New energy high-low voltage direct current relay energy-saving control method

Abstract

The invention discloses an energy-saving control method for a new-energy high-low-voltage direct-current relay. The energy-saving control method comprises the steps of analyzing a mapping relation between a silicon steel sheet stacking angle and a magnetic flux path deviation, calculating magnetic domain wall moving resistance according to magnetic domain boundary stress, determining a magnetic domain overturning speed by combining a magnetic field change rate, and measuring a hysteresis loop width parameter. Adjusting the width and frequency of the excitation current pulse according to the magnetic domain overturning frequency and the hysteresis loop offset and width to obtain an optimized excitation current pulse sequence, and determining the hysteresis loop expansion speed according to the hysteresis loop area change rate; the local high-temperature area temperature is analyzed through the iron core temperature rise rate, the local high-temperature area distribution and the magnetic domain energy dissipation data, if the local high-temperature area temperature exceeds the preset threshold value, the excitation current pulse is adjusted, stable iron core temperature rise control data is obtained, the coercive force change amplitude is determined, the magnetic hysteresis loss and the temperature rise are reduced, the stability of the relay under high-frequency switching is improved, and the reliability of the relay is improved. And the operation efficiency and reliability of the system are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of information technology, and in particular to an energy-saving control method for high and low voltage DC relays in new energy sources. Background Technology

[0002] As a key component in energy storage systems, the performance of the electromagnet core of a DC relay directly affects the system's efficiency and reliability. Especially during frequent charge-discharge mode switching, the changing state places higher demands on the core's hysteresis loss and overall energy consumption. Researching the hysteresis loss characteristics and holding power optimization strategies of the electromagnet core is crucial for improving the stability and energy-saving effect of energy storage systems. However, existing methods have significant shortcomings in dealing with the dynamic changes in the core's magnetic properties. Most solutions rely too heavily on static design, neglecting the dynamic adjustment requirements of the magnetic flux distribution under high-frequency switching, leading to increased energy loss and difficulties in temperature rise control. Particularly when the energy storage system undergoes multiple charge-discharge switching cycles in a short period, the magnetic domain arrangement inside the core frequently reconfigures, and the hysteresis loop area dynamically expands. This not only exacerbates hysteresis loss but also results in additional energy consumption due to the lack of precise control over the coil excitation current. The core challenge lies in the non-uniformity of the magnetic flux distribution inside the core and its amplifying effect on hysteresis loss. The stacking orientation of silicon steel sheets directly affects the uniformity of the magnetic flux path. Improper stacking orientation can lead to localized magnetic flux concentration within the core, exacerbating energy dissipation during domain reconfiguration. For example, during rapid mode switching in an energy storage system, a region of the core may experience localized high temperatures due to magnetic flux concentration, affecting the stability of the relay's holding state and potentially triggering thermal runaway. Therefore, optimizing the stacking orientation of silicon steel sheets to improve the uniformity of magnetic flux distribution and designing an adaptive excitation current pulse modulation strategy to reduce hysteresis loss and temperature rise during frequent state switching is crucial for improving the energy efficiency and stability of DC relays. Summary of the Invention

[0003] In order to solve the above-mentioned technical problems, the present invention provides an energy-saving control method for high and low voltage DC relays in new energy sources.

[0004] The technical solution of this invention is implemented as follows: A new energy high and low voltage DC relay energy-saving control method, comprising: S1. Obtain the relay holding status index during the charging and discharging switching of the energy storage system, record the switching frequency and holding time, collect the core magnetic flux density fluctuation data, determine the uniformity of magnetic flux distribution and the local magnetic saturation distribution characteristics, and determine the magnetic domain orientation angle and size distribution through magnetic induction intensity measurement. S2. Based on the uniformity of magnetic flux distribution and the characteristics of local magnetic saturation distribution, combined with the orientation angle and size distribution of magnetic domains, the mapping relationship between the stacking angle of silicon steel sheets and the magnetic flux path deviation is analyzed. The magnetic domain wall movement resistance is calculated based on the magnetic domain boundary stress. The magnetic domain flipping speed is determined by combining the magnetic field change rate. The hysteresis loop width parameter is measured. S3. Perform frequency domain analysis on the magnetic flux density fluctuation data, the magnetic flux path deviation, the charge-discharge switching frequency and the magnetic domain flipping speed. Obtain the magnetic domain wall displacement distance and hysteresis loss energy by calculating the magnetic domain wall movement distance and using the energy integration method. Determine the magnetic domain flipping frequency and hysteresis loop offset. S4. Adjust the width and frequency of the excitation current pulse according to the magnetic domain reversal frequency, the hysteresis loop offset and the hysteresis loop width parameters to generate an excitation current pulse sequence. S5. Adjust the excitation current during the relay holding time by the excitation current pulse sequence, collect the core temperature rise rate and the distribution of local high temperature areas, and determine the magnetic domain energy dissipation. S6. Adjust the excitation current pulse sequence by the core temperature rise rate and the local high temperature area distribution to generate core temperature rise control data; S7. Based on the core temperature rise control data, verify the domain flipping speed and hysteresis loop shape stability of the core at the switching frequency, and determine the core optimal configuration and saturation magnetic induction intensity.

[0005] Furthermore, in step S1, the relay holding state index is obtained when the energy storage system switches between charging and discharging, the switching frequency and holding time are recorded, the core magnetic flux density fluctuation data are collected, the uniformity of magnetic flux distribution and the local magnetic saturation distribution characteristics are determined, and the magnetic domain orientation angle and size distribution are determined by magnetic induction intensity measurement.

[0006] Furthermore, in step S1, the specific steps are as follows: The relay pull-in voltage and release voltage values ​​are obtained during the charging and discharging switching process of the energy storage system. The contact resistance change data is recorded at each switching. The relay working status dataset is constructed based on the relationship between voltage difference and contact resistance. The magnetic induction intensity data of each region of the iron core are collected through Hall sensor array to obtain the magnetic flux density spatial distribution matrix. The magnetic flux gradient value is calculated by dividing the difference in magnetic flux density between adjacent measuring points in the magnetic flux density spatial distribution matrix by the distance between the measuring points. If the gradient value exceeds the preset threshold, it is marked as a magnetic flux concentration area. Magneto-optic imaging technology is used to obtain the magnetic domain structure image on the iron core surface. The magnetic domain boundary contour is extracted by the edge detection method to determine the orientation angle and size parameters of each magnetic domain region. A magnetic domain distribution feature vector is established based on the magnetic domain orientation angle and size parameters. Combined with the location information of the magnetic flux concentration area, the local magnetic saturation value is calculated by the ratio of the magnetic flux density value to the material saturation magnetic flux density. By comparing the change law of magnetic saturation under different charging and discharging switching frequencies with the change trend of the central contact resistance of the relay working state data, the evolution characteristics of the relay core magnetic properties are judged. Based on the evolution characteristics of the relay core magnetic properties, the correlation between the magnetic domain distribution feature vector and the contact resistance change trend is calculated to obtain the corresponding data between the magnetic flux distribution uniformity index and the relay holding state stability, and to determine the distribution of relay performance degradation characteristic parameters during the charging and discharging switching of the energy storage system.

[0007] Further, in step S2, based on the uniformity of magnetic flux distribution and the characteristics of local magnetic saturation distribution, combined with the orientation angle and size distribution of magnetic domains, the mapping relationship between the stacking angle of silicon steel sheets and the deviation of magnetic flux path is analyzed. The magnetic domain wall movement resistance is calculated based on the magnetic domain boundary stress, the magnetic domain flipping speed is determined by combining the magnetic field change rate, and the hysteresis loop width parameter is measured.

[0008] Furthermore, in step S2, the specific steps are as follows: Data on the stacking angle of silicon steel sheets were obtained. The magnetic flux distribution values ​​under different stacking angles were collected by a magnetic flux density measuring instrument. The actual direction of the magnetic flux path was calculated based on the angle between the magnetic domain orientation angle and the grain direction of the silicon steel sheet. The path deviation value was obtained by comparing it with the reference direction of the magnetic flux path perpendicular to the stacking plane. A dataset of the correspondence between the stacking angle and the path deviation value was established. Based on the corresponding dataset, strain sensors are used to measure the stress distribution in the domain boundary region. The domain wall movement resistance value is calculated by multiplying the stress value by the material magnetostriction coefficient and then by the domain wall thickness. The domain flipping speed parameter is determined by combining the derivative of the applied magnetic field strength with respect to time with the domain wall movement resistance value. For the domain flipping speed parameter, the domain flipping completion time is obtained by summing the speed parameter within the magnetization period. If the flipping completion time exceeds a preset threshold, it is marked as a flipping hysteresis region. The relationship curve between magnetization intensity and magnetic field intensity corresponding to different flipping hysteresis regions is recorded by a hysteresis loop tester. The difference between the magnetization intensity value when the magnetic field intensity is zero and the magnetic field intensity value when the magnetic field intensity is zero is extracted from the curve as the hysteresis loop width parameter.

[0009] Further, in step S3, frequency domain analysis is performed on the magnetic flux density fluctuation data, the magnetic flux path deviation, the charge-discharge switching frequency, and the magnetic domain flipping speed. The magnetic domain wall displacement distance and hysteresis loss energy are obtained by calculating the magnetic domain wall movement distance and using the energy integration method, and the magnetic domain flipping frequency and hysteresis loop offset are determined.

[0010] Furthermore, in step S3, the specific steps are as follows: Time series data of magnetic flux density fluctuation, magnetic flux path deviation, charge-discharge switching frequency and magnetic domain reversal speed are acquired. The time domain data are converted to the frequency domain by fast Fourier transform to obtain the spectral distribution characteristics of each parameter. The correspondence between the main frequency of magnetic flux density fluctuation and the charge-discharge switching frequency is determined by the position of the spectral peak. Based on the frequency matching degree in the aforementioned correspondence, the domain wall displacement distance is calculated by integrating the velocity of the domain wall over time within a single magnetization cycle. The formula for calculating the domain wall displacement distance is as follows: d represents the total displacement distance of the domain wall in a single magnetization cycle, v(t) represents the instantaneous velocity of the domain wall at time t, T represents the time length of a complete magnetization cycle, and the integral symbol represents the summation of the velocity over the entire cycle over time. The hysteresis loss energy value per unit cycle is obtained by using the integral value of the product of the magnetic field strength and the magnetization intensity in a complete cycle of the hysteresis loop. If the loss energy value exceeds the preset threshold, the frequency point is marked as a high loss frequency point. For high-loss frequencies, the domain reversal frequency is calculated by the ratio of the domain wall displacement distance to the magnetization period time. The formula for calculating the domain reversal frequency is as follows: f d d represents the domain reversal frequency. w t represents the displacement distance of the magnetic domain walls. m The magnetization period time is represented by the hysteresis loop offset parameter, which is determined by the coordinate change of the midpoint of the line connecting the maximum and minimum magnetization points on the hysteresis loop under different charge and discharge switching frequencies.

[0011] Further, in step S4, the width and frequency of the excitation current pulse are adjusted according to the domain reversal frequency, the hysteresis loop offset, and the hysteresis loop width parameters to generate an excitation current pulse sequence.

[0012] Furthermore, in step S4, the specific steps are as follows: The target frequency value of the excitation current pulse is calculated by multiplying the domain reversal frequency and the hysteresis loop offset parameter. The pulse width adjustment is determined by the difference between the hysteresis loop width parameter and the width value at the initial measurement. If the difference exceeds the threshold, the pulse width is increased proportionally to obtain the adjusted excitation current pulse parameter combination. An excitation current pulse sequence is generated using the aforementioned excitation current pulse parameter combination. This sequence is then output to the excitation coil of the energy storage system via a power amplifier. The area values ​​of the hysteresis loop at different times are recorded. The rate of change of the hysteresis loop area is calculated based on the ratio of the area difference between adjacent times to the time interval. The calculation formula is as follows: A t Let A represent the area of ​​the hysteresis loop at time t.t+Δt dA / dt represents the area of ​​the hysteresis loop at time t+Δt, where Δt represents the time interval, and dA / dt represents the rate of change of the hysteresis loop area with time. The rate of change of the hysteresis loop area is recorded over time, and the expansion speed of the hysteresis loop is determined by the increasing or decreasing trend of the rate of change.

[0013] Furthermore, in step S5, the excitation current during the relay holding time is adjusted by the excitation current pulse sequence, the core temperature rise rate and the distribution of local high temperature areas are collected, and the energy dissipation of magnetic domains is determined.

[0014] Furthermore, in step S5, the specific steps are as follows: By optimizing the excitation current pulse sequence and hysteresis loop expansion speed parameters, the pulse amplitude and interval are adjusted according to the real-time measurement of magnetic flux density changes by the magnetic field sensor during the relay holding time, generating an excitation current sequence that matches the hysteresis loop expansion speed. Infrared thermal imager is used to collect temperature distribution data of various regions of the iron core. The core temperature rise rate is obtained by calculating the ratio of the temperature difference between adjacent moments to the time interval based on the temperature distribution data. If the temperature rise rate exceeds a preset threshold, it is marked as a local high temperature region. The magnetic domain energy dissipation power value is calculated by multiplying the temperature rise rate of the high temperature region by the volume of the region and the specific heat capacity of the material. A time series correspondence is established between the energy dissipation power value of the magnetic domain and the excitation current sequence parameters. The system's operational stability is judged based on the ratio of the fluctuation amplitude of the energy dissipation power value to the average value. If the ratio exceeds the preset stability threshold, the system is assessed as being in an unstable state.

[0015] Furthermore, in step S6, the excitation current pulse sequence is adjusted by the core temperature rise rate and the distribution of the local high temperature region to generate core temperature rise control data.

[0016] Furthermore, in step S6, the specific steps are as follows: By using data on core temperature rise rate, local high temperature region distribution and magnetic domain energy dissipation, the highest temperature value of each high temperature region is extracted. If the temperature value exceeds the preset threshold, the excitation current pulse amplitude is reduced according to the ratio of the temperature exceeding the threshold. The temperature change data of each measuring point of the core over time is recorded after adjustment. A temperature distribution curve is formed based on the temperature change data over time. The spatial coordinates of the temperature peak point are identified as the hot spot location coordinates. The heat dissipation power is calculated by multiplying the temperature gradient of the hot spot area by the thermal conductivity. The ratio of heat dissipation power to magnetic loss power is calculated by combining the magnetic domain energy dissipation data of the area to obtain the heat dissipation efficiency parameter. Thus, core temperature rise control data including temperature distribution curve, hot spot location coordinates and heat dissipation efficiency parameter are obtained. By using the hot spot locations corresponding to different temperatures in the core temperature rise control data, the coercivity values ​​are obtained by measuring the hysteresis characteristics at different temperatures at these locations using a magnetic tester. The coercivity variation range is determined based on the difference between the coercivity at the highest temperature and the coercivity at the initial temperature.

[0017] Furthermore, in step S7, based on the core temperature rise control data, the domain flipping speed and hysteresis loop shape stability of the core under the switching frequency are verified, and the core optimal configuration and saturation magnetic induction intensity are determined.

[0018] Furthermore, in step S7, the specific steps are as follows: Based on the core temperature rise control data and coercivity change amplitude, the domain flipping completion time is measured at the charge-discharge switching frequency. The deviation rate is obtained by dividing the difference between the measured time and the initial measurement time by the initial measurement time. The coercivity and remanence values ​​of the hysteresis loop at different times are recorded by the hysteresis loop tester. The change rate of values ​​at adjacent times is calculated to determine the stability of the hysteresis loop shape. Using the hysteresis loop shape stability data, the magnetic flux distribution uniformity index is calculated by the ratio of the standard deviation to the average value of the magnetic flux density measurement points. The cumulative hysteresis loss energy is obtained by multiplying the hysteresis loop area by the number of charge and discharge cycles. The difference between the maximum and minimum temperatures is extracted from the temperature distribution curve of the core temperature rise control data as the temperature fluctuation amplitude to evaluate the temperature control performance. A comprehensive verification report containing these three indicators is generated. By combining the numerical values ​​of magnetic flux distribution uniformity, hysteresis loss energy, and temperature control performance indicators from the comprehensive verification report, the corresponding core configuration parameters are determined as the final optimized configuration. The saturation magnetic induction intensity is determined based on the maximum magnetic flux density measured under the optimized configuration.

[0019] The energy-saving control method for high and low voltage DC relays in new energy sources described in this invention has the following advantages: This invention discloses an energy-saving control method for high and low voltage DC relays in new energy sources. By collecting data on core magnetic flux density fluctuations, domain orientation angles, and size distributions, and combining this with the mapping relationship between magnetic flux path deviation and silicon steel sheet stacking angles, the method analyzes the domain wall movement resistance and flipping speed to optimize the excitation current pulse sequence. Real-time adjustment of pulse width and frequency controls the hysteresis loop expansion speed, reducing hysteresis loss energy. Simultaneously, by using core temperature rise rate and local high-temperature region distribution data, the excitation current is dynamically adjusted to ensure temperature stability and reduce coercivity variation. This invention significantly improves magnetic flux distribution uniformity, reduces hysteresis loss and temperature rise, enhances relay stability under high-frequency switching, and ultimately achieves optimized core configuration, increased saturation magnetic induction intensity, and a substantial improvement in system operating efficiency and reliability. Attached Figure Description

[0020] Figure 1This is a flowchart of a new energy high and low voltage DC relay energy-saving control method according to the present invention; Figure 2 This is a schematic diagram of an energy-saving control method for high and low voltage DC relays in new energy sources according to the present invention. Detailed Implementation

[0021] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0022] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0023] When used herein, the singular forms of “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising / including” or “having,” etc., specify the presence of the stated features, wholes, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0024] Please see Figure 1 As shown, a new energy high and low voltage DC relay energy-saving control method includes: S1. Obtain the relay holding status index during the charging and discharging switching of the energy storage system, record the switching frequency and holding time, collect the core magnetic flux density fluctuation data, determine the uniformity of magnetic flux distribution and the local magnetic saturation distribution characteristics, and determine the magnetic domain orientation angle and size distribution through magnetic induction intensity measurement. S2. Based on the uniformity of magnetic flux distribution and the characteristics of local magnetic saturation distribution, combined with the orientation angle and size distribution of magnetic domains, the mapping relationship between the stacking angle of silicon steel sheets and the deviation of magnetic flux path is analyzed. The domain wall movement resistance is calculated based on the domain boundary stress, the domain flipping speed is determined by combining the magnetic field change rate, and the hysteresis loop width parameter is measured. S3. Perform frequency domain analysis on magnetic flux density fluctuation data, magnetic flux path deviation, charge-discharge switching frequency and magnetic domain flipping speed. Obtain the magnetic domain wall displacement distance and hysteresis loss energy by calculating the magnetic domain wall movement distance and using the energy integration method. Determine the magnetic domain flipping frequency and hysteresis loop offset. S4. Adjust the width and frequency of the excitation current pulse according to the domain reversal frequency, hysteresis loop offset and width to obtain an optimized excitation current pulse sequence. Determine the hysteresis loop expansion speed by the hysteresis loop area change rate. S5. By optimizing the excitation current pulse sequence and the hysteresis loop expansion speed parameters, the excitation current pulse during the relay holding time is adjusted in real time to generate the excitation current sequence, collect the core temperature rise rate and the distribution of local high temperature areas, and determine the magnetic domain energy dissipation. S6. Analyze the temperature of the local high temperature region by using the core temperature rise rate, local high temperature region distribution and magnetic domain energy dissipation data. If the temperature exceeds the preset threshold, adjust the excitation current pulse to obtain stable core temperature rise control data and determine the coercivity change range. S7. Based on the core temperature rise control data and coercivity change amplitude, verify the domain flipping speed and hysteresis loop shape stability of the core under the charging and discharging switching frequency, generate a comprehensive verification report including magnetic flux distribution uniformity, hysteresis loss energy and temperature control performance, and determine the final core optimization configuration and saturation magnetic induction intensity.

[0025] like Figures 1-2 As shown, in step S1, the relay holding state index is obtained when the energy storage system switches between charging and discharging, the switching frequency and holding time are recorded, the core magnetic flux density fluctuation data are collected, the uniformity of magnetic flux distribution and the local magnetic saturation distribution characteristics are determined, and the magnetic domain orientation angle and size distribution are determined by magnetic induction intensity measurement.

[0026] Specifically, in the actual operation of an energy storage system, the charging and discharging switching process will generate continuous electromagnetic stress on the relay, which directly affects the relay's service life and reliability. When switching from charging mode to discharging mode, the relay needs to complete the opening and closing of the contacts in a short time. During this process, the magnetic field inside the iron core will change drastically. The arrangement of the Hall sensor array plays a key role in the accuracy of magnetic flux density measurement. Nine Hall sensors are arranged in a 3×3 matrix on the surface of the relay core, with a spacing of 5 mm between each sensor. This allows the distribution of magnetic induction intensity in different areas of the core to be obtained. When the charging and discharging switching frequency reaches 10 times per minute, the sensors will collect the magnetic flux density values ​​of each measuring point in real time, forming a dynamic spatial distribution dataset. By dividing the difference in magnetic flux density between adjacent measuring points by the spacing between the measuring points, the magnetic flux gradient value can be calculated. When the magnetic flux gradient value of a certain area exceeds a set threshold, such as exceeding 0.8 Tesla / meter, it indicates that there is a magnetic flux concentration phenomenon in that area. This concentration often indicates the risk of local magnetic saturation of the core. Magneto-optic imaging technology has unique advantages in the observation of magnetic domain structure. Magnetic domains are tiny regions within ferromagnetic materials that are spontaneously magnetized in the same direction. Their size and orientation directly affect the magnetic properties of the material. Through magneto-optical imaging equipment, the distribution image of magnetic domains on the surface of relay cores can be observed intuitively. Edge detection methods can accurately identify the boundaries of magnetic domains and then extract the geometric parameters of each magnetic domain. The size of magnetic domains in the iron core under normal operating conditions is usually in the range of 20-50 micrometers, and the orientation angle is relatively uniform. However, as the number of charge and discharge switching increases, the magnetic domains in some areas will merge or split, and the size may increase to more than 100 micrometers. The orientation angle will also show significant deviation. The calculation of local magnetic saturation provides a quantitative indicator for relay performance evaluation. When the magnetic flux density in a certain area is close to the saturation magnetic flux density of the material, the permeability of that area will drop sharply, resulting in an increase in magnetic reluctance. For example, the saturation magnetic flux density of silicon steel sheet material is about 1.8 Tesla. When the local magnetic flux density reaches 1.6 Tesla, the magnetic saturation has reached 89%. At this time, the relay's attraction force will be significantly weakened. At the same time, the change trend of contact resistance is closely related to the magnetic saturation. Under normal circumstances, the contact resistance should be kept at the milliohm level. However, when the iron core has local magnetic saturation, insufficient attraction force will lead to poor contact, and the resistance value may increase to tens of milliohms or even higher.

[0027] like Figure 1 As shown, in step S2, based on the uniformity of magnetic flux distribution and the characteristics of local magnetic saturation distribution, combined with the orientation angle and size distribution of magnetic domains, the mapping relationship between the stacking angle of silicon steel sheets and the deviation of magnetic flux path is analyzed. The magnetic domain wall movement resistance is calculated based on the magnetic domain boundary stress, the magnetic domain flipping speed is determined by combining the magnetic field change rate, and the hysteresis loop width parameter is measured.

[0028] Specifically, the stacking angle of silicon steel sheets has a decisive influence on the magnetic flux path; When silicon steel sheets are stacked in parallel at a 0-degree angle, the magnetic flux is mainly conducted along the rolling direction of the steel sheets, at which point the magnetic resistance is minimal. However, when the stacking angle deviates from the rolling direction, such as when it is tilted at 15 or 30 degrees, the magnetic flux is forced to change its original path, resulting in a significant path deviation. This deviation can be accurately quantified by multi-point acquisition by a magnetic flux density measuring instrument. The sensor array arranged on the surface of the silicon steel sheet by the measuring instrument can capture subtle changes in the magnetic flux distribution. The relationship between the magnetic domain orientation angle and the grain direction directly affects the magnetic flux conduction efficiency. The grains inside silicon steel sheets have specific easy magnetization directions. When the magnetic domain orientation is consistent with the easy magnetization direction of the grains, the magnetic flux conduction is the smoothest. By measuring the angle between the magnetic domain orientation angle and the grain direction, the deviation between the actual magnetic flux path and the ideal path can be calculated. The ideal path is usually defined as the direction perpendicular to the lamination plane, because this is the main direction of magnetic flux conduction in transformers or motors. The calculation of the magnetic domain wall movement resistance involves the magnetostrictive properties of the material. When a domain wall is subjected to an external magnetic field and prepares to move, stress concentration occurs in the domain boundary region. Strain sensors can accurately measure this stress distribution. The measured stress value needs to be multiplied by the magnetostriction coefficient of the material, which reflects the deformation characteristics of the material during magnetization, and then multiplied by the thickness of the domain wall, typically at the nanometer level. This yields the resistance value that the domain wall needs to overcome to move. The greater this resistance value, the more difficult it is for the domain to flip. The rate of change of magnetic field strength is a key factor affecting the domain flipping speed. When the applied magnetic field changes at a rate of 100 amperes per second, the domain flipping speed can be determined by combining the previously calculated domain wall movement resistance. This speed parameter reflects how quickly the material responds to changes in the magnetic field, and is particularly important for high-frequency applications. The domain flipping completion time is obtained by summing the speed parameters. When the flipping time of a certain region is significantly longer than that of other regions, a flipping hysteresis phenomenon is formed. The hysteresis loop tester can completely record the magnetization characteristic curves of these hysteresis regions. The key parameters extracted from the curves include remanence and coercivity. Remanence is the magnetization intensity retained by the material when the magnetic field strength drops to zero, and coercivity is the reverse magnetic field strength required to reduce the magnetization intensity to zero. The difference between the two constitutes the hysteresis loop width parameter. The larger this parameter is, the more severe the hysteresis loss of the material, which has an adverse effect on the efficiency of the energy storage system.

[0029] like Figure 1 As shown, in step S3, frequency domain analysis is performed on the magnetic flux density fluctuation data, magnetic flux path deviation, charge-discharge switching frequency and magnetic domain flipping speed. The magnetic domain wall displacement distance and hysteresis loss energy are obtained by calculating the magnetic domain wall movement distance and using the energy integration method, and the magnetic domain flipping frequency and hysteresis loop offset are determined.

[0030] Specifically, frequency domain analysis has unique advantages in evaluating the magnetic properties of energy storage systems, as it can reveal periodic features that are difficult to detect in time domain signals. The magnetic flux density fluctuation data appears as seemingly chaotic fluctuations in the time domain, but after being converted to the frequency domain by fast Fourier transform, it shows obvious spectral peaks. The frequencies corresponding to these peaks precisely reflect the main fluctuation period of the magnetic flux density. For example, when the charge-discharge switching frequency is 50 Hz, the magnetic flux density spectrum will also show peaks at 50 Hz and its harmonics. This frequency matching relationship directly proves the influence of charge-discharge switching on magnetic flux distribution. The calculation of the magnetic domain wall displacement distance needs to consider the dynamic process throughout the entire magnetization cycle. Magnetic domain walls move at a specific speed under the influence of an external magnetic field. This speed varies within one cycle. By integrating the speed over time, the cumulative displacement distance of the domain walls can be obtained. When the magnetic field changes from its positive maximum value to its negative maximum value, the domain walls undergo a complete round-trip motion. The total displacement distance reflects the magnetization reversal capability of the material. The larger the displacement distance, the more drastic the change in the magnetic domain structure, and the higher the corresponding energy loss. The calculation of hysteresis loss energy is based on the area principle of the hysteresis loop. The hysteresis loop is a closed curve that reflects the change in magnetization with the magnetic field strength. The area enclosed by the hysteresis loop represents the irreversible energy loss within one magnetization cycle. The calculation requires integrating the product of the magnetic field strength and the magnetization, with the integration interval covering the entire magnetization cycle. The energy value obtained by multiplying this integral value by the material volume directly reflects the power loss level of the energy storage system at that frequency. Identifying high-loss frequency points is crucial for system optimization. When the hysteresis loss energy at a certain frequency exceeds a preset threshold, it indicates a significant decrease in system efficiency at that operating frequency. These frequency points are often related to the inherent magnetic resonance of the material. The resonant frequency or structural resonant frequency is related and needs to be avoided in system design. The domain reversal frequency is calculated by the relationship between displacement distance and time, which characterizes the speed at which the domain responds to changes in the external field. The determination of the hysteresis loop offset parameter is more precise. It is achieved by tracking the position changes of characteristic points on the hysteresis loop. The midpoint of the line connecting the maximum and minimum magnetization points represents the geometric center of the hysteresis loop. When the charging and discharging frequency changes, this center point will shift. The magnitude and direction of the shift contain rich information on the magnetic degradation of the material, providing a quantitative basis for the state monitoring and lifetime prediction of the energy storage system.

[0031] like Figure 1 As shown, in step S4, the width and frequency of the excitation current pulse are adjusted according to the domain reversal frequency, hysteresis loop offset and width to obtain an optimized excitation current pulse sequence, and the hysteresis loop expansion speed is determined by the hysteresis loop area change rate.

[0032] Specifically, optimizing and adjusting the excitation current pulse parameters is a key step in improving the magnetic performance of the energy storage system. The domain reversal frequency reflects how quickly the internal magnetic structure of a material responds to an external field. When the reversal frequency is 100 Hz, it means that the domains complete 100 directional reversals per second. The hysteresis loop offset parameter reveals the asymmetry of the material's magnetization characteristics. The larger the offset value, the more uneven the magnetization process of the material. By multiplying these two parameters, the obtained value directly corresponds to the target frequency of the excitation current pulse. This correspondence is based on the principle of synchronization between the magnetic field and the magnetization intensity. The hysteresis loop width at the initial measurement is recorded as a reference value. As the system runs, the current measured width value differs from the reference value. This difference reflects the degree of degradation of the material's magnetic properties. When the difference exceeds a set threshold, such as exceeding 20% ​​of the reference value, the pulse width needs to be increased proportionally. The increase is proportional to the difference; the larger the difference, the more the pulse width increases, thereby compensating for the degradation of the material's performance. The generation and output process of the excitation current pulse sequence involves a power amplification stage. The adjusted pulse parameter combination includes multiple elements such as frequency, width, and amplitude. These parameters are encoded into control signals and input to a power amplifier. The power amplifier amplifies the low-power control signals to a power level sufficient to drive the excitation coil, typically requiring the amplification of milliwatt-level signals to tens or even hundreds of watts. The amplified pulse sequence generates an alternating magnetic field through the excitation coil, directly acting on the magnetic materials of the energy storage system. Dynamic monitoring of the hysteresis loop area reveals the real-time changes in energy loss. The hysteresis loop measured at each moment has a corresponding area value. The difference in area between two adjacent moments divided by the time interval yields the result. The area change rate, in physical terms, represents the increase in hysteresis loss per unit time. When the change rate is positive and continuously increasing, it indicates that the hysteresis loss is accelerating. When the change rate tends to stabilize, it indicates that the system has reached a new equilibrium state. The criterion for judging the hysteresis loop expansion speed is the trend of the area change rate. If the change rate at multiple consecutive measurement points shows an increasing trend, it indicates that the hysteresis loop is expanding rapidly and the hysteresis loss of the material is increasing sharply. Conversely, if the change rate shows a decreasing trend or even becomes negative, it indicates that the optimized excitation pulse sequence is playing a role and effectively suppressing the expansion of the hysteresis loop.

[0033] like Figure 1 As shown, in step S5, the excitation current pulses during the relay holding time are adjusted in real time by optimizing the excitation current pulse sequence and the hysteresis loop expansion speed parameter, generating the excitation current sequence, collecting the core temperature rise rate and the distribution of local high temperature areas, and determining the energy dissipation of magnetic domains.

[0034] Specifically, the real-time excitation control of relays in energy storage systems requires precise coordination of multiple parameters; The optimized excitation current pulse sequence includes frequency, width, and amplitude parameters calculated in the early stage. These parameters form a dynamic mapping relationship with the hysteresis loop expansion speed. When the hysteresis loop expands rapidly, it indicates that the magnetic properties of the material are degrading. At this time, it is necessary to adjust the excitation parameters to compensate for this degradation. The magnetic field sensor is placed at a key position in the relay core to monitor the changes in magnetic flux density in real time. Whenever the magnetic flux density deviates from the normal range, the control system will adjust the pulse amplitude and interval time accordingly. The relay holding time refers to the time period from contact engagement to release. During this time, the excitation current must be maintained at an appropriate level. When the magnetic flux density drops below the threshold, the pulse amplitude needs to be increased to improve the magnetic field strength; when the magnetic flux density is too high, the pulse amplitude should be reduced to avoid magnetic saturation. The adjustment of the pulse interval is also important. Too short an interval will lead to increased eddy current loss, while too long an interval will affect the magnetization effect. Through this real-time adjustment mechanism, the generated excitation current sequence can accurately match the actual needs of the system. Infrared thermal imaging technology plays a key role in core temperature monitoring. Hysteresis loss and eddy current loss are ultimately converted into heat energy, causing the core temperature to rise. Infrared thermal imagers can capture temperature distribution images on the core surface with a resolution of millimeters. By continuously collecting temperature data and calculating the temperature difference between adjacent moments divided by the time interval, the temperature rise rate of each region can be obtained. When the temperature rise rate of a certain region is significantly higher than that of the surrounding regions, it indicates that there is abnormal energy loss at that location. The calculation of magnetic domain energy dissipation power is based on thermodynamic principles. The temperature rise rate of the high-temperature region multiplied by the volume of the region, and then multiplied by the specific heat capacity of the material, gives the energy dissipation power per unit time. For example, the specific heat capacity of silicon steel sheets is approximately 460 joules per kilogram per Kelvin. When the temperature rise rate of a region with a volume of 10 cubic centimeters reaches 0.5 Kelvin per second, the corresponding power loss can be calculated. This power value directly reflects the energy loss during the magnetic domain movement process in that region. By establishing a time series of energy dissipation power values, the fluctuation amplitude can be calculated, i.e., the difference between the maximum and minimum values, and then divided by the average value to obtain the relative volatility. When this ratio remains within a small range, it indicates that the system is operating smoothly; when the ratio exceeds a preset threshold, such as exceeding 30%, it indicates that there are unstable factors in the system.

[0035] like Figure 1 As shown, in step S6, the temperature of the local high-temperature region is analyzed by the core temperature rise rate, the distribution of local high-temperature regions, and the energy dissipation data of magnetic domains. If the temperature exceeds the preset threshold, the excitation current pulse is adjusted to obtain stable core temperature rise control data and determine the coercivity change range.

[0036] Specifically, core temperature control plays a crucial role in the operation of energy storage systems; When the temperature in a certain area reaches 85 degrees Celsius, while the preset safety threshold is 80 degrees Celsius, the temperature exceeds the limit by 5 degrees Celsius. At this time, according to the ratio between the excess value and the threshold, i.e., 5 / 80 is approximately 6.25%, the amplitude of the excitation current pulse is reduced accordingly. This proportional adjustment mechanism can accurately control the temperature rise and avoid system oscillation caused by over-adjustment. The formation of the temperature distribution curve requires the support of multiple temperature data points. Multiple temperature sensors are arranged on the surface of the iron core. A typical arrangement is to arrange three sensors at 120-degree intervals on the upper, middle and lower cross sections of the iron core, for a total of nine measuring points. Each sensor records the temperature value at a fixed sampling frequency. Connecting these discrete temperature data points forms a curve that reflects the overall temperature distribution of the iron core. The peak point of the curve often corresponds to the area with the highest magnetic flux density or the most severe loss. The coordinates of the hot spot are determined by a three-dimensional positioning method. Each temperature sensor has its fixed spatial coordinates. When a sensor detects the highest temperature value among all measuring points, its coordinates are marked as the hot spot location. This coordinate information is helpful for subsequent targeted cooling measures. For example, the design of the heat dissipation airflow can be enhanced at the hot spot location. The calculation of the heat dissipation efficiency parameter involves the principle of heat conduction. The temperature gradient refers to the temperature change per unit distance, which is obtained by dividing the temperature difference between adjacent measuring points by the distance between the measuring points. The thermal conductivity is an inherent property of the material. The thermal conductivity of silicon steel sheets is usually in the range of 20-50 watts per meter per Kelvin. The product of the temperature gradient and the thermal conductivity gives the heat flux density. Multiplying this by the heat dissipation area gives the heat dissipation power. The ratio obtained by comparing the heat dissipation power with the magnetic loss power of the area is the heat dissipation efficiency parameter. When this parameter is less than 1, it indicates that the heat dissipation is insufficient and heat is accumulating. The characteristic of coercivity changing with temperature reflects the magnetic stability of the material. The hysteresis loop is measured at different temperatures using a magnetic tester, and the coercivity value is extracted from the loop. The coercivity of silicon steel sheet at room temperature may be 50 amperes per meter. When the temperature rises to 100 degrees Celsius, the coercivity may decrease to 40 amperes per meter. This difference of 10 amperes per meter is the range of coercivity change. The decrease in coercivity means that the material is more easily magnetized and demagnetized. Although this reduces hysteresis loss, it may also affect the stability of the magnetic circuit.

[0037] like Figure 1 As shown, in step S7, based on the core temperature rise control data and coercivity change amplitude, the domain flipping speed and hysteresis loop shape stability of the core under the charging and discharging switching frequency are verified, a comprehensive verification report including magnetic flux distribution uniformity, hysteresis loss energy and temperature control performance is generated, and the final core optimization configuration and saturation magnetic induction intensity are determined.

[0038] Specifically, the deviation rate of the magnetic domain flipping completion time is a key indicator for evaluating the stability of an energy storage system. During the initial system operation, the magnetic domain reversal completion time was measured to be 2 milliseconds, and this time was recorded as a baseline value. After a period of operation, at the same charge-discharge switching frequency, the measured reversal time became 2.2 milliseconds. The deviation rate was calculated by dividing the time difference of 0.2 milliseconds by the initial time of 2 milliseconds, resulting in a deviation rate of 10%. This deviation rate directly reflects the degree of degradation of the material's magnetic properties. The larger the deviation rate, the more significant the performance degradation of the system. Determining the stability of the hysteresis loop shape requires continuous monitoring of multiple magnetic property parameters. The hysteresis loop tester measures a complete hysteresis loop at fixed time intervals to extract two key parameters: coercivity and remanence. In the first measurement, the coercivity was 50 amperes per meter and the remanence was 1.2 Tesla; in the second measurement, the coercivity became 48 amperes per meter and the remanence was 1.18 Tesla. By calculating the rate of change of values ​​between the two adjacent measurements, the rate of change of coercivity was 4% and the rate of change of remanence was 1.67%. When these rates of change remain within a small range, it indicates that the shape of the hysteresis loop is basically stable. The calculation of the uniformity index of magnetic flux distribution was carried out using statistical methods. Multiple magnetic flux density measurement points arranged at different locations on the iron core will yield a set of data. For example, if the magnetic flux density values ​​of 10 points are measured to be between 1.4 and 1.6 Tesla, the standard deviation of this set of data is calculated. Assuming it is 0.05 Tesla and the average value is 1.5 Tesla, the uniformity index is 0.05 divided by 1.5, which is approximately 3.3%. The smaller this percentage, the more uniform the magnetic flux distribution and the higher the iron core utilization rate. The calculation of cumulative hysteresis loss energy takes into account the time accumulation effect. The area of ​​the hysteresis loop in each charge and discharge cycle represents the energy loss of a single cycle. Multiplying this area value by the number of cycles already run gives the cumulative loss. The evaluation of temperature control performance depends on the temperature fluctuation range. Find the highest temperature point of 85 degrees Celsius and the lowest temperature point of 65 degrees Celsius from the temperature distribution curve. The difference of 20 degrees Celsius between the two is the temperature fluctuation range. The smaller the fluctuation range, the more accurate the temperature control. The comprehensive verification report integrates the above three indicators to form a comprehensive evaluation of system performance. When the uniformity of magnetic flux distribution is less than 5%, the cumulative hysteresis loss energy is within an acceptable range, and the temperature fluctuation is less than 25 degrees Celsius, the core configuration corresponding to this set of parameters is determined to be the optimal configuration. Under this configuration, the maximum value obtained by measuring the magnetic flux density, such as 1.8 Tesla, is the saturation magnetic induction intensity of the system.

[0039] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0040] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and rules of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for energy-saving control of high and low voltage DC relays in new energy sources, characterized in that, Includes the following steps: S1. Obtain the relay holding status index during the charging and discharging switching of the energy storage system, record the switching frequency and holding time, collect the core magnetic flux density fluctuation data, determine the uniformity of magnetic flux distribution and the local magnetic saturation distribution characteristics, and determine the magnetic domain orientation angle and size distribution through magnetic induction intensity measurement. S2. Based on the uniformity of magnetic flux distribution and the characteristics of local magnetic saturation distribution, combined with the orientation angle and size distribution of magnetic domains, the mapping relationship between the stacking angle of silicon steel sheets and the magnetic flux path deviation is analyzed. The magnetic domain wall movement resistance is calculated based on the magnetic domain boundary stress. The magnetic domain flipping speed is determined by combining the magnetic field change rate. The hysteresis loop width parameter is measured. S3. Perform frequency domain analysis on the magnetic flux density fluctuation data, the magnetic flux path deviation, the charge-discharge switching frequency and the magnetic domain flipping speed. Obtain the magnetic domain wall displacement distance and hysteresis loss energy by calculating the magnetic domain wall movement distance and using the energy integration method. Determine the magnetic domain flipping frequency and hysteresis loop offset. S4. Adjust the width and frequency of the excitation current pulse according to the magnetic domain reversal frequency, the hysteresis loop offset and the hysteresis loop width parameters to generate an excitation current pulse sequence. S5. Adjust the excitation current during the relay holding time by the excitation current pulse sequence, collect the core temperature rise rate and the distribution of local high temperature areas, and determine the magnetic domain energy dissipation. S6. Adjust the excitation current pulse sequence by the core temperature rise rate and the local high temperature area distribution to generate core temperature rise control data; S7. Based on the core temperature rise control data, verify the domain flipping speed and hysteresis loop shape stability of the core at the switching frequency, and determine the core optimal configuration and saturation magnetic induction intensity.

2. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, Step S1 specifically involves: By collecting the relay pull-in voltage and release voltage values ​​during the charging and discharging switching of the energy storage system using sensors, and recording the contact resistance change data for each switching, a relay operating status dataset is constructed. The magnetic flux density data of each region of the iron core are collected by Hall sensor array, and the ratio of the difference in magnetic flux density between adjacent measuring points to the distance between measuring points is calculated to determine the magnetic flux gradient value. Obtain an image of the magnetic domain structure on the surface of the iron core, extract the boundary contour of the magnetic domain structure image, and determine the orientation angle and size parameters of each magnetic domain region; Based on the magnetic domain orientation angle and size parameters, a magnetic domain distribution feature vector is generated. Combined with the magnetic flux gradient value and the relay operating state dataset, the correspondence between the local magnetic saturation distribution characteristics and the contact resistance change trend is determined, and the relay performance degradation feature parameter distribution is generated.

3. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, Step S2 specifically involves: Data on the stacking angle of silicon steel sheets were collected to obtain the magnetic flux distribution values ​​under different stacking angles. Based on the angle between the magnetic domain orientation angle and the grain direction of the silicon steel sheet, the actual direction of the magnetic flux path was calculated. By comparing it with the reference direction perpendicular to the stacking plane, a dataset of the correspondence between the stacking angle and the path deviation value was generated. The stress distribution of the magnetic domain boundary profile is measured by strain sensors, and the resistance value of the magnetic domain wall movement is calculated by combining the magnetostriction coefficient of the material and the thickness of the magnetic domain wall. The domain flipping speed parameter is determined based on the ratio of the derivative of the applied magnetic field strength with respect to time to the resistance value of the domain wall movement. The relationship curves between magnetization and magnetic field strength at different domain flipping velocities are recorded using a hysteresis loop tester. The difference between the magnetization value when the magnetic field strength is zero and the magnetic field strength value when the magnetic field strength is zero is extracted from the relationship curve to determine the hysteresis loop width parameter.

4. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, The frequency domain analysis of magnetic flux density fluctuation data, magnetic flux path deviation, and magnetic domain flipping velocity in step S3 specifically involves: The time series data of the magnetic flux density fluctuation data and the magnetic flux path deviation are obtained, and the spectral distribution characteristics are generated by fast Fourier transform to determine the correspondence between the main frequency and the switching frequency of the magnetic flux density fluctuation. The domain wall displacement distance is calculated by integrating the domain flipping velocity over the magnetization period.

5. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, In step S4, adjusting the width and frequency of the excitation current pulse based on the domain reversal frequency, hysteresis loop offset, and hysteresis loop width parameters specifically involves: The target frequency value of the excitation current pulse is calculated based on the product of the domain reversal frequency and the hysteresis loop offset. The pulse width adjustment amount is determined by the difference between the hysteresis loop width parameter and the initial measurement value, and the adjusted excitation current pulse parameter combination is generated.

6. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, The step S5, which involves adjusting the excitation current during the relay holding time using an excitation current pulse sequence and collecting the core temperature rise rate and the distribution of local high-temperature areas, specifically involves: Based on the excitation current pulse sequence and combined with the real-time measured change in magnetic flux density, the pulse amplitude and interval are adjusted to generate an excitation current sequence that matches the shape stability of the hysteresis loop. Temperature distribution data of various regions of the iron core are collected by an infrared thermal imager. The ratio of the temperature difference between adjacent moments to the time interval in the temperature distribution data is calculated to determine the temperature rise rate of the iron core.

7. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, In step S6, adjusting the excitation current pulse sequence based on the core temperature rise rate and the distribution of local high-temperature regions to generate core temperature rise control data specifically involves: Extract the highest temperature value in the local high temperature region distribution, and adjust the pulse amplitude of the excitation current pulse sequence according to the ratio between the highest temperature value and a preset threshold. A temperature distribution curve is generated from the temperature distribution data. The spatial coordinates of the temperature peak point are identified as the hot spot location coordinates. The product of the temperature gradient and thermal conductivity in the hot spot area is calculated to determine the heat dissipation efficiency parameter.

8. The energy-saving control method for new energy high and low voltage DC relays according to claim 1, characterized in that, In step S7, based on the core temperature rise control data, the verification of the domain flipping speed and hysteresis loop shape stability of the core at the switching frequency specifically involves: Based on the core temperature rise control data, the time for magnetic domain flipping to complete at the switching frequency is measured, and the deviation rate from the initial measurement time is calculated. The coercivity and remanence values ​​of the hysteresis loop shape stability are recorded using a hysteresis loop tester, and the rate of change of values ​​at adjacent time points is calculated to determine the shape stability of the hysteresis loop.

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