Engine order cancellation optimized for drive mode

Abstract

Engine order cancellation (EOC) systems generate feedforward noise signals based on engine or other rotating shaft RPM and use those signals and an adaptively configured W filter to reduce SPL within the cabin by emitting anti-noise via speakers. One EOC system can include a drive mode detector for detecting different vehicle drive modes based on analysis of signals indicative of current vehicle operating conditions. Upon detection, the EOC system can adaptively adjust various tuning parameters of the EOC algorithm based on the current vehicle drive mode. The EOC system can also selectively target different sets of engine orders for noise cancellation based on which engine orders dominate during the drive mode, depending on the current vehicle drive mode.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of U.S. Provisional Application No. 62 / 869,247, filed July 1, 2019, the disclosure of which is hereby incorporated herein by reference in its entirety. Technical Field

[0003] This disclosure relates to engine order elimination, and more particularly, to optimizing engine order elimination and corresponding tuning parameters based on the detected vehicle drive mode. Background Technology

[0004] Active noise control (ANC) systems use feedforward and feedback structures to attenuate unwanted noise, adaptively removing unwanted noise within the listening environment (e.g., inside a vehicle cabin). ANC systems typically eliminate or reduce unwanted noise by generating canceling sound waves that cancel out the unwanted audible noise. Cancellation occurs when noise is combined with an "anti-noise" component that is substantially the same magnitude as the noise but opposite in phase to reduce the sound pressure level (SPL) at a point. In a vehicle cabin listening environment, potential sources of unwanted noise include the interaction between the engine, vehicle tires, and the road surface on which the vehicle travels, and / or sound emitted by vibrations from other parts of the vehicle. Therefore, unwanted noise varies with vehicle speed, road conditions, and operating status.

[0005] Engine Order Cancellation (EOC) systems are specific ANC systems implemented in vehicles to reduce unwanted in-vehicle noise levels originating from narrowband acoustic and vibration emissions from the vehicle's engine and exhaust system or other rotating drivetrain components. EOC systems generate feedforward noise signals based on the engine or other rotating shaft angular velocities (such as revolutions per minute (RPM)) and use those signals and adaptively configured W filters to reduce SPL within the cabin by emitting anti-noise via loudspeakers.

[0006] EOC systems are typically least mean square (LMS) adaptive feedforward systems that continuously adjust the W filter based on both RPM inputs from sensors mounted to the drive shaft and signals from microphones located at various positions within the vehicle cabin. When tuning the EOC system, engineers begin with a single run of data at full throttle (WOT). By considering the contrasting RPMs of sound measured at the occupant's ears, the dominant engine order is identified. For each engine order, a single value is identified for each of the key EOC algorithm parameters. These EOC algorithm parameters typically include step size, stability SPL threshold, leakage, gain, etc. Summary of the Invention

[0007] Various aspects of the present disclosure relate to optimizing engine order cancellation (EOC) parameters in an EOC system based on a current vehicle drive mode. In one or more illustrative implementations, a method for dynamically tuning an EOC system based on a vehicle drive mode is provided. The method can include the steps of storing a set of EOC tuning parameters for each of a plurality of vehicle drive modes in a memory, each set of EOC tuning parameters being different between vehicle drive modes; applying a first set of EOC tuning parameters corresponding to a current vehicle drive mode; receiving at least one signal indicative of a vehicle operating condition; detecting a change in the current vehicle drive mode based on the at least one signal; and applying a second set of EOC tuning parameters in response to the change in the current vehicle drive mode.

[0008] Implementations can include one or more of the following features. The step of applying a first set of EOC tuning parameters corresponding to the current vehicle drive mode can include selecting the first set of EOC tuning parameters corresponding to a first vehicle drive mode from a memory when the first vehicle drive mode is the current vehicle drive mode; and employing the first set of EOC tuning parameters. Additionally, the step of applying a second set of EOC tuning parameters in response to the change in the current vehicle drive mode can include selecting the second set of EOC tuning parameters corresponding to a second vehicle drive mode from a memory in response to a change in the current vehicle drive mode from the first vehicle drive mode to the second vehicle drive mode; and employing the second set of EOC tuning parameters during EOC when the current vehicle drive is the second vehicle drive mode.

[0009] The set of EOC tuning parameters for each of the plurality of vehicle drive modes can include at least a step size, a leakage value, a gain applied to one of an anti-noise signal and a noise signal, or a sound pressure level threshold applied to an error signal. The signal indicative of a vehicle operating condition can be indicative of a cruise control engagement. Alternatively, the signal indicative of a vehicle operating condition can be indicative of one of a revolutions per minute (RPM), a speed, and a torque. Accordingly, detecting the change in the current vehicle drive mode based on the at least one signal can include determining a rate of change of at least one of the RPM, the speed, and the torque; and comparing the rate of change to one or more predetermined thresholds.

[0010] The plurality of vehicle drive modes can include at least a throttle partially open drive mode and a constant speed drive mode. The plurality of vehicle drive modes can also include a throttle fully open drive mode.

[0011] One or more additional embodiments of the present disclosure relate to an engine order cancellation (EOC) system. The EOC system can include at least one controllable filter configured to generate an anti-noise signal based on an adaptive transfer characteristic and a noise signal received from a noise signal generator. The adaptive transfer characteristic of the at least one controllable filter can be characterized by a set of filter coefficients. The EOC system can also include an adaptive filter controller including a processor and a memory programmed to: store a set of EOC tuning parameters for each of a plurality of vehicle drive modes, each set of EOC tuning parameters differing between vehicle drive modes; apply the set of EOC tuning parameters corresponding to a current vehicle drive mode; and adapt the set of filter coefficients based on the noise signal and an error signal received from a microphone located in a passenger compartment of a vehicle. The EOC system can also include a drive mode detector in communication with at least the adaptive filter controller. The drive mode detector can include a processor and a memory programmed to: receive at least one signal indicative of a vehicle operating condition; analyze the at least one signal to determine the current vehicle drive mode; and transmit a drive mode signal indicative of the current vehicle drive mode to the adaptive filter controller.

[0012] Implementations can include one or more of the following features. The drive mode detector can transmit the drive mode signal in response to detecting a change in the current vehicle drive mode. The set of EOC tuning parameters for each of the plurality of vehicle drive modes can include at least one of a step size and a leakage value. The plurality of vehicle drive modes can include at least a throttle partially open drive mode and a constant speed drive mode. The at least one signal indicative of a vehicle operating condition can be indicative of one of revolutions per minute (RPM), speed, and torque. The at least one signal indicative of a vehicle operating condition can be indicative of a transmission gear state.

[0013] One or more additional embodiments of the present disclosure relate to a method for dynamically targeting dominant engine orders as active noise cancellation in an engine order cancellation (EOC) system based on a vehicle drive mode. The method can include: storing a set of dominant engine orders for each of a plurality of vehicle drive modes, each set of dominant engine orders differing between vehicle drive modes; receiving at least one signal indicative of a vehicle operating condition; detecting a current vehicle drive mode based on the at least one signal; selecting the set of dominant engine orders corresponding to the current drive mode; and applying noise cancellation to each engine order in the set of dominant engine orders corresponding to the current vehicle drive mode.

[0014] Implementations can include one or more of the following features. The method can also include selecting a different set of dominant engine orders in response to detecting a change in the current vehicle drive mode. Each of the plurality of vehicle drive modes can correspond to a different state of a vehicle transmission. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a block diagram of a vehicle having an engine order cancellation (EOC) system in accordance with one or more embodiments of the present disclosure;

[0016] Figure 2 is a block diagram of an EOC system including a drive mode detector in accordance with one or more embodiments of the present disclosure; Figure 1 a detailed view of the noise signal generator depicted;

[0017] Figure 3 is an exemplary plot showing sound pressure level (SPL) versus engine order in several different vehicle drive modes;

[0018] Figure 4 is a schematic block diagram representing an EOC system including a drive mode detector in accordance with one or more embodiments of the present disclosure;

[0019] Figure 5 is an exemplary flowchart depicting a method for optimizing EOC tuning parameters based on vehicle drive mode in accordance with one or more embodiments of the present disclosure;

[0020] Figure 6 is an exemplary table showing EOC tuning parameters that can be applied for a given drive mode or scenario in accordance with one or more embodiments of the present disclosure;

[0021] Figure 7 is an exemplary plot showing relative SPL versus engine order measured for a vehicle in two different drive modes; and

[0022] Figure 8 is an exemplary table showing dominant engine orders for a given drive mode or scenario that can be targeted as EOC in accordance with one or more embodiments of the present disclosure. DETAILED DESCRIPTION

[0023] Detailed embodiments of the application are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the application that can be embodied in various and alternative forms. The Figures are not necessarily to scale; some features can be exaggerated or minimised for purpose of clarity. Specific structural and functional details disclosed herein are not to be interpreted as limiting, but only as a representative basis for teaching one skilled in the art to employ the present application in various and alternative forms.

[0024] 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 a variety of programming languages and / or technologies. Generally, a processor, such as a microprocessor, receives instructions, for example, from memory, computer-readable media, etc., and executes the instructions. A processing unit includes a non-transitory computer-readable storage medium that is capable of executing instructions of a software program. The computer-readable storage medium can be, but is not limited to, an electronic storage, a magnetic storage, an optical storage, an electromagnetic storage, a semiconductor storage, or any suitable combination thereof.

[0025] Figure 1 An engine order cancellation (EOC) system 100 for a vehicle 102 is shown having a noise signal generator 108. The noise signal generator 108 can generate a reference noise signal X(n) corresponding to an audible engine order noise originating from each engine order of a vehicle engine and exhaust system 110. The EOC system 100 can be integrated with a feedforward and feedback active noise control (ANC) framework or system 104 that generates an anti-noise by adaptively filtering the noise signal X(n) from the noise signal generator 108 using one or more microphones 112. The anti-noise signal Y(n) can then be played through one or more loudspeakers 124. S(z) represents the transfer function between a single loudspeaker 124 and a single microphone 112. Although Figure 1 A single noise signal generator 108, microphone 112, and loudspeaker 124 are shown for simplicity, but it should be noted that a typical EOC system can include multiple engine order noise signal generators 108, in addition to multiple loudspeakers 124 (e.g., 4 to 8) and microphones 112 (e.g., 4 to 6).

[0026] Reference is made to Figure 2 The noise signal generator 108 can include an RPM sensor 242 that can provide an RPM signal 244 (e.g., a square wave signal) indicative of the rotation of an engine drive shaft or other rotating shaft, which is indicative of the engine speed. In some embodiments, the RPM signal 244 can be obtained from a vehicle network bus (not shown). Because the emitted engine orders are proportional to the drive shaft RPM, the RPM signal 244 represents the frequencies generated by the driveline including the engine and exhaust system. Therefore, the signal from the RPM sensor 242 can be used to generate a reference engine order signal corresponding to each of the engine orders of the vehicle. Thus, the RPM signal 244 can be used in conjunction with a lookup table 246 of RPM versus engine order frequencies.

[0027] More specifically, the look-up table 246 can be used to convert the RPM signal 244 into one or more engine order frequencies. The frequency of a given engine order at the sensed RPM, retrieved from the look-up table 246, can be supplied to an oscillator or frequency generator 248, generating a sinusoidal wave at the given frequency. This sinusoidal wave represents the noise signal X(n) indicative of the engine order noise of the given engine order. When there can be multiple engine orders, the EOC system 100 can include multiple noise signal generators 108 and / or frequency generators 248 for generating a noise signal X(n) for each engine order based on the RPM signal 244.

[0028] An engine rotating at a rate of 1800 RPM can be considered to be running at 30 Hz (1800 / 60 = 30), which corresponds to the fundamental or first engine order frequency. For a four cylinder engine, the crank fires two cylinders per revolution, resulting in a 60 Hz (30 x 2 = 60) dominant frequency that defines the sound of a four cylinder engine at 1800 RPM. In a four cylinder engine, this is also referred to as the "second engine order" because the frequency is twice that of the frequency of the engine rotational rate. At 1800 RPM, other dominant engine orders for a four cylinder engine are the fourth order at 120 Hz and the sixth order at 180 Hz. In a six cylinder engine, the firing frequency results in a dominant third engine order; in a V-10, the fifth engine order dominates. As the RPM increases, the firing frequency rises proportionally. As previously described, the EOC system 100 can include multiple noise signal generators 108 and / or frequency generators 248 for generating a noise signal X(n) for each engine order based on the RPM signal 244. Further, the ANC framework 104 (e.g., controllable filter 118, adaptive filter controller 120, secondary path filter 122) within the EOC system 100 can be scaled to reduce or cancel each of these multiple engine orders. For example, an EOC system that reduces the second, fourth, and sixth engine orders requires three of the ANC framework or subsystems 104, one for each engine order. Certain system components, such as the error microphone 112 and anti-noise loudspeaker 124, can be common to all systems or subsystems.

[0029] Referring again to Figure 1The characteristic frequencies of the noise and vibrations originating from the engine and exhaust system 110 can be sensed by one or more of the sensing sources in the RPM sensor 242, which can be optionally housed within the noise signal generator 108. The noise signal generator 108 can output a noise signal X(n) that is a signal representative of a particular engine order frequency. As previously described, the noise signal X(n) can be at different engine orders of interest. Additionally, these noise signals can be used individually or can be combined in various ways known to those skilled in the art. The noise signal X(n) can be filtered by the secondary path filter 122 with a modeled transfer characteristic S'(z) that estimates the secondary path (i.e., the transfer function between the anti-noise speaker 124 and the error microphone 112).

[0030] Drive line noise (e.g., engine, drive shaft, or exhaust noise) is mechanically and / or acoustically transmitted into the passenger cabin and received by one or more microphones 112 inside the vehicle 102. The one or more microphones 112 can be located, for example, in the headrest 114 of the seat 116, as shown. Figure 1

[0031] The microphone 112 can output an error signal e(n) that is representative of the noise present in the vehicle 102 cabin as detected by the microphone 112. In the EOC system 100, the adaptive transfer characteristic W(z) of the controllable filter 118 can be controlled by the adaptive filter controller 120. The adaptive filter controller 120 can operate based on the error signal e(n) and the noise signal X(n), which is optionally filtered by the filter 122 with the modeled transfer characteristic S'(z), according to the known least mean square (LMS) algorithm. The controllable filter 118 is often referred to as the W filter. The LMS adaptive filter controller 120 can provide a sum cross-spectrum configured to update the transfer characteristic W(z) filter coefficients based on the error signal e(n). The process that results in the adaptation or updating of W(z) that leads to improved noise cancellation is referred to as convergence. Convergence refers to the W filter being produced that minimizes the error signal e(n), which is controlled by the step size that governs the rate of adaptation for a given input signal. The step size is a scaling factor that determines the speed at which the algorithm will converge to minimize e(n) by limiting the magnitude change of the W filter coefficients with each update of the controllable W filter 118.

[0032] ​An anti-noise signal Y(n) can be generated by an adaptive filter formed by controllable filter 118 and adaptive filter controller 120 based on the identified transfer characteristic W(z) and a combination of the noise signal or noise signal X(n). The anti-noise signal Y(n) ideally has a waveform such that when played through loudspeaker 124, an anti-noise is generated near the ear of the occupant and microphone 112 that is substantially opposite in phase and identical in magnitude to the engine order noise audible to the occupant of the vehicle cabin. The anti-noise from loudspeaker 124 can combine with the engine order noise near microphone 112 in the vehicle cabin, thereby reducing the sound pressure level (SPL) caused by the engine order noise at that location. In certain embodiments, EOC system 100 can receive sensor signals from other acoustic sensors in the passenger cabin, such as acoustic energy sensors, acoustic intensity sensors, or acoustic particle velocity or acceleration sensors, to generate the error signal e(n).

[0033] Vehicles typically have other shafts that rotate at other rates relative to the engine RPM. For example, the drive shaft rotates at a rate related to the engine at the current gear ratio set by the transmission. The drive shaft can not have perfect rotational balance, as the drive shaft can have some degree of eccentricity. The eccentricity causes rotational imbalances when rotating, which exert oscillating forces on the vehicle, and these vibrations can result in audible acoustic sounds in the passenger cabin. Other rotating shafts that rotate at different rates than the engine include axles or bridges, which rotate at rates set by the gear ratios in their differentials. In certain embodiments, noise signal generator 108 can have RPM sensors on different rotating shafts, such as the drive shaft or axles.

[0034] While vehicle 102 is in operation, processor 128 can collect and optionally process data from RPM sensors 242 in noise signal generator 108, as well as microphone 112, to build a database or map containing data and / or parameters to be used by vehicle 102. The collected data can be stored locally at storage 130 or in the cloud for future use by vehicle 102. Examples of the types of data related to EOC system 100 that can be stored locally at storage 130 include, but are not limited to, RPM history, microphone frequency spectrum or time-dependent signals, microphone-based acoustic performance data, drive mode-based EOC tuning parameters, and dominant engine orders, among others. Additionally, processor 128 can analyze the RPM sensor and microphone data and extract key features to determine a set of parameters to be applied to EOC system 100. The set of parameters can be selected upon triggering by an event. In one or more embodiments, processor 128 and storage 130 can be integrated with one or more EOC system controllers, such as adaptive filter controller 120.

[0035] Figure 1 The depicted simplified EOC system schematic shows one secondary path between each loudspeaker 124 and each microphone 112 represented by S(z). As previously mentioned, an EOC system typically has multiple loudspeakers, microphones, and noise signal generators. Thus, a 6-loudspeaker, 6-microphone EOC system would have a total of 36 secondary paths (i.e., 6 x 6). Correspondingly, a 6-loudspeaker, 6-microphone EOC system likewise can have 36 S'(z) filters (i.e., secondary path filters 122) that estimate the transfer function of each secondary path. As Figure 1 As shown, an EOC system also would have one W(z) wave filter (i.e., controllable filter 118) between each noise signal X(n) from a noise signal generator 108 and each loudspeaker 124. Thus, a 5-noise signal generator, 6-loudspeaker EOC system can have 30 W(z) filters. Alternatively, a 6-frequency generator 248, 6-loudspeaker EOC system can have 36 W(z) filters.

[0036] As previously stated, the EOC system can be tuned starting from a single wide open throttle (WOT) data logging session. By considering the sound recorded at the passenger's ear versus RPM, the dominant engine orders are identified. For each engine order, a single value for each of the main EOC algorithm parameters is typically identified. These EOC algorithm parameters typically include step size, stability SPL threshold, leakage, gain, etc. As previously described, the step size is a scaling factor that determines the speed at which the algorithm will converge to minimize the error signal e(n) by limiting the magnitude change of the W filter coefficients with each update based on the controllable W filter. In adaptive LMS filtering, leakage refers to the step in the W filter update process where the previous W filter is reduced by multiplying it by a term less than 1. The W filter is adapted by adding a term based on the error signal and the step size to the previous W filter. In adding this update term, the previous W filter can also be reduced by multiplying it by a term less than 1. Using leakage is the process of multiplying the previous W filter magnitude by a coefficient less than 1 in the adaptation process. The stability SPL threshold refers to a threshold applied to the error microphone output signal (i.e., the error signal e(n)) above which the EOC system is at least temporarily disabled. Finally, the gain refers to an increase or decrease in the output magnitude of the frequency generator 248 or any component within the noise signal generator 108 that results in an increase or decrease in the X(n) magnitude. In an alternative embodiment, the gain can also refer to an increase or decrease in the anti-noise signal Y(n) magnitude. In another alternative embodiment, the gain can refer to an increase or decrease in the controllable filter 118 magnitude. A possible benefit of adjusting the gain of the anti-noise signal Y(n) or the noise signal X(n) based on the drive mode is to adapt more quickly to a new drive mode. For example, when moving from a higher engine noise drive mode to a lower engine noise drive mode, decreasing the gain of the anti-noise signal Y(n) can assist the W filter to adapt more quickly to the new, lower desired anti-noise level compared to relying only on the W filter update process controlled by the step size.

[0037] The single value for each of these algorithm parameters at each engine order does not provide the best EOC experience for all vehicle drive scenarios (e.g., WOT vs. constant speed drive). Furthermore, the dominant engine orders during a WOT event are not always the same as the dominant orders during idle and other vehicle drive modes. One or more embodiments of the present disclosure involve selecting the optimal set of EOC algorithm parameters based on the current vehicle operating conditions or drive mode.

[0038] During a WOT event, the engine or other shaft RPM changes rapidly over time, and thus the frequency of the engine orders also changes rapidly. In most cases, WOT conditions exhibit the highest internal noise levels due to higher torque requirements compared to constant speed or throttle partially open driving scenarios. In order for the EOC to maintain convergence (i.e., for the EOC system to continue reducing engine order noise) when the engine order frequency is changing rapidly or when the engine noise level is high, typically large step sizes are required. In order to maintain stability (i.e., avoid divergence) using relatively large step sizes at rapidly changing frequencies, additional leakage should also be used.

[0039] However, when the vehicle is operating in steady state, the RPM is essentially constant, and the sound characteristics of the vehicle change. In this case, the step size can be reduced in order to improve noise cancellation, since an LMS based EOC system will converge more accurately to the minimum sound energy with small step sizes. Additionally, small step sizes can be employed to reduce the audibility of "ANC swing" or "ANC wobble," where the LMS algorithm oscillates between several W filters (magnitude and phase values) resulting in audible and undesirable fluctuations in cancellation level. Furthermore, such small step sizes do not require high leakage values to maintain stability. Therefore, leakage can be reduced or eliminated to further improve EOC cancellation depth, making the vehicle interior quieter. Thus, aggressive leakage and step size can provide optimal EOC during WOT, while non-aggressive leakage and step size can provide optimal EOC during steady state.

[0040] Any single set of EOC tuning parameters will naturally result in compromised noise cancellation performance or stability during all driving conditions. Employing driving scenario dependent EOC parameters can also simplify certain EOC tuning. For example, a known corner case is divergence of the EOC algorithm after the vehicle has operated at highway speeds (i.e., steady state RPM) for a long period of time. By providing a separate set of tuning parameters for this driving mode, no compromises need to be made, and divergence avoidance or stability can be improved.

[0041] There are more possible driving scenarios than just WOT and constant speed. Intermediate values of the tuning parameters can be possible for intermediate or partially open throttle (POT) positions. Driving modes can be detected and labeled by monitoring the time history of RPM, speed, and torque, and possibly additional inputs from the vehicle controller area network (CAN) bus or other systems. Non-limiting examples of various driving modes that can be detected and labeled can include: WOT, towing, steady state at various speeds (e.g., 75 mph, 60 mph, and 30 mph), cylinder deactivation, coasting, partially open throttle (POT), idle, etc. Figure 3 is a graph showing SPL versus engine order in the passenger cabin under several of the above-mentioned driving modes to demonstrate the effect of driving mode on engine order noise in the passenger cabin.

[0042] In addition to monitoring the time history of RPM, speed, and torque, monitoring the cruise control engagement or transmission gear state is another possible way to identify the vehicle drive mode. For example, a WOT (wide open throttle) condition can be detected by the rate of change of RPM, a sudden downshift of multiple gears, the rate of fuel flow into the engine (cylinders), the rate of change of vehicle speed, the pedal position, the rate of change of engine torque output, the value of vehicle acceleration, etc. A POT (partially open throttle) condition is a lower threshold of the same quantities listed above for WOT.

[0043] Towing can be detected by elevated engine torque at each RPM relative to "normal driving." For example, a range of engine output torque for "normal driving" can be stored. If the torque exceeds this value range, a "towing" mode can be identified. Although not specifically mentioned, the "inclined driving" mode (e.g., when driving uphill) is similar to the towing mode in both detection methods and ideal EOC parameter selection. These two modes can be distinguished by, for example, input from an angular position sensor that indicates the angle of the vehicle relative to the horizontal.

[0044] Constant speed driving mode can be detected by a zero or negligible rate of change of RPM for a certain duration. Cylinder deactivation can be detected by CAN messages or by sound detection of different engine orders. For example, when an 8-cylinder engine deactivates 2 cylinders, it emits the engine orders of a 6-cylinder engine (i.e., third, sixth, and ninth engine orders) instead of the second, fourth, and sixth engine orders emitted by an 8-cylinder engine. Coasting driving mode can be detected by a negative rate of change of RPM or application of the brakes within a certain force tolerance.

[0045] Idle condition can be identified by the engine operating at a constant speed between a cold idle RPM and a warm idle RPM. An alternative or supplementary identification method is simply detecting that the vehicle's engine is on, but the vehicle speed is substantially zero. The transmission gear state can also assist in the identification of idle, however, the gear state can be park or idle drive.

[0046] Figure 4 is a schematic block diagram representing an EOC system 400 in accordance with one or more embodiments of the present disclosure. As understood by one skilled in the art, the EOC system 400 can be a Filter-X Least Mean Square (FX-LMS) EOC system. Similar to the EOC system 100, the EOC system 400 can include elements 408, 410, 412, 418, 420, 422, and 424 that operate in accordance with elements 108, 110, 112, 118, 120, 122, and 124, respectively, discussed above. Figure 4 Also shown is a block diagram of an EOC system 400 in accordance with one or more embodiments of the present disclosure. Figure 1The primary path P(z) and secondary path S(z) are described. Because the engine order noise is narrowband, the error microphone signal e(n) can be filtered by a bandpass filter 450 before being passed into the LMS-based adaptive filter controller 420. In one embodiment, the noise signal X(n) output by the noise signal generator 408 is bandpass filtered using the same bandpass filter parameters. Because the frequencies of the various engine orders are different, each engine order can have its own bandpass filter with different high pass filter corner frequencies and low pass filter corner frequencies. The number of frequency generators and corresponding noise cancellation components will ultimately vary based on the number of engine orders for which a reduction level is desired for a particular vehicle.

[0047] To detect the vehicle drive mode, the EOC system 400 can also include a drive mode detector 462. The drive mode detector 462 can include a processor and memory (not shown), such as the processor 128 and storage 130, that are programmed to identify and flag various drive modes or scenarios, such as those described previously. Again, this drive mode detection can involve monitoring the time history of RPM, speed, and torque, cruise control engagement, transmission gear state, etc. The drive mode detector 462 can be a dedicated controller for detecting the vehicle drive mode, or can be integrated with another controller or processor in the EOC system 400, such as the LMS adaptive filter controller 420. Alternatively, the drive mode detector 462 can be integrated into another controller or processor within the vehicle 102 separate from the other components in the EOC system.

[0048] The drive mode detection scheme can result in a particular drive mode being identified after any period of time in which the pilot signal is analyzed. For example, the drive mode can be identified after only 10 milliseconds of data being analyzed, and improved detection can occur after 100 milliseconds. Further, the drive mode detection can be employed continuously at regular time intervals and / or in response to particular events. Such events can include, but are not limited to, receiving a CAN message, identifying an input that cruise control is engaged, identifying an input that the transmission state has changed from drive to park, receiving a signal indicating that the accelerator pedal has been fully depressed, etc.

[0049] Figure 5is an exemplary flowchart depicting a method 500 for optimizing EOC tuning parameters based on vehicle drive mode according to one or more embodiments of the present disclosure. At step 510, sensor data can be acquired, including the types listed above. For example, the system can monitor or receive signals indicative of vehicle operating conditions. As stated above, this can involve monitoring the time history of RPM, speed, and torque, pedal position, fuel flow rate, as well as signals indicative of cruise control engagement, transmission gear state, etc. At step 520, the data can be analyzed and statistical results calculated. For example, the drive mode detector 462 or another controller can calculate the rate of change of RPM, the rate of change of vehicle speed, or the rate of change of torque output of the engine. At step 530, the resulting statistical results can be compared to predetermined thresholds related to speed, pedal position, torque, etc. For example, a rate of change of RPM, speed, or torque between a first lower threshold and a second upper threshold can indicate a POT drive mode, while a rate of change above the second upper threshold can indicate a WOT drive mode. Additionally, CAN messages can optionally be received and compared to a list of messages identifying particular drive modes.

[0050] The drive mode detector 462 can determine whether a drive mode has changed, as provided at step 540. If the drive mode has not changed, there is no need to alter the parameters, and as shown, new sensor data can be acquired at step 510. However, if a new drive mode is detected at step 540, the drive mode detector 462 can transmit a signal 466 indicative of the current drive mode or scenario to the adaptive filter controller 420. In response to the signal 466, the adaptive filter controller 420 can modify one or more of the LMS algorithm parameters, as provided at step 550. For example, the step size and leakage can be adjusted to appropriate values depending on the current rate of change of vehicle RPM.

[0051] Figure 6is an example table 600 showing EOC tuning parameters for each driving scenario. The four main tuning parameters described previously can be intelligently adjusted based on the driving mode to maximize EOC system performance. As shown, a discrete state (e.g., high / low or high / medium / low) can be assigned to each tuning parameter based on the detected driving mode. For each tuning parameter, a corresponding value associated with each state can be applied in the EOC algorithm by the adaptive filter controller 420. Alternatively, the table 600 can include specific numerical values for each tuning parameter to further optimize the EOC based on various driving modes. These specific numerical values can be predetermined and can be stored in the memory 130. For example, when moving from a low step size driving mode to a medium step size driving mode, the step size can be increased by a predetermined amount, such as 10 dB or 20 dB. When moving from a medium step size driving mode back to a low step size driving mode, the step size can be decreased by a predetermined amount, such as 10 dB or 20 dB. In one embodiment, when moving from a high leakage driving mode to a low leakage driving mode, the leakage value can be decreased by a predetermined amount, such as 50% or 73%. In another embodiment, when moving from a high stability SPL threshold to a low stability SPL threshold, the SPL threshold can be decreased by a predetermined amount, such as 10 dB.

[0052] In one or more embodiments, when a new driving mode (or shift) is identified (i.e., a change in driving mode is detected), the step size can initially be increased for a short duration to reduce the adaptation time in this new driving mode. After this short duration, the main tuning parameters (including the step size) can be adjusted according to the table 600 in Figure 6

[0053] In addition to changing the EOC tuning parameters, engine order noise from dominant engine orders can also be reduced based on the driving and / or transmission mode. Due to processing power and other EOC system limitations, the EOC system 400 and its corresponding algorithm can be limited in the number of engine order noise magnitudes that can be reduced. The number of machine code instructions that a computer can process while executing a "standard" program is measured in MIPS (millions of instructions per second). Thus, for example, for a given MIPS and memory limit, the EOC algorithm can only be able to reduce the magnitudes of five engine orders. Elimination of more engine orders would require additional digital signal processing (DSP) resources, which can not be available or desirable. However, the five dominant engine orders can be different in different driving or transmission modes.

[0054] Transmission modes can include, but are not limited to, sport, economy (ECO), snow, tow, baja, rock, and track. Transmission modes change the torque request on the engine and the shift points, thereby changing the engine order levels. Figure 7 ​is an exemplary plot showing the relative SPL versus engine order measured in one vehicle in two drive modes. The measurements in the first drive mode were taken with the vehicle stationary and the engine at warm idle speed. The measurements in the second drive mode were taken during WOT. As Figure 7 shown, in these two vehicle drive modes, the five dominant engine orders are different. Furthermore, even the single most dominant engine order is different between these two drive modes. Between these two drive modes, two of the five most dominant engine orders differ by more than 15 dB.

[0055] Therefore, to optimize the EOC without dedicating DSP resources to canceling all engine orders, the EOC system 400 and corresponding algorithm can target the dominant engine orders in each drive mode, not just the dominant engine orders in WOT. If the EOC system can target five engine orders for noise cancellation, the algorithm can select the five most dominant engine orders to target based on the drive or transmission mode. An additional benefit of using gear or transmission state to identify the vehicle drive mode is related to driveline cancellation. As generally understood, certain acoustic sound sources in the passenger cabin are caused by vibrations from rotational imbalance of the drive shaft. For each transmission gear, the drive shaft RPM is related to the engine RPM by a different factor (due to different gear ratios). Therefore, for each gear, the EOC algorithm needs a different set of RPM versus frequency lookup tables to cancel the driveline-induced noise in the vehicle. Similarly, for each drive state, a different set of RPM versus frequency lookup tables can be employed, so the EOC algorithm targets the dominant engine orders in each drive mode.

[0056] In view of the foregoing, the identification of the drive mode can result in not only loading the ideal adaptation parameters that result in optimal noise cancellation of the particular engine orders, but also loading the list of dominant engine orders for that particular new drive mode. Similar to Figure 6 , Figure 8 is an exemplary table 800 showing the dominant engine orders for a particular engine relative to each drive scenario. This results in a generally lower overall noise floor in the vehicle, further optimizing the noise cancellation performance experienced by the vehicle occupants.

[0057] While the foregoing describes exemplary implementations, these implementations are not intended to describe all possible forms of the present application. Rather, the words used in this specification are words of description, not limitation, and it is understood that various changes can be made without departing from the spirit and scope of the application. Additionally, features of various implementations described herein can be combined to form further implementations of the present application.

[0058] Although Figure 1 andFigure 4 LMS-based adaptive filter controllers 120 and 420 are shown, respectively, but other methods and apparatuses for adapting or generating optimal controllable W-filters 118 and 418 are possible. For example, in one or more embodiments, a neural network can be employed in place of an LMS adaptive filter controller to generate and optimize a W-filter. In other embodiments, machine learning or artificial intelligence can be used in place of an LMS adaptive filter controller to generate an optimal W-filter.

[0059] Those of ordinary skill in the art will appreciate that functionally equivalent processing steps can be performed in the time or frequency domain. Thus, although not explicitly stated for each signal processing block in the figures, signal processing can occur in the time domain, the frequency domain or a combination thereof. Additionally, although individual processing steps are illustrated using typical terminology of digital signal processing, equivalent steps can be performed using analog signal processing without departing from the scope of the present disclosure.

[0060] The terms “comprise,” “comprises,” “comprising,” “having,” “including,” “includes” or any variation thereof is intended to refer to a non-exclusive inclusion, such that a process, method, article, composition or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to 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 present inventive subject matter, in addition to those not specifically described above, can be varied or otherwise particularized, according to specific environments, manufacturing specifications, design parameters or other operating requirements, without departing from the general inventive concepts.

Claims

1. A method for dynamically tuning an engine order-based EOC elimination system based on vehicle driving modes, the method comprising: A set of EOC tuning parameters for each of a plurality of vehicle drive modes is stored in a memory. Each set of EOC tuning parameters differs between vehicle drive modes and is configured to tune the speaker output to cancel noise. The plurality of vehicle drive modes include at least one of a partially open throttle drive mode, a constant speed drive mode, a fully open throttle drive mode, a traction mode, and a tilt drive mode. The set of EOC tuning parameters for each of the plurality of vehicle drive modes includes a step size, a leakage value, a gain applied to either an anti-noise signal or a noise signal, and a sound pressure level threshold applied to an error signal. Apply the first set of EOC tuning parameters corresponding to the current vehicle drive mode; Receive at least one signal indicating the vehicle's operating condition; Detecting changes in the current vehicle driving mode based on at least one of the signals; and A second set of EOC tuning parameters is applied in response to the change in the current vehicle driving mode.

2. The method of claim 1, wherein: The first set of EOC tuning parameters corresponding to the current vehicle driving mode includes: When the first vehicle drive mode is the current vehicle drive mode, the first set of EOC tuning parameters corresponding to the first vehicle drive mode is selected from the memory; and The first set of EOC tuning parameters is used during EOC; and The application of the second set of EOC tuning parameters in response to the change in the current vehicle driving mode includes: In response to the change of the current vehicle driving mode from the first vehicle driving mode to the second vehicle driving mode, the second set of EOC tuning parameters corresponding to the second vehicle driving mode is selected from the memory; and When the current vehicle drive is the second vehicle drive mode, the second set of EOC tuning parameters is used during EOC.

3. The method of claim 1, wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes at least a step size.

4. The method of claim 1, wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes at least a leakage value.

5. The method of claim 1, wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes a gain applied to at least one of the noise immunity signal and the noise signal.

6. The method of claim 1, wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes at least a sound pressure level threshold applied to the error signal.

7. The method of claim 1, wherein the at least one signal indicates cruise control engagement.

8. The method of claim 1, wherein the at least one signal indicates one of revolutions per minute (RPM), speed, and torque.

9. The method of claim 8, wherein detecting the change in the current vehicle driving mode based on the at least one signal comprises: Determine the rate of change of at least one of RPM, speed, and torque; as well as The rate of change is compared with one or more predetermined thresholds.

10. An engine order-based EOC elimination system, comprising: At least one controllable filter is configured to generate an anti-noise signal based on an adaptive transfer characteristic and a noise signal received from a noise signal generator, wherein the adaptive transfer characteristic of the at least one controllable filter is characterized by a set of filter coefficients. An adaptive filter controller, comprising a processor and a memory, wherein the processor and memory are programmed to: A set of EOC tuning parameters is stored for each of a plurality of vehicle drive modes, each set of EOC tuning parameters being different between different vehicle drive modes and configured to tune the speaker output to cancel noise, wherein the plurality of vehicle drive modes include at least one of a partially open throttle drive mode, a constant speed drive mode, a fully open throttle drive mode, a traction mode, and a tilt drive mode, and wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes a step size, a leakage value, a gain applied to one of an anti-noise signal and a noise signal, and a sound pressure level threshold applied to an error signal; Apply the set of EOC tuning parameters corresponding to the current vehicle drive mode; and The set of filter coefficients are adjusted based on the noise signal and the error signal received from a microphone located in the vehicle's passenger compartment; and A driving mode detector, which communicates with at least the adaptive filter controller, includes a processor and memory programmed to: Receive at least one signal indicating the vehicle's operating condition; Analyze the at least one signal to determine the current vehicle driving mode; and The drive mode signal, indicating the current vehicle drive mode, is transmitted to the adaptive filter controller.

11. The system of claim 10, wherein the drive mode detector transmits the drive mode signal in response to detecting a change in the current vehicle drive mode.

12. The system of claim 10, wherein the set of EOC tuning parameters for each of the plurality of vehicle drive modes includes at least one of step size and leakage value.

13. The system of claim 10, wherein the at least one signal indicating vehicle operating conditions indicates one of revolutions per minute (RPM), speed, and torque.

14. The system of claim 10, wherein the at least one signal indicating vehicle operating conditions indicates transmission gear status.

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