator winding.

[0100] Rotor surface temperature sensor: used to directly measure the temperature of the motor rotor surface, which is the key to evaluating the rotor heat dissipation effect and thermal state.

[0101] Motor housing temperature sensor: monitors the temperature of the motor housing and reflects the overall heat dissipation situation of the motor.

[0102] Temperature data acquisition and transmission: Each temperature sensor collects the temperature data of the corresponding target object in real time. These data are transmitted to the control unit and used as the basis for subsequent temperature correlation analysis and cooling system adjustment.

[0103] Application of temperature correlation coefficient: Temperature correlation coefficients (such as λ01, λ02, λ03, λ04, λ05) describe the degree of association of temperature changes between different temperature sensors. The temperature correlation coefficient between the temperature sensor on the rotor surface and the temperature sensor on the motor housing is jointly determined by the temperature influence coefficient k01 between the stator and the rotor and the influence coefficient k02 of the motor housing temperature on the stator temperature, reflecting the complexity and mutual relevance of temperature changes. The control unit performs intelligent analysis based on the received temperature data and temperature correlation coefficients. Based on the analysis results, the control unit dynamically adjusts the parameters of the cooling system (such as the rotational speed of the electric water pump and the coolant flow rate) to achieve precise control of the motor temperature. At the same time, the system continuously monitors temperature changes and adjusts the data acquisition frequency of the temperature sensors and the adjustment strategy of the cooling system as needed.

[0104] The effects of the above technical solution are as follows: By arranging multiple temperature sensors and considering the temperature correlation coefficients between them, the system can more comprehensively monitor the temperature state of the motor. This helps to accurately identify temperature abnormal points and improve the accuracy and reliability of temperature monitoring. Using the temperature correlation coefficients for intelligent analysis, the control unit can more precisely adjust the parameters of the cooling system. This helps to maximize the cooling efficiency while reducing unnecessary energy consumption. Precise temperature monitoring and cooling system adjustment help to keep the motor operating within the optimal working temperature range. This reduces the risk of damage caused by overheating and improves the stability and safety of the entire new energy vehicle drive system. The specific values of the temperature correlation coefficients and influence coefficients are obtained through experimental simulation, which helps to verify and optimize the performance of the system. Based on the experimental data, the system can be further optimized and improved to enhance its adaptability and reliability.

[0105] In summary, through the application of the temperature sensor array and temperature correlation coefficients, the technical solution realizes precise monitoring and intelligent adjustment of the temperature of the drive motor of a new energy vehicle. This helps to improve the stability and safety of the system, while optimizing the performance of the cooling system and reducing energy consumption.

[0106] In one embodiment of the present invention, the data acquisition frequency of each temperature sensor in the temperature sensor array is dynamically adjusted according to the temperature data of each part of the motor, including:

[0107] Real-time monitoring of the temperature values obtained by each temperature sensor included in the temperature sensor array;

[0108] Obtaining the temperature change coefficient of the target object corresponding to each temperature sensor according to the temperature data collected by each temperature sensor;

[0109] Comparing the temperature change coefficient with a preset temperature change coefficient threshold;

[0110] When any one of the temperature change coefficients exceeds a preset temperature change coefficient threshold, the temperature sensor with a temperature change coefficient exceeding the preset temperature change coefficient threshold is used as the target sensor, and the temperature sensor with a temperature change coefficient not exceeding the preset temperature change coefficient threshold is used as the associated sensor;

[0111] Adjust the temperature acquisition frequency of the target sensor using the temperature change coefficient of the target sensor;

[0112] Adjust the temperature acquisition frequency of the associated sensor using the temperature change coefficient of the target sensor in combination with the temperature change coefficient of the associated sensor.

[0113] The working principle of the above technical solution is as follows: The system first monitors in real time the temperature values obtained by each temperature sensor included in the temperature sensor array. These temperature values reflect the current temperature states of various parts of the motor. Then, based on the temperature data collected by each temperature sensor, the system calculates the temperature change coefficient of the target object monitored by each temperature sensor. This coefficient reflects the speed or intensity of the temperature change of the target object. The system compares the calculated temperature change coefficient with a preset temperature change coefficient threshold. This threshold is set according to the normal operating conditions of the motor and the temperature monitoring requirements. When the temperature change coefficient of any temperature sensor exceeds the preset threshold, the sensor is identified as the target sensor. At the same time, other sensors with temperature change coefficients not exceeding the threshold are used as associated sensors. For the target sensor, the system directly adjusts its temperature acquisition frequency using its temperature change coefficient. If the temperature change coefficient is large, it indicates that the temperature of the target object changes rapidly, and more frequent temperature data acquisition is required for real-time monitoring. For the associated sensors, the system adjusts their temperature acquisition frequencies not only considering their own temperature change coefficients but also in combination with the temperature change coefficient of the target sensor. This is because the associated sensors may be affected by the temperature change of the object monitored by the target sensor, or there is a certain temperature correlation between them.

[0114] The effects of the above technical solution are as follows: By dynamically adjusting the data acquisition frequency of the temperature sensors, the system can more efficiently monitor the temperature changes of various parts of the motor. When the temperature changes rapidly, increasing the data acquisition frequency can ensure that the system promptly captures temperature anomalies and thus takes corresponding adjustment measures. Dynamically adjusting the data acquisition frequency can also optimize the allocation of system resources. For parts with slow temperature changes, reducing the data acquisition frequency can reduce the system's energy consumption and data processing burden. When a temperature anomaly occurs in a certain part of the motor, the system can quickly identify and adjust the data acquisition frequency of the relevant temperature sensors, thereby more rapidly responding to temperature changes and ensuring the safe operation of the motor. By combining the temperature change coefficients of the target sensors and the associated sensors to adjust the data acquisition frequency, the system can more accurately reflect the temperature correlation and changes among various parts of the motor, thus improving the accuracy of temperature monitoring.

[0115] In summary, through dynamically adjusting the data acquisition frequencies of the temperature sensors in the temperature sensor array, this technical solution realizes precise monitoring and efficient response to the temperature changes of various parts of the motor. This helps improve the stability and safety of the system, while optimizing resource allocation and reducing energy consumption.

[0116] In one embodiment of the present invention, obtaining the temperature change coefficient of the target object monitored by each temperature sensor according to the temperature data collected by each temperature sensor includes:

[0117] Extracting the temperature data collected by each temperature sensor n times and using the temperature data collected n times to form a temperature vector corresponding to each temperature sensor; wherein, the structure of the temperature vector is as follows:

[0118]

[0119] wherein, T represents the temperature vector; T1, T2,..., T n respectively represent the temperature data collected n times;

[0120] Performing normalization processing on the temperature vector to obtain a normalized temperature standard vector, wherein the structure of the temperature standard vector is as follows:

[0121]

[0122] wherein, S represents the temperature standard vector, and S = [1 + exp(-T)] -1 ; T represents the temperature vector;;

[0123] Obtaining the temperature change coefficient of the target object monitored by each temperature sensor by using the temperature standard vector corresponding to each temperature sensor;

[0124] Among them, the temperature change coefficient of the target object monitored by each temperature sensor is obtained through the following formula:

[0125]

[0126] Among them, G represents the temperature change coefficient of the target object monitored by each temperature sensor; D r represents the first-order difference vector of the temperature standard vector, used to capture the temperature change trend; ⊙ represents the dot product operation of the corresponding elements of the vector; S represents the temperature standard vector; S J represents the mean vector of the temperature standard vector; ΔS represents the second-order difference vector of the temperature standard vector; σ(ΔS) is the standard deviation function corresponding to the second-order difference ΔS of the temperature standard vector; I represents the identity matrix; S smooth represents the smoothed vector after smoothing the temperature standard vector; δ(S) represents the variance corresponding to the temperature standard vector.

[0127] The working principle of the above technical solution is as follows: The system first extracts the temperature data collected n times by each temperature sensor, and these data constitute the temperature vector T corresponding to each temperature sensor. The temperature vector T is an array containing n elements, where T1, T2,..., Tn respectively represent the temperature data collected n times.

[0128] Next, the system performs standardization processing on the temperature vector T to obtain the temperature standard vector S after standardization processing. The purpose of standardization processing is to eliminate the differences caused by factors such as range and accuracy between different temperature sensors, so that the temperature data is comparable. The formula for standardization processing is S = [1 + exp(-T)]-1, where S represents the temperature standard vector and T represents the original temperature vector. After obtaining the temperature standard vector S, the system uses this vector to calculate the temperature change coefficient G of the target object monitored by each temperature sensor. This coefficient reflects the speed or intensity of the temperature change of the target object.

[0129] The calculation formula of the temperature change coefficient G involves multiple parameters and operation steps. First, calculate the first-order difference vector Dr of the temperature standard vector S to capture the temperature change trend. Then, use parameters such as the first-order difference vector Dr, the temperature standard vector S, the mean vector SJ of the temperature standard vector, the second-order difference vector ΔS of the temperature standard vector and its standard deviation σ(ΔS), the identity matrix I, and the smoothed vector Ssmooth after smoothing the temperature standard vector to finally obtain the temperature change coefficient G.

[0130] The effects of the above technical solution are as follows: By standardizing the temperature vector, the differences between different temperature sensors are eliminated, making the temperature data comparable. This helps improve the accuracy of temperature monitoring. Using the first-order difference vector Dr to capture the temperature change trend can more sensitively reflect the temperature change. This is of great significance for timely detecting temperature anomalies and preventing equipment failures. By calculating the temperature change coefficient G, the speed or severity of the temperature change of the target object is quantified. This provides an important basis for evaluating the thermal state of the equipment and optimizing the cooling system. The technical solution takes into account various factors (such as first-order difference, second-order difference, smoothing processing, etc.), enabling the system to analyze temperature data more comprehensively and enhancing its adaptability to different working conditions and environments. At the same time, obtaining the temperature change coefficient through the above mathematical operations also improves the robustness of the system.

[0131] On the other hand, by standardizing the temperature vector, the differences caused by factors such as range and accuracy between different temperature sensors are eliminated, making the temperature data comparable. This helps improve the accuracy of temperature data acquisition and provides a reliable basis for subsequent calculation of the temperature change coefficient and adjustment of the acquisition frequency. Using the above mathematical operations and various parameters (such as first-order difference, second-order difference, smoothing processing, etc.) to calculate the temperature change coefficient can more comprehensively reflect the temperature change characteristics of the target object. This refined calculation method improves the accuracy of the temperature change coefficient, thus ensuring the accuracy of the dynamic adjustment of the temperature acquisition frequency. By calculating the first-order difference vector of the temperature standard vector, the temperature change trend can be sensitively captured. When the temperature changes slightly, the first-order difference vector will respond quickly, providing a timely signal for the dynamic adjustment of the temperature acquisition frequency. When the temperature change coefficient exceeds the preset threshold, the system can quickly identify and adjust the data acquisition frequency of the relevant temperature sensors. This rapid response mechanism ensures that the system can timely capture temperature anomalies and take effective adjustment measures. When adjusting the data acquisition frequency of the temperature sensors, not only the temperature change coefficient of the target sensor is considered, but also the temperature change coefficients of the associated sensors are comprehensively considered. This global adjustment strategy ensures that the data acquisition frequencies of each sensor can match each other, avoiding redundancy and missing of data acquisition. By dynamically adjusting the data acquisition frequency, the system can reasonably allocate resources according to actual needs. For parts with faster temperature changes, the data acquisition frequency is increased to ensure timely monitoring; for parts with slower temperature changes, the data acquisition frequency is reduced to reduce energy consumption and data processing burden. This optimization strategy improves the overall efficiency and performance of the system.

[0132] Meanwhile, dynamically adjust the data acquisition frequency of the temperature sensor so that the system can more efficiently monitor the temperature changes of each part of the motor. This helps improve the monitoring efficiency of the system and reduce the monitoring cost. Through precise temperature monitoring and timely adjustment of the acquisition frequency, the system can more accurately reflect the temperature correlation and change situation among different parts of the motor. This helps enhance the stability of the system and improve the reliability and service life of the equipment. This technical solution provides strong support for the intelligent decision-making of the temperature monitoring system. By real-time analyzing the temperature change coefficient and dynamically adjusting the data acquisition frequency, the system can automatically optimize the monitoring strategy and improve the accuracy and efficiency of monitoring.

[0133] In summary, the above technical solution shows significant technical effects in performance indicators such as the accuracy and sensitivity of the dynamic adjustment of the temperature acquisition frequency and the matching between the data acquisition frequencies of various sensors. These effects together improve the overall performance and reliability of the temperature monitoring system, providing strong guarantee for the safe operation and intelligent management of the equipment. At the same time, through a series of the above mathematical operations and parameter settings, this technical solution realizes the precise analysis of temperature data and the accurate calculation of the temperature change coefficient. This helps improve the accuracy of temperature monitoring, capture the temperature change trend, quantify the degree of temperature change, and enhance the adaptability and robustness of the system.

[0134] In one embodiment of the present invention, adjusting the temperature acquisition frequency of the target sensor by using the temperature change coefficient of the target sensor includes:

[0135] Extracting the temperature change coefficient corresponding to the target sensor and the temperature acquisition frequency of the target sensor;

[0136] Obtaining the adjusted temperature acquisition frequency of the target sensor by using the temperature change coefficient corresponding to the target sensor;

[0137] Wherein, the adjusted temperature acquisition frequency of the target sensor is obtained through the following formula:

[0138]

[0139] Wherein, f a represents the adjusted temperature acquisition frequency of the target sensor; f a0 represents the temperature acquisition frequency of the target sensor before adjustment; G m represents the temperature change coefficient of the target object monitored by the target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset non-linear factor, which is used to further control the smoothness and sensitivity of the adjustment, and its value range is 0.58 - 1.73.

[0140] The working principle of the above technical solution is as follows: The system first extracts the temperature change coefficient Gm corresponding to the target sensor, which reflects the speed or intensity of the temperature change of the target object. At the same time, the system also extracts the current temperature acquisition frequency of the target sensor, that is, the acquisition frequency before adjustment. Using the extracted temperature change coefficient and the preset influence factors (α, β, γ), the adjusted temperature acquisition frequency of the target sensor is calculated through a specific formula. In the formula, α represents the influence factor of the temperature change coefficient on the frequency adjustment, which determines the influence degree of the temperature change coefficient on the adjustment range of the acquisition frequency. β represents the influence factor of the temperature change amount on the adjustment range, which reflects the direct contribution of the temperature change amount to the adjustment range of the acquisition frequency. γ represents the non-linear factor, which is used to further control the smoothness and sensitivity of the adjustment to ensure that the adjustment of the acquisition frequency is neither too drastic nor too slow. The system applies the calculated adjusted temperature acquisition frequency to the target sensor, thereby realizing the dynamic adjustment of the temperature acquisition frequency.

[0141] The effect of the above technical solution is as follows: By dynamically adjusting the acquisition frequency of the temperature sensor, the system can more efficiently monitor the temperature change of the target object. When the temperature changes rapidly, the acquisition frequency increases to ensure timely detection of temperature anomalies; when the temperature changes slowly, the acquisition frequency decreases to reduce unnecessary energy consumption and data processing burden. This technical solution can reasonably allocate resources according to actual needs. For parts with drastic temperature changes, the acquisition frequency is increased to ensure the timeliness of monitoring; for parts with gentle temperature changes, the acquisition frequency is reduced to reduce costs. This optimization strategy improves the overall efficiency and performance of the system. Through accurate temperature monitoring and timely adjustment of the acquisition frequency, the system can more accurately reflect the temperature change characteristics of the target object. This helps to enhance the stability of the system, improve the reliability and service life of the equipment. This technical solution provides strong support for the intelligent decision-making of the temperature monitoring system. By real-time analyzing the temperature change coefficient and dynamically adjusting the acquisition frequency, the system can automatically optimize the monitoring strategy and improve the accuracy and efficiency of monitoring. Due to the introduction of the non-linear factor γ, this technical solution can more flexibly adapt to the temperature change characteristics under different working conditions and environments. Whether it is a rapid change or a slow change, the system can ensure the accuracy and timeliness of monitoring by adjusting the acquisition frequency.

[0142] In summary, the above technical solution realizes the optimization and improvement of the temperature monitoring system by using the temperature change coefficient of the target sensor to dynamically adjust its temperature acquisition frequency. This technical solution not only improves the monitoring efficiency, optimizes the resource allocation, enhances the system stability, but also supports intelligent decision-making and has strong adaptability.

[0143] An embodiment of the present invention adjusts the temperature acquisition frequency of an associated sensor by combining the temperature change coefficient of a target sensor with the temperature change coefficient of the associated sensor, including:

[0144] Extract the temperature correlation coefficient between the temperature of the target object corresponding to each preset associated sensor and the temperature of the target object corresponding to each target sensor;

[0145] Use the temperature correlation coefficient between the temperature of the target object corresponding to each associated sensor and the temperature of the target object corresponding to each target sensor, combined with the temperature change coefficient of the associated sensor and the temperature change coefficient of the target sensor, to obtain the adjusted temperature acquisition frequency corresponding to each associated sensor;

[0146] Among them, the adjusted temperature acquisition frequency corresponding to each associated sensor is obtained through the following formula:

[0147]

[0148] Among them, f b represents the adjusted temperature acquisition frequency corresponding to the associated sensor; f b0 represents the temperature acquisition frequency corresponding to the associated sensor before adjustment; G mi represents the temperature change coefficient of the target object monitored by the i-th target sensor associated with the target object monitored by the associated sensor; G g represents the temperature change coefficient of the target object monitored by the associated sensor; w i represents the temperature correlation coefficient between the target objects monitored by the associated sensor and the i-th target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset non-linear factor, which is used to further control the smoothness and sensitivity of the adjustment, and its value range is 0.58 - 1.73.

[0149] The working principle of the above technical solution is as follows: First, the system extracts the temperature correlation coefficient wi between the temperature of the target object corresponding to each preset associated sensor and the temperature of the target object corresponding to each target sensor. These coefficients reflect the correlation of temperature changes between the associated sensor and the target sensor. Then, the system obtains the temperature change coefficient of the target object monitored by the associated sensor, and the temperature change coefficients of each target sensor that has an associated relationship with the target object monitored by the associated sensor. Using the extracted temperature correlation coefficient, the temperature change coefficient of the associated sensor, the temperature change coefficient of the target sensor, and the preset influencing factors (α, β, γ), the system calculates the adjusted temperature acquisition frequency corresponding to the associated sensor through a specific formula. In the formula, α represents the influencing factor of the temperature change coefficient on the frequency adjustment, which determines the degree of influence of the temperature change coefficient on the adjustment range of the acquisition frequency. β represents the influencing factor of the temperature change amount on the adjustment range, which reflects the direct contribution of the temperature change amount to the adjustment range of the acquisition frequency. γ represents the non-linear factor, which is used to further control the smoothness and sensitivity of the adjustment to ensure that the adjustment of the acquisition frequency is neither too drastic nor too slow. w i As the temperature correlation coefficient, it reflects the degree of temperature change correlation between the associated sensor and the target sensor, thus affecting the adjustment of the acquisition frequency of the associated sensor. The system applies the calculated adjusted temperature acquisition frequency fb to the associated sensor, thereby realizing the dynamic adjustment of the temperature acquisition frequency of the associated sensor.

[0150] The effects of the above technical solution are as follows: By comprehensively considering the temperature correlation coefficient between the associated sensor and the target sensor and their respective temperature change coefficients, the system can more accurately reflect the temperature correlation and change situation between the target objects. This helps to improve the accuracy of temperature monitoring. This technical solution can reasonably allocate resources according to actual needs. For parts with drastic temperature changes and high correlation, the acquisition frequency is increased to ensure the timeliness of monitoring; for parts with gentle temperature changes or low correlation, the acquisition frequency is reduced to lower costs. This optimization strategy improves the overall efficiency and performance of the system. Through precise temperature monitoring and timely adjustment of the acquisition frequency, the system can more accurately reflect the temperature change characteristics of the target object, thereby enhancing the stability of the system. This helps to improve the reliability and service life of the equipment. This technical solution provides strong support for the intelligent decision-making of the temperature monitoring system. By analyzing the temperature change coefficient, temperature correlation coefficient in real time and dynamically adjusting the acquisition frequency, the system can automatically optimize the monitoring strategy and improve the accuracy and efficiency of monitoring. Due to the introduction of the non-linear factor γ and the temperature correlation coefficient, this technical solution can more flexibly adapt to the temperature change characteristics and the correlation between sensors under different working conditions and environments. Whether it is a fast-changing or slow-changing situation, the system can ensure the accuracy and timeliness of monitoring by adjusting the acquisition frequency.

[0151] In summary, the above technical solution dynamically adjusts the temperature acquisition frequency of the associated sensor by comprehensively considering the temperature change coefficients of the target sensor and the associated sensor and the temperature correlation coefficient between them, achieving the optimization and improvement of the temperature monitoring system. This technical solution not only improves the monitoring accuracy, optimizes the resource allocation, enhances the system stability, but also supports intelligent decision-making and has strong adaptability.

[0152] An embodiment of the present invention obtains a rotational speed dynamic compensation coefficient and a flow rate dynamic compensation coefficient according to the received temperature data, and adaptively adjusts the rotational speed of the electric water pump and the coolant flow rate through the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient, including:

[0153] The control unit receives the temperature data sent by the temperature sensor array in real time;

[0154] Obtain a rotational speed dynamic compensation coefficient and a flow rate dynamic compensation coefficient by using the temperature data sent by the temperature sensor array;

[0155] Use the rotational speed dynamic compensation coefficient to adaptively adjust the rotational speed of the electric water pump, and at the same time, use the flow rate dynamic compensation coefficient to adaptively adjust the coolant flow rate of the electric water pump.

[0156] The working principle of the above technical solution is as follows: The control unit receives the temperature data sent by the temperature sensor array in real time. These temperature data reflect the temperature conditions at different positions in the cooling system. By using the received temperature data, the system calculates the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient through a specific algorithm or model. These coefficients reflect the changes in the requirements for the rotational speed of the electric water pump and the coolant flow rate under the current temperature conditions. According to the calculated rotational speed dynamic compensation coefficient, the system adaptively adjusts the rotational speed of the electric water pump. When the temperature data indicates that an increase in cooling effect is required, the rotational speed dynamic compensation coefficient will increase accordingly, thereby increasing the rotational speed of the electric water pump and improving the coolant circulation speed. At the same time, according to the flow rate dynamic compensation coefficient, the system adaptively adjusts the coolant flow rate of the electric water pump. When the temperature data indicates that an increase in coolant flow rate is required to improve the heat dissipation efficiency, the flow rate dynamic compensation coefficient will increase accordingly, thereby increasing the coolant flow rate.

[0157] The effects of the above technical solution are as follows: By receiving temperature data in real time and dynamically adjusting the rotational speed and coolant flow rate of the electric water pump accordingly, the system can more accurately meet the requirements of the cooling system. This helps improve the cooling efficiency and ensure that key components such as the engine always remain within the optimal operating temperature range. The dynamic compensation coefficient adjustment mechanism enables the system to better cope with external disturbances such as temperature fluctuations and load changes. This helps enhance the stability of the system and reduce the risk of failures caused by abnormal temperatures. By adaptively adjusting the rotational speed and coolant flow rate of the electric water pump, the system can avoid unnecessary energy consumption. When the temperature is low or the load is light, the system can reduce the rotational speed and coolant flow rate of the electric water pump, thereby reducing energy consumption. A stable cooling system can ensure that the vehicle always maintains a good operating state, reducing the failure rate and maintenance costs caused by temperature problems. This helps improve the driving experience and satisfaction of users. This technical solution embodies the concept of intelligent management. Through real-time monitoring and dynamic adjustment, the system can automatically optimize the performance of the cooling system and reduce the need for manual intervention.

[0158] In summary, the above technical solution realizes the intelligent management of the cooling system by receiving temperature data in real time and dynamically adjusting the rotational speed and coolant flow rate of the electric water pump accordingly. This technical solution not only improves the cooling efficiency, enhances the system stability, reduces the energy consumption, but also improves the user experience and the level of intelligent management.

[0159] An embodiment of the present invention for obtaining the rotational speed dynamic compensation coefficient by using the temperature data sent by the temperature sensor array includes:

[0160] Extract the temperature data sent by the temperature sensor array;

[0161] Compare the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold;

[0162] When the temperature data collected by any one of the temperature sensors reaches or exceeds its corresponding temperature threshold, then obtain the rotational speed dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array;

[0163] Wherein, the rotational speed dynamic compensation coefficient is obtained through the following formula:

[0164]

[0165] Wherein, B r represents the rotational speed dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; y represents the number of target objects corresponding to the temperature data lower than its corresponding temperature threshold; T xirepresents the temperature data of the target object corresponding to the i-th temperature data reaching or exceeding its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object corresponding to the i-th temperature data being lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; J 01 and J 02 represent the first adjustment coefficient and the second adjustment coefficient;

[0166] Among them, the first adjustment coefficient is obtained through the following formula:

[0167]

[0168] Among them, J 01 represents the first adjustment coefficient; T xmaxi and T xmini represent the maximum temperature and the minimum temperature corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; f xbi represents the standard deviation of the temperature acquisition frequency of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T xbi represents the standard deviation of the temperature data of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold;

[0169] Meanwhile, the first adjustment coefficient is obtained through the following formula:

[0170]

[0171] Among them, J 02 represents the second adjustment coefficient; T ymaxi and T ymini represent the maximum temperature and the minimum temperature corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; f ybi represents the standard deviation of the temperature acquisition frequency of the target object whose i-th temperature data is lower than its corresponding temperature threshold; T ybi represents the standard deviation of the temperature data of the target object whose i-th temperature data is lower than its corresponding temperature threshold.

[0172] The working principle of the above technical solution is as follows: The system first extracts the temperature data sent by the temperature sensor array. Then, it compares the temperature data collected by each temperature sensor with its corresponding temperature threshold. These temperature thresholds are preset according to the system requirements and are used to determine whether the temperature is within the normal range. When the temperature data collected by any temperature sensor reaches or exceeds its corresponding temperature threshold, the calculation process of the rotational speed dynamic compensation coefficient is triggered. This indicates that the system has detected an abnormal temperature or a high-temperature situation and needs to adjust the rotational speed of the electronic water pump to enhance the cooling effect. The calculation of the first adjustment coefficient takes into account the maximum temperature, minimum temperature, standard deviation of the temperature acquisition frequency, and standard deviation of the temperature data of the target object whose temperature data reaches or exceeds the threshold. The calculation of the second adjustment coefficient considers the corresponding parameters of the target object whose temperature data is lower than the threshold. The calculation of these two adjustment coefficients helps to more accurately reflect the characteristics of the temperature data, thereby more accurately calculating the rotational speed dynamic compensation coefficient. Finally, according to the calculated rotational speed dynamic compensation coefficient, the system adaptively adjusts the rotational speed of the electronic water pump. When the temperature data indicates that the cooling effect needs to be increased, the rotational speed dynamic compensation coefficient will increase accordingly, thereby increasing the rotational speed of the electronic water pump.

[0173] The effects of the above technical solution are as follows: By real-time monitoring of the temperature data and dynamically adjusting the rotational speed of the electronic water pump according to the temperature anomaly, the system can respond more accurately to the cooling requirements. This helps to improve the cooling efficiency and ensure that the system is always in the best working state. The dynamic rotational speed adjustment mechanism enables the system to better cope with external interferences such as temperature fluctuations and load changes. This helps to enhance the stability of the system and reduce the risk of failures caused by abnormal temperatures. Through precise temperature monitoring and rotational speed adjustment, the system can avoid unnecessary energy consumption. When the temperature is low or the load is light, the system can reduce the rotational speed of the electronic water pump, thereby saving energy. This technical solution embodies the concept of intelligent management. Through real-time monitoring and dynamic adjustment, the system can automatically optimize the performance of the cooling system and reduce the need for manual intervention. This technical solution takes into account various temperature data characteristics (such as maximum value, minimum value, standard deviation, etc.), enabling the system to more flexibly adapt to temperature changes under different working conditions and environments.

[0174] In summary, the above technical solution realizes the intelligent management of the cooling system by real-time monitoring of the temperature data and dynamically adjusting the rotational speed of the electronic water pump according to the temperature anomaly. This technical solution not only improves the cooling efficiency, enhances the system stability, optimizes the resource allocation, but also improves the intelligent level and adaptability.

[0175] An embodiment of the present invention obtains a flow dynamic compensation coefficient by using the temperature data sent by the temperature sensor array, including:

[0176] Extracting the temperature data sent by the temperature sensor array;

[0177] Compare the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold;

[0178] When the temperature data collected by any one temperature sensor reaches or exceeds its corresponding temperature threshold, obtain a flow dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array;

[0179] Among them, the flow dynamic compensation coefficient is obtained through the following formula:

[0180]

[0181] Among them, B v represents the flow dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data that reaches or exceeds its corresponding temperature threshold; y represents the number of target objects corresponding to the temperature data that is lower than its corresponding temperature threshold; T xi represents the temperature data of the target object corresponding to the i-th temperature data that reaches or exceeds its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object corresponding to the i-th temperature data that is lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; f xbp represents the average value of the standard deviation of the temperature acquisition frequency of the target objects with x temperature data reaching or exceeding their corresponding temperature thresholds; T xbp represents the average value of the standard deviation of the temperature data of the target objects with x temperature data reaching or exceeding their corresponding temperature thresholds; f ybp represents the average value of the standard deviation of the temperature acquisition frequency of the target objects with y temperature data lower than their corresponding temperature thresholds; T ybp represents the average value of the standard deviation of the temperature data of the target objects with y temperature data lower than their corresponding temperature thresholds.

[0182] The working principle of the above technical solution is as follows: The system first extracts the temperature data sent by the temperature sensor array. Then, these temperature data are compared with a preset temperature threshold. The temperature threshold is set according to the normal operating temperature range of the system or device and is used to determine whether the current temperature deviates from the normal range. When the temperature data collected by any temperature sensor reaches or exceeds its corresponding temperature threshold, the calculation of the flow dynamic compensation coefficient is triggered. This indicates that the system has detected a temperature anomaly or high temperature situation, and it may be necessary to increase the coolant flow to enhance the cooling effect. According to the calculated flow dynamic compensation coefficient Bv, the system adaptively adjusts the flow rate of the coolant. When the temperature data indicates that an increase in the cooling effect is required, the flow dynamic compensation coefficient will increase accordingly, thereby increasing the coolant flow rate.

[0183] The effects of the above technical solution are as follows: By real-time monitoring of temperature data and dynamically adjusting the coolant flow according to temperature anomalies, the system can respond more accurately to cooling requirements. This helps to improve the cooling efficiency and ensure that the system or device is always in the best working state. The dynamic flow adjustment mechanism enables the system to better cope with external disturbances such as temperature fluctuations and load changes. This helps to enhance the stability of the system and reduce the risk of failures caused by temperature anomalies. Through precise temperature monitoring and flow adjustment, the system can avoid unnecessary energy consumption. When the temperature is low or the load is light, the system can reduce the coolant flow rate, thus saving energy. This technical solution embodies the concept of intelligent management. Through real-time monitoring and dynamic adjustment, the system can automatically optimize the performance of the cooling system and reduce the need for manual intervention. This technical solution takes into account various temperature data characteristics (such as the standard deviation average of temperature acquisition frequency, the standard deviation average of temperature data, etc.), enabling the system to more flexibly adapt to temperature changes under different working conditions and environments.

[0184] In summary, the above technical solution realizes the intelligent management of the cooling system by real-time monitoring of temperature data and dynamically adjusting the coolant flow according to temperature anomalies. This technical solution not only improves the cooling efficiency, enhances the system stability, optimizes the resource allocation, but also improves the intelligent level and adaptability.

[0185] In an embodiment of the present invention, the rotational speed of the electronic water pump is adaptively adjusted by using the rotational speed dynamic compensation coefficient, and at the same time, the coolant flow rate of the electronic water pump is adaptively adjusted by using the flow dynamic compensation coefficient, including:

[0186] The rotational speed of the electronic water pump is compensated and adjusted by using the rotational speed dynamic compensation coefficient to obtain the compensated and adjusted rotational speed;

[0187] Wherein, the compensated and adjusted rotational speed is obtained through the following formula:

[0188]

[0189] Wherein, R represents the rotational speed after compensation adjustment; R0 represents the rotational speed before compensation adjustment; B r represents the rotational speed dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; T xi represents the temperature data of the i-th target object corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object for which the i-th temperature data reaches or exceeds its corresponding temperature threshold; η represents the preset regulation correlation coefficient between temperature and rotational speed regulation; and, the regulation correlation coefficient between temperature and rotational speed regulation is obtained through experiments or simulations, etc.;

[0190] Control the motor of the electronic water pump to operate at the rotational speed after compensation adjustment;

[0191] Use the flow dynamic compensation coefficient to compensate and adjust the coolant flow of the electronic water pump to obtain the coolant flow after compensation adjustment;

[0192] Wherein, the coolant flow after compensation adjustment is obtained through the following formula:

[0193]

[0194] Wherein, V represents the coolant flow after compensation adjustment; V0 represents the coolant flow before compensation adjustment; B v represents the flow dynamic compensation coefficient; ξ represents the preset regulation correlation coefficient between temperature and coolant flow regulation; and, the regulation correlation coefficient between temperature and coolant flow regulation is obtained through experiments or simulations, etc.;

[0195] Control the electronic water pump to operate at the coolant flow after compensation adjustment.

[0196] The working principle of the above technical solution is as follows: The system first calculates the rotational speed dynamic compensation coefficient according to the temperature data sent by the temperature sensor array. Then, use this rotational speed dynamic compensation coefficient to compensate and adjust the original rotational speed of the electronic water pump to obtain the rotational speed after compensation adjustment. The compensation adjustment process takes into account the number of target objects corresponding to the temperature data reaching or exceeding the temperature threshold, the number of target objects corresponding to the temperature data lower than the temperature threshold, the relevant temperature data, and the preset regulation correlation coefficient between temperature and rotational speed regulation. The regulation correlation coefficient is obtained through experiments or simulations, etc., and is used to reflect the regulation relationship between temperature and rotational speed. Finally, the system controls the motor of the electronic water pump to operate at the rotational speed after compensation adjustment.

[0197] Similar to the dynamic compensation adjustment of the rotational speed, the system also calculates the dynamic compensation coefficient of the flow rate based on the temperature data sent by the temperature sensor array. Then, the original coolant flow rate of the electric water pump is compensated and adjusted using this dynamic compensation coefficient of the flow rate to obtain the compensated and adjusted coolant flow rate. The process of compensation and adjustment also takes into account the number of target objects whose temperature data reaches or exceeds the temperature threshold, the number of target objects whose temperature data is lower than the temperature threshold, the relevant temperature data, and the preset regulation correlation coefficient between temperature and coolant flow rate. The regulation correlation coefficient is also obtained through experiments or simulations, etc., and is used to reflect the regulation relationship between temperature and coolant flow rate. Finally, the system controls the electric water pump to operate according to the compensated and adjusted coolant flow rate.

[0198] The effects of the above technical solution are as follows: By monitoring the temperature data in real time and dynamically adjusting the rotational speed and coolant flow rate of the electric water pump according to the temperature anomalies, the system can respond more accurately to the cooling requirements. This helps to improve the cooling efficiency and ensure that the system or equipment is always in the best working state. The dynamic rotational speed and flow rate adjustment mechanism enables the system to better cope with external disturbances such as temperature fluctuations and load changes. This helps to enhance the stability of the system and reduce the risk of failures caused by temperature anomalies. Through precise temperature monitoring and rotational speed and flow rate adjustment, the system can avoid unnecessary energy consumption. When the temperature is low or the load is light, the system can reduce the rotational speed and coolant flow rate of the electric water pump, thus saving energy. This technical solution embodies the concept of intelligent management. Through real-time monitoring and dynamic adjustment, the system can automatically optimize the performance of the cooling system and reduce the need for manual intervention. This technical solution takes into account various temperature data characteristics (such as the number of target objects whose temperature data reaches or exceeds the temperature threshold, the number of target objects whose temperature data is lower than the temperature threshold, etc.), as well as the preset regulation correlation coefficient, enabling the system to more flexibly adapt to temperature changes under different working conditions and environments. Through precise rotational speed and flow rate adjustment, the system can ensure that the cooling system always operates in the best state, thereby extending the service life of the system or equipment and improving the reliability of the system.

[0199] In summary, the above technical solution realizes the intelligent management of the cooling system by monitoring the temperature data in real time and dynamically adjusting the rotational speed and coolant flow rate of the electric water pump according to the temperature anomalies. This technical solution not only improves the cooling efficiency, enhances the system stability, optimizes the resource allocation, but also improves the intelligent level and adaptability, and at the same time enhances the reliability of the system.

[0200] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications.

Claims

1. An intelligent temperature control cooling system for a drive motor of a new energy vehicle, characterized in that, The intelligent temperature-controlled cooling system includes an electronic water pump, a temperature sensor array, and a control unit; wherein, The temperature sensor array is used to collect the temperature data of each part of the motor in real time and send the temperature data to the control unit; The control unit is used to dynamically adjust the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of each part of the motor and the temperature change coefficient of the target object monitored by each temperature sensor; at the same time, obtain the rotational speed dynamic compensation coefficient and the flow dynamic compensation coefficient according to the received temperature data, and adaptively adjust the rotational speed and the coolant flow of the electronic water pump through the rotational speed dynamic compensation coefficient and the flow dynamic compensation coefficient; wherein, the temperature change coefficient is obtained by the following method: Obtaining the temperature change coefficient of the target object monitored by each temperature sensor according to the temperature data collected by each temperature sensor, including: Extracting the temperature data collected by each temperature sensor n times and forming a temperature vector corresponding to each temperature sensor by using the temperature data collected n times; wherein, the structure of the temperature vector is as follows: Among them, T represents the temperature vector; T1, T2, ……, T n respectively represent the temperature data collected n times; Performing normalization processing on the temperature vector to obtain a normalized temperature standard vector, wherein, the structure of the temperature standard vector is as follows: Among them, S represents the temperature standard vector, and S = [1 + exp(-T)] -1 ; T represents the temperature vector; Obtaining the temperature change coefficient of the target object monitored by each temperature sensor by using the temperature standard vector corresponding to each temperature sensor; Wherein, the temperature change coefficient of the target object monitored by each temperature sensor is obtained by the following formula: Among them, G represents the temperature change coefficient of the target object monitored by each temperature sensor; D r represents the first-order difference vector of the temperature standard vector, used to capture the temperature change trend; ⊙ represents the dot product operation of the corresponding elements of the vector; S represents the temperature standard vector; S J represents the mean vector of the temperature standard vector; ΔS represents the second-order difference vector of the temperature standard vector; σ(ΔS) is the standard deviation function corresponding to the second-order difference ΔS of the temperature standard vector; I represents the identity matrix; S smooth represents the smoothed vector after smoothing the temperature standard vector; δ(S) represents the variance corresponding to the temperature standard vector; The electronic water pump is used to adjust the rotational speed and the coolant flow according to the instructions corresponding to the rotational speed and the coolant flow given by the control unit to achieve precise regulation of the motor temperature.

2. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 1, wherein The temperature sensor array includes an ambient temperature sensor, a stator temperature sensor, a rotor surface temperature sensor, and a motor housing temperature sensor; The temperature correlation coefficients between the target objects corresponding to the temperature sensors included in the temperature sensor array are as follows: The temperature correlation coefficients between the ambient temperature sensor and the stator temperature sensor, the rotor surface temperature sensor, and the motor housing temperature sensor are λ 01 = 0.2, λ 02 = 0.1, and λ 03 = 0.4; The temperature correlation coefficients between the stator temperature sensor, the rotor surface temperature sensor, and the motor housing temperature sensor are λ 04 = 0.6 and λ 05 = 0.5; The temperature correlation coefficient k between the rotor surface temperature sensor and the motor housing temperature sensor 01 λ 04 +k 02 λ 05 , where k 01 and k 02 respectively represent the temperature influence coefficient between the stator and the rotor and the influence coefficient of the motor housing temperature on the stator temperature.

3. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 1, wherein, Dynamically adjusting the data acquisition frequency of each temperature sensor in the temperature sensor array according to the temperature data of each part of the motor, including: Real-time monitoring the temperature values obtained by each temperature sensor included in the temperature sensor array; Obtaining the temperature change coefficient of the target object monitored by each temperature sensor according to the temperature data collected by each temperature sensor; Comparing the temperature change coefficient with a preset temperature change coefficient threshold; When any one of the temperature change coefficients exceeds the preset temperature change coefficient threshold, the temperature sensor whose temperature change coefficient exceeds the preset temperature change coefficient threshold is used as the target sensor, and the temperature sensor whose temperature change coefficient does not exceed the preset temperature change coefficient threshold is used as the associated sensor; Adjusting the temperature acquisition frequency of the target sensor by using the temperature change coefficient of the target sensor; Adjusting the temperature acquisition frequency of the associated sensor by using the temperature change coefficient of the target sensor in combination with the temperature change coefficient of the associated sensor.

4. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 3, wherein Adjusting the temperature acquisition frequency of the target sensor by using the temperature change coefficient of the target sensor, including: Extract the temperature change coefficient corresponding to the target sensor and the temperature acquisition frequency of the target sensor; Obtain the adjusted temperature acquisition frequency of the target sensor by using the temperature change coefficient corresponding to the target sensor; Among them, the adjusted temperature acquisition frequency of the target sensor is obtained through the following formula: Among them, f a represents the adjusted temperature acquisition frequency of the target sensor; f a0 represents the temperature acquisition frequency of the target sensor before adjustment; G m represents the temperature change coefficient of the target object monitored by the target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset non - linear factor, which is used to further control the smoothness and sensitivity of the adjustment, and its value range is 0.58 - 1.

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5. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 3, characterized in that, Adjust the temperature acquisition frequency of the associated sensor by using the temperature change coefficient of the target sensor in combination with the temperature change coefficient of the associated sensor, including: Extract the temperature correlation coefficient between the temperature of the target object corresponding to each preset associated sensor and the temperature of the target object corresponding to each target sensor; Obtain the adjusted temperature acquisition frequency corresponding to each associated sensor by using the temperature correlation coefficient between the temperature of the target object corresponding to each associated sensor and the temperature of the target object corresponding to each target sensor in combination with the temperature change coefficient of the associated sensor and the temperature change coefficient of the target sensor; Among them, the adjusted temperature acquisition frequency corresponding to each associated sensor is obtained through the following formula: Among them, f b represents the adjusted temperature acquisition frequency corresponding to the associated sensor; f b0 represents the temperature acquisition frequency before adjustment corresponding to the associated sensor; G mi represents the temperature change coefficient of the target object monitored by the i-th target sensor associated with the target object monitored by the associated sensor; G g represents the temperature change coefficient of the target object monitored by the associated sensor; w i represents the temperature correlation coefficient between the target objects monitored by the associated sensor and the i-th target sensor; α represents the influence factor of the preset temperature change coefficient on the frequency adjustment, and its value range is 0.26 - 0.51; β represents the influence factor of the preset temperature change amount on the adjustment amplitude, and its value range is 0.14 - 0.33; γ represents the preset nonlinear factor, which is used to further control the smoothness and sensitivity of the adjustment, and moreover, its value range is 0.58 - 1.

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6. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 1, wherein Obtain the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient according to the received temperature data, and adaptively adjust the rotational speed and the coolant flow rate of the electric water pump by using the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient, including: The control unit receives the temperature data sent by the temperature sensor array in real time; Obtain the rotational speed dynamic compensation coefficient and the flow rate dynamic compensation coefficient by using the temperature data sent by the temperature sensor array; Adaptively adjust the rotational speed of the electric water pump by using the rotational speed dynamic compensation coefficient. At the same time, adaptively adjust the coolant flow rate of the electric water pump by using the flow rate dynamic compensation coefficient.

7. The intelligent temperature control cooling system for a drive motor of a new energy vehicle according to claim 6, characterized in that Obtain the rotational speed dynamic compensation coefficient by using the temperature data sent by the temperature sensor array, including: Extract the temperature data sent by the temperature sensor array; Compare the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold; When the temperature data collected by any one temperature sensor reaches or exceeds its corresponding temperature threshold, then obtain the rotational speed dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array; Among them, the rotational speed dynamic compensation coefficient is obtained through the following formula: Among them, B r represents the rotational speed dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; y represents the number of target objects corresponding to the temperature data lower than its corresponding temperature threshold; T xi represents the temperature data of the target object corresponding to the i-th temperature data reaching or exceeding its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object where the i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object corresponding to the i-th temperature data lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object where the i-th temperature data is lower than its corresponding temperature threshold; J 01 and J 02 represent the first adjustment coefficient and the second adjustment coefficient; Among them, the first adjustment coefficient is obtained through the following formula: Among them, J 01 represents the first adjustment coefficient; T xmaxi and T xmini represent the maximum temperature and the minimum temperature corresponding to the target object when the i-th temperature data reaches or exceeds its corresponding temperature threshold; f xbi represents the standard deviation of the temperature acquisition frequency of the target object when the i-th temperature data reaches or exceeds its corresponding temperature threshold; T xbi represents the standard deviation of the temperature data of the target object when the i-th temperature data reaches or exceeds its corresponding temperature threshold; At the same time, the first adjustment coefficient is obtained through the following formula: Among them, J 02 represents the second adjustment coefficient; T ymaxi and T ymini represent the maximum temperature and the minimum temperature corresponding to the target object whose ith temperature data is lower than its corresponding temperature threshold; f ybi represents the standard deviation of the temperature acquisition frequency of the target object whose ith temperature data is lower than its corresponding temperature threshold; T ybi represents the standard deviation of the temperature data of the target object whose ith temperature data is lower than its corresponding temperature threshold.

8. The intelligent temperature control and cooling system for the drive motor of a new energy vehicle according to claim 6, characterized in that, Obtain the flow rate dynamic compensation coefficient by using the temperature data sent by the temperature sensor array, including: Extract the temperature data sent by the temperature sensor array; Compare the temperature data collected by each temperature sensor included in the temperature sensor array with its corresponding temperature threshold; When the temperature data collected by any one temperature sensor reaches or exceeds its corresponding temperature threshold, then obtain the flow rate dynamic compensation coefficient by using the temperature data collected by each temperature sensor included in the temperature sensor array; Among them, the flow rate dynamic compensation coefficient is obtained through the following formula: Among them, B v represents the flow dynamic compensation coefficient; x represents the number of target objects whose temperature data reaches or exceeds its corresponding temperature threshold; y represents the number of target objects whose temperature data is lower than its corresponding temperature threshold; T xi represents the temperature data of the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; T yi represents the temperature data of the target object whose i-th temperature data is lower than its corresponding temperature threshold; T zyi represents the temperature threshold value corresponding to the target object whose i-th temperature data is lower than its corresponding temperature threshold; f xbp represents the average standard deviation of the temperature acquisition frequency of the target objects whose x temperature data reaches or exceeds its corresponding temperature threshold; T xbp represents the average standard deviation of the temperature data of the target objects whose x temperature data reaches or exceeds its corresponding temperature threshold; f ybp represents the average standard deviation of the temperature acquisition frequency of the target objects whose y temperature data is lower than its corresponding temperature threshold; T ybp represents the average standard deviation of the temperature data of the target objects whose y temperature data is lower than its corresponding temperature threshold.

9. The intelligent temperature control cooling system for the drive motor of a new energy vehicle according to claim 6, characterized in that, Adaptively adjust the rotational speed of the electric water pump by using the rotational speed dynamic compensation coefficient. At the same time, adaptively adjust the coolant flow rate of the electric water pump by using the flow rate dynamic compensation coefficient, including: Compensate and adjust the speed of the electric water pump by using the rotational speed dynamic compensation coefficient to obtain the compensated and adjusted speed; Among them, the compensated and adjusted speed is obtained through the following formula: Wherein, R represents the rotational speed after compensation adjustment; R0 represents the rotational speed before compensation adjustment; B r represents the rotational speed dynamic compensation coefficient; x represents the number of target objects corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; T xi represents the temperature data of the i-th target object corresponding to the temperature data reaching or exceeding its corresponding temperature threshold; T zxi represents the temperature threshold value corresponding to the target object whose i-th temperature data reaches or exceeds its corresponding temperature threshold; η represents the preset regulation correlation coefficient between temperature and rotational speed regulation; Control the motor of the electric water pump to operate at the compensated and adjusted speed; Compensate and adjust the coolant flow rate of the electric water pump by using the flow rate dynamic compensation coefficient to obtain the compensated and adjusted coolant flow rate; Among them, the compensated and adjusted coolant flow rate is obtained through the following formula: Among them, V represents the coolant flow rate after compensation adjustment; V0 represents the coolant flow rate before compensation adjustment; B v represents the flow dynamic compensation coefficient; ξ represents the preset control correlation coefficient between temperature and coolant flow rate regulation; control the electronic water pump to operate according to the coolant flow rate after compensation adjustment.

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