A method and system for electromagnetic interference suppression of a domestic appliance

Abstract

This invention discloses a method and system for suppressing electromagnetic interference in household appliances, comprising: real-time acquisition of electromagnetic noise signals and switching action data of each functional module to obtain the noise generation time sequence and intensity distribution characteristics; identification of potential risk periods where noise from different modules overlaps on the time axis based on features, and assessment of the superimposed interference intensity; generation of a high-precision clock reference signal using a unified reference clock source; acquisition of response delay parameters of each module, and, with the goal of reducing interference superposition during risk periods, generation of a synchronization scheduling scheme for adjusting the switching times of each module through a synchronization coordination algorithm based on the clock signal, delay parameters, and risk periods; distribution of delay compensation instructions according to the scheme, with each module executing the adjusted action according to the unified clock and instructions; and re-acquiring noise data after execution to assess the dispersion effect. This invention can actively disperse electromagnetic interference energy and reduce peak interference through time-series coordinated scheduling, achieving dynamic electromagnetic compatibility management.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic interference suppression technology for household appliances, and in particular to a method and system for suppressing electromagnetic interference in household appliances. Background Technology

[0002] With the rapid development of intelligence and integration in home appliances, the various functional modules integrated within them, such as motors, digital control circuits, and power conversion units, are becoming increasingly complex. These modules generate electromagnetic noise with distinct characteristics during operation. When multiple modules start and stop asynchronously due to functional requirements, the resulting electromagnetic noise can easily overlap on the time axis, forming a strong, instantaneous interference peak. This superimposed interference not only seriously threatens the stable operation of the appliance's own control system, leading to performance degradation or malfunctions, but may also pollute the power grid or the electromagnetic environment through conduction or radiation, affecting the normal operation of other nearby electronic devices. Therefore, effectively managing and suppressing such electromagnetic interference has become a key challenge in improving the reliability of home appliances and ensuring electromagnetic compatibility standards are met.

[0003] Current mainstream solutions in the industry mostly focus on optimizing spatial layout or frequency domain, such as using metal shielding housings, adding filters, or optimizing printed circuit board traces to block or attenuate interference propagation paths. These methods have good suppression effects on steady-state or isolated interference sources. However, they have a fundamental limitation: they fail to fully consider the instantaneous interference peaks caused by the concurrent and asynchronous operation of multiple internal functional modules during the actual dynamic operation of home appliances. Due to the lack of global insight and proactive coordination of the operating timing of each module, the electromagnetic noise generated by different modules exhibits a disordered convergence effect in the time dimension, causing the interference intensity to increase dramatically at specific moments. This puts enormous pressure on static, passive suppression measures, often resulting in excessive design margins, increased costs, or suppression failure under harsh operating conditions. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the shortcomings of the prior art in which electromagnetic interference is concentrated and superimposed in time due to the asynchronous operation of multiple modules inside home appliances, forming instantaneous peaks, and static suppression measures are difficult to deal with this dynamic problem. The present invention provides a method and system for suppressing electromagnetic interference in home appliances, which can actively disperse electromagnetic interference energy on the time axis and reduce interference peaks by establishing a unified time reference, identifying interference risk periods, and selectively coordinating and scheduling modules with timing adjustment potential, while ensuring the normal operation of core synchronization functions, and achieving efficient and practical dynamic electromagnetic compatibility management.

[0005] To address the aforementioned technical problems, this invention provides a method for suppressing electromagnetic interference from household appliances, comprising the following steps:

[0006] Real-time acquisition of electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances, to obtain the noise generation time sequence and intensity distribution characteristics;

[0007] Based on time sequence and intensity distribution characteristics, potential risk periods where noise from different functional modules overlaps on the time axis are identified, and the intensity of superimposed interference is assessed.

[0008] A high-precision clock reference signal is generated using a unified reference clock source, and clock reference signals are configured for each functional module.

[0009] The response delay parameters of each module to control commands are obtained. With the goal of eliminating or reducing interference superposition during potential risk periods, a synchronization coordination algorithm is used to calculate and generate a synchronization scheduling scheme that adjusts the delay of the switching action time of each module based on the clock reference signal, response delay parameters and potential risk periods.

[0010] According to the synchronous scheduling scheme, corresponding delay compensation instructions are distributed to the control units of each functional module; each functional module executes the adjusted switching action based on the clock reference signal and the delay compensation instructions.

[0011] After executing the synchronization scheduling scheme, electromagnetic noise distribution data is collected again, and the dispersion effect of interference superposition is evaluated based on the collected data.

[0012] In one embodiment of the present invention, electromagnetic noise signals and corresponding switching action data generated by various functional modules of a household appliance are collected in real time to obtain the noise generation time sequence and intensity distribution characteristics, including:

[0013] Configure corresponding current sensors and voltage differential probes for multiple functional modules inside the home appliance to form a sensor array; set up a central acquisition unit based on a unified high-frequency clock to generate synchronous acquisition trigger pulses, and send them to each sensor in the sensor array and the control signal monitoring points of each module.

[0014] The central acquisition unit receives analog noise signals from sensors and switch level signals from monitoring points. When any switch level signal changes, the central acquisition unit immediately takes the moment of change as a reference point and extracts a segment of noise analog signal with a predetermined time length before and after it. This segment of signal is marked as a noise characteristic segment associated with the switch action.

[0015] Determine the start and end times of the noise characteristic segment, and calculate the average and peak values ​​of the signal amplitude within the noise characteristic segment, which are respectively used as the steady-state intensity characteristics and transient intensity characteristics of the noise event.

[0016] In chronological order, the generation time, steady-state intensity characteristics and transient intensity characteristics of all noise events generated by multiple functional modules in multiple working cycles are combined and arranged to generate a noise generation time sequence and intensity distribution characteristic data packet.

[0017] In one embodiment of the present invention, background noise stripping is further included, comprising:

[0018] During the silent period when the functional module is in a shutdown or standby state, the sensor array is activated to sample and collect the background environmental noise signal for a certain period of time as a background noise reference.

[0019] When extracting feature segments, short-time reference signals containing only background noise that are adjacent to the feature segments are extracted simultaneously. The extracted short-time reference signals are compared with the background noise model to dynamically estimate the instantaneous intensity level of the background noise at the current moment. From the original signal of the marked noise feature segments, the background noise component is subtracted according to the estimated intensity level to obtain the purified noise feature segments that reflect the noise of the functional module itself.

[0020] In one embodiment of the present invention, identifying potential risk periods where noise from different functional modules overlaps on the time axis and assessing the intensity of superimposed interference includes:

[0021] Based on the noise generation time sequence, the noise generation time periods of all functional modules are mapped onto a unified time axis; a continuous time interval in which the noise generation time periods of any two or more modules overlap in time is defined as a time conflict domain.

[0022] For each time conflict domain, the electromagnetic energy integral value represented by the noise intensity distribution characteristics of each functional module is calculated; the electromagnetic energy integral values ​​of all functional modules in the same conflict domain are combined to obtain the total interference energy estimate of the conflict domain.

[0023] Sort all time conflict domains from highest to lowest according to their total interference energy estimates. Select one or more time conflict domains with the highest total interference energy estimates from the sorted list from top to bottom, and identify them as potential risk periods that require time-series coordination.

[0024] In one embodiment of the present invention, calculating the electromagnetic energy integral value characterized by the noise intensity distribution features of each functional module includes:

[0025] For each functional module within the time conflict domain, the envelope curve of noise intensity changing with time within the corresponding time period is extracted from the electromagnetic noise signal acquired in real time.

[0026] For each extracted noise intensity envelope curve, mathematical integration is performed within the time range of its corresponding time conflict domain. The area enclosed by the noise intensity envelope curve and the time axis is calculated to characterize the total electromagnetic noise energy radiated or conducted by the functional module within the time conflict domain, which is used as the electromagnetic energy integral value.

[0027] In one embodiment of the present invention, after calculating the total interference energy estimate for a certain time conflict domain, the electromagnetic energy integral values ​​of each functional module in the conflict domain under the historical normal operating state and at the same time sequence position are retrieved as reference values, and the electromagnetic energy integral values ​​of each module obtained in this calculation are compared with the corresponding reference values:

[0028] When the deviation between the current electromagnetic energy integral value of a certain functional module and the reference value exceeds the preset fluctuation range, the noise envelope data of the functional module in the current collision domain is determined to be abnormal data; the functional module is marked as a module to be verified, and its calculated electromagnetic energy integral value is temporarily set to invalid.

[0029] For each marked module to be verified, based on the inherent patterns of its noise generation time sequence and intensity distribution characteristics, and combined with the noise data of other normal modules that have temporal correlation with it, the noise intensity envelope curve of the module to be verified in the collision domain is predictively repaired to complete or correct the contaminated part; based on the repaired envelope curve, the electromagnetic energy integral value of the module to be verified in the collision domain is recalculated.

[0030] In one embodiment of the present invention, a synchronization scheduling scheme is generated by calculating using a synchronization coordination algorithm to adjust the delay of the switching action times of each module, including:

[0031] The potential risk period is divided into multiple consecutive scheduling time units on the time axis, and the length of each scheduling time unit is an integer multiple of the period of the unified reference clock source signal.

[0032] For each functional module that will cause interference during the risk period, based on its functional constraints and the preset maximum allowable timing offset, determine the start and end boundary times that can be safely adjusted on the time axis before and after the risk period, forming the schedulable time window of the functional module.

[0033] The first optimization objective is to ensure that the interference time windows of any two functional modules do not overlap within the same scheduling time unit. When the first objective cannot be fully achieved, the second optimization objective is to ensure that the overlap occurs between functional modules with weaker interference intensity and to minimize the number of overlapping units and the total duration.

[0034] Using the clock reference signal as the absolute reference, an initial switching action offset is assigned to each functional module within its schedulable time window. According to the set optimization target, the offsets of each functional module are adjusted sequentially, and the adjusted timing is simulated. After each adjustment, the interference overlap state of all scheduled time units within the risk period is evaluated. This process is repeated until the final offset combination of each functional module that optimizes the overlap state is achieved.

[0035] In one embodiment of the present invention, the generation of the synchronization scheduling scheme further includes constructing a scheduling dependency table, specifically:

[0036] Based on the preset workflow between the functional modules of home appliances, all module action pairs with a mandatory sequential order are extracted; the logical dependency of each module action pair is converted into timing constraints based on a unified reference clock signal, which specifies the minimum safe delay time of subsequent module actions relative to the completion time of the preceding module actions.

[0037] All module action pairs and their corresponding timing constraints are integrated to generate a scheduling dependency table; this table serves as an auxiliary execution rule for the synchronous scheduling scheme, and together with the final offsets of each functional module, it forms a complete scheduling instruction set.

[0038] In one embodiment of the present invention, the synchronization scheduling scheme further includes an emergency recovery plan, the generation and execution of which include the following steps:

[0039] A set of monitoring conditions for triggering emergency recovery is pre-configured, including at least system-level fault signals, abnormal status of critical modules, or external safety commands;

[0040] For each functional module subject to timing adjustment in the synchronous scheduling scheme, a corresponding safe recovery path is preset, which defines the certain safe state that the functional module should switch to or the logical sequence that should be followed to fall back to the original timing when emergency recovery is triggered;

[0041] Establish and operate a high-priority monitoring and response mechanism; when any monitoring condition is met, immediately interrupt the current synchronization scheduling process, and forcibly distribute emergency control instructions to the functional modules according to the safe recovery path, so that they can perform state recovery operations.

[0042] To address the aforementioned technical problems, the present invention also provides a household appliance electromagnetic interference suppression system for implementing the above method, comprising:

[0043] The signal acquisition unit is configured to acquire electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances in real time, and obtain the noise generation time sequence and intensity distribution characteristics of each module based on the acquired data.

[0044] A risk analysis unit, connected to the signal acquisition unit, is configured to identify potential risk periods in which the noise of different functional modules overlaps on the time axis based on the noise generation time sequence and intensity distribution characteristics, and to assess the superimposed interference intensity during those periods.

[0045] The timing reference unit is configured to generate a high-precision clock reference signal using a unified reference clock source, and to configure the clock reference signal for each functional module.

[0046] The scheduling calculation unit is connected to the risk analysis unit and the timing reference unit respectively. It is configured to obtain the response delay parameters of each module to the control command, and with the goal of eliminating or reducing the interference superposition during the potential risk period, it calculates based on the clock reference signal, the response delay parameters and the potential risk period through a synchronization coordination algorithm to generate a synchronization scheduling scheme that adjusts the delay of the switching action time of each module.

[0047] The instruction distribution and execution unit is connected to the scheduling calculation unit and the timing reference unit, respectively, and is configured to distribute corresponding delay compensation instructions to the control units of each functional module according to the synchronous scheduling scheme; the control units of each functional module execute the adjusted switching action according to the clock reference signal and the delay compensation instructions.

[0048] The effect verification unit is connected to the signal acquisition unit and is configured to collect electromagnetic noise distribution data again through the signal acquisition unit after the instruction distribution and execution unit executes the synchronization scheduling scheme, and evaluate the dispersion effect of interference superposition based on the collected data.

[0049] The technical solution of the present invention has the following advantages compared with the prior art:

[0050] The electromagnetic interference suppression method for household appliances described in this invention aims to solve the electromagnetic interference problem of different functional modules of household appliances from a temporal perspective. By coordinating the switching times of each functional module, the electromagnetic noise is dispersed along the time axis, thereby avoiding energy concentration.

[0051] This invention achieves the following beneficial effects: First, by actively scheduling the timing, it fundamentally reduces the peak intensity of instantaneous interference caused by the overlapping operation of multiple modules, reducing the absolute dependence on passive backend measures such as filtering and shielding, and improving the overall margin and robustness of electromagnetic compatibility design. Second, the technical solution of this invention has dynamic adaptability, capable of risk assessment and scheduling optimization based on real-time collected data, thereby adapting to actual operating conditions such as appliance operating mode switching, load changes, and component parameter drift, ensuring long-term consistency of suppression effect. Finally, the implementation of the method of this invention mainly relies on system-level time base management and software algorithm scheduling, without the need for large-scale addition of hardware filtering or shielding components. While achieving efficient interference suppression, it effectively controls the material cost and complexity of the system, providing a feasible technical path for the development of high-performance, cost-effective smart home appliances. Attached Figure Description

[0052] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings, wherein:

[0053] Figure 1 This is a flowchart of the steps of the electromagnetic interference suppression method for household appliances of the present invention;

[0054] Figure 2 This is a flowchart of the steps in the present invention to obtain the noise generation time sequence and intensity distribution characteristics;

[0055] Figure 3 This is a flowchart of the steps for evaluating the intensity of superimposed interference according to the present invention;

[0056] Figure 4 This is a flowchart of the steps for generating a synchronization scheduling scheme according to the present invention;

[0057] Figure 5 This is a structural framework diagram of the electromagnetic interference suppression system for household appliances of the present invention. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0059] Reference Figure 1 As shown, the present invention provides a method for suppressing electromagnetic interference in household appliances. Its core lies in selectively and actively scheduling and dispersing the switching sequence of various functional modules inside the household appliance, thereby reducing the superposition peak value of electromagnetic interference in the time dimension.

[0060] The method of this invention first performs a data acquisition step, acquiring the electromagnetic noise signals of each functional module and their corresponding switching action timing data in real time. This step enables precise measurement and quantification of the timing characteristics of internal electromagnetic interference, providing an objective data foundation for subsequent analysis. Based on the acquired timing data, the method further extracts the generation time sequence and intensity distribution characteristics of noise from each module, and thereby identifies potential risk periods where noise signals from different modules overlap on the time axis, while simultaneously assessing the intensity of superimposed interference within these periods. This analysis process completes the transformation from raw data to specific risk location, clarifying the specific time window requiring intervention.

[0061] To implement coordinated control, the method employs a unified reference clock source to generate a high-precision clock reference signal, which is then configured in each functional module. This establishes a unified and reliable time reference for all controlled units, eliminating timing errors caused by differences in distributed clock sources. Based on this, the method obtains the inherent response delay parameters of each module to control commands and, by integrating the high-precision clock reference signal, response delay parameters, and identified potential risk periods, calculates a synchronization coordination algorithm with the goal of minimizing interference aggregation. This calculation outputs a specific synchronization scheduling scheme, specifying the delay adjustment required for the switching actions of each module.

[0062] Subsequently, according to the synchronous scheduling scheme, corresponding delay compensation instructions are distributed to the control units of each functional module. After receiving the unified clock reference signal and the specific delay compensation instructions, each module accurately executes the adjusted switching actions, thereby achieving timing reconstruction at the physical level. To verify and optimize the effect, after executing the scheduling scheme, the method will again collect the electromagnetic noise distribution data of the system, evaluate the dispersion effect of interference superposition, and calibrate and iterate the scheduling parameters based on the evaluation results to form a closed-loop optimization.

[0063] It should be noted that this method is applicable to smart home appliances that contain multiple functional modules that can work asynchronously or allow a certain timing offset (such as fan motors, water pump motors, auxiliary heaters, specific lighting units, etc.), such as refrigerators, washing machines, air conditioners, dishwashers, etc.

[0064] Taking a smart washing machine as an example, the washing machine contains functional modules such as a main washing motor, drain pump, water inlet valve, heater, and multiple sensors and control circuits. Among these modules, the main washing motor and drain pump have relatively independent working cycles and are allowed to make certain fine adjustments to their start and stop times within the time tolerance allowed by their functions; however, the coordinated operation of the water inlet valve and heater, as well as certain core sensor circuits that ensure the synchronization of the washing process, belong to parts that must be strictly synchronized or are extremely sensitive to timing deviations, and are not suitable for the timing adjustment method of this invention.

[0065] Existing technologies for interference analysis typically suffer from two fundamental flaws in their data acquisition methods: First, they employ independent and asynchronous acquisition methods for each module, resulting in the inability to precisely align the noise and switching timing data of different modules on the time axis, leading to inherent errors in subsequent analysis. Second, the acquisition process often involves continuous recording or simple threshold triggering, which not only generates massive amounts of redundant data but also fails to effectively distinguish between the noise of the target module and the complex background electromagnetic environment noise, resulting in distorted feature extraction.

[0066] To solve the above problems, refer to Figure 2 As shown, this invention further proposes a data acquisition method. First, sensor arrays are deployed in the power circuits and control nodes of key functional modules within the home appliance. A central processing unit generates a global synchronization trigger signal using a highly stable clock source. This design ensures absolute uniformity of the time reference for data acquisition across all channels, enabling subsequent millisecond- or even microsecond-level timing analysis. When the system detects a change in the switching control signal of any functional module, it immediately uses this moment as a reference to precisely extract the signal segment within a predetermined time window before and after the change from all synchronously buffered sensor data, marking it as a noise feature segment uniquely associated with that specific switching event. Data is captured only when a critical event occurs, thus eliminating data redundancy at the source. Subsequently, each feature segment is digitized, accurately identifying its start and end times as noise time labels, and calculating its amplitude statistical characteristics (such as mean and peak value), thereby converting the continuous analog signal into discrete, structured feature metadata containing "time-steady-state intensity-transient intensity". Finally, these feature metadata are organized into standardized data packets in chronological order. This entire process clarifies the previously ambiguous collected data into specific noise segment features acquired and structured through event triggering under a unified time base. It establishes a precise and traceable causal correspondence between switching events and noise features, laying the only reliable data foundation for accurate interference timing analysis in dynamic environments.

[0067] However, even with the aforementioned precise acquisition scheme, in real-world home appliance operating environments, the signals captured by sensors are still a mixture of target noise and background electromagnetic noise. The background noise sources are complex and may vary over time; without processing, it will severely contaminate the extracted features, leading to distorted subsequent risk assessments. Therefore, a dynamic background noise stripping step was further defined. During implementation, a background noise model is first established during the device's quiet period. Simultaneously, while extracting each target noise feature segment, a short-term background reference signal from the vicinity of that feature segment, excluding target module activity, is acquired. By comparing this reference signal with the quiet period model in real time, the instantaneous characteristics of the background noise at the current moment can be dynamically estimated, and this estimated background component is then digitally subtracted from the original feature segment signal. This process is not a simple static filtering but an adaptive real-time purification that effectively strips away background interference that fluctuates with grid load and environmental changes, ensuring that the final noise feature segment reflects the electromagnetic emission nature of the target module to the greatest extent possible.

[0068] Reference Figure 3 As shown, in order to achieve the process of "identifying potential risk periods and assessing the intensity of superimposed interference", this invention further constructs a systematic interference risk quantification assessment and data protection system, including: First, plotting the noise generation periods of all modules (i.e. from the noise start time to the end time) on a global time axis based on a unified clock, automatically scanning this time axis, and when it is found that the noise periods of any two or more modules overlap, the continuous overlapping interval is identified and defined as a time conflict domain.

[0069] Subsequently, the evaluation phase begins. For each identified temporal conflict domain, instead of relying solely on experience to judge its severity as in existing technologies, electromagnetic energy integral values ​​are calculated. Then, the energy integral values ​​of all functional modules are arithmetically synthesized (summed) to obtain a single quantitative indicator that characterizes the overall interference severity of the conflict domain—the total interference energy estimate. This value has a clear physical meaning and directly reflects the cumulative energy intensity of overlapping noise.

[0070] Finally, all identified conflict domains are globally ranked from highest to lowest based on their calculated total disturbance energy estimates. This ranking provides a clear priority list for subsequent scheduling decisions. Instead of attempting to resolve all conflicts, one or more conflict domains with the highest energy estimates (i.e., the most prominent risks) can be selected from the ranking list from top to bottom, based on currently available control resources (such as timing adjustment margins), and these are identified as potential risk periods that need to be prioritized for the current scheduling cycle.

[0071] In this embodiment, specific execution standards for the quantitative evaluation process are further proposed, defining how to calculate the integral value of electromagnetic energy from the original signal. During implementation, for each functional module within the collision domain, the processing unit retrieves the original noise sampling data of the functional module within the corresponding time period in this domain from the cache. First, through digital signal processing (e.g., performing absolute value processing on the signal followed by low-pass filtering), the intensity envelope curve of the noise signal is extracted. This curve smoothly depicts the contour of the noise amplitude changing over time, filtering out high-frequency carrier details and focusing on the temporal distribution of energy.

[0072] Subsequently, discrete numerical integration (e.g., using the trapezoidal rule or Simpson's rule) is performed on the extracted envelope curve within the clearly defined start and end time range of the conflict domain. This operation essentially calculates the geometric area enclosed by the envelope curve and the time axis. This area value is physically proportional to the total electromagnetic noise energy radiated or conducted by the module during this time period. Using this area value as the electromagnetic energy integral value of the functional module has the advantage that it simultaneously considers the intensity and duration of the noise, providing a more comprehensive and accurate characterization of the potential hazard of a noise event than simply using peak or average values.

[0073] In practical engineering, even after background stripping, the collected noise data may still exhibit local anomalies due to extreme transient interference, instantaneous sensor saturation, or communication packet loss. Directly using this abnormal data to calculate energy would lead to distorted risk ranking. Therefore, this invention further introduces a data verification and self-healing mechanism based on historical benchmark comparison and intelligent predictive repair.

[0074] During implementation, the system maintains a module behavior knowledge base, which stores the energy integral values ​​and their statistical ranges (such as mean and variance) calculated multiple times by each functional module under historical normal operating conditions at typical operating points (same time sequence locations), serving as benchmark reference values. After completing the energy calculation for a new conflict domain, the integral values ​​of each functional module are compared with their corresponding historical benchmarks. If the calculated value of a certain functional module deviates significantly from its historical statistical range (e.g., exceeding ±3 standard deviations), its data is deemed abnormal, and the functional module is temporarily marked as pending verification. Its abnormal integral values ​​are isolated and not included in the current total energy synthesis.

[0075] Subsequently, predictive repair is initiated. The inherent patterns of the noise behavior of the module in the knowledge base (such as the noise envelope usually exhibiting an exponential decay pattern) are utilized, along with data from other normal modules that are strongly correlated with it. Algorithms (such as Kalman filter prediction based on the state-space model or interpolation based on association rules) are used to reconstruct the noise intensity envelope curve of the abnormal module in the conflict domain, complete or correct the distorted parts, and recalculate the energy integral value of the functional module based on the repaired envelope curve.

[0076] Finally, the previously invalidated outliers are replaced with the repaired and more reliable new integral values, and energy synthesis and risk ranking are re-executed. This closed-loop mechanism ensures that the output of the risk assessment engine maintains a high degree of robustness and reliability even when faced with imperfect data, avoiding a chain of decision-making errors caused by a single data anomaly.

[0077] Reference Figure 4 As shown, to achieve the "synchronous scheduling scheme," this application further provides the core operational logic and optimization objective of the synchronization coordination algorithm. In specific implementation, the selected potential risk periods are first discretized: using one or more cycles of a unified reference clock source as the basic unit, the continuous risk periods are divided into hundreds or even thousands of scheduling time units, and the length of each scheduling time unit is set to an integer multiple of the cycle of the unified reference clock source signal. This effectively constructs a digital time grid for fine-grained scheduling.

[0078] Subsequently, the algorithm defines the activity range for each target module within the risk period. For each functional module that will cause interference during the risk period, based on its functional constraints and the preset maximum allowable timing offset, it determines the start and end boundary times on the time axis before and after the risk period that can be safely adjusted, forming the schedulable time window of the functional module. For example, for the drain pump of a washing machine, based on its mechanical and hydraulic characteristics, its start time may be allowed a maximum adjustment margin of ±100ms before and after the original time point without affecting the overall washing process. The system will mark the start and end boundary times on the time axis where the pump can move safely based on such functional constraints; this interval is its schedulable time window. The schedulable time windows of all modules constitute the solution space boundary of the algorithm search.

[0079] Having defined the boundaries, the algorithm sets clear two-level optimization objectives: The first objective is to pursue conflict-free scheduling, that is, by adjusting the offset, to arrange the noise periods (i.e., their "interference time windows") of any two modules into different scheduling time units, thereby achieving complete isolation of interference on the time axis, which is an ideal state. When complete conflict-free scheduling cannot be achieved due to overlapping time windows or insufficient margin, the algorithm initiates the second objective: prioritizing the overlap of noise from modules with weaker interference intensity (such as a low-power fan) with that of modules with strong interference intensity, and striving to minimize the number of units involved in the overlap and the total duration, in order to mitigate the harmful effects of superposition.

[0080] The search process uses the clock reference signal as the absolute coordinate origin. The algorithm randomly or systematically assigns an initial switching action offset to each module within its time window. Then, it enters an iterative adjustment and evaluation loop: fine-tuning the offset of a functional module sequentially, simulating the execution of a new global timing sequence in memory, and quickly evaluating the overlap state of all scheduling units during the risk period. Through repeated trials, it finds the final offset combination that optimizes the overlap state evaluation function (corresponding to the optimization objective mentioned above). This combination is the core of the optimal scheduling scheme for the current risk period.

[0081] Specifically, when implementing the above-mentioned synchronous scheduling scheme, it is also necessary to combine the actual working conditions and impose functional safety and logical correctness constraints on the generated scheduling scheme to ensure that the scheduling does not disrupt the inherent working logic of the product. The generation of the synchronous scheduling scheme also includes building a scheduling dependency table, including: extracting all module action pairs with mandatory sequential order based on the preset workflow between the functional modules of the home appliance; converting the logical dependency of each module action pair into timing constraints based on a unified reference clock signal, specifying the minimum safe delay time of subsequent module actions relative to the completion time of previous module actions; integrating all module action pairs and their corresponding timing constraints to generate a scheduling dependency table; and using it as an auxiliary execution rule of the synchronous scheduling scheme, which, together with the final offset of each functional module, constitutes a complete scheduling instruction set.

[0082] In practice, it is necessary to access or integrate a functional workflow manual for the home appliance. For example, in a washing machine, the water inlet valve can only be opened after the water level sensor detects a low water level, which is a safety logic; the heater can only be started after the water inlet is complete and the water level sensor confirms a high water level, which is another logical dependency.

[0083] The algorithm parses these processes, extracting all module action pairs with a mandatory sequential order (e.g., the completion of water level sensor feedback is a prerequisite for heater startup). Then, these logical dependencies are converted into precisely quantified timing constraints based on the same unified clock. For example, it is stipulated that the heater startup time must be at least 50ms later than the water level sensor feedback completion time (minimum safe delay). These constraints are compiled into a scheduling dependency table.

[0084] During the optimization search process, each constraint in this table is incorporated as a hard rule. The algorithm must verify that each offset combination satisfies all constraints in the table before attempting it. The final output offset combination is packaged together with this scheduling dependency table to form a complete scheduling instruction set. When distributing instructions, the execution unit uses both the offset combination and the dependency table for interlocking control to ensure functional safety.

[0085] Simultaneously, when implementing the aforementioned synchronous scheduling scheme, this invention also designs an independent and prioritized safe escape channel for the entire dynamic scheduling system, namely, an emergency recovery plan. This is a necessary design to deal with sudden failures and ensure the ultimate safety of the system, and its implementation is divided into two parts: plan configuration and runtime response.

[0086] During the configuration phase, a set of explicit emergency recovery trigger conditions needs to be predefined, such as: main controller watchdog reset (system-level fault), motor current over-limit (critical module status abnormality), and user emergency pause button being pressed (external safety command). Simultaneously, a defined safety recovery path should be pre-defined for each module whose timing has been adjusted. For example, for a drain pump whose start-up was delayed, the safety path might be to immediately cancel the delay and resume the original start-up time; for a heater that was prematurely shut down, the path might be to immediately restore power and continue operating for at least 5 seconds to ensure temperature safety.

[0087] During runtime, a high-priority monitoring thread, independent of the normal scheduling loop, continuously runs to monitor the aforementioned triggering conditions. Once the conditions are met (such as detecting an emergency stop signal), this thread immediately issues a hardware interrupt, unconditionally suspending the ongoing or about-to-be-executed normal scheduling process. Following this, it forcibly writes emergency control instructions (usually overriding normal scheduling instructions) to the control ports of the relevant modules according to a preset safety recovery path. These instructions drive the modules to quickly and definitively switch to a safe state or revert to the original logical sequence, thereby removing the system from any uncertain risk state that scheduling might introduce, ensuring the safety of personnel and equipment.

[0088] Reference Figure 5 As shown, in order to achieve the above method, the present invention also discloses a household appliance electromagnetic interference suppression system, comprising:

[0089] The signal acquisition unit is configured to acquire electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances in real time, and obtain the noise generation time sequence and intensity distribution characteristics of each module based on the acquired data.

[0090] The risk analysis unit, connected to the signal acquisition unit, is configured to identify potential risk periods where noise from different functional modules overlaps on the time axis based on the noise generation time sequence and intensity distribution characteristics, and to assess the superimposed interference intensity during those periods.

[0091] The timing reference unit is configured to generate a high-precision clock reference signal using a unified reference clock source, and to configure clock reference signals for each functional module.

[0092] The scheduling calculation unit is connected to the risk analysis unit and the timing reference unit respectively. It is configured to obtain the response delay parameters of each module to the control command. With the goal of eliminating or reducing the interference superposition during the potential risk period, it calculates based on the clock reference signal, response delay parameters and potential risk period through a synchronization coordination algorithm to generate a synchronization scheduling scheme that adjusts the delay of the switching action time of each module.

[0093] The instruction distribution and execution unit is connected to the scheduling calculation unit and the timing reference unit, respectively, and is configured to distribute corresponding delay compensation instructions to the control units of each functional module according to the synchronous scheduling scheme; the control units of each functional module execute the adjusted switching action according to the clock reference signal and the delay compensation instructions.

[0094] The effect verification unit is connected to the signal acquisition unit and is configured to collect electromagnetic noise distribution data again through the signal acquisition unit after the instruction distribution and execution unit executes the synchronization scheduling scheme, and evaluate the dispersion effect of interference superposition based on the collected data.

[0095] To further verify the beneficial effects of the electromagnetic interference suppression method and system for household appliances of the present invention, a control experiment was further designed:

[0096] The experiment used two identical smart washing machines from the same batch as platforms. One machine was equipped with a traditional static suppression scheme, an optimized LC filter circuit, and a local shielding cover. The firmware used standard sequential logic. Machine A, without collaborative scheduling functionality, served as the control group and the experimental group. Machine B, equipped with the same basic filtering and shielding hardware as machine A, but with the collaborative scheduling system of this invention implanted, served as the experimental group. Under the same environment and test configuration, both machines performed the same complex "intensive cotton wash" cycle, including asynchronous operation of multiple modules such as main motor forward / reverse switching, intermittent start of the drain pump, and heater temperature control.

[0097] The tests strictly followed the national standard GB4343.1: "Electromagnetic compatibility requirements for household appliances, power tools and similar appliances - Part 1: Emissions", with a focus on monitoring conducted disturbance voltage and time-domain interference peak values.

[0098] Both prototypes were run continuously for 10 working cycles under the same environment and test configuration. The data after stabilization were collected and are shown in Tables 1 and 2.

[0099] Table 1: Comparison of key frequency points for conducted disturbance voltage (unit: dBμV)

[0100]

[0101] Table 2: Comparison of peak temporal interference during specific risk periods

[0102]

[0103] Experimental data shows that, in terms of conducted interference, the interference voltage values ​​of prototype B at key frequency points such as 1MHz, 5MHz, 10MHz, and 20MHz are reduced by an average of approximately 6dB compared to prototype A, achieving a more ample EMC (electromagnetic compatibility) margin. Prototype A is close to the limit at 10MHz, while prototype B still maintains a safety margin of over 5dB. This directly proves that the present invention disperses the interference spectrum energy at the source, reducing the pressure on the back-end filter. Even more convincing evidence comes from time-domain analysis: during a period of overlapping risk identified by the system's intelligent system, involving main motor commutation and drainage pump startup, prototype A generated a peak instantaneous current of up to 28.5A, with the high interference state lasting for 4.2 milliseconds. Prototype B, by implementing a synchronization scheduling scheme, precisely delayed the drainage pump startup time by 8 milliseconds, successfully decomposing the aforementioned single high-intensity interference pulse into two dispersed pulses with amplitudes below 20A, resulting in a 33% reduction in the peak instantaneous current and an 88% reduction in the duration of high interference. Further calculations using time integration of the square of the interference current show that the total interference energy was reduced by approximately 55% during this period.

[0104] In summary, this comparative experiment, through quantifiable and repeatable data comparison, confirms the substantial features and significant progress of this invention compared to existing technologies. By establishing a unified time reference, intelligently identifying risks, and proactively coordinating scheduling, this invention successfully transforms the electromagnetic interference suppression strategy from passive spatial / frequency domain blocking to proactive time domain mitigation. This enables effective control of dynamic instantaneous interference peaks in cost-sensitive home appliances, significantly improving the product's electromagnetic compatibility, operational reliability, and overall design optimization.

[0105] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for suppressing electromagnetic interference from household appliances, characterized in that, Includes the following steps: Real-time acquisition of electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances, to obtain the noise generation time sequence and intensity distribution characteristics; Based on time sequence and intensity distribution characteristics, potential risk periods where noise from different functional modules overlaps on the time axis are identified, and the intensity of superimposed interference is assessed. A high-precision clock reference signal is generated using a unified reference clock source, and clock reference signals are configured for each functional module. The response delay parameters of each module to control commands are obtained. With the goal of eliminating or reducing interference superposition during potential risk periods, a synchronization coordination algorithm is used to calculate and generate a synchronization scheduling scheme that adjusts the delay of the switching action time of each module based on the clock reference signal, response delay parameters and potential risk periods. According to the synchronous scheduling scheme, corresponding delay compensation instructions are distributed to the control units of each functional module; each functional module executes the adjusted switching action based on the clock reference signal and the delay compensation instructions. After executing the synchronization scheduling scheme, electromagnetic noise distribution data is collected again, and the dispersion effect of interference superposition is evaluated based on the collected data.

2. The method for suppressing electromagnetic interference from household appliances according to claim 1, characterized in that: Real-time acquisition of electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances, obtaining the noise generation time sequence and intensity distribution characteristics, including: Configure corresponding current sensors and voltage differential probes for multiple functional modules inside the home appliance to form a sensor array; set up a central acquisition unit based on a unified high-frequency clock to generate synchronous acquisition trigger pulses, and send them to each sensor in the sensor array and the control signal monitoring points of each module. The central acquisition unit receives analog noise signals from sensors and switch level signals from monitoring points. When any switch level signal changes, the central acquisition unit immediately takes the moment of change as a reference point and extracts a segment of noise analog signal with a predetermined time length before and after it. This segment of signal is marked as a noise characteristic segment associated with the switch action. Determine the start and end times of the noise characteristic segment, and calculate the average and peak values ​​of the signal amplitude within the noise characteristic segment, which are respectively used as the steady-state intensity characteristics and transient intensity characteristics of the noise event. In chronological order, the generation time, steady-state intensity characteristics and transient intensity characteristics of all noise events generated by multiple functional modules in multiple working cycles are combined and arranged to generate a noise generation time sequence and intensity distribution characteristic data packet.

3. The method for suppressing electromagnetic interference from household appliances according to claim 2, characterized in that: It also includes background noise stripping, including: During the silent period when the functional module is in a shutdown or standby state, the sensor array is activated to sample and collect the background environmental noise signal for a certain period of time as a background noise reference. When extracting feature segments, short-time reference signals containing only background noise that are adjacent to the feature segments are extracted simultaneously. The extracted short-time reference signals are compared with the background noise model to dynamically estimate the instantaneous intensity level of the background noise at the current moment. From the original signal of the marked noise feature segments, the background noise component is subtracted according to the estimated intensity level to obtain the purified noise feature segments that reflect the noise of the functional module itself.

4. The method for suppressing electromagnetic interference from household appliances according to claim 1, characterized in that: Identify potential risk periods where noise from different functional modules overlaps on the time axis, and assess the intensity of the superimposed interference, including: Based on the noise generation time sequence, the noise generation time periods of all functional modules are mapped onto a unified time axis; a continuous time interval in which the noise generation time periods of any two or more modules overlap in time is defined as a time conflict domain. For each time conflict domain, the electromagnetic energy integral value represented by the noise intensity distribution characteristics of each functional module is calculated; the electromagnetic energy integral values ​​of all functional modules in the same conflict domain are combined to obtain the total interference energy estimate of the conflict domain. Sort all time conflict domains from highest to lowest according to their total interference energy estimates. Select one or more time conflict domains with the highest total interference energy estimates from the sorted list from top to bottom, and identify them as potential risk periods that require time-series coordination.

5. The method for suppressing electromagnetic interference from household appliances according to claim 4, characterized in that: Calculate the integral value of electromagnetic energy characterized by the noise intensity distribution features of each functional module, including: For each functional module within the time conflict domain, the envelope curve of noise intensity changing with time within the corresponding time period is extracted from the electromagnetic noise signal acquired in real time. For each extracted noise intensity envelope curve, mathematical integration is performed within the time range of its corresponding time conflict domain. The area enclosed by the noise intensity envelope curve and the time axis is calculated to characterize the total electromagnetic noise energy radiated or conducted by the functional module within the time conflict domain, which is used as the electromagnetic energy integral value.

6. The method for suppressing electromagnetic interference from household appliances according to claim 5, characterized in that: After calculating the total interference energy estimate for a specific time-domain conflict, the electromagnetic energy integral values ​​of each functional module within the conflict domain under historical normal operating conditions and at the same time sequence position are retrieved as benchmark reference values. The electromagnetic energy integral values ​​of each module obtained in this calculation are then compared with the corresponding benchmark reference values. When the deviation between the current electromagnetic energy integral value of a certain functional module and the reference value exceeds the preset fluctuation range, the noise envelope data of the functional module in the current collision domain is determined to be abnormal data. Mark the functional module as a module to be verified, and temporarily invalidate its calculated electromagnetic energy integral value; For each marked module to be verified, based on the inherent patterns of its noise generation time sequence and intensity distribution characteristics, and combined with the noise data of other normal modules that have temporal correlation with it, the noise intensity envelope curve of the module to be verified in the collision domain is predictively repaired to complete or correct the contaminated part; based on the repaired envelope curve, the electromagnetic energy integral value of the module to be verified in the collision domain is recalculated.

7. The method for suppressing electromagnetic interference from household appliances according to claim 1, characterized in that: A synchronization scheduling scheme is generated by calculating using a synchronization coordination algorithm to adjust the delay of the switching actions of each module, including: The potential risk period is divided into multiple consecutive scheduling time units on the time axis, and the length of each scheduling time unit is an integer multiple of the period of the unified reference clock source signal. For each functional module that will cause interference during the risk period, based on its functional constraints and the preset maximum allowable timing offset, determine the start and end boundary times that can be safely adjusted on the time axis before and after the risk period, forming the schedulable time window of the functional module. The first optimization objective is to ensure that the interference time windows of any two functional modules do not overlap within the same scheduling time unit. When the first objective cannot be fully achieved, the second optimization objective is to ensure that the overlap occurs between functional modules with weaker interference intensity and to minimize the number of overlapping units and the total duration. Using the clock reference signal as the absolute reference, an initial switching action offset is assigned to each functional module within its schedulable time window. According to the set optimization target, the offsets of each functional module are adjusted sequentially, and the adjusted timing is simulated. After each adjustment, the interference overlap state of all scheduled time units within the risk period is evaluated. This process is repeated until the final offset combination of each functional module that optimizes the overlap state is achieved.

8. The method for suppressing electromagnetic interference from household appliances according to claim 7, characterized in that: The generation of a synchronization scheduling scheme also includes constructing a scheduling dependency table, specifically: Based on the preset workflow between the functional modules of home appliances, all module action pairs with a mandatory sequential order are extracted; the logical dependency of each module action pair is converted into timing constraints based on a unified reference clock signal, which specifies the minimum safe delay time of subsequent module actions relative to the completion time of the preceding module actions. Integrate all module action pairs and their corresponding timing constraints to generate a scheduling dependency table; It is used as an auxiliary execution rule of the synchronous scheduling scheme, and together with the final offset of each functional module, it forms a complete set of scheduling instructions.

9. The method for suppressing electromagnetic interference from household appliances according to claim 7, characterized in that: The synchronization scheduling scheme also includes an emergency recovery plan, the generation and execution of which include the following steps: A set of monitoring conditions for triggering emergency recovery is pre-configured, including at least system-level fault signals, abnormal status of critical modules, or external safety commands; For each functional module subject to timing adjustment in the synchronous scheduling scheme, a corresponding safe recovery path is preset, which defines the certain safe state that the functional module should switch to or the logical sequence that should be followed to fall back to the original timing when emergency recovery is triggered; Establish and operate a high-priority monitoring and response mechanism; when any monitoring condition is met, immediately interrupt the current synchronization scheduling process, and forcibly distribute emergency control instructions to the functional modules according to the safe recovery path, so that they can perform state recovery operations.

10. A household appliance electromagnetic interference suppression system, used to implement the method described in any one of claims 1 to 9, characterized in that: include: The signal acquisition unit is configured to acquire electromagnetic noise signals and corresponding switching action data generated by various functional modules of household appliances in real time, and obtain the noise generation time sequence and intensity distribution characteristics of each module based on the acquired data. The risk analysis unit, connected to the signal acquisition unit, is configured to identify potential risk periods where noise from different functional modules overlaps on the time axis based on the noise generation time sequence and intensity distribution characteristics, and to assess the superimposed interference intensity during those periods. The timing reference unit is configured to generate a high-precision clock reference signal using a unified reference clock source, and to configure clock reference signals for each functional module. The scheduling calculation unit is connected to the risk analysis unit and the timing reference unit respectively. It is configured to obtain the response delay parameters of each module to the control command. With the goal of eliminating or reducing the interference superposition during the potential risk period, it calculates based on the clock reference signal, response delay parameters and potential risk period through a synchronization coordination algorithm to generate a synchronization scheduling scheme that adjusts the delay of the switching action time of each module. The instruction distribution and execution unit is connected to the scheduling calculation unit and the timing reference unit, respectively, and is configured to distribute corresponding delay compensation instructions to the control units of each functional module according to the synchronous scheduling scheme; the control units of each functional module execute the adjusted switching action according to the clock reference signal and the delay compensation instructions. The effect verification unit is connected to the signal acquisition unit and is configured to collect electromagnetic noise distribution data again through the signal acquisition unit after the instruction distribution and execution unit executes the synchronization scheduling scheme, and evaluate the dispersion effect of interference superposition based on the collected data.

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