Motor rotor position sensor calibration method and related apparatus

Abstract

The application discloses a motor rotor position sensor calibration method and related equipment, and relates to the technical field of motor control. The method comprises the following steps: controlling a target motor to move in an open loop manner within a preset motion range, and obtaining an original signal sequence output by a rotor position sensor installed on the target motor; performing waveform feature extraction on the original signal sequence to obtain signal feature information of the rotor position sensor; determining target calibration parameters for compensating for installation errors and temperature influences of the rotor position sensor based on an environmental temperature detection value of the target motor and the signal feature information; and storing the target calibration parameters to a nonvolatile memory associated with the target motor, so that the target motor compensates for the detection result of the motor rotor position sensor based on the target calibration parameters when running. The application can reduce the influence of installation errors and temperature changes on position detection, and improve rotor position detection precision, stability and motor control stability.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and more specifically, to a method and related equipment for calibrating a motor rotor position sensor. Background Technology

[0002] With the continuous development of motor control technology and intelligent drive systems, the impact of motor rotor position detection accuracy on motor operating performance is becoming increasingly prominent. As a crucial component for acquiring motor rotor position information, the rotor position sensor's detection results directly affect the position resolution accuracy, speed control effectiveness, and operational stability of the motor control system. Therefore, precise calibration of the motor rotor position sensor is of great significance for improving motor control performance and ensuring stable motor operation.

[0003] In related technologies, the calibration of motor rotor position sensors typically employs fixed parameter compensation, empirical value correction, or position analysis based on recommended sensor parameters. While these methods can achieve position detection to a certain extent, unavoidable installation errors during motor assembly can easily lead to zero-point offset, amplitude deviation, and phase deviation in the rotor position sensor output signal. Furthermore, temperature variations in the motor's operating environment can further affect the sensor's output characteristics, causing deviations in the position detection results. During long-term motor operation, position detection errors can further impact motor speed stability and control performance, making it difficult to meet the application requirements of high-precision control scenarios. In other words, related technologies suffer from low detection accuracy and insufficient control stability in motor rotor position sensors. Summary of the Invention

[0004] In the summary section of this application, the relevant technical solutions are described in general terms, and a series of simplified concepts are introduced. These concepts will be further elaborated in the detailed embodiments section. This summary section should not be construed as limiting the key or essential technical features of the claimed solutions, nor is it intended to limit the scope of protection of the claimed solutions.

[0005] The motor rotor position sensor calibration method and related equipment provided in this application can obtain the rotor position sensor signal under the actual operating state of the target motor and extract the signal features, determine the calibration parameters in combination with the ambient temperature and perform storage compensation, thereby reducing the impact of installation errors and temperature changes on position detection and improving the accuracy and stability of rotor position detection and motor control stability.

[0006] In a first aspect, this application provides a method for calibrating a motor rotor position sensor, applied to a target motor, comprising: controlling the target motor to move in an open-loop manner within a preset motion range, and acquiring the original signal sequence output by a rotor position sensor installed on the target motor; extracting waveform features from the original signal sequence to obtain signal feature information of the rotor position sensor, wherein the signal feature information includes at least one of zero-point offset, amplitude deviation, and phase deviation; determining target calibration parameters for compensating for installation errors and temperature effects of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal feature information; and storing the target calibration parameters in a non-volatile memory associated with the target motor, so that the target motor compensates for the detection results of the motor rotor position sensor based on the target calibration parameters during operation.

[0007] In some embodiments, before controlling the target motor to move in an open-loop manner within a preset motion range, the motor rotor position sensor calibration method further includes: confirming the installation status of the rotor position sensor and obtaining an installation confirmation result; if the installation confirmation result is successful, acquiring motion condition detection information of the target motor, wherein the motion condition detection information includes the locking mechanism status information and phase current fault detection information of the target motor; determining whether the target motor has the motion conditions based on the motion condition detection information; if it is determined that the target motor has the motion conditions, allocating the preset motion range to the target motor so that the continuous rotation of the target motor within the preset motion range does not cause displacement of the load connected to the target motor.

[0008] In some embodiments, controlling the target motor to move in an open-loop manner within a preset motion range and acquiring the original signal sequence output by the rotor position sensor installed on the target motor includes: generating a rotating magnetic field by applying an orthogonal voltage vector with a preset amplitude and a preset frequency to the stator winding of the target motor to drive the target motor to rotate at a preset speed within the preset motion range; and obtaining the original signal sequence by synchronously acquiring at least one complete electrical cycle of orthogonal analog signal output by the rotor position sensor during the rotation of the target motor.

[0009] In some embodiments, the step of extracting waveform features from the original signal sequence to obtain the signal feature information of the rotor position sensor includes: performing digital filtering on the original signal sequence to obtain a filtered signal sequence; performing curve fitting on the filtered signal sequence to obtain the initial zero-point offset, initial amplitude deviation, and initial phase deviation of the rotor position sensor; constructing a Lissajous figure of the rotor position sensor under the ambient temperature detection value based on the sine and cosine signal components in the filtered signal sequence; extracting the elliptical geometric features of the Lissajous figure, wherein the elliptical geometric features include the offset coordinates of the ellipse center relative to the origin, the ratio of the length of the major axis to the minor axis of the ellipse, and the deflection angle of the major axis of the ellipse relative to a preset ideal reference axis; correcting the initial zero-point offset according to the offset coordinates to obtain the zero-point offset; correcting the initial amplitude deviation according to the length ratio to obtain the amplitude deviation; correcting the initial phase deviation according to the deflection angle to obtain the phase deviation; and determining the zero-point offset, the amplitude deviation, and the phase deviation as the signal feature information.

[0010] In some implementations, determining the target calibration parameters for compensating for the installation error and temperature influence of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal characteristic information includes: determining the temperature change rate based on the first ambient temperature detection value at a first time and the second ambient temperature detection value at a second time; querying preset temperature compensation mapping information to obtain a first set of temperature drift correction coefficients corresponding to the first ambient temperature detection value and a second set of temperature drift correction coefficients corresponding to the second ambient temperature detection value; if the temperature change rate exceeds a preset rate threshold, performing linear interpolation based on the first set of temperature drift correction coefficients and the second set of temperature drift correction coefficients to generate an intermediate temperature drift correction coefficient; otherwise, determining the second set of temperature drift correction coefficients as the intermediate temperature drift correction coefficient; and performing temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation in the signal characteristic information based on the intermediate temperature drift correction coefficient to obtain the target calibration parameters.

[0011] In some embodiments, the step of performing temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation in the signal feature information based on the intermediate temperature drift correction coefficient to obtain the target calibration parameters includes: acquiring thermal hysteresis compensation parameters corresponding to the rotor position sensor, wherein the thermal hysteresis compensation parameters characterize the asymmetry of the temperature drift characteristics of the rotor position sensor during the heating and cooling processes; selecting a corresponding hysteresis correction amount from the thermal hysteresis compensation parameters based on the direction of the temperature change rate; adjusting the intermediate temperature drift correction coefficient based on the hysteresis correction amount to obtain the target temperature drift correction coefficient; and performing temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation based on the target temperature drift correction coefficient to obtain the target calibration parameters.

[0012] In some embodiments, after storing the target calibration parameters in a non-volatile memory associated with the target motor, the motor rotor position sensor calibration method further includes: acquiring the real-time speed and real-time torque of the target motor during operation; determining the current operating condition category of the target motor based on the real-time speed and real-time torque; retrieving the segmented compensation correction coefficient corresponding to the operating condition category from the non-volatile memory based on the operating condition category; and adjusting the target calibration parameters according to the segmented compensation correction coefficient to obtain dynamic calibration parameters under the current operating condition, so as to adapt to different operating conditions when compensating the detection results of the motor rotor position sensor.

[0013] Secondly, this application also provides a motor rotor position sensor calibration device, applied to a target motor, comprising: a data acquisition unit, used to control the target motor to move in an open-loop manner within a preset motion range, and to acquire the original signal sequence output by the rotor position sensor installed on the target motor; a feature extraction unit, used to extract waveform features from the original signal sequence to obtain signal feature information of the rotor position sensor, wherein the signal feature information includes at least one of zero-point offset, amplitude deviation, and phase deviation; a parameter determination unit, used to determine target calibration parameters for compensating for installation errors and temperature effects of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal feature information; and a parameter storage unit, used to store the target calibration parameters in a non-volatile memory associated with the target motor, so that the target motor can compensate for the detection results of the motor rotor position sensor based on the target calibration parameters during operation.

[0014] Thirdly, this application also provides an electronic device, including: a memory and a processor, wherein the processor is configured to execute a computer program stored in the memory to implement the steps of the motor rotor position sensor calibration method described in the first aspect.

[0015] Fourthly, this application also provides a computer-readable storage medium storing computer-executable instructions or a computer program, which, when executed by a processor, implement the steps of the motor rotor position sensor calibration method described in the first aspect.

[0016] Fifthly, this application also provides a computer program product, including a computer program or computer-executable instructions, which, when executed by a processor, implement the steps of the motor rotor position sensor calibration method provided in the embodiments of this application.

[0017] In summary, this application controls the target motor to move in an open-loop manner within a preset motion range and acquires the original signal sequence output by the rotor position sensor. This allows for the formation of sensor output data corresponding to the actual position changes of the rotor during motor movement. Since the calibration process acquires signals based on the actual operating state of the target motor, it reflects the actual output characteristics after sensor installation, thus providing data support for subsequent calibration and improving the matching degree between the calibration process and the actual assembly state of the target motor. By extracting waveform features from the original signal sequence and obtaining at least one signal feature information among zero-point offset, amplitude deviation, and phase deviation, deviation characteristics in the rotor position sensor output signal can be identified. Since the signal feature information reflects the difference between the sensor output and the ideal state, it provides a basis for subsequent error correction, thereby reducing the impact of installation factors. This method addresses position detection deviations and improves the accuracy of rotor position detection results. By combining the target motor's ambient temperature detection value with signal characteristic information to determine target calibration parameters, it can simultaneously compensate for installation errors and temperature effects. Since changes in ambient temperature may cause changes in sensor output characteristics, incorporating temperature factors into the calibration parameter determination process ensures that the calibration results take into account both installation status and environmental changes, thereby improving the stability and consistency of rotor position detection results under different temperature conditions. By storing the target calibration parameters in a non-volatile memory associated with the target motor, the rotor position sensor detection results can be compensated based on the target calibration parameters during motor operation. This allows the calibration results to be continuously applied to subsequent operation stages without repeated parameter acquisition and calculation, thus maintaining rotor position detection accuracy and improving the control stability of the target motor during operation. In summary, the motor rotor position sensor calibration method provided in this application, by acquiring the rotor position sensor signal under the actual operating state of the target motor and extracting signal characteristics, combining ambient temperature to determine calibration parameters and storing and compensating for them, can reduce the impact of installation errors and temperature changes on position detection, improving rotor position detection accuracy, stability, and motor control stability. Attached Figure Description

[0018] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A schematic flowchart illustrating a motor rotor position sensor calibration method provided in this application embodiment; Figure 2 This is a schematic diagram of the composition structure of a motor rotor position sensor calibration device provided in an embodiment of this application; Figure 3 This is a schematic diagram of the composition structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The terms used in the specification, claims, and drawings of this application, such as "first," "second," "third," "fourth," etc. (if any), are used to distinguish similar objects and not to describe a specific order or sequence. Therefore, it is to be understood that these terms can be used interchangeably where appropriate, allowing the described embodiments to be used in different orders, unless specifically required by the illustrations or description. Furthermore, the terms "is" and "has," and any variations thereof, are intended to cover, non-exclusively, all possible constituent elements. For example, a process, method, system, product, or apparatus comprising several steps or units is not necessarily limited to the steps or units explicitly listed, but may also include other steps or units not explicitly listed, or steps or units inherent to the process, method, product, or apparatus.

[0020] In this application, a "module" or "unit" refers to a computer program or part of a computer program that has a specific function and works in conjunction with other related parts to achieve a predetermined goal. These modules or units can be implemented by software, hardware (e.g., processing circuitry or memory), or a combination of both. One or more processors or memories can implement one or more modules or units. Furthermore, each module or unit can also be part of a larger module or unit.

[0021] The technical solutions of this application will be described in detail below with reference to the accompanying drawings of the embodiments. It should be noted that the described embodiments are only a part of this application, and not all embodiments. In the following description, the "some embodiments" mentioned are only a subset of all possible embodiments, which may be the same or different subsets, and different embodiments can be combined with each other without conflict.

[0022] Figure 1 This is a schematic flowchart illustrating a motor rotor position sensor calibration method provided in an embodiment of this application. For example, see [link to example]. Figure 1 The motor rotor position sensor calibration method provided in this application embodiment is applied to a target motor, which is the controlled motor to be calibrated during this rotor position sensor calibration operation. The target motor can be a mass-produced drive motor equipped with a rotor position sensor, or a permanent magnet synchronous drive motor used in industrial equipment or vehicle drive scenarios. The motor rotor position sensor calibration method provided in this application embodiment may include the following steps 101 to 104: Step 101: Control the target motor to move in an open-loop manner within a preset motion range, and acquire the original signal sequence output by the rotor position sensor installed on the target motor.

[0023] In some examples, the Motor Position Sensor (MPS) is a position detection component that is mounted and fixed on the target motor assembly structure. It is mainly used to sense the rotational position, operating angle, and motion state of the target motor rotor in real time and output the corresponding analog electrical signal. It is the detection unit for the motor control system to analyze the rotor position and achieve precise closed-loop control. This sensor will have inherent installation deviations during mass production assembly, and its working signal is easily affected by ambient temperature, which is also the object of this calibration operation. The rotor position sensor can establish a signal transmission path with the motor controller through hardware wiring and upload the detection signal in real time. For example, a magnetoelectric rotor position sensor that can output orthogonal dual-channel analog signals can be selected to adapt to the standardized assembly structure of mass-produced motors.

[0024] The preset motion range is the safe and controllable motion range of the target motor, which is detected, calculated, and defined in advance by the motor controller. This range has been verified by the load status and mechanical structure. When the motor rotates continuously within this range, it will not cause physical displacement of the external load. At the same time, it can avoid the mechanical limit structure of the motor and eliminate the risks of jamming, interference, and structural damage. It is a dedicated safe motion range defined for sensor calibration operations. It can automatically calculate and generate a fixed motion range by combining the motor mechanical parameters and load connection status to ensure that the calibration process is safe and interference-free. For example, the preset motion range can be set to a small amplitude of motor electrical angle rotation range, which only meets the basic motion stroke required for complete signal acquisition by the sensor, without the need for large-scale motor rotation.

[0025] The open-loop operation mode differs from the conventional closed-loop control of motors. Specifically, it refers to a control method where the motor controller does not rely on feedback signals from the rotor position sensor for closed-loop adjustment of speed and position, but instead actively outputs preset drive signals to drive the target motor to operate autonomously. This mode completely avoids the intervention of closed-loop control algorithms in correcting the motor's operating state, fully preserving the original signal deviation characteristics of the rotor position sensor caused by installation errors and temperature interference, thus ensuring the authenticity of subsequent calibration data. For example, controlling the target motor to operate in a stable, low-speed, uniform state in an open-loop manner ensures that the motor's operating conditions are singular and stable.

[0026] The original signal sequence is a collection of raw electrical signals continuously output by the rotor position sensor during the open-loop motion of the target motor, without any filtering, correction, fitting, compensation, or other algorithmic processing. It fully includes the signal characteristics caused by sensor zero-point offset, amplitude deviation, phase deviation, and basic temperature interference, and serves as the original data basis for subsequent extraction of sensor error characteristics and calculation of calibration parameters. The real-time output signals of the sensor can be synchronously and continuously recorded through the signal acquisition port and integrated into a complete signal sequence in chronological order. For example, the original signal sequence includes a complete periodic orthogonal sine analog signal and a cosine analog signal output by the sensor.

[0027] For example, after the motor controller completes the verification of the status of the front-end equipment and confirms that the motor meets the calibration conditions, it automatically locks the pre-calculated safe movement range, closes all closed-loop regulation and control logic, and controls the target motor to run smoothly in open loop at low speed within the limited range by outputting a stable drive signal; during the entire process of the motor's continuous uniform speed movement, the real-time output signal of the rotor position sensor is continuously and synchronously collected, and continuously recorded and integrated into a complete original signal sequence according to the time dimension.

[0028] By implementing step 101, the target motor is controlled to move in an open-loop manner within a preset motion range, and the original signal sequence output by the rotor position sensor is acquired. The corresponding sensor output data can be obtained based on the actual motion process of the target motor. Since the acquired original signal can reflect the position sensor output of the target motor in its current assembly state, it can provide a data basis for subsequent signal feature analysis and parameter calibration, thereby improving the matching degree between the calibration process and the actual state of the target motor.

[0029] Step 102: Extract waveform features from the original signal sequence to obtain the signal feature information of the rotor position sensor.

[0030] The signal characteristic information includes at least one of zero-point offset, amplitude deviation, and phase deviation.

[0031] In some examples, waveform feature extraction is a process of data parsing and feature recognition of the raw signal sequence acquired by the target motor rotor position sensor. This process relies on the signal parsing algorithm built into the motor controller to remove invalid and redundant data from the continuously changing sensor waveform data, and accurately identify and quantify various deviation features of the sensor waveform. For example, waveform feature extraction can identify core feature parameters such as waveform reference position, fluctuation amplitude, and phase interval for the periodic orthogonal waveform signal output by the sensor, providing data support for subsequent error determination.

[0032] Signal feature information is a set of parameters that characterizes the working deviation state of a rotor position sensor. It is the effective output result after waveform feature extraction and can intuitively reflect signal anomalies caused by assembly process deviations in the sensor. It mainly includes at least one parameter of zero-point offset, amplitude deviation, and phase deviation, which can comprehensively reflect the difference between the sensor's original output waveform and the standard ideal waveform. For example, signal feature information can include the zero-point offset parameter alone, or it can integrate the three types of deviation parameters of zero point, amplitude, and phase simultaneously to adapt to the error performance of different sensors. Zero-point offset is a numerical value that characterizes the deviation of the reference zero point of the rotor position sensor's output waveform from the standard theoretical zero point. In an ideal state, the zero point of the sensor's standard waveform is the coordinate reference origin. Mass production assembly errors will cause the reference zero point of the actual output waveform of the sensor to shift, resulting in an initial analytical deviation of the motor rotor position. For example, if the reference center point of the actual output waveform of the sensor has a fixed offset relative to the standard origin, the corresponding calculated offset value is the zero-point offset, which can be used to compensate for the initial position detection error of the sensor. Amplitude deviation is the numerical value representing the difference between the actual output waveform amplitude of a rotor position sensor and the standard theoretical amplitude. The amplitude of the quadrature output waveform of a standard sensor is consistent and meets the design threshold. However, due to component tolerances and assembly deviations, the actual output waveform of the sensor may exhibit excessive or insufficient amplitude, leading to a decrease in position resolution accuracy. For example, when there is a difference between the peak values ​​of the sine and cosine output waveforms of the sensor, this difference is the corresponding amplitude deviation, used to correct the detection error caused by inconsistent waveform amplitudes. Phase deviation is the numerical value representing the deviation between the actual phase difference of the two quadrature output waveforms of a rotor position sensor and the standard theoretical phase difference. Ideally, the phase difference between the sine and cosine waveforms output by the sensor is a fixed standard angle. Assembly deviations can cause phase shifts and phase difference inaccuracies in the two waveforms, directly affecting the accurate calculation of the rotor angle. For example, if the actual phase interval of the two quadrature waveforms deviates from the standard design angle, the corresponding deviation value is the phase deviation, used to correct the position resolution error caused by waveform phase shifts.

[0033] By implementing step 102, waveform features are extracted from the original signal sequence, and at least one signal feature information among zero offset, amplitude deviation, and phase deviation is obtained, which can identify the deviation features in the output signal of the rotor position sensor. Since the above signal feature information can reflect the difference between the sensor output and the target state, it can provide a basis for determining the subsequent compensation parameters, thereby reducing the impact of installation deviation on the position detection results and improving the accuracy of rotor position detection.

[0034] Step 103: Based on the ambient temperature detection value and signal characteristic information of the target motor, determine the target calibration parameters used to compensate for the installation error and temperature influence of the rotor position sensor.

[0035] In some examples, the detected ambient temperature value is the real-time temperature value of the working environment where the target motor and the rotor position sensor are currently located, which can truly reflect the temperature condition during the operation of the sensor. The output signal characteristics of the rotor position sensor will change regularly with the ambient temperature. This temperature value is the basic data for quantifying the temperature interference error and implementing temperature compensation. The ambient temperature of the motor body or the sensor installation area can be collected in real time through the temperature acquisition unit supporting the motor controller. For example, the detected ambient temperature value can be the initial temperature value when the motor is at room temperature and stationary, or the working temperature value when the motor is in a steady state after short-term operation, which is used to match the signal error correction requirements under different temperature conditions.

[0036] The target calibration parameter is an integrated final compensation parameter that combines mechanical installation error correction and temperature drift error correction. This parameter is comprehensively generated based on the inherent signal deviation of the sensor and the real-time temperature interference characteristics, and can simultaneously offset fixed installation errors such as zero-point offset, amplitude deviation, and phase deviation caused by the mass production assembly process, as well as dynamic signal drift errors caused by ambient temperature changes. The extracted signal feature information can be associated with the real-time ambient temperature detection value for calculation, and combined with the preset error correction logic, to obtain a standardized callable parameter after unified fitting and correction of various deviations. For example, the target calibration parameter is a set of comprehensive correction parameters adapted to the current temperature condition, which can correspond to the compensation requirements for single or multiple combined deviations of the sensor zero point, amplitude, and phase.

[0037] By implementing step 103, the target calibration parameter is determined by combining the detected ambient temperature value of the target motor and the signal feature information, which can simultaneously compensate for the effects caused by installation errors and temperature changes. Since the ambient temperature change may affect the output characteristics of the rotor position sensor, incorporating the temperature factor into the parameter determination process can make the compensation process take into account different operating environment factors, thereby improving the stability and consistency of the rotor position detection results under different temperature conditions.

[0038] Step 104: Store the target calibration parameter in the non-volatile memory associated with the target motor, so that the target motor can compensate the detection result of the motor rotor position sensor based on the target calibration parameter during operation.

[0039] In some examples, the non-volatile memory (NVM) associated with the target motor is a dedicated storage hardware unit that matches the target motor controller and enables persistent data retention even when power is off. Unlike volatile memory units that lose data upon power failure, this memory can continuously retain the internally stored calibration parameter data when the motor is powered off or the equipment is stopped, providing stable data support for error compensation during subsequent motor power-on operation. For example, this non-volatile memory can be an electrically erasable programmable read-only memory (EEPROM) to permanently store various sensor calibration parameters corresponding to the target motor, meeting the long-term stable storage requirements of mass-produced motors.

[0040] For example, after the motor controller completes the calibration parameter verification and finds no errors, it performs a fixed-point writing operation to solidify the parameters. Subsequently, each time the motor is powered on, it automatically reads the stored target calibration parameters and adds them to the real-time detection results of the sensor to complete the deviation correction. For example, each time the motor starts running, the controller automatically retrieves the solidified target calibration parameters and performs correction calculations on the position detection data output by the rotor position sensor in real time, so as to offset the signal drift error caused by the inherent installation deviation of the sensor and the current temperature conditions, thereby improving the position detection accuracy.

[0041] By implementing step 104, the target calibration parameters are stored in the non-volatile memory associated with the target motor, which allows the target motor to directly call the target calibration parameters to compensate for the detection results during subsequent operation. Since the calibration parameters can be continuously retained, there is no need to repeat the parameter acquisition and calculation process, thereby maintaining the position detection accuracy and improving the control stability of the target motor during operation.

[0042] In summary, this embodiment controls the target motor to move in an open-loop manner within a preset motion range and acquires the original signal sequence output by the rotor position sensor. This allows for the formation of sensor output data corresponding to the actual position changes of the rotor during motor movement. Since the calibration process acquires signals based on the actual operating state of the target motor, it reflects the actual output characteristics after sensor installation, thus providing data support for subsequent calibration and improving the matching degree between the calibration process and the actual assembly state of the target motor. By extracting waveform features from the original signal sequence and obtaining at least one signal feature information among zero-point offset, amplitude deviation, and phase deviation, deviation characteristics in the rotor position sensor output signal can be identified. Since the signal feature information reflects the difference between the sensor output and the ideal state, it provides a basis for subsequent error correction, thereby reducing installation-related factors. This method improves the accuracy of rotor position detection results by addressing position detection deviations caused by installation errors and temperature variations. By combining the target motor's ambient temperature detection value with signal characteristic information to determine target calibration parameters, it can simultaneously compensate for installation errors and temperature effects. Since changes in ambient temperature may cause variations in sensor output characteristics, incorporating temperature factors into the calibration parameter determination process ensures that the calibration results take into account both installation conditions and environmental changes, thereby improving the stability and consistency of rotor position detection results under different temperature conditions. By storing the target calibration parameters in a non-volatile memory associated with the target motor, the rotor position sensor detection results can be compensated based on the target calibration parameters during motor operation. This allows the calibration results to be continuously applied to subsequent operating stages without repeated parameter acquisition and calculation, thus maintaining rotor position detection accuracy and improving the control stability of the target motor during operation. In summary, the motor rotor position sensor calibration method provided in this application, by acquiring the rotor position sensor signal under the actual operating state of the target motor and extracting signal characteristics, combining ambient temperature to determine calibration parameters and storing and compensating for them, can reduce the impact of installation errors and temperature variations on position detection, improving rotor position detection accuracy, stability, and motor control stability.

[0043] In some embodiments, before controlling the target motor to move in an open-loop manner within a preset motion range, the motor rotor position sensor calibration method may further include: verifying the installation status of the rotor position sensor to obtain an installation verification result; if the installation verification result is successful, acquiring motion condition detection information of the target motor, wherein the motion condition detection information may include locking mechanism status information and phase current fault detection information of the target motor; determining whether the target motor has the motion conditions based on the motion condition detection information; if the target motor has the motion conditions, allocating a preset motion range to the target motor so that the load connected to the target motor does not cause displacement when the target motor rotates continuously within the preset motion range.

[0044] In some examples, the installation confirmation result is a judgment result obtained after the motor controller comprehensively verifies the assembly firmness of the rotor position sensor, the hardware wiring status, and the integrity of the signal transmission path, and is used to confirm that the sensor has normal signal output and detection working conditions; this result can be obtained by the motor controller calling the built-in hardware self-check program to automatically detect and verify the connection line, installation and fixation status, and signal port connectivity of the sensor; for example, the installation confirmation result is divided into two states: passed and failed. When the installation confirmation result is passed, it means that the sensor is firmly installed, the line connection is normal, and the signal path is normal; when the installation confirmation result is failed, it means that there are problems such as looseness, loose connection, disassembly, or line failure of the sensor, and calibration operations cannot be carried out.

[0045] The motion condition detection information is a set of status data used to comprehensively determine whether the target motor has safe calibration motion conditions, covering two major dimensions: the mechanical operation state and the electrical operation state of the motor, and is the basis for judging whether the motor can start an open-loop calibration motion; for example, the motion condition detection information mainly includes the locking mechanism state information and the phase current fault detection information of the target motor. The locking mechanism state information is feedback data representing the current working state of the locking mechanism supporting the target motor. The locking mechanism is used to lock the rotor position under the motor shutdown condition to prevent the rotor from rotating freely, and its working state directly determines whether the motor can rotate normally; this information can be obtained by the motor controller reading the hardware feedback port signal corresponding to the locking mechanism and analyzing the current working mode and operation state of the mechanism; for example, the locking mechanism state information can reflect different working states such as the mechanism being fully unlocked, the mechanism being locked and jammed, and the mechanism not being fully unlocked. Only when the mechanism is in the fully unlocked state can the motor rotate freely. The phase current fault detection information is fault judgment data representing the operation state of the electrical circuit of the three-phase stator winding of the target motor, and is used to detect whether there are abnormal faults in the electrical circuit of the motor to avoid electrical damage during the calibration process; this information can be obtained by the motor controller collecting the real-time current values of the three-phase stator winding through the built-in current sampling unit and comparing and analyzing them with the preset normal current threshold; for example, the phase current fault detection information can reflect states such as the electrical circuit being normal, the phase current being open, the phase current being overcurrent, and the current bias being abnormal. A fault-free electrical circuit is the basis for the safe operation of the motor.

[0046] The process of judging whether the target motor has motion conditions based on the motion condition detection information can adopt multi-condition AND logic verification, and both conditions of normal mechanical structure and normal electrical circuit need to be met simultaneously; for example, when the locking mechanism is fully unlocked and there is no fault in the phase current, it is determined that the target motor has effective motion conditions; if the locking mechanism is not unlocked or there is any fault in the phase current, it is determined that the motor does not have motion conditions and the calibration process is prohibited from starting.

[0047] The preset motion range can isolate the impact of calibration motion on the back-end load while ensuring that the motor can rotate normally and complete the sensor signal acquisition. It can retrieve the motor mechanical limit parameters and load binding parameters to calculate and generate a small-amplitude, load-free exclusive electrical angle motion range. For example, the assigned preset motion range is the small-amplitude electrical angle rotation range of the motor. The motor rotor rotates continuously back and forth within this range, only completing its own mechanical action, without causing the connected load to move, thus completely avoiding the risk of load interference and equipment displacement during the calibration process.

[0048] For example, the motor controller first starts the sensor installation self-test program to complete the installation status verification of the rotor position sensor and generate the corresponding installation confirmation result. Under the premise that the installation status verification is passed, the controller synchronously collects the status of the motor locking mechanism and the three-phase current status, and integrates them to obtain complete motor motion condition detection information. The detection information is comprehensively verified through preset judgment logic. After confirming that there are no abnormalities in the motor mechanical structure and electrical circuit, the controller automatically matches and allocates a safe motion range suitable for the current motor operating conditions.

[0049] By implementing the above embodiments, the installation status of the rotor position sensor is confirmed before calibration, and the target motor is judged to have the conditions for movement by combining the locking mechanism status information and phase current fault detection information. This can avoid the problem of mislearning caused by calibration under abnormal sensor installation or motor fault conditions. At the same time, by allocating a preset movement range that will not cause load displacement, the target motor can complete continuous rotation calibration without affecting the status of the external mechanism. This can improve the data validity and security of the calibration process, avoid the interference of abnormal working conditions on the calibration results, and further improve the calibration accuracy of the rotor position sensor and the stability of motor control.

[0050] In some embodiments, the aforementioned step 101 may include: generating a rotating magnetic field by applying an orthogonal voltage vector with a preset amplitude and a preset frequency to the stator winding of the target motor to drive the target motor to rotate at a preset speed within a preset motion range; and obtaining the original signal sequence by synchronously acquiring at least one complete electrical cycle of orthogonal analog signals output by the rotor position sensor during the rotation of the target motor.

[0051] In some examples, based on preset calibration-specific control parameters, two sets of mutually orthogonal constant voltage vectors can be output to the three-phase stator windings of the target motor. The preset amplitude and preset frequency are fixed parameters that are pre-calibrated and stored, adapting to the low-speed calibration requirements of the motor, ensuring the stability and standardization of the output voltage signal, and avoiding abnormal motor operation caused by voltage parameter fluctuations. For example, the preset amplitude is set to a low voltage amplitude suitable for low-speed motor drive, and the preset frequency is set to a low-frequency constant frequency. By matching the motor magnetic field drive requirements with two sets of orthogonal voltage vectors, the motor vibration problem caused by excessively high voltage amplitude and unstable frequency is eliminated. After the stator windings are connected to the orthogonal voltage vectors, a continuous and stable spatial rotating magnetic field is formed through electromagnetic induction, which drives the motor rotor to rotate at a uniform speed by magnetic field traction.

[0052] During the rotation of the target motor, the process of synchronously acquiring at least one complete electrical cycle of orthogonal analog signals output by the rotor position sensor to obtain the original signal sequence involves the motor controller simultaneously activating the signal sampling function while the motor is running stably in open loop. This process involves continuously acquiring complete cycle orthogonal analog waveforms output by the sensor and integrating them to generate the original data sequence without any algorithmic processing. For example, the controller synchronously acquires two orthogonal analog signals from the rotor position sensor within one complete electrical cycle, fully recording all original features of the waveforms, such as peak values, zero points, and phase intervals, and integrating them to form the original signal sequence that can be used for subsequent analytical calculations.

[0053] For example, the motor controller calls the pre-stored calibration-specific voltage parameters to stably output orthogonal voltage vectors with fixed amplitude and fixed frequency to the stator windings of the target motor; relying on the electromagnetic coupling effect of the orthogonal voltage vectors, a continuous and stable rotating magnetic field is generated, which pulls the target motor to rotate continuously at a constant preset low speed within the safe movement range; throughout the process of the motor maintaining uniform and stable operation, a high-precision signal sampling mechanism is simultaneously activated to continuously collect the orthogonal analog signals output by the rotor position sensor; collect the timing waveform data of at least one complete electrical cycle, complete the data integration and storage, and generate the original signal sequence.

[0054] By implementing the above embodiments, applying an orthogonal voltage vector with a preset amplitude and frequency to the stator winding of the target motor generates a rotating magnetic field, which can drive the target motor to perform open-loop motion at a stable preset speed, making the rotor position sensor output continuous and regular. At the same time, by synchronously acquiring orthogonal analog signals of at least one complete electrical cycle, complete sensor output feature information can be obtained, which can reduce feature extraction deviations caused by unstable motion or incomplete sampling, improve the accuracy of installation error identification, and thus improve rotor position detection accuracy and control stability.

[0055] In some embodiments, step 102 may include: performing digital filtering on the original signal sequence to obtain a filtered signal sequence; performing curve fitting on the filtered signal sequence to obtain the initial zero-point offset, initial amplitude deviation, and initial phase deviation of the rotor position sensor; constructing a Lissajous figure of the rotor position sensor under the ambient temperature detection value based on the sine and cosine signal components in the filtered signal sequence; extracting the elliptical geometric features of the Lissajous figure, wherein the elliptical geometric features may include the offset coordinates of the ellipse center relative to the origin, the ratio of the length of the major axis to the minor axis of the ellipse, and the deflection angle of the major axis of the ellipse relative to a preset ideal reference axis; correcting the initial zero-point offset according to the offset coordinates to obtain the zero-point offset; correcting the initial amplitude deviation according to the length ratio to obtain the amplitude deviation; correcting the initial phase deviation according to the deflection angle to obtain the phase deviation; and determining the zero-point offset, amplitude deviation, and phase deviation as signal feature information.

[0056] In some examples, digital filtering is a digital processing procedure that uses a built-in digital filtering algorithm in the motor controller to remove noise and optimize the signal from the raw signal sequence acquired by the rotor position sensor. This effectively filters out invalid noise signals generated by electromagnetic interference, high-frequency jitter, and sampling errors during motor operation, preserving the sensor's true and valid waveform characteristics and improving signal purity. For example, digital filtering can employ conventional filtering algorithms such as mean filtering and low-pass filtering to remove high-frequency spikes and random noise from the raw signal, retaining continuous and stable valid waveform data. The filtered signal sequence is a collection of pure time-series signals that has undergone digital filtering to remove noise interference and retain true waveform characteristics. This signal sequence eliminates invalid interference components from the external environment and sampling equipment, accurately reflecting the inherent waveform deviation characteristics of the rotor position sensor. For example, the filtered signal sequence is smooth, continuous, orthogonal waveform time-series data, free of random spikes and numerical jumps, completely preserving the sensor waveform's zero-point, amplitude, and phase characteristics.

[0057] Curve fitting is a computational process that uses mathematical fitting algorithms to reconstruct discrete waveform data into a continuous and standardized form after filtering and clean signal sequences. It can eliminate data deviations at discrete sampling points, restore the standard continuous variation law of sensor waveforms, and accurately highlight various inherent deviations in waveforms. For example, curve fitting can smoothly fit discrete sine and cosine sampling data to restore a continuous periodic waveform that is close to the theoretical standard form, which facilitates the subsequent quantitative extraction of deviation parameters.

[0058] The initial zero-point offset is the preliminary zero-point offset value after waveform curve fitting without geometric feature correction. It initially reflects the degree of deviation of the sensor waveform's reference zero point from the theoretical zero point. The zero-point offset value can be initially calculated by comparing the actual reference center point of the fitted waveform with the preset theoretical zero-point coordinates through difference calculation. The initial amplitude deviation is the preliminary amplitude deviation value after waveform curve fitting without geometric feature correction. It is used to initially characterize the difference between the actual output waveform amplitude and the theoretical standard amplitude. It can be initially quantified by comparing the peak data of the statistically fitted waveform with the preset standard amplitude parameters. The initial phase deviation is the preliminary phase deviation value after waveform curve fitting without geometric feature correction. It is used to initially characterize the offset difference between the actual phase difference and the theoretical standard phase difference of two orthogonal waveforms. It can be calculated by comparing the actual phase interval of the two orthogonal waveforms after analytical fitting with the standard orthogonal phase parameters.

[0059] The sinusoidal signal component is an analog signal component in the quadrature output waveform of the rotor position sensor that changes periodically according to a sinusoidal law. It is one of the sensor's output signals and carries the fundamental information about rotor position changes. Its waveform deviation directly affects the accuracy of position analysis. It can be extracted separately from the filtered signal sequence, with the time-series signal data changing according to a sinusoidal periodic law, to form an independent set of sinusoidal signals. The cosine signal component is an analog signal component in the quadrature output waveform of the rotor position sensor that changes periodically according to a cosine law. It is orthogonal to the sinusoidal signal component and together they constitute the signal basis for rotor position analysis. This component, in conjunction with the sinusoidal signal component, can completely characterize the real-time angular position of the rotor. It can be extracted separately from the filtered signal sequence, with the time-series signal data changing according to a cosine periodic law, to form an independent set of cosine signals.

[0060] The signal Lissajous figure is a closed geometric figure constructed using the sinusoidal and cosine signal components of a filtered signal sequence as the horizontal and vertical coordinate variables. It is an analytical model for quantifying the overall deviation characteristics of orthogonal waveforms. In an ideal state, the sensor signal corresponds to a standard circular Lissajous figure, while when there is assembly error, it presents an elliptical figure. This figure can be generated by the click controller by mapping the sinusoidal and cosine signal data of the same period one by one in a plane coordinate system, thus generating a closed geometric trajectory figure. For example, the signal Lissajous figure is an elliptical trajectory figure that fits the actual error state of the sensor. The geometric deformation characteristics of the figure can intuitively correspond to the zero point, amplitude, and phase deviation of the sensor.

[0061] Elliptical geometric features are a collective term for the standardized geometric parameters possessed when a signal Lissajous figure presents an elliptical shape. They serve as the basis for decomposing and quantifying multidimensional signal errors from sensors. Geometric analytical algorithms can be used to extract global parameters from the generated elliptical trajectory, quantifying various geometric feature parameters. For example, elliptical geometric features mainly include three core parameters: the offset coordinates of the ellipse center relative to the origin, the ratio of the major to minor axes of the ellipse, and the deflection angle of the major axis relative to a preset ideal reference axis. These parameters comprehensively cover various waveform deviation characteristics of the sensor. The offset coordinates of the ellipse center relative to the origin are a combination of the lateral and longitudinal offset values ​​of the elliptical geometric center of the signal Lissajous figure relative to the theoretical origin of the plane coordinate system. These coordinates can be obtained by calculating the center point coordinates of the elliptical trajectory using an elliptical geometric center solving algorithm and comparing them with the origin of the coordinate system to obtain bidirectional offset data. The ratio of the major to minor axes of the ellipse is the ratio of the longest diameter to the shortest diameter of the elliptical structure in the signal Lissajous figure. This ratio can be obtained by calculating the actual lengths of the major and minor axes of the ellipse separately using a motor controller and then performing a division operation. The deflection angle of the major axis of the ellipse relative to the preset ideal reference axis is the angle between the axis of the major axis of the ellipse in the signal Lissajous figure and the preset standard ideal reference axis. This angle can be calculated by comparing the angle of the axis of the major axis of the ellipse with the preset ideal reference axis. For example, the larger the deflection angle, the more serious the phase shift problem of the two orthogonal waveforms of the sensor, and the greater the phase deviation.

[0062] The process of correcting the initial zero-point offset based on the offset coordinates to obtain the zero-point offset relies on the precise geometric error data of the ellipse center offset coordinates. The initially zero-point offset obtained by rough calculation is calibrated and optimized. The initial zero-point offset can be compensated, corrected and numerically iterated and optimized based on the ellipse center offset coordinates. For example, after the offset coordinates are corrected, the waveform fitting error interference can be eliminated, and the final zero-point offset that can accurately characterize the true zero-point offset state of the sensor can be obtained.

[0063] The process of correcting the initial amplitude deviation based on the length ratio to obtain the amplitude deviation is based on the geometric characteristic parameter of the ratio of the major and minor axes of the ellipse. The initially calculated amplitude deviation is then precisely corrected. The initial amplitude deviation can be proportionally corrected and numerically optimized based on the difference between the actual major and minor axis ratio and the standard ratio. For example, the amplitude deviation after length ratio correction can accurately reflect the difference in amplitude between the two waveforms caused by mass production assembly of the sensor.

[0064] The process of correcting the initial phase deviation based on the deflection angle to obtain the phase deviation quantity relies on the geometric feature data of the major axis deflection angle of the ellipse. This allows for precise calibration of the roughly calculated initial phase deviation, using the major axis deflection angle as a correction benchmark for angle compensation and iterative calibration. For example, the phase deviation quantity after deflection angle correction can accurately correspond to the true phase shift of the sensor's orthogonal waveform. The three types of high-precision deviation parameters corrected by the elliptical geometric features can be integrated and summarized to form a complete, accurate set of sensor error features that can be used for subsequent calibration parameter calculations. By implementing the above embodiments, the original signal sequence is first digitally filtered to reduce the impact of noise signals on the subsequent feature extraction process. Furthermore, the initial zero-point offset, initial amplitude deviation, and initial phase deviation are obtained through curve fitting, and the above parameters are corrected by combining the elliptical geometric features of the Lissajous figure. The waveform spatial distribution features can be used to further identify signal distortion caused by installation errors, thereby improving the accuracy of the zero-point offset, amplitude deviation, and phase deviation extraction results, enhancing the rotor position detection accuracy, and strengthening the control stability during motor operation.

[0065] In some embodiments, step 103 may include: determining the temperature change rate based on the first ambient temperature detection value at a first time and the second ambient temperature detection value at a second time; querying preset temperature compensation mapping information to obtain a first set of temperature drift correction coefficients corresponding to the first ambient temperature detection value and a second set of temperature drift correction coefficients corresponding to the second ambient temperature detection value; if the temperature change rate exceeds a preset rate threshold, performing linear interpolation based on the first set of temperature drift correction coefficients and the second set of temperature drift correction coefficients to generate an intermediate temperature drift correction coefficient; otherwise, determining the second set of temperature drift correction coefficients as the intermediate temperature drift correction coefficient; and performing temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation in the signal feature information based on the intermediate temperature drift correction coefficient to obtain the target calibration parameters.

[0066] In some examples, the first moment is the first temperature acquisition time node recorded by the motor controller within the temperature sampling period, serving as the starting time reference for determining the temperature change state; for example, the first moment can be the initial timing node at the instant the temperature compensation calculation starts after the sensor signal feature extraction is completed. The second moment is the second temperature acquisition time node recorded by the motor controller after a preset sampling interval, serving as the ending time reference for determining the temperature change state; for example, the second moment is a timing node with a preset millisecond or second interval from the first moment.

[0067] The first ambient temperature detection value is the real-time temperature value of the environment where the target motor and rotor position sensor are located, acquired at the first moment, representing the initial temperature state of the temperature change process. This effective temperature sampling data can be obtained by the motor controller synchronously calling the temperature acquisition unit at the first moment to collect and convert the data. The second ambient temperature detection value is the real-time temperature value of the environment where the target motor and rotor position sensor are located, acquired at the second moment, representing the current temperature state of the temperature change process. This effective temperature data can be obtained by the motor controller synchronously completing ambient temperature sampling, filtering, and numerical calibration at the second moment. For example, the second ambient temperature detection value can be the temperature value after the motor has slightly heated up during operation, or it can be the temperature value after natural cooling.

[0068] The rate of temperature change is the amount of change in the ambient temperature of the target motor per unit time. It is used to characterize how quickly the ambient temperature rises or falls under the current operating conditions. It is a criterion for distinguishing between static temperature conditions and dynamic temperature change conditions. It can intuitively reflect the degree of dynamic change in the temperature environment where the sensor is located, and provide a basis for determining differentiated temperature drift compensation strategies. It can be calculated by the controller by the ratio of the temperature difference between two moments to the time interval. For example, the larger the rate of temperature change value, the more drastic the fluctuation of the ambient temperature, the more obvious the nonlinear change of the sensor temperature drift, and the greater the impact on calibration accuracy.

[0069] The preset temperature compensation mapping information is a dataset of correspondences between temperature and temperature drift correction coefficients, obtained in advance through calibration experiments and stored internally within the motor controller. This mapping information covers the entire operating temperature range of the motor and establishes a matching relationship between different temperature values ​​and the optimal temperature drift correction coefficient. For example, the preset temperature compensation mapping information includes a complete set of temperature drift correction parameters corresponding to multiple temperature nodes, including low temperature, normal temperature, and high temperature. The first set of temperature drift correction coefficients is a set of temperature drift correction parameters uniquely corresponding to the first ambient temperature detection value, obtained by querying the preset temperature compensation mapping information. The first ambient temperature detection value can be used as an index to traverse the preset temperature compensation mapping information and match the corresponding first set of temperature drift correction coefficients. The second set of temperature drift correction coefficients is a set of temperature drift correction parameters uniquely corresponding to the second ambient temperature detection value, obtained by querying the preset temperature compensation mapping information. The second ambient temperature detection value can be used as an index to retrieve the corresponding second set of temperature drift correction coefficients after searching the preset temperature compensation mapping information.

[0070] The preset rate threshold is a pre-calibrated critical value for the rate of temperature change, used to distinguish between steady-state temperature conditions and drastic temperature change conditions. It serves as a benchmark for determining whether interpolation correction is needed and can filter out different operating scenarios where the temperature changes slowly or rapidly. For example, when the rate of temperature change is less than the preset rate threshold, the temperature is determined to be in a steady-state slow-change state; when the rate of temperature change is greater than the preset rate threshold, the temperature is determined to be in a rapid fluctuation state. The preset rate threshold can be set to 0.5 degrees Celsius per second.

[0071] When the temperature changes rapidly, the fixed coefficient of a single temperature node cannot match the continuous temperature drift characteristics. By linearly interpolating two sets of coefficients, an intermediate correction coefficient for continuous transition can be obtained to adapt to the dynamic temperature change characteristics. When the temperature changes slowly and steadily, the correction coefficient corresponding to the current temperature can be directly used to meet the compensation accuracy requirements. For example, linear interpolation is used in rapid heating or cooling conditions, while the second set of temperature drift correction coefficients corresponding to the current temperature is directly reused in steady-state conditions at normal temperature.

[0072] The process of obtaining target calibration parameters by temperature compensation correction of zero-point offset, amplitude deviation, and phase deviation in signal feature information based on intermediate temperature drift correction coefficients involves superimposing the intermediate temperature drift correction coefficients onto the zero-point offset, amplitude deviation, and phase deviation respectively to complete multi-dimensional error coupling correction and integrate them to generate the final calibration parameters that can be applied in practice. For example, the parameters after this step not only compensate for the fixed deviations caused by mass production assembly, but also offset the dynamic temperature drift deviation under the current temperature conditions, forming high-precision integrated target calibration parameters.

[0073] For example, during the calibration process, the motor controller records the ambient temperature values ​​at two different times. By calculating the temperature difference between time and temperature, it accurately calculates the rate of temperature change under the current operating condition. Using the built-in preset temperature compensation mapping information, it matches two sets of temperature drift correction coefficients corresponding to the two temperature nodes and combines them with a preset rate threshold to complete the operating condition determination. For the rapid temperature change condition, it performs linear interpolation to generate intermediate temperature drift correction coefficients for transitional adaptation. For the steady-state condition, it directly selects the correction coefficient corresponding to the current temperature. Using the finally determined intermediate temperature drift correction coefficients, it performs comprehensive temperature compensation correction on the extracted sensor zero point, amplitude, and phase deviation parameters, and finally generates high-precision target calibration parameters that take into account both installation error and temperature drift error.

[0074] By implementing the above embodiments, the rate of temperature change is determined by combining the ambient temperature detection values ​​at different times, and compensation is performed by combining the temperature drift correction coefficient. This allows the calibration parameters to be dynamically adjusted with temperature changes. Furthermore, when the rate of temperature change is large, an intermediate temperature drift correction coefficient is generated by linear interpolation, which can reduce the compensation abruptness problem during rapid temperature changes. This can improve the continuity and adaptability of the temperature compensation process, reduce the position detection error caused by temperature drift, and improve the stability of rotor position detection and motor control.

[0075] In some embodiments, the aforementioned temperature compensation correction of the zero-point offset, amplitude deviation, and phase deviation in the signal characteristic information based on the intermediate temperature drift correction coefficient to obtain the target calibration parameters may include: obtaining thermal hysteresis compensation parameters corresponding to the rotor position sensor, wherein the thermal hysteresis compensation parameters characterize the asymmetry of the temperature drift characteristics of the rotor position sensor during the heating and cooling processes; selecting a corresponding hysteresis correction amount from the thermal hysteresis compensation parameters based on the direction of the temperature change rate; adjusting the intermediate temperature drift correction coefficient based on the hysteresis correction amount to obtain the target temperature drift correction coefficient; and performing temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation based on the target temperature drift correction coefficient to obtain the target calibration parameters.

[0076] In some examples, the thermal hysteresis compensation parameters corresponding to the rotor position sensor are a set of exclusive compensation parameters obtained through batch calibration for the corresponding model of rotor position sensor. These parameters characterize the asymmetric differences in temperature drift characteristics exhibited by the sensor during the heating and cooling operation phases. Under different temperature change trends, the degree of signal drift corresponding to the same temperature point of the sensor varies. This set of parameters can completely record such nonlinear and asymmetric temperature drift patterns. These parameters can be obtained by calibrating the sensor under uniform heating and uniform cooling full-range operating conditions in a controlled high and low temperature test environment before the equipment leaves the factory, collecting signal error data under different temperature change directions, and then fitting and solidifying them to obtain a standardized parameter set. For example, the thermal hysteresis compensation parameters independently distinguish between the heating condition parameter group and the cooling condition parameter group, respectively adapting to two different temperature change trends, and can cover the temperature alternation scenario of normal motor operation.

[0077] The hysteresis correction is a single-condition adaptation correction value extracted from the thermal hysteresis compensation parameter set. It is a correction component used to compensate for the asymmetric error of sensor thermal hysteresis. This correction can specifically compensate for the calibration deviation caused by the difference in temperature drift characteristics during heating and cooling, and solve the defect that a single temperature drift coefficient cannot adapt to bidirectional temperature change conditions. This correction can distinguish the temperature change trend based on the positive or negative attribute of the temperature change rate and accurately match the corresponding value. It selects the independent correction value that matches the corresponding condition from the pre-stored thermal hysteresis compensation parameters. For example, when the temperature change rate is positive, it is determined that the current condition is heating, and the hysteresis correction value corresponding to heating is retrieved; when the temperature change rate is negative, it is determined that the current condition is cooling, and the hysteresis correction value corresponding to cooling is retrieved.

[0078] The target temperature drift correction coefficient is the final temperature drift correction coefficient obtained by superimposing the thermal hysteresis asymmetry error correction on the intermediate temperature drift correction coefficient. This coefficient integrates three types of influencing factors: temperature change amplitude, temperature change rate, and temperature change direction. It not only corrects the conventional signal drift error caused by dynamic temperature changes, but also compensates for the nonlinear hysteresis error of sensor heating and cooling. Its adaptability and accuracy are far superior to that of a single static correction coefficient. For example, the target temperature drift correction coefficient can accurately adapt to complex working conditions such as alternating temperature changes and rapid heating and cooling, completely making up for the accuracy shortcomings of conventional temperature compensation.

[0079] The process of obtaining target calibration parameters by performing temperature compensation correction on zero-point offset, amplitude deviation, and phase deviation based on target temperature drift correction coefficients involves coupling the target temperature drift correction coefficients to the zero-point offset, amplitude deviation, and phase deviation respectively, completing multi-dimensional error compensation calculations, and integrating and standardizing them to obtain the final target calibration parameters that can be solidified and used. For example, the target calibration parameters obtained after this step can ensure that the sensor maintains high-precision position detection capability under all operating conditions such as constant temperature, rapid heating, rapid cooling, and temperature alternation.

[0080] By implementing the above embodiments, thermal hysteresis compensation parameters are introduced, and the differences in temperature drift characteristics during the heating and cooling processes are distinguished. This allows for compensation for asymmetric changes in the temperature response of the rotor position sensor. Furthermore, by selecting the corresponding hysteresis correction amount based on the direction of temperature change and adjusting the temperature drift correction coefficient, the compensation deviation caused by thermal hysteresis can be reduced, thereby improving the temperature compensation accuracy and making the rotor position detection results more accurate and stable. This further enhances the control stability of the target motor in dynamic temperature change scenarios.

[0081] In some embodiments, after storing the target calibration parameters in a non-volatile memory associated with the target motor, the motor rotor position sensor calibration method may further include: acquiring the real-time speed and real-time torque of the target motor during operation; determining the current operating condition category of the target motor based on the real-time speed and real-time torque; retrieving the segmented compensation correction coefficient corresponding to the operating condition category from the non-volatile memory based on the operating condition category; and adjusting the target calibration parameters according to the segmented compensation correction coefficient to obtain dynamic calibration parameters under the current operating condition, so as to adapt to different operating conditions when compensating the detection results of the motor rotor position sensor.

[0082] In some examples, real-time rotational speed is the instantaneous rotor speed of the target motor during actual operation. It is an operating parameter characterizing the motor's operating speed state and one of the fundamental dimensions for classifying motor operating conditions. Real-time rotational speed can intuitively reflect the current operating speed of the motor. The signal error characteristics of the rotor position sensor vary slightly across different speed ranges. For example, real-time rotational speed can correspond to the instantaneous rotational speed values ​​of different speed states, such as low-speed creeping, medium-speed steady operation, and high-speed continuous operation. Real-time torque is the instantaneous electromagnetic torque output by the target motor during actual operation. It is used to characterize the motor's current load output state and is another core dimension parameter for classifying motor operating conditions. Different load states of the motor will cause vibration of the motor body and changes in the magnetic circuit, which will indirectly affect the signal output accuracy of the rotor position sensor. For example, real-time torque can correspond to the instantaneous torque output values ​​of different load conditions, such as no-load, light-load, rated load, and heavy-load overload.

[0083] The current operating condition category of the target motor is a standardized operating condition type determined by the motor controller based on the coupling state of real-time speed and real-time torque. The operating condition category categorizes and distinguishes the complex and ever-changing operating scenarios of the motor. Different operating condition categories correspond to different sensor error offset patterns, which serve as the classification basis for achieving segmented and accurate compensation. According to the preset operating condition classification threshold model, the real-time collected speed and torque data are matched and compared with the threshold range to automatically determine and output the corresponding operating condition category. For example, the operating condition category can be divided into standardized operating conditions such as low-speed light load, medium-speed medium load, high-speed heavy load, and start-stop transition.

[0084] The segmented compensation correction coefficients corresponding to the operating condition categories are exclusive compensation parameters obtained through operating condition calibration experiments for each standardized motor operating condition category. Each operating condition category is independently matched with a set of exclusive correction coefficients. These coefficients are used to compensate for the shortcomings of fixed target calibration parameters in adapting to the differences in operating conditions, and to accurately correct the specific detection deviations generated by sensors under different operating conditions. These coefficients can be generated by traversing the full speed and full load range of the motor before the equipment leaves the factory, fitting the sensor error offset pattern under different operating conditions, generating the segmented compensation correction coefficients corresponding to each operating condition, and storing them in the non-volatile memory in advance. For example, the segmented compensation correction coefficients corresponding to the high-speed heavy load operating condition can specifically compensate for the offset error of the sensor signal under high load and high speed, while the correction coefficients corresponding to the low-speed light load operating condition are adapted to the error correction requirements of stable operation under low load.

[0085] The controller can retrieve the segmented compensation correction coefficients corresponding to the current operating condition, perform coupled calculations and superimposed corrections with the static target calibration parameters, and update and generate dynamic calibration parameters in real time, which are then applied to compensate for sensor detection results. For example, when the motor switches operating conditions, the controller synchronously updates the corresponding segmented compensation correction coefficients and iterates the calibration parameters in real time to ensure that the sensor position detection results always match the actual operating state of the current operating condition, thus preventing the decrease in compensation accuracy and motor vibration caused by the switching of operating conditions.

[0086] For example, after the target motor enters normal operation, the motor controller continuously collects the instantaneous speed and torque data of the motor in real time, and simultaneously completes data filtering and validity verification; the real-time speed and torque data are substituted into the preset working condition judgment model to accurately match and determine the current working condition category of the motor; the segmented compensation correction coefficients of the corresponding working condition are quickly retrieved from the non-volatile memory, and the pre-stored static target calibration parameters are dynamically corrected and optimized to generate dynamic calibration parameters that are adapted to the current real-time working condition, and applied to the detection results of the rotor position sensor in real time to compensate for the motor's operation under all working conditions, thereby achieving high-precision position analysis and smooth control of the motor.

[0087] By implementing the above embodiments, the real-time speed and torque of the target motor during operation are obtained to determine the current operating condition category. The corresponding segmented compensation correction coefficient is called to dynamically adjust the target calibration parameters for different operating conditions, so that the rotor position sensor compensation process can adapt to the control requirements under different operating conditions. Since the degree of influence of sensor error may vary under different motor speeds and load conditions, targeted compensation through dynamic calibration parameters can reduce position detection deviation under complex operating conditions, improve position detection accuracy and control stability under different operating conditions, and thus enhance the overall operating performance of the target motor.

[0088] Furthermore, as an implementation of the aforementioned method embodiments, this application also provides a motor rotor position sensor calibration device for implementing the aforementioned method embodiments. This device embodiment corresponds to the aforementioned method embodiments. For ease of reading, this motor rotor position sensor calibration device embodiment will not repeat the details of the aforementioned method embodiments one by one, but it should be understood that the device in this application embodiment can correspondingly implement all the contents of the aforementioned method embodiments. For example... Figure 2 As shown, the motor rotor position sensor calibration device 20 includes: a data acquisition unit 201, a feature extraction unit 202, a parameter determination unit 203, and a parameter storage unit 204. The data acquisition unit 201 controls the target motor to move in an open-loop manner within a preset motion range and acquires the original signal sequence output by the rotor position sensor installed on the target motor. The feature extraction unit 202 extracts waveform features from the original signal sequence to obtain signal feature information of the rotor position sensor, wherein the signal feature information may include at least one of zero-point offset, amplitude deviation, and phase deviation. The parameter determination unit 203 determines target calibration parameters for compensating for installation errors and temperature effects of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal feature information. The parameter storage unit 204 stores the target calibration parameters in a non-volatile memory associated with the target motor, so that the target motor compensates for the detection results of the motor rotor position sensor based on the target calibration parameters during operation.

[0089] In some embodiments, the data acquisition unit 201 is further configured to confirm the installation status of the rotor position sensor and obtain an installation confirmation result; if the installation confirmation result is passed, the motion condition detection information of the target motor is acquired, wherein the motion condition detection information includes the locking mechanism status information and phase current fault detection information of the target motor; based on the motion condition detection information, it is determined whether the target motor has the motion conditions; if it is determined that the target motor has the motion conditions, a preset motion range is allocated to the target motor so that the load connected to the target motor does not cause displacement when the target motor rotates continuously within the preset motion range.

[0090] In some embodiments, the data acquisition unit 201 is further configured to generate a rotating magnetic field by applying an orthogonal voltage vector with a preset amplitude and a preset frequency to the stator winding of the target motor to drive the target motor to rotate at a preset speed within a preset motion range; during the rotation of the target motor, the original signal sequence is obtained by synchronously acquiring at least one complete electrical cycle of orthogonal analog signal output by the rotor position sensor.

[0091] In some embodiments, the feature extraction unit 202 is further configured to perform digital filtering on the original signal sequence to obtain a filtered signal sequence; perform curve fitting on the filtered signal sequence to obtain the initial zero-point offset, initial amplitude deviation, and initial phase deviation of the rotor position sensor; construct a Lissajous figure of the rotor position sensor under the ambient temperature detection value based on the sine and cosine signal components in the filtered signal sequence; extract the elliptical geometric features of the Lissajous figure, wherein the elliptical geometric features include the offset coordinates of the ellipse center relative to the origin, the ratio of the length of the major axis to the minor axis of the ellipse, and the deflection angle of the major axis of the ellipse relative to a preset ideal reference axis; correct the initial zero-point offset according to the offset coordinates to obtain the zero-point offset; correct the initial amplitude deviation according to the length ratio to obtain the amplitude deviation; correct the initial phase deviation according to the deflection angle to obtain the phase deviation; and determine the zero-point offset, amplitude deviation, and phase deviation as signal feature information.

[0092] In some embodiments, the parameter determination unit 203 is further configured to determine the temperature change rate based on the first ambient temperature detection value at the first time and the second ambient temperature detection value at the second time; query the preset temperature compensation mapping information to obtain the first set of temperature drift correction coefficients corresponding to the first ambient temperature detection value and the second set of temperature drift correction coefficients corresponding to the second ambient temperature detection value; if the temperature change rate exceeds the preset rate threshold, perform linear interpolation based on the first set of temperature drift correction coefficients and the second set of temperature drift correction coefficients to generate an intermediate temperature drift correction coefficient; otherwise, determine the second set of temperature drift correction coefficients as the intermediate temperature drift correction coefficients; and perform temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation in the signal feature information based on the intermediate temperature drift correction coefficients to obtain the target calibration parameters.

[0093] In some embodiments, the parameter determination unit 203 is further configured to acquire thermal hysteresis compensation parameters corresponding to the rotor position sensor, wherein the thermal hysteresis compensation parameters characterize the asymmetry of the temperature drift characteristics of the rotor position sensor during the heating and cooling processes; select a corresponding hysteresis correction amount from the thermal hysteresis compensation parameters based on the direction of the temperature change rate; adjust the intermediate temperature drift correction coefficient based on the hysteresis correction amount to obtain the target temperature drift correction coefficient; and perform temperature compensation correction on the zero-point offset, amplitude deviation, and phase deviation based on the target temperature drift correction coefficient to obtain the target calibration parameters.

[0094] In some embodiments, the parameter storage unit 204 is further configured to acquire the real-time speed and real-time torque of the target motor during the operation of the target motor; determine the current operating condition category of the target motor based on the real-time speed and real-time torque; retrieve the segmented compensation correction coefficient corresponding to the operating condition category from the non-volatile memory based on the operating condition category; and adjust the target calibration parameters according to the segmented compensation correction coefficient to obtain the dynamic calibration parameters under the current operating condition, so as to adapt to different operating conditions when compensating the detection results of the motor rotor position sensor.

[0095] This application also provides a computer-readable storage medium storing computer-executable instructions or computer programs, which, when executed by a processor, will cause the processor to perform any step of the motor rotor position sensor calibration method provided in this application.

[0096] In some embodiments, the computer-readable storage medium may be a random access memory (RAM), a read-only memory (ROM), flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); or it may be a variety of devices that include one or any combination of the above-mentioned memories.

[0097] In some embodiments, computer-executable instructions may take the form of programs, software, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.

[0098] In some embodiments, computer-executable instructions may, but do not necessarily, correspond to files in a file system, and may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., files that store one or more modules, subroutines, or code sections).

[0099] In some embodiments, computer-executable instructions may be deployed to execute on an electronic device, or on multiple electronic devices located at one location, or on multiple electronic devices distributed across multiple locations and interconnected via a communication network.

[0100] like Figure 3As shown, this application also provides an electronic device 30, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor. When the processor 320 executes the computer program 311, it implements any step of the above-described motor rotor position sensor calibration method.

[0101] This application also provides a computer program product comprising a computer program or computer-executable instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer program or computer-executable instructions from the computer-readable storage medium and executes the computer program or computer-executable instructions, causing the electronic device to perform any step of the motor rotor position sensor calibration method described above.

[0102] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for calibrating a motor rotor position sensor, characterized in that, The motor rotor position sensor calibration method, applied to the target motor, includes: The target motor is controlled to move in an open-loop manner within a preset motion range, and the original signal sequence output by the rotor position sensor installed on the target motor is acquired. Waveform feature extraction is performed on the original signal sequence to obtain the signal feature information of the rotor position sensor, wherein the signal feature information includes at least one of zero offset, amplitude deviation and phase deviation; Based on the ambient temperature detection value of the target motor and the signal characteristic information, target calibration parameters for compensating for the installation error and temperature influence of the rotor position sensor are determined. The target calibration parameters are stored in a non-volatile memory associated with the target motor so that the target motor can compensate for the detection results of the motor rotor position sensor based on the target calibration parameters during operation.

2. The motor rotor position sensor calibration method according to claim 1, characterized in that, Before controlling the target motor to move in an open-loop manner within a preset motion range, the motor rotor position sensor calibration method further includes: The installation status of the rotor position sensor is confirmed to obtain the installation confirmation result. If the installation confirmation result is successful, the motion condition detection information of the target motor is obtained, wherein the motion condition detection information includes the locking mechanism status information and phase current fault detection information of the target motor. Based on the motion condition detection information, it is determined whether the target motor has the conditions for motion. If it is determined that the target motor meets the motion conditions, then the preset motion range is assigned to the target motor so that the target motor does not cause displacement of the load connected to the target motor when it rotates continuously within the preset motion range.

3. The motor rotor position sensor calibration method according to claim 1, characterized in that, The control of the target motor to move in an open-loop manner within a preset motion range, and the acquisition of the original signal sequence output by the rotor position sensor installed on the target motor, includes: By applying an orthogonal voltage vector with a preset amplitude and a preset frequency to the stator winding of the target motor, a rotating magnetic field is generated to drive the target motor to rotate at a preset speed within the preset motion range. During the rotation of the target motor, the original signal sequence is obtained by synchronously acquiring at least one complete electrical cycle of orthogonal analog signal output by the rotor position sensor.

4. The motor rotor position sensor calibration method according to claim 1, characterized in that, The step of extracting waveform features from the original signal sequence to obtain the signal feature information of the rotor position sensor includes: The original signal sequence is digitally filtered to obtain a filtered signal sequence; The filtered signal sequence is subjected to curve fitting processing to obtain the initial zero-point offset, initial amplitude deviation, and initial phase deviation of the rotor position sensor; Based on the sinusoidal and cosine signal components in the filtered signal sequence, a Lissajous figure of the signal of the rotor position sensor under the ambient temperature detection value is constructed. Extract the elliptical geometric features of the signal Lissajous figure, wherein the elliptical geometric features include the offset coordinates of the ellipse center relative to the origin, the ratio of the length of the major axis to the minor axis of the ellipse, and the deflection angle of the major axis of the ellipse relative to a preset ideal reference axis. The initial zero-point offset is corrected based on the offset coordinates to obtain the zero-point offset; The initial amplitude deviation is corrected based on the length ratio to obtain the amplitude deviation. The initial phase deviation is corrected based on the deflection angle to obtain the phase deviation amount; The zero-point offset, the amplitude deviation, and the phase deviation are determined as the signal characteristic information.

5. The motor rotor position sensor calibration method according to claim 1, characterized in that, The determination of target calibration parameters for compensating for installation errors and temperature effects of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal characteristic information includes: The rate of temperature change is determined based on the first ambient temperature detection value at the first moment and the second ambient temperature detection value at the second moment. The first set of temperature drift correction coefficients corresponding to the first ambient temperature detection value and the second set of temperature drift correction coefficients corresponding to the second ambient temperature detection value are obtained from the preset temperature compensation mapping information. If the rate of temperature change exceeds a preset rate threshold, then a linear interpolation is performed based on the first set of temperature drift correction coefficients and the second set of temperature drift correction coefficients to generate an intermediate temperature drift correction coefficient; otherwise, the second set of temperature drift correction coefficients is determined as the intermediate temperature drift correction coefficient. Based on the intermediate temperature drift correction coefficient, the zero-point offset, amplitude deviation, and phase deviation in the signal characteristic information are corrected by temperature compensation to obtain the target calibration parameters.

6. The motor rotor position sensor calibration method according to claim 5, characterized in that, The process of applying temperature compensation correction to the zero-point offset, amplitude deviation, and phase deviation in the signal feature information based on the intermediate temperature drift correction coefficient to obtain the target calibration parameters includes: Obtain the thermal hysteresis compensation parameter corresponding to the rotor position sensor, wherein the thermal hysteresis compensation parameter characterizes the asymmetry of the temperature drift characteristics of the rotor position sensor during the heating and cooling processes; Based on the direction of the temperature change rate, a corresponding hysteresis correction amount is selected from the thermal hysteresis compensation parameters; The intermediate temperature drift correction coefficient is adjusted based on the hysteresis correction amount to obtain the target temperature drift correction coefficient; Based on the target temperature drift correction coefficient, the zero-point offset, the amplitude deviation, and the phase deviation are corrected by temperature compensation to obtain the target calibration parameters.

7. The motor rotor position sensor calibration method according to claim 1, characterized in that, After storing the target calibration parameters in a non-volatile memory associated with the target motor, the motor rotor position sensor calibration method further includes: During the operation of the target motor, the real-time speed and real-time torque of the target motor are acquired; Based on the real-time speed and the real-time torque, the current operating condition category of the target motor is determined; Based on the operating condition category, the segmented compensation correction coefficient corresponding to the operating condition category is retrieved from the non-volatile memory; The target calibration parameters are adjusted according to the segmented compensation correction coefficient to obtain the dynamic calibration parameters under the current operating conditions, so as to adapt to different operating conditions when compensating the detection results of the motor rotor position sensor.

8. A motor rotor position sensor calibration device, characterized in that, The motor rotor position sensor calibration device, applied to the target motor, includes: The data acquisition unit is used to control the target motor to move in an open-loop manner within a preset motion range, and to acquire the original signal sequence output by the rotor position sensor installed on the target motor. The feature extraction unit is used to extract waveform features from the original signal sequence to obtain signal feature information of the rotor position sensor, wherein the signal feature information includes at least one of zero offset, amplitude deviation and phase deviation. The parameter determination unit is used to determine the target calibration parameters for compensating for the installation error and temperature influence of the rotor position sensor based on the ambient temperature detection value of the target motor and the signal characteristic information. A parameter storage unit is used to store the target calibration parameters in a non-volatile memory associated with the target motor, so that the target motor can compensate for the detection results of the motor rotor position sensor based on the target calibration parameters during operation.

9. An electronic device, comprising: The memory and processor are characterized in that the processor, when executing a computer program stored in the memory, implements the steps of the motor rotor position sensor calibration method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon computer-executable instructions or a computer program, characterized in that, When the computer-executable instructions or the computer program are executed by a processor, the steps of the motor rotor position sensor calibration method as described in any one of claims 1 to 7 are implemented.

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