A motor starting control method and device, electronic equipment and storage medium

Abstract

The application discloses a motor starting control method and device, electronic equipment and storage medium, and relates to the technical field of motor control. The method comprises the following steps: collecting the current rotating speed and the initial rotating speed instruction of a motor, calculating the sliding average change rate of the actual rotating speed based on different time scales; obtaining the deviation between the initial rotating speed instruction and the sliding average change rate under different time scales, performing weighted fusion processing on the deviation to obtain a starting hysteresis quantization index; generating a rotating speed guide compensation instruction according to the starting hysteresis quantization index; estimating the moment of inertia and the damping coefficient of the motor based on the collection period and the current rotating speed, and adaptively updating the rotating speed guide compensation instruction by using the moment of inertia; superimposing the initial rotating speed instruction and the updated rotating speed guide compensation instruction to obtain a target rotating speed instruction; and performing starting control on the motor based on the target rotating speed instruction. The application can be applied to an energy-saving air conditioner and can enhance the control effect of the motor during the starting process.

Description

Technical Field

[0001] This invention relates to the field of motor control technology, and in particular to a motor starting control method, device, electronic equipment, and storage medium. Background Technology

[0002] Permanent magnet synchronous motors (PMSMs) possess outstanding advantages such as high operating efficiency, high power density, and excellent dynamic control performance, and are now widely used in industrial transmission equipment, new energy vehicles, rail transit equipment, large motor units, and air conditioner compressors. Among these, air conditioner scroll compressors, large industrial compressors, fluid transfer pumps, and industrial robot joints are typical high-inertia load systems, and PMSMs used in these devices face significant control challenges during the low-speed start-up phase.

[0003] At the initial startup of the motor, the speed gradually increases from zero. The rate of change of the speed loop command is much greater than the response speed of the actual motor speed. This directly leads to a significant dynamic response mismatch between the outer speed loop and the inner current loop. To quickly eliminate the speed tracking deviation, the speed loop PI regulator continuously outputs an excessively high q-axis current command. The inner current loop quickly tracks this command, ultimately causing a sharp increase in the q-axis current and resulting in a large overshoot. Once the current overshoot amplitude exceeds the overcurrent protection threshold of the driver hardware, the system will immediately trigger a protective shutdown, causing startup failure and significantly reducing the operational reliability and overall availability of high-inertia PMSM drive equipment such as air conditioners and large compressors.

[0004] Current mainstream PMSM start-up control schemes mainly rely on smooth open-loop / closed-loop switching and pre-set S-shaped or sinusoidal speed command curves to mitigate start-up current surges. However, these methods are all passive buffering strategies and cannot fundamentally solve the core problem of dual-loop dynamic response mismatch. Some technical solutions suppress current overshoot by reducing the proportional gain of the speed loop and extending the integral time constant, sacrificing dynamic response speed for start-up safety. This directly results in slow motor acceleration and severe tracking lag, making them unsuitable for air conditioners and industrial drive scenarios with high precision and response speed requirements. Meanwhile, the parameters of existing control algorithms are mostly factory-calibrated values, lacking the ability to online perceive and adaptively correct real-time inertial characteristics of the system. When facing variable operating conditions such as changing air conditioner loads, changing pump flow rates, and changing robot loads, the control adaptability is poor, easily leading to excessive start-up surges or slow start-up.

[0005] In summary, the industry urgently needs a PMSM low-speed start control scheme that can actively identify the dynamic hysteresis characteristics of the motor during the start-up phase and has adaptive compensation capabilities. This scheme should avoid start-up overcurrent faults and ensure equipment operation safety without sacrificing motor start-up speed and dynamic response performance, thereby comprehensively improving the start-up success rate and long-term operational stability of air conditioner compressors and various high-inertia electromechanical equipment. Summary of the Invention

[0006] This invention provides a motor starting control method, device, electronic device, and storage medium, aiming to achieve intelligent suppression of the low-speed starting process of a permanent magnet synchronous motor and enhance the starting control effect of the motor.

[0007] In a first aspect, embodiments of the present invention provide a motor starting control method, comprising: The current speed and initial speed command of the motor are periodically collected, and the moving average rate of change of the actual speed is calculated based on multiple preset time scales. The deviation between the initial speed command and the moving average rate of change at different time scales is obtained, and the deviation is weighted and fused to obtain the start-up hysteresis quantification index. Generate speed guidance compensation command based on the aforementioned start-up hysteresis quantification index; Based on the acquisition cycle and the current speed, the moment of inertia and damping coefficient of the motor are estimated in real time, and the moment of inertia is used to adaptively update the speed guidance compensation command. The initial speed command is superimposed with the updated speed guidance compensation command to obtain the target speed command; The motor is started based on the target speed command.

[0008] Secondly, embodiments of the present invention provide a motor starting control device, comprising: The data acquisition unit is used to periodically acquire the current speed and initial speed command of the motor, and calculate the moving average rate of change of the actual speed based on multiple preset time scales. The deviation fusion unit is used to obtain the deviation between the initial speed command and the moving average rate of change at different time scales, and to perform weighted fusion processing on the deviation to obtain the start-up hysteresis quantification index. The compensation generation unit is used to generate a speed guidance compensation command based on the start-up hysteresis quantification index. The instruction update unit is used to estimate the moment of inertia and damping coefficient of the motor in real time based on the acquisition cycle and the current speed, and to adaptively update the speed guidance compensation instruction using the moment of inertia. The instruction superposition unit is used to superimpose the initial speed instruction and the updated speed guidance compensation instruction to obtain the target speed instruction; A start control unit is used to start the motor based on the target speed command.

[0009] Thirdly, embodiments of the present invention provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the motor start control method as described in the first aspect.

[0010] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the motor start control method as described in the first aspect.

[0011] This invention provides a motor starting control method, device, electronic device, and storage medium. The method includes periodically acquiring the current speed and initial speed command of the motor, and calculating the moving average rate of change of the actual speed based on multiple preset time scales; obtaining the deviation between the initial speed command and the moving average rate of change at different time scales, and performing weighted fusion processing on the deviation to obtain a starting hysteresis quantification index; generating a speed guidance compensation command based on the starting hysteresis quantification index; estimating the moment of inertia and damping coefficient of the motor in real time based on the acquisition period and the current speed, and adaptively updating the speed guidance compensation command using the moment of inertia; superimposing the initial speed command and the updated speed guidance compensation command to obtain a target speed command; and performing starting control of the motor based on the target speed command. This invention quantifies the dynamic hysteresis characteristics of the motor startup process across multiple time scales, transforming previously ignored system dynamic delays into usable control information. Based on this, it proactively generates speed guidance compensation commands to pre-adjust the motor speed, fundamentally improving the dynamic response mismatch between the speed loop and current loop. This avoids the risk of startup failure due to severe current overshoot triggering hardware overcurrent protection. Simultaneously, this invention also identifies the system's moment of inertia and damping coefficient in real time, adaptively correcting the compensation commands based on the actual load inertia state. This overcomes the limitations of fixed parameters in traditional solutions, significantly improving the robustness of the control strategy and adapting to the startup control requirements of various complex variable load conditions. While ensuring motor startup safety, this invention does not sacrifice startup speed or dynamic response performance, achieving intelligent suppression of the low-speed startup process of permanent magnet synchronous motors. This effectively improves the startup success rate and operational stability of permanent magnet synchronous motors with large inertia loads, optimizing the overall startup control effect of the motor. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating a motor starting control method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the first sub-process in a motor starting control method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the second sub-process in a motor starting control method provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the third sub-process in a motor starting control method provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the fourth sub-process in a motor starting control method provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the fifth sub-process in a motor starting control method provided in an embodiment of the present invention; Figure 7 This is a block diagram of a dual closed-loop control for a permanent magnet synchronous motor in the prior art; Figure 8 This is a starting control block diagram of a motor starting control method provided in an embodiment of the present invention; Figure 9 This is another schematic flowchart of a motor starting control method provided in an embodiment of the present invention; Figure 10 A test comparison diagram of a motor starting control method provided in an embodiment of the present invention; Figure 11 A schematic block diagram of a motor starting control device provided in an embodiment of the present invention; Figure 12 This is a first sub-schematic block diagram of a motor starting control device provided in an embodiment of the present invention; Figure 13 This is a second schematic block diagram of a motor starting control device provided in an embodiment of the present invention; Figure 14 This is a schematic block diagram of a third sub-section of a motor starting control device provided in an embodiment of the present invention; Figure 15 This is a fourth schematic block diagram of a motor starting control device provided in an embodiment of the present invention; Figure 16This is a fifth schematic block diagram of a motor starting control device provided in an embodiment of the present invention; Figure 17 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0016] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0017] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0018] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0019] Please see below. Figure 1 The present invention provides a motor starting control method, specifically including steps S101 to S106.

[0020] Step S101: Periodically collect the current speed and initial speed command of the motor, and calculate the moving average rate of change of the actual speed based on multiple preset time scales. Step S102: Obtain the deviation between the initial speed command and the moving average rate of change at different time scales, and perform weighted fusion processing on the deviation to obtain the start-up hysteresis quantification index. Step S103: Generate a speed guidance compensation command based on the startup hysteresis quantification index; Step S104: Based on the acquisition period and the current speed, estimate the moment of inertia and damping coefficient of the motor in real time, and use the moment of inertia to adaptively update the speed guidance compensation command; Step S105: Superimpose the initial speed command with the updated speed guidance compensation command to obtain the target speed command; Step S106: Perform start control on the motor based on the target speed command.

[0021] In this embodiment, the current speed and initial speed command of the motor are first collected periodically, and the moving average rate of change of the actual speed is calculated at multiple different time scales. Then, the deviation between the initial speed command and the moving average rate of change at each time scale is calculated, and the deviations are weighted and fused to obtain the start-up hysteresis quantification index. The speed guidance compensation command is generated based on the start-up hysteresis quantification index. Then, the motor's moment of inertia and damping coefficient are estimated in real time by combining the collection period and the current speed, and the speed guidance compensation command is updated adaptively using the moment of inertia. Finally, the initial speed command and the updated compensation command are superimposed to obtain the final target speed command, thereby completing the motor start-up control through the target speed command.

[0022] This embodiment quantifies the dynamic hysteresis characteristics of the motor startup process across multiple time scales, transforming previously ignored system dynamic delays into usable control information. Based on this, it proactively generates speed guidance compensation commands to pre-adjust the motor speed, fundamentally improving the dynamic response mismatch between the speed loop and current loop. This avoids the risk of startup failure caused by severe current overshoot triggering hardware overcurrent protection. Simultaneously, this embodiment also identifies the system's moment of inertia and damping coefficient in real time, adaptively correcting the compensation commands based on the actual load inertia state. This overcomes the limitations of fixed parameters in traditional solutions, significantly improving the robustness of the control strategy and adapting to the startup control requirements of various complex variable load conditions. While ensuring motor startup safety, this embodiment does not sacrifice startup speed or dynamic response performance, achieving intelligent suppression of the low-speed startup process of permanent magnet synchronous motors. This effectively improves the startup success rate and operational stability of permanent magnet synchronous motors with large inertia loads, optimizing the overall startup control effect of the motor.

[0023] like Figure 7As shown, traditional PMSMs employ a speed-current dual closed-loop control architecture. The outer loop is the speed loop, where a PI controller outputs the q-axis current reference value iq*. The inner loop is the current loop, enabling rapid tracking of the d-axis and q-axis current reference commands id* and iq*. This control architecture exhibits excellent performance under steady-state motor operation, but it is prone to dynamic response mismatch between the speed loop and the current loop when facing the starting conditions of motors with large inertia loads. This can lead to current overshoot, and in severe cases, cause motor starting failure.

[0024] Figure 8 This is the block diagram of the PMSM low-speed start suppression control proposed in this embodiment. Based on the traditional field-oriented control (FOC) architecture, this embodiment adds a multi-scale dynamic sensing module and an adaptive nonlinear guidance module. The system collects the current motor speed ω(k) and speed command ω. ref (k), calculates the rate of change of rotational speed on three time scales: fast, medium, and slow, and outputs the quantification index of start-up hysteresis Ψ(k), where Ψ s After discretization, Ψ(k) is obtained; this quantization index is then fed into a Sigmoid-type compensation function to generate the rotational speed guidance command ω. guid (k). Simultaneously, the online parameter identification module estimates the system's moment of inertia J and damping coefficient B in real time, dynamically adjusting the compensation gain λ; finally, the original velocity command and the guiding command are superimposed to obtain the fused total velocity command ω. ref total (k) = ω ref (k) + ω guid (k) is used as the input reference for the speed loop to achieve active guidance and impact suppression during the motor starting process.

[0025] The algorithm execution flow in this embodiment is as follows: Figure 9 As shown, the system first samples and acquires the three-phase currents ia(k), ib(k), and ic(k), and performs coordinate transformation processing through Clark transformation and Park transformation; then it calculates the three-scale rotational speed change rate and obtains the quantitative index Ψ(k); the parameter identification module estimates the real-time inertia J(k) and damping coefficient B(k), and updates the compensation gain λ(k) accordingly; finally, it calculates the rotational speed guidance command ω by combining Ψ(k) and λ(k). guid (k); will ω guid (k) superimposed on the original velocity command ω ref (k), to obtain the compensated desired rotational speed ω ref total (k) completes the speed loop reference value update.

[0026] The above algorithm is executed cyclically in each control sampling cycle, forming a closed-loop adaptive control. Therefore, the PMSM low-speed start-up suppression method based on multi-scale dynamic sensing and adaptive nonlinear guidance proposed in this embodiment constructs an integrated control architecture of "sensing-evaluation-guidance-adaptation," which can effectively solve the dual-loop dynamic response mismatch problem existing in the start-up phase of large-inertia PMSMs.

[0027] Furthermore, the motor start-up control method provided in this embodiment can be applied to energy-saving air conditioners, especially suitable for the drive control scenarios of large-inertia scroll compressors inside air conditioners. Addressing the application characteristics of frequent compressor starts and stops and dynamic load changes with ambient temperature, this embodiment can suppress current surges during the low-speed compressor start-up phase, reduce start-up overcurrent faults, and lower the electrical stress on power devices. While ensuring rapid compressor start-up response, it not only improves the overall operational reliability of the air conditioner but also helps improve the operating energy efficiency of the air conditioning system, meeting the design and development requirements of energy-saving air conditioners.

[0028] In one embodiment, step S101 includes: The number of sampling points at different time scales is calculated based on preset fast-scale time windows, medium-scale time windows, and slow-scale time windows, combined with the sampling period, current rotation speed, and initial rotation speed command; wherein, the fast-scale time window, medium-scale time window, and slow-scale time window increase sequentially. The moving average rate of change at different time scales is calculated based on the number of sampling points at different time scales.

[0029] In this embodiment, to address the multi-dimensional dynamic changes in motor speed during the startup phase, three types of time windows of varying lengths are used for sliding calculations. The short, fast-scale window captures the instantaneous speed increase at the initial startup moment, while the long, slow-scale window reflects the slow, hysteretic evolution of speed caused by a large inertial load, overcoming the limitation of a single time window in fully characterizing the system's dynamic hysteresis. This yields multiple sets of speed change rates covering both instantaneous rapid changes and long-term slow evolution, providing multi-dimensional feature support for subsequent accurate quantification of system startup hysteresis. Specifically, during the multi-scale speed change rate calculation, the system collects the current motor speed ω(k) and speed command ω in real-time with a sampling period (Ts). ref (k), solve for the moving average rate of change at each scale: fast scale (τ1=10ms), medium scale (τ2=100ms), and slow scale (τ3=1s). ; ; ; in, This represents the rate of change of the moving average over a fast time scale. This represents the moving average rate of change over a medium time scale. The moving average rate of change represents the moving average over a slow time scale, N1 = τ1 / Ts, N2 = τ2 / Ts, and N3 = τ3 / Ts. Additionally, k is the current discrete sampling time; ki is the historical sampling time i steps backward from the current time k; and ki-1 is the sampling time immediately preceding ki.

[0030] In one embodiment, such as Figure 2 As shown, step S102 includes steps S201 to S203.

[0031] Step S201: Set weighting coefficients for different time scales; Step S202: Calculate the absolute value of the deviation between the initial speed command and the moving average rate of change at each time scale; Step S203: Based on the weighting coefficients, the absolute values ​​of each deviation are weighted and summed to obtain the startup hysteresis quantification index.

[0032] In this embodiment, independent weighting coefficients are configured for the calculation results at different time scales (fast, medium, and slow). This allows for differentiated weighting of dynamic mismatch components at different time dimensions, effectively highlighting the long-cycle slow hysteresis effect caused by large inertia loads while suppressing ineffective interference from momentary small speed fluctuations during startup. The resulting startup hysteresis quantification index objectively and accurately characterizes the true dynamic hysteresis level during motor startup, providing a reliable quantitative evaluation basis for subsequent speed guidance compensation commands and effectively avoiding the defects of insufficient or excessive compensation caused by inaccurate hysteresis evaluation. Specifically, when generating the startup hysteresis quantification index Ψ(k), the quantification index can be constructed based on the speed change rate obtained from the aforementioned three time scales, and the calculation formula is as follows: ; The weighting coefficients α=0.4, β=0.35, and γ=0.25 are obtained through offline simulation combined with the experience of engineering experts. These parameters can take into account the contribution of different time scales, fast and slow, to the dynamic mismatch of the system.

[0033] In one embodiment, such as Figure 3 As shown, step S103 includes steps S301 to S303.

[0034] Step S301: Construct a nonlinear compensation function using the hyperbolic tangent function; Step S302: Set the maximum compensation amplitude of the nonlinear compensation function based on the rated speed of the motor; Step S303: Set the adjustment gain for the start-up hysteresis quantification index, and use the nonlinear compensation function to calculate the start-up hysteresis quantification index to obtain the speed guidance compensation command.

[0035] This embodiment utilizes the hyperbolic tangent function to construct a Sigmoid-type nonlinear compensation mapping relationship. The compensation output adaptively changes according to the magnitude of the start-up hysteresis quantification index. Simultaneously, a maximum compensation amplitude is configured to constrain the upper limit of the compensation output, effectively preventing excessive compensation output from causing speed overshoot. When the system hysteresis is high, sufficient compensation can be output to achieve effective speed guidance; when the system hysteresis is low, the compensation effect is automatically weakened to avoid overcompensation slowing down the motor start-up speed, thus balancing safety constraints and rapid response requirements during motor start-up.

[0036] When generating adaptive nonlinear guidance instructions, the Sigmoid type compensation function can be designed according to the following formula: ; Where δ is the maximum compensation amplitude, which can be set to 10% of the motor's rated speed, and is used to limit the upper limit of the output of the speed-guided compensation command; λ is the adjustment gain, used to control the response sensitivity of nonlinear compensation; Ψ(k) is the starting hysteresis quantification index output by the preceding steps.

[0037] In one embodiment, such as Figure 4 As shown, step S104 includes steps S401 to S403.

[0038] Step S401: Obtain rotational speed data for multiple sampling periods and the corresponding initial rotational speed command; Step S402: Based on the rotational speed data and the corresponding initial rotational speed command, the recursive least squares method is invoked to estimate the moment of inertia and mechanical time constant of the motor in real time; Step S403: Calculate the damping coefficient based on the moment of inertia and mechanical time constant.

[0039] This embodiment employs the recursive least squares method to achieve online real-time identification of rotational inertia, mechanical time constant, and damping coefficient. No additional hardware detection devices are required; the parameters can be solved solely based on the speed and current-related operating data collected during motor control. The algorithm has low computational complexity and is easy to implement in engineering. Parameter updates can be completed within each control sampling cycle, enabling real-time tracking of the actual characteristics of the current load condition and providing reliable parameter input for subsequent adaptive adjustment of compensation gain. Specifically, during online parameter identification and gain pre-calculation, the recursive least squares identification module is activated to estimate the system's rotational inertia J and damping coefficient B in real time. The corresponding calculation formulas are as follows: ; ; in, T is the system rotational inertia identified at the k-th sampling time; s M represents the system sampling period; M represents the number of historical sampling data points used in the identification calculation. Let be the system damping coefficient at the k-th sampling time; is the mechanical time constant identified at the k-th sampling time; avg(·) is the averaging operation; ω(k) is the actual speed of the motor at the current time; iq*(k) is the q-axis current reference command.

[0040] Furthermore, such as Figure 5 As shown, step S104 further includes steps S501 to S503.

[0041] Step S501: Obtain the preset reference moment of inertia, lower limit of gain, upper limit of gain, and inertia adjustment coefficient; Step S502: Call the mapping function to map the real-time estimated moment of inertia to a new adjustment gain of the start-up hysteresis quantification index; wherein, the parameters of the mapping function include the reference moment of inertia, the lower limit of gain, the upper limit of gain, and the inertia adjustment coefficient; Step S503: Adaptively update the speed guidance compensation command using the new adjustment gain.

[0042] In this embodiment, the larger the system's moment of inertia, the more significant the hysteresis effect exhibited during the motor's startup phase, and the corresponding compensation intensity should also be increased. This embodiment, based on the real-time moment of inertia identified online, uses a mapping function to dynamically map and correct the adjustment gain, enabling the compensation intensity to adaptively change with the actual magnitude of the load inertia. This effectively improves the control algorithm's adaptability to various load conditions and solves the technical defects of insufficient compensation for large-inertia loads and excessive compensation for small-inertia loads under fixed-gain mode. The calculation formula for dynamically updating the adjustment gain λ(k) is as follows: ; The reference moment of inertia can be set to J0 = 1.5 kg·m. 2 The inertia adjustment coefficient η = 0.5, the lower limit of gain λ_min = 0.1, and the upper limit of gain λ_max = 2.0.

[0043] Based on this, the initial speed command can be superimposed with the adaptively updated speed guidance compensation command to output the target speed command. The specific calculation expression is as follows: ; The target speed command is used as a new input reference value for the speed loop and sent to the speed loop controller to drive the motor to start, thereby achieving active suppression of current overshoot during the startup process.

[0044] In one embodiment, such as Figure 6 As shown, the motor start control method further includes steps S601 to S604.

[0045] Step S601: Collect the three-phase current of the motor; Step S602: Perform Clark transformation and Park transformation on the three-phase current in sequence to obtain the actual q-axis current; Step S603: Compare the real-time peak current corresponding to the actual current of the q-axis with the preset peak current threshold to obtain the peak current comparison result; Step S604: Dynamically adjust the adjustment gain based on the peak current comparison result.

[0046] This embodiment also introduces a closed-loop feedback mechanism for q-axis current peak, which monitors the actual peak current of the motor's q-axis in real time. When the detected peak current approaches a preset protection threshold, the adjustment gain is dynamically increased to enhance the strength of nonlinear compensation and further suppress the current rise trend. When the peak current is far below the protection threshold, the adjustment gain is appropriately reduced to decrease the constraint of compensation on speed climb and fully ensure the motor's starting response speed. This method adds current feedback closed-loop constraints to the original inertia identification adaptive adjustment, forming a dual protection mechanism to further improve the operational safety of the entire motor starting process and avoid the risk of hardware protection being triggered due to overcurrent during startup.

[0047] After completing the above-mentioned closed-loop feedback regulation of the current, the system continuously monitors the operating status of the motor speed and current, iteratively updates the identification parameters and speed compensation commands, and ensures that the motor can achieve efficient, safe and fast start-up and operation under various loads and complex working conditions.

[0048] In practical applications, to verify the effectiveness of the PMSM low-speed start-up control method based on multi-scale dynamic sensing and adaptive nonlinear guidance proposed in this embodiment, the same large inertia simulation condition was set up, namely, rotational inertia J = 2.0 kg·m. 2 At a rated speed of 1500 rpm, a comparative simulation was conducted between the traditional PI control strategy and the method proposed in this embodiment. The simulation results are as follows: Figure 10 As shown in the figure, the upper subplot is a comparison curve of rotational speed response, and the lower subplot is a comparison curve of q-axis current suppression effect.

[0049] Depend on Figure 10As shown in the sub-figure above: the traditional PI control strategy, corresponding to the blue dashed curve, exhibits a situation where, during the initial startup phase of a large inertia system, the rate of change of the speed loop command is far greater than the response speed of the actual motor speed. This leads to rapid saturation of the speed loop integral term, resulting in a drastically changing current reference value and significant speed overshoot and oscillation problems. Not only is the maximum speed tracking error large, but the system also takes longer to return to steady state. Especially after applying a load disturbance at t=1.0s, the speed under traditional PI control drops significantly, and the speed recovery process is accompanied by low-frequency oscillations, fully demonstrating the insufficient dynamic robustness of this control scheme. In contrast, the method in this embodiment, corresponding to the red solid curve, relies on a multi-scale dynamic sensing module to quantify the system's dynamic hysteresis Ψ(k) in real time, and combines this with an adaptive gain λ to generate a smooth, nonlinear guiding command ω. guid (k); This guiding command effectively compensates for the dynamic response mismatch between the speed loop and the current loop, allowing the actual motor speed to rise smoothly along an approximately S-shaped trajectory. Simulation results show that the method in this embodiment has no overshoot or oscillation throughout the startup process; when encountering load disturbances, the system can recover to the set speed in a very short time (less than 0.2 s), significantly improving the system's dynamic response capability and anti-disturbance performance.

[0050] Figure 10 The sub-figures below show the q-axis current waveforms corresponding to the two control strategies. Traditional PI control experiences significant speed deviations at startup, resulting in a very high q-axis current reference value output by the PI controller. Simulations show that the peak current of traditional PI control reaches 2.50 A (blue box in the figure), exceeding the hardware's preset overcurrent protection threshold (green dashed line, 1.5 pu). This severe current surge triggers the driver's overcurrent protection, directly causing motor startup failure, and also inflicts severe stress damage on power devices. In contrast, the control method provided in this embodiment utilizes multi-scale sensing for feedforward guidance, actively constraining the current change rate during the startup phase. Simulations show that the peak current is controlled at 1.10 A (red box in the figure), significantly lower than the 1.5 pu protection threshold, remaining within a safe operating range. Furthermore, the current rise time is smooth throughout the startup process, without drastic fluctuations, thus verifying that the method in this embodiment effectively suppresses startup shocks and ensures safe and reliable system operation.

[0051] In summary, the core features of this embodiment are as follows: A multi-scale dynamic sensing mechanism is proposed, constructing rotational speed change rate characteristics at three time scales: fast (10ms), medium (100ms), and slow (1s). Weighted fusion is used to generate a quantifiable start-up hysteresis index Ψ(k), transforming the system's dynamic delay characteristics into a quantifiable and calculable control input. An adaptive nonlinear guidance compensation function is designed, employing a Sigmoid-type nonlinear function to generate the guidance command ω. guid(k) The gain λ of this function is dynamically adjusted by the system inertia J and damping coefficient B obtained online, which can achieve the intelligent response effect of "strong compensation for large inertia and weak compensation for small inertia"; an online parameter identification and adaptive adjustment closed loop is constructed, and the system inertia J and mechanical time constant τ are estimated in real time by relying on the recursive least squares method. m The gain λ is dynamically updated, enabling the control strategy to adapt to different operating conditions and improve control robustness.

[0052] Compared with the prior art, this embodiment has the following outstanding advantages: (1) Construct a multi-scale dynamic sensing model and use the moving average change rate of three time scales (fast (10ms), medium (100ms), and slow (1s)) to quantify the speed response hysteresis during motor start-up in all aspects, generate a quantitative index Ψ(k) with physical meaning, and realize accurate perception of system dynamic response mismatch. (2) Design a Sigmoid-type nonlinear compensation function to convert the hysteresis sensing results into a dynamically adjustable speed guidance command ω. guid (k) forms a closed-loop control logic of "perception-evaluation-guidance" to improve the intelligence level of the control strategy; (3) Set up an online parameter identification module, estimate the system inertia J and damping coefficient B in real time based on the recursive least squares method, dynamically correct the compensation gain λ, complete the adaptive adjustment of control parameters, and greatly improve the system's adaptability to different load conditions. (4) The entire control strategy is implemented entirely by software algorithms, without the need for additional hardware components, and has excellent engineering portability and practical application value; (5) Without sacrificing the motor starting speed, it effectively suppresses the current overshoot phenomenon during the starting stage and improves the motor starting success rate. It is especially suitable for applications in industrial and transportation equipment scenarios with high reliability requirements.

[0053] This embodiment can be adapted to various high-inertia PMSM drive systems, such as compressors, water pumps, elevator traction machines, industrial robot joints, and other equipment, and has broad engineering application prospects.

[0054] Figure 11 This is a schematic block diagram of a motor starting control device 1100 provided in an embodiment of the present invention. The device 1100 includes: The data acquisition unit 1101 is used to periodically acquire the current speed and initial speed command of the motor, and calculate the moving average rate of change of the actual speed based on multiple preset time scales. The deviation fusion unit 1102 is used to obtain the deviation between the initial speed command and the moving average rate of change at different time scales, and to perform weighted fusion processing on the deviation to obtain the start-up hysteresis quantification index. The compensation generation unit 1103 is used to generate a speed guidance compensation command based on the start-up hysteresis quantification index; The instruction update unit 1104 is used to estimate the moment of inertia and damping coefficient of the motor in real time based on the acquisition period and the current speed, and to adaptively update the speed guidance compensation instruction using the moment of inertia. The instruction superposition unit 1105 is used to superimpose the initial speed instruction and the updated speed guidance compensation instruction to obtain the target speed instruction; The start control unit 1106 is used to start the motor based on the target speed command.

[0055] In one embodiment, the data acquisition unit 1101 includes: The sampling point calculation unit is used to calculate the number of sampling points at different time scales according to preset fast-scale time windows, medium-scale time windows, and slow-scale time windows, combined with the sampling period, current rotation speed, and initial rotation speed command; wherein the fast-scale time window, medium-scale time window, and slow-scale time window increase in size sequentially. The rate of change calculation unit is used to calculate the moving average rate of change at different time scales based on the number of sampling points at different time scales.

[0056] In one embodiment, such as Figure 12 As shown, the deviation fusion unit 1102 includes: The coefficient setting unit 1201 is used to set weight coefficients for different time scales; The deviation calculation unit 1202 is used to calculate the absolute value of the deviation between the initial speed command and the sliding average rate of change at each time scale; The deviation weighting unit 1203 is used to perform a weighted summation of the absolute values ​​of each deviation based on the weight coefficients to obtain the start-up hysteresis quantification index.

[0057] In one embodiment, such as Figure 13 As shown, the compensation generation unit 1103 includes: Function building unit 1301 is used to construct a nonlinear compensation function using the hyperbolic tangent function; The amplitude setting unit 1302 is used to set the maximum compensation amplitude of the nonlinear compensation function based on the rated speed of the motor; The gain setting unit 1303 is used to set the adjustment gain of the start-up hysteresis quantification index and to calculate the start-up hysteresis quantification index using the nonlinear compensation function to obtain the speed guidance compensation command.

[0058] In one embodiment, such as Figure 14As shown, the instruction update unit 1104 includes: The instruction acquisition unit 1401 is used to acquire rotational speed data for multiple sampling cycles and the corresponding initial rotational speed instruction; The real-time estimation unit 1402 is used to estimate the moment of inertia and mechanical time constant of the motor in real time by calling the recursive least squares method based on the rotational speed data and the corresponding initial rotational speed command. The damping calculation unit 1403 is used to calculate the damping coefficient based on the moment of inertia and mechanical time constant.

[0059] In one embodiment, such as Figure 15 As shown, the instruction update unit 1104 further includes: The preset acquisition unit 1501 is used to acquire preset reference moment of inertia, lower limit of gain, upper limit of gain, and inertia adjustment coefficient; Gain mapping unit 1502 is used to call a mapping function to map the real-time estimated moment of inertia to a new adjustment gain of the start-up hysteresis quantification index; wherein, the parameters of the mapping function include the reference moment of inertia, lower gain limit, upper gain limit, and inertia adjustment coefficient; The adaptive update unit 1503 is used to adaptively update the speed guidance compensation command using the new adjustment gain.

[0060] In one embodiment, such as Figure 16 As shown, the motor start control device 1100 further includes: The current acquisition unit 1601 is used to acquire the three-phase current of the motor; The current transformation unit 1602 is used to sequentially perform Clark transformation and Park transformation on the three-phase current to obtain the actual q-axis current. The peak comparison unit 1603 is used to compare the real-time peak current corresponding to the actual current of the q-axis with a preset current peak threshold to obtain the peak current comparison result. The gain adjustment unit 1604 is used to dynamically adjust the adjustment gain based on the peak current comparison result.

[0061] The aforementioned motor starting control device can be implemented as a computer program, which can, for example... Figure 17 It runs on the electronic device shown.

[0062] Please see Figure 17 , Figure 17 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention. The electronic device 1700 is a device with both wireless and wired communication capabilities.

[0063] See Figure 17The electronic device 1700 includes a processor 1702, a memory, and a network interface 1705 connected via a device bus 1701. The memory may include a non-volatile storage medium 1703 and internal memory 1704.

[0064] The non-volatile storage medium 1703 can store the operating device 17031 and the computer program 17032. When the computer program 17032 is executed, it causes the processor 1702 to execute a motor starting control method.

[0065] The processor 1702 provides computing and control capabilities to support the operation of the entire electronic device 1700.

[0066] The internal memory 1704 provides an environment for the execution of the computer program 17032 in the non-volatile storage medium 1703. When the computer program 17032 is executed by the processor 1702, the processor 1702 can execute a motor start control method.

[0067] This network interface 1705 is used for network communication with other devices. Those skilled in the art will understand that... Figure 17 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the electronic device 1700 to which the present invention is applied. The specific electronic device 1700 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0068] The processor 1702 is used to run a computer program 17032 stored in a memory to implement any embodiment of the above-described motor start control method.

[0069] It should be understood that, in this embodiment of the invention, the processor 1702 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0070] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer device to implement the process steps of the embodiments of the above methods.

[0071] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program. When executed by a processor, the computer program causes the processor to perform any embodiment of the above-described motor start control method.

[0072] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0073] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0074] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0075] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0076] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0077] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0078] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Since these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0079] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A motor starting control method, characterized in that, include: The current speed and initial speed command of the motor are periodically collected, and the moving average rate of change of the actual speed is calculated based on multiple preset time scales. The deviation between the initial speed command and the moving average rate of change at different time scales is obtained, and the deviation is weighted and fused to obtain the start-up hysteresis quantification index. Generate speed guidance compensation command based on the aforementioned start-up hysteresis quantification index; Based on the acquisition cycle and the current speed, the moment of inertia and damping coefficient of the motor are estimated in real time, and the moment of inertia is used to adaptively update the speed guidance compensation command. The initial speed command is superimposed with the updated speed guidance compensation command to obtain the target speed command; The motor is started based on the target speed command.

2. The motor starting control method according to claim 1, characterized in that, The periodic acquisition of the motor's current speed and initial speed command, and the calculation of the moving average rate of change of the actual speed based on multiple preset time scales, include: The number of sampling points at different time scales is calculated based on preset fast-scale time windows, medium-scale time windows, and slow-scale time windows, combined with the sampling period, current rotation speed, and initial rotation speed command; wherein, the fast-scale time window, medium-scale time window, and slow-scale time window increase sequentially. The moving average rate of change at different time scales is calculated based on the number of sampling points at different time scales.

3. The motor starting control method according to claim 1, characterized in that, The step involves obtaining the deviation between the initial speed command and the moving average rate of change at different time scales, and then performing a weighted fusion process on the deviation to obtain a startup hysteresis quantification index, including: Weighting coefficients are set for different time scales; Calculate the absolute value of the deviation between the initial speed command and the moving average rate of change at each time scale; Based on the weighting coefficients, the absolute values ​​of each deviation are weighted and summed to obtain the quantification index of startup hysteresis.

4. The motor starting control method according to claim 1, characterized in that, The step of generating a speed guidance compensation command based on the start-up hysteresis quantification index includes: A nonlinear compensation function is constructed using the hyperbolic tangent function; The maximum compensation amplitude is set for the nonlinear compensation function based on the rated speed of the motor. An adjustment gain is set for the start-up hysteresis quantification index, and the nonlinear compensation function is used to calculate the start-up hysteresis quantification index to obtain the speed guidance compensation command.

5. The motor starting control method according to claim 1, characterized in that, The process of estimating the motor's moment of inertia and damping coefficient in real time based on the acquisition period and current speed, and adaptively updating the speed guidance compensation command using the moment of inertia, includes: Acquire rotational speed data for multiple sampling periods and the corresponding initial rotational speed command; Based on the speed data and the corresponding initial speed command, the recursive least squares method is invoked to estimate the moment of inertia and mechanical time constant of the motor in real time; The damping coefficient is calculated based on the moment of inertia and mechanical time constant.

6. The motor starting control method according to claim 4, characterized in that, The method of estimating the moment of inertia and damping coefficient of the motor in real time based on the acquisition period and the current speed, and adaptively updating the speed guidance compensation command using the moment of inertia, further includes: Obtain the preset reference moment of inertia, lower limit of gain, upper limit of gain, and inertia adjustment coefficient; The mapping function is invoked to map the real-time estimated moment of inertia to a new adjustment gain of the start-up hysteresis quantification index; wherein the parameters of the mapping function include the reference moment of inertia, the lower limit of gain, the upper limit of gain, and the inertia adjustment coefficient; The speed guidance compensation command is adaptively updated using a new adjustment gain.

7. The motor starting control method according to claim 4, characterized in that, Also includes: Collect the three-phase current of the motor; The three-phase currents are sequentially subjected to Clark transformation and Park transformation to obtain the actual q-axis current; The real-time peak current corresponding to the actual current of the q-axis is compared with the preset peak current threshold to obtain the peak current comparison result; The adjustment gain is dynamically adjusted based on the peak current comparison results.

8. A motor starting control device, characterized in that, include: The data acquisition unit is used to periodically acquire the current speed and initial speed command of the motor, and calculate the moving average rate of change of the actual speed based on multiple preset time scales. The deviation fusion unit is used to obtain the deviation between the initial speed command and the moving average rate of change at different time scales, and to perform weighted fusion processing on the deviation to obtain the start-up hysteresis quantification index. The compensation generation unit is used to generate a speed guidance compensation command based on the start-up hysteresis quantification index. The instruction update unit is used to estimate the moment of inertia and damping coefficient of the motor in real time based on the acquisition cycle and the current speed, and to adaptively update the speed guidance compensation instruction using the moment of inertia. The instruction superposition unit is used to superimpose the initial speed instruction and the updated speed guidance compensation instruction to obtain the target speed instruction; A start control unit is used to start the motor based on the target speed command.

9. An electronic device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the motor starting control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the motor starting control method as described in any one of claims 1 to 7.

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