Dynamic In-Vehicle Noise Cancellation Diffusion Control

Abstract

To provide a method for controlling the stability of a dynamic in-vehicle noise cancellation system.SOLUTION: An ANC system 500 mounted in a vehicle adaptively controls a controllable filter 518 by an adaptive filter controller 520, generates a noise resistant signal yl[n], and thereby reduces in-vehicle noises. Here, a diffusion controller 562 compares a parameter calculated from this noise reduction signal with a threshold value, and detects an adaptation error and diffusion of the controllable filter. An output of the controllable filter is then controlled to become zero for a frequency at which the diffusion is detected.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present disclosure relates to active noise cancellation, and more particularly to mitigating the effects of adaptive filter spreading in engine command cancellation and / or road noise cancellation systems. [Background technology]

[0002] Active noise control (ANC) systems attenuate unwanted noise using feed-forward and feedback configurations to adaptively eliminate unwanted noise in a listening environment, such as a vehicle cabin. ANC systems generally cancel or reduce unwanted noise by generating cancellation sound waves that destructively interfere with the unwanted audible noise. Destructive interference results when a noise and a "noise-resistant" that is largely identical in magnitude to the noise but opposite in phase combine to reduce the sound pressure level (SPL) at a location. In a vehicle cabin listening environment, potential undesirable noise sources come from sounds radiated by the engine, interactions between the vehicle's tires and the road surface on which the vehicle is traveling, and / or vibrations of other parts of the vehicle. Thus, unwanted noise varies with the vehicle's speed, road conditions, and operating conditions.

[0003] Road noise cancellation (RNC) systems are specific ANC systems implemented in vehicles to minimize unwanted road noise inside the vehicle cabin. RNC systems use vibration sensors to detect road-induced vibrations resulting from tire and road contact that lead to unwanted audible road noise. This unwanted road noise inside the cabin is then cancelled or reduced in level by using speakers to generate sound waves that are ideally opposite in phase and identical in magnitude to the noise that would be reduced at the typical location of one or more listeners' ears. Cancelling such road noise results in a more comfortable ride for vehicle passengers and allows vehicle manufacturers to use lighter weight materials, thereby reducing energy consumption and reducing emissions.

[0004] Engine Command Cancellation (EOC) systems are specific ANC systems implemented in vehicles to minimize undesirable vehicle interior noise arising from narrowband acoustic and vibration emissions from the vehicle engine and exhaust system. EOC systems use a non-acoustic signal, such as a revolutions per minute (RPM) sensor, to reference a reference signal representative of engine speed. This reference signal is used to generate sound waves that are opposite in phase to the engine noise audible inside the vehicle. Because EOC systems use data from an RPM sensor, they do not require a vibration sensor.

[0005] RNC systems are typically designed to cancel wideband signals, while EOC systems are designed and optimized to cancel narrowband signals, such as individual engine operating commands. ANC systems in vehicles can provide both RNC and EOC technologies. Such vehicle-based ANC systems are typically least mean square (LMS) adaptive feedforward systems that continuously adapt the W filters based on both noise inputs (e.g., acceleration inputs from vibration sensors in the RNC system) and signals from error microphones located at various locations inside the vehicle cabin. ANC systems are susceptible to adaptive W filter instability or diffusion. As the W filters are adapted by the LMS system, one or more of the W filters may diverge rather than converge to minimize pressure at the error microphone location. The diffusion of the adaptive filters may lead to a rise in wideband or narrowband noise, or other undesirable behavior of the ANC system. Summary of the Invention [Means for solving the problem]

[0006] In one or more exemplary embodiments, a method of controlling stability in an active noise cancellation (ANC) system is provided. The method may include receiving a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting an interior soundscape of a vehicle cabin, and adjusting a nominal threshold for detecting diffusion of the ANC system based on the sensor signal to obtain an adjusted threshold. The method may further include receiving a noise immunity signal output from a controllable filter, the noise immunity signal indicative of noise immunity to be radiated from the speaker into the vehicle cabin. The method may further include calculating a parameter based on at least a portion of an analysis of the noise immunity signal, and modifying a characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold.

[0007] Implementations may include one or more of the following features: The parameter may be an amplitude of a noise-resistant signal at one or more frequencies; The nominal threshold may be a predetermined static threshold programmed for the ANC system under nominal operating conditions; The sensor signal received from the vehicle sensor may include a noise signal received from a vibration sensor; The sensor signal received from the vehicle sensor may include an engine torque signal received from a vehicle network bus; The sensor signal received from the vehicle sensor may be indicative of at least one of a vehicle speed, an engine rotation speed, and an accelerator pedal position; Adjusting the nominal threshold based on the sensor signal may include retrieving a threshold adjustment value from a lookup table based on a short-term average of the sensor signal, and modifying the nominal threshold by the threshold adjustment value to obtain an adjusted threshold.

[0008] Modifying the characteristics of the controllable filter may include deactivating at least one of the ANC system and the controllable filter. Modifying the characteristics of the controllable filter may include resetting filter coefficients of the controllable filter to zero and allowing the controllable filter to re-adapt. Modifying the characteristics of the controllable filter may include resetting filter coefficients of the controllable filter to a set of filter coefficient values ​​stored in a memory. Moreover, modifying the characteristics of the controllable filter may include increasing a leakage value of the adaptive filter controller. To achieve this goal, the method may further include reducing a leakage value of the adaptive filter controller when the parameter falls below an adjusted threshold.

[0009] One or more additional embodiments may be directed to an ANC system including at least one controllable filter configured to generate a noise-resistant signal based on an adaptive transfer characteristic and a noise signal received from a sensor. The adaptive transfer characteristic of the at least one controllable filter may be characterized by a set of filter coefficients. The ANC system may further include an adaptive filter controller and a diffusion controller in communication with at least the adaptive filter controller. The adaptive filter controller may include a processor and memory programmed to adapt the set of filter coefficients based on the noise signal and an error signal received from a microphone located in the cabin of the vehicle. The diffusion controller may include a processor and memory programmed to receive a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting the interior soundscape of the cabin, adjust a dynamic threshold for detecting diffusion of the ANC system based on the sensor signal, receive an error signal from the microphone, calculate a parameter based on an analysis of at least a portion of the error signal, and modify a characteristic of the at least one controllable filter in response to the parameter exceeding the dynamic threshold.

[0010] Implementations may include one or more of the following features: The parameter may be an amplitude of the error signal at one or more frequencies; The sensor signal received from the vehicle sensor may include at least one of a noise signal and an engine torque signal; The characteristics of the at least one controllable filter may be modified by the diffusion controller by resetting filter coefficients of the at least one controllable filter to a known state using a different set of filter coefficients stored in the memory; Alternatively, the characteristics of the at least one controllable filter may be modified by the diffusion controller by increasing a leakage value of the adaptive filter controller.

[0011] One or more additional embodiments may be directed to a computer program product embodied in a non-transitory computer-readable medium programmed for active noise cancellation (ANC). The computer program product may include instructions for receiving a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting the interior soundscape of the vehicle cabin, adjusting a nominal threshold for detecting diffusion of the ANC system based on the sensor signal to obtain an adjusted threshold, and receiving at least one of a noise immunity signal output from a controllable filter and an error signal output from a microphone located in the vehicle cabin, the noise immunity signal being indicative of the noise immunity to be radiated from the speaker into the vehicle cabin. The computer program product may further include instructions for calculating a parameter based on an analysis of at least one of the noise immunity signal and the error signal, and modifying an adaptive transfer characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold.

[0012] Implementations may include one or more of the following features: A computer program product, wherein the instructions for modifying the adaptive transfer characteristic of the controllable filter may include detecting a spread frequency of the controllable filter, and resetting the spread frequency of the controllable filter to zero, attenuating a filter coefficient at the spread frequency, or increasing a leakage value of the adaptive filter controller at the spread frequency. Moreover, the instructions for modifying the adaptive transfer characteristic of the controllable filter may include reducing a rate of change of the adaptive transfer characteristic. For example, the present application provides the following: (Item 1) 1. A method for controlling stability in an active noise cancellation (ANC) system, comprising: receiving a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting an interior soundscape of the vehicle cabin; adjusting a nominal threshold for detecting diffusion of the ANC system based on the sensor signal to obtain an adjusted threshold; receiving a noise immunity signal output from a controllable filter, the noise immunity signal being indicative of noise immunity to be radiated from a speaker into the vehicle cabin; calculating a parameter based on an analysis of at least a portion of the noise-resistant signal; modifying a characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold; The above method. (Item 2) 2. The method according to claim 1, wherein the parameter is the amplitude of the noise-resistant signal at one or more frequencies. (Item 3) 2. The method of claim 1, wherein the nominal threshold is a predetermined static threshold programmed into the ANC system under nominal operating conditions. (Item 4) 13. The method of claim 1, wherein the sensor signals received from vehicle sensors include noise signals received from a vibration sensor. (Item 5) 13. The method of claim 1, wherein the sensor signal received from a vehicle sensor includes an engine torque signal. (Item 6) 5. The method of claim 1, wherein the sensor signal received from a vehicle sensor is indicative of at least one of vehicle speed, engine speed, and accelerator pedal position. (Item 7) Adjusting the nominal threshold based on the sensor signal comprises: retrieving a threshold adjustment value from a lookup table based on a short term average of the sensor signal; modifying the nominal threshold value by the threshold adjustment value to obtain the adjusted threshold value; The method according to any one of the above items, comprising: (Item 8) 2. The method of claim 1, wherein modifying a characteristic of the controllable filter comprises deactivating at least one of the ANC system and the controllable filter. (Item 9) 2. The method of claim 1, wherein modifying the characteristics of the controllable filter comprises resetting filter coefficients of the controllable filter to zero and allowing the controllable filter to readapt. (Item 10) 2. The method of claim 1, wherein modifying a characteristic of the controllable filter comprises resetting filter coefficients of the controllable filter to a set of filter coefficient values ​​stored in a memory. (Item 11) 13. The method of claim 1, wherein modifying a characteristic of the controllable filter comprises increasing a leakage value of the adaptive filter controller. (Item 12) 20. The method of claim 19, further comprising reducing the leakage value of the adaptive filter controller when the parameter falls below the adjusted threshold. (Item 13) 1. An active noise cancellation (ANC) system, comprising: at least one controllable filter configured to generate a noise-resistant signal based on an adaptive transfer characteristic and a noise signal received from a sensor, the adaptive transfer characteristic of the at least one controllable filter being characterized by a set of filter coefficients; an adaptive filter controller including a processor and a memory programmed to adapt the set of filter coefficients based on the noise signal and an error signal received from a microphone located in the vehicle cabin; a diffusion controller in communication with at least the adaptive filter controller, the diffusion controller comprising: receiving sensor signals from vehicle sensors indicative of current vehicle operating conditions affecting the interior soundscape of the cabin; adjusting a dynamic threshold for detecting occlusion of the ANC system based on the sensor signal; receiving the error signal from the microphone and calculating a parameter based on an analysis of at least a portion of the error signal; modifying a characteristic of the at least one controllable filter in response to the parameter exceeding the dynamic threshold. the diffusion controller, comprising a processor and memory programmed to Including the above ANC system. (Item 14) The ANC system described in the preceding item, wherein the parameter is the amplitude of the error signal at one or more frequencies. (Item 15) 2. The ANC system of claim 1, wherein the sensor signal received from the vehicle sensor includes at least one of the noise signal and an engine torque signal. (Item 16) 2. The ANC system of claim 1, wherein the characteristics of the at least one controllable filter are modified by the diffusion controller by resetting the filter coefficients of the at least one controllable filter to a known state using a different set of filter coefficients stored in a memory. (Item 17) 2. The ANC system of claim 1, wherein the characteristics of the at least one controllable filter are modified by the diffusion controller by increasing a leakage value of the adaptive filter controller. (Item 18) 1. A computer program product embodied in a non-transitory computer readable medium programmed for active noise cancellation (ANC), the computer program product comprising: receiving, from a vehicle sensor, a sensor signal indicative of a current vehicle operating condition that affects the interior soundscape of the vehicle cabin; adjusting a nominal threshold for detecting diffusion of the ANC system based on the sensor signal to obtain an adjusted threshold; receiving at least one of a noise immunity signal output from a controllable filter and an error signal output from a microphone located in the vehicle cabin, the noise immunity signal indicative of noise immunity to be radiated from a speaker into the vehicle cabin; Calculating a parameter based on an analysis of at least one of the noise-resistant signal and the error signal; modifying an adaptive transfer characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold. The computer program product as described above, comprising instructions for: (Item 19) The instructions for modifying an adaptive transfer characteristic of the controllable filter include: Detecting a spread frequency of the controllable filter; resetting the spread frequency of the controllable filter to zero, attenuating a filter coefficient at the spread frequency, or increasing a leakage value of an adaptive filter controller at the spread frequency; The computer program product according to the preceding paragraph, (Item 20) 20. The computer program product of claim 19, wherein the instructions for modifying the adaptive transfer characteristic of the controllable filter include reducing a rate of change of the adaptive transfer characteristic. (Summary) An active noise cancellation (ANC) system may include an adaptive filter diffusion detector for detecting diffusion of one or more controllable filters as they adapt based on a dynamically adapted threshold. Upon detecting controllable filter diffusion, the ANC system may be deactivated or a particular speaker may be muted. Alternatively, the ANC system may modify the diffused controllable filters to restore proper operation of the noise canceling system. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is an environmental block diagram of a vehicle having an active noise control (ANC) system including road noise cancellation (RNC) in accordance with one or more embodiments of the present disclosure. [Diagram 2] FIG. 13 is a sample schematic demonstrating the relevant portions of an RNC system dimensioned to include an R accelerometer signal and an L speaker signal. [Diagram 3] FIG. 1 is a sample schematic block diagram of an ANC system including an engine command cancellation (EOC) system and an RNC system. [Figure 4] 1 is a sample lookup table of the frequency of each engine operating command for a given RPM in an EOC system. [Diagram 5] FIG. 1 is a schematic block diagram illustrating an ANC system including a diffusion controller in accordance with one or more embodiments of the present disclosure. [Figure 6] 6 is a block diagram illustrating in greater detail the diffusion controller from FIG. 5 in accordance with one or more embodiments of the present disclosure. [Figure 7] 6 is an alternative block diagram illustrating in greater detail the diffusion controller from FIG. 5 in accordance with one or more embodiments of the present disclosure. [Figure 8] FIG. 13 is a block diagram illustrating an effort calculator for a spreading controller in accordance with one or more embodiments of the present disclosure. [Figure 9] 1 is a flowchart describing a method for detecting and correcting adaptive filter diffusion in an ANC system in accordance with one or more embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Where necessary, detailed embodiments of the present invention are disclosed herein, but it should be understood that the disclosed embodiments are merely examples of the present invention that may be embodied in various and alternative forms. The figures are not necessarily to scale, and some features may be exaggerated or minimized to show details of particular components. Thus, specific structural and functional details disclosed herein are not intended to be limiting, but should be construed merely as representative references to teach those skilled in the art to variously use the present invention.

[0015] Any one or more of the controllers or devices described herein include computer-executable instructions that can be compiled or interpreted from computer programs created using various programming languages ​​and / or technologies. Generally, a processor (such as a microprocessor) receives instructions, such as from a memory or computer-readable medium, and executes the instructions. The processing unit includes a non-transitory computer-readable storage medium capable of executing instructions of a software program. The computer-readable storage medium may be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof.

[0016] 1 shows a road noise cancellation (RNC) system 100 for a vehicle 102 having one or more vibration sensors 108. The vibration sensors are placed throughout the vehicle 102 to monitor the vibration behavior of the vehicle's suspension, subframe as well as other axle and chassis components. The RNC system 100 may be integrated with a wideband feedforward and feedback active noise control (ANC) framework or system 104 that generates a noise-resistant signal by adaptive filtering of the signal from the vibration sensors 108 using one or more microphones 112. The noise-resistant signal may then be played back through one or more speakers 124. S(z) represents the transfer function between a single speaker 124 and a single microphone 112. It should be noted that while FIG. 1 shows a single vibration sensor 108, microphone 112, and speaker 124 for simplicity purposes only, a typical RNC system uses multiple vibration sensors 108 (e.g., 10 or more), microphones 112 (e.g., 4-6), and speakers 124 (e.g., 4-8).

[0017] The vibration sensor 108 may include, but is not limited to, an accelerometer, a force gauge, a ground wave transducer, a linear variable differential transformer, a strain gauge, and a load cell. For example, an accelerometer is a device whose output signal amplitude is proportional to acceleration. A wide range of accelerometers are available for use in RNC systems. They include accelerometers that are sensitive to vibrations in one, two, and three typically orthogonal directions. These multi-axis accelerometers typically have separate electrical outputs (or channels) for vibrations sensed in their X, Y, and Z directions. Thus, single-axis and multi-axis accelerometers may be used as vibration sensors 108 to detect the magnitude and phase of acceleration, and may also be used to sense orientation, movement, and vibration.

[0018] Noise and vibrations originating from the wheels 106 moving on the road surface 150 may be sensed by one or more of the vibration sensors 108 mechanically coupled to the suspension device 110 or chassis components of the vehicle 102. The vibration sensor 108 may output a noise signal X(n), which is a vibration signal representative of the detected road-induced vibrations. It should be noted that multiple vibration sensors are possible and their signals may be used separately or combined in various manners known by those skilled in the art. In certain embodiments, a microphone, an acoustic energy sensor, an acoustic intensity sensor, or an acoustic velocity sensor may be used instead of a vibration sensor to output a noise signal X(n) indicative of the noise resulting from the interaction of the wheels 106 and the road surface 150. The noise signal X(n) may be filtered by a modeled transfer characteristic S'(z), which estimates the secondary path (i.e., the transfer function between the noise-resistant speaker 124 and the error microphone 112) by the secondary path filter 122.

[0019] Road noise arising from the interaction of the wheels 106 and the road surface 150 is also transferred mechanically and / or acoustically to the passenger compartment and received by one or more microphones 112 inside the vehicle 102. The one or more microphones 112 may be located, for example, in a headrest 114 of a seat 116, as shown in FIG. 1. Alternatively, the one or more microphones 112 may be located in a headliner of the vehicle 102, or in some other suitable location that senses the acoustic noise field heard by an occupant inside the vehicle 102. The road noise arising from the interaction of the road surface 150 and the wheels 106 is transferred to the microphone 112 according to a transfer characteristic P(z), which represents the first-order path (i.e., the transfer function between the real noise source and the error microphone).

[0020] The microphone 112 may output an error signal e(n) representative of the noise present in the cabin of the vehicle 102 as detected by the microphone 112. In the RNC system 100, the adaptive transfer characteristic W(z) of the controllable filter 118 may be controlled by an adaptive filter controller 120, which may operate according to a known least mean square (LMS) algorithm based on the error signal e(n) and the noise signal X(n) filtered by the transfer characteristic S'(z) modeled by the filter 122. The controllable filter 118 is often referred to as a W filter. The LMS adaptive filter controller 120 may provide a sum cross spectrum configured to update the transfer characteristic W(z) filter coefficients based on the error signal e(n). The process of adapting or updating W(z) resulting in improved noise cancellation is referred to as converging. Convergence refers to the creation of a W filter that minimizes the error signal e(n), controlled by a step size that governs the rate of adaptation for a given input signal. The step size is a scaling factor that dictates how fast the algorithm converges to minimize e(n) by limiting the change in the magnitude of the W filter coefficients upon each update of the controllable W filter 118.

[0021] The noise-resistant signal Y(n) may be generated by an adaptive filter formed by the controllable filter 118 and adaptive filter controller 120 based on the identified transfer characteristic W(z) and the noise signal, or a combination of the noise signal, X(n). The noise-resistant signal Y(n) ideally has a waveform such that when played through the speaker 124, the noise-resistant signal is generated near the occupant's ears and the microphone 112, which is substantially opposite in phase and identical in magnitude to the phase and magnitude of the road noise audible to the occupant of the vehicle cabin. The noise-resistant signal from the speaker 124 may combine with the road noise in the vehicle cabin near the microphone 112, resulting in a reduction in the road noise-induced sound pressure level (SPL) at this location. In certain embodiments, the RNC system 100 may receive sensor signals from other acoustic sensors, such as acoustic energy sensors, acoustic intensity sensors, or acoustic particle velocity or acceleration sensors, in the passenger cabin to generate the error signal e(n).

[0022] While the vehicle 102 is in operation, the processor 128 may collect data from the vibration sensors 108 and microphones 112 and optionally process the data to build a database or map containing data and / or parameters to be used by the vehicle 102. The collected data may be stored locally in the storage 130 or in the cloud for later use by the vehicle 102. Examples of types of data related to the RNC system 100 that may be useful to store locally in the storage 130 include, but are not limited to, accelerometer or microphone spectra or other acceleration characteristics including time-dependent signals, spectra and time-dependent characteristics, pre-adapted W filter values, predicted error signals and noise-resistant signal thresholds for low, medium and high torque conditions, typical error signals and noise-resistant signal thresholds at various speeds on various pavement types (e.g., flat, rough, chip seal, cobblestone, expansion joint, etc.), dynamic leakage increase and decrease values, etc. Additionally, the processor 128 may analyze the sensor data and extract key features to determine a set of key parameters to be applied to the RNC system 100. The set of key parameters may be selected when the parameters exceed a threshold. In one or more embodiments, the processor 128 and memory 130 may be integrated with one or more RNC system controllers, such as the adaptive filter controller 120.

[0023] As previously described, a typical RNC system may use several vibration sensors, microphones, and speakers to detect the vibration behavior from the vehicle's structure and generate noise immunity. The vibration sensors may be multi-axis accelerometers with multiple output channels. For example, triaxial accelerometers typically have separate electrical outputs for vibrations detected in their X, Y, and Z directions. A typical configuration for an RNC system may have six error microphones, six speakers, and twelve channels of acceleration signals from four triaxial accelerometers or six biaxial accelerometers. Thus, the RNC system also includes multiple S'(z) filters (i.e., secondary path filters 122) and multiple W(z) filters (i.e., controllable filters 118).

[0024] The simplified RNC system schematic depicted in FIG. 1 shows one secondary path, represented by S(z), between each speaker 124 and each microphone 112. As previously mentioned, an RNC system typically has multiple speakers, microphones, and vibration sensors. Thus, a six speaker, six microphone RNC system has a total of 36 secondary paths (i.e., 6×6). Correspondingly, a six speaker, six microphone RNC system may also have 36 S′(z) filters (i.e., stored secondary path filters 122) that estimate the transfer function for each secondary path. As shown in FIG. 1, the RNC system also has one W(z) filter (i.e., controllable filter 118) between the vibration sensor (i.e., accelerometer) 108 and each noise signal X(n) from each speaker 124. Thus, a twelve accelerometer signal, six speaker RNC system may have 72 W(z) filters. The relationship between the accelerometer signal, the speaker, and the number of W(z) filters is shown in FIG.

[0025] FIG. 2 illustrates the R accelerometer signal [X 1 (n), X 2 (n), …X R(n)] and L noise-resistant signal [Y 1 (n), Y 2 (n), …Y L FIG. 1 is a sample schematic diagram demonstrating relevant portions of an RNC system 200 dimensioned to include an R*L controllable filter (or W filter) 218 ​​between each of the accelerometer signals and each of the speakers. As an example, an RNC system having 12 accelerometer outputs (i.e., R=12) may employ six biaxial accelerometers or four triaxial accelerometers. Thus, in the same example, a vehicle having six speakers (i.e., L=6) for noise immunity reproduction may use a total of 72 W filters. In each of the L speakers, the RW filter outputs are summed to create a noise immunity signal Y(n) for the speaker. Each of the L speakers may include an amplifier (not shown). In one or more embodiments, the R accelerometer signals filtered by the RW filters are summed to create an electrical noise immunity signal y(n), which is fed to an amplifier to generate an amplified noise immunity signal Y(n) that is sent to the speaker.

[0026] The ANC system 104 shown in FIG. 1 may also include an engine operating command cancellation (EOC) system. As described above, EOC techniques use a non-acoustic signal, such as an RPM signal representing engine speed, as a reference to generate a sound that is opposite in phase to the engine noise audible inside the vehicle. A common EOC system utilizes a narrowband feedforward ANC framework to generate an anti-noise signal using the RPM signal to guide the generation of an engine operating command signal that is identical in frequency to the engine operating command that is to be canceled, and adaptively filter it to create the anti-noise signal. After being transmitted via a secondary path from the anti-noise source to the listening position or error microphone, the anti-noise ideally has the same amplitude but opposite phase as the combined sound generated by the engine and exhaust pipe and filtered by the primary path extending from the engine to the listening position and from the exhaust pipe outlet to the listening position. Thus, where the error microphone is present in the vehicle cabin (i.e., most likely to be at or near the listening position), the superposition of engine operating command noise and noise immunity will ideally be zero, so that the acoustic error signal received by the error microphone will record only sounds other than the engine operating command (which would ideally be cancelled) or the operating commands produced by the engine and exhaust.

[0027] Typically, a non-acoustic sensor, e.g., an RPM sensor, is used as the reference. The RPM sensor may be, for example, a Hall effect sensor placed adjacent to a spinning steel disk. Other detection principles, such as optical or inductive sensors, may be employed. The signal from the RPM sensor may be used as a guide signal to generate any number of reference engine operating command signals corresponding to each of the engine operating commands. The reference engine operating commands form the principal components for the noise canceling signals generated by one or more narrowband adaptive feedforward LMS blocks forming the EOC system.

[0028] 3 is a schematic block diagram illustrating an example of an ANC system 304, including both an RNC system 300 and an EOC system 340. Similar to the RNC system 100, the RNC system 300 may include elements 308, 312, 318, 320, 322, and 324, consistent with the operation of elements 108, 112, 118, 120, 122, and 124, respectively, discussed above. The EOC system 340 may include an RPM sensor 342, which may provide an RPM signal 344 (e.g., a square wave signal) indicative of the rotation of the engine drive shaft or other rotating shaft indicative of the engine rotational speed. In some embodiments, the RPM signal 344 may be obtained from a vehicle network bus (not shown). As the emitted engine operating command is directly proportional to the drive shaft RPM, the RPM signal 344 is indicative of the frequency generated by the engine and exhaust system. Thus, the signal from the RPM sensor 342 may be used to generate a reference engine operating command signal corresponding to each of the engine operating commands for the vehicle. Thus, the RPM signal 344 may be used in conjunction with an RPM vs. engine operating command frequency lookup table 346 that provides a list of engine operating commands emitted at each RPM.

[0029] 4 shows an example EOC cancellation tuning table 400 that can be used to generate the lookup table 346. The example table 400 lists the frequency (in cycles / second) of each engine operating command for a given RPM. In the illustrated example, four engine operating commands are shown. The LMS algorithm takes the RPM as an input and generates a sine wave for each operating command based on this lookup table 400. As previously explained, the associated RPM for the table 400 may be the drive shaft RPM.

[0030] 3, the frequency of a given engine operating command at the sensed RPM, as retrieved from lookup table 346, may be provided to frequency generator 348, which generates a sine wave at the given frequency. This sine wave represents a noise signal X(n) indicative of engine operating command noise for the given engine operating command. Similar to RNC system 300, this noise signal X(n) from frequency generator 348 may be sent to adaptive controllable filter 318 or W filter, which provides a corresponding noise-resistant signal Y(n) to loudspeaker 324. As shown, for this narrowband variety of components, EOC system 340 may be identical to wideband RNC system 300, including error microphone 312, adaptive filter controller 320, and secondary path filter 322. The noise-resistant signal Y(n) broadcast by the speaker 324 generates an anti-noise signal that is substantially out of phase with but identical in magnitude to the actual engine operating command noise at the listener's ear position, which may be in close proximity to the error microphone 312, thereby reducing the sound amplitude of the engine operating command. Because the engine operating command noise is narrowband, the error microphone signal e(n) may be filtered by bandpass filters 350, 352 before being passed to the LMS-based adaptive filter controller 320. In an embodiment, proper operation of the LMS adaptive filter controller 320 is achieved when the noise signal X(n) output by the frequency generator 348 is bandpass filtered using the same bandpass filter parameters.

[0031] To simultaneously reduce the amplitude of multiple engine operating commands, the EOC system 340 may include multiple frequency generators 348 to generate a noise signal X(n) for each engine operating command based on the RPM signal 344. By way of example, FIG. 3 illustrates a method for generating a unique noise signal (e.g., X(n)) for each engine operating command based on the engine speed. 1 (n), X 23 shows a two-command EOC system having two such frequency generators for generating the two engine operation commands (e.g., frequency generators 350, 352 (labeled BPF and BPF2, respectively) with different high-pass and low-pass filter corner frequencies due to the different frequencies of the two engine operation commands. The number of frequency generators and corresponding noise cancellation components will ultimately vary based on the number of engine operation commands for a particular engine of the vehicle. As the two command EOC systems 340 are combined with the RNC system 300 to form the ANC system 304, the noise-resistant signal Y(n) output from the three controllable filters 318 are summed and sent to the speaker 324 as the speaker signal S(n). Similarly, the error signal e(n) from the error microphone 312 may be sent to the three LMS adaptive filter controllers 320.

[0032] One major factor that can lead to instability or reduced noise cancellation performance in an ANC system occurs when the adaptive W filters diverge during adaptation by a feedforward LMS system. When the adaptive W filters converge properly, the sound pressure level at the location of the error microphone is minimized. However, when one or more of those adaptive W filters diverge, instability resulting in noise rise can occur instead of noise cancellation. Therefore, systems and methods may be employed to detect and control adaptive filter divergence to maintain ANC system performance and stability.

[0033] An ANC system can detect instabilities or noise rises caused by misadaptation or diffusion of the W filter by acquiring and analyzing data from one or more microphones placed around the passenger vehicle cabin. However, the interior soundscape of the vehicle can vary greatly. For example, the interior soundscape of the cabin can range from very quiet to very loud as the vehicle accelerates from a low speed, low engine torque scenario to a high vehicle speed, high engine torque scenario. Current ANC systems only allow a single in-cabin SPL threshold to detect all instabilities. This approach can be problematic because the interior noise level in the vehicle depends on the vehicle speed, engine output torque, and road surface roughness, etc. Thus, at high vehicle speeds and high engine torques, for example, the microphone SPL threshold should be set relatively high since there may be loud engine noise when the system is operating properly. However, with low vehicle speeds and low engine torques, there may be relatively quiet engine noise when the system is operating properly, requiring a low SPL threshold to detect instabilities immediately.

[0034] Because current systems only allow a single SPL threshold, it is typically set at a very high level to allow proper ANC operation at high vehicle speeds (i.e., because the ANC algorithm does not properly deactivate at high vehicle speeds or on rough roads). Thus, misadaptation of the W filter resulting in noise rise at low and medium vehicle speeds with relatively low torque may not be detected immediately or at all. Rather, instability during this low speed / low torque operating condition may take a relatively long time to be detected, i.e., until the noise rise increases highly enough in amplitude to exceed the high SPL threshold. Meanwhile, the vehicle occupants are subject to the instability of high and annoyingly increasing amplitude over a relatively long period of time (e.g., 20 seconds or more). As a result, relying on a single in-cabin SPL magnitude limitation for use as a threshold detector for ANC instability may be inappropriate. Dynamically determined SPL thresholds may be employed to avoid slow (or in some cases no) detection of EOC / RNC noise rise, instability, or spread.

[0035] Briefly, the cabin SPL value as measured by the microphone may be compared to the dynamically determined SPL threshold. For the EOC, the SPL threshold may be multiplied by a factor proportional to the engine torque. For example, when the vehicle is in a high torque driving scenario, a relatively high SPL threshold may be generated by multiplying the nominal SPL threshold with a (high) torque multiplier. When the vehicle is in a low torque driving scenario, a low SPL threshold may be generated by multiplying the nominal SPL threshold with a (low) torque multiplier. For better performance of this algorithm, a short-time average of the engine torque signal, or other vehicle signal that can serve as a suitable surrogate for the engine torque, may be required. For the RNC, the same dynamic threshold setting may be adopted for early detection of instability. In the case of the RNC, a short-time average of the noise signal output from a vibration sensor such as an accelerometer may replace the engine torque value. This is because the interior noise level is relatively high on a rough road with a high amplitude accelerometer output and relatively low for a flat road with a low amplitude accelerometer output. When SPL values ​​exceed their dynamic thresholds, diffusion mitigation may be employed to prevent noise rise or other undesirable behavior such as inappropriate noise cancellation, which may include, for example, muting the ANC system, resetting the diffused W-filter to a zero state or some other stored state, and temporarily or permanently increasing the W-filter leakage.

[0036] According to one or more additional embodiments, ANC instability detection may be employed using dynamic thresholding of the noise-resistant signal Y(n) instead of the cabin SPL as determined by the microphone error signal e(n). The microphone error signal e(n) may include all noise sources in the passenger cabin. Instead of detecting only engine noise or road noise, the error microphone also detects wind noise, music, speech, and other interfering noises in the passenger cabin, which are included in the corresponding error signal e(n). Moreover, the error signal e(n) in a pure RNC system also includes engine noise, and the error signal e(n) in a pure EOC system also includes road noise. The noise-resistant signal Y(n) generated by the ANC system does not include any of the above-mentioned interfering signals, and the contribution of the noise-resistant signal Y(n) from the EOC system may be analyzed separately from the contribution of the noise-resistant signal Y(n) from the RNC system when those systems are combined into one ANC system.

[0037] In an embodiment, the EOC instability detection threshold applied to the noise immunity signal Y(n) may be dynamically modified by values ​​stored in a look-up table of short-term averages of the engine torque signal because the level of noise immunity generated by the LMS-based EOC algorithm is relatively high for high engine torques and relatively low for low engine torques. To determine the dynamic instability threshold, engine torque may be used as a guide signal that approximates engine noise, and other guide signals such as engine speed, accelerator pedal position, vehicle acceleration, instantaneous fuel economy, or uniform statistics from a fuel pump may be employed as well.

[0038] Similarly, the RNC instability detection threshold applied to the noise immunity signal Y(n) may be dynamically modified by values ​​stored in a look-up table of short-term averages of the noise signal X(n), such as those output from a vibration sensor. This is because the noise immunity level generated by the RNC algorithm is relatively high for rough roads and relatively low for smooth roads. Other signals indicative of a rough pavement type may be used instead of a signal from a vibration sensor. For example, instead of a processed output from an accelerometer or other vibration sensor, a GPS derived or previously stored roughness estimate of the currently navigating road may be used as a guide signal for the look-up table.

[0039] FIG. 5 is a schematic block diagram of a vehicle-based ANC system 500 illustrating many of the key ANC system parameters that can be used to detect adaptive W filter spread and optimize ANC system performance. For ease of illustration, the ANC system 500 illustrated in FIG. 5 is illustrated with the components and features of an RNC system, such as the RNC system 100. However, the ANC system 500 may include an EOC system, such as that shown and described in connection with FIG. 3. Thus, the ANC system 500 is a schematic representation of an RNC and / or EOC system, such as that described in connection with FIGS. 1-3, featuring additional system components. Similar components may be numbered using similar conventions. For example, similar to the RNC system 100, the ANC system 500 may include elements 508, 510, 512, 518, 520, 522, and 524, consistent with the operation of elements 108, 110, 112, 118, 120, 122, and 124, respectively, discussed above.

[0040] As shown, the ANC system 500 may further include a diffusion controller 562 disposed along the path between the controllable filter 518 and the adaptive filter controller 520. The diffusion controller 562 may include a processor and memory (not shown) programmed to detect the diffusion of the controllable filter 518. This may include computing parameters by analyzing samples from the error signal from the microphone 512 and / or the noise-resistant signal from the controllable filter 518 in either or both the time domain or the frequency domain. To achieve this goal, FIG. 5 clearly shows Fast Fourier Transform (FFT) blocks 564, 566 and an Inverse Fast Fourier Transform (IFFT) block 568 for converting signals between the time domain and the frequency domain. Thus, the variable names in FIG. 5 are slightly changed from those shown in FIGS. 1-3. Uppercase variables represent signals in the frequency domain and lowercase variables represent signals in the time domain. The letter "n" refers to a sample in the time domain and the letter "k" refers to a bin in the frequency domain. The diagram in Figure 5 further illustrates the presence of multiple signals, indicating an R reference signal, an L speaker signal, and an M error signal. The following table provides a detailed explanation of the various symbols and variables in Figure 5. [Table 1]

[0041] Similar to FIG. 1, a noise signal x from a noisy input such as a vibration sensor 508 r [n] is the transfer characteristic modeled by the secondary path filter 522 using the stored estimate of the secondary path as previously described.

number

[0042] The diffusion controller 562 receives the time domain error signal e from the microphone(s) 512. m [n] and / or the frequency domain error signal E m Additionally or alternatively, the spread controller 562 may receive the noise-resistant signal(s) y [k, n] generated by the controllable filter(s) 518. l [n]. Moreover, the diffusion controller 562 may calculate one or more parameters by analyzing the error signal or the noise-resistant signal. The parameter may be the amplitude of the error signal and / or the noise-resistant signal at one or more frequencies or frequency ranges, although other parameters may be employed. In an embodiment, the parameter is a frequency-dependent amplitude of the error signal and / or the noise-resistant signal at one or more frequency ranges. The parameter may be compared to a dynamic threshold to detect instability of the ANC system (e.g., diffusion of the controllable filter 518). If diffusion is detected, the diffusion controller 562 may again send an adjustment signal to the adaptive filter controller 520 instructing the adaptive filter controller to modify the characteristics of at least one controllable filter 518 or an adaptive parameter of the LMS system 520, such as leakage.

[0043] In either the RNC or EOC systems, a response to detecting diffusion may be for the diffusion controller 562 to replace some or all of the W filter values, for example, using a previously stored adjusted W filter. Other responses to detecting diffusion by the diffusion controller 562 may include replacing some or all of the controllable filter 518 with a filter constructed from scratch, which effectively resets the controllable filter. Other diffusion mitigation measurements by the diffusion controller 562 may include adding leakage at frequencies including the diffused frequencies, resetting coefficients at the diffused frequencies to or toward zero, attenuating some or all of the W filter coefficients, or decreasing the step size (i.e., decreasing the rate of change of the adapter transfer characteristic of the controllable filter 518) to reduce the risk of a later diffusion event. In certain embodiments, the adjustment signal from the diffusion controller 562 may mute the ANC algorithm for a period of time (referred to as a "pause") before unmuting with or without any of the above-described modifications to the controllable W filter 518.

[0044] The diffusion controller 562 may be a dedicated controller for detecting the diffused controllable W filter, or may be integrated with another controller or processor in the ANC system, such as the LMS controller 520. Alternatively, the diffusion controller 562 may be integrated into another controller or processor in the vehicle 102 that is separate from the other components in the ANC system 500.

[0045] 6 is a block diagram illustrating the diffusion controller 562 in more detail, in accordance with one or more embodiments of the present disclosure. As previously described, the threshold for detecting instability in the ANC system 500 may be dynamic to account for the changing interior soundscape of the vehicle cabin. Accordingly, the diffusion controller 562 may be further configured to modify or adjust this dynamic instability threshold. In the example shown in FIG. 6, instability in the ANC system 500 is detected by detecting an error signal e from the microphone 512. m [n] may be used to evaluate the in-cabin SPL against a dynamic instability threshold. However, the diffusion controller 562 may also use the noise tolerant signal y l It should be noted that [n] may also be used to detect instability.

[0046] The spread controller 562 is configured to set a nominal threshold TH nom may be stored or received, and a threshold value TH nom , under predetermined nominal vehicle operating conditions, the error signal e m [n] may be compared. The diffusion controller 562 may also receive sensor signals 610 from one or more vehicle sensors indicative of current vehicle operating conditions that may affect the interior soundscape of the vehicle cabin. As previously described, the sensor signals 610 may include noise signals x from noise inputs, such as the vibration sensor 508, which may generally indicate the interior noise level due to current road conditions. r [n]. The sensor signals 610 may also include other vehicle signals generally indicative of engine noise, such as engine torque, engine speed, vehicle speed, and accelerator pedal position. The sensor signals 610 may also include any music or other audio being played from a speaker, and a signal indicative of any associated characteristics of the audio, such as its frequency-dependent amplitude. Additionally, vehicle signals may be received by the diffusion controller 562 from a vehicle network bus 612, such as a controller area network (CAN) bus.

[0047] The diffusion controller 562 may further include a threshold adjustment table 614. The threshold adjustment table 614 adjusts the nominal SPL threshold TH based on one or more of the sensor signals 610. nom VAL from the threshold adjustment table 614. In an embodiment, a short-term average of one or more of the sensor signals 610 may be used to obtain the adjustment value ADJ_VAL from the threshold adjustment table 614. The adjustment value may be a look-up table that stores threshold adjustment values ​​that are used to dynamically modify the adjusted threshold TH. That is, one or more of the sensor signals 610 may be used to obtain the adjustment value ADJ_VAL from the threshold adjustment table 614. In an embodiment, a short-term average of one or more of the sensor signals 610 may be used to obtain the adjustment value ADJ_VAL from the threshold adjustment table 614. adj The threshold adjustment value may be combined with the nominal threshold to obtain an adjusted threshold. As shown, the threshold adjustment value may modify the nominal threshold through an addition operation, as indicated by adder 616. Alternatively, the nominal threshold may be multiplied with the threshold adjustment value to obtain an adjusted threshold. For example, as previously described, the threshold adjustment value may be a factor proportional to a value indicated by the sensor signal 610 (e.g., engine torque, accelerometer output, etc.).

[0048] The diffusion controller may further include a threshold detector 618. The threshold detector 618 may receive both the adjusted threshold and the error signal (or noise-resistant signal). The threshold detector 618 may further compare the error signal (or noise-resistant signal) to the adjusted threshold. In certain embodiments, the threshold detector 618 may calculate a parameter based on at least a partial analysis of the error signal (or noise-resistant signal). Instability, noise rise, or diffusion of the ANC system 500 may be detected by the threshold detector 618 when the error signal or a corresponding parameter exceeds the adjusted threshold. If instability is detected, the threshold detector 618 may generate an adjustment signal, which is again communicated by the diffusion controller 562 to the adaptive filter controller 520 as previously described. Naturally, the adjustment signal may include instructions to modify the characteristics of the controllable filter 518 or the LMS adaptive filter controller 520 in response to the error signal or a corresponding parameter exceeding the adjusted threshold. In certain embodiments, the adjustment signal may simply be a positive indicator to the adaptive filter controller 520 that diffusion has been detected. In other embodiments, the adjustment signal may include specific instructions regarding the response strategy to be adopted by the adaptive filter controller 520.

[0049] 7 is a block diagram of an alternative embodiment for the spreading controller 562. In this embodiment, the spreading controller 562 may analyze both the error signal and the noise-resistant signal for spreading along separate paths and may calculate a joint adjustment value based on the results of the spreading analysis of both incoming signals. In this embodiment, the spreading controller 562 calculates a nominal threshold TH nom For example, an error signal e m [n] may be compared against a nominal minimum level threshold under predetermined nominal vehicle operating conditions. l[n] may be compared against a nominal noise tolerance threshold under a predetermined nominal vehicle operating condition. As previously described, the diffusion controller 562 may also receive sensor signals 610 from one or more vehicle sensors indicative of current vehicle operating conditions that may affect the interior soundscape of the vehicle cabin. As shown in FIG. 7, the sensor signals 610 may be received by an effort calculator 720. The effort calculator 720 may consider multiple sensor signals in calculating an overall effort value indicative of the current vehicle operating conditions that affect the interior soundscape of the vehicle cabin. FIG. 8 is an exemplary block diagram illustrating the effort calculator 720 in more detail. As shown, the effort calculator 720 may include multiple effort vs. sensor signal lookup tables 830. Each of the sensor signals 610 used to indicate the current interior soundscape (e.g., engine torque, pedal position, accelerometer output, etc.) may be fed into an associated lookup table 830 to obtain a corresponding effort value component (i.e., eff1, eff2...effN). The effort value components may be combined by effort calculator 720 to generate an overall effort value.

[0050] 7, the spread controller 562 may further include a pair of threshold adjustment tables 714, one each for the noise tolerant signal and the error signal. The threshold adjustment tables 714 adjust the nominal threshold TH based on the effort value. nom Alternatively, the threshold adjustment table 714 may be a look-up table that stores threshold adjustment values ​​that are used to dynamically modify the adjusted threshold TH. Separate threshold adjustment tables 714 may be provided for both the nominal noise tolerance threshold and the nominal minimum level threshold, since the corresponding adjustment values ​​may differ for a given effort value. The adjustment values ​​are stored in the adjusted threshold TH. adj6, each threshold adjustment value may be modified through an arithmetic operator 716 to obtain a pair of adjusted thresholds, one for each noise-tolerant signal and error signal. Each adjusted threshold may be received by a corresponding threshold detector 718. A first threshold detector 718 may receive both the adjusted noise-tolerant threshold and the noise-tolerant signal (or the noise-tolerant signal), and a second threshold detector 718 may receive both the adjusted minimum level threshold and the error signal. The threshold detector 718 may further compare the noise-tolerant signal to the adjusted noise-tolerant threshold and the error signal to the adjusted minimum level threshold, respectively. In certain embodiments, the threshold detector 718 may calculate a parameter based on at least a portion of an analysis of each of the noise-tolerant signal and the error signal.

[0051] Instability or diffusion of the ANC system 500 may be detected by either or both of the threshold detectors 718 when the input signal or corresponding parameter exceeds their respective adjusted threshold. The output of each threshold detector 718 may be received by an adjustment calculator 722, which may generate a combined adjustment output as an adjustment value communicated to the adaptive filter controller 520, as previously described. One anti-noise signal y for each of the L speakers 524 may be generated by the threshold detectors 718. l [n], one error signal e from each of the M microphones 512. m Because of the presence of [n], it is possible for the adjustment calculator 722 to mitigate the noise rise without acting on all of the R×LW filters. In an embodiment, if one noise-resistant signal exhibits a noise rise above the threshold, then only the RW filter associated with this one noise-resistant signal can be acted on. This is the least invasive change to the system that can mitigate the rise.

[0052] It is possible to go beyond these RW filters to reduce noise rise. In another embodiment, one error signal em When [n] exceeds its dynamically adjusted threshold, thereby indicating a noise rise, only the W filter of the closest speaker may act to mitigate the rise. In yet another embodiment, a single error signal e m If [n] exceeds its dynamically adjusted threshold, thereby indicating a noise rise, only the speaker or W filter of the speaker(s) with this highest magnitude transfer function S(z) to this microphone may act to mitigate the rise. Optionally, only the speaker signal or W filter contributing to the signal with the highest magnitude transfer function S(z) in this frequency range of the noise rise may act. Alternatively, all speakers may act. Because of the presence of the L noise-resistant signal, the L noise-resistant signal y l When one of [n] exceeds its adjusted threshold, mitigation may be triggered for one or more of the W filters that contribute to the noise-resistant signal.

[0053] 9 is a flow chart describing a method 900 for mitigating the effects of a diffused or misadapted controllable W filter in an ANC system 500. Various steps of the disclosed method may be performed by the diffuse controller 562, either alone or in conjunction with other components of the ANC system.

[0054] In step 910, the diffusion controller 562 may receive one or more sensor signals indicative of current vehicle operating conditions that affect the interior soundscape of the vehicle cabin. For example, the sensor signals may include a noise signal x from a noise input, such as a vibration sensor 508. r[n]. In addition, the sensor signals may include other vehicle signals indicative of other vehicle operating parameters such as engine torque, engine speed, vehicle speed, and accelerator pedal position. Such additional sensor data may be received, for example, from a controller area network (CAN) bus of the vehicle. In step 920, the diffusion controller 562 may further receive a nominal threshold for detecting diffusion or noise rise of the ANC system. For example, the diffusion controller 562 may receive an error signal e m If the stability of the ANC system is being evaluated based on an analysis of [n], the nominal threshold may be a nominal minimum level threshold corresponding to the in-cabin SPL limit under pre-determined nominal operating conditions. Alternatively, the diffusion controller 562 may generate a noise immunity signal y l When evaluating the stability of an ANC system based on an analysis of [n], the nominal thresholds may be nominal noise tolerance thresholds corresponding to noise tolerance SPL limits under predetermined nominal operating conditions, and may be frequency dependent for one or more sub- or major bands of frequencies.

[0055] At step 930, the diffusion controller 562 may adjust a nominal threshold for detecting diffusion of the ANC system based on the sensor signal to obtain an adjusted threshold. According to one or more embodiments, adjusting the nominal threshold may include retrieving a threshold adjustment value from a lookup table based on a short-term average of the sensor signal, and modifying the nominal threshold by the threshold adjustment value to obtain the adjusted threshold. Modifying the nominal threshold by the threshold adjustment value may include adding the adjusted threshold to the nominal threshold or multiplying the nominal threshold by the threshold adjustment value.

[0056] In step 940, the diffusion controller 562 may receive an input signal for detecting instability in the ANC system and may calculate an analysis based at least in part on the input signal. As previously described, the input signal for detecting instability in the system may include an error signal e m[n] or noise-resistant signal y l The parameter calculated from the input signal may include the amplitude of the input signal at one or more frequencies.

[0057] In step 950, the parameters calculated from either the input signal, the error signal, or the noise-resistant signal may be directly compared to the corresponding adjusted thresholds. If the parameters exceed the adjusted thresholds, the spreading controller 562 may conclude that a spreading or adaptation error has been detected. If the parameters from the input signal do not exceed the thresholds, the spreading controller 562 may conclude that a spreading or adaptation error has not been detected.

[0058] With reference to step 960, when the adjusted threshold is exceeded indicating diffusion of the controllable filter, the method may proceed to step 970. In step 970, mitigation measures may be applied to the diffused controllable W filter to minimize in-cabin noise rise or reduce the ANC impact of the W filter diffusion. However, when diffusion is not detected, the method may skip any mitigation and return to step 910 so that processing can be repeated.

[0059] In step 970, diffusion mitigation may be applied to either or both of the diffusion or misadapted time domain W filters or frequency domain W filters. In certain embodiments, countermeasures may be applied to the entire W filter or only to certain frequencies for the frequency domain W filter. Mitigation methods that may be applied to the entire controllable W filter (in either the time domain or the frequency domain) may include resetting filter coefficients of one or more W filters to zero to allow the filter coefficients to be re-adapted or set to a set of filter coefficient values ​​stored in the memory of the ANC system. The set of filter coefficient values ​​stored in the memory may include filter coefficient values ​​from a W filter that is in a known good state, such as a W filter tuned by an experienced engineer or obtained from a controllable filter prior to when diffusion was detected. For example, the controllable filter may be reset using filter coefficients that had, for example, 10 seconds or 1 minute prior to diffusion. Alternatively, the controllable W filter may be reset to an initial state, such as when the ANC system 500 was powered on. Another mitigation technique may be to simply deactivate or mute the ANC system when diffusion is detected. In an embodiment, when diffusion is detected, only the diffused W filter may be deactivated or set to zero, but may not be adapted. In an embodiment, when diffusion is detected, the amplitude of all filter taps or the magnitude of all frequency domain filter coefficients may be decreased. In an embodiment, the value of leakage at all frequencies may be increased by the adaptive filter controller 520 in response to an adjustment signal from the diffusion controller 562 when diffusion is detected.

[0060] Countermeasures that apply only the frequency domain approach may include attenuating the W filter coefficients at or near the spread frequencies, and adding or increasing the leakage values ​​at or near the spread frequencies. In an embodiment for mitigation applied in the frequency domain, the spreading controller 562 applies mitigation to the input signal x r[n] and e m The unstable, spread frequencies identified in step 630 can be adaptively notched out by adding notches or band-reject filters for [n] or their frequency range counterparts. This prevents the adaptive filter controller 520 from increasing the magnitude of the W filter in frequency ranges that are problematic in subsequent operation of the ANC system 500. This can optionally involve reconfiguring the W filter as outlined above or using leakage at those unstable, spread frequencies or all frequencies.

[0061] As previously mentioned, in one or more additional embodiments, the noise-resistant signal y l When diffusion is detected, such as when [n] exceeds its adjusted threshold, a value of leakage may be increased in the LMS adaptive filter controller 520. This leakage value may be calculated by multiplying the noise-resistant signal y l As long as [n] is still above its adjusted threshold, it may continue to increase by a predetermined amount with each iteration through the process flow shown in FIG. l When [n] no longer exceeds its adjusted threshold, the noise-resistant signal y l As long as [n] does not exceed its adjusted threshold, it may be decreased by a predetermined amount during subsequent iterations through the process flow shown in FIG.

[0062] In an embodiment, the noise-resistant signal y l When [n] exceeds its adjusted threshold, leakage can be increased for all W filters in the ANC system 500. In another embodiment, the noise-resistant signal y l When [n] exceeds its adjusted threshold, leakage increases for all W filters for that speaker. The LMS controller 520 may be instructed to increase or decrease the leakage value in response to receiving an adjustment signal from the diffusion controller 562. In an embodiment, the error signal e mA similar process can be effected to ramp up the leakage if [n] exceeds its adjusted threshold, followed by ramping down the leakage if it continues not to exceed its adjusted threshold.

[0063] As previously explained, there is one controllable W filter for each combination of speaker 512 and noise input (e.g., each engine operating command or vibration sensor). Thus, a 12 accelerometer, 6 speaker RNC system would have 72 W filters (i.e., 12×6=72), and a 5 engine operating command, 6 speaker EOC system would have 30 W filters (i.e., 5×6=30). The method 9000 shown in FIG. 9 may be performed after every new set of W filters is calculated, or may be performed less frequently, to reduce the computational power required and thereby save CPU cycles.

[0064] It should be noted that multiplying the sensor output voltage with an adjustment value or dividing the sensor output voltage by an adjustment value can have the same effect as dividing the threshold value with an adjustment value or multiplying the threshold value with an adjustment value. That is, in an alternative embodiment, rather than adjusting the detection threshold, the signal y l [n] and / or e m [n] can be adjusted, resulting in a slightly modified flow from Figure 9, but the detection threshold setting still works.

[0065] 1, 3, and 5 show LMS-based adaptive filter controllers 120, 320, and 520, respectively, other methods and devices for adapting or creating optimal controllable W filters 118, 318, and 518 are possible. For example, in one or more embodiments, instead of an LMS adaptive filter controller, a neural network may be employed to create and optimize the W filter. In other embodiments, instead of an LMS adaptive filter controller, machine learning or artificial intelligence may be used to create the optimal W filter.

[0066] In the above specification, the inventive subject matter has been described with reference to certain exemplary embodiments. However, various modifications and changes may be made without departing from the scope of the inventive subject matter as set forth in the claims. The specification and drawings are exemplary rather than restrictive, and modifications are intended to be included within the scope of the inventive subject matter. Thus, the scope of the inventive subject matter should be determined by the claims and their legal equivalents, and not merely by the examples described.

[0067] For example, the steps recited in any method or process claim may be performed in any order and are not limited to the particular order present in the claims. Equations may be implemented in conjunction with filters to minimize the effects of signal noise. Additionally, the components and / or elements recited in any apparatus claim may be assembled or otherwise operatively configured in various permutations and therefore are not limited to the particular configuration recited in the claims.

[0068] Those skilled in the art will appreciate that functionally equivalent processing steps can be undertaken in either the time domain or the frequency domain. Thus, although not explicitly described for each signal processing block in the figures, particularly in Figures 1-3, signal processing may be performed in either the time domain, the frequency domain, or a combination thereof. Moreover, although various processing steps have been described in terms of exemplary digital signal processing, equivalent steps may be performed using analog signal processing without departing from the scope of the present disclosure.

[0069] Benefits, advantages, and solutions to problems have been described above with respect to specific embodiments. However, any benefit, advantage, solution to a problem, or any element that can enable or make more pronounced any particular benefit, advantage, or solution, is not to be construed as a critical, required, or essential feature or component of any or all of the claims.

[0070] The terms "comprise," "comprises," "comprising," "having," "including," "includes," or any variation thereof, are intended to refer to a non-exclusive inclusion, such that a process, method, article, composition, or apparatus that includes a list of elements may include not only those elements listed, but also other elements not expressly listed or inherent in such process, method, article, composition, or apparatus. Other combinations and / or modifications of the above-described structures, arrangements, applications, proportions, elements, materials, or components used in the practice of the inventive subject matter, besides those not specifically listed, may be varied without departing from the general principles thereof or may otherwise be specifically adapted to particular environments, manufacturing specifications, design parameters, or other operating requirements.

Claims

1. 1. A method for controlling stability in an active noise cancellation (ANC) system, the method comprising: receiving a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting an interior soundscape of the vehicle cabin; adjusting a nominal threshold for detecting diffusion of an ANC system based on the sensor signal to obtain an adjusted threshold; receiving a noise immunity signal output from a controllable filter, the noise immunity signal being indicative of noise immunity to be radiated from a speaker into the vehicle cabin; calculating a parameter based on an analysis of at least a portion of the noise immune signal; modifying a characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold; A method comprising:

2. The parameter is a first parameter, and the method further comprises: receiving an error signal from a microphone located in the vehicle cabin; Calculating a second parameter based on at least a portion of the analysis of the error signal; and modifying the characteristic of the controllable filter in response to the second parameter exceeding the adjusted threshold or in response to both the first parameter and the second parameter exceeding the adjusted threshold; The method of claim 1 further comprising:

3. The method of claim 1 or claim 2, wherein the parameter is the amplitude of the noise-resistant signal at one or more frequencies.

4. 3. The method of claim 1 or claim 2, wherein the nominal threshold is a predetermined static threshold programmed into the ANC system under nominal operating conditions.

5. The method of claim 1 or claim 2, wherein the sensor signals received from vehicle sensors include noise signals received from a vibration sensor.

6. The method of claim 1 or claim 2, wherein the sensor signals received from vehicle sensors include engine torque signals.

7. 3. The method of claim 1 or claim 2, wherein the sensor signals received from vehicle sensors are indicative of at least one of vehicle speed, engine speed, and accelerator pedal position.

8. Adjusting the nominal threshold based on the sensor signal comprises: retrieving a threshold adjustment value from a lookup table based on a short-term average of the sensor signal; modifying the nominal threshold value by the threshold adjustment value to obtain the adjusted threshold value; The method of claim 1 or claim 2, comprising:

9. The method of claim 1 or claim 2, wherein modifying a characteristic of the controllable filter comprises deactivating at least one of the ANC system and the controllable filter.

10. 3. The method of claim 1 or claim 2, wherein modifying the characteristics of the controllable filter comprises resetting filter coefficients of the controllable filter to zero and allowing the controllable filter to re-adapt.

11. The method of claim 1 or claim 2, wherein modifying a characteristic of the controllable filter comprises resetting filter coefficients of the controllable filter to a set of filter coefficient values ​​stored in a memory.

12. 3. The method of claim 1 or 2, wherein modifying a characteristic of the controllable filter comprises increasing a leakage value of an adaptive filter controller that controls an adaptive transfer characteristic of the controllable filter.

13. The method of claim 12 , further comprising: reducing the leakage value of the adaptive filter controller when the parameter falls below the adjusted threshold.

14. 1. An active noise cancellation (ANC) system, comprising: at least one controllable filter configured to generate a noise-resistant signal based on an adaptive transfer characteristic and a noise signal received from a sensor, the adaptive transfer characteristic of the at least one controllable filter being characterized by a set of filter coefficients; an adaptive filter controller including a processor and a memory programmed to adapt the set of filter coefficients based on the noise signal and an error signal received from a microphone located in the vehicle cabin; a diffusion controller in communication with at least the adaptive filter controller, the diffusion controller comprising: receiving sensor signals from vehicle sensors indicative of current vehicle operating conditions affecting the interior soundscape of the cabin; adjusting a dynamic threshold for detecting divergence of an ANC system based on the sensor signal; receiving the error signal from the microphone and calculating a parameter based on an analysis of at least a portion of the error signal; modifying a characteristic of the at least one controllable filter in response to the parameter exceeding the dynamic threshold; a diffusion controller including a processor and memory programmed to execute the An ANC system including:

15. The ANC system of claim 14 , wherein the parameter is an amplitude of the error signal at one or more frequencies.

16. The ANC system of claim 14 , wherein the sensor signals received from vehicle sensors include at least one of the noise signal and an engine torque signal.

17. 15. The ANC system of claim 14, wherein the characteristics of the at least one controllable filter are modified by the diffusion controller by resetting the filter coefficients of the at least one controllable filter to known states using different sets of filter coefficients stored in a memory.

18. 15. The ANC system of claim 14, wherein the characteristics of the at least one controllable filter are modified by the diffusion controller by increasing a leakage value of the adaptive filter controller.

19. 1. A computer program for active noise cancellation (ANC), the computer program, when executed by a processor, causing the processor to: receiving a sensor signal from a vehicle sensor indicative of a current vehicle operating condition affecting an interior soundscape of the vehicle cabin; adjusting a nominal threshold for detecting diffusion of an ANC system based on the sensor signal to obtain an adjusted threshold; receiving at least one of a noise immunity signal output from a controllable filter and an error signal output from a microphone located in the vehicle cabin, the noise immunity signal being indicative of noise immunity to be radiated from a speaker into the vehicle cabin; calculating a parameter based on an analysis of at least one of the noise immunity signal and the error signal; modifying an adaptive transfer characteristic of the controllable filter in response to the parameter exceeding the adjusted threshold; A computer program for causing a computer to carry out a method comprising:

20. Modifying the adaptive transfer characteristic of the controllable filter comprises: Detecting a spread frequency of the controllable filter; resetting the spread frequency of the controllable filter to zero, attenuating a filter coefficient at the spread frequency, or increasing a leakage value of an adaptive filter controller at the spread frequency; 20. The computer program of claim 19, comprising:

21. 20. The computer program product of claim 19, wherein modifying the adaptive transfer characteristic of the controllable filter comprises reducing a rate of change of the adaptive transfer characteristic.

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