Motor stalling detection method and device, and electronic speed regulator

Abstract

The invention discloses a motor locked-rotor detection method and device, and an electronic speed regulator, and relates to the technical field of motor fault identification, the disclosed motor locked-rotor detection method and device, and the electronic speed regulator determine a locked-rotor state by integrating multi-dimensional parameters of motor input power, rotating speed and efficiency, and combine a dynamic threshold adjustment and temperature compensation mechanism, so that the motor fault identification efficiency is improved. The problems that traditional single parameter detection is high in false alarm rate and poor in adaptability are effectively solved, the detection precision can be effectively improved, the thermal damage risk can be reduced, and the service life of equipment can be prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor fault recognition, and particularly relates to a motor stall detection method and device and an electronic speed regulator. BACKGROUND

[0002] Motor stall is a common fault phenomenon in the field of motor control, which refers to the situation that the rotor cannot rotate or the rotation speed is abnormally reduced due to excessive load or mechanical jamming of the motor, while the electronic speed regulation system is still in a state of continuous power supply. This abnormal working condition can instantly generate an electric current several times the rated value, resulting in a large amount of heat energy accumulated in the motor winding and power device of the electronic speed regulator in a short time. If timely detection and protective measures are not taken, irreversible damage such as demagnetization of permanent magnets, damage of winding insulation or burning of power devices can easily occur.

[0003] The current mainstream stall protection scheme is mainly based on a single parameter threshold judgment mechanism, including two typical implementation methods of current detection method and rotation speed detection method. The current detection method monitors the current value of the DC bus or the power device branch, and triggers protection when the detected current value exceeds the preset threshold value and lasts for a specified time. The rotation speed detection method relies on the rotation speed signal obtained by the Hall sensor or back electromotive force estimation, and determines stall when the throttle command and the measured rotation speed are seriously mismatched. The above detection schemes are difficult to accurately distinguish between stall and normal working conditions (such as motor starting, sudden load increase, etc.), and in order to reduce the false alarm rate, the protection delay time has to be extended, which in turn increases the risk of thermal damage to the equipment.

[0004] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0005] The main purpose of the present application is to provide a motor stall detection method and device and an electronic speed regulator, aiming to improve the accuracy of motor stall detection.

[0006] To achieve the above purpose, the present application provides a motor stall detection method, which comprises: obtaining the DC bus voltage and DC bus current of the motor, and calculating based on the DC bus voltage and DC bus current to obtain the input power of the motor; obtaining the torque current component and the rotation speed of the motor, and calculating based on the torque current component, the rotation speed of the motor and the preset torque constant to obtain the mechanical power of the motor; calculating based on the mechanical power of the motor and the input power of the motor to obtain the efficiency of the motor; when the input power of the motor is greater than the preset power value, the rotation speed of the motor is lower than the preset rotation speed value, and the efficiency of the motor is lower than the preset efficiency value, and the duration reaches the preset time length, determining that the motor is stalled.

[0007] In an embodiment, the step of acquiring the DC bus voltage and the DC bus current of the motor comprises: acquiring a raw voltage signal through a voltage sensor, and performing mean filtering processing on the raw voltage signal to obtain the DC bus voltage; acquiring a raw current signal through a current sensor, and performing sliding window filtering processing on the raw current signal to obtain the DC bus current.

[0008] In an embodiment, the step of calculating based on the DC bus voltage and the DC bus current to obtain the motor input power comprises: multiplying the DC bus voltage and the DC bus current to obtain instantaneous power data; performing time integration operation on the instantaneous power data to generate cumulative energy data within a preset period; dividing the cumulative energy data by the current period to obtain the motor input power.

[0009] In an embodiment, the step of determining motor stall when the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time length comprises: starting a timer when the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value; real-time detecting whether the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value after the timer is started, and resetting the timer if at least one of them is not satisfied; generating a stall confirmation flag when the timer cumulative value reaches a preset time length to determine motor stall.

[0010] In an embodiment, the method further comprises: extracting a torque constant initial value based on the model parameters of the motor; acquiring the motor operating temperature, and compensating and correcting the torque constant initial value according to the motor operating temperature to obtain the preset torque constant.

[0011] In an embodiment, after determining motor stall, the method further comprises: acquiring the real-time temperature of the motor; triggering the motor power-off protection mechanism when the real-time temperature of the motor exceeds a safety threshold; When the real-time temperature of the motor does not exceed the safety threshold, the drive current of the motor is periodically reduced and the change in motor speed is detected. When the motor speed is detected to be rising continuously and exceeding the preset recovery threshold, a stall release signal is generated to restore the motor drive current.

[0012] In one embodiment, the method further includes: Continuously record the motor efficiency and build a historical efficiency dataset; The sliding variance of the historical efficiency dataset is calculated to obtain the efficiency variance value. When the efficiency variance value continuously exceeds the preset warning range, a bearing wear warning signal is generated.

[0013] In one embodiment, before determining that the motor is stalled when the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time, the method further includes: Determine the current operating condition of the motor; Increase the preset efficiency value when the motor is under heavy load, and decrease the preset efficiency value when the motor is under no-load.

[0014] In addition, to achieve the above objectives, this application also proposes a motor stall detection device, wherein the motor stall detection includes: a memory, a processor, and a motor stall detection program stored in the memory and executable on the processor, wherein the motor stall detection program is configured to implement the steps of the motor stall detection method described above.

[0015] In addition, to achieve the above objectives, this application also proposes an electronic speed controller that uses the aforementioned motor stall detection method, or the electronic speed controller includes the aforementioned motor stall detection device.

[0016] The motor stall detection method, equipment, and electronic speed controller proposed in this application determine the stall state by comprehensively considering multiple parameters such as motor input power, speed, and efficiency. Combined with dynamic threshold adjustment and temperature compensation mechanisms, it effectively solves the problems of high false alarm rate and poor adaptability of traditional single-parameter detection. It can not only effectively improve detection accuracy but also reduce the risk of thermal damage and extend equipment life. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an embodiment of the motor stall detection method of this application. Figure 2 For this application Figure 1 A detailed flowchart of step S100; Figure 3 For this application Figure 1 Detailed flowchart of step S400; Figure 4 This is a flowchart illustrating another embodiment of the motor stall detection method of this application; Figure 5 A flowchart illustrating yet another embodiment of the motor stall detection method of this application; Figure 6 A flowchart illustrating yet another embodiment of the motor stall detection method of this application; Figure 7 This is a schematic diagram of a structure provided for an embodiment of the motor stall detection device of this application.

[0020] Explanation of icon numbers: 10. Memory; 20. Processor.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0023] It should be understood that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] In existing technologies, motor stall detection generally uses single-dimensional criteria such as current detection or speed detection. When the motor starts or is subjected to a sudden heavy load, the current will rise instantaneously, and the speed may drop sharply. At this time, traditional detection methods are prone to misjudging the state as stall. In order to reduce the false alarm rate, existing technologies have to extend the protection delay, which causes the motor to be subjected to a large current impact for too long when it is actually stalled, posing a risk of device damage.

[0025] To address these issues, researchers discovered that single-parameter detection cannot accurately distinguish between normal operating conditions and stalled states. Analysis of the energy conversion relationship during motor operation revealed a significant imbalance between input power and mechanical power under stalled conditions. Based on this, a multi-dimensional judgment model was proposed, using input power, mechanical power, and speed as co-judgments, combined with efficiency parameters.

[0026] Based on this, the embodiments of this application provide a method for detecting motor stall, referring to... Figure 1 The motor stall detection method includes steps S100 to S400, wherein: Step S100: Obtain the DC bus voltage and DC bus current of the motor, and calculate the motor input power based on the DC bus voltage and DC bus current; Step S200: Obtain the torque current component and motor speed, and calculate the motor mechanical power based on the torque current component, the motor speed and a preset torque constant; Step S300: Calculate the motor efficiency based on the motor mechanical power and the motor input power; Step S400: When the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time, the motor is determined to be stalled.

[0027] In this embodiment, the DC bus voltage refers to the voltage across the DC power supply in the motor drive circuit. It can be obtained by collecting the raw signal from a voltage sensor and then filtering it using an average value, reflecting the power input level. The DC bus current refers to the total current flowing through the motor drive circuit. It can be obtained by collecting the raw signal from a current sensor and then filtering it using a sliding window, used to calculate instantaneous power. The torque current component refers to the current component used to generate electromagnetic torque in the motor control system, which can be obtained directly through the electronic speed controller. The preset torque constant refers to the torque value corresponding to a unit torque current component, which can be calibrated according to motor parameters and used to calculate mechanical power. The preset efficiency value refers to the minimum ratio of mechanical power to input power during normal operation, which can be dynamically adjusted according to the motor type and used to identify energy conversion anomalies.

[0028] In this embodiment, the input power is obtained by real-time monitoring of the product of the DC bus voltage and current, reflecting the total energy consumption. Simultaneously, the mechanical power is obtained by multiplying the product of the torque current component and the rotational speed by the torque constant, characterizing the effective output energy. The efficiency parameter, reflecting the energy conversion efficiency, is obtained by calculating the ratio of these two components. When the input power abnormally increases, the rotational speed drops sharply, and the efficiency falls below a threshold, the stall state is comprehensively determined based on the duration of the event. This determination mechanism can effectively filter out the current surge at startup and distinguish between heavy-load conditions and true stall.

[0029] In this embodiment, by introducing efficiency parameters to construct an energy conversion efficiency criterion and combining it with multi-dimensional collaborative detection of power and speed, a stall determination model is established from the perspective of energy conservation. This significantly reduces the probability of false triggering and avoids malfunctions of protection systems caused by normal startup or short-term overload. Simultaneously, by dynamically monitoring energy conversion efficiency through efficiency parameters, the true stall state can be quickly identified, improving system reliability while ensuring detection sensitivity.

[0030] In one feasible implementation, the steps of obtaining the DC bus voltage and DC bus current of the motor include: acquiring a raw voltage signal through a voltage sensor and performing mean filtering on the raw voltage signal to obtain the DC bus voltage; acquiring a raw current signal through a current sensor and performing sliding window filtering on the raw current signal to obtain the DC bus current.

[0031] In this embodiment, mean filtering refers to performing an arithmetic average on multiple consecutive sampled values ​​acquired by the voltage sensor. Specifically, this can be achieved by continuously acquiring ten voltage sampled values ​​within a fixed period and calculating their average value, thereby improving the stability of the voltage signal by eliminating high-frequency random noise. Sliding window filtering refers to truncating the continuous data stream acquired by the current sensor into a fixed window length and calculating statistics. Specifically, this can be achieved by forming a window of five adjacent current sampled values ​​and calculating their moving average value, thereby suppressing transient fluctuations while preserving the dynamic trend of current changes.

[0032] In this embodiment, high-frequency noise in the voltage signal mainly originates from electromagnetic interference or sensor errors. After mean filtering, abnormal spikes in the voltage signal are smoothed out; for example, voltage fluctuations generated at the moment of motor startup are corrected by the average value of multiple sampling points. Fluctuations in the current signal are mainly caused by sudden load changes or commutation processes. Sliding window filtering preserves the direction of current change while limiting the amplitude of abrupt changes in adjacent sampling values ​​within the window range. For example, when the motor suddenly accelerates, causing a surge in current, the moving average of multiple sampling values ​​within the window can avoid distortion caused by single-point sampling anomalies. Thus, the voltage and current signals undergo targeted filtering to provide accurate input data for subsequent power calculations.

[0033] In this embodiment, differentiated filtering strategies are designed for high-frequency noise in the voltage signal and transient fluctuations in the current signal. This eliminates random noise in the voltage signal while retaining effective change information in the current signal, avoiding signal distortion or response delay caused by a single filtering method. It suppresses noise interference in the DC bus voltage and current signals, solving the problem of stall detection errors caused by signal distortion. Mean filtering of the voltage signal reduces the impact of instantaneous voltage anomalies on input power calculation, while sliding window filtering of the current signal avoids distortion of current sampling values ​​caused by sudden load changes. The combination of these two methods ensures accurate acquisition of motor input power and mechanical power, thereby improving the reliability of stall detection.

[0034] In one feasible implementation, refer to Figure 2 The step of calculating the motor input power based on the DC bus voltage and the DC bus current includes steps S110 to S130, wherein: Step S110: Multiply the DC bus voltage and the DC bus current to obtain instantaneous power data; Step S120: Perform time integration on the instantaneous power data to generate cumulative energy data within a preset period; Step S130: Divide the accumulated energy data by the current cycle to obtain the motor input power.

[0035] In this embodiment, time integration refers to the summation of instantaneous power data over a continuous time period. This can be achieved using the trapezoidal integration method or the rectangular integration method, transforming discrete power data into a continuous cumulative energy amount. The preset period refers to the time window used to calculate the average power, which can be set to an integer multiple of 50 milliseconds to 200 milliseconds, such as 100 milliseconds. Periodic division normalizes the power data. Periodic averaging involves dividing the cumulative energy data by the corresponding time window length, which can be achieved using floating-point division. This averaging operation eliminates short-term noise interference.

[0036] In this embodiment, during motor operation, the instantaneous product of the DC bus voltage and current reflects the transient power, but this value is easily affected by motor commutation noise or sensor sampling errors. By accumulating discrete power points through time integration, an energy accumulation curve is formed. This curve is continuous in the time dimension, effectively suppressing abnormal fluctuations at individual sampling points. For example, within a 100-millisecond period, power data is collected and integrated every 1 millisecond, and the total energy is finally divided by 0.1 seconds to obtain the average power value. This processing method preserves the overall trend of power change while eliminating high-frequency interference components through the smoothing characteristics of integration, establishing a statistically stable power index through periodic averaging.

[0037] In this embodiment, an energy accumulation model is constructed through integral calculations, transforming transient power fluctuations into continuous changes in accumulated energy. Then, periodic averaging is used to obtain statistically significant power indicators, effectively distinguishing between instantaneous fluctuations under normal operating conditions and persistent anomalies during stall. For example, short-term power peaks occurring during motor acceleration are diluted after integration and averaging, while the sustained high power state during stall is accurately captured. Thus, this application can eliminate instantaneous power spike interference caused by motor commutation noise, sensor sampling errors, or sudden load changes, accurately calculating the average value of the motor input power. This technical solution, through dual processing of energy accumulation and periodic averaging, establishes the temporal correlation and statistical stability of power data while ensuring real-time performance, providing a reliable power calculation benchmark for subsequent stall determination and solving the misjudgment problem caused by relying solely on current or speed threshold detection in existing technologies.

[0038] In one feasible implementation, refer to Figure 3 Step S400 includes steps S410 to S430, wherein: Step S410: When the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, start the timer. Step S420: After the timer starts, it is detected in real time whether the motor input power is greater than the preset power value, the motor speed is lower than the preset speed value, and the motor efficiency is lower than the preset efficiency value. If at least one of them is not met, the timer is reset. Step S430: When the accumulated value of the timer reaches the preset duration, a stall confirmation flag is generated to determine that the motor is stalled.

[0039] In this embodiment, starting the timer refers to triggering a time accumulation mechanism when the motor's input power, speed, and efficiency all simultaneously exceed a set threshold. This can be implemented using a microcontroller's timer module to quantify the duration of the abnormal state. Real-time detection refers to continuously collecting parameter data and performing logical judgments during the timing process. This can be achieved through an interrupt service routine or polling to ensure dynamic monitoring of the parameter status. Resetting the timer means clearing the accumulated time value when any parameter returns to the normal range. This can be implemented using a zero-set timer counter to avoid misjudgments caused by brief anomalies. Generating a stall confirmation flag means outputting a status indicator after the timer reaches a preset duration. This can be implemented using a register flag or a digital signal output to trigger subsequent protection actions.

[0040] In this embodiment, when the motor input power, speed, and efficiency all exceed the threshold simultaneously, the timer begins to accumulate time. During the timer's operation, the three parameters are continuously monitored in real time: if any parameter returns to the normal range, the timer is immediately reset to zero; if the three parameters remain abnormal until the timer's accumulated time reaches the preset duration, a stall confirmation flag is generated. In this process, the timer's start-up and reset mechanism distinguishes between short-term fluctuations and continuous abnormal states. For example, a sudden increase in instantaneous power during motor startup or a brief decrease in speed caused by a sudden change in load will cause the timer to reset due to parameter recovery, while a true stall state is characterized by continuous abnormalities in the three parameters.

[0041] In this embodiment, by combining multi-parameter judgment with dynamic timer linkage, the time dimension is dynamically associated with the parameter status, which not only eliminates short-term abnormal interference, but also avoids the response lag caused by fixed delay. This solves the problem of false protection triggered by instantaneous operating condition fluctuations in existing stall detection methods, while avoiding the risk of response lag or equipment damage caused by simply relying on delay mechanism.

[0042] In one feasible implementation, refer to Figure 4 The method further includes steps S510 to S520, wherein: Step S510: Extract the initial value of the torque constant based on the motor model parameters; Step S520: Obtain the motor operating temperature, and compensate and correct the initial value of the torque constant based on the motor operating temperature to obtain the preset torque constant.

[0043] In this embodiment, the model parameter refers to the set of inherent parameters calibrated at the motor's factory, which can be obtained from the motor nameplate data or parameters recorded in the manufacturer's technical manual, used to determine the initial reference value of the torque constant. The initial torque constant value refers to the theoretical torque value generated by the motor per unit current under standard temperature conditions, which can be obtained by analyzing the motor's electromagnetic design parameters or experimental calibration data, providing a reference for subsequent temperature compensation. The motor operating temperature refers to the real-time temperature data generated by the motor windings or magnets during operation, which can be obtained by collecting temperature signals using thermocouples, thermistors, or infrared sensors, used to reflect the impact of temperature changes on the torque constant. Compensation correction refers to the process of dynamically adjusting the initial value of the torque constant according to temperature changes, which can be achieved by constructing a temperature-torque correction coefficient mapping table and using a lookup method to match the compensation parameters corresponding to the real-time temperature, used to offset the torque constant offset caused by temperature-induced magnetic flux attenuation or changes in winding resistance.

[0044] In this embodiment, an initial value of the torque constant is first extracted from the motor model parameters. This initial value corresponds to the theoretical performance parameters of the motor at room temperature. Then, the motor's operating temperature is collected in real time using a temperature sensor and input into a pre-established temperature-torque correction coefficient mapping table to match the compensation parameters corresponding to the current temperature range. The compensation parameters are set based on physical laws such as the thermal expansion coefficient of materials and the temperature characteristics of magnetic flux. For example, a negative compensation coefficient is used in the high-temperature range to reflect the magnetic flux attenuation effect. Finally, the initial value of the torque constant is multiplied by the compensation parameters to generate a dynamically corrected torque constant, which is used for subsequent mechanical power calculations. This process, through a dual calibration mechanism, preserves the accuracy of the original motor design parameters while achieving dynamic adaptation to temperature changes.

[0045] In this embodiment, by introducing a temperature compensation mechanism, a correlation between temperature and torque constant is established based on physical characteristics. A lookup table method is used to achieve low-latency dynamic parameter correction, effectively eliminating the impact of temperature changes on calculation accuracy. This solves the problem of mechanical power calculation error caused by torque constant deviation due to temperature changes, avoids false triggering or missed detection caused by inaccurate mechanical power calculation during stall detection, and improves the reliability of stall detection.

[0046] In one feasible implementation, refer to Figure 5 The method further includes steps S610 to S620, wherein: Step S610: Obtain the real-time temperature of the motor; Step S620: When the real-time temperature of the motor exceeds the safety threshold, the motor power-off protection mechanism is triggered; when the real-time temperature of the motor does not exceed the safety threshold, the motor drive current is periodically reduced and the motor speed change is detected. When the motor speed is detected to be rising continuously and exceeding the preset recovery threshold, a stall release signal is generated to restore the motor drive current.

[0047] In this embodiment, the real-time motor temperature refers to the instantaneous temperature data of the motor windings or casing, which can be collected using surface-mounted thermocouples or infrared temperature sensors to assess the thermal accumulation state during motor operation. The safety threshold is a preset temperature resistance limit for the motor material, which can be set according to the motor's insulation class, for example, to 130℃ or 155℃, to trigger an emergency power-off to prevent thermal runaway. Periodically reducing the drive current refers to gradually decreasing the PWM duty cycle output control at fixed time intervals, specifically using a stepped reduction strategy, with each reduction set to 5%–10% of the current value, to alleviate energy input during stall conditions. The preset recovery threshold is the critical speed value for determining when the motor is out of stall conditions, specifically set to 20%–30% of the rated speed, to identify conditions where mechanical load is reduced or stall obstacles are eliminated.

[0048] In this embodiment, when the motor is determined to be stalled, the temperature monitoring module immediately starts real-time sampling. If the detected temperature exceeds the safety threshold, the main controller directly cuts off the power supply to the three-phase inverter bridge, forcing the motor into a shutdown state. If the temperature is within the safe range, the drive current gradually decreases at a fixed cycle, while continuously monitoring the motor speed. When the detected speed exceeds the recovery threshold for three consecutive sampling cycles, the stalled state is determined to be lifted, and the drive current recovers to the normal value according to a preset slope. During this process, temperature data and current regulation form a closed-loop control, preventing overheating damage while maintaining system operating capability.

[0049] In this embodiment, by introducing a synergistic mechanism of temperature monitoring and dynamic current regulation, the system's self-recovery capability is preserved while ensuring thermal safety. Existing technologies require manual reset after a sudden current drop, but this solution automatically releases the protection state through speed feedback, achieving unattended intelligent recovery. Through the above technical solution, this application effectively resolves the contradiction between safety and availability during stall protection. The temperature-triggered graded protection mechanism can both promptly cut off power to prevent equipment burnout under extreme conditions and maintain system operation and automatic recovery within a controllable temperature range. Periodic current regulation combined with the speed feedback mechanism avoids malfunctions or response delays caused by fixed delays in traditional solutions, significantly improving the reliability and adaptability of the protection system.

[0050] In one feasible implementation, refer to Figure 6 The method further includes steps S710 to S730, wherein: Step S710: Continuously record the motor efficiency and construct a historical efficiency dataset; Step S720: Calculate the sliding variance of the historical efficiency dataset to obtain the efficiency variance value; Step S730: When the efficiency variance value continuously exceeds the preset warning range, a bearing wear warning signal is generated.

[0051] In this embodiment, the historical efficiency dataset refers to a time-series data set formed by periodically sampling and storing motor efficiency values. This can be implemented using a circular buffer or a database table structure, reflecting the long-term trend of motor operating efficiency. Sliding variance calculation refers to performing variance calculations on a fixed-length continuous sample segment within the dataset. This can be implemented using a moving window algorithm, dynamically updating the data within the window to eliminate the impact of transient interference on the statistical results. The preset warning range refers to a reasonable range of variance fluctuations set according to the motor model and operating conditions. This range can be determined through experimental calibration or historical data analysis, and is used to distinguish between normal and abnormal fluctuations.

[0052] In this embodiment, motor efficiency values ​​are periodically collected and stored in a historical dataset, forming a record of efficiency changes at multiple time points. The sliding variance calculation module traverses the dataset with a fixed window length, calculating the variance of the efficiency values ​​within the window each time, generating a numerical sequence reflecting the degree of efficiency fluctuation. When multiple consecutive variance calculation results exceed a preset threshold range, it is determined that there are progressive mechanical loss characteristics, triggering a bearing wear warning signal. This continuous over-limit judgment mechanism can effectively filter out occasional interference and accurately capture abnormal efficiency fluctuations caused by bearing wear.

[0053] Understandably, existing stall detection methods rely solely on instantaneous values ​​of current or speed, failing to identify the gradual decline in efficiency caused by bearing wear. This proposed solution, however, analyzes the continuous trend of efficiency variance to detect mechanical component anomalies in advance, providing early warning before stall occurs. Traditional methods, lacking an efficiency fluctuation monitoring mechanism, cannot generate warning signals in the early stages of bearing wear, leading to misjudgments of stall or sudden faults. This application, however, can monitor efficiency fluctuation characteristics in real time during motor operation, triggering warning signals before severe bearing wear, enabling maintenance personnel to perform timely preventative maintenance. This effectively avoids misjudgments of stall due to unidentified mechanical component anomalies, while also reducing the risk of equipment damage caused by sudden mechanical failures.

[0054] In one feasible implementation, before step S400, the method further includes: determining the current operating condition of the motor; increasing the preset efficiency value when the motor is under heavy load, and decreasing the preset efficiency value when the motor is under no-load.

[0055] In this embodiment, the current operating condition of the motor is determined by real-time monitoring of its operating parameters to ascertain its load status. Specifically, this can be achieved using the ratio analysis of current to speed. When the current increases significantly but the speed does not increase synchronously, it is determined to be a heavy load condition; when the current is at a low level and the speed fluctuation is small, it is determined to be an no-load condition. Increasing the preset efficiency value means adjusting the efficiency judgment threshold upwards under heavy load conditions. Specifically, this can be done by dynamically setting the threshold according to the load level using a lookup table method or linear interpolation method. Decreasing the preset efficiency value means adjusting the efficiency judgment threshold downwards under no-load conditions. Specifically, this can be done by scaling the baseline threshold using a preset proportional coefficient, so that efficiency fluctuations during low-power operation do not trigger false judgments.

[0056] In this embodiment, during motor operation, the load rate is first calculated by collecting current and speed data, and the load rate range is used to classify the motor into heavy load or no-load conditions. When a heavy load condition is identified, the efficiency judgment threshold is increased by a certain amount based on a preset compensation coefficient, for example, by multiplying the original threshold by 1.2 times. This ensures that under normal operating conditions with increased mechanical power demand, a temporary decrease in efficiency will not lead to a false judgment of stall. When a no-load condition is identified, a reverse compensation mechanism is used to decrease the efficiency threshold, for example, by multiplying the original threshold by 0.8 times. This ensures that abnormal efficiency drops can still be effectively detected under low-load operating conditions. This dynamic threshold adjustment mechanism complements the fixed threshold scheme, allowing the three conditions for stall judgment to automatically match the optimal parameter combination according to the actual operating conditions.

[0057] In this embodiment, a dynamic mapping relationship between load status and efficiency threshold is established through operating condition perception, which solves the problem of insufficient adaptability of fixed threshold. This allows the stall detection conditions to be automatically optimized according to the actual operating state of the motor. Under heavy load conditions, the threshold is increased to avoid normal high-power operation being misjudged as stall. Under no-load conditions, the threshold is decreased to enhance the detection sensitivity under low-power conditions, which significantly improves the stall detection accuracy under different load conditions.

[0058] In this embodiment, the motor stall detection method judges the stall state by comprehensively considering multiple parameters such as motor input power, speed and efficiency. Combined with dynamic threshold adjustment and temperature compensation mechanism, it effectively solves the problems of high false alarm rate and poor adaptability of traditional single parameter detection. It can not only effectively improve detection accuracy, but also reduce the risk of thermal damage and extend equipment life.

[0059] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the motor stall detection method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0060] This application also provides a motor stall detection device, see reference. Figure 7The motor stall detection includes: a memory 10, a processor 20, and a motor stall detection program stored in the memory 10 and executable on the processor 20. The motor stall detection program is configured to implement the steps of the motor stall detection method.

[0061] The motor stall detection device provided in this application, employing the motor stall detection method in the above embodiments, can improve the accuracy of motor stall detection. Compared with the prior art, the beneficial effects of the motor stall detection device provided in this application are the same as those of the motor stall detection method provided in the above embodiments, and other technical features in the motor stall detection device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0062] This application also provides an electronic speed controller that uses the aforementioned motor stall detection method, or the electronic speed controller includes the aforementioned motor stall detection device.

[0063] The electronic speed controller in this embodiment uses the motor stall detection method or includes the motor stall detection device, thus improving the accuracy of motor stall detection. Furthermore, compared to the prior art, the beneficial effects of the electronic speed controller provided in this application are the same as those of the motor stall detection method and device provided in the above embodiments. Other technical features of the electronic speed controller are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0064] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0065] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. All equivalent structural transformations made under the technical concept of this application using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included within the scope of patent protection of this application.

Claims

1. A method for detecting motor stall, characterized in that, The aforementioned motor stall detection method includes: Obtain the DC bus voltage and DC bus current of the motor, and calculate the motor input power based on the DC bus voltage and DC bus current; The torque current component and motor speed are obtained, and the motor mechanical power is calculated based on the torque current component, the motor speed and a preset torque constant. The motor efficiency is calculated based on the motor's mechanical power and the motor's input power. When the following conditions are met simultaneously: the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time, the motor is determined to be stalled.

2. The motor stall detection method as described in claim 1, characterized in that, The steps for obtaining the DC bus voltage and DC bus current of the motor include: The original voltage signal is acquired by a voltage sensor, and the original voltage signal is subjected to mean filtering to obtain the DC bus voltage. The raw current signal is acquired by a current sensor and then subjected to sliding window filtering to obtain the DC bus current.

3. The motor stall detection method as described in claim 1, characterized in that, The step of calculating the motor input power based on the DC bus voltage and the DC bus current includes: Multiply the DC bus voltage by the DC bus current to obtain the instantaneous power data; The instantaneous power data is integrated over time to generate cumulative energy data within a preset period; Divide the accumulated energy data by the current cycle to obtain the motor input power.

4. The motor stall detection method as described in claim 1, characterized in that, The step of determining motor stall when the following conditions are met simultaneously: the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time, includes: The timer is started when the following conditions are met simultaneously: the motor input power is greater than the preset power value, the motor speed is lower than the preset speed value, and the motor efficiency is lower than the preset efficiency value. After the timer starts, it continuously detects whether the following conditions are met: the motor input power is greater than the preset power value, the motor speed is lower than the preset speed value, and the motor efficiency is lower than the preset efficiency value. If at least one condition is not met, the timer is reset. When the timer's accumulated value reaches the preset duration, a stall confirmation flag is generated to determine that the motor is stalled.

5. The motor stall detection method as described in claim 1, characterized in that, The method further includes: Based on the motor model parameters, the initial value of the torque constant is extracted; The motor operating temperature is obtained, and the initial value of the torque constant is compensated and corrected based on the motor operating temperature to obtain the preset torque constant.

6. The motor stall detection method as described in claim 1, characterized in that, After determining that the motor is stalled, the method further includes: Get the real-time temperature of the motor; When the real-time temperature of the motor exceeds the safety threshold, the motor power-off protection mechanism is triggered. When the real-time temperature of the motor does not exceed the safety threshold, the drive current of the motor is periodically reduced and the change in motor speed is detected. When the motor speed is detected to be rising continuously and exceeding the preset recovery threshold, a stall release signal is generated to restore the motor drive current.

7. The motor stall detection method as described in claim 1, characterized in that, The method further includes: Continuously record the motor efficiency and build a historical efficiency dataset; The sliding variance of the historical efficiency dataset is calculated to obtain the efficiency variance value. When the efficiency variance value continuously exceeds the preset warning range, a bearing wear warning signal is generated.

8. The motor stall detection method as described in claim 1, characterized in that, Before determining that the motor is stalled when the following conditions are met simultaneously: the motor input power is greater than a preset power value, the motor speed is lower than a preset speed value, and the motor efficiency is lower than a preset efficiency value, and the duration reaches a preset time, the method further includes: Determine the current operating condition of the motor; Increase the preset efficiency value when the motor is under heavy load, and decrease the preset efficiency value when the motor is under no-load.

9. A motor stall detection device, characterized in that, The motor stall detection includes: a memory, a processor, and a motor stall detection program stored in the memory and executable on the processor, the motor stall detection program being configured to implement the steps of the motor stall detection method as described in any one of claims 1 to 8.

10. An electronic speed controller, characterized in that, The electronic speed controller uses the motor stall detection method as described in any one of claims 1 to 8, or the electronic speed controller includes the motor stall detection device as described in claim 9.

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