Active noise reduction method and system and automobile

Abstract

The invention relates to an active noise reduction method and system and an automobile. The method comprises the following steps: acquiring a pressure signal in a tire cavity of the vehicle; processing the pressure signal to obtain a noise signal, and controlling to generate an anti-phase sound wave signal based on the noise signal; and the loudspeaker is used for playing sound corresponding to the anti-phase sound wave signal in the tire cavity. According to the method, a pressure signal in a tire is directly obtained, after the pressure signal is processed, a noise signal is obtained, an anti-phase sound wave signal corresponding to the noise signal is generated, and the anti-phase sound wave signal is directly played in the tire, so that noise is directly processed in the tire. By adopting the active noise reduction method, the tire pressure sensor on the automobile can be directly adopted as the detection sensor, the vehicle-mounted chip is adopted as the processor, only one loudspeaker needs to be added, and the cost is low. And the active noise reduction method can adapt to tires of different sizes, and the application scene is wide.

Description

An active noise reduction method, system and vehicle Technical Field

[0001] This application relates to the field of noise reduction technology, and in particular to an active noise reduction method, system and automobile. Background Technology

[0002] Due to their enclosed structure, car tires have cavity modes within their internal cavities. Under road surface excitation, these cavities undergo periodic deformation, causing repeated changes in air pressure. The internal air vibrates like a "resonance chamber," generating cavity noise, typically manifested as a continuous "humming" sound. This sound is transmitted through the wheel hub, suspension, and body structure to the vehicle interior, ultimately being perceived as low-frequency noise by the driver and passengers, thus impacting their driving and riding experience. Currently, the main methods for improving tire cavity noise include the following:

[0003] The first method is to add sound-absorbing cotton inside the tire. By filling the tire with this cotton, the original tire cavity structure is disrupted, altering the modal frequencies of the tire cavity. The cotton itself can also absorb sound to some extent, reducing interior noise. The second method is to add multiple resonant cavities within the tire cavity. The resonance between these cavities and the cavity modes reduces cavity noise. The third method is to add inert gas inside the tire, which also alters the cavity modal frequencies, thus reducing noise.

[0004] However, all of the above solutions have certain drawbacks. Adding sound-absorbing cotton inside the tire is costly, and there is a risk of the cotton falling off after prolonged use. Furthermore, adding sound-absorbing cotton alters the tire cavity modes, generating new frequency noise. Adding multiple resonant cavities inside the tire cavity also presents the problem of high cost, and the resonant cavities, located on the rim, have a large static balance, leading to significant tire assembly vibration and potential other problems. Adding inert gas inside the tire has limited effectiveness in suppressing tire cavity noise, and finding a suitable inert gas filling point after a tire deflation is difficult, making it cumbersome to use. Summary of the Invention

[0005] Therefore, it is necessary to provide an active noise reduction method, system, and vehicle that can reduce tire noise effectively at a low cost, in response to the above-mentioned technical problems.

[0006] In a first aspect, this application provides an active noise reduction method, the method comprising:

[0007] Acquire the pressure signal inside the tire cavity of the vehicle;

[0008] The pressure signal is processed to obtain a noise signal; based on the noise signal, an anti-phase sound wave signal is generated so that the loudspeaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0009] In one embodiment, the pressure signal is processed to obtain a noise signal, including:

[0010] The pressure signal is amplified to obtain an amplified pressure signal. Based on the amplified pressure signal, a static pressure signal is obtained, which is the tire pressure signal when the tire does not generate noise under the same environmental conditions. Based on the amplified pressure signal and the static pressure signal, a dynamic pressure signal is obtained, which is used to characterize the noise signal.

[0011] In one embodiment, acquiring the amplified dynamic pressure signal includes:

[0012] The system periodically acquires tire pressure signals, including pressure signals within a preset time period, and calculates the average pressure value of the amplified pressure signals over multiple preset time periods. The average pressure value represents the static pressure signal within the overall pressure signal set. The difference between the amplified pressure signal and the static pressure signal is then calculated; this difference represents the dynamic pressure signal.

[0013] In one embodiment, generating an anti-phase acoustic signal based on a noise signal includes:

[0014] Based on the time delay caused by the transmission of noise signals in the transmission path, the noise signal is delayed to obtain the target noise-reduced signal. Initial correction coefficients are obtained based on tire parameters. These initial correction coefficients are then optimized using the target noise-reduced signal, the initial correction coefficients, and a preset FxLMS algorithm to obtain the target correction coefficients. Based on the noise signal and the target correction coefficients, the corrected noise-reduced signal is obtained. An inverse-phase acoustic signal is then generated based on the corrected noise-reduced signal. The inverse-phase acoustic signal has the same frequency, equal amplitude, and opposite phase to the corrected noise-reduced signal.

[0015] In one implementation, optimizing the initial correction coefficient to obtain the target correction coefficient includes: performing at least one iterative optimization on the initial correction coefficient to obtain the target correction parameter. In each iteration, based on a gradient descent iteration strategy and a preset step size, the correction parameter to be optimized is iterated to generate the optimized correction parameter. Based on the optimized correction parameter and the noise signal, an optimized denoised signal is obtained. Based on the target denoised signal and the optimized denoised signal, a residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target parameter.

[0016] In one embodiment, obtaining the residual pressure signal includes:

[0017] The residual pressure signal is calculated using the formula e(n)=d(n)- w(z)×x(n);

[0018] Where e(n) represents the residual pressure signal, d(n) represents the target noise reduction signal, w(z) represents the target correction coefficient, and x(n) represents the noise signal.

[0019] Secondly, this application also provides an active noise reduction device, including a signal acquisition module and a noise reduction processing module, wherein:

[0020] The signal acquisition module is used to acquire the pressure signal inside the tire cavity of the vehicle;

[0021] The noise reduction processing module is used to process the pressure signal to obtain a noise signal; based on the noise signal, it controls the generation of an anti-phase sound wave signal so that the speaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0022] Thirdly, this application also provides an active noise cancellation system, which includes:

[0023] The detection sensor is installed inside the tire cavity of the vehicle to detect the pressure signal inside the tire cavity.

[0024] The processor, communicatively connected to the detection sensor, is used to execute the active noise reduction method of the first aspect and any of its embodiments.

[0025] The speaker is installed inside the tire cavity of the vehicle. The speaker is connected to the signal processor and is used to output anti-phase sound wave signals.

[0026] Fourthly, this application also provides a vehicle including the active noise cancellation system provided in the second aspect.

[0027] Fifthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0028] Acquire the pressure signal inside the tire cavity of the vehicle;

[0029] The pressure signal is processed to obtain a noise signal; based on the noise signal, an anti-phase sound wave signal is generated so that the loudspeaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0030] Sixthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0031] Acquire the pressure signal inside the tire cavity of the vehicle;

[0032] The pressure signal is processed to obtain a noise signal; based on the noise signal, an anti-phase sound wave signal is generated so that the loudspeaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0033] In a seventh aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0034] Acquire the pressure signal inside the tire cavity of the vehicle;

[0035] The pressure signal is processed to obtain a noise signal; based on the noise signal, an anti-phase sound wave signal is generated so that the loudspeaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0036] The aforementioned active noise cancellation method, system, device, computer equipment, computer-readable storage medium, computer program product, and automobile directly acquire the pressure signal inside the tire, process the pressure signal to obtain a noise signal, generate an anti-phase sound wave signal corresponding to the noise signal, and directly play the anti-phase sound wave signal inside the tire. This achieves direct noise processing inside the tire, resulting in good noise reduction and effectively reducing the impact of cavity noise on the driving experience. Using this active noise cancellation method, the tire pressure sensor on the vehicle can be directly used as the detection sensor, and an onboard chip can be used as the processor. Only one speaker needs to be added, resulting in low cost. Furthermore, this active noise cancellation method can be adapted to tires of different sizes, making it applicable to a wide range of scenarios. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 is a schematic diagram of an active noise reduction system in one embodiment;

[0039] Figure 2 is a flowchart of an active noise reduction method in one embodiment;

[0040] Figure 3 is a flowchart of an active noise reduction method in another embodiment;

[0041] Figure 4 is a flowchart of the active noise reduction method in another embodiment;

[0042] Figure 5 is a flowchart of the active noise reduction method in another embodiment;

[0043] Figure 6 is a flowchart of an active noise reduction device in one embodiment;

[0044] Figure 7 is an internal structure diagram of a computer device in one embodiment. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0046] Referring to Figure 1, which is a schematic diagram of an active noise cancellation system in one embodiment, this application provides an active noise cancellation system applied in an automobile. The system includes a detection sensor 101, a processor 102, and a speaker 103. The detection sensor 101 is disposed within the tire cavity of the vehicle and is used to detect pressure signals within the tire cavity. The processor 102 is communicatively connected to the detection sensor 101 and is used to execute an active noise cancellation method. The speaker 103 is disposed within the tire cavity of the vehicle and is communicatively connected to the processor 102, used to output anti-phase sound wave signals.

[0047] The detection sensor 101 is a tire pressure sensor, preferably installed on the rim side inside the tire cavity. This location avoids interfering with the tire's normal rotation and dynamic balance while allowing for close-range capture of pressure fluctuations within the cavity, improving the sensitivity and accuracy of signal acquisition. The tire pressure sensor is primarily used to monitor tire pressure. This system utilizes the existing tire pressure sensors on the vehicle for signal acquisition, eliminating the need for a dedicated microphone and reducing system complexity and hardware costs. Furthermore, a power amplifier can be integrated into the tire pressure sensor to amplify the weak pressure signal, preventing noise-related dynamic pressure fluctuations from being drowned out by interference signals.

[0048] The processor 102 uses the vehicle's built-in infotainment chip, eliminating the need for an additional dedicated processing module. This fully utilizes existing onboard hardware resources and reduces system deployment costs. The processor 102 and the detection sensor 101 can be connected using common automotive communication methods, such as wired communication like CAN bus or Ethernet, or wireless communication like Bluetooth or LoRa. Wired communication offers greater stability, while wireless communication is easier to install and wire, allowing for flexible selection based on the vehicle's specific design.

[0049] The processor 102, as the system's control unit, integrates a signal processing module, a filtered-x Least Mean Square (FxLMS) algorithm module, and a signal generation module. Its main function is to execute active noise reduction methods. After receiving the dynamic pressure signal (noise signal) transmitted from the detection sensor 101, the signal processing module analyzes and resolves the key features of the noise, such as frequency and amplitude, using a Fast Fourier Transform (FFT). The technique of converting time-domain noise signals into frequency-domain signals using FFT to extract features such as frequency and amplitude is a common technique in acoustic detection and noise source identification. This embodiment does not provide a specific description of the analysis of the frequency and amplitude features of the dynamic pressure signal (noise signal).

[0050] Based on the stable and small space characteristics of tire cavity noise, the FxLMS algorithm module iteratively optimizes the correction coefficients to compensate for the small time difference during signal transmission, ensuring that the subsequently generated anti-phase sound wave can be synchronized with the actual noise. The signal generation module, based on the optimized noise characteristics, generates an anti-phase sound wave electrical signal with the same frequency, equal amplitude, and opposite phase as the corrected noise signal, providing a basis for the speaker 103 to produce sound.

[0051] The speaker 103 is installed in the gap between the wheel hub and the tire within the tire cavity. During installation, its installation posture and weight distribution are controlled to avoid adverse effects on the tire's dynamic balance and normal driving. Simultaneously, it ensures that the speaker 103's sound emission direction evenly covers the entire tire cavity, improving the uniformity of noise cancellation. The speaker 103 is selected to suit the complex operating conditions of the tire, possessing vibration resistance, temperature change resistance, and waterproof and dustproof characteristics, allowing it to operate stably in harsh environments such as bumps and temperature fluctuations during vehicle operation.

[0052] The speaker 103 and processor 102 can be connected via wired or wireless communication. The speaker receives the anti-phase acoustic wave signal transmitted by processor 102 and converts it into an actual acoustic wave signal for playback within the tire cavity. This acoustic wave and the original noise within the tire cavity can achieve sufficient superposition and interference in the early stages of propagation. Because they have the same frequency, opposite phase, and equal amplitude, their acoustic wave energies cancel each other out, thus suppressing the noise source. The speaker 103 can be powered via wired or wireless means. For example, it can be powered via a slip ring-type collector, or wirelessly via electromagnetic induction coupling or magnetic resonance coupling. When the speaker 103 and processor 102 communicate via wired means, a slip ring can be used to integrate power supply and communication. For example, the fixed end of the slip ring is used to connect to processor 102, and the rotating end is used to connect to the speaker 103 inside the tire. The slip ring connects the corresponding power supply and communication lines, thus achieving integrated power supply and communication. Other methods can also be used; this embodiment does not limit this approach.

[0053] The system's workflow is as follows:

[0054] When a vehicle is in motion, the tire cavity generates cavity noise under road surface excitation, causing pressure fluctuations within the cavity. Sensor 101 collects this pressure signal in real time. After amplification by a power amplifier and DC component removal, the purified dynamic pressure signal (noise signal) is transmitted to processor 102. Upon receiving the noise signal, processor 102 analyzes its key features through a signal processing module, iteratively calculates and optimizes correction coefficients using the FxLMS algorithm module, generates an anti-phase acoustic wave signal, and sends it to speaker 103. Speaker 103 converts the electrical signal into sound waves, which are then superimposed on and cancel out the original noise. Simultaneously, sensor 101 collects the pressure signal after noise reduction by speaker 103 in real time and feeds it back to processor 102. Processor 102 iteratively updates the correction coefficients using the FxLMS algorithm, dynamically adjusting the anti-phase acoustic wave signal to reduce the noise to a preset value, ensuring the system can adapt to dynamic noise changes and maintain a stable noise reduction effect.

[0055] In an exemplary embodiment, referring to FIG2, FIG2 is a flowchart illustrating an active noise reduction method in one embodiment. This method can be applied to the active noise reduction system in FIG1. ​​As shown in FIG2, the method includes the following steps:

[0056] S201, acquire the pressure signal inside the tire cavity of the vehicle.

[0057] When a tire is excited by road surface conditions, its closed cavity generates cavity modes, which in turn cause pressure fluctuations. These pressure fluctuations are directly related to cavity noise, therefore the pressure signal contains key noise characteristics. By using a detection sensor 101 deployed within the tire cavity to acquire this pressure signal in real time, noise-related information can be captured. The acquisition process must ensure signal continuity and integrity to provide accurate data for subsequent processing.

[0058] Preferably, in step S201, obtaining the pressure signal inside the tire cavity of the vehicle includes obtaining the pressure signal inside the tire cavity of the vehicle through a tire pressure sensor, wherein the tire pressure sensor is installed inside the tire cavity.

[0059] In this embodiment, the pressure signal is acquired through a tire pressure sensor, which is installed inside the tire cavity, preferably on the rim side. This arrangement does not affect the normal driving of the tire and allows for close-range acquisition of the pressure signal, improving the sensitivity of signal acquisition. This embodiment utilizes a tire pressure sensor installed in the tire for pressure signal acquisition, eliminating the need for an additional dedicated pressure sensor and reducing the complexity and cost of the system.

[0060] When the tire pressure sensor acquires pressure signals, it is necessary to ensure the continuity of acquisition and the sampling rate is compatible. The sampling rate must meet the frequency requirements of the noise signal to avoid signal distortion due to insufficient sampling rate. The acquired pressure signal is transmitted to the system processor 102 via wired or wireless communication to provide raw data for subsequent processing.

[0061] The advantage of this method lies in sensor reuse, making full use of the vehicle's existing tire pressure monitoring hardware resources without incurring additional hardware costs. Furthermore, the tire pressure sensors are directly deployed within the tire cavity, enabling them to directly capture pressure fluctuations corresponding to noise. The collected signals are closer to the nature of the noise, resulting in higher accuracy compared to external acquisition methods. This design simplifies the system structure and improves the reliability of signal acquisition, laying the foundation for the smooth implementation of subsequent noise reduction processes.

[0062] Preferably, in step S201, the method further includes: the sampling rate of the tire pressure sensor is greater than or equal to 500Hz.

[0063] In this embodiment, the sampling rate of the tire pressure sensor is set to be greater than or equal to 500Hz. This setting is based on the Nyquist sampling theorem, which states that the sampling rate must be greater than or equal to twice the highest frequency of the signal in order to restore the signal without distortion.

[0064] Since the core frequency of tire cavity noise is generally around 200Hz and its highest frequency component does not exceed 250Hz, the sampling rate is set to be greater than or equal to 500Hz. This satisfies the requirements of the sampling theorem, ensuring that the noise characteristics in the pressure signal are collected without distortion, while also avoiding a surge in data volume due to an excessively high sampling rate.

[0065] Setting the sampling rate to be greater than or equal to 500Hz also takes into account the computational power requirements. The processor 102 has limited computing resources. If the sampling rate is too high, the amount of data to be processed per unit time will increase significantly, which may overload the processor 102 and affect the real-time performance of signal processing. A sampling rate of 500Hz can control the amount of data within the processing capacity of the processor 102 while ensuring signal quality. This ensures that subsequent steps such as signal separation and anti-phase signal generation can be completed efficiently, avoiding a decrease in noise reduction effect due to processing delay.

[0066] S202, the pressure signal is processed to obtain a noise signal, and based on the noise signal, an anti-phase sound wave signal is generated so that the speaker 103 can play a sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0067] Pressure signals contain not only dynamic components related to noise but may also include other irrelevant signals. Through filtering, amplification, and separation, a noise signal that purely reflects the noise characteristics can be extracted, clarifying key parameters such as frequency and amplitude. Subsequently, based on the principle of acoustic cancellation, an anti-phase sound wave signal with the same frequency, amplitude, and opposite phase as the noise signal is generated. When the two anti-phase sound waves meet, they interfere and superimpose, canceling each other out, thus achieving a noise reduction effect.

[0068] In this embodiment, the anti-phase sound is played through a speaker 103, which is located inside the tire cavity of the vehicle. Preferably, it is installed in the gap between the wheel hub and the tire. The installation position must avoid affecting the dynamic balance of the tire, while ensuring that the sound can evenly cover the entire tire cavity to improve the cancellation effect. The speaker 103 must be selected to suit the special environment of the tire cavity, possessing vibration resistance and temperature change resistance characteristics to ensure stable operation under complex driving conditions.

[0069] The generated anti-phase sound wave signal is converted into actual sound and played through a speaker 103 deployed inside the tire cavity. Since the playback position is located inside the tire cavity, that is, at the source of noise generation, the anti-phase sound can be superimposed and canceled out with the cavity noise in the early stage of propagation, preventing the noise from being transmitted into the vehicle.

[0070] The speaker 103 is communicatively connected to the system processor 102. The anti-phase sound wave signal generated by the processor 102 is transmitted to the speaker 103 through the communication link. The speaker 103 converts the electrical signal into a sound wave signal and plays it. During playback, the sound power of the speaker 103 needs to match the noise amplitude to ensure that the anti-phase sound wave has enough energy to cancel out the noise, while avoiding excessive power that could cause additional interference. Since the speaker 103 is directly deployed inside the tire cavity, the anti-phase sound can be superimposed on the cavity noise at the source, resulting in a more direct cancellation effect. This avoids energy attenuation during the noise's propagation into the vehicle, making the noise reduction more efficient compared to playing anti-phase sound inside the vehicle.

[0071] The method in this embodiment directly acquires the pressure signal inside the tire, processes the pressure signal to obtain a noise signal, generates an anti-phase sound wave signal corresponding to the noise signal, and directly plays the anti-phase sound wave signal inside the tire. This achieves direct noise reduction within the tire, resulting in good noise reduction and effectively reducing the impact of cavity noise on the driving experience. Using this active noise reduction method, the tire pressure sensor on the vehicle can be directly used as the detection sensor 101, and an onboard chip can be used as the processor 102. Only one speaker 103 needs to be added, resulting in low cost. Furthermore, this active noise reduction method can be adapted to tires of different sizes, making it applicable to a wide range of scenarios.

[0072] In one embodiment of this application, referring to FIG3, FIG3 is a flowchart of an active noise reduction method in another embodiment. As shown in FIG3, step S202 processes the pressure signal to obtain a noise signal, including:

[0073] S301 amplifies the pressure signal to obtain an amplified pressure signal.

[0074] Since the pressure fluctuation amplitude corresponding to tire cavity noise may be small, direct extraction is easily subject to interference. Therefore, it is necessary to amplify the acquired raw pressure signal using a power amplifier. The main purpose of amplification is to improve the sensitivity of the dynamic pressure signal, making subsequent signal separation more accurate and preventing weak noise features from being masked. At the same time, it is necessary to ensure that the amplification process does not introduce additional distortion and to guarantee the authenticity of the signal.

[0075] S302, based on the pressure amplification signal, obtains the static pressure signal after the pressure signal is amplified. The static pressure signal is the tire pressure signal when the tire does not generate noise under the same environmental conditions.

[0076] The amplified pressure signal consists of two parts: first, a static pressure signal corresponding to the tire pressure. This static pressure signal is the tire pressure signal when the tire is stationary under the same environmental conditions and no noise is generated. It can also be understood as the tire pressure signal when the tire is stationary under the same environmental conditions. The static pressure signal can be obtained through testing or calculated from the detected pressure signal. This static pressure signal is stable and unchanging, independent of noise. "Same environmental conditions" means that the environment in which the tire is stationary and in motion is the same, including the ambient temperature, humidity, and atmospheric pressure. Second, a dynamic pressure signal corresponding to cavity noise. This dynamic pressure signal fluctuates with changes in noise. Through signal analysis algorithms, a stable static pressure signal can be separated from the amplified pressure signal. This static pressure signal is essentially the DC component of the amplified pressure signal, reflecting the tire's baseline tire pressure state. This step serves to eliminate irrelevant static components, preparing for the extraction of noise-related dynamic components.

[0077] S303 acquires the dynamic pressure signal after amplification of the pressure signal based on the pressure amplification signal and the static pressure signal, and uses the dynamic pressure signal to characterize the noise signal.

[0078] By subtracting the static pressure signal from the amplified pressure signal, the static component can be removed, resulting in a dynamic pressure signal that reflects only noise fluctuations. The frequency and amplitude variations of this dynamic pressure signal correspond to the cavity noise, and therefore can be directly used as a noise signal to characterize the noise.

[0079] In the method of this application embodiment, the problem of weak original signal is solved by amplifying the signal, and the accuracy of noise signal is ensured by effectively eliminating irrelevant interference signals, which provides a key guarantee for the subsequent noise reduction effect.

[0080] In one embodiment of this application, referring to FIG4, FIG4 is a flowchart of an active noise reduction method in another embodiment. As shown in FIG4, step S202, acquiring the amplified dynamic pressure signal, includes:

[0081] S401 periodically acquires the tire pressure signal, acquires the pressure signal within a preset time period, and acquires the average pressure value of the pressure amplification signal within the preset time period. The average pressure value is the static pressure signal in the pressure signal.

[0082] S402, obtain the difference between the pressure amplification signal and the static pressure signal, the difference is the dynamic pressure signal.

[0083] The static pressure signal, i.e., the DC component corresponding to tire pressure, is theoretically stable and constant, but slight fluctuations may occur during actual acquisition. Therefore, analysis over multiple time periods can reduce errors that may occur during actual acquisition. The selection of the preset time period needs to balance stability and real-time performance; it should not be too short, which would cause excessive fluctuations in the average pressure value, nor too long, which would affect the real-time performance of subsequent processing.

[0084] This embodiment uses the signal block averaging algorithm to obtain the static pressure signal from the pressure signal. The specific process is as follows:

[0085] First, the processor 102 divides the pressure amplified signal into preset time periods. The length of these preset time periods can be selected based on the characteristics of the tire cavity noise. For example, if the core frequency of the tire cavity noise is around 200Hz, the corresponding noise period is approximately 5ms. Therefore, the preset time period can be 10ms. A 10ms time period can contain two complete noise periods, ensuring that the pressure signal within each preset time period contains sufficient noise fluctuation information, preventing the average pressure value within the preset time period from being affected by local fluctuations in a single noise period. It also ensures the real-time performance of the signal processing, avoiding lag in dynamic pressure signal extraction due to excessively long preset time periods.

[0086] Taking the 512Hz sampling rate of the tire pressure sensor as an example, a 10ms time block corresponds to approximately 5 sampling points. This number of sampling points satisfies the stability requirements of the average pressure value calculation without increasing the computational burden on the processor 102 due to too many sampling points, thus adapting to the resource constraints of the vehicle scenario. Subsequently, the processor 102 calculates the average pressure of all sampling points within each preset time period. This average value is the DC component in the pressure amplification signal Pa within the corresponding preset time period, which is also the reference value of the static pressure signal within that time period.

[0087] After acquiring the static pressure signal, the processor 102 calculates the difference between the amplified pressure signal Pa and the static pressure signal. This difference is the dynamic pressure signal. Since the static pressure signal represents a DC component independent of noise, the difference between the amplified pressure signal Pa and the static pressure signal represents the dynamic pressure signal containing only tire cavity noise. The frequency and amplitude changes of this difference are synchronized with the cavity noise, and it can characterize the core features of the noise.

[0088] The dynamic pressure signal obtained by this method can preserve the original characteristics of tire cavity noise to the greatest extent and effectively avoid interference from static tire pressure components. This provides data support for the subsequent generation of accurate anti-phase acoustic signals, indirectly improving the noise reduction effect and stability of the entire active noise cancellation system. Furthermore, this method is adaptable to the tire cavity noise characteristics of tires of different sizes. Even with small, slow changes in tire pressure, the static pressure signal can be updated in a timely manner through dynamic adjustments of the average values ​​over multiple preset time periods, ensuring that the extraction accuracy of the dynamic pressure signal is not affected, further enhancing the system's adaptability and reliability.

[0089] In one embodiment of this application, referring to FIG5, FIG5 is a schematic flowchart of an active noise reduction method in another embodiment. As shown in FIG5, step S202, generating an anti-phase acoustic wave signal based on the noise signal, includes:

[0090] S501 performs delay processing on the noise signal based on the time delay generated by the transmission of the noise signal in the transmission path to obtain the target noise-reduced signal.

[0091] The noise signal is obtained by amplifying and de-DC processing the pressure signal collected by the tire pressure sensor. It can reflect the frequency and amplitude characteristics of tire cavity noise relatively accurately, providing a reference for subsequent signal generation. From the acquisition of the noise signal to the playback of the anti-phase sound wave signal by the speaker 103, there are unavoidable time delays due to signal transmission and chip processing. If the anti-phase sound wave signal is directly generated based on the original noise signal, the two sound waves may not be able to be superimposed synchronously due to the time lag, affecting the noise reduction effect.

[0092] Therefore, based on the time delay generated by the transmission of the noise signal in the transmission path, it is necessary to perform delay processing on the noise signal to obtain the target denoised signal. The main purpose of delay processing is to correct the noise signal through a preset primary path weight. The calculation of the target denoised signal can refer to the formula d(n)=x(n)×P(z).

[0093] Where d(n) represents the target noise reduction signal, x(n) represents the noise signal, and P(z) is a weighting parameter characterizing the signal transmission and processing delay. The value of the target noise reduction signal is pre-calibrated based on the spatial characteristics of the tire cavity and the transmission speed of the system hardware, which can simulate the time difference between the noise signal being collected by the tire pressure sensor and its actual propagation within the cavity. Through this delay processing, the target noise reduction signal can basically match the actual propagation noise timing, providing a basis for the generation of subsequent anti-phase acoustic wave signals and avoiding noise reduction failure or poor noise reduction effect caused by time delay.

[0094] S502 obtains the initial correction coefficient based on the tire parameters, and optimizes the initial correction coefficient based on the target noise reduction signal, the initial correction coefficient and the preset FxLMS algorithm to obtain the target correction coefficient.

[0095] Based on the preset FxLMS algorithm, the correction coefficient of the noise signal is optimized. The main function of this correction coefficient is to dynamically adapt to the small fluctuations of the noise signal and ensure that the subsequently generated sound wave signal cancels out the noise as much as possible.

[0096] Since the modal frequencies of the tire cavity are basically fixed after the tire model is determined, the two inherent modal frequencies w1 and w2 of the tire can be calibrated experimentally in the early stage of system development, while recording the initial amplitude of the noise signal without noise reduction. Initial correction coefficients are obtained based on preset parameters such as inherent modal frequencies and initial amplitudes, enabling the correction coefficients to have initial adaptability and reducing the cycle of subsequent iterative optimization. Determining the initial correction coefficients based on parameters such as inherent modal frequencies and initial amplitudes is existing technology and can be directly determined by referring to corresponding methods in the prior art; it will not be described in detail in this embodiment. The initial correction coefficients can also be preset based on the experience of those skilled in the art, and the specific method can be flexibly selected; this embodiment does not limit this. The iterative process of the correction coefficients is the core of the FxLMS algorithm, which will be described in detail below in conjunction with the calculation logic of FxLMS.

[0097] The initial correction coefficient is optimized to obtain the target correction coefficient, including: performing at least one iteration of optimization on the initial correction coefficient to obtain the target correction coefficient. In each iteration, the correction parameter to be optimized is iterated based on a gradient descent iteration strategy and a preset step size to generate optimized correction parameters. Based on the optimized correction parameters and the noise signal, an optimized denoised signal is obtained. Based on the target denoised signal and the optimized denoised signal, a residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target correction coefficient.

[0098] First, processor 102 generates a corrected acoustic signal based on the current correction coefficients (which can be the initial correction coefficients or correction coefficients generated during iterative optimization of the initial correction coefficients) and the noise signal, according to the formula y(n)=w(z)×x(n). Here, y(n) represents the corrected acoustic signal, and the acoustic signal to be emitted by speaker 103 is the inverse phase of this corrected acoustic signal. w(z) represents the target correction coefficient, and x(n) represents the noise signal.

[0099] Subsequently, the residual pressure signal is calculated. This signal is the difference between the target denoised signal and the corrected acoustic signal, and can be calculated using the formula e(n) = d(n) - y(n). Here, e(n) represents the residual pressure signal, d(n) represents the target denoised signal, and y(n) represents the corrected acoustic signal. The amplitude of the residual pressure signal directly reflects the current denoising effect. A larger amplitude indicates a lower matching degree between the corrected acoustic signal and the target denoised signal, requiring further optimization of the target correction coefficient w(z).

[0100] Finally, based on the gradient descent iterative strategy and the preset step size, the correction parameters to be optimized are iterated. In this embodiment, the correction parameters to be optimized include the initial correction coefficients and the correction coefficients generated during the iterative optimization of the initial correction coefficients. The correction coefficients can be iteratively updated according to the formula w(z) = w(z) + mu × e(n) × x(n), where mu is the preset step size, used to adjust the adjustment range of the correction coefficients, avoiding algorithm oscillations due to excessively rapid adjustment or adaptation lag due to excessively slow adjustment.

[0101] During the iteration process, the value of the preset step size (mu) can be flexibly set by relevant technical personnel based on experience, and will not be described in detail in this embodiment. After each iteration, the new correction coefficient will be re-used to calculate the corrected acoustic signal. The process of updating the corrected acoustic signal, collecting the error between the updated corrected acoustic signal and the target noise reduction signal, and updating the correction coefficient is repeated until the amplitude of the residual pressure signal is lower than or equal to the preset threshold. At this time, the correction coefficient is the target correction coefficient that adapts to the current noise state, and the corresponding corrected acoustic signal basically matches the frequency and amplitude of the target noise reduction signal.

[0102] S503 obtains the corrected noise reduction signal based on the noise signal and the target correction coefficient, and generates an inverse phase acoustic signal based on the corrected noise reduction signal.

[0103] Among them, the anti-phase acoustic wave signal and the corrected noise reduction signal have the same frequency, equal amplitude, and opposite phase.

[0104] After obtaining the target correction coefficient, the corrected acoustic signal y(n) is calculated based on the noise signal and the target correction coefficient using the formula y(n)=w(z)×x(n). This corrected acoustic signal is the corrected noise reduction signal. The processor 102 generates an anti-phase acoustic signal with the same frequency, equal amplitude, and opposite phase as the corrected noise reduction signal, based on the principle of acoustic interference cancellation. Opposite phase is a prerequisite for noise cancellation; when two sound waves with opposite phases meet in the tire cavity, their vibration directions are opposite, and their energy is superimposed and cancels each other out. Same frequency is the basis for a stable cancellation effect, avoiding phase relationship fluctuations due to frequency differences, ensuring the continuity and effectiveness of the cancellation effect, and ultimately achieving efficient suppression of tire cavity noise. Same amplitude ensures thorough cancellation, avoiding residual noise due to amplitude mismatch, and ultimately achieving efficient suppression of tire cavity noise.

[0105] The method in this application compensates for signal transmission delay through delay processing, ensuring timing synchronization between the anti-phase acoustic signal and the noise signal. Iterative correction using the FxLMS algorithm allows the correction coefficients to dynamically adapt to minute changes in noise, improving signal adaptability. Generating an anti-phase acoustic signal with the same frequency, opposite phase, and same amplitude as the corrected noise reduction signal ensures thorough noise reduction. This method fully utilizes the stable characteristics of tire noise while also considering dynamic changes. Compared to fixed-parameter anti-phase signal generation methods, it offers more stable and thorough noise reduction and is adaptable to the noise reduction needs of different tire models.

[0106] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0107] Based on the same inventive concept, this application also provides an active noise cancellation device for implementing the active noise cancellation method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more active noise cancellation device embodiments provided below can be found in the limitations of the active noise cancellation method described above, and will not be repeated here.

[0108] In an exemplary embodiment, referring to FIG6, FIG6 is a schematic flowchart of an active noise reduction device in one embodiment. As shown in FIG6, this application embodiment provides an active noise reduction device, including a signal acquisition module 601 and a noise reduction processing module 602, wherein:

[0109] The signal acquisition module 601 is used to acquire the pressure signal inside the tire cavity of the vehicle.

[0110] The noise reduction processing module 602 is used to process the pressure signal to obtain a noise signal; based on the noise signal, it controls the generation of an anti-phase sound wave signal so that the speaker can play the sound corresponding to the anti-phase sound wave signal in the tire cavity.

[0111] In one exemplary embodiment, the active noise reduction device provided in this application further includes a signal processing module:

[0112] The signal amplification module is used to amplify the pressure signal and obtain the amplified pressure signal.

[0113] The static pressure signal acquisition module is used to acquire the amplified static pressure signal based on the pressure amplification signal. The static pressure signal is the tire pressure signal when the tire does not generate noise under the same environmental conditions.

[0114] The noise signal acquisition module is used to acquire the dynamic pressure signal after the pressure signal is amplified based on the pressure amplification signal and the static pressure signal, and to characterize the noise signal through the dynamic pressure signal.

[0115] In an exemplary embodiment, the active noise reduction device provided in this application includes a static pressure signal acquisition module that is further configured to periodically acquire tire pressure signals, acquire pressure signals within a preset time period, acquire the average pressure value of the pressure amplification signal within the preset time period, and acquire the static pressure signal in the pressure signal based on the change in the average pressure value.

[0116] The noise signal acquisition module is also used to acquire the difference between the pressure amplification signal and the static pressure signal. The difference is the dynamic pressure signal, which is used to characterize the noise signal.

[0117] In one exemplary embodiment, the active noise reduction device provided in this application further includes a signal processing module:

[0118] The noise reduction signal acquisition module is used to perform delay processing on the noise signal based on the time delay generated by the transmission of the noise signal in the transmission path, so as to obtain the target noise reduction signal.

[0119] The correction coefficient acquisition module is used to obtain the initial correction coefficient based on the tire parameters, and optimize the initial correction coefficient based on the target noise reduction signal, the initial correction coefficient and the preset FxLMS algorithm to obtain the target correction coefficient.

[0120] The anti-phase acoustic signal acquisition module is used to obtain the corrected noise reduction signal based on the noise signal and the target correction coefficient, and generate an anti-phase acoustic signal based on the corrected noise reduction signal; the anti-phase acoustic signal has the same frequency, equal amplitude, and opposite phase as the corrected noise reduction signal.

[0121] In an exemplary embodiment, the active noise reduction device provided in this application includes a correction coefficient acquisition module that further comprises performing at least one iterative optimization on the initial correction coefficient to obtain a target correction parameter. In each iterative optimization, the correction parameter to be optimized is iterated based on a gradient descent iteration strategy and a preset step size to generate an optimized correction parameter. Based on the optimized correction parameter and the noise signal, an optimized noise-reduced signal is obtained. Based on the target noise-reduced signal and the optimized noise-reduced signal, a residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target parameter.

[0122] Each module in the aforementioned active noise cancellation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0123] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram is shown in Figure 7. The computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements an active noise reduction method. The display unit of the computer device is used to form a visually visible image and may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0124] Those skilled in the art will understand that the structure shown in Figure 7 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0125] In one exemplary embodiment, this application provides a car, which includes tires and an on-board chip. A tire pressure sensor and a speaker are disposed in the tire cavity. Both the tire pressure sensor and the speaker are communicatively connected to the on-board chip. The tire pressure sensor, the speaker, and the on-board chip can constitute the active noise cancellation system described in the above embodiments. The on-board chip can be used to implement the active noise cancellation method described in the above embodiments.

[0126] The automobile provided in the above embodiments has a similar implementation principle and technical effect to the method embodiments described above, and will not be repeated here. It should be noted that the automobile can be an autonomous vehicle, a manually driven vehicle, or an intelligent vehicle; the type of automobile is not limited, as long as the automobile can perform the methods described in any of the foregoing embodiments.

[0127] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0128] Acquire the pressure signal within the tire cavity of the vehicle. Process the pressure signal to obtain a noise signal. Based on the noise signal, generate an anti-phase sound wave signal, which is then used by the speaker to play the sound corresponding to the anti-phase sound wave signal within the tire cavity.

[0129] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0130] The pressure signal is amplified to obtain an amplified pressure signal. Based on the amplified pressure signal, a static pressure signal is obtained, which is the tire pressure signal when the tire does not generate noise under the same environmental conditions. Based on the amplified pressure signal and the static pressure signal, a dynamic pressure signal is obtained, which is used to characterize the noise signal.

[0131] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0132] The system periodically acquires tire pressure signals, including pressure signals within a preset time period. It also acquires the average pressure value of the amplified pressure signals over multiple preset time periods; this average pressure value is the static pressure signal. Finally, it acquires the difference between the amplified pressure signal and the static pressure signal; this difference is the dynamic pressure signal.

[0133] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0134] Based on the time delay caused by the transmission of noise signals in the transmission path, the noise signal is delayed to obtain the target noise-reduced signal. Initial correction coefficients are obtained based on tire parameters. These initial correction coefficients are then optimized using the target noise-reduced signal, the initial correction coefficients, and a preset FxLMS algorithm to obtain the target correction coefficients. Based on the noise signal and the target correction coefficients, a corrected noise-reduced signal is obtained. An inverse-phase acoustic signal is then generated based on this corrected signal. The inverse-phase acoustic signal has the same frequency, equal amplitude, and opposite phase to the corrected noise-reduced signal.

[0135] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0136] The initial correction coefficients are optimized through at least one iteration to obtain the target correction parameters;

[0137] In each iteration of optimization, the correction parameters to be optimized are iterated based on the gradient descent iteration strategy and the preset step size to generate the optimized correction parameters.

[0138] Based on the optimized correction parameters and the noise signal, the optimized denoising signal is obtained;

[0139] Based on the target noise reduction signal and the optimized noise reduction signal, the residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target parameter.

[0140] The computer device provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0141] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0142] Acquire the pressure signal within the tire cavity of the vehicle. Process the pressure signal to obtain a noise signal. Based on the noise signal, generate an anti-phase sound wave signal, which is then used by the speaker to play the sound corresponding to the anti-phase sound wave signal within the tire cavity.

[0143] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0144] The pressure signal is amplified to obtain an amplified pressure signal. Based on the amplified pressure signal, a static pressure signal is obtained, which is the tire pressure signal when the tire does not generate noise under the same environmental conditions. Based on the amplified pressure signal and the static pressure signal, a dynamic pressure signal is obtained, which is used to characterize the noise signal.

[0145] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0146] The system periodically acquires tire pressure signals, including pressure signals within a preset time period. It also acquires the average pressure value of the amplified pressure signals over multiple preset time periods; this average pressure value is the static pressure signal. Finally, it acquires the difference between the amplified pressure signal and the static pressure signal; this difference is the dynamic pressure signal.

[0147] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0148] Based on the time delay caused by the transmission of noise signals in the transmission path, the noise signal is delayed to obtain the target noise-reduced signal. Initial correction coefficients are obtained based on tire parameters. These initial correction coefficients are then optimized using the target noise-reduced signal, the initial correction coefficients, and a preset FxLMS algorithm to obtain the target correction coefficients. Based on the noise signal and the target correction coefficients, a corrected noise-reduced signal is obtained. An inverse-phase acoustic signal is then generated based on this corrected signal. The inverse-phase acoustic signal has the same frequency, equal amplitude, and opposite phase to the corrected noise-reduced signal.

[0149] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0150] The initial correction coefficients are optimized through at least one iteration to obtain the target correction parameters;

[0151] In each iteration of optimization, the correction parameters to be optimized are iterated based on the gradient descent iteration strategy and the preset step size to generate the optimized correction parameters.

[0152] Based on the optimized correction parameters and the noise signal, the optimized denoising signal is obtained;

[0153] Based on the target noise reduction signal and the optimized noise reduction signal, the residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target parameter.

[0154] The computer-readable storage medium provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0155] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0156] Acquire the pressure signal within the tire cavity of the vehicle. Process the pressure signal to obtain a noise signal. Based on the noise signal, generate an anti-phase sound wave signal, which is then used by the speaker to play the sound corresponding to the anti-phase sound wave signal within the tire cavity.

[0157] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0158] The pressure signal is amplified to obtain an amplified pressure signal. Based on the amplified pressure signal, a static pressure signal is obtained, which is the tire pressure signal when the tire does not generate noise under the same environmental conditions. Based on the amplified pressure signal and the static pressure signal, a dynamic pressure signal is obtained, which is used to characterize the noise signal.

[0159] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0160] The system periodically acquires tire pressure signals, including pressure signals within a preset time period. It also acquires the average pressure value of the amplified pressure signals over multiple preset time periods; this average pressure value is the static pressure signal. Finally, it acquires the difference between the amplified pressure signal and the static pressure signal; this difference is the dynamic pressure signal.

[0161] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0162] Based on the time delay caused by the transmission of noise signals in the transmission path, the noise signal is delayed to obtain the target noise-reduced signal. Initial correction coefficients are obtained based on tire parameters. These initial correction coefficients are then optimized using the target noise-reduced signal, the initial correction coefficients, and a preset FxLMS algorithm to obtain the target correction coefficients. Based on the noise signal and the target correction coefficients, a corrected noise-reduced signal is obtained. An inverse-phase acoustic signal is then generated based on this corrected signal. The inverse-phase acoustic signal has the same frequency, equal amplitude, and opposite phase to the corrected noise-reduced signal.

[0163] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0164] The initial correction coefficients are optimized through at least one iteration to obtain the target correction parameters;

[0165] In each iteration of optimization, the correction parameters to be optimized are iterated based on the gradient descent iteration strategy and the preset step size to generate the optimized correction parameters.

[0166] Based on the optimized correction parameters and the noise signal, the optimized denoising signal is obtained;

[0167] Based on the target noise reduction signal and the optimized noise reduction signal, the residual pressure signal is obtained. When the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target parameter.

[0168] The computer program product provided in the above embodiments has a similar implementation principle and technical effect to the above method embodiments, and will not be described again here.

[0169] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0170] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0171] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. An active noise reduction method, characterized in that, The method includes: acquiring a pressure signal within the tire cavity of a vehicle; processing the pressure signal to obtain a noise signal; and, based on the noise signal, controlling the generation of an anti-phase sound wave signal so that a loudspeaker can play a sound corresponding to the anti-phase sound wave signal within the tire cavity.

2. The method according to claim 1, characterized in that, The step of processing the pressure signal to obtain a noise signal includes: amplifying the pressure signal to obtain an amplified pressure signal; obtaining a static pressure signal amplified from the pressure signal based on the amplified pressure signal, wherein the static pressure signal is the tire pressure signal when the tire does not generate noise under the same environmental conditions; and obtaining a dynamic pressure signal amplified from the pressure signal based on the amplified pressure signal and the static pressure signal, thereby characterizing the noise signal through the dynamic pressure signal.

3. The method according to claim 2, characterized in that, The step of acquiring the amplified dynamic pressure signal of the pressure signal includes: periodically acquiring the pressure signal of the tire, acquiring the pressure signal within a preset time period, and acquiring the average pressure value of the amplified pressure signal within the preset time period, wherein the average pressure value is the static pressure signal in the pressure signal; and acquiring the difference between the amplified pressure signal and the static pressure signal, wherein the difference is the dynamic pressure signal.

4. The method according to any one of claims 1 to 3, characterized in that, The step of controlling the generation of an anti-phase acoustic signal based on the noise signal includes: performing delay processing on the noise signal based on the time delay generated by the transmission of the noise signal in the transmission path to obtain a target noise reduction signal; obtaining an initial correction coefficient based on tire parameters; optimizing the initial correction coefficient based on the target noise reduction signal, the initial correction coefficient, and a preset FxLMS algorithm to obtain a target correction coefficient; obtaining a corrected noise reduction signal based on the noise signal and the target correction coefficient; and generating the anti-phase acoustic signal based on the corrected noise reduction signal; wherein the anti-phase acoustic signal has the same frequency, equal amplitude, and opposite phase as the corrected noise reduction signal.

5. The method according to claim 4, characterized in that, The step of optimizing the initial correction coefficient to obtain the target correction coefficient includes: performing at least one iterative optimization on the initial correction coefficient to obtain the target correction coefficient; wherein, in each iterative optimization, the correction parameter to be optimized is iterated based on a gradient descent iterative strategy and a preset step size to generate an optimized correction parameter; an optimized denoised signal is obtained based on the optimized correction parameter and the noise signal; a residual pressure signal is obtained based on the target denoised signal and the optimized denoised signal; when the residual pressure signal is lower than or equal to a preset threshold, the optimized correction parameter is determined as the target correction coefficient.

6. The method according to claim 4, characterized in that, The process of obtaining the residual pressure signal includes: the residual pressure signal is calculated according to the formula e(n)=d(n)-w(z)×x(n); where e(n) represents the residual pressure signal, d(n) represents the target noise reduction signal, w(z) represents the target correction coefficient, and x(n) represents the noise signal.

7. An active noise reduction device, characterized in that, The device includes: a signal acquisition module for acquiring pressure signals within the tire cavity of a vehicle; a noise reduction processing module for processing the pressure signals to obtain noise signals; and, based on the noise signals, controlling the generation of anti-phase sound wave signals so that a speaker can play sounds corresponding to the anti-phase sound wave signals within the tire cavity.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

9. An active noise cancellation system, characterized in that, include: A detection sensor is installed inside the tire cavity of the vehicle to detect the pressure signal inside the tire cavity; A processor, communicatively connected to the detection sensor, is used to execute the active noise reduction method according to any one of claims 1-7; a speaker, disposed in the tire cavity of the vehicle, the speaker being communicatively connected to the signal processor, is used to play a sound corresponding to an anti-phase sound wave signal in the tire cavity.

10. A car, characterized in that, Includes the active noise cancellation system as described in claim 9.

Images