Thyristor control method of aircraft electric pulse deicing device

Abstract

The invention provides a thyristor control method for an aircraft electric pulse deicing device, relates to the technical field of thyristor control and regulation, and aims to acquire and fuse multi-dimensional working condition data such as icing thickness, icing rate, environment temperature, environment humidity and flight data in real time, and calculate attitude influence factors to realize the control of the aircraft electric pulse deicing device according to the real-time attack angle and roll angle change of the aircraft. The icing aggravation trend of different pneumatic surfaces is predicted, the comprehensive icing severity index ISI is calculated for real-time quantitative evaluation, the deicing action can be automatically triggered in the early stage or the middle stage of ice condition development according to the icing speed, the low predefined interval, the middle predefined interval and the high predefined interval are judged according to the value of the ISI, and the deicing effect is improved. Compared with the prior art, the method has the advantages that deicing strategies with different emergency degrees are directly mapped, a time window from icing risk identification to effective deicing intervention application is shortened through a dynamic pre-judgment and hierarchical response mechanism, the coping capacity for sudden strong icing working conditions is improved, and the flight safety risk caused by untimely deicing is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of thyristor control and regulation technology, specifically to a thyristor control method for an aircraft electrical pulse de-icing device. Background Technology

[0002] Electro-pulse de-icing devices apply high-voltage pulse current to induction coils embedded under the aircraft skin, generating instantaneous electromagnetic force that causes the skin to vibrate at low amplitude and high frequency, thereby breaking up and peeling off the ice layer. The core actuator is a high-voltage, high-current thyristor, and the required pulse is generated by controlling the thyristor's conduction. Currently, most existing aircraft electro-pulse de-icing control methods use fixed parameter modes, that is, preset one or several sets of fixed pulse amplitudes, frequencies, widths, and energies. This method has the following problems: Problem 1: The thyristor parameters are fixed and the control logic is simple. It relies on the icing sensor alarm to apply a fixed energy pulse, but lacks real-time judgment of the icing rate and thickness. It is not timely in response to sudden severe icing situations, and cannot dynamically adjust the thyristor parameters, resulting in a large response lag and safety risks. Question 2: Due to the complex and varied flight environment, such as high-altitude low-temperature and dry environments and low-altitude high-humidity environments, different types of icing occur. When de-icing is performed using a single preset fixed set of thyristor pulse parameters, the de-icing energy is either excessive, causing skin fatigue damage or premature electrode failure, or insufficient, resulting in incomplete de-icing. This easily leads to resource waste, increases the ineffective load on the aircraft's electrical system, and thus causes problems such as insufficient resource utilization, low de-icing efficiency, and poor de-icing adaptability. Summary of the Invention

[0003] To achieve the above objectives, the present invention provides the following technical solution: a thyristor control method for an aircraft electrical pulse de-icing device, the method comprising: Real-time acquisition of multi-dimensional operating condition data of aircraft; calculation and generation of comprehensive icing severity index based on multi-dimensional operating condition data; and determination of dominant icing type. Based on the comprehensive icing severity index, a predefined interval is determined. Based on the predefined interval and the dominant icing type, a dynamic parameter mapping table is queried to generate a target pulse control parameter set. Based on the target pulse control parameter set, a predicted command energy is calculated and generated. A thyristor trigger signal is generated based on the target pulse control parameter set, and a current pulse is applied to de-icing after the thyristor is turned on based on the thyristor trigger signal. Acquire the actual waveform data of the current pulse and the residual ice thickness data after de-icing; The actual output energy is calculated based on the actual waveform data. The energy deviation between the actual output energy and the predicted command energy is calculated. The thyristor trigger signal is corrected based on the energy deviation. The dynamic parameter mapping table is optimized and adjusted based on the residual icing thickness data.

[0004] Furthermore, the real-time acquisition of multi-dimensional aircraft operating condition data, the calculation of a comprehensive icing severity index based on the multi-dimensional operating condition data, and the determination of the dominant icing type include: The multidimensional operating condition data includes ambient temperature, ambient humidity, icing thickness, icing rate and flight data. The flight data includes flight altitude, flight speed and flight attitude angle. An aircraft body coordinate system is generated based on the flight data. The multidimensional operating condition data is obtained for time synchronization and unified coordinate processing. The icing thickness and icing rate are mapped to the aircraft body coordinate system. The liquid water content is calculated based on multi-dimensional operating condition data. The dominant icing type is determined based on the liquid water content, ambient temperature, and flight speed, and the confidence level of the icing type is calculated. The attitude influence factor is calculated based on flight data, and the comprehensive icing severity index is calculated based on the attitude influence factor and multi-dimensional operating condition data. The comprehensive icing severity index ranges from [0,10].

[0005] Furthermore, the predefined interval is determined based on the comprehensive icing severity index. This predefined interval includes a low interval, a medium interval, and a high interval. Based on the predefined interval and the dominant icing type, a dynamic parameter mapping table is queried to generate a target pulse control parameter set, including: A predefined interval is defined by setting an interval threshold, and a dynamic parameter mapping table is established with the predefined interval and the dominant icing type as the index. The dynamic parameter mapping table contains a set of pulse control parameters corresponding to the dominant icing type in different predefined intervals. The set of pulse control parameters includes pulse frequency, pulse width and energy level coefficient. The comprehensive icing severity index is compared with the interval threshold to determine the predefined interval to which it belongs. Based on the predefined interval and the dominant icing type, the dynamic parameter mapping table is queried to obtain the pulse frequency, pulse width and energy level coefficient. Calculate the pulse charging voltage command based on the energy level coefficient and attitude influence factor; The target pulse control parameter set is generated by integrating the pulse charging voltage command, pulse frequency, pulse width, and energy level coefficient.

[0006] Furthermore, the interval threshold includes a first interval threshold and a second interval threshold, and the second interval threshold is greater than the first interval threshold; When the comprehensive icing severity index is less than or equal to the threshold of the first interval, it is judged as a low interval; When the comprehensive icing severity index is greater than the threshold of the second interval, it is judged as a high interval; When the comprehensive icing severity index is less than or equal to the second interval threshold and greater than the first interval threshold, it is determined to be in the middle interval.

[0007] Furthermore, the dynamic parameter mapping table sets the value range of the energy level coefficient. Each predefined interval is set with an interval range, and the interval range is a subset of the value range. A base value of the energy level coefficient is set based on the interval range.

[0008] Furthermore, the step of generating a thyristor trigger signal based on the target pulse control parameter set, and applying a current pulse for de-icing after driving the thyristor to conduct based on the thyristor trigger signal includes: The pulse frequency and pulse width of the target pulse control parameter set are programmed to generate thyristor trigger signals; Obtain the connection topology of the thyristor, decode and process the thyristor trigger signal, and generate N trigger pulse sequences; The pulse charging voltage command is parsed into charging voltage data. Based on the N-channel trigger pulse sequence and the charging voltage data, the thyristors are turned on in sequence to generate current pulses for de-icing.

[0009] Furthermore, the step of obtaining the thyristor connection topology, decoding the thyristor trigger signal, and generating N trigger pulse sequences includes: The driving circuit and digital delay generator in the connection topology of the thyristors are obtained. The driving circuit includes a master thyristor and n slave thyristors. After receiving the thyristor trigger signal, the digital delay generator immediately generates the first trigger pulse to trigger the main thyristor to conduct. After a preset first delay time, a second trigger pulse is generated to trigger the first thyristor to turn on, until all thyristors that need to be turned on receive a trigger pulse. All trigger pulses are then integrated according to the trigger time of the thyristors to form an N-path trigger pulse sequence.

[0010] Furthermore, the correction of the thyristor trigger signal based on energy deviation includes: The actual waveform data is acquired and integrated over the entire pulse width to obtain the actual output energy. Obtain the preset load circuit parameters, and calculate the predicted command energy based on the pulse charging voltage command and pulse width; The energy deviation between the predicted command energy and the actual output energy is calculated. A first deviation threshold and a second deviation threshold are set to judge the energy deviation. The thyristor trigger signal is corrected based on the judgment result, and the second deviation threshold is greater than the first deviation threshold.

[0011] Furthermore, the optimization and adjustment of the dynamic parameter mapping table based on residual icing thickness data includes: The residual ice thickness data after the applied current pulse is obtained is compared with the preset clearing standard threshold. If the residual ice thickness data is less than the clearing standard threshold, it is determined that the de-icing is completed. If the residual ice thickness is greater than or equal to the clearing standard threshold, it is determined that the de-icing is not complete. When it is determined that de-icing is incomplete, the current de-icing decision is recorded. The current de-icing decision includes the predefined range used for this de-icing, the dominant icing type, and the energy level coefficient. Query and adjust the base value of the energy level coefficient corresponding to the current de-icing decision from the dynamic parameter mapping table.

[0012] Furthermore, the generation of the target pulse control parameter set also includes: Obtain the energy level coefficient from the target pulse control parameter set and calculate the real-time overcurrent protection threshold. The system monitors the instantaneous current of the thyristors in real time. If the instantaneous current exceeds the real-time overcurrent protection threshold, it immediately forces the shutdown of all thyristor trigger signals.

[0013] This invention provides a thyristor control method for an aircraft electrical pulse de-icing device. It has the following beneficial effects: 1. This invention collects and integrates multi-dimensional operating condition data such as icing thickness, icing rate, ambient temperature, ambient humidity, and flight data in real time. By calculating attitude influence factors, it can predict the trend of icing intensification on different aerodynamic surfaces based on real-time changes in the aircraft's angle of attack and roll angle. This allows for prediction before the ice layer develops to a dangerous thickness. Quantitative assessment is performed by calculating the Comprehensive Icing Severity Index (ISI). Based on continuous and real-time calculation of the ISI, de-icing actions can be automatically triggered in the early or middle stages of icing development, depending on the icing rate. Simultaneously, based on the ISI value, three predefined intervals (low, medium, and high) are directly mapped to de-icing strategies of different urgency levels. This changes the slow response mode of traditional sensing, alarm, and fixed actions, adopting a rapid closed-loop transformation of sensing, assessment, and graded precise response. Through dynamic prediction and graded response mechanisms, the time window from identifying icing risk to applying effective de-icing intervention is shortened, improving the ability to respond to sudden severe icing conditions and effectively reducing flight safety risks caused by untimely de-icing.

[0014] 2. This invention combines ice type identification with ISI quantitative assessment to construct a two-dimensional dynamic parameter mapping table. Based on the distinct mechanical properties of frost, hoarfrost, and clear ice, it specifies differentiated optimal pulse frequency and pulse width ratio strategies. For hoarfrost, a high-frequency, narrow pulse width is used to generate micro-vibrations for disintegration; for frost, a low-frequency, wide pulse width is used to generate greater shear force for peeling. This ensures that the output pulse energy pattern strictly matches the actual physical requirements of ice layer breakage, avoiding skin overload, electrode erosion, and energy waste caused by using a single high-energy mode, and also overcoming... Incomplete de-icing due to insufficient energy is addressed by employing a dual-loop closed-loop feedback system. The inner loop uses pulse waveform energy feedback to fine-tune the voltage in real time, while the outer loop uses residual ice thickness feedback to offline optimize the parameters of the dynamic parameter mapping table. This continuously compensates for load changes and device aging, and performs self-learning optimization tailored to the specific characteristics of each aircraft. As a result, it maintains extremely high energy delivery accuracy throughout the aircraft's entire lifecycle, ensuring de-icing effectiveness under various complex operating conditions while significantly reducing ineffective energy consumption, improving the energy utilization efficiency of the entire aircraft power supply system, and extending the service life of the de-icing device itself. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the steps of a thyristor control method for an aircraft electrical pulse de-icing device according to the present invention. Figure 2 This is a data flow diagram of a thyristor control method for an aircraft electrical pulse de-icing device according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] like Figures 1 to 2 As shown, a thyristor control method for an aircraft electrical pulse de-icing device includes: Step S100: Collect multi-dimensional operating condition data of the aircraft in real time, calculate and generate the comprehensive icing severity index (ISI) based on the multi-dimensional operating condition data, and determine the dominant icing type. Step S101: Multidimensional operating condition data includes ambient temperature, ambient humidity, icing thickness, icing rate and flight data. Flight data includes flight altitude, flight speed and flight attitude angle. An aircraft body coordinate system is generated based on the flight data. Multidimensional operating condition data is acquired for time synchronization and unified coordinate processing. Icing thickness and icing rate are mapped to the aircraft body coordinate system. The multi-dimensional operating condition data is collected in real time through a dedicated sensor network integrated on the aircraft: ambient temperature and humidity are directly measured by meteorological probes installed on the wing leading edge or nose, such as platinum resistance temperature sensors and capacitive humidity sensors; icing thickness and icing rate are obtained through icing detectors distributed on key skin surfaces such as the wings and tail. These icing detectors include ultrasonic pulse echo detectors and optical scattering sensors. The ultrasonic pulse echo detectors emit high-frequency sound waves and receive ice reflection signals to calculate icing thickness, while the optical scattering sensors analyze ice crystal growth rates using laser diffraction. Icing rate is taken; the flight altitude in the flight data is converted by the atmospheric data computer through static pressure measurement, the flight speed is calculated by the difference between dynamic pressure and static pressure measured by the pitot tube, and the flight attitude angles, including pitch angle, roll angle and yaw angle, are calculated by the fusion of gyroscope and accelerometer in the inertial measurement unit (IMU). The specific calculation method can be obtained from the existing publicly available technology, which will not be elaborated here. The flight data is used to reflect the spatial motion state of the aircraft in real time and provide a dynamic benchmark for icing assessment. For example, the flight speed affects the trajectory of water droplets that hit the skin by the airflow, and the flight attitude angle changes the icing distribution on the local windward side. The aircraft body coordinate system is generated based on the flight attitude angle data in the flight data. With the aircraft's center of gravity as the origin, the X-axis points to the nose along the longitudinal axis of the fuselage, the Y-axis points to the right wing along the wingspan, and the Z-axis points vertically downward according to the right-hand rule. The aircraft body coordinate system unifies the sensor data scattered at various locations on the fuselage into the same spatial reference system, eliminating the measurement reference offset caused by aircraft maneuvers such as climbing and turning. When synchronizing and processing multi-dimensional operating condition data in time and with unified coordinates, the first step is to acquire multi-dimensional operating condition data collected by various sensors and devices and transmit it to the central processing unit via an airborne bus such as ARINC429 or AFDX. A high-precision synchronization clock, such as a GPS timing module, timestamps each frame of data and aligns it to the same sampling time using an interpolation algorithm. The installation positions of the icing detectors that collect icing thickness and icing rate data are pre-calibrated in the three-dimensional coordinates of the aircraft body coordinate system. Combined with the rotation matrix calculated from the current flight attitude angle, the thickness scalar value in the local coordinate system of the icing detector is converted into a component along the skin normal in the aircraft body coordinate system. The icing rate vector is decomposed into three-axis components in the aircraft body coordinate system, thereby obtaining unified spatial distribution data for the entire aircraft, providing accurate input for subsequent comprehensive icing assessment.

[0018] Step S102: Calculate the liquid water content based on multi-dimensional operating condition data; determine the dominant icing type based on the liquid water content, ambient temperature, and flight speed; and calculate the confidence level of the icing type. Where: Liquid water content (LWC) refers to the mass concentration of suspended liquid water droplets per unit volume of air. It is used to quantify the amount of water available for freezing in an icing environment and is a key parameter for determining the rate of ice formation and the dominant freezing type. Liquid water content is calculated based on multi-dimensional operating condition data. First, using the ambient temperature T and relative humidity RH, the saturated vapor pressure formula e is applied. s =6.112×exp(17.67×T / (T+243.5)) Calculate the saturated vapor pressure e s The unit is hPa. Then, based on the actual atmospheric pressure P and water vapor partial pressure e calculated from the flight altitude, and e = RH × e s / 100, the liquid water content LWC=ρ is derived from the ideal gas law. air ×(e / (R v ×T)), where ρ air R is the air density, calculated from atmospheric pressure P and ambient temperature T. v The constant for water vapor is typically 461.5 J / (kg·K); The dominant ice formation types include rime, frost ice, and clear ice. Rime has a brittle ice crystal structure, frost ice is porous and cloudy ice, and clear ice is dense and transparent ice. The classification is based on the interaction of liquid water content, ambient temperature, and flight speed. When LWC > 0.5 g / m³, temperature is close to 0℃, and flight speed is low, water droplets have sufficient time to spread and freeze to form clear ice. When LWC < 0.2 g / m³, temperature is below -15℃, and flight speed is high, water droplets freeze instantly to form rime. Intermediate conditions tend to result in... Frost and ice are generated, and the flight speed is classified according to the aircraft's flight aviation standards. A three-dimensional decision space is established with liquid water content (LWC), ambient temperature (T), and flight speed (V) as axes. The physical boundaries of each icing type are defined based on wind tunnel test data. When LWC > 0.5 g / m³, T ∈ [-10℃, 0℃], and V < 200 m / s, clear ice is output; when LWC < 0.2 g / m³, T < -15℃, and V > 150 m / s, hoarfrost is output; and frost and ice are output in other ranges. Ice type confidence is an indicator that quantifies the reliability of the current dominant ice type judgment result. It is used as a weight reference for parameter adjustment in subsequent control. After LWC, T, and V are normalized, they are input into the fuzzy inference system. The membership function of each ice type is preset, such as a triangular or Gaussian function. Through the rules set in the preset rule base, such as "if LWC is high and T is high, then the membership degree of clear ice is high", the matching degree of each type is calculated. The rules in the preset rule base are based on a large number of experimental analyses and historical data of actual ice formation, combined with physical theory knowledge and preset. Finally, the maximum matching degree value is used as the confidence of the dominant ice type, realizing the credibility measurement from continuous data to discrete decision.

[0019] Step S103: Calculate the attitude influence factor based on flight data, and calculate the comprehensive icing severity index (ISI) based on the attitude influence factor and multi-dimensional operating condition data. The attitude influence factor is a correction coefficient that quantifies the effect of non-standard flight attitude on the severity of icing. It is used to capture abnormal water impact caused by airflow separation and local eddies at high angles of attack or roll angles, thereby improving the accuracy of icing assessment. The comprehensive icing severity index (ISI) is a normalized scalar indicator used to comprehensively reflect the threat level of current icing to flight safety, serving as the core input for subsequent pulse de-icing energy regulation. First, acquire the roll angle φ and pitch angle from the flight data, including the current angle of attack α and roll angle φ, and combine them with preset weighting coefficients C1, C2 and the cruise reference angle of attack α. cruise Cruise reference angle of attack α cruise Determined by the aircraft aerodynamic model, the weighting coefficients are calibrated through flight tests, typically C1 = 0.05 / degree and C2 = 0.03 / degree, according to formula K. αφ =1 + C1 × |α - α cruise |+C2×|φ|, real-time calculation of attitude influence factor K αφ ; Secondly, the multi-dimensional operating condition data is preprocessed by dividing the icing thickness d and icing rate v by the maximum design value d. max and v max Normalization is performed to determine the maximum expected icing rate v. max and maximum design icing thickness d max The anti-icing limit of the aircraft skin material is determined by the conversion of ambient temperature T and humidity H through nonlinear functions F(T) and G(H). F(T) is a piecewise exponential function, which outputs a high value when the ambient temperature T is close to 0°C, reflecting a high risk of icing. G(H) is a logarithmic function to fit the saturation effect of ambient humidity. Finally, the normalized data and the weight coefficients W are compared. th W rate W T W H By using the analytic hierarchy process (AHP), weighted summation is performed, and then multiplied by the attitude influence factor to obtain the comprehensive icing severity index (ISI), where ISI = K. αφ ×[W th ×(d / d max )+W rate ×(v / v max )+W T ×F(T)+W H ×G(H)], such as W th =0.3、W rate =0.3、W T =0.2、W H =0.2, and Wth +W rate +W T +W H =1, the range of the Integrated Icing Severity Index (ISI) is [0,10]; the calculation of the ISI is periodically performed in the onboard processor to ensure that the ISI dynamically responds to changes in the icing environment.

[0020] Step S200: Determine the predefined interval based on the comprehensive icing severity index; query the dynamic parameter mapping table based on the predefined interval and the dominant icing type; generate the target pulse control parameter set; and calculate and generate the predicted command energy based on the target pulse control parameter set. Step S201: Set interval thresholds to divide predefined intervals, and establish a dynamic parameter mapping table indexed by the predefined intervals and the dominant icing type. The dynamic parameter mapping table contains the pulse control parameter set corresponding to the dominant icing type in different predefined intervals. The pulse control parameter set includes pulse frequency, pulse width, and energy level coefficient, wherein: The interval thresholds include a first interval threshold M1 and a second interval threshold M2, where M2 > M1; When ISI≤M1, it is determined to be the low interval; when ISI>M2, it is determined to be the high interval; when M1<ISI≤M2, it is determined to be the middle interval. The interval thresholds are discrete boundaries that divide the continuous range of the Integrated Icing Severity Index (ISI), including the first interval threshold M1 and the second interval threshold M2, for example, M1=3 and M2=7. They are set based on the energy consumption safety boundary of the aircraft de-icing system and the statistical data of historical icing accidents, and are calibrated through icing wind tunnel tests. M1 corresponds to the initial stage of icing, when the ice thickness is less than 0.5 mm and the rate is slow, while M2 corresponds to the dangerous stage of icing, when the ice thickness exceeds 2 mm or the rate increases sharply. Based on the nonlinear characteristics of the impact of ice accumulation on aerodynamic performance and the ISI value, the predefined intervals are divided into three different de-icing response levels: low interval, medium interval, and high interval. For example, the low interval only requires preventive de-icing, while the high interval requires emergency high-energy removal, thus achieving a tiered adaptation of the control strategy. The dynamic parameter mapping table specifies that for rime ice, which has a loose structure, the low, medium, and high ranges are mapped to the first, second, and third pulse frequency and pulse width combinations, respectively. For frost ice, which has a more porous structure than clear ice and requires stronger sustained force but has a slightly lower peak impact, the low, medium, and high ranges are mapped to the fourth, fifth, and sixth pulse frequency and pulse width combinations, respectively. For clear ice, which has a dense and hard structure with extremely strong adhesion, higher peak impact force and sufficient energy deposition are required for removal, thus the low, medium, and high ranges are mapped to the seventh, eighth, and ninth pulse frequency and pulse width combinations, respectively. Within the same predefined ISI range, the first pulse frequency is higher than the fourth pulse frequency, and the first pulse width is smaller than the fourth pulse width. Dynamic parameters... The parameter ranges for pulse frequency and pulse width in the mapping table are all based on simulation optimization of the electromagnetic pulse de-icing principle (such as eddy current thermal effect and Maxwell force impact) and the skin-ice layer coupling model, and were set through flight test verification. The skin-ice layer coupling model is a simulation model established based on the relationship between the skin and ice layer in terms of mechanical action, material characteristics, and environmental factors. This model analyzes the stress changes of the ice layer and skin under temperature changes, pulse changes, and mechanical impacts; analyzes the influence of parameters such as the elasticity and adhesion strength of the ice layer and skin materials on the coupling behavior; and analyzes the impact of external environmental changes such as temperature and humidity on the ice layer growth and desorption process. The simulation results are used to define the parameter ranges for pulse frequency and pulse width in the dynamic parameter mapping table. The specific mapping rules in the dynamic parameter mapping table are as follows: When the dominant icing type is rime and the ISI is in the low range, the mapped pulse frequency is 8-12Hz and the pulse width is 20-30ms. When the dominant icing type is hoarfrost and the ISI is in the middle range, the mapped pulse frequency is 6-8Hz and the pulse width is 30-50ms. When the dominant icing type is hoarfrost and the ISI is in the high range, the mapped pulse frequency is 4-6Hz and the pulse width is 50-70ms. When the dominant icing type is frost ice and the ISI is in the low range, the mapped pulse frequency is 5-7Hz and the pulse width is 45-60ms. When the dominant icing type is frost ice and the ISI is in the middle range, the mapped pulse frequency is 3-5Hz and the pulse width is 70-90ms. When the dominant icing type is frost ice and the ISI is in the high range, the mapped pulse frequency is 2-4Hz and the pulse width is 95-115ms.

[0021] When the dominant icing type is clear ice and the ISI belongs to the low range, the mapped pulse frequency is 4 - 6 Hz, and the pulse width is 50 - 65 ms; compared with rime ice, a slightly higher frequency or slightly wider pulse width is used to adjust the force spectrum in the same range; When the dominant icing type is clear ice and the ISI belongs to the medium range, the mapped pulse frequency is 2.5 - 4.5 Hz, and the pulse width is 75 - 95 ms; When the dominant icing type is clear ice and the ISI belongs to the high range, the mapped pulse frequency is 1.5 - 3.5 Hz, and the pulse width is 100 - 120 ms.

[0022] The dynamic parameter mapping table is a two-dimensional query table jointly indexed by predefined ranges and dominant icing types, containing a parameter set of pulse frequency, pulse width, and energy level coefficient, which is used to directly convert the complex working condition judgment results into executable electrical instructions. Existing strategies usually adopt a single parameter combination, such as a fixed frequency of 5 Hz and a width of 50 ms, ignoring the dynamic differences in icing types and severity, resulting in insufficient or excessive deicing energy. The use of a dynamic mapping table is based on the dual dimensions of the physical properties of ice layers such as the high brittleness of rime ice and the strong adhesion of clear ice, and the ISI range, achieving adaptive matching; for example, for rime ice in the high range, a low pulse frequency of 4 - 6 Hz and a long pulse width of 50 - 70 ms are used to enhance the penetration ability, thereby improving the deicing efficiency and reducing the risk of skin damage; The dynamic parameter mapping table further includes the value range and base value of the energy level coefficient corresponding to the predefined range of each dominant icing type. The energy level coefficient is used to globally adjust the energy reference of the pulse according to the severity and type of icing. The energy level coefficient E level It is set according to the predefined range to which the icing type and the comprehensive icing severity index (ISI) belong. Its value range is usually between 0.5 and 2.5. The interval range of the energy level coefficient corresponding to each predefined range is generally set as follows; Low range (ISI ≤ M1), the energy requirement is low, E level Is set to a lower range, such as 0.7 - 1.0; Medium range (M1 < ISI ≤ M2), the energy requirement is medium, E level Is set to a medium range, such as 1.0 - 1.5; High range (ISI > M2), the energy requirement is high, E level Is set to a higher range, such as 1.5 - 2.2; At the same time, for different dominant icing types, within the predefined range of the same dominant icing type, a base value of the energy level coefficient is set. The base value ∈ interval range ∈ value range. The base value of the energy level coefficient is set from within the interval range, and the energy level coefficient can be set differently: For rime ice, due to its loose structure, the required energy is relatively low, and the lower limit of the above range can be taken as the base value; For frost and ice, since they have strong adhesion and require moderate energy, the middle value can be taken as the base value within the above range. For clear ice, since it has the strongest and densest adhesion and requires the most energy, the upper limit of the above range can be taken as the base value. For example, in the high-frequency range, the E value corresponding to rime ice is... level The base value can be set to 1.6, 1.8 for frost ice, and 2.0 for clear ice. The specific values ​​or ranges are determined through ground icing wind tunnel tests and calibration of the aircraft skin coil system. The base value of the energy level coefficient is adjusted according to the amplitude in step S505 when de-icing is not complete.

[0023] The pulse frequency represents the number of pulses per unit time, affecting the rhythm of ice fatigue breakage; the pulse width represents the conduction time of a single pulse, determining the duration of electromagnetic force action; the energy level coefficient is a scaling factor of the reference voltage that controls the pulse energy amplitude; the pulse frequency, pulse width, and energy level coefficient are set according to the de-icing mechanical requirements of different icing types and ISI ranges.

[0024] Step S202: Compare the comprehensive icing severity index with the interval threshold to determine the predefined interval to which it belongs; based on the predefined interval and the dominant icing type, query the dynamic parameter mapping table to obtain the pulse frequency, pulse width and energy level coefficient. When querying the dynamic parameter mapping table based on the predefined interval and the dominant icing type, the obtained pulse frequency, pulse width and energy level coefficient are all preset interval ranges, rather than a single specific parameter. After obtaining these interval ranges, the upper and lower limits of the interval ranges are used as boundaries, and the relative position of the current Integrated Icing Severity Index (ISI) within the predefined interval is used as the interpolation factor. For example, if the query result indicates that the rime ice is in the low range, the pulse frequency range is 8-12Hz, and the pulse width range is 20-30ms, and if the current ISI value is close to the upper boundary of the range, such as M1=3 and the current ISI=2.9, then the pulse frequency is set to a specific value close to 12Hz, such as 11.5Hz, and the pulse width is set to a specific value close to 20ms, such as 21ms, through linear interpolation; if the ISI is close to the lower boundary of the range, then the value tends to the lower limit. The energy level coefficient sets a base value for each predefined range of dominant icing type. The base value of the energy level coefficient is within the range of the energy level coefficient. Through refined icing wind tunnel tests and specific values, for example, within the value range of 0.7-2.2, the base value of "clear ice - high range" is set to 2.0, and the base value of "rime - low range" is set to 0.8. When selecting the energy level coefficient, the basic value of the energy level coefficient can be directly selected as the specific value, or the differentiated setting of the energy level coefficient in step S201 above can be used to ensure that the control parameters can still be fine-tuned based on the actual icing severity within the macro strategy framework, thereby improving the precision of control. Step S203, based on the energy level coefficient E level and attitude influence factor K αφ Calculate the pulse charging voltage command U; U = U base ×E level ×K αφ , among which, U base The reference voltage, pulse charging voltage command, is the target value for controlling the charging voltage of the energy storage capacitor. It is used to precisely set the energy amplitude of subsequent discharge pulses, directly determining the magnitude of the electromagnetic force and the intensity of the thermal effect acting on the de-icing coil; reference voltage U base It is a base voltage value obtained through system-level calibration. In a laboratory environment, a series of tests are conducted on a specific combination of de-icing coils and skin materials to determine the minimum pulse energy required to reliably remove standard thickness ice, such as 2mm ice. The corresponding charging voltage is then calculated in reverse based on the load circuit resistance and capacitance values. This voltage is stored as the reference voltage and serves as the calculation basis for all energy regulation. Step S204 integrates the pulse charging voltage command, pulse frequency, pulse width, and energy level coefficient to generate a target pulse control parameter set. The target pulse control parameter set is a set of specific electrical control parameters that have been calculated and selected and can be directly used to drive the hardware to perform de-icing actions. It transforms the abstract icing condition judgment into a programmable physical quantity command. The target pulse control parameter set includes core parameters such as pulse frequency, pulse width, and pulse charging voltage command. After the interval query and interpolation refinement in step S202 and the voltage calculation in step S203, all the data in the target pulse control parameter set have become specific values, such as a frequency of 10.5Hz, a width of 45ms, and a voltage command of 1500V, rather than range values, to ensure that the control signal can be accurately executed by the timer and power module. Step S300: Generate a thyristor trigger signal based on the target pulse control parameter set, and apply a current pulse to de-icing after driving the thyristor to conduct based on the thyristor trigger signal; Step S301: Program the pulse frequency F and pulse width W of the target pulse control parameter set to generate a thyristor trigger signal; wherein, the thyristor trigger signal is a digital logic level signal used to precisely control the conduction time of the thyristor gate, and the signal characteristics of the thyristor trigger signal include period T. c High-level width W L With edge timing, based on a programmable timer to write pulse frequency and pulse width and automatic reload cycle counting, the output period is T. c =1 / F, high-level width is W L The square wave sequence is the thyristor trigger signal; Step S302: Obtain the connection topology of the thyristor, decode the thyristor trigger signal, and generate N trigger pulse sequences, where N is an integer; The drive circuit and digital delay generator in the connection topology of the thyristors are obtained. The drive circuit is used to receive the trigger pulse to drive the thyristor to conduct. The drive circuit contains one master thyristor and n slave thyristors, where n is an integer and n∈N. The digital delay generator is mainly used to generate accurate delay pulse signals, i.e. trigger pulses, to realize the timing control of the master thyristor and slave thyristors. After receiving the thyristor trigger signal, the digital delay generator immediately generates the first trigger pulse to trigger the main thyristor to turn on. After a preset first delay time, the digital delay generator generates a second trigger pulse to trigger the first thyristor to turn on, until all thyristors that need to be turned on receive a trigger pulse. All trigger pulses are then integrated according to the trigger time of the thyristors to form an N-path trigger pulse sequence.

[0025] The thyristor connection topology describes the electrical connection relationship and physical layout of multiple thyristors in a high-voltage pulse discharge circuit. It typically includes a master thyristor connected in series with multiple slave thyristors to share the high voltage; or connected in parallel to share the large current, which is used to achieve safe and reliable distribution of high voltage or large current. The thyristor connection topology is obtained by reading the circuit design file pre-stored in the control system. The file defines the master-slave relationship of each thyristor, its position on the circuit board, and its connection relationship. A digital delay generator is a programmable time delay control module that precisely decomposes a single input trigger signal into multiple trigger pulses with a specific timing sequence according to preset delay parameters. It is typically implemented by a programmable logic device (such as a CPLD) and operates by reading a preset delay time table. The N-channel trigger pulse sequence is a set of trigger pulse signals arranged sequentially on the time axis. It contains N trigger pulses, each trigger pulse corresponding to the triggering time of a thyristor. This ensures that multiple thyristors are turned on in a strict timing sequence, so as to achieve the sequential superposition of voltage or current and avoid excessive surge current caused by simultaneous conduction. The master thyristor is usually connected on the critical path of the discharge circuit, and is responsible for initial conduction and establishing the main current path. The slave thyristor is used to expand the current capacity or voltage withstand capability. The master thyristor and slave thyristor are connected and controlled through independent output channels in the drive circuit. Each channel is controlled by the trigger pulse of the corresponding channel output by the digital delay generator, thereby realizing time-division and orderly conduction.

[0026] Step S303: The pulse charging voltage command U is parsed into charging voltage data, and the thyristors are turned on in sequence based on the N-channel trigger pulse sequence and the charging voltage data to generate current pulses for de-icing. Among them, the charging voltage data is an analog voltage reference value or digital setting value that can be directly input to the thyristor after the pulse charging voltage command is converted from digital to analog. The current pulse is a strong transient current generated by releasing the electrical energy stored in the energy storage capacitor instantaneously into the de-icing coil through a conducting thyristor. This current is used to generate a strong transient magnetic field around the de-icing coil. On the one hand, the magnetic field induces eddy currents in the metal skin to generate Joule heating, and on the other hand, it interacts with the magnetic field itself to generate Maxwell stress. The combined effect of the two causes the ice layer to break and peel off from the skin.

[0027] During the execution of steps S200 and S300, to ensure the safety of the execution process, a dynamic setting of the real-time overcurrent protection threshold is also included, specifically: Obtain the energy level coefficient E from the target pulse control parameter set. level Calculate the real-time overcurrent protection threshold I protect The formula is I protect =I nominal ×E level ×K safe , among which, I nominal K is the system's nominal operating current. safe A safety factor greater than 1; During step S300, the instantaneous current of the thyristor is monitored in real time. If the instantaneous current exceeds the real-time overcurrent protection threshold I... protect If it does, all thyristor trigger signals will be forcibly shut down immediately.

[0028] Among them, the real-time overcurrent protection threshold is a dynamically changing upper limit of current, which is used to monitor whether the current is abnormal during pulse discharge and prevent current spikes caused by line short circuit, thyristor mis-conduction or abnormal load from damaging the equipment. The nominal operating current is the current at which the system operates under design conditions, using a reference voltage U. base The expected steady-state current value for discharging a standard load is calculated using Ohm's law based on the reference voltage and the nominal resistance of the load coil. The safety factor is a margin factor introduced to take into account component tolerances, temperature drift, and measurement errors. Its specific value (such as 1.2-1.5) is determined based on the reliability index of the component datasheet and the system safety design specifications. Instantaneous current refers to the instantaneous current value of the thyristor circuit that is acquired in real time by a current sensor (such as a Rogowski coil) during pulse discharge, and is used to calculate the actual output energy E. actual Furthermore, it compares the current with the real-time overcurrent protection threshold to achieve millisecond-level fast hardware protection, immediately blocking all trigger signals once the limit is exceeded.

[0029] Step S400: Obtain the actual waveform data I of the current pulse. actually（t） The data includes residual ice thickness after de-icing; actual waveform data refers to the discrete sequence data of current change over time obtained by real-time sampling and recording by a broadband current sensor (such as a Rogowski coil) connected in series in the discharge circuit during the de-icing process with applied current pulses; residual ice thickness data refers to the ice thickness value still attached to the skin, which is remeasured by ice detectors distributed in the de-icing area (such as the leading edge of the wing) after one or a series of de-icing pulses. It is used to objectively quantify the effect of this de-icing operation, determine whether the de-icing is thorough, and serve as a key input for the outer loop optimization algorithm to evaluate the effectiveness of the current energy strategy. Step S500: Calculate the actual output energy based on the actual waveform data, calculate the energy deviation between the actual output energy and the predicted command energy, perform inner loop correction on the thyristor trigger signal based on the energy deviation, perform rapid compensation on the pulse charging voltage through a millisecond-level cycle to stabilize the energy output accuracy of a single pulse, perform outer loop optimization adjustment on the dynamic parameter mapping based on the residual icing thickness data, and perform slow adjustment on the energy level coefficient in the dynamic parameter mapping table based on a second-level or single de-icing task cycle to adapt to long-term slow changes such as aircraft skin characteristics and coil aging.

[0030] Step S501, acquire actual waveform data I actually（t） Integrating over the entire pulse width yields the actual output energy E. actual ; Actual output energy refers to the total electrical energy actually converted and dissipated by a single current pulse on the de-icing coil load. It reflects the true physical energy intensity applied during the de-icing action and serves as the basis for comparing with the theoretically predicted command energy, revealing the energy output deviation caused by factors such as component parameter drift, temperature changes, or differences in load characteristics. First, the actual waveform data I within a complete pulse width (W) time window is read. actually（t） The process involves several steps: first, obtaining the corresponding equally spaced sampling time series; second, acquiring the pre-calibrated total load circuit resistance R1, including coil resistance and line resistance; then, using numerical integration methods, such as the trapezoidal integration method, calculating the integral of the square of the current over the pulse width; and finally, multiplying this integral by R1 to obtain the Joule thermal energy, as shown in the formula. , where t represents the time variable, dt represents the derivative of the time variable t, the integral calculation is completed by the processor within a few milliseconds after the pulse ends, and the result is used for subsequent energy deviation analysis; Step S502: Obtain preset load circuit parameters, and calculate the predicted command energy E based on the pulse charging voltage command U and pulse width W. command ; Load circuit parameters refer to the electrical characteristic parameters that constitute the main circuit of pulse discharge. They mainly include the equivalent inductance L and equivalent resistance R2 of the de-icing coil and the capacitance C of the energy storage capacitor. These parameters are used to establish a mathematical model of the discharge process and are key inputs for theoretical calculation and prediction of command energy. Load circuit parameters are obtained in two ways: first, during the system design phase, the coil and capacitor are measured using instruments such as an LCR meter, and the initial values ​​are estimated by combining the PCB traces; second, after the system is installed, small signal test pulses are injected and the response waveform is analyzed for online identification and calibration. The load circuit parameters are set based on the physical structure of the circuit and the measured datasheets of the components. The predicted command energy refers to the energy expected to be released on the load, derived from the pulse charging voltage command U calculated in step S203 and the pulse width W determined in step S202, based on the load loop model theory. Given the load loop resistance R2 and inductance L, the discharge process is approximated as the R2-L circuit discharging a capacitor, and the predicted command energy E... command The calculation formula is E command =0.5×C×U ² ×η, where C is the energy storage capacitor value, U is the charging voltage command, and η is the energy transfer efficiency factor calculated based on R2, L, and W. It is usually obtained by looking up a table or a simplified formula, and represents how much of the capacitor's stored energy is consumed in the load circuit resistance R2 within a given pulse width W. Step S503, calculate the energy deviation ΔE between the predicted command energy and the actual output energy, ΔE = (E actual -E command ) / E commandThe system sets a first deviation threshold ε1 and a second deviation threshold ε2 to judge the energy deviation ΔE. Based on the judgment result, the thyristor trigger signal is corrected. The first deviation threshold ε1 and the second deviation threshold ε2 are set according to the system's graded requirements for energy control accuracy and the stability tolerance of the hardware. ε1, for example, ±3%, is usually set close to the upper limit of the system's measurement noise and random disturbance amplitude, representing "good matching". ε2, for example, ±10%, is set according to the sensitivity of the de-icing effect to energy fluctuations. Both ε1 and ε2 are positive numbers, and ε2 > ε1. If ΔE > ε2, the actual output energy is determined to be higher than the predicted command energy, indicating pulse energy overshoot. The voltage needs to be reduced to decrease the energy of the next pulse, generating a negative voltage compensation amount ΔU. neg And according to formula U next =U + ΔU neg Calculate the charging voltage command U for the next triggering of the same de-icing coil. next , where ΔU neg It is a negative value; If ΔE < -ε1, then the actual output energy is determined to be lower than the predicted command energy, indicating insufficient pulse energy. The voltage needs to be increased to increase the energy of the next pulse, generating a positive voltage compensation amount ΔU. pos And according to formula U next =U + ΔU pos Calculate the charging voltage command U for the next triggering of the same de-icing coil. next , where ΔU pos It is a positive value; If -ε2≤ΔE≤ε2, then further determine whether the absolute value of the energy deviation ΔE is less than or equal to the first deviation threshold ε1; If |ΔE|≤ε1, it is determined that the actual output energy matches the predicted command energy well, and the current charging voltage command U is kept unchanged for the next triggering of the same de-icing coil; If ε1<|ΔE|≤ε2, then it is determined that there is an acceptable, non-significant deviation between the actual output energy and the predicted command energy, according to formula U. next =U + λ × (E) command -E actual ), calculate the charging voltage command U for the next trigger. next , where λ is a preset proportional coefficient.

[0031] The dynamic parameter mapping table was optimized and adjusted based on residual icing thickness data, including: Step S504: Obtain the residual ice thickness data d after applying the current pulse. residualThe system compares the residual ice thickness with a preset removal threshold. If the residual ice thickness is less than the threshold, de-icing is considered complete. If the residual ice thickness is greater than or equal to the threshold, de-icing is considered incomplete. The removal threshold is the upper limit of residual ice thickness used to determine whether the de-icing task is complete. It is set according to flight safety regulations and aerodynamic performance requirements, usually referring to the allowable trace amounts of ice residue on "critical surfaces" in aviation airworthiness standards (such as FAR / CS25 Appendix C Icing Conditions). The removal threshold is generally set to a small fixed value, such as 0.5 mm to 1.0 mm, providing a unified and clear physical judgment standard: if the measured residual ice thickness after de-icing is lower than the removal threshold, the de-icing is considered successful, and the de-icing cycle for the current area can be terminated; if it is higher than or equal to the removal threshold, de-icing is considered incomplete, and subsequent optimization and adjustment logic needs to be triggered to ensure that the de-icing effect meets the minimum requirements for safe flight. Step S505: When it is determined that the de-icing is not complete, record the current de-icing decision. The current de-icing decision includes the predefined range used for this de-icing, the dominant icing type, and the energy level coefficient. Query and adjust the base value of the energy level coefficient corresponding to the current de-icing decision from the dynamic parameter mapping table. The adjustment range is the set fine-tuning step size. The base value of the energy level coefficient refers to the original nominal value of the energy level coefficient stored in the dynamic parameter mapping table, corresponding to each predefined interval and dominant icing type combination, without adjustment in the current correction cycle. It serves as the benchmark starting point for energy regulation under this operating condition. First, based on the predefined interval and dominant icing type recorded in the current de-icing decision as joint key values, the corresponding cell in the dynamic parameter mapping table is located. Then, the base value of the current energy level coefficient stored in that cell is read. Next, based on the judgment conclusion of "de-icing incomplete", a new base value of the energy level coefficient is calculated according to a preset, small fine-tuning step size, such as adjusting upward by 0.1. The new base value of the energy level coefficient is equal to the sum of the original base value of the energy level coefficient and the fine-tuning step size. Finally, the original value in the dynamic parameter mapping table is updated with the new base value of the energy level coefficient, completing the optimization of the base value. The adjustment of the base value of the energy level coefficient is carried out slowly at the second level or task cycle to avoid over-adjustment due to a single anomaly.

[0032] In this embodiment, by real-time collection and fusion of multi-dimensional operating condition data such as icing thickness, icing rate, ambient temperature, ambient humidity, and flight data, and by calculating attitude influence factors, the trend of icing intensification on different aerodynamic surfaces can be predicted based on the real-time changes in the aircraft's angle of attack and roll angle. This allows for prediction before the ice layer develops to a dangerous thickness. Quantitative assessment is performed by calculating the Comprehensive Icing Severity Index (ISI). Based on the continuous and real-time calculation of ISI, de-icing actions can be automatically triggered in the early or middle stages of icing development, depending on the icing rate. Simultaneously, based on the ISI value, three predefined intervals of low, medium, and high are determined and directly mapped to de-icing strategies of different urgency levels. This changes the slow response mode of traditional perception, alarm, and fixed actions, adopting a rapid closed-loop transformation of perception, assessment, and graded precise response. Through dynamic prediction and graded response mechanisms, the time window from identifying icing risks to applying effective de-icing intervention is shortened, improving the ability to respond to sudden severe icing conditions and effectively reducing flight safety risks caused by untimely de-icing. This invention combines icing type identification with ISI quantitative assessment to construct a two-dimensional dynamic parameter mapping table. Based on the distinct mechanical properties of frost, hoarfrost, and clear ice, it specifies differentiated optimal pulse frequency and pulse width ratio strategies. For hoarfrost, a high-frequency, narrow pulse width is used to generate micro-vibrations for disintegration; for frost, a low-frequency, wide pulse width is used to generate greater shear force for peeling. This ensures that the output pulse energy pattern strictly matches the actual physical requirements of ice layer breakage, avoiding skin overload, electrode erosion, and energy waste caused by using a single high-energy mode. It also overcomes the limitations imposed by… Incomplete de-icing due to insufficient energy is addressed by a dual-loop closed-loop feedback system. The inner loop uses pulse waveform energy feedback to fine-tune the voltage in real time, while the outer loop uses residual ice thickness feedback to offline optimize the parameters of the dynamic parameter mapping table. This system continuously compensates for load changes and device aging, and performs self-learning optimization for the specific characteristics of each aircraft. As a result, it maintains extremely high energy delivery accuracy throughout the aircraft's entire life cycle, ensuring the effectiveness of de-icing under various complex operating conditions while significantly reducing ineffective energy consumption, improving the energy utilization efficiency of the entire aircraft power supply system, and extending the service life of the de-icing device itself.

[0033] In practical implementation, in addition to the hardware directly involved in each step, such as the sensors, central processing unit, high-precision clock, and various modules mentioned above, this application also provides electronic equipment. This electronic equipment may include one or more processors and one or more memories. The memories store computer-readable code, which, when executed by one or more processors, can perform the thyristor control method for an aircraft electrical pulse de-icing device as described above.

[0034] The method according to the embodiments of this application can also be implemented using the architecture of the electronic device shown in this application. The electronic device may include a bus, one or more CPUs, ROM, RAM, a communication port connected to a network, input / output, a hard disk, etc. The storage device in the electronic device, such as a ROM or hard disk, may store the thyristor control method for an aircraft electrical pulse de-icing device provided in this application. Furthermore, the electronic device may also include a user interface. Of course, the architecture shown in this application is merely exemplary; when implementing different devices, one or more components in the electronic device shown in this application may be omitted according to actual needs.

[0035] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising a reference structure" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A thyristor control method for an aircraft electrical pulse de-icing device, characterized in that, The method includes: Real-time acquisition of multi-dimensional operating condition data of aircraft; calculation and generation of comprehensive icing severity index based on multi-dimensional operating condition data; and determination of dominant icing type. Based on the comprehensive icing severity index, a predefined interval is determined. Based on the predefined interval and the dominant icing type, a dynamic parameter mapping table is queried to generate a target pulse control parameter set. Based on the target pulse control parameter set, a predicted command energy is calculated and generated. A thyristor trigger signal is generated based on the target pulse control parameter set, and a current pulse is applied to de-icing after the thyristor is turned on based on the thyristor trigger signal. Acquire the actual waveform data of the current pulse and the residual ice thickness data after de-icing; The actual output energy is calculated based on the actual waveform data. The energy deviation between the actual output energy and the predicted command energy is calculated. The thyristor trigger signal is corrected based on the energy deviation. The dynamic parameter mapping table is optimized and adjusted based on the residual icing thickness data.

2. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 1, characterized in that, The real-time acquisition of multi-dimensional aircraft operating condition data, the calculation of a comprehensive icing severity index based on the multi-dimensional operating condition data, and the determination of the dominant icing type include: The multidimensional operating condition data includes ambient temperature, ambient humidity, icing thickness, icing rate and flight data. The flight data includes flight altitude, flight speed and flight attitude angle. An aircraft body coordinate system is generated based on the flight data. The multidimensional operating condition data is obtained for time synchronization and unified coordinate processing. The icing thickness and icing rate are mapped to the aircraft body coordinate system. The liquid water content is calculated based on multi-dimensional operating condition data. The dominant icing type is determined based on the liquid water content, ambient temperature, and flight speed, and the confidence level of the icing type is calculated. The attitude influence factor is calculated based on flight data, and the comprehensive icing severity index is calculated based on the attitude influence factor and multi-dimensional operating condition data. The comprehensive icing severity index ranges from [0,10].

3. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 2, characterized in that, The process involves determining a predefined interval based on a comprehensive icing severity index, querying a dynamic parameter mapping table based on the predefined interval and the dominant icing type, and generating a target pulse control parameter set, including: A predefined interval is defined by setting an interval threshold, and a dynamic parameter mapping table is established with the predefined interval and the dominant icing type as the index. The dynamic parameter mapping table contains a set of pulse control parameters corresponding to the dominant icing type in different predefined intervals. The set of pulse control parameters includes pulse frequency, pulse width and energy level coefficient. The comprehensive icing severity index is compared with the interval threshold to determine the predefined interval to which it belongs. The predefined interval includes a low interval, a medium interval, and a high interval. Based on the predefined interval and the dominant icing type, the dynamic parameter mapping table is queried to obtain the pulse frequency, pulse width, and energy level coefficient. Calculate the pulse charging voltage command based on the energy level coefficient and attitude influence factor; The target pulse control parameter set is generated by integrating the pulse charging voltage command, pulse frequency, pulse width, and energy level coefficient.

4. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 3, characterized in that, The interval thresholds include a first interval threshold and a second interval threshold, and the second interval threshold is greater than the first interval threshold; When the comprehensive icing severity index is less than or equal to the threshold of the first interval, it is judged as a low interval; When the comprehensive icing severity index is greater than the threshold of the second interval, it is judged as a high interval; When the comprehensive icing severity index is less than or equal to the second interval threshold and greater than the first interval threshold, it is determined to be in the middle interval.

5. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 3, characterized in that, The dynamic parameter mapping table sets the value range of the energy level coefficient. Each predefined interval has a range, and the range is a subset of the value range. A base value of the energy level coefficient is set based on the range.

6. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 3, characterized in that, The step of generating a thyristor trigger signal based on the target pulse control parameter set, and applying a current pulse for de-icing after driving the thyristor to conduct based on the thyristor trigger signal includes: The pulse frequency and pulse width of the target pulse control parameter set are programmed to generate thyristor trigger signals; Obtain the connection topology of the thyristor, decode and process the thyristor trigger signal, and generate N trigger pulse sequences; The pulse charging voltage command is parsed into charging voltage data. Based on the N-channel trigger pulse sequence and the charging voltage data, the thyristors are turned on in sequence to generate current pulses for de-icing.

7. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 6, characterized in that, The process of acquiring the thyristor connection topology, decoding the thyristor trigger signal, and generating N trigger pulse sequences includes: The driving circuit and digital delay generator in the connection topology of the thyristors are obtained. The driving circuit includes a master thyristor and n slave thyristors. After receiving the thyristor trigger signal, the digital delay generator immediately generates the first trigger pulse to trigger the main thyristor to conduct. After a preset first delay time, a second trigger pulse is generated to trigger the first thyristor to turn on, until all thyristors that need to be turned on receive a trigger pulse. All trigger pulses are then integrated according to the trigger time of the thyristors to form an N-path trigger pulse sequence.

8. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 1, characterized in that, The correction of the thyristor trigger signal based on energy deviation includes: The actual waveform data is acquired and integrated over the entire pulse width to obtain the actual output energy. Obtain the preset load circuit parameters, and calculate the predicted command energy based on the pulse charging voltage command and pulse width; The energy deviation between the predicted command energy and the actual output energy is calculated. A first deviation threshold and a second deviation threshold are set to judge the energy deviation. The thyristor trigger signal is corrected based on the judgment result, and the second deviation threshold is greater than the first deviation threshold.

9. The thyristor control method for an aircraft electrical pulse de-icing device according to claim 1, characterized in that, The optimization and adjustment of the dynamic parameter mapping table based on residual icing thickness data includes: The residual ice thickness data after the applied current pulse is obtained is compared with the preset clearing standard threshold. If the residual ice thickness data is less than the clearing standard threshold, it is determined that the de-icing is completed. If the residual ice thickness is greater than or equal to the clearing standard threshold, it is determined that the de-icing is not complete. When it is determined that de-icing is incomplete, the current de-icing decision is recorded. The current de-icing decision includes the predefined range used for this de-icing, the dominant icing type, and the energy level coefficient. Query and adjust the base value of the energy level coefficient corresponding to the current de-icing decision from the dynamic parameter mapping table.

10. A thyristor control method for an aircraft electrical pulse de-icing device according to claim 3, characterized in that, The set of control parameters for generating the target pulse also includes: Obtain the energy level coefficient from the target pulse control parameter set and calculate the real-time overcurrent protection threshold. The system monitors the instantaneous current of the thyristors in real time. If the instantaneous current exceeds the real-time overcurrent protection threshold, it immediately forces the shutdown of all thyristor trigger signals.

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