Permanent magnet frequency conversion double-sine modulation swimming pool pump energy-saving control method

Abstract

The invention provides a permanent magnet frequency conversion double-sine modulation swimming pool pump energy-saving control method, and relates to the technical field of motor driving and control, and the method comprises the steps: building a double-sine carrier modulation model of a permanent magnet synchronous motor, and calculating a dynamic harmonic suppression factor and a double-sine modulation depth in real time; feedforward compensation is carried out on the inverter current based on the DHSIF, and a q-axis current reference value is generated by adopting double-closed-loop vector control; dynamically adjusting a carrier frequency range according to the DSMD, generating double sine carriers with a phase difference of pi / 3, and superposing the double sine carriers into a composite modulated wave; the modulation wave amplitude is corrected through a DHSIF, and fifth and seventh harmonics are eliminated in combination with an adaptive filtering algorithm; a carrier wave ratio is dynamically optimized to generate a PWM signal, and a transient compensation mechanism is triggered to correct a voltage instruction when a load suddenly changes; and an energy efficiency optimization database is constructed to call historical optimal parameters, and nonlinear mapping of DHSIF and motor characteristics is established through parameter self-tuning. According to the invention, cooperative control is realized through dynamic harmonic suppression, modulation depth optimization and intelligent thermal protection.

Description

Technical Field

[0001] The present invention relates to the technical field of motor drive and control, and particularly to an energy-saving control method for a permanent magnet variable-frequency double-sine modulation pool pump. Background Art

[0002] In fluid control devices such as pool pumps and circulating water systems, permanent magnet synchronous motors have gradually become the mainstream drive solution due to their advantages of high efficiency, high power density, and dynamic performance. However, traditional variable-frequency control technologies still face many challenges in practical applications. Traditional pulse width modulation technologies mostly adopt a fixed carrier frequency and a single modulation method, which are difficult to adapt to the dynamic changes of the load. Especially in light-load or variable working condition scenarios, fixed parameters are likely to lead to an increase in switching losses, and at the same time, due to the concentrated distribution of harmonic energy, electromagnetic interference and an increase in iron losses are caused, severely restricting the system energy efficiency. In addition, existing harmonic suppression means mostly rely on hardware filtering or fixed-threshold compensation, lacking targeted treatment of characteristic harmonics such as the 5th and 7th harmonics, which not only increases motor losses, but may also cause the current distortion rate to exceed the standard due to load mutations or grid disturbances, exacerbating vibration and noise problems.

[0003] In terms of dynamic response, traditional double closed-loop control relies on a linear compensation mechanism, is sensitive to parameter changes and has a lagging response, and is prone to torque pulsation and speed overshoot when the load mutates. Existing transient compensation methods mostly based on fixed gain coefficients are difficult to dynamically adjust in combination with complex factors such as harmonic states and temperature changes, and the compensation effect is limited. At the same time, the thermal management of power devices mostly adopts passive temperature threshold protection, lacking dynamic prediction and active adjustment of the thermal state. When the temperature is high or the heat dissipation deteriorates, it is easy to cause operation interruption or excessive derating, affecting the continuous operation ability of the equipment. In addition, the decoupled design of modulation parameters and thermal states leads to an imbalance between device losses and heat dissipation requirements, accelerating the aging of power modules.

[0004] More critically, existing control methods generally rely on offline parameter tuning, making it difficult to track the changes in working conditions in real time. Key parameters such as the carrier ratio and modulation depth cannot be optimized synergistically under dynamic loads, resulting in efficiency fluctuations and waste of energy efficiency potential. The lack of intelligent analysis ability for historical operation data makes it difficult for the system to achieve parameter adaptive adjustment through a self-learning mechanism, resulting in limited energy efficiency performance during long-term operation. In summary, existing technologies are difficult to balance high-efficiency operation, harmonic suppression, dynamic stability, and long-term reliability, and there is an urgent need for a comprehensive control scheme integrating dynamic modulation optimization, precise harmonic suppression, intelligent thermal management, and adaptive learning capabilities to break through the limitations of traditional methods. Summary of the Invention

[0005] In order to solve the technical problems in the prior art that it is difficult to balance energy efficiency and harmonic suppression, the dynamic response is lagging, the thermal management is passive, and there is a lack of intelligent adaptive optimization, the present invention provides an energy-saving control method for a permanent magnet variable-frequency double-sine modulation pool pump.

[0006] The technical solution provided by the present invention is as follows:

[0007] An energy-saving control method for a permanent magnet variable frequency double sine modulation pool pump provided by the present invention includes:

[0008] S1. Establish a double sine carrier modulation model of a permanent magnet synchronous motor (PMSM), and calculate the dynamic harmonic suppression intensity factor (DHSIF) and the dual sinusoidal modulation depth (DSMD) by collecting three-phase current signals and rotor position angles in real time;

[0009] S2. Perform feed-forward compensation on the inverter output current based on the dynamic harmonic suppression factor, adopt a double closed-loop vector control structure, introduce an adaptive sliding mode observer in the outer speed loop to generate the q-axis current reference value;

[0010] S3. Adjust the carrier frequency distribution range according to the dual sinusoidal modulation depth, generate two groups of sinusoidal carrier signals with a phase difference of π / 3 in the range of 0.8 - 1.2 times the fundamental frequency, and superimpose the two groups of carrier signals to form a composite modulation wave;

[0011] S4. Dynamically correct the amplitude of the composite modulation wave through the dynamic harmonic suppression factor, and adopt an adaptive filtering algorithm based on harmonic energy distribution to eliminate the 5th and 7th harmonic components;

[0012] S5. Compare the corrected modulation wave with the triangular carrier wave to generate a PWM drive signal, and dynamically adjust the carrier ratio according to the motor efficiency optimal point detected in real time;

[0013] S6. Start the transient compensation mechanism when the load suddenly changes, calculate the compensation coefficient through the deviation between the motor torque observed value and the actual value, and correct the d-q axis voltage command;

[0014] S7. Establish an energy efficiency optimization database, store the optimal dynamic harmonic suppression factor and dual sinusoidal modulation depth combination parameters under different working conditions, and call the historical optimal parameter combination during steady-state operation;

[0015] S8. Execute the parameter self-tuning program during the initialization stage of the control system, measure the system response characteristics by injecting a characteristic frequency signal, and establish a non-linear mapping relationship between the dynamic harmonic suppression factor and the motor parameters.

[0016] S9. During the initialization stage of the control system, execute the parameter self-tuning program, measure the system response characteristics by injecting a characteristic frequency signal, and establish a non-linear mapping relationship between the dynamic harmonic suppression factor and the motor parameters.

[0017] The beneficial effects brought by the technical solution provided by the present invention at least include:

[0018] (1) In the present invention, through the collaborative control of the dynamic harmonic suppression factor DHSIF and the double-sine modulation depth DSMD, precise suppression of the harmonic components of the motor and dynamic optimization of the modulation parameters are achieved. By adjusting the carrier frequency distribution range and the composite modulation waveform in real time, the switching loss and the content of high-order harmonics are significantly reduced, effectively improving the power utilization efficiency. At the same time, the adaptive filtering algorithm eliminates the 5th and 7th characteristic harmonics directionally, further reducing electromagnetic interference and ensuring that the system operates efficiently and stably within a wide load range. The overall energy-saving effect is remarkable;

[0019] (2) In the present invention, under complex working conditions such as load mutation or grid fluctuation, the transient compensation mechanism combines the dynamic deviation calculation between the torque observer and the actual value to quickly correct the d-q axis voltage command, effectively suppressing torque ripple and current shock. The introduction of the adaptive sliding mode observer enhances the robustness of the speed loop, overcoming the problem that the traditional PI controller is sensitive to parameters. Through the linkage control of the carrier ratio dynamic optimization and the thermal protection strategy, the system can maintain stable operation under extreme conditions, significantly improving the anti-interference ability and the dynamic response speed;

[0020] (3) In the present invention, the energy efficiency optimization database pre-stores the optimal parameter combinations for typical working conditions through the genetic algorithm, and updates the data in real time in combination with the online learning mechanism to achieve the adaptive optimization of the control strategy. The parameter self-tuning program automatically matches the motor characteristic differences and aging effects through the injection of sweep signals and system identification technology, ensuring the precise adaptation of the control model. The collaborative control of the hierarchical thermal protection mechanism and the heat dissipation system actively prevents the overheating damage of power devices, extends the service life of the equipment, reduces the maintenance frequency and operating costs at the same time, and comprehensively improves the intelligent level and long-term reliability of the system. Description of the Drawings

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a schematic flow chart of an energy-saving control method for a permanent magnet variable frequency double-sine modulation pool pump provided by an embodiment of the present invention;

[0023] Figure 2 It is a schematic flow chart of generating a composite modulation wave for an energy-saving control method for a permanent magnet variable frequency double-sine modulation pool pump provided by an embodiment of the present invention;

[0024] Figure 3 It is a schematic diagram of the parameter self-tuning program flow of a permanent magnet variable frequency double sine modulation pool pump energy-saving control method provided by an embodiment of the present invention. Specific embodiments

[0025] The technical solutions in the present invention will be described below with reference to the accompanying drawings.

[0026] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or more advantageous than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0027] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0028] In the embodiments of the present invention, sometimes subscripts such as W1 may be miswritten as non-subscript forms such as W1. When the difference is not emphasized, the meanings they express are the same.

[0029] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0030] Refer to the attached drawings of the specification Figure 1 , which shows a schematic diagram of the flow of a permanent magnet variable frequency double sine modulation pool pump energy-saving control method provided by an embodiment of the present invention.

[0031] The embodiments of the present invention provide a permanent magnet variable frequency double sine modulation pool pump energy-saving control method, and the processing flow may include the following steps:

[0032] S1. Establish a double sine carrier modulation model of a permanent magnet synchronous motor, and calculate the dynamic harmonic suppression factor DHSIF and the double sine modulation depth DSMD by collecting three-phase current signals and rotor position angles in real time.

[0033] It should be noted that this step aims to solve the contradiction between harmonic suppression and efficiency optimization in traditional modulation methods by establishing a double-sine carrier modulation model and calculating the Dynamic Harmonic Suppression Index (DHSIF) and Double-Sine Modulation Depth (DSMD). The introduction of DHSIF can quantify the degree of harmonic distortion in real time, providing a dynamic benchmark for subsequent feedforward compensation; while DSMD precisely controls the amplitude of the modulation wave by integrating voltage, frequency, and thermal state parameters to optimize the switching losses. The logic is as follows: based on the real-time feedback of three-phase current and rotor position, a dynamic parameter system is constructed to provide basic modulation parameters for the entire control process, realizing the closed-loop start from signal acquisition to control decision-making.

[0034] S2. Perform feedforward compensation on the inverter output current based on the Dynamic Harmonic Suppression Index, adopt a double-closed-loop vector control structure, introduce an adaptive sliding mode observer in the outer speed loop to generate the q-axis current reference value.

[0035] It should be noted that the core reason for introducing an adaptive sliding mode observer in the double-closed-loop vector control is that the traditional PI controller is sensitive to parameters and has insufficient dynamic response. The sliding mode observer suppresses the speed fluctuation through strong robustness and generates an accurate q-axis current reference value; the feedforward compensation term ΔI_d is dynamically coupled with DHSIF to actively cancel the d-axis current offset caused by harmonics. Its logic connects with the output parameters of S1, forming a coordinated mechanism between the outer speed control and the inner current control, ensuring a stable torque output under harmonic interference and providing an optimized current command for the modulation wave generation in S3.

[0036] S3. Adjust the carrier frequency distribution range according to the Double-Sine Modulation Depth, generate two groups of sine carrier signals with a phase difference of π / 3 within the range of 0.8 - 1.2 times the fundamental frequency, and superimpose the two groups of carrier signals to form a composite modulation wave.

[0037] It should be noted that generating two sine carrier signals with a phase difference of π / 3 aims to break the periodic harmonic distribution characteristics of the traditional single carrier. By dynamically adjusting the carrier frequency range (0.8 - 1.2 times the fundamental frequency), the switching harmonic energy can be dispersed to a wider frequency band, reducing the peak value of electromagnetic interference; the superimposed design of the composite modulation wave enhances the modulation freedom, providing a flexible waveform basis for harmonic suppression in S4. The logic is as follows: based on the DSMD calculated in S1, the carrier parameters are dynamically adjusted to make the modulation wave form adapt to the working condition changes, forming a key conversion link from the control command to the waveform generation.

[0038] S4. Dynamically correct the amplitude of the composite modulation wave through the Dynamic Harmonic Suppression Index, and adopt an adaptive filtering algorithm based on harmonic energy distribution to eliminate the 5th and 7th harmonic components.

[0039] It should be noted that the combination of dynamic correction and adaptive filtering algorithm directly targets the 5th / 7th harmonics, which are the main harmonic sources of permanent magnet motors. DHSIF participates in amplitude correction to ensure the dynamic matching of the modulation wave amplitude and harmonic intensity; the improved LMS algorithm suppresses weight drift through the leakage factor γ and accurately eliminates the target harmonic components. Its logic inherits the composite modulation wave of S3 and implements secondary optimization at the waveform level, forming a three-level processing chain of "parameter calculation - waveform generation - harmonic filtering" to provide a purified modulation signal for the PWM generation of S5.

[0040] S5. Compare the corrected modulation wave with the triangular carrier wave to generate a PWM drive signal, and at the same time, dynamically adjust the carrier ratio according to the real-time detected optimal motor efficiency point.

[0041] It should be noted that the design of the carrier ratio dynamic adjustment mechanism stems from the trade-off requirements between switching losses and harmonic performance. By real-time detecting the optimal motor efficiency point, the optimization calculation of the carrier ratio N_opt is driven by a formula, and the frequency is actively reduced before the switching losses increase, avoiding the steep efficiency drop caused by the traditional fixed carrier ratio. Its logic connects the modulation wave processed by S4, converts the waveform parameters into specific PWM timing signals, and realizes the final closed-loop of the energy efficiency control chain through the adaptive adjustment of the carrier ratio.

[0042] S6. Start the transient compensation mechanism during load mutation, calculate the compensation coefficient according to the deviation between the motor torque observation value and the actual value, and correct the d-q axis voltage command.

[0043] It should be noted that the transient compensation mechanism aims at the torque ripple and current impact problems caused by load mutation. By constructing a deviation model between the torque observer and the actual value, and using DHSIF as the compensation coefficient weight factor, the correction amount of the d-q axis voltage command reflects both the harmonic state and the dynamic error. Its logic is: superimpose a transient compensation layer on the double closed-loop control framework of S2 to form a dual-mode structure of "steady-state control + transient correction" to ensure the fast recovery ability of the system under mutation conditions.

[0044] S7. Establish an energy efficiency optimization database to store the optimal dynamic harmonic suppression factor and the combined parameters of double sine modulation depth under different working conditions, and call the historical optimal parameter combination during steady-state operation.

[0045] It should be noted that the construction of the energy efficiency optimization database solves the problem of large online real-time global optimization calculation. By pre-storing the optimal DHSIF-DSMD combination through an offline genetic algorithm and directly calling historical data during steady-state operation, the repeated calculation overhead is avoided. Its logic forms a "learning - application" cycle with S1 - S6: the real-time data of S1 - S6 continuously updates the database, and the database in turn provides experience guidance for subsequent control, significantly improving the decision-making efficiency under steady-state conditions.

[0046] S8. During the initialization stage of the control system, execute the parameter self-tuning program. Measure the system response characteristics by injecting characteristic frequency signals, and establish a non-linear mapping relationship between the dynamic harmonic suppression factor and the motor parameters.

[0047] It should be noted that the original design intention of the parameter self-tuning program is to eliminate the influence of motor individual differences and aging on the control performance. By injecting characteristic frequency signals to stimulate the system dynamic response, combined with the RLS algorithm to accurately identify the motor parameters, and establish a non-linear mapping relationship between the DHSIF and the motor intrinsic parameters. Its logic runs through the entire control system: complete the system "fingerprint" identification during the initialization stage, provide personalized parameter benchmarks for all algorithms of S1-S7, and ensure the precise matching of the control strategy and the physical object.

[0048] In a possible implementation manner, the calculation method of the dynamic harmonic suppression factor DHSIF includes:

[0049]

[0050] where K p is the harmonic suppression proportionality coefficient, an adjustable parameter between 0.5 and 1.2; I harmonic is the total harmonic distortion rate of the current detected in real time; I threshold is the preset harmonic threshold, taking 8%-12% of the rated current; α is the non-linear correction exponent, α = 1.5 + 0.2×sin(2πft), f is the fundamental frequency; K i is the integral gain coefficient, R s is the stator resistance, L q is the q-axis inductance; Δθ err is the rotor position angle detection error.

[0051] It should be noted that this method solves the defect that the traditional fixed threshold cannot dynamically adapt to the working condition changes by real-time fusing the harmonic intensity and the rotor angle error. Its core role is to quantify the dynamic weight of the harmonic suppression demand, which not only reflects the severity of the current harmonic distortion but also takes into account the cumulative effect of the angle detection error, ensuring that the suppression intensity is accurately matched with the system state. Logically, as the basic parameter of the harmonic suppression system, it provides a dynamic benchmark for the feedforward compensation and filtering algorithms, forming a closed-loop control link from detection to suppression.

[0052] In a possible implementation manner, the calculation formula of the double sine modulation depth DSMD is:

[0053]

[0054] where V dc is the DC bus voltage; V peakis the peak value of the motor phase voltage; ω is the electrical angular velocity; β is the temperature attenuation coefficient, β = 0.05×(T junc -25) / 75, T junc is the junction temperature of the power device; the calculation process is updated within each 1ms control period and smoothed through cubic spline interpolation.

[0055] It should be noted that this model breaks through the limitation of single - dimension regulation. By comprehensively considering the multiple effects of voltage fluctuation, high - frequency oscillation, and temperature attenuation, it not only ensures the utilization rate of the fundamental wave voltage, but also disperses the high - frequency harmonic energy, and automatically derates for protection according to temperature. Its function is to dynamically couple the electrical characteristics and thermal state, logically connect the parameter calculation and carrier generation links, and provide a multi - dimensional decision - making basis for modulation wave optimization.

[0056] In a possible implementation manner, as Figure 2 shown, the specific method for generating the composite modulation wave in S3 includes:

[0057] S301. Use Clarke transformation to convert the three - phase current into components in the α - β coordinate system;

[0058] S302. Apply Park transformation to convert the α - β components into d - q rotating coordinate system components;

[0059] S303. Apply a feed - forward compensation term ΔI d = K comp ×DHSIF×|I q | to the d - axis current component, where K comp is the compensation coefficient;

[0060] S304. Generate the initial modulation wave through space vector pulse width modulation for the compensated d - q axis current.

[0061] It should be noted that for the current offset problem under asymmetric loads, the three - phase current is decoupled into rotating coordinate system components, and the flux linkage components are dynamically corrected in combination with the harmonic state. Its function is to eliminate the current imbalance caused by harmonics, logically form a closed - loop path of "detection - decoupling - compensation", and ensure the real - time adaptation of the modulation command to the load characteristics.

[0062] In a possible implementation manner, the adaptive filtering algorithm in S4 adopts an improved LMS (Least Mean Square) algorithm, and its iterative formula is:

[0063] w(n + 1)= w(n)+μ×e(n)×[x(n)-γ×sign(w(n))]

[0064] where w(n) is the filter weight vector of the nth iteration; μ is the step - size factor, μ = 0.01×DSMD2 ; e(n) is the error signal, which is determined by the difference between the harmonic components of the output current and the reference value; x(n) is the input signal vector; γ is the leakage factor, γ = 0.001×f sw , f sw is the switching frequency.

[0065] It should be noted that to solve the pain points of traditional filters being prone to divergence or slow convergence under dynamic operating conditions, a balance between fast tracking and long-term stability is achieved through dynamic step size adjustment and anti-divergence mechanisms. Its core function is to accurately eliminate specific harmonics, and logically, as the final processing link for harmonic suppression, it converts parameter calculation into actual waveform purification operations.

[0066] In a possible implementation, the method for dynamically adjusting the carrier ratio in S5 includes:

[0067] When it is detected that the motor efficiency drops by more than 2%, start the carrier ratio optimization program, and calculate the optimal carrier ratio N according to the following formula opt :

[0068]

[0069] where, floor represents the floor function; f sw is the current switching frequency; f base is the fundamental frequency; during the calculation process, N opt is constrained to be in the range of 21 - 51.

[0070] It should be noted that it aims to balance the switching loss and harmonic performance, and by real-time evaluating the change of system efficiency, it intelligently adjusts the carrier frequency distribution. Its function is to avoid the excessive loss or wide frequency band problem of the fixed carrier ratio, and logically, it directly links the energy efficiency monitoring and the switching control to form a fast response chain.

[0071] In a possible implementation, S6 specifically includes: The calculation method of the compensation coefficient includes:

[0072] Establish a torque observer model:

[0073]

[0074] The actual torque calculation adopts:

[0075]

[0076] The compensation coefficient K comp is determined by the following formula:

[0077]

[0078] where, p is the number of pole pairs of the motor; ψ fis the permanent magnet flux linkage; L d and L q are the d-q axis inductances; J is the moment of inertia; B is the damping coefficient; T load is the load torque; T rated is the rated torque; ΔV dc is the DC bus voltage fluctuation; V dc_nom is the rated DC voltage.

[0079] It should be noted that for the dynamic mismatch problem under sudden load, by comparing the theoretical torque with the mechanical motion extrapolation value, a composite compensation coefficient including harmonic state and voltage fluctuation is constructed. Its role is to quickly suppress torque ripple. Logically, a dynamic compensation layer is added to the control system to form a dual guarantee mechanism of "steady-state tracking + transient correction".

[0080] In a possible implementation manner, the construction method of the energy efficiency optimization database in S7 includes:

[0081] Using the genetic algorithm (Genetic Algorithm, GA) to search for the optimal solution in the three-dimensional parameter space, and the objective function is:

[0082]

[0083] The constraint conditions include:

[0084]

[0085] Among them, P out is the output mechanical power; P in is the input electrical power; THD is the total harmonic distortion rate; λ1 and λ2 are penalty factors, with values of 0.3 and 0.15 respectively; DHSIF ref is the preset reference value.

[0086] It should be noted that by pre-storing the optimal parameter combinations of typical working conditions, the problem of large online global optimization calculation amount is solved. Its role is to improve the steady-state operation decision-making efficiency. Logically, it forms a complementary architecture with real-time control and constitutes a self-learning system through historical data iterative optimization.

[0087] In a possible implementation manner, as Figure 3 shown, the S8 parameter self-tuning program specifically includes:

[0088] S801, injecting a swept-frequency signal with an amplitude of 5% of the rated current, and the frequency range covers 0.5f base to 3f base ;

[0089] S802. Identify the system transfer function using the Recursive Least Squares (RLS) method:

[0090]

[0091] S803. Establish the mapping relationship of the dynamic harmonic suppression factor:

[0092]

[0093] where K is the system gain; τ is the time delay constant; T1 and T2 are the time constants.

[0094] It should be noted that it aims to eliminate the influence of individual device differences on the control accuracy, excite the response through the characteristic signal and identify the motor characteristics. Its role is to establish an accurate mapping between the control model and the physical object, and logically serve as the core link of system initialization, providing personalized reference parameters for all algorithms.

[0095] In a possible implementation, it further includes step S9:

[0096] When the junction temperature of the power device exceeds 110 °C, start the thermal protection mode and correct the control parameters according to the following rules:

[0097] The dynamic harmonic suppression factor is corrected to:

[0098] DHSIF′ = DHSIF × [1 - 0.015(T junc - 100)]

[0099] The double-sine modulation depth is corrected to:

[0100]

[0101] Forcibly reduce the carrier ratio to 70% - 80% of the original value; the corrected parameters continue until the junction temperature drops below 90 °C and then gradually recover at a recovery rate of 5% of the initial value per minute.

[0102] It should be noted that by dynamically attenuating the modulation intensity and reducing the frequency operation, the risk of overheating of the power device is solved. Its role is to actively prevent thermal failure and maintain the basic operation ability, and logically it is deeply coupled with temperature monitoring to form a closed-loop protection system of "perception - adjustment - recovery" to achieve the dynamic balance of safety and performance.

[0103] After the system is powered on, a multi-level initialization program is executed first, including hardware interface detection, sensor zero calibration, and preloading of control parameters. During the initialization phase, the phase consistency of the three-phase current sensors is verified by injecting a small test current. If the phase difference between any two-phase currents is detected to deviate from 120° by more than ±0.5°, the phase compensation algorithm is automatically triggered. The angle decoding module of the resolver executes a self-calibration program. By rotating the motor rotor to a preset mechanical position, the error between the decoded angle and the mechanical scale is compared. If the deviation exceeds 0.1°, the update of the angle offset compensation table is started. The IGBT drive circuit of the power module conducts a conduction test, applying microsecond-level pulse signals to each bridge arm in turn. The health status of the power device is judged by detecting the reverse recovery time of the freewheeling diode. In case of an abnormality, the faulty bridge arm is automatically isolated and the redundant control mode is enabled.

[0104] The real-time performance of the control system is ensured by multi-core task allocation. The main core is responsible for the calculation of double closed-loop vector control, and the coprocessor is dedicated to harmonic analysis and filtering operations. Data acquisition adopts a double-buffer alternating storage mechanism. The data collected in the previous cycle is processed in the current control cycle to ensure that the operation and acquisition are executed in parallel. The update of key parameters (such as DHSIF, DSMD) adopts a priority interrupt mechanism. When a load mutation or harmonic over-standard is detected, the parameter recalculation is immediately triggered, and the interrupt response time is less than 10 μs. The historical operation data is stored in a circular queue structure, with the latest data overwriting the oldest data, ensuring that the working condition information within the most recent 100 ms is always obtained when the database is called.

[0105] The system is built-in with a multi-level fault detection mechanism: when the current sensor fails, it switches to a virtual current reconstruction mode based on voltage observation; when the rotor position signal is abnormal, a sliding mode observer is enabled for full-speed range angle estimation; when a sudden drop in the DC bus voltage exceeding 20% is detected, it immediately enters the low-voltage ride-through mode, restricting the output power and preferentially maintaining the power supply for the control logic. For PWM pulse abnormalities, a hardware watchdog circuit is designed to monitor the duty cycle of the drive signal in real time. If the detected duty cycle exceeds the safety threshold of 95% and lasts for 5 μs, the pulse output is immediately blocked and the fault log is started.

[0106] For the typical load characteristics of the pool pump (such as the gradual change in load caused by filter clogging), the system sets a dynamic sensitivity adjustment mechanism: when the load change rate is lower than 5% / s, the pre-stored parameters in the database are used for a smooth transition; when the change rate exceeds 10% / s, the feedforward compensation coefficient is automatically increased and the control cycle is shortened to 50 μs. For periodic load fluctuations (such as water pump impeller disturbances), a frequency tracking algorithm is introduced. By analyzing the main frequency of the load fluctuation through FFT, a reverse harmonic component is injected into the control instruction to achieve active cancellation.

[0107] The device is equipped with a man-machine interface module, supporting two debugging modes: in the expert mode, manual adjustment of advanced parameters such as DHSIF gain and DSMD temperature coefficient is allowed, and the adjustment results are used to display the efficiency and harmonic change curves in real time; in the wizard mode, an initial control parameter set is automatically recommended based on installation parameters such as pump head and pipe diameter. The debugging data can be uploaded to the cloud platform through a wireless module to generate an energy efficiency optimization report and feedback new parameter combinations to the local database.

[0108] The rotation speed of the cooling fan is dynamically coupled with the junction temperature of the power device: when the junction temperature is below 80°C, the fan operates at the lowest speed; in the range of 80 - 100°C, the speed increases by 50 rpm for every 1°C increase; after exceeding 100°C, the forced cooling mode is started, and the fan speed linearly increases to the maximum value. At the same time, an air flow sensor is arranged in the cooling air duct to monitor the cooling efficiency in real time. If insufficient air volume is detected (such as filter blockage), the pump speed is automatically increased to increase the cooling water circulation flow rate, forming a linkage control between the thermal management and the hydraulic system.

[0109] The system is built-in with an energy consumption measurement module to calculate the cumulative energy savings in real time: based on the comparison between the current operating parameters and the theoretical energy consumption model of the standard SVPWM control, the energy saving percentage is dynamically displayed. An energy consumption report is generated every 24 hours to count the proportion of harmonic losses, switching losses, and temperature rise losses in each time period, providing an optimization direction for maintenance personnel. During the low-load period at night, it automatically switches to the ECO mode, in which the historical optimal low-frequency parameter combination is preferentially called to further reduce the standby power consumption.

[0110] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0111] (1) In the present invention, through the collaborative control of the dynamic harmonic suppression factor DHSIF and the double sine modulation depth DSMD, precise suppression of the harmonic components of the motor and dynamic optimization of the modulation parameters are achieved. By adjusting the carrier frequency distribution range and the composite modulation waveform in real time, the switching losses and the content of high-order harmonics are significantly reduced, effectively improving the power utilization efficiency. At the same time, the adaptive filtering algorithm eliminates the 5th and 7th characteristic harmonics directionally, further reducing electromagnetic interference and ensuring the system operates efficiently and stably within a wide load range, with a significant overall energy saving effect;

[0112] (2) In the present invention, under complex working conditions such as load mutation or grid fluctuation, the transient compensation mechanism combines the dynamic deviation calculation between the torque observer and the actual value to quickly correct the d-q axis voltage command, effectively suppressing torque ripple and current impact. The introduction of the adaptive sliding mode observer enhances the robustness of the speed loop, overcoming the problem that the traditional PI controller is sensitive to parameters. Through the linkage control of the carrier ratio dynamic optimization and the thermal protection strategy, the system can maintain stable operation under extreme conditions, significantly improving the anti-interference ability and the dynamic response speed;

[0113] (3) In the present invention, the energy efficiency optimization database pre-stores the optimal parameter combinations under typical working conditions through genetic algorithms, and combines an online learning mechanism to update data in real time, achieving the adaptive optimization of control strategies. The parameter self-tuning program automatically matches the differences in motor characteristics and the impact of aging through frequency sweep signal injection and system identification technology, ensuring the accurate adaptation of the control model. The coordinated control of the hierarchical thermal protection mechanism and the heat dissipation system actively prevents overheating damage of power devices, extends the service life of the equipment, reduces the maintenance frequency and operating costs at the same time, and comprehensively improves the intelligent level and long-term reliability of the system.

[0114] The above content is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

[0115] The following points need to be explained:

[0116] (1) The drawings of the embodiments of the present invention only relate to the structures involved in the embodiments of the present invention, and other structures can refer to the general design.

[0117] (2) For clarity, in the drawings used to describe the embodiments of the present invention, the thickness of layers or regions is enlarged or reduced, that is, these drawings are not drawn according to the actual scale. It can be understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element can be "directly" on or under the other element or there can be intermediate elements.

[0118] (3) Without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0119] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A permanent magnet variable frequency double sine modulation energy-saving control method for a pool pump, characterized in that, Including: S1. Establish a double-sine carrier modulation model for a permanent magnet synchronous motor. By collecting three-phase current signals and rotor position angles in real time, calculate the dynamic harmonic suppression factor DHSIF and the double-sine modulation depth DSMD; S2. Based on the dynamic harmonic suppression factor, perform feedforward compensation on the inverter output current. Adopt a double-closed-loop vector control structure, introduce an adaptive sliding mode observer in the outer speed loop to generate the q-axis current reference value; S3. Adjust the carrier frequency distribution range according to the double-sine modulation depth. Generate two groups of sine carrier signals with a phase difference of π / 3 in the range of 0.8 - 1.2 times the fundamental frequency, and superimpose the two groups of carrier signals to form a composite modulation wave; S4. Dynamically correct the amplitude of the composite modulation wave through the dynamic harmonic suppression factor, and adopt an adaptive filtering algorithm based on harmonic energy distribution to eliminate the 5th and 7th harmonic components; S5. Compare the corrected modulation wave with the triangular carrier to generate a PWM drive signal, and at the same time dynamically adjust the carrier ratio according to the motor efficiency optimal point detected in real time; S6. Start the transient compensation mechanism when the load suddenly changes. Calculate the compensation coefficient through the deviation between the motor torque observation value and the actual value, and correct the d-q axis voltage command; S7. Establish an energy efficiency optimization database to store the optimal combination parameters of the dynamic harmonic suppression factor and the double-sine modulation depth under different working conditions, and call the historical optimal parameter combination during steady-state operation; S8. Execute the parameter self-tuning program during the initialization stage of the control system. Measure the system response characteristics by injecting characteristic frequency signals, and establish a non-linear mapping relationship between the dynamic harmonic suppression factor and the motor parameters.

2. The energy-saving control method for a permanent magnet variable frequency double-sine modulation pool pump according to claim 1, wherein The calculation method of the dynamic harmonic suppression factor DHSIF includes: Among them, K p is the harmonic suppression proportionality coefficient, which is an adjustable parameter between 0.5 and 1.2; I harmonic is the total harmonic distortion rate of the current detected in real time; I threshold is the preset harmonic threshold, which is 8%-12% of the rated current; α is the nonlinear correction exponent, f is the fundamental frequency; K i is the integral gain coefficient, R s is the stator resistance, L q is the q-axis inductance; Δθ err is the detection error of the rotor position angle.

3. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that, The calculation formula of the double-sine modulation depth DSMD is: Among them, V dc is the DC bus voltage; V peak is the peak value of the motor phase voltage; ω is the electrical angular velocity; β is the temperature decay coefficient, β = 0.05×(T junc - 25) / 75, T junc is the junction temperature of the power device; the calculation process is updated within each 1 ms control cycle and smoothed by cubic spline interpolation.

4. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that, The specific method for generating the composite modulation wave in S3 includes: S301. Use the Clarke transformation to convert the three-phase current into components in the α-β coordinate system; S302. Apply the Park transformation to convert the α-β components into d-q rotating coordinate system components; S303. Apply a feedforward compensation term ΔI based on the dynamic harmonic suppression factor to the d-axis current component d = K comp × DHSIF × |I q |, where K comp is the compensation coefficient; S304. Generate the initial modulation wave through space vector pulse width modulation for the compensated d-q axis current.

5. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that The adaptive filtering algorithm in S4 adopts an improved LMS algorithm, and its iteration formula is: w(n + 1) = w(n) + μ × e(n) × [x(n) - γ × sign(w(n))] where, w(n) is the filter weight vector at the nth iteration; μ is the step size factor, μ = 0.01×DSMD 2 ; e(n) is the error signal, determined by the difference between the output current harmonic component and the reference value; x(n) is the input signal vector; γ is the leakage factor, γ = 0.001×f sw , f sw is the switching frequency.

6. The energy-saving control method for a permanent magnet variable frequency double-sine modulation pool pump according to claim 1, wherein The method for dynamically adjusting the carrier ratio in S5 includes: When it is detected that the motor efficiency drops by more than 2%, start the carrier ratio optimization program and calculate the optimal carrier ratio N according to the following formula opt : where, floor represents the floor function; f sw is the current switching frequency; f base is the fundamental frequency; during the calculation, N opt is constrained to be within the range of 21 - 51.

7. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that, S6 specifically includes: The calculation method of the compensation coefficient includes: Establish a torque observer model: The actual torque calculation adopts: Compensation factor K comp is determined by the following formula: where p is the number of pole pairs of the motor; ψ f is the permanent magnet flux linkage; L d , L q are the d-q axis inductances; J is the moment of inertia; B is the damping coefficient; T load is the load torque; T rated is the rated torque; ΔV dc is the DC bus voltage fluctuation; V dc_nom is the rated DC voltage.

8. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that The construction method of the energy efficiency optimization database in S7 includes: Use the genetic algorithm GA to search for the optimal solution in the three-dimensional parameter space, and the objective function is: The constraint conditions include: Among them, P out is the output mechanical power; P in is the input electric power; THD is the total harmonic distortion rate; λ1 and λ2 are penalty factors, with values of 0.3 and 0.15 respectively; DHSIF ref is the preset reference value.

9. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that, The parameter self-tuning program in S8 specifically includes: Inject a swept-frequency signal with an amplitude of 5% of the rated current, and the frequency range covers 0.5f base to 3f base ; S802. Use the recursive least squares method RLS to identify the system transfer function; S803. Establish the mapping relationship of the dynamic harmonic suppression factor.

10. A permanent magnet variable frequency double sine modulation pool pump energy-saving control method according to claim 1, characterized in that, It also includes step S9: When the junction temperature of the power device exceeds 110°C, start the thermal protection mode, correct the control parameters, and force the carrier ratio to be reduced to 70%-80% of the original value; the corrected parameters continue until the junction temperature drops below 90°C and then gradually recover at a rate of 5% of the initial value per minute.

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