A method and system for compressor frequency noise regulation based on heating rate feedback

Abstract

This invention proposes a compressor frequency noise reduction method and system based on heating rate feedback. The method includes: constructing a state input vector; calculating a temperature difference target based on the current inlet water temperature of the target compressor, and identifying whether the heating effect is effective after frequency change; constructing a listening score model including a frequency penalty term and a trend correction term through dynamic coupling of noise intensity and thermal path response impedance, generating a listening score and a listening risk increment; weightedly fusing the thermal path response impedance and the listening score to obtain a frequency modulation tendency score and a frequency adjustment command; and applying the frequency adjustment command to the actual equipment to complete the operation execution of compressor frequency conversion noise reduction. This invention solves the technical deficiency of existing methods that cannot simultaneously determine heating effectiveness and noise comfort.

Description

Technical Field

[0001] This invention belongs to the field of compressors, and particularly relates to a method and system for adjusting compressor frequency and noise based on heating rate feedback. Background Technology

[0002] Air source heat pumps are widely used in residential and commercial heating systems due to their energy-saving characteristics. The compressor, as its core component, determines not only the system's heating rate but also directly affects its operating noise level. Currently, most control strategies rely on fixed rules based on set temperature differences or temperature rise rates to control the compressor's frequency increase or decrease. However, this method has several problems in actual operation. During initial startup or under low ambient temperature conditions, frequency increases do not immediately translate into a significant temperature rise. The system may misjudge ineffective heating due to a lack of perceived effective temperature increase, leading to premature frequency reduction decisions, resulting in repeated start-stop cycles or decreased efficiency. Furthermore, the noise change caused by frequency increases is not always proportional to the decibel level. Users' subjective hearing is often influenced by sound structure characteristics such as high-frequency sharpness and low-frequency resonance. Traditional methods of judging quietness solely by decibels cannot accurately reflect actual comfort; the system may be perceived as excessively noisy even when the sound pressure level meets the standard.

[0003] Furthermore, current control systems typically handle heating control and noise reduction separately, lacking a control logic that can provide feedback and unified decision-making based on both thermal response and auditory perception. This leads to conflicts in frequency adjustment strategies under dynamic conditions, making it impossible to achieve coordinated optimization between rapid heating and quiet operation. Therefore, existing technologies lack a complete compressor frequency control mechanism that considers both dynamic heating response and user auditory perception, and possesses real-time adaptive adjustment capabilities. Summary of the Invention

[0004] The purpose of this invention is to propose a compressor frequency noise control method and system based on heating rate feedback, so as to solve the technical defects of existing methods that cannot simultaneously determine heating effectiveness and noise comfort.

[0005] To achieve the above objectives, a method for compressor frequency noise regulation based on heating rate feedback is provided in a first aspect of the present invention, the method comprising:

[0006] S1. Obtain the current inlet water temperature, target temperature, compressor frequency, noise intensity, and actual temperature rise rate of the target compressor to construct the state input vector;

[0007] S2. Calculate the target temperature difference based on the current inlet water temperature of the target compressor, and calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency, to identify whether the heating effect is effective after the frequency change.

[0008] S3. By dynamically coupling the noise intensity and the thermal path response impedance, a listening score model containing a frequency penalty term and a trend correction term is constructed to generate a listening score and a listening risk increment to determine whether the compressor should be allowed to increase its frequency or maintain the current frequency.

[0009] S4. The thermal path response impedance and the listening score are weighted and fused to obtain the frequency modulation tendency score, and a frequency adjustment command is generated based on the comparison between the frequency modulation tendency score and the preset response threshold.

[0010] S5. Apply the frequency adjustment command to the actual equipment to complete the operation of compressor frequency conversion adjustment and noise adjustment, and collect the behavior feedback status after the system response to generate running label variables as part of the state input vector of the controller in the next cycle, so as to perform control closed loop.

[0011] Furthermore, S1 specifically includes:

[0012] The water temperature of the previous cycle and the current inlet water temperature are collected by an NTC thermistor on the water circuit side.

[0013] The compressor frequency is fed back in real time by the frequency converter;

[0014] A MEMS microphone module is used to collect sound signals, and the controller calculates the decibel value as the noise intensity using a fixed weighted average algorithm.

[0015] Calculate the difference between the current inlet water temperature and the water temperature of the previous cycle, and calculate the actual temperature rise rate of the current cycle based on the difference;

[0016] The state input vector is constructed by combining the water temperature of the previous cycle, the current inlet water temperature, the compressor frequency, the noise intensity, and the temperature rise rate.

[0017] Furthermore, S2 specifically includes:

[0018] Obtain the target temperature of the target compressor set by the user, and calculate the difference between the target temperature and the current inlet water temperature to obtain the temperature difference target;

[0019] The thermal path response impedance is calculated based on the current inlet water temperature, target temperature rise rate, compressor frequency, and maximum compressor frequency; if the thermal path response impedance is closest to 0, then the system enters a constant temperature state.

[0020] Furthermore, S3 specifically includes:

[0021] Based on the noise intensity, compressor frequency, maximum compressor frequency, heat load adjustment function, and temperature difference target, a hearing score model is constructed to obtain a hearing score. The heat load adjustment function is calculated based on the thermal path response impedance and is used to dynamically scale the user's tolerance. If the thermal path response impedance is at its maximum, it indicates that heating has not yet been completed and the system's noise tolerance should be enhanced. The value of the heat load adjustment function is closest to 1.

[0022] The hearing score ranges from 0 to 1, with a smaller value indicating that the user is more likely to perceive noise interference from the compressor.

[0023] The incremental hearing risk is calculated based on the current hearing score and the hearing score of the previous period.

[0024] Furthermore, the noise intensity is measured using A-weighted filtering.

[0025] Furthermore, S4 specifically includes:

[0026] Based on the thermal path response impedance and the preset maximum thermal path response impedance, combined with the listening score, the frequency modulation tendency score is calculated.

[0027] The frequency modulation suppression variable is calculated based on the current frequency modulation propensity score and the frequency modulation propensity score of the previous period, which is used to measure the degree of difference between the current frequency modulation score and the frequency modulation propensity score of the previous period.

[0028] The frequency adjustment command is generated based on the frequency modulation suppression variable and is used as an up command, down command or maintenance command issued by the controller to the frequency converter module.

[0029] Furthermore, the step of generating control commands based on the frequency modulation suppression variable, used as up commands, down commands, or maintenance commands issued by the controller to the frequency converter module, specifically includes:

[0030] When the frequency modulation suppression variable exceeds the set sensitivity threshold, the frequency modulation trend is considered unstable and there are instantaneous fluctuations. Therefore, the frequency modulation behavior is paused and the current frequency is kept unchanged. When the frequency modulation suppression variable is less than the set sensitivity threshold, the trend is considered continuous and reliable. Therefore, the frequency is increased or decreased based on the current score.

[0031] Furthermore, S5 specifically includes:

[0032] The upper and lower frequency boundaries set by the acquisition device;

[0033] Calculate the target frequency by combining the upper and lower operating frequency boundaries set by the device, the frequency adjustment command, and the compressor frequency;

[0034] The target frequency is transmitted to the frequency converter via serial port command or PWM output to control the compressor motor to run at the specified frequency. The controller records this value as the current cycle frequency status.

[0035] After the specified frequency is run, a running label variable is constructed. The running label variable is an enumerated value that represents the execution context of the current frequency adjustment behavior.

[0036] Furthermore, the running label variables include:

[0037] If the frequency adjustment command is 0, it means that the frequency of this cycle has not been adjusted and is marked as held.

[0038] If the frequency adjustment command is greater than 0 and the frequency modulation tendency score is greater than or equal to the preset threshold, it is marked as frequency upsampling - reasonable;

[0039] If the frequency adjustment command is greater than 0 and the frequency modulation tendency score is less than a preset threshold, it is marked as up-critical.

[0040] If the frequency adjustment command is less than 0 and the frequency tuning tendency score is less than or equal to the negative preset threshold, it is marked as frequency reduction - reasonable;

[0041] If the frequency adjustment command is less than 0 and the frequency modulation tendency score is less than the negative preset threshold, it is marked as frequency reduction-critical.

[0042] In another aspect of the invention, a compressor frequency noise reduction system based on heating rate feedback is provided, the system comprising:

[0043] Data acquisition module: used to acquire the current inlet water temperature, target temperature, compressor frequency, noise intensity and actual temperature rise rate of the target compressor in order to construct a state input vector;

[0044] Thermal impedance estimation module: used to calculate the temperature difference target based on the current inlet water temperature of the target compressor, and to calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency;

[0045] The listening assessment module is used to construct a listening assessment model that includes a frequency penalty term and a trend correction term by dynamically coupling the noise intensity and the thermal path response impedance, and to generate a listening assessment score and a listening risk increment to determine whether to allow the compressor to increase its frequency or maintain the current frequency.

[0046] Frequency modulation control module: used to weight and fuse the thermal path response impedance with the listening score to obtain a frequency modulation tendency score, and generate a frequency adjustment command based on the comparison of the frequency modulation tendency score with a preset response threshold;

[0047] Execution feedback module: used to apply the frequency adjustment command to the actual equipment, complete the operation of compressor frequency conversion adjustment and noise adjustment, and collect the behavior feedback status after the system response, generate running label variables, which are used as part of the state input vector of the controller in the next cycle to perform control closed loop.

[0048] The beneficial technical effects of the present invention are at least as follows:

[0049] This invention first collects core variables such as water temperature, temperature rise rate, noise intensity, and compressor frequency to form a state vector for the current cycle. Based on this, a thermal path response impedance is constructed to identify the degree of system response to the target temperature per unit time after a frequency change, thereby avoiding control misjudgments caused by system thermal inertia. Furthermore, the system quantifies the subjective discomfort risk caused by the current frequency and noise structure by calculating the user's listening score in real time, overcoming the shortcomings of traditional methods that only judge quietness based on decibels. Next, the control strategy uses these two feedback variables as inputs to a unified scoring function and designs a frequency modulation suppression mechanism to prevent system oscillations caused by repeated frequency adjustments, outputting commands to increase, decrease, or maintain the frequency.

[0050] The instruction is actually executed in each cycle and recorded as a behavior label, which serves as part of the subsequent state input, constructing a complete behavior-response closed loop. Through this scheme, the system can dynamically balance the frequency control strategy according to heat load requirements and user comfort thresholds at different operating stages, achieving dual optimization of thermal efficiency and noise suppression. This fundamentally solves the pain points of existing control methods in terms of response lag, auditory misjudgment, and frequency modulation instability. Attached Figure Description

[0051] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0052] Figure 1 This is a flowchart of a compressor frequency silent adjustment method based on heating rate feedback according to an embodiment of the present invention.

[0053] Figure 2 This is a framework diagram of a compressor frequency silent adjustment system based on heating rate feedback according to an embodiment of the present invention. Detailed Implementation

[0054] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0055] NTC: Negative Temperature Coefficient.

[0056] MEMS: Micro-Electro-Mechanical System.

[0057] PWM: Pulse Width Modulation.

[0058] ADC: Analog-to-Digital Converter.

[0059] like Figure 1 As shown in the figure, an embodiment of the present invention provides a compressor frequency noise reduction method based on heating rate feedback, the method comprising:

[0060] S1. Obtain the current inlet water temperature, target temperature, compressor frequency, noise intensity, and actual temperature rise rate of the target compressor to construct the state input vector.

[0061] Specifically, this step is used to collect key state variables that are highly relevant to control decisions during the current compressor operating cycle, and to construct a unified input state vector. The input includes five types of basic variables from sensor and controller feedback:

[0062] When the inlet water temperature The data is collected every 60 seconds by an NTC thermistor on the water path side and read through the controller's ADC port;

[0063] Previous cycle inlet water temperature From the controller's local cache;

[0064] Current target temperature T set : Configured by the user and transmitted to the controller via a communication interface (such as RS-485);

[0065] Current compressor frequency The signal is obtained in real time from the frequency converter through serial port or PWM signal decoding.

[0066] Current noise level The sound signal is collected by a MEMS microphone module installed near the compressor, and the controller calculates the decibel value according to a fixed weighted average algorithm.

[0067] Furthermore, to determine whether the system is currently operating effectively for heating, a quantitative sensing mechanism for changes in heat output after compressor frequency adjustment needs to be established. This step involves collecting the inlet water temperature for the current cycle. Inlet water temperature compared to the previous cycle The difference is calculated internally by the controller, and this difference is defined as the temperature rise rate for this cycle. and All data are collected by NTC thermistors inside the water pipes at a fixed control cycle; the default sampling cycle of the control system is 60 seconds. This temperature rise rate... The subsequent construction of the thermal path response impedance Z in this invention is... t This is a necessary input that reflects whether the compressor's current frequency setting has substantially improved the system's heat exchange process. Unlike traditional control methods that rely solely on absolute temperature difference, this periodic incremental sensing method can more promptly identify the specific impact of frequency changes on the heating rate, effectively avoiding misjudgments due to response lag.

[0068] Regarding user auditory feedback, the system incorporates the noise intensity of the current cycle. This serves as the basic input for noise level assessment. The variable is generated by a MEMS microphone module installed near the compressor, which acquires the sound signal. The controller then uses a fixed A-weighted filtering algorithm to weight the sound signal, ultimately producing a scalar value representing the ambient sound pressure level for that period. The system sampling time is 1 second, and the output value is refreshed periodically according to the controller's internal clock.

[0069] During this cycle, in order to meet the input requirements of subsequent thermal response judgment and silent frequency tuning strategy, the system combines the currently acquired and calculated key variables to construct a complete state input vector X. t The vector consists of five variables, namely the current inlet water temperature. User-defined target temperature T set Current compressor frequency Noise intensity calculated in real time by sound sensors and the rate of temperature rise calculated from the current and previous cycle water temperature difference.

[0070] These variables each serve to represent the state in different dimensions. and Describes the current heating status of the heat pump system in this cycle, T set Temperature targets that reflect user needs; This indicates the current frequency modulation control action, which belongs to the control state at the equipment level; while These are key parameters used to assess the potential auditory interference that the current operation may cause to users. These five categories of indicators are combined into a state input vector X. t This not only achieves a unified expression in data structure, but also establishes the necessary data foundation for subsequent estimation of thermal path response impedance and calculation of listening scores.

[0071] This step outputs two variables: the state input vector X. t Actual temperature rise rate

[0072] S2. Calculate the target temperature difference based on the current inlet water temperature of the target compressor, and calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency, to identify whether the heating effect is effective after the frequency change.

[0073] Specifically, this step aims to address a core pain point in compressor frequency regulation: a significant delay in heating response after frequency increases, especially during low-temperature startup or the initial heating phase under heavy load, where water temperature changes often fail to reflect the effectiveness of frequency adjustments in a timely manner. If the control logic relies solely on the instantaneous temperature rise rate, it can easily misjudge a slow temperature rise within a short period as an excessively high frequency, leading to premature frequency reduction, insufficient heating, repeated starts, and even system oscillations. This step is based on the state vector X output from the first step. t and rate of temperature rise A dynamic response index Z is proposed. t It is used to quantify the relationship between the distance of the current system temperature from the target temperature and the thermal response per unit time, and introduces two additional adjustment terms so that the impedance can not only reflect the thermal response, but also the frequency usage cost and the stability of the temperature rise trend.

[0074] The first part of this indicator measures the approximate time required for the water temperature to rise from the current level to the user-set temperature under the current system conditions. Essentially, it compares the current target temperature difference with the actual rate of temperature rise. This indicates the user-set target temperature T. set With current inlet water temperature The difference between the two values, calculated in real time from the input of the wired controller and the data from the water temperature sensor, represents the level of heat that the system still needs to replenish. Correspondingly, The actual temperature rise rate for the current cycle is indicated by the controller reading the current cycle data. Compared with the previous cycle The difference is calculated to reflect the heating rate per unit time after the compressor starts running.

[0075] By comparing these two variables, the system can obtain the approximate response time required for the current heat pump system to achieve the temperature target at this frequency. To avoid judgment distortion or calculation abnormalities caused by extremely low temperature rise rates, a very small constant term is introduced to ensure the stability of the judgment mechanism even during the initial startup phase or thermal response fluctuation cycle. If the current temperature difference is small and the temperature rise rate is high, the calculated required response time will be very short, indicating that the compressor's heating efficiency at the current frequency is high, and the system can consider entering a maintenance or energy-saving state. However, if the temperature rise rate is very low, even if the temperature difference is not large, a longer response time will be calculated, indicating that the current frequency increase has not been effective, or that the system has problems such as insufficient refrigerant or high thermal resistance, and it is not advisable to reduce the frequency too early.

[0076] In actual operation, while increased compressor frequency usually means faster heating, it also leads to a significant increase in energy consumption and noise. More importantly, in some high-frequency operating states, the water temperature rise does not increase as significantly as expected, exhibiting a high-frequency, low-efficiency operating condition. If the controller does not recognize this state, the system may remain in a high-energy-consumption operating mode for an extended period, resulting in neither efficiency gains nor a positive user experience. To avoid this situation, the system calculates the thermal path response impedance Z... t At that time, a correction term related to the current frequency was introduced to reflect the impact of high-frequency operating costs.

[0077] Specifically, the system reads the current compressor frequency. And compare it with the maximum operating frequency F set at the time of manufacture. max A proportional conversion is performed to obtain a value reflecting the relative intensity of the current operating frequency. A larger ratio indicates that the compressor is operating under high load. In the overall construction of the response impedance, this frequency ratio is multiplied by an adjustment weighting coefficient λ1 and accumulated as an additional cost term to Z. t The result of this treatment is that when the system operates at a high frequency but does not exhibit sufficient temperature rise response, Z t The value will rise significantly, prompting subsequent control logic to tend to maintain the current frequency or trigger frequency reduction in advance. This mechanism essentially constructs a frequency penalty mechanism, effectively suppressing high-frequency inertia and guiding the system to operate with the goal of efficient heating and minimum necessary frequency, avoiding undesirable operating conditions where energy waste and noise interference coexist.

[0078] In order for the system to not only sense the current thermal response state, but also to judge the trend changes in thermal response, this step involves constructing the thermal path response impedance Z. t At this time, a dynamic term reflecting the temperature rise trend was introduced. In specific operation, the controller records the temperature rise rate of the previous cycle through an internal cache. The rate of temperature rise in the current cycle By comparing the two cycles, we can obtain the temperature rise variation between them. This difference indicates whether the current heating efficiency is trending upward or downward. For example, if the water temperature increased by 0.6℃ in the previous cycle, but only by 0.3℃ in the current cycle, it means that the heating trend is weakening and the system's thermal response is deteriorating. This trend information is crucial for determining whether to continue maintaining the current frequency or appropriately reduce the frequency earlier.

[0079] In the calculation, the absolute value of this trend change will be included in Z. t In its composition, it serves as a response attenuation compensation term. If a slowdown in the thermal response is detected, i.e. compared to If the decrease is significant, then this term will amplify the overall impedance value and increase Z. t Based on the output, the system determines that the thermal response may be about to saturate and that continued high-frequency operation is not advisable. Conversely, if the current temperature rise rate is higher than the previous cycle, it indicates a good thermal response trend, and this term is close to zero, having no actual interference with the total impedance. This mechanism enables the system to identify in real time whether the current thermal efficiency is improving or deteriorating, thereby providing trend judgment support in the frequency modulation strategy, reducing the controller's dependence on isolated state values, and enhancing its responsiveness to the system's dynamic behavior.

[0080] The final thermal path response impedance is constructed in the following complete form:

[0081]

[0082] in:

[0083] The first item indicates how long it takes to reach the target temperature, which is the thermal response intensity;

[0084] The second item indicates whether the current frequency is too high, which is a frequency burden;

[0085] The third item indicates whether the current warming trend is slowing down, or whether it is a warming trend.

[0086] This step outputs two variables: one is the thermal path response impedance Z. t The first is used to determine whether to increase the frequency, maintain the current level, or enter the diagnostic buffer; the second is the temperature difference target. Used to determine whether the temperature has been stabilized (i.e., Z). t (Approaching 0).

[0087] S3. By dynamically coupling the noise intensity and the thermal path response impedance, a listening score model containing a frequency penalty term and a trend correction term is constructed to generate a listening score and a listening risk increment, so as to determine whether the compressor is allowed to increase its frequency or maintain the current frequency.

[0088] Specifically, this step is used to construct a user hearing evaluation index during compressor operation. This scoring mechanism will serve as the mute feedback branch in the frequency modulation control logic, in conjunction with the thermal path response impedance Z in step two. t Together, they decide whether to allow the compressor to increase its frequency or maintain the current frequency. The problem it addresses is that traditional air-source heat pump systems typically rely solely on decibel thresholds for noise assessment, such as... It is considered too noisy. The assumption of quiet operation ignores the non-linear impact of frequency-induced sound structure changes (such as resonance, high-frequency howling, and low-frequency booming) on ​​user hearing during compressor operation. Especially in the mid-frequency range (e.g., 65–75Hz) and low-frequency range (35–45Hz), although the noise level may be within safe decibel levels, it can still cause significant discomfort in quiet nights, enclosed spaces, or during continuous high-frequency operation. This misjudgment of low intensity but high perception means that even if the system does not trigger a physical sound pressure warning when the frequency increases, user discomfort will lead to complaints or interruptions in use. Therefore, this step plays a crucial role in the overall invention, forming an efficiency-comfort control dual with thermal impedance.

[0089] Traditional scoring functions mostly use a decibel threshold model, while this step innovatively introduces a heat load adjustment function φ(Z). t By dynamically adjusting the weight of the sound discomfort penalty term in the scoring formula, adaptive shaping of the current FM safety boundary is achieved. The scoring function is defined as follows:

[0090]

[0091] Where: σ(·) is the standard Sigmoid function, which makes the scoring result controllable between (0,1), which facilitates the classification of frequency modulation control levels; The current noise level is measured by a MEMS microphone using an A-weighted filter, reflecting the overall sound pressure level. This is the normalized value of the current frequency at the compressor's maximum frequency (e.g., 100Hz), reflecting the structural superposition trend of sound as the speed changes. The target temperature difference for the current system; α1, α2, and α3 are the weighting coefficients for the corresponding terms;

[0092] φ(Z t ) is the thermal impedance adjustment function, used to dynamically scale user tolerance, and is defined as:

[0093]

[0094] Where β is an empirical coefficient, Z t Z represents the thermal response impedance from step two. tThe larger the value, the less complete the heating process is; therefore, the system's noise tolerance should be increased. φ(Z) t If Z approaches 1; conversely, if Z approaches 1, then... t →0 indicates that the target temperature is approaching, φ(Z) t When the temperature drops to 0, the system should quickly reduce its frequency to enter the comfort maintenance zone. The significance of this design lies in introducing the dynamic state of thermal response into the hearing tolerance model, thereby achieving strategic coupling between thermal load and subjective perception, rather than treating them as two separate objectives.

[0095] This step outputs two items: listening score. Used as a comfort constraint input in the next step of the frequency modulation control strategy; auditory risk increment. By comparing the score with the previous cycle, the trend of changes in hearing risk can be determined, and a rapid response mechanism can be triggered when the score drops sharply.

[0096] S4. The thermal path response impedance and the listening score are weighted and fused to obtain the frequency modulation tendency score. The frequency adjustment command is generated by comparing the frequency modulation tendency score with the preset response threshold.

[0097] Specifically, in this invention, the control system not only determines whether frequency boosting is currently needed, but also dynamically determines whether frequency boosting is permissible. In other words, if the thermal response is slow but the user is already at the noise tolerance limit, the system should avoid blindly boosting the frequency; conversely, if the thermal response is good but there is still a margin for heating, the frequency can be appropriately boosted within the perceptible range to improve efficiency. Therefore, the logical structure of this step must allow the system to make balanced trade-offs rather than simple decisions, which is the source of the ingenuity of this solution.

[0098] Furthermore, to achieve the above objectives, we first define the frequency modulation tendency scoring function R. t It will reduce the thermal response impedance Z t Listening score Perform joint modeling:

[0099]

[0100] Among them: Z t Z is the output variable of step two, reflecting the estimated time required to reach the set temperature at the current frequency; max It is the maximum thermal resistance threshold set empirically, and the value is usually set to 25 for normalization.

[0101] η t It is the dynamic coefficient of heat load, the value of which is determined by the current target temperature difference. The maximum control temperature difference range (i.e., T) max -T min The ratio between T and T is calculated. set It is the target temperature set by the user. The difference between the current actual inlet water temperature and this temperature is... When the temperature difference is large, it indicates that the system still has a large amount of heat to be replenished. The controller should prioritize frequency upsampling to quickly meet the heating target, while ensuring that noise does not increase excessively. This coefficient plays a dynamic amplification role in the joint frequency modulation score. t The effect of thermal resistance means that when the heat load demand is high, the frequency modulation strategy tends to prioritize efficiency.

[0102] Meanwhile, to accurately measure whether the current compressor operation has caused perceptible auditory discomfort to the user, this step continues to use the user hearing score output in step three. The rating ranges from 0 to 1. A smaller value indicates that the user is more likely to perceive noise interference from the compressor, and is therefore converted into a noise risk item within the controller. This is used to penalize high-noise operation. Based on this, to enable the system to automatically adjust its noise tolerance under different usage scenarios, a hearing weighting adjustment factor ω is introduced. t The controller automatically sets this value based on system operating conditions, such as night mode or quiet residential mode, ω. t It will be automatically increased to strengthen the suppression of noise risks; and in the initial stage of equipment startup, or in low-temperature high-load startup scenarios, ω t The noise level will be lowered to allow the system to temporarily increase to a certain extent in exchange for faster heating.

[0103] Furthermore, to avoid instability caused by frequent frequency increases and decreases near the scoring threshold, this step introduces a frequency modulation suppression variable, named ΔR, into the frequency modulation decision logic. t This variable is used to measure the current FM rating R. t R score from the previous control period t-1 The degree of difference between them. When the difference exceeds a set sensitivity threshold θ (e.g., 0.05), the system will consider the frequency modulation trend to be unstable, with instantaneous fluctuations caused by environmental disturbances, sensor jitter, or user behavior. At this time, the frequency modulation behavior will be suspended, and the current frequency will remain unchanged; while when the score change is small, i.e., ΔR t If the value is below this threshold, the system considers the trend to be continuous and reliable, and can adjust the frequency based on the current score. This mechanism essentially constitutes a frequency-controlled, repeatedly switching damper to delay the execution of the strategy under edge conditions, thereby improving the stability of the system response and the consistency of user comfort perception.

[0104] During the specific generation of the frequency modulation command, the controller first determines the current score R. t Does it exceed the set response threshold δ for frequency upsampling or downsampling, for example, set to 0.1; if R tGreater than δ, and the difference ΔR between the score of this period and the score of the previous period. t If the value is less than θ, the controller outputs a positive frequency adjustment command. Represents frequency upsampling operation; if R t If R is less than -δ and the score change is still within the stable range, then a negative frequency adjustment command is output, representing a frequency reduction behavior; if R t If the score is within the threshold range, or if the score fluctuates too much to meet the stability condition, the system will not adjust the frequency. The value is 0. The output adjustment step size is a fixed value, named γ, for example, it can be set to 2Hz, to ensure that the frequency modulation response rate is within the range allowed by the physical device.

[0105] This step outputs two data items: frequency adjustment command. The controller sends rise / fall / hold commands to the frequency converter module; frequency regulation tendency score R t It is used for frequency regulation log recording and trend comparison in the next cycle.

[0106] S5. Apply the frequency adjustment command to the actual equipment to complete the operation of compressor frequency conversion adjustment and noise adjustment, and collect the behavior feedback status after the system response to generate running label variables as part of the state input vector of the controller in the next cycle, so as to perform control closed loop.

[0107] Specifically, this step is used to process the frequency adjustment command generated by the controller in the previous cycle. Applied to actual equipment, it executes the variable frequency control operation of the compressor, collects the feedback status of the core control behavior after the system response, and generates a labeled variable. As a component of the controller's state vector for the next cycle.

[0108] Furthermore, before executing the frequency modulation command, the system reads the current frequency. (Feedback from the frequency converter control module), then the target frequency is calculated:

[0109]

[0110] F in this formula min and F max These are the operating frequency boundaries set for the device (e.g., 25Hz and 100Hz). This process ensures that frequency commands do not exceed these boundaries. The final... The signal is transmitted to the frequency converter via serial port commands or PWM output to control the compressor motor to run at a specified frequency. The controller records this value as the current cycle frequency status.

[0111] Furthermore, after the frequency is distributed, in order to maintain the traceability of system operation and the connectability of subsequent logic, this step constructs basic operation label variables. This variable is an enumeration value representing the execution context of the current frequency adjustment behavior. Its definition is as follows:

[0112] like This indicates that the frequency for this cycle has not been adjusted and is marked as "hold".

[0113] like And R t ≥δ, marked as "up-frequency - reasonable";

[0114] like And R t <δ, marked as "frequency up-critical";

[0115] like And R t ≤-δ, marked as "Frequency Reduction - Reasonable";

[0116] like And R t >-δ, marked as "frequency reduction-critical".

[0117] Here, δ is the preset frequency modulation threshold in step four (e.g., δ = 0.1), representing the lower bound of the system's allowable adjustment. This design enables the controller to identify whether the current adjustment behavior is on the scoring edge, so that in the next cycle, in the state vector X... t+1 This can be utilized, for example, by setting up dead zone protection and preventing short-term repetitive frequency modulation.

[0118] like Figure 2 As shown, another embodiment of the present invention provides a compressor frequency noise reduction system based on heating rate feedback, the system comprising:

[0119] Data acquisition module 301: used to acquire the current inlet water temperature, target temperature, compressor frequency, noise intensity and actual temperature rise rate of the target compressor, in order to construct a state input vector;

[0120] Thermal impedance estimation module 302: used to calculate the temperature difference target based on the current inlet water temperature of the target compressor, and to calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency;

[0121] The hearing assessment module 303 is used to construct a hearing assessment model containing a frequency penalty term and a trend correction term through the dynamic coupling of the noise intensity and the thermal path response impedance, and to generate a hearing assessment score and a hearing risk increment to determine whether the compressor is allowed to increase its frequency or maintain the current frequency.

[0122] Frequency modulation control module 304: used to weight and fuse the thermal path response impedance and the listening score to obtain a frequency modulation tendency score, and generate a frequency adjustment command based on the comparison between the frequency modulation tendency score and a preset response threshold.

[0123] Execution feedback module 305: used to apply the frequency adjustment command to the actual equipment, complete the operation execution of compressor frequency conversion adjustment and silent adjustment, and collect the behavior feedback status after the system response, generate running label variables, and use them as part of the state input vector of the controller in the next cycle to perform control closed loop.

[0124] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0125] In addition, for technical details not described in detail in this embodiment, please refer to the parameter operation method provided in any embodiment of the present invention, which will not be repeated here.

[0126] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0127] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0128] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0129] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for compressor frequency noise regulation based on heating rate feedback, characterized in that, The method includes: S1. Obtain the current inlet water temperature, target temperature, compressor frequency, noise intensity, and actual temperature rise rate of the target compressor to construct the state input vector; S2. Calculate the target temperature difference based on the current inlet water temperature of the target compressor, and calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency, to identify whether the heating effect is effective after the frequency change. S3. By dynamically coupling the noise intensity and the thermal path response impedance, a listening score model containing a frequency penalty term and a trend correction term is constructed to generate a listening score and a listening risk increment to determine whether the compressor should be allowed to increase its frequency or maintain the current frequency. S4. The thermal path response impedance and the listening score are weighted and fused to obtain the frequency modulation tendency score, and a frequency adjustment command is generated based on the comparison between the frequency modulation tendency score and the preset response threshold. S5. Apply the frequency adjustment command to the actual equipment to complete the operation of compressor frequency conversion adjustment and noise adjustment, and collect the behavior feedback status after the system response to generate running label variables as part of the state input vector of the controller in the next cycle, so as to perform control closed loop.

2. The compressor frequency noise reduction method based on heating rate feedback according to claim 1, characterized in that, S1 specifically includes: The water temperature of the previous cycle and the current inlet water temperature are collected by an NTC thermistor on the water circuit side. The compressor frequency is fed back in real time by the frequency converter; A MEMS microphone module is used to collect sound signals, and the controller calculates the decibel value as the noise intensity using a fixed weighted average algorithm. Calculate the difference between the current inlet water temperature and the water temperature of the previous cycle, and calculate the actual temperature rise rate of the current cycle based on the difference; The state input vector is constructed by combining the water temperature of the previous cycle, the current inlet water temperature, the compressor frequency, the noise intensity, and the temperature rise rate.

3. The compressor frequency noise reduction method based on heating rate feedback according to claim 1, characterized in that, S2 specifically includes: Obtain the target temperature of the target compressor set by the user, and calculate the difference between the target temperature and the current inlet water temperature to obtain the temperature difference target; The thermal path response impedance is calculated based on the current inlet water temperature, target temperature rise rate, compressor frequency, and maximum compressor frequency; if the thermal path response impedance is closest to 0, then the system enters a constant temperature state.

4. The compressor frequency noise reduction method based on heating rate feedback according to claim 1, characterized in that, S3 specifically includes: Based on the noise intensity, compressor frequency, maximum compressor frequency, heat load adjustment function, and temperature difference target, a hearing score model is constructed to obtain a hearing score. The heat load adjustment function is calculated based on the thermal path response impedance and is used to dynamically scale the user's tolerance. If the thermal path response impedance is at its maximum, it indicates that heating has not yet been completed and the system's noise tolerance should be enhanced. The value of the heat load adjustment function is closest to 1. The hearing score ranges from 0 to 1, with a smaller value indicating that the user is more likely to perceive noise interference from the compressor. The incremental hearing risk is calculated based on the current hearing score and the hearing score of the previous period.

5. A method for compressor frequency noise reduction based on heating rate feedback according to claim 2, characterized in that, The noise intensity was measured using A-weighted filtering.

6. The compressor frequency noise reduction method based on heating rate feedback according to claim 1, characterized in that, S4 specifically includes: Based on the thermal path response impedance and the preset maximum thermal path response impedance, combined with the listening score, the frequency modulation tendency score is calculated. The frequency modulation suppression variable is calculated based on the current frequency modulation propensity score and the frequency modulation propensity score of the previous period, which is used to measure the degree of difference between the current frequency modulation score and the frequency modulation propensity score of the previous period. The frequency adjustment command is generated based on the frequency modulation suppression variable and is used as an up command, down command or maintenance command issued by the controller to the frequency converter module.

7. A compressor frequency noise reduction method based on heating rate feedback according to claim 6, characterized in that, The step of generating control commands based on the frequency modulation suppression variable, used as up commands, down commands, or maintenance commands issued by the controller to the frequency converter module, specifically includes: When the frequency modulation suppression variable exceeds the set sensitivity threshold, the frequency modulation trend is considered unstable and there are instantaneous fluctuations. Therefore, the frequency modulation behavior is paused and the current frequency is kept unchanged. When the frequency modulation suppression variable is less than the set sensitivity threshold, the trend is considered continuous and reliable. Therefore, the frequency is increased or decreased based on the current score.

8. The compressor frequency noise reduction method based on heating rate feedback according to claim 1, characterized in that, S5 specifically includes: The upper and lower frequency boundaries set by the acquisition device; Calculate the target frequency by combining the upper and lower operating frequency boundaries set by the device, the frequency adjustment command, and the compressor frequency; The target frequency is transmitted to the frequency converter via serial port command or PWM output to control the compressor motor to run at the specified frequency. The controller records this value as the current cycle frequency status. After the specified frequency is run, a running label variable is constructed. The running label variable is an enumerated value that represents the execution context of the current frequency adjustment behavior.

9. A method for compressor frequency noise reduction based on heating rate feedback according to claim 8, characterized in that, The running label variables include: If the frequency adjustment command is 0, it means that the frequency of this cycle has not been adjusted and is marked as held. If the frequency adjustment command is greater than 0 and the frequency modulation tendency score is greater than or equal to the preset threshold, it is marked as frequency upsampling - reasonable; If the frequency adjustment command is greater than 0 and the frequency modulation tendency score is less than a preset threshold, it is marked as up-critical. If the frequency adjustment command is less than 0 and the frequency tuning tendency score is less than or equal to the negative preset threshold, it is marked as frequency reduction - reasonable; If the frequency adjustment command is less than 0 and the frequency modulation tendency score is less than a negative preset threshold, it is marked as frequency reduction-critical.

10. A compressor frequency noise control system based on heating rate feedback, characterized in that, The system includes: Data acquisition module: used to acquire the current inlet water temperature, target temperature, compressor frequency, noise intensity and actual temperature rise rate of the target compressor in order to construct a state input vector; Thermal impedance estimation module: used to calculate the temperature difference target based on the current inlet water temperature of the target compressor, and to calculate the thermal path response impedance in combination with the current inlet water temperature, compressor frequency, and maximum compressor frequency; The listening assessment module is used to construct a listening assessment model that includes a frequency penalty term and a trend correction term by dynamically coupling the noise intensity and the thermal path response impedance, and to generate a listening assessment score and a listening risk increment to determine whether to allow the compressor to increase its frequency or maintain the current frequency. Frequency modulation control module: used to weight and fuse the thermal path response impedance with the listening score to obtain a frequency modulation tendency score, and generate a frequency adjustment command based on the comparison of the frequency modulation tendency score with a preset response threshold; Execution feedback module: used to apply the frequency adjustment command to the actual equipment, complete the operation of compressor frequency conversion adjustment and noise adjustment, and collect the behavior feedback status after the system response, generate running label variables, which are used as part of the state input vector of the controller in the next cycle to perform control closed loop.

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