Propeller sound quality optimization method and device, electronic equipment and storage medium

Abstract

The application discloses a propeller sound quality optimization method and device, electronic equipment and a storage medium. According to the application, the two types of sound sources, i.e., electromagnetic noise of an electric propulsion system and aerodynamic noise of a rotor, are simultaneously differentiated for noise reduction processing, the weights of the two types of noise reduction strategies are dynamically distributed in combination with flight conditions, noise reduction parameters are closed-loop optimized relying on psychoacoustic indexes, and not only the sound pressure level is simply reduced, but also the noise characteristics are optimized from the dual dimensions of spectral distribution and human ear hearing perception. Therefore, the technical problem that the existing low-altitude aircraft noise reduction method only simply reduces the sound pressure level and is difficult to improve the problems of prominent tone, low-frequency modulation and excessively high roughness, and easily causes auditory fatigue, dizziness and discomfort of cabin personnel can be solved, and the technical effects of uniformly dispersing electromagnetic noise spectral energy, avoiding aerodynamic noise falling into the sensitive interval of human ears, intelligently adjusting the noise reduction scheme for different flight conditions, greatly improving the auditory comfort in the cabin, and optimizing the driving experience of the low-altitude aircraft are achieved.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle technology, and in particular to a method, apparatus, electronic device, and storage medium for optimizing the acoustic quality of a propeller. Background Technology

[0002] Low-altitude aircraft are increasingly widely used as important transportation tools in urban air traffic, logistics distribution, and emergency rescue. Among related technologies, the power system of the aircraft is constructed through the coordinated operation of a distributed electric propulsion system, a motor controller, and a propeller.

[0003] Existing noise control methods often employ strategies that directly reduce sound pressure levels. This can lead to problems such as tonal prominence, low-frequency modulation effects, and excessive harshness, which can easily cause auditory fatigue and dizziness, thereby affecting the auditory comfort of passengers in the cabin. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, and storage medium for optimizing the acoustic quality of a propeller.

[0005] According to a first aspect of this disclosure, a method for optimizing the acoustic quality of a propeller is provided, comprising: Random frequency modulation is applied to the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from the discrete spectrum to the continuous spectrum; Monitor the speed difference between adjacent rotor groups, and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range, so that the modulation frequency of aerodynamic noise is moved out of the human ear sensitive frequency band. Identify the current flight condition of the aircraft and switch the priority of electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition; The cabin noise is evaluated in real time based on psychoacoustic indicators, and the parameters are dynamically adjusted and optimized based on the evaluation results.

[0006] Optionally, the step of randomly frequency modulating the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from a discrete spectrum to a continuous spectrum includes: The pulse width modulation reconstruction unit generates a randomly varying carrier frequency based on a pseudo-random sequence, and generates a pulse width modulation signal based on the carrier frequency to control the switching of the drive motor.

[0007] Optionally, the pseudo-random sequence is generated based on a linear feedback shift register or a Markov chain algorithm.

[0008] Optionally, monitoring the speed difference between adjacent rotor groups and adjusting the rotor group speed when the speed difference falls within a preset sensitive range to shift the modulation frequency of aerodynamic noise out of the human ear's sensitive frequency band includes: The rotational speeds of adjacent rotor groups are acquired in real time by the rotational speed decoupling unit, and the speed difference is calculated. When the speed difference is lower than the preset beat frequency suppression threshold, the speed command of one of the rotor groups is finely adjusted to widen the speed difference, so that the modulation frequency is moved out of the human ear sensitive frequency band.

[0009] Optionally, the identification of the aircraft's current flight condition and the switching of electromagnetic noise diffusion and aerodynamic noise suppression strategy priorities based on the current flight condition include: In hovering conditions, the speed decoupling strategy is prioritized. Under cruise conditions, the pulse width modulation random modulation strategy is prioritized. It balances noise control and dynamic response during climbing or descending operations.

[0010] Optionally, the real-time evaluation of cabin noise based on psychoacoustic indicators and the dynamic adjustment and optimization parameters based on the evaluation results include: The sound quality evaluation unit calculates the sharpness, roughness, and vibration intensity of the cabin noise in real time, and dynamically adjusts the random modulation parameters or rotation speed decoupling parameters when any of the indicators exceeds the preset threshold.

[0011] Optionally, the method further includes: In hovering mode, the rotor is divided into at least two groups, with different reference speeds set for different groups, so that the speed difference between groups meets the preset requirements to disperse the beat frequency.

[0012] According to a second aspect of this disclosure, a propeller acoustic quality optimization device is provided, comprising: The modulation unit is used to perform random frequency modulation on the pulse width modulation signal of the motor controller, thereby diffusing electromagnetic noise energy from the discrete spectrum to the continuous spectrum. The adjustment unit is used to monitor the speed difference between adjacent rotor groups and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range, so that the modulation frequency of aerodynamic noise is moved out of the human ear sensitive frequency band. The switching unit is used to identify the current flight condition of the aircraft and switch the priority of the electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition. The evaluation unit is used to evaluate cabin noise in real time based on psychoacoustic indicators and dynamically adjust and optimize parameters according to the evaluation results.

[0013] Optionally, the modulation unit is further configured to: generate a randomly varying carrier frequency based on a pseudo-random sequence by the pulse width modulation reconstruction unit, and generate a pulse width modulation signal based on the carrier frequency to control the switching on and off of the drive motor's switching transistor.

[0014] Optionally, the modulation unit is further configured to generate the pseudo-random sequence based on a linear feedback shift register or a Markov chain algorithm.

[0015] Optionally, the adjustment unit is further configured to: obtain the rotational speed of adjacent rotor groups in real time by the rotational speed decoupling unit and calculate the rotational speed difference; when the rotational speed difference is lower than a preset beat frequency suppression threshold, finely adjust the rotational speed command of one of the rotor groups to widen the rotational speed difference, so that the modulation frequency is moved out of the human ear sensitive frequency band.

[0016] Optionally, the switching unit is further configured to: prioritize the execution of the speed decoupling strategy during hovering; prioritize the execution of the pulse width modulation random modulation strategy during cruising; and balance noise control and power response during climbing or descending conditions.

[0017] Optionally, the evaluation unit is also used to: calculate the sharpness, roughness and vibration intensity of cabin noise in real time, and dynamically adjust the random modulation parameters or rotation speed decoupling parameters when any of the indicators exceeds a preset threshold.

[0018] Optionally, the device further includes: The grouping unit is used to divide the rotor into at least two groups in the hovering condition. Different groups are set with different reference speeds so that the speed difference between groups meets the preset requirements to disperse the beat frequency.

[0019] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0020] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0021] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0022] The propeller sound quality optimization method, apparatus, electronic equipment, and storage medium disclosed herein, through this application, simultaneously consider both electromagnetic noise from the electric propulsion system and aerodynamic noise from the rotor, implementing differentiated noise reduction processing, and dynamically allocating the weights of the two noise reduction strategies based on flight conditions. Furthermore, it relies on a closed-loop optimization of noise reduction parameters based on psychoacoustic indices, rather than simply reducing sound pressure level. It optimizes noise characteristics from both spectral distribution and human auditory perception dimensions. Therefore, it can solve the technical problems of existing low-altitude aircraft noise reduction methods that only reduce sound pressure level, making it difficult to improve issues such as prominent pitch, low-frequency modulation, and excessive roughness, which easily cause auditory fatigue, dizziness, and discomfort for cabin personnel. It achieves the technical effects of uniformly dispersing electromagnetic noise spectrum energy, avoiding aerodynamic noise from falling into the sensitive range of human hearing, intelligently adjusting noise reduction schemes to adapt to different flight conditions, significantly improving cabin auditory comfort, and optimizing the low-altitude aircraft riding experience.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0024] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 This is a schematic flowchart of a propeller acoustic quality optimization method provided in an embodiment of the present disclosure; Figure 2 This is a schematic diagram of the structure of a propeller acoustic quality optimization device provided in an embodiment of the present disclosure; Figure 3 This is a schematic diagram of the structure of a propeller acoustic quality optimization device provided in an embodiment of the present disclosure; Figure 4 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0025] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0026] The following description, with reference to the accompanying drawings, outlines a method, apparatus, electronic device, and storage medium for optimizing propeller acoustic quality according to embodiments of the present disclosure.

[0027] Figure 1This is a schematic flowchart of a propeller acoustic quality optimization method provided in an embodiment of the present disclosure.

[0028] like Figure 1 As shown, the method includes the following steps: Step 101: Perform random frequency modulation on the pulse width modulation signal of the motor controller to diffuse the electromagnetic noise energy from the discrete spectrum to the continuous spectrum. In motor inverters, the on / off control signals for power switches no longer use a fixed carrier frequency. Instead, the carrier frequency dynamically changes in a pseudo-random sequence over time. This randomized frequency modulation mechanism acts at the source of electromagnetic noise. By altering the periodicity of the inverter's switching action, it disrupts the energy concentration at the fundamental frequency and its harmonics, redistributing the electromagnetic noise energy density from discrete frequency peaks to a continuous, wide-bandwidth range. The noise spectrum thus exhibits a flattened characteristic similar to a continuous spectrum. After this processing, the highly prominent tonal components originally formed at specific frequencies are significantly weakened, reducing the sharpness of the noise perceived by the human ear.

[0029] As one implementation method, the random frequency jump range of the carrier frequency can be set between several kilohertz and over ten kilohertz. The random sequence generation algorithm can employ pseudo-random number generation mechanisms such as linear feedback shift registers or Markov chains to ensure the unpredictability of frequency jumps and the uniformity of frequency domain energy distribution. The carrier frequency update rate can be adjusted according to specific application requirements; a faster update frequency helps to obtain a smoother continuous spectrum effect.

[0030] Step 102: Monitor the speed difference between adjacent rotor groups, and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range so that the modulation frequency of aerodynamic noise is moved out of the sensitive frequency band of human ear. In subsequent steps of this method, the system monitors and evaluates the speed difference between adjacent rotor groups in real time. The actual speed signal of the drive motor is acquired by the speed detection unit, and the system calculates the speed difference between adjacent rotor groups based on this signal, comparing it to a preset sensitive range threshold. When the speed difference falls within this sensitive range, it means that the acoustic modulation frequency generated by the propeller rotation is within the frequency range where human hearing is most sensitive. At this time, the human ear will clearly perceive the periodic changes in noise intensity, producing a rough and fluctuating auditory experience. To address this, the system sends a speed compensation command to the corresponding motor controller to fine-tune the target speed of one or more rotor groups, forcibly pulling the speed difference out of the sensitive range, thereby shifting the modulation frequency of the aerodynamic noise towards a frequency range where the human ear is less sensitive.

[0031] The acoustic modulation frequency is determined by the rotational speed difference and the number of propeller blades, with the basic relationship being the product of the rotational speed difference and the number of blades divided by sixty. The human ear is particularly sensitive to low-to-mid-frequency modulation signals, but relatively insensitive to extremely low-frequency or higher-frequency modulation changes. Therefore, by actively adjusting the rotational speed difference, the modulation frequency can be guided to a region with lower auditory sensitivity, effectively suppressing the annoyance and discomfort caused by aerodynamic interference noise. As one implementation method, the sensitive range can be set within the modulation frequency range of 20 Hz to 80 Hz. Correspondingly, the goal of rotational speed adjustment is to make the modulation frequency lower than 10 Hz or higher than 100 Hz. The threshold of the sensitive range can be calibrated based on the rotor parameters of the specific aircraft model and measured acoustic data. It is worth noting that the magnitude of the rotational speed adjustment is usually controlled within a small proportion to ensure it remains within the allowable range of the motor efficiency plateau, thereby not significantly affecting the aircraft's thrust output and flight stability.

[0032] Step 103: Identify the current flight condition of the aircraft and switch the priority of the electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition; The operational characteristics of an aircraft's propulsion system differ significantly at different flight phases, resulting in varying noise compositions and their impact on auditory comfort. The system identifies and classifies the current flight condition by acquiring real-time motion parameters such as horizontal flight speed, vertical motion rate, and attitude stability. Based on this, the control module adjusts the execution weights and priorities of two noise control strategies according to the identified flight condition, achieving a dynamic balance between sound quality optimization and flight performance requirements.

[0033] The core logic of this adaptive adjustment mechanism lies in the fact that the dominant noise sources and their disturbing characteristics differ under different flight conditions. Therefore, the timing and depth of intervention for various optimization strategies should be differentiated. For example, in low-speed static steady-state conditions such as hovering, the rotational speeds of each rotor tend to be consistent, and the low-frequency modulation effect generated by aerodynamic interference has a particularly prominent impact on auditory comfort. In this case, the system can prioritize speed decoupling operations, actively widening the speed difference between adjacent rotor groups to suppress low-frequency modulation noise. At the same time, the depth of random frequency modulation can be appropriately reduced to decrease the losses of switching devices. Furthermore, in steady-state flight conditions such as cruise, the background noise in the cockpit is mainly contributed by the switching action of the motor inverter. The system can then shift its optimization focus to the random frequency modulation of the pulse width modulation signal to fully diffuse electromagnetic noise energy and improve the overall quality of the cabin acoustic environment. The constraint on the speed difference between rotors can be appropriately relaxed to balance thrust efficiency. In transitional operating conditions with high dynamic response requirements, such as climbing or descending, the system can adopt a hybrid strategy or temporarily reduce the optimization intensity to ensure that the response speed of the dynamic system is not constrained by the sound quality adjustment.

[0034] As one implementation of this adjustment mechanism, flight conditions can be determined by setting threshold combinations of corresponding motion parameters. The mapping relationship between each condition and strategy priority can be pre-stored in the system's control logic and invoked in real time during flight based on condition switching. Through this condition-aware strategy scheduling, the system can continuously provide sound quality optimization schemes adapted to the current state within the entire operating envelope of the aircraft, avoiding efficiency losses or insufficient optimization that may be caused by a single fixed control strategy under certain conditions.

[0035] Step 104: Evaluate cabin noise in real time based on psychoacoustic indicators, and dynamically adjust and optimize parameters according to the evaluation results.

[0036] Sound acquisition devices deployed inside the cockpit convert ambient noise signals into digital signals in real time. Based on this, the system calculates psychoacoustic indicators that characterize subjective auditory perception, including but not limited to parameters such as sharpness, roughness, and jitter intensity. These indicators, from different dimensions, depict the perceptual effects of the noise's spectral structure and temporal modulation characteristics on the human ear, and compared to traditional total sound pressure level (SPL) indicators, can more accurately reflect the degree of auditory discomfort. The system compares the real-time calculated psychoacoustic indicator values ​​with pre-calibrated comfort thresholds. Once an indicator exceeds an acceptable range, it indicates that the current noise quality deviates from the expected optimization target.

[0037] At this point, the system performs targeted corrections to the adjustable parameters in the aforementioned electromagnetic noise diffusion and aerodynamic noise suppression stages based on the type of exceeding the standard and the degree of deviation. If the noise sharpness is too high, it indicates that the perception of high-frequency tone components is still significant. The system can expand the jump range of random frequency modulation or increase the frequency update rate to further disperse high-frequency energy. If the noise roughness is too high, it indicates that the mid-to-low frequency modulation effect has not been sufficiently suppressed. The system can increase the adjustment amplitude of the bridging speed decoupling to push the modulation frequency further into the frequency band where human hearing is less sensitive. The adjustment amplitude of each parameter can adopt a graded response strategy according to the degree of exceeding the standard to avoid unnecessary disturbances to the operating efficiency of the power system caused by over-adjustment. When the various psychoacoustic indicators have been continuously stable within the comfort range for a certain period of time, the system can also gradually converge the optimization intensity, reducing the energy consumption of the control action while maintaining good sound quality.

[0038] Through this closed-loop adjustment mechanism, the sound quality optimization process no longer relies on fixed preset parameters, but is guided by the actual auditory perception of the human ear for continuous iteration, enabling the system to adapt to the dynamic changes in environmental conditions, flight status and power output during flight, and always maintain the cabin noise in a good quality state in a psychoacoustic sense.

[0039] In some embodiments, the random frequency modulation of the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from a discrete spectrum to a continuous spectrum includes: The pulse width modulation reconstruction unit generates a randomly varying carrier frequency based on a pseudo-random sequence, and generates a pulse width modulation signal based on the carrier frequency to control the switching of the drive motor.

[0040] The generation of pseudo-random sequences can employ a linear feedback shift register algorithm. This algorithm uses a shift register with a specific feedback polynomial as its core. Each clock cycle, the register updates its position based on the XOR operation result of the feedback taps. The values ​​in the output sequence are then linearly mapped to carrier frequency values ​​falling between a preset lower and upper frequency limit. Taking an eight-stage shift register as an example, its feedback polynomial can be x. 8 +x 6 +x 5 +x 4 +1, under this configuration, the register traverses all non-zero states in 255 periods, which can generate a sufficiently rich combination of frequencies within a single period, ensuring the uniformity of frequency domain energy distribution. In addition to the linear feedback shift register, the random sequence of carrier frequencies can also be generated by the Markov chain algorithm, using the state transition probability matrix to generate frequency jumps with statistical randomness between adjacent sampling times.

[0041] In one specific embodiment, the pseudo-random sequence generator outputs a new frequency value every fifty microseconds. The pulse width modulation (PWM) reconstruction unit then uses this frequency value as the period reference for the current carrier waveform, regenerates a triangular carrier or sawtooth carrier, and compares it with the modulation signal from the speed loop or current loop controller, outputting a PWM waveform with the corresponding duty cycle. This PWM waveform is sent to the gate drive circuit of the power switch transistors of each bridge arm of the three-phase inverter in the motor controller, directly controlling the turn-on and turn-off times of each switch transistor. Because the carrier frequency continuously and randomly jumps within the preset range of 4 kHz to 12 kHz, the frequency spectrum of the inverter output voltage no longer shows discrete spikes concentrated at a fixed frequency. The electromagnetic noise energy that was originally accumulated at the fixed switching frequency and its integer multiples is uniformly distributed throughout the jumping frequency band, forming a continuous and flat wide-spectrum distribution characteristic. Taking a motor inverter with a fixed original switching frequency of 8 kHz as an example, after adopting the above-mentioned random frequency modulation scheme, the spectral discrete peak of up to 58 dB at 8 kHz is eliminated, and the energy in this frequency band is evenly distributed between 4 kHz and 12 kHz. The peak sound pressure level drops to 43 dB, and the noise perceived by the human ear changes from a sharp and piercing whistling sound to a soft broadband airflow sound, and the sharpness of hearing is significantly improved.

[0042] In some embodiments, the pseudo-random sequence is generated based on a linear feedback shift register or a Markov chain algorithm.

[0043] Linear feedback shift registers, as a deterministic pseudo-random sequence generation mechanism, have a simple hardware implementation structure and are easily integrated into field-programmable gate arrays or application-specific integrated circuits (ASICs) of motor controllers. The register consists of several stages of flip-flops connected in series, with each stage storing one binary bit. The outputs of each stage are XORed according to a selected feedback polynomial and then fed into the first stage input. Taking an eight-stage linear feedback shift register as an example, its feedback taps select the outputs of the fourth, fifth, sixth, and eighth stages for XOR combination, with the corresponding characteristic polynomial being x. 8 +x 6 +x 5 +x 4 +1, this polynomial is a primitive polynomial, ensuring that the register can traverse all 255 states before returning to its initial value in a non-zero initial state, thus generating a sequence of maximum length with a period of 255. The register's clock frequency determines the output rate of the sequence. When the clock frequency is set to 20 kHz, a new 8-bit binary value is output every 50 microseconds. This value is then linearly mapped to a carrier frequency value falling within the target frequency range of 4 kHz to 12 kHz. The mapping relationship can be achieved using a simple linear interpolation formula, mapping each of the 0 to 254 integer values ​​output by the register to uniformly segmented points in the frequency range, ensuring that the probability of hitting each frequency sub-range is approximately equal, thereby making the distribution of electromagnetic noise energy in the frequency domain tend to be uniform.

[0044] The Markov chain algorithm provides another pseudo-random frequency generation path based on state transitions. Its significant feature is the controlled statistical correlation between adjacent frequency values, which can suppress drastic abrupt changes during frequency jumps while maintaining a uniform spectral spread. This algorithm discretizes the target frequency range into several frequency states, for example, taking a state point every 200 Hz, resulting in 41 discrete states in the 4 kHz to 12 kHz range. The transition probability between states is defined by a pre-calibrated state transition probability matrix, where the sum of the elements in each row is one, representing the probability distribution of jumping from the current frequency state to each possible next state. In a typical configuration, the transition probability matrix adopts a banded sparse structure, meaning the current state transitions to its adjacent or nearby states with a high probability, while the probability of jumping to a more distant state decreases with distance. This design makes short-term carrier frequency changes exhibit local walk characteristics, while the long-term statistical distribution tends to uniformly traverse all states. Register state updates can also use a 50-microsecond period. During each update, the algorithm randomly samples based on the current state and the transition probability matrix to determine the carrier frequency value for the next moment. Compared to the linear feedback shift register scheme, the Markov chain scheme generates a frequency sequence with relatively smooth transitions between adjacent values, which helps reduce the transient current surge caused by sudden changes in the switching cycle during frequency switching. However, its implementation requires slightly more storage resources and computational logic than the former. Both schemes can be selected or combined based on the resource constraints of the specific hardware platform and the sound quality optimization goals. In practical deployments, both schemes can achieve the expected effect of effectively diffusing the discrete spectrum of electromagnetic noise into a continuous spectrum.

[0045] In some embodiments, monitoring the speed difference between adjacent rotor groups and adjusting the rotor group speed when the speed difference falls within a preset sensitive range, so that the modulation frequency of aerodynamic noise is shifted out of the human ear's sensitive frequency band, includes: The rotational speeds of adjacent rotor groups are acquired in real time by the rotational speed decoupling unit, and the speed difference is calculated. When the speed difference is lower than the preset beat frequency suppression threshold, the speed command of one of the rotor groups is finely adjusted to widen the speed difference, so that the modulation frequency is moved out of the human ear sensitive frequency band.

[0046] In one specific implementation, the speed detection device employs a Hall sensor, installed at the stator end of the motor. It outputs pulse signals by sensing the alternating switching of the rotor magnetic poles, with the pulse frequency directly proportional to the motor speed. The speed decoupling unit reads the signals from each Hall sensor at a sampling frequency of at least 1 kHz. After signal conditioning and pulse counting, the signals are converted into the instantaneous speed values ​​of each drive motor, expressed in revolutions per minute (RPM). For adjacent rotor groups one and two, the decoupling unit takes the absolute difference between their real-time speeds, obtaining the speed difference ΔRPM. This speed difference value is then compared with a pre-stored beat frequency suppression threshold Δmin in the storage unit to determine whether the current speed relationship between the two rotor groups might cause auditory discomfort.

[0047] The setting of the beat frequency suppression threshold Δmin needs to comprehensively consider the number of propeller blades and the boundary conditions of the human ear's sensitive modulation frequency range. Since the acoustic modulation frequency between rotor assemblies satisfies a definite mathematical relationship with the speed difference and the number of blades—that is, the modulation frequency equals the speed difference divided by 60 and then multiplied by the number of blades—the speed difference needs to be controlled outside the corresponding range to ensure the modulation frequency deviates from the human ear's sensitive range of 20 Hz to 80 Hz. This threshold is typically set to 2% to 5% of the target speed. Taking a permanent magnet synchronous motor with a rated speed of 2000 rpm and a five-bladed propeller as an example, when the beat frequency suppression threshold is set to 3% of the target speed, Δmin equals 60 rpm, and the corresponding modulation frequency is 5 Hz, which is already below the lower limit of the 10 Hz human ear's sensitive range.

[0048] When the system determines that the current speed difference ΔRPM is lower than the preset beat frequency suppression threshold Δmin, it indicates that the speeds of adjacent rotor groups are too close, and the resulting acoustic modulation frequency is within the frequency range most sensitive to the human ear. Without intervention, a noticeable low-frequency periodic roaring sound will occur in the cockpit. At this time, the speed decoupling unit sends a speed compensation command to the controller of one of the motors, directionally shifting the target speed of that motor to create a sufficient speed difference with the adjacent motors. In a specific adjustment example, initially, the speed of motor 1 is 2,000 rpm, and the speed of motor 2 is 1,998 rpm, with a speed difference of only 2 rpm, far below the threshold of 60 rpm. The system sends a compensation command to the controller of motor 2, adjusting its target speed to 1,940 rpm, increasing the speed difference between the two motors to 60 rpm, and reducing the corresponding modulation frequency to 5 Hz, successfully moving it out of the range sensitive to the human ear. The speed adjustment range is about three percent, which is within the allowable range of the motor efficiency platform. The impact on rotor thrust output is less than one percent, and it will not cause any perceptible disturbance to the attitude stability and flight safety of the aircraft.

[0049] In some embodiments, identifying the current flight condition of the aircraft and switching the priority of electromagnetic noise diffusion and aerodynamic noise suppression strategies based on the current flight condition includes: In hovering conditions, the speed decoupling strategy is prioritized. Under cruise conditions, the pulse width modulation random modulation strategy is prioritized. It balances noise control and dynamic response during climbing or descending operations.

[0050] The hovering condition is determined when the aircraft's ground speed is below 0.5 m / s, its vertical motion speed is below 0.2 m / s, and this state lasts for more than two seconds. When this condition is met, the aircraft is in a low-speed hovering state where it is nearly stationary above the ground. Under this condition, the drive motors of each rotor group rotate at a similar speed with minimal difference. The acoustic modulation frequency generated by the propeller rotation falls precisely within the 20 Hz to 80 Hz range, which is the most sensitive range for the human ear. This results in a noticeable low-frequency periodic variation in intensity within the cockpit, causing significant auditory harshness and irritation. Therefore, the system sets the speed decoupling strategy to the highest priority, strictly locking the speed difference between adjacent rotor groups to no less than 3% of the target speed, ensuring that the modulation frequency is suppressed to below 10 Hz. At the same time, the modulation depth of random frequency modulation can be reduced to 50% of the full modulation depth to reduce switching losses of the inverter power switching transistors during high-frequency random switching, avoiding adverse effects on hovering accuracy due to increased electromagnetic interference.

[0051] Cruise conditions are categorized based on the aircraft's horizontal airspeed. Airspeeds between 5 and 15 meters per second are classified as low-speed cruise, while airspeeds exceeding 15 meters per second are classified as high-speed cruise. During cruise, the aircraft maintains a relatively stable flight attitude and power output. The acoustic environment within the cockpit is dominated by steady-state electromagnetic noise generated by the switching action of the motor inverter. At this time, the random frequency modulation strategy is given the highest priority, the pulse width modulation reconstruction unit operates at full modulation depth, and the carrier frequency randomly jumps across the entire range of 4 kHz to 12 kHz to fully diffuse electromagnetic noise energy and optimize the continuous spectrum quality of the cabin background noise. In low-speed cruise, the speed difference constraint between adjacent rotor groups is relaxed to no less than 2% of the target speed, and in high-speed cruise, it is further relaxed to no less than 1%, to balance thrust efficiency and the aircraft's aerodynamic performance.

[0052] The criteria for determining whether an aircraft is in a climb or descent phase are that the absolute value of its vertical velocity exceeds one meter per second. This transitional phase places high demands on the instantaneous response capability of the power system, requiring the motors to provide significant thrust increments or decrements within a short period. Maintaining strict speed decoupling constraints or a deep random modulation depth during this phase could interfere with the motor controller's rapid tracking of the target speed, delaying power response. Therefore, the system employs a balanced strategy, reducing the optimization intensity of noise control to a basic level: random frequency modulation maintains a small modulation depth, providing only basic spectral spread; the speed decoupling threshold constraint is correspondingly relaxed, allowing adjacent rotor groups to adjust freely within a large speed difference range, ensuring that the thrust commands output by the flight controller can be executed quickly and accurately by each motor. When the flight control computer detects that the vertical velocity has returned to below one meter per second and the horizontal velocity has stabilized, the system automatically determines that the aircraft has exited the transitional phase, then re-determines the flight stage based on the new motion parameters and restores the corresponding optimization strategy priority.

[0053] In some embodiments, the real-time evaluation of cabin noise based on psychoacoustic indicators and the dynamic adjustment of optimization parameters according to the evaluation results include: The sound quality evaluation unit calculates the sharpness, roughness, and vibration intensity of the cabin noise in real time, and dynamically adjusts the random modulation parameters or rotation speed decoupling parameters when any of the indicators exceeds the preset threshold.

[0054] The front-end signal acquisition of the sound quality evaluation unit is accomplished by a MEMS silicon microphone installed inside the cockpit. This microphone is calibrated to a sensitivity of -26 dB full scale and continuously digitizes the cabin sound pressure level signal at a sampling rate of 44,100 Hz. The acquired digital audio stream is transmitted to the evaluation unit's digital signal processor via a serial bus. The processor first applies an A-weighted filter to the input time-domain sound pressure level signal to simulate the equal loudness perception characteristics of the human ear. Then, it performs frame processing along the time axis, with each frame consisting of 100 milliseconds. Adjacent frames have a 50% overlap rate to ensure the continuity and temporal resolution of the index calculation.

[0055] Sharpness calculation is based on the Zwicker model. The sound pressure signal within each analysis frame is decomposed into loudness contributions across multiple frequency bands using a one-third octave band filter bank. The total loudness is then integrated using a weighted function of the center frequency of each band, with the weights increasing with frequency, ensuring that high-frequency components contribute significantly more to the sharpness value than low-frequency components. The calculation results are expressed in acum (acum), with a higher value indicating a stronger perceived intensity of high-frequency tonal components in the noise. In a typical application scenario, when the motor inverter operates at a fixed switching frequency of 8 kHz, the sharpness measurement in the cabin can reach 1.5 acum, which is subjectively perceived as a distinct, piercing howl. Roughness calculation focuses on the time-domain envelope modulation characteristics of the sound pressure signal. The processor performs a Hilbert transform on the signal within the analysis frame to extract the instantaneous amplitude envelope. The envelope signal is then bandpass filtered, and the modulation depth is calculated. The roughness value is determined by the weighted sum of the modulation depth of each frequency band and its center frequency, expressed in asper (asper). This index primarily reflects the intensity of the mid-frequency modulation component in the range of 100 Hz to 2 kHz, corresponding to the interference effect caused by the speed difference between multi-rotors. The calculation method for jitter intensity is similar to that for roughness, but it focuses on a lower modulation frequency range, typically below 20 Hz, and is expressed in vacils to characterize the intensity of human hearing's perception of low-frequency periodic amplitude fluctuations.

[0056] The storage unit pre-stores comfort thresholds for various psychoacoustic indicators, serving as trigger criteria for closed-loop adjustment. Taking a specific parameter configuration as an example, the sharpness threshold is set to 1.2 acum, and the roughness threshold is set to 0.3 asper. At the end of each analysis frame, the sound quality evaluation unit compares the calculated values ​​of the three indicators with their corresponding thresholds one by one. When the sharpness index exceeds the preset threshold, it indicates that the spectral diffusion effect of the current random frequency modulation is insufficient to adequately disperse high-frequency energy. The evaluation unit then sends a parameter adjustment command to the pulse width modulation reconstruction unit, expanding the random jump range of the carrier frequency outwards, for example, from the original range of 4 kHz to 12 kHz to 3,500 Hz to 12,500 Hz, to cover a wider frequency band and further reduce the energy concentration in the high-frequency band. If the roughness index exceeds the threshold, it indicates that the speed decoupling amplitude between adjacent rotor groups is insufficient, and the modulation frequency still remains near the range sensitive to human hearing. The evaluation unit then sends an instruction to the speed decoupling unit to increase the amplitude, raising the beat frequency suppression threshold from 3% to 4% of the target speed, further widening the speed difference and suppressing the modulation frequency to a lower range. When the jitter intensity index exceeds the standard, the system can comprehensively adjust the speed decoupling parameters and the update rate of random modulation to suppress amplitude fluctuations in the low-frequency band through synergistic effects.

[0057] The adjustments to the parameters are not a one-step, abrupt change, but rather a gradual approximation strategy. Each time feedback of exceeding the limit is received, the corresponding parameter is adjusted incrementally in a single step, according to a preset step size. The adjusted parameter immediately applies to the noise optimization process in the next control cycle, and then the sound quality evaluation unit reassesses the trend of the indicators in subsequent analysis frames. If the indicator value falls back below the threshold, the current parameter remains unchanged; if it continues to exceed the limit, incremental adjustments are applied in the next cycle until all indicators return to the comfortable range. When all three indicators remain stably within the threshold for thirty consecutive seconds, the system determines that the current noise sound quality has reached the optimization target. The optimization intensity can then be gradually reduced to decrease the consumption of control actions on the power system's operating efficiency, achieving a balance between maintaining sound quality and saving energy.

[0058] In some embodiments, the method further includes: In hovering mode, the rotor is divided into at least two groups, with different reference speeds set for different groups, so that the speed difference between groups meets the preset requirements to disperse the beat frequency.

[0059] The differentiated grouping strategy for rotor groups is suitable for aircraft platforms with a large number of rotors. The rationale is that when multiple rotors operate at the same or very similar rotational speeds, the beat frequencies generated between different rotor pairs tend to overlap. Multiple modulation components superimpose near the same frequency, causing a sharp increase in energy density within that frequency band, which manifests as a strong, periodic roar and a harsh sound. By dividing the rotors into several groups and assigning each group a different reference rotational speed, the beat energy originally concentrated at a single frequency can be dispersed to multiple different frequency points, reducing the superposition amplitude at each frequency and thus improving the overall harshness of the noise.

[0060] In a specific implementation scenario, an eight-rotor logistics drone is used as the application object. When hovering, all eight rotors initially rotate at 1800 revolutions per minute, using five-bladed propellers. The system first divides the eight rotors into four groups based on their diagonal positions, with each group containing a pair of rotors diagonally opposite the fuselage. This grouping method balances the needs of acoustic decoupling and mechanical balance: the diagonally opposite rotors are furthest apart, resulting in the weakest aerodynamic interference effect; grouping them together minimizes acoustic coupling between rotors within the same group. Furthermore, the diagonally opposite rotors within the same group maintain the same rotational speed, causing their counter-torques to cancel each other out, ensuring that the fuselage does not experience yaw torque due to differentiated rotational speed distribution.

[0061] The reference speeds for each group are set according to a preset allocation rule. The reference speeds for the four rotor groups are 1800 rpm, 1740 rpm, 1860 rpm, and 1920 rpm, respectively. The speed increment or decrement between adjacent groups is approximately 3.3% to 6.7% of the target speed. The minimum speed difference between each group is no less than 60 rpm. Substituting the parameters of the five-bladed propeller into the modulation frequency calculation formula, the minimum modulation frequency is 5 Hz, which is below the lower limit of the human ear's sensitive range of 10 Hz. Since the four rotor groups operate at different reference speeds, the beat frequencies between any two groups are 5 Hz, 10 Hz, and 15 Hz, respectively. The modulation energy that was originally concentrated at a single frequency is dispersed to multiple discrete frequency points, and the amplitude at each frequency is significantly reduced. Before optimization, the noise roughness was as high as 0.58 asper, which was subjectively perceived as noisy and irritating. After differential grouping, the roughness was reduced to 0.28 asper, and the noise spectrum showed a dispersed multi-peak structure. The auditory perception changed from an irritating fluctuating feeling to a stable and low continuous background sound.

[0062] This grouping strategy can work in conjunction with the aforementioned speed decoupling unit. After the differentiated reference speed is set, the speed decoupling unit continues to perform closed-loop monitoring of the actual speed within each group. When speed drift caused by load disturbance is detected between diagonal rotors within the same group or between adjacent groups, a compensation command is promptly applied to maintain the preset speed distribution relationship, ensuring that each beat frequency remains within a frequency range insensitive to the human ear. The specific values ​​of the reference speeds for each group and the number of groups can be specifically optimized and adjusted according to the aircraft's rotor configuration, number of propeller blades, and measured acoustic data.

[0063] Corresponding to the aforementioned propeller sound quality optimization method, this invention also proposes a propeller sound quality optimization device. Since the device embodiments of this invention correspond to the aforementioned method embodiments, details not disclosed in the device embodiments can be referred to the aforementioned method embodiments, and will not be repeated here.

[0064] Figure 2 This is a schematic diagram of the structure of a propeller sound quality optimization device provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes: The modulation unit 21 is used to perform random frequency modulation on the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from the discrete spectrum to the continuous spectrum. Adjustment unit 22 is used to monitor the speed difference between adjacent rotor groups and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range, so that the modulation frequency of aerodynamic noise is moved out of the human ear sensitive frequency band. The switching unit 23 is used to identify the current flight condition of the aircraft and switch the priority of the electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition. Evaluation unit 24 is used to evaluate cabin noise in real time based on psychoacoustic indicators and dynamically adjust and optimize parameters according to the evaluation results.

[0065] Furthermore, in one possible implementation of this disclosure, the modulation unit 21 is further configured to: The pulse width modulation reconstruction unit generates a randomly varying carrier frequency based on a pseudo-random sequence, and generates a pulse width modulation signal based on the carrier frequency to control the switching of the drive motor.

[0066] Furthermore, in one possible implementation of this disclosure, the modulation unit 21 is further configured to: The pseudo-random sequence is generated based on a linear feedback shift register or a Markov chain algorithm.

[0067] Furthermore, in one possible implementation of this disclosure, the adjustment unit 22 is further configured to: The rotational speeds of adjacent rotor groups are acquired in real time by the rotational speed decoupling unit, and the speed difference is calculated. When the speed difference is lower than the preset beat frequency suppression threshold, the speed command of one of the rotor groups is finely adjusted to widen the speed difference, so that the modulation frequency is moved out of the human ear sensitive frequency band.

[0068] Furthermore, in one possible implementation of this disclosure, the switching unit 23 is further configured to: In hovering conditions, the speed decoupling strategy is prioritized; in cruise conditions, the pulse width modulation random modulation strategy is prioritized; and in climbing or descending conditions, noise control and power response are taken into account.

[0069] Furthermore, in one possible implementation of this disclosure, the evaluation unit 24 is further configured to: The system calculates the sharpness, roughness, and vibration intensity of cabin noise in real time, and dynamically adjusts random modulation parameters or rotational speed decoupling parameters when any of these parameters exceeds a preset threshold.

[0070] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the device further includes: Grouping unit 25 is used to divide the rotor into at least two groups in the hovering condition, wherein different reference speeds are set for different groups so that the speed difference between groups meets the preset requirements to disperse the beat frequency.

[0071] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0072] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0073] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0074] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0075] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0076] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the propeller sound quality optimization method. For example, in some embodiments, the propeller sound quality optimization method can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned propeller acoustic quality optimization method by any other suitable means (e.g., by means of firmware).

[0077] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0078] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0079] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0080] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0081] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0082] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0083] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0084] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0085] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for optimizing the acoustic quality of a propeller, characterized in that, include: Random frequency modulation is applied to the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from the discrete spectrum to the continuous spectrum; Monitor the speed difference between adjacent rotor groups, and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range, so that the modulation frequency of aerodynamic noise is moved out of the human ear sensitive frequency band. Identify the current flight condition of the aircraft and switch the priority of electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition; The cabin noise is evaluated in real time based on psychoacoustic indicators, and the parameters are dynamically adjusted and optimized based on the evaluation results.

2. The method according to claim 1, characterized in that, The step of randomly frequency modulating the pulse width modulation signal of the motor controller to diffuse electromagnetic noise energy from a discrete spectrum to a continuous spectrum includes: The pulse width modulation reconstruction unit generates a randomly varying carrier frequency based on a pseudo-random sequence, and generates a pulse width modulation signal based on the carrier frequency to control the switching of the drive motor.

3. The method according to claim 2, characterized in that, The pseudo-random sequence is generated based on a linear feedback shift register or a Markov chain algorithm.

4. The method according to claim 1, characterized in that, The monitoring of the rotational speed difference between adjacent rotor groups, and adjusting the rotational speed of the rotor groups when the speed difference falls within a preset sensitive range, so that the modulation frequency of aerodynamic noise is shifted out of the human ear's sensitive frequency band, includes: The rotational speeds of adjacent rotor groups are acquired in real time by the rotational speed decoupling unit, and the speed difference is calculated. When the speed difference is lower than the preset beat frequency suppression threshold, the speed command of one of the rotor groups is finely adjusted to widen the speed difference, so that the modulation frequency is moved out of the human ear sensitive frequency band.

5. The method according to claim 1, characterized in that, The identification of the aircraft's current flight condition, and the switching priority of electromagnetic noise diffusion and aerodynamic noise suppression strategies based on the current flight condition, include: In hovering conditions, the speed decoupling strategy is prioritized. Under cruise conditions, the pulse width modulation random modulation strategy is prioritized. It balances noise control and dynamic response during climbing or descending operations.

6. The method according to claim 1, characterized in that, The method of evaluating cabin noise in real time based on psychoacoustic indicators and dynamically adjusting and optimizing parameters according to the evaluation results includes: The sound quality evaluation unit calculates the sharpness, roughness, and vibration intensity of the cabin noise in real time, and dynamically adjusts the random modulation parameters or rotation speed decoupling parameters when any of the indicators exceeds the preset threshold.

7. The method according to claim 5, characterized in that, The method further includes: In hovering mode, the rotor is divided into at least two groups, with different reference speeds set for different groups, so that the speed difference between groups meets the preset requirements to disperse the beat frequency.

8. A propeller sound quality optimization device, characterized in that, include: The modulation unit is used to perform random frequency modulation on the pulse width modulation signal of the motor controller, thereby diffusing electromagnetic noise energy from the discrete spectrum to the continuous spectrum. The adjustment unit is used to monitor the speed difference between adjacent rotor groups and adjust the speed of the rotor group when the speed difference falls into the preset sensitive range, so that the modulation frequency of aerodynamic noise is moved out of the human ear sensitive frequency band. The switching unit is used to identify the current flight condition of the aircraft and switch the priority of the electromagnetic noise diffusion and aerodynamic noise suppression strategies according to the current flight condition. The evaluation unit is used to evaluate cabin noise in real time based on psychoacoustic indicators and dynamically adjust and optimize parameters according to the evaluation results.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-7.

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