A high-temperature-resistant brushless hollow cup motor and a thermal management system

Abstract

The application relates to the technical field of electric machines, and discloses a high-temperature-resistant brushless hollow cup motor and a thermal management system, the system comprising a temperature working condition judgment module, a dynamic current regulation module, a self-adaptive heat dissipation module, a load-temperature adaptation module and a cloud strategy optimization module; the temperature working condition judgment module generates a three-dimensional temperature distribution map in real time and locates a hot spot area, thereby providing a data basis for thermal management; the self-adaptive heat dissipation module is combined to perform directional air cooling adjustment on the identified overheated area, the problems of heat dissipation control lag and overcontrol caused by unclear temperature field sensing are solved, and the reliability of the motor caused by local high temperature is avoided. The dynamic current regulation module is used for intelligently regulating driving current based on a real-time temperature rise rate, and a smooth modulation technology is adopted to avoid output torque mutation, and the contradiction between rapid current reduction and performance maintenance is solved.

Description

Technical Field

[0001] This invention relates to the field of motor technology, specifically to a high-temperature resistant brushless hollow cup motor and its thermal management system. Background Technology

[0002] Coreless motors are DC permanent magnet servo and control motors, and can also be classified as micro motors. In terms of structure, coreless motors break through the traditional rotor structure of motors. Coreless motors have outstanding energy-saving characteristics, sensitive and convenient control characteristics, and stable operation characteristics. As a high-efficiency energy conversion device, they represent the development direction of motors in many fields.

[0003] Currently, when high-temperature resistant brushless coreless motors operate under high-temperature conditions, their internal temperature field distribution is uneven and dynamically changes drastically. Existing thermal management methods cannot reconstruct the three-dimensional temperature distribution inside the motor in real time and accurately locate overheated areas. This results in a lack of precise data for heat dissipation control, causing response lag and overreaction, making it difficult to suppress the formation of local hot spots, and leading to motor insulation aging and permanent magnet demagnetization failures.

[0004] Therefore, a high-temperature resistant brushless hollow cup motor and thermal management system are proposed to solve the above problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a high-temperature resistant brushless hollow cup motor and thermal management system, which solves the problems of motor insulation aging and permanent magnet demagnetization mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a high-temperature resistant brushless hollow cup motor and a thermal management system, the system comprising:

[0007] The temperature condition judgment module collects the internal temperature data of the motor in real time through a multi-source sensor array, performs fusion processing on the collected temperature data, generates a three-dimensional temperature distribution map inside the motor and calculates the overall temperature rise rate. When the temperature value exceeds the preset warning threshold and the temperature rise rate exceeds the preset safety threshold, it determines that the motor has entered a high temperature condition state and activates the thermal management control process.

[0008] The dynamic current control module receives the high-temperature operating condition status signal, three-dimensional temperature distribution map and temperature rise rate data output by the temperature operating condition judgment module. Based on the temperature rise rate, it dynamically adjusts the drive current parameters. When the temperature rise rate exceeds the preset safety threshold, it gradually reduces the drive current amplitude and achieves smooth adjustment of output power through pulse width modulation technology.

[0009] An adaptive heat dissipation module receives the three-dimensional temperature distribution map generated by the temperature working condition judgment module, identifies the hotspot area with a temperature greater than 150 DEG C in the map, and adjusts the rotation speed of the heat dissipation fan and the angle of the flow guide piece in real time, wherein the rotation speed of the fan is positively correlated with the temperature of the hotspot area.

[0010] Preferably, it further comprises:

[0011] A load-temperature adaptation module receives the driving current parameters output by the dynamic current regulation module, the temperature data and the three-dimensional temperature distribution map of the temperature working condition judgment module, combines real-time load change data, dynamically calculates the optimal matching parameters of the rotation speed and the torque through a fuzzy logic decision unit, and ensures the stability of the output performance under high temperature working conditions;

[0012] A cloud strategy optimization module receives the operation data, regulation parameters and three-dimensional temperature distribution map of the temperature working condition judgment module, the dynamic current regulation module, the adaptive heat dissipation module and the load-temperature adaptation module, uploads them to the cloud platform, generates a historical fault mode matching library and an optimized control strategy through data desensitization, fault mode induction and strategy iteration comparison, and feeds back the optimized working condition warning threshold, safety threshold and control parameters to the temperature working condition judgment module and the dynamic current regulation module to update their preset values.

[0013] Preferably, the temperature working condition judgment module comprises:

[0014] The multi-source sensor array is specifically a micro thermocouple sensor array, which is arranged in the key heat-sensitive areas of the motor stator winding, the rotor axis and the bearing position;

[0015] A noise suppression unit: an adaptive filter circuit is used to eliminate environmental electromagnetic interference, so that the temperature collection error is less than ±1 DEG C;

[0016] A high-temperature activation logic unit: when the temperature value of three consecutive sampling periods exceeds the working condition warning threshold, and the temperature gradient change rate is greater than 5 DEG C / min, the heat management control process is triggered.

[0017] Preferably, the execution steps of the dynamic current regulation module comprise:

[0018] Establishing a temperature rise rate-current mapping table: storing the maximum allowable current amplitude corresponding to different temperature intervals;

[0019] A hierarchical current reduction mechanism: when the temperature rise rate exceeds the threshold, the driving current is reduced by 10% gradient step by step, and the adjustment interval is greater than 30 seconds each time;

[0020] A pulse width modulation compensation unit: the pulse width modulation technology is used to adjust the PWM duty cycle to compensate for the output fluctuation caused by the current change, realize the smooth adjustment of the output power, and maintain the output torque fluctuation range less than ±5%.

[0021] Preferably, the dynamic current regulation module is configured with a current protection subunit:

[0022] A minimum current protection threshold is set, and when the driving current amplitude decreases to 30% of the rated value, the standby cooling device is automatically triggered;

[0023] The standby cooling device is a micro liquid cooling circulation module, and the pipeline is embedded in the heat conduction layer inside the motor housing.

[0024] Preferably, the adaptive cooling module comprises:

[0025] Temperature distribution reconstruction unit: convert discrete sensor data into a three-dimensional thermal map, and identify hot spot areas with a temperature greater than 150°C;

[0026] Fan speed control logic: set the speed according to the following formula:

[0027] ;

[0028] Wherein is the fan speed, is the heat dissipation efficiency coefficient, is the hot spot temperature rise difference;

[0029] Air deflector deflection mechanism: automatically adjust the angle of the air deflector according to the temperature gradient direction, so that the airflow concentrates on the hot spot area;

[0030] The heat dissipation efficiency coefficient is optimized by historical operation data self-learning:

[0031] The initial value is set to 80RPM / ℃;

[0032] Every 24 hours of operation, the actual heat dissipation effect is dynamically corrected according to the deviation from the theoretical value Value, the correction process satisfies the formula:

[0033] ;

[0034] Wherein is the corrected coefficient, is the uncorrected coefficient, is the actual temperature drop difference, is the theoretical temperature drop difference, is the correction factor and ;

[0035] The correction amplitude is less than 5%.

[0036] Preferably, the load-temperature adaptive module comprises:

[0037] Performance mapping model: Stores a table showing the correspondence between the maximum allowable load, speed, and torque of the motor at different temperatures;

[0038] Fuzzy decision engine: Input variables include real-time load change rate, current temperature value and heat dissipation efficiency, and output variables are speed adjustment coefficient and torque compensation value;

[0039] Dynamic limiter: When the model output parameters exceed the material tolerance limit, the output is forcibly locked to a safe threshold.

[0040] Preferably, the performance mapping model is constructed in the following manner:

[0041] Collect historical operating data: covering motor operating parameters in the temperature range of -40℃ to 200℃ and the load range of 10%-100%;

[0042] Data filtering rules: Remove abnormal operating condition data with temperature fluctuations greater than ±10℃ / min;

[0043] Model validation mechanism: After every 100 hours of additional running data, the model prediction error rate is re-validated. The error rate is calculated using the following formula:

[0044] ;

[0045] in For error rate, This is the actual value. This is a predicted value;

[0046] Model reconstruction is triggered when the error rate is greater than 8%.

[0047] Preferably, the cloud-based strategy optimization module is implemented in the following ways:

[0048] Data anonymization unit: Uploads data after removing device identification information from the operational data;

[0049] Historical fault mode library generation: Historical fault data is summarized into five typical modes: winding overheating, bearing failure, insulation aging, rotor eccentricity and drive abnormality.

[0050] Strategy iteration process: The local control effect is compared with the cloud simulation results every week, and the optimization strategy that can reduce the temperature rise by more than 15% is given priority.

[0051] Preferably, the motor performance parameters satisfy:

[0052] Rated speed ≥10000 r / min, rated current ≤5.8A, rated torque ≥0.27 N·m;

[0053] Locked rotor current ≤ 41A, locked rotor torque ≥ 1.940 N·m;

[0054] Furthermore, under conditions where the temperature increases by 5°C, the torque output can be maintained at 10 N·m when the speed increases by 50 rpm.

[0055] Beneficial effects

[0056] Compared with the prior art, the present invention provides a high-temperature resistant brushless hollow cup motor and thermal management system, which has the following beneficial effects:

[0057] 1. In this invention, a three-dimensional temperature distribution map is generated in real time and hot spots are located by a temperature condition judgment module, providing a data foundation for thermal management; combined with an adaptive heat dissipation module, directional air cooling adjustment is performed on the identified overheated areas, solving the problems of lag and over-heating control caused by unclear temperature field perception, and avoiding the decrease in motor reliability caused by local high temperature.

[0058] 2. In this invention, the drive current is intelligently adjusted based on the real-time temperature rise rate by the dynamic current control module, and the output torque is avoided by smooth modulation technology, thus solving the contradiction between rapid current reduction and performance maintenance; combined with the load-temperature adaptation module, the optimal speed and torque parameters are dynamically calculated according to the real-time operating conditions, overcoming the defect of poor adaptability of the fixed model, and ensuring the stable operation of the motor under complex thermal-load coupling conditions.

[0059] 3. In this invention, the cloud-based strategy optimization module performs in-depth mining and learning of multi-source operating data, generates a fault mode library, iteratively optimizes the control strategy, and feeds it back to the local execution unit. This frees the system from dependence on human experience, enables it to continuously self-optimize and make forward-looking decisions, and improves the accuracy of thermal management and the long-term reliability of the system. Attached Figure Description

[0060] Figure 1 This is a thermal management system architecture diagram of a high-temperature resistant brushless hollow cup motor according to the present invention. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] For specific implementation examples, please refer to: Figure 1 A high-temperature resistant brushless hollow cup motor and thermal management system, the system comprising:

[0063] The temperature condition judgment module collects the internal temperature data of the motor in real time through a multi-source sensor array, performs fusion processing on the collected temperature data, generates a three-dimensional temperature distribution map inside the motor and calculates the overall temperature rise rate. When the temperature value exceeds the preset warning threshold and the temperature rise rate exceeds the preset safety threshold, it determines that the motor has entered a high temperature condition state and activates the thermal management control process.

[0064] The specific steps for generating a three-dimensional temperature distribution map include:

[0065] I. Spatial Data Mapping: Obtain the spatial coordinates of each sensor in the multi-source sensor array and the real-time temperature data it collects;

[0066] II. Temperature Field Interpolation and Reconstruction: Based on the acquired discrete point temperature data, a spatial interpolation algorithm is used to estimate the temperature value in the three-dimensional space inside the motor, generating continuous voxelized temperature field data;

[0067] The interpolation calculation formula is as follows:

[0068] ;

[0069] in For estimation points Temperature value at that location, For the first The measured temperature values ​​of each sensor. For estimation points To the The Euclidean distance between the sensors This is the distance attenuation coefficient. The number of sensors involved in the interpolation. For summation index;

[0070] III. Heatmap Rendering Output: Convert temperature field data into a two-dimensional heatmap layer containing color information corresponding to different temperature values, and generate a three-dimensional temperature distribution map through layer stacking and rendering;

[0071] The dynamic current control module receives the high-temperature operating condition status signal, three-dimensional temperature distribution map and temperature rise rate data output by the temperature condition judgment module. Based on the temperature rise rate, it dynamically adjusts the drive current parameters. When the temperature rise rate exceeds the preset safety threshold, it gradually reduces the drive current amplitude and achieves smooth adjustment of output power through pulse width modulation technology.

[0072] The adaptive heat dissipation module receives a three-dimensional temperature distribution map generated by the temperature condition judgment module, identifies hot spots with temperatures greater than 150°C in the map, and adjusts the cooling fan speed and the angle of the air guide in real time. The fan speed is positively correlated with the temperature of the hot spot area.

[0073] Also includes:

[0074] The load-temperature adaptation module receives the drive current parameters output by the dynamic current control module, the temperature data and three-dimensional temperature distribution map from the temperature condition judgment module, and combines them with real-time load change data. Through the fuzzy logic decision unit, it dynamically calculates the optimal matching parameters of speed and torque to ensure stable output performance under high temperature conditions.

[0075] The cloud-based strategy optimization module receives operating data, control parameters, and a three-dimensional temperature distribution map from the temperature condition judgment module, dynamic current control module, adaptive heat dissipation module, and load-temperature adaptation module. It then uploads these data to the cloud platform. Through data anonymization, fault mode summarization, and strategy iteration comparison, it generates a historical fault mode matching library and optimized control strategies. The optimized operating condition warning threshold, safety threshold, and control parameters are then fed back to the temperature condition judgment module and dynamic current control module to update their preset values.

[0076] The temperature condition judgment module includes:

[0077] The multi-source sensor array is specifically a miniature thermocouple sensor array: deployed in key heat-sensitive areas of the motor stator windings, rotor shaft, and bearing positions.

[0078] Noise suppression unit: Adaptive filtering circuit is used to eliminate environmental electromagnetic interference, ensuring that the temperature acquisition error is less than ±1℃;

[0079] High temperature activation logic unit: When the temperature value exceeds the operating condition warning threshold for three consecutive sampling cycles and the temperature gradient change rate is greater than 5℃ / min, the thermal management control process is triggered.

[0080] The dynamic current regulation module performs the following steps:

[0081] Establish a temperature rise rate-current mapping table: store the maximum allowable current amplitude corresponding to different temperature ranges;

[0082] Graded current reduction mechanism: When the temperature rise rate exceeds the threshold, the drive current is reduced in stages by 10%, with each adjustment interval greater than 30 seconds. The calculation formula is as follows:

[0083] ;

[0084] in The adjusted drive current amplitude, This represents the maximum allowable current amplitude corresponding to the current temperature range. For real-time temperature rise rate, To preset a safety threshold, This is the gradient step size;

[0085] Pulse Width Modulation Compensation Unit: Adjusts the PWM duty cycle using pulse width modulation technology to compensate for output fluctuations caused by current changes, achieving smooth adjustment of output power and maintaining output torque fluctuations within ±5%.

[0086] The specific steps by which the pulse width modulation compensation unit achieves smooth adjustment include:

[0087] I. Current Sampling and Comparison: The actual driving current of the motor winding is sampled in real time and compared with the target current amplitude given by the graded current reduction mechanism to generate a current error signal;

[0088] II. Duty Cycle Calculation: The adjusted PWM duty cycle is calculated using a proportional-integral controller based on the current error signal.

[0089] Ⅲ. Drive signal generation: Based on the calculated PWM duty cycle, the corresponding drive signal is generated and sent to the motor drive circuit. The average supply voltage of the motor winding is adjusted by changing the on / off ratio of the voltage per unit time, thereby achieving an output torque fluctuation range of less than ±5%.

[0090] The dynamic current regulation module is configured with a current protection subunit:

[0091] Set a minimum current protection threshold; when the drive current amplitude drops to 30% of the rated value, the backup cooling device will be automatically triggered.

[0092] The backup cooling device is a miniature liquid cooling circulation module, whose pipes are embedded in the heat-conducting layer inside the motor housing.

[0093] The adaptive heat dissipation module includes:

[0094] Temperature distribution reconstruction unit: converts discrete sensor data into a three-dimensional heat map and identifies hot spots with temperatures greater than 150°C;

[0095] Fan speed control logic: Set the speed according to the following formula:

[0096] ;

[0097] in This refers to the fan speed. The heat dissipation efficiency coefficient. This refers to the temperature rise difference of hot spots;

[0098] Deflector mechanism: Automatically adjusts the angle of the deflector according to the direction of the temperature gradient, so that the airflow is concentrated to cover the hot spot area;

[0099] Heat dissipation efficiency coefficient Optimize through self-learning from historical operational data:

[0100] The initial value is set to 80 RPM / ℃;

[0101] The system is dynamically adjusted every 24 hours based on the deviation between the actual heat dissipation effect and the theoretical value. The value and correction process satisfy the formula:

[0102] ;

[0103] in These are the corrected coefficients. For the coefficients before correction, This represents the actual temperature drop difference. This is the theoretical temperature drop difference. As a correction factor and ;

[0104] The correction range is less than 5%.

[0105] The load-temperature adaptation module includes:

[0106] Performance mapping model: Stores a table showing the correspondence between the maximum allowable load, speed, and torque of the motor at different temperatures;

[0107] The fuzzy logic decision unit is a fuzzy decision engine that dynamically solves parameters through fuzzy logic algorithms: input variables include real-time load change rate, current temperature value and heat dissipation efficiency, and output variables are speed adjustment coefficient and torque compensation value.

[0108] The specific steps include:

[0109] Input variable fuzzification: The received real-time load change rate, current temperature value, and heat dissipation efficiency are converted into fuzzy language values ​​and assigned corresponding membership degrees;

[0110] Fuzzy rule reasoning: It calls a preset fuzzy rule library, which contains "IF (input condition) THEN (output decision)" type rules based on historical data. It performs matching and reasoning based on the fuzzy linguistic value of the current input variable.

[0111] Output decision defuzzification: The output decision language value obtained from fuzzy inference is solved into accurate speed adjustment coefficient and torque compensation value by the centroid method and then sent to the dynamic limiter.

[0112] The formula for the centroid method is as follows:

[0113]

[0114] in To obtain the accurate output value after deblurring, For the first Membership degree of each output language value For the first The center point of each output language value To output the total number of language values. For summation index;

[0115] Dynamic limiter: When the model output parameters exceed the material tolerance limit, the output is forcibly locked to a safe threshold.

[0116] The performance mapping model is constructed in the following way:

[0117] Collect historical operating data: covering motor operating parameters in the temperature range of -40℃ to 200℃ and the load range of 10%-100%;

[0118] Data filtering rules: Remove abnormal operating condition data with temperature fluctuations greater than ±10℃ / min;

[0119] Model validation mechanism: After every 100 hours of additional running data, the model prediction error rate is re-validated. The error rate is calculated using the following formula:

[0120] ;

[0121] in For error rate, This is the actual value. This is a predicted value;

[0122] Model reconstruction is triggered when the error rate is greater than 8%.

[0123] The cloud-based strategy optimization module is implemented in the following ways:

[0124] Data anonymization unit: Uploads data after removing device identification information from the operational data;

[0125] Historical fault mode library generation: Historical fault data is summarized into five typical modes: winding overheating, bearing failure, insulation aging, rotor eccentricity and drive abnormality.

[0126] Strategy iteration process: The local control effect is compared with the cloud simulation results every week, and the optimization strategy that can reduce the temperature rise by more than 15% is given priority.

[0127] The historical fault pattern library is generated by the K-means clustering algorithm in unsupervised learning: clustering analysis is performed using current fluctuations, temperature rise rates and vibration amplitudes in historical operating data as feature vectors to aggregate fault data into five typical patterns.

[0128] The optimized control strategy is generated using the Q-learning algorithm in reinforcement learning: the reward function is the reduction in system temperature rise. The long-term returns under different control strategies are simulated, and the optimized Q-value table is calculated iteratively to generate the optimized control strategy that maximizes the cumulative reward.

[0129] The strategy iteration process includes verifying the optimized control strategy in a simulation environment, and then sending the updated strategy parameters after the verification is successful.

[0130] The motor performance parameters meet the following requirements:

[0131] Rated speed ≥10000 r / min, rated current ≤5.8A, rated torque ≥0.27 N·m;

[0132] Locked rotor current ≤ 41A, locked rotor torque ≥ 1.940 N·m;

[0133] Furthermore, under conditions where the temperature increases by 5°C, the torque output can be maintained at 10 N·m when the speed increases by 50 rpm.

[0134] The operating steps of this high-temperature resistant brushless hollow cup motor and thermal management system are as follows:

[0135] I. Accurate System Status Perception and Operating Condition Judgment

[0136] After the system starts up, it first continuously collects real-time temperature data inside the motor through a multi-source sensor array densely deployed in key heat-sensitive areas of the motor stator windings, rotor shaft, and bearings. The collected multi-channel temperature signals are processed by an adaptive filtering circuit for noise suppression and data fusion, ultimately generating a three-dimensional temperature distribution map that can intuitively reflect the details of the internal temperature field of the motor, and calculating the overall temperature rise rate based on this map. The system compares the real-time temperature value and temperature rise rate with preset operating condition warning thresholds and safety thresholds. When any indicator exceeds the limit, it determines that the motor has entered a high-temperature operating condition, and then activates the entire thermal management control process.

[0137] II. Dynamic Regulation of Drive Current and Power Smoothing

[0138] Once the system determines that it has entered a high-temperature operating condition, the dynamic current control module immediately intervenes. Based on the real-time acquired temperature rise rate data, it queries the pre-stored temperature rise rate-current mapping table. When the temperature rise rate exceeds the safety threshold, it activates a graded current reduction mechanism to gradually reduce the amplitude of the drive current with a fixed gradient. To ensure that the output performance does not fluctuate drastically due to the current reduction, the module simultaneously adjusts the PWM duty cycle through pulse width modulation technology to control the average voltage and power supplied to the motor. This suppresses temperature rise while stabilizing the fluctuation of output torque within a very small range, achieving smooth power regulation.

[0139] III. Adaptive Execution of the Cooling System

[0140] The adaptive heat dissipation module receives a three-dimensional temperature distribution map from the temperature condition judgment module and automatically identifies specific hot spots in the map with temperatures exceeding 150°C. Based on the temperature values ​​and distribution locations of these hot spots, the system adjusts the speed of the cooling fan and the deflection angle of the airflow guide vanes in real time and independently. The fan speed is positively correlated with the temperature value of the hot spots, and the guide vanes direct the cooling airflow to the high-temperature areas, achieving targeted and enhanced heat dissipation of locally overheated areas, thereby improving overall heat dissipation efficiency and avoiding waste of cooling resources.

[0141] IV. Adaptive Matching for Load-Temperature Coupled Operating Conditions

[0142] The load-temperature adaptation module simultaneously receives drive current parameters, real-time temperature data, a 3D temperature distribution map, and external load change signals, which are then processed by an embedded fuzzy logic decision engine. This engine converts clear input variables into fuzzy language values, calls a rule base based on historical data for reasoning, and finally calculates the decision output into precise speed adjustment coefficients and torque compensation values. This dynamically calculates the optimal matching parameters of speed and torque under the current high-temperature operating conditions, ensuring the stability of motor output performance.

[0143] V. Cloud-based collaborative learning and continuous strategy optimization

[0144] The cloud-based strategy optimization module gathers the operating data, control parameters, and temperature distribution maps of all local modules, and uploads them to the cloud platform after data anonymization. The cloud uses machine learning capabilities to perform cluster analysis on massive amounts of historical data, generating a historical fault mode matching library containing typical faults such as winding overheating and bearing failure. It also uses algorithms to simulate and compare the effects of different control strategies, iteratively generating optimized control strategies that can reduce system temperature rise. Finally, these optimized strategy parameters are fed back to the temperature judgment and current control module of the lower-level machine to update its local preset values, thereby completing a learning and optimization closed loop and enabling the system to have the intelligent ability to continuously evolve.

[0145] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0146] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-temperature resistant brushless hollow cup motor thermal management system, characterized in that: The system includes: The temperature condition judgment module collects the internal temperature data of the motor in real time through a multi-source sensor array, performs fusion processing on the collected temperature data, generates a three-dimensional temperature distribution map inside the motor and calculates the overall temperature rise rate. When the temperature value exceeds the preset warning threshold and the temperature rise rate exceeds the preset safety threshold, it determines that the motor has entered a high temperature condition state and activates the thermal management control process. The dynamic current control module receives the high-temperature operating condition status signal, three-dimensional temperature distribution map and temperature rise rate data output by the temperature operating condition judgment module. Based on the temperature rise rate, it dynamically adjusts the drive current parameters. When the temperature rise rate exceeds the preset safety threshold, it gradually reduces the drive current amplitude and achieves smooth adjustment of output power through pulse width modulation technology. An adaptive heat dissipation module receives a three-dimensional temperature distribution map generated by the temperature condition judgment module, identifies hot spots with temperatures exceeding 150°C in the map, and adjusts the cooling fan speed and the angle of the air guide vanes in real time. The fan speed is positively correlated with the temperature of the hot spots, including: Temperature distribution reconstruction unit: converts discrete sensor data into a three-dimensional heat map and identifies hot spots with temperatures greater than 150°C; Fan speed control logic: Set the speed according to the following formula: ； in This refers to the fan speed. The heat dissipation efficiency coefficient. This refers to the temperature rise difference of hot spots; Deflector mechanism: Automatically adjusts the angle of the deflector according to the direction of the temperature gradient, so that the airflow is concentrated to cover the hot spot area; The heat dissipation efficiency coefficient Optimize through self-learning from historical operational data: The initial value is set to 80 RPM / ℃; The system is dynamically adjusted every 24 hours based on the deviation between the actual heat dissipation effect and the theoretical value. The value and correction process satisfy the formula: ； in These are the corrected coefficients. For the coefficients before correction, This represents the actual temperature drop difference. This is the theoretical temperature drop difference. As a correction factor and ; The correction range is less than 5%.

2. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 1, characterized in that: Also includes: The load-temperature adaptation module receives the drive current parameters output by the dynamic current control module, the temperature data and three-dimensional temperature distribution map from the temperature condition judgment module, and combines them with real-time load change data. It then uses a fuzzy logic decision unit to dynamically calculate the optimal matching parameters of speed and torque to ensure stable output performance under high-temperature conditions. The cloud-based strategy optimization module receives operating data, control parameters, and a three-dimensional temperature distribution map from the temperature condition judgment module, dynamic current control module, adaptive heat dissipation module, and load-temperature adaptation module. It then uploads these data to the cloud platform. Through data anonymization, fault mode summarization, and strategy iteration comparison, it generates a historical fault mode matching library and optimized control strategies. The optimized operating condition warning threshold, safety threshold, and control parameters are then fed back to the temperature condition judgment module and dynamic current control module to update their preset values.

3. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 1, characterized in that: The temperature condition determination module includes: The multi-source sensor array is specifically a miniature thermocouple sensor array, which is deployed in key heat-sensitive areas such as the motor stator winding, rotor shaft, and bearing positions. Noise suppression unit: Adaptive filtering circuit is used to eliminate environmental electromagnetic interference, ensuring that the temperature acquisition error is less than ±1℃; High temperature activation logic unit: When the temperature value exceeds the operating condition warning threshold for three consecutive sampling cycles and the temperature gradient change rate is greater than 5℃ / min, the thermal management control process is triggered.

4. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 1, characterized in that: The dynamic current regulation module performs the following steps: Establish a temperature rise rate-current mapping table: store the maximum allowable current amplitude corresponding to different temperature ranges; Graded current reduction mechanism: When the temperature rise rate exceeds the threshold, the drive current is reduced step by step in increments of 10%, with each adjustment interval being greater than 30 seconds; Pulse Width Modulation Compensation Unit: Adjusts the PWM duty cycle through pulse width modulation technology to compensate for output fluctuations caused by current changes, achieving smooth adjustment of output power and maintaining output torque fluctuation range within ±5%.

5. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 4, characterized in that: The dynamic current regulation module is configured with a current protection subunit: Set a minimum current protection threshold; when the drive current amplitude drops to 30% of the rated value, the backup cooling device will be automatically triggered. The backup cooling device is a miniature liquid cooling circulation module, whose pipes are embedded in the heat-conducting layer inside the motor housing.

6. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 2, characterized in that: The load-temperature adaptation module includes: Performance mapping model: Stores a table showing the correspondence between the maximum allowable load, speed, and torque of the motor at different temperatures; Fuzzy decision engine: Input variables include real-time load change rate, current temperature value and heat dissipation efficiency, and output variables are speed adjustment coefficient and torque compensation value; Dynamic limiter: When the model output parameters exceed the material tolerance limit, the output is forcibly locked to a safe threshold.

7. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 6, characterized in that: The performance mapping model is constructed in the following way: Collect historical operating data: covering motor operating parameters in the temperature range of -40℃ to 200℃ and the load range of 10%-100%; Data filtering rules: Remove abnormal operating condition data with temperature fluctuations greater than ±10℃ / min; Model validation mechanism: After every 100 hours of additional running data, the model prediction error rate is re-validated. The error rate is calculated using the following formula: ； in For error rate, This is the actual value. This is a predicted value; Model reconstruction is triggered when the error rate is greater than 8%.

8. The high-temperature resistant brushless hollow cup motor thermal management system according to claim 2, characterized in that: The cloud-based strategy optimization module is implemented in the following ways: Data anonymization unit: Uploads data after removing device identification information from the operational data; Historical fault mode library generation: Historical fault data is summarized into five typical modes: winding overheating, bearing failure, insulation aging, rotor eccentricity and drive abnormality. Strategy iteration process: The local control effect is compared with the cloud simulation results every week, and the optimization strategy that can reduce the temperature rise by more than 15% is given priority.

9. A high-temperature resistant brushless hollow cup motor, characterized in that: For use in conjunction with the thermal management system of the high-temperature resistant brushless hollow cup motor as described in any one of claims 1-8, the motor performance parameters meet the following requirements: Rated speed ≥10000 r / min, rated current ≤5.8A, rated torque ≥0.27 N·m; Locked rotor current ≤ 41A, locked rotor torque ≥ 1.940 N·m; Furthermore, under conditions where the temperature increases by 5°C, the torque output can be maintained at 10 N·m when the speed increases by 50 rpm.

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