This application is the U.S. national phase of PCT Application No. PCT/IB2016/056044 filed on Oct. 10, 2016, which claims priority to EP Patent Application No. 15190987.6 filed on Oct. 22, 2015, the disclosures of which are incorporated in their entirety by reference herein.
The disclosure relates to noise and vibration sensor arrangements for road-noise control systems, active road-noise control systems and noise and vibration measurement methods.
When driven on roads and other surfaces, land-based vehicles generate low-frequency noise known as road noise. Even in modem vehicles, cabin occupants may be exposed to road noise transmitted to the cabin through the structure (e.g., via tire-suspension-body-cabin paths) or through airborne paths (e.g., tire-body-cabin paths). Reducing the road noise experienced by cabin occupants is desirable. Active noise, vibration and harshness (NVH) control technologies, including active road-noise control (RNC) systems, can be used to reduce these noise components without modifying the vehicle's structure, as active vibration technologies do. However, active sound technologies for road-noise cancellation may require very specific noise and vibration (N&V) sensor arrangements throughout the vehicle structure in order to observe road noise and vibration signals.
An exemplary active road-noise control system includes a sensor arrangement configured to generate a first sense signal representative of at least one acceleration, motion and/or vibration that occurs at a first position on a vehicle body and a second sense signal representative of sound that occurs at a second position within the vehicle body. The system further includes an active road-noise control module configured to provide a noise-reducing signal by processing the first sense signal and the second sense signal according to a first mode of operation or a second mode of operation. At least one loudspeaker is disposed at a third position within the vehicle body and is configured to generate noise-reducing sound at the second position from the noise-reducing signal. The system further includes a malfunction detection module configured to evaluate the operational state of the sensor arrangement and to control the active road-noise control module so that the active road-noise control module operates in the first mode of operation when the sensor arrangement is in a proper operational state and in the second mode of operation when a malfunction of the sensor arrangement has been detected.
An exemplary active road-noise control method includes using a sensor arrangement to generate a first sense signal representative of at least one acceleration, motion and/or vibration that occurs at a first position on a vehicle body and a second sense signal representative of sound that occurs at a second position within the vehicle body. The method also provides a noise-reducing signal by processing the first sense signal and the second sense signal according to a first mode of operation or a second mode of operation. The method further includes generating noise-reducing sound within the vehicle body at the second position from the noise-reducing signal and evaluating the operational state of the sensor arrangement; it also includes controlling processing of the first sense signal and the second sense signal so that the first sense signal and the second sense signal are processed in the first mode of operation when the sensor arrangement is in a proper operational state and in the second mode of operation when a malfunction of the sensor arrangement has been detected.
The disclosure may be better understood by reading the following description of non-limiting embodiments attached to the drawings, in which like elements are referred to with like reference numbers, wherein below:
Noise and vibration sensors provide reference inputs to active RNC systems (e.g., multi-channel feed-forward active road-noise control systems) as a basis for generating the anti-noise that reduces or cancels road noise. Noise and vibration sensors may include acceleration sensors such as accelerometers, force gauges, load cells, etc. For example, an accelerometer is a device that measures proper acceleration. Proper acceleration is not the same as coordinate acceleration, which is the rate of change of velocity. Single- and multi-axis models of accelerometers are available for detecting the magnitude and direction of proper acceleration; they can be used to sense orientation, coordinate acceleration, motion, vibration and shock.
Airborne and structure-borne noise sources are monitored by the noise and vibration sensors in order to provide the highest possible road-noise reduction (cancellation) performance between 0 Hz and 1 kHz. For example, acceleration sensors used as input noise and vibration sensors may be disposed across the vehicle to monitor the structural behavior of the suspension and other axle components for global RNC. Above a frequency range that extends between 0 Hz and approximately 500 Hz, acoustic sensors that measure the airborne road noise may be used as reference control inputs. Furthermore, two microphones may be placed in the headrest in close proximity to the passenger's ears to provide an error signal or error signals in case of binaural reduction or cancellation. The feed-forward filters are tuned or adapted to achieve maximum noise reduction or noise cancellation at both ears.
A simple single-channel feed-forward active RNC system may be constructed. as shown in
Transfer characteristic W(z) of a controllable filter 108 is controlled by an adaptive filter controller 109. Adaptive filter controller 109 may operate according to the known least mean square (LMS) algorithm based on error signal e(n) and road-noise signal x(n), which is filtered with a transfer characteristic F′(z) by a filter 110, wherein W(z)=−P(z)/F(z). F′(z)=F(z), wherein F(z) represents the transfer function between a loudspeaker 111 and microphone 105. A signal y(n), which has a waveform inverse in phase to that of the road noise audible within the cabin, is generated by an adaptive filter 116; this is formed by at least controllable filter 108 and filter controller 109, which is based on the thus identified transfer characteristic W(z) and noise and vibration signal x(n). From signal y(n), a waveform inverse in phase to that of the road noise audible within the cabin is then generated by loudspeaker 111, which may be arranged in the cabin, to thereby reduce the road noise within the cabin. The exemplary system described above may employ an adaptive filter 107 with a straightforward single-channel feed-forward filtered-x LMS control structure, but other control structures (e.g., multi-channel structures with a multiplicity of additional channels, a multiplicity of additional noise sensors 112, a multiplicity of additional microphones 113 and/or a multiplicity of additional loudspeakers 114) may be applied as well.
The system shown in
The system shown in
In conventional active RNC systems, the malfunction of only one sensor can significantly deteriorate the system performance or even give rise to unwanted audible artifacts. However, it is challenging not only to detect a malfunction with a sufficient degree of certainty, but also to decide, upon successful detection, how to proceed with this information, aside from switching off the whole system. The determination of whether the mode of operation has changed and in what way it has changed may depend on information such as how many sensors exhibit malfunctions, which and what types of sensors exhibit malfunctions, what types of malfunctions are detected and what their specific effects on the system Malfunction detection modules 115 and 205 evaluate the operational statuses of the sensors, use their evaluations to determine if one or more of the sensors exhibit malfunctions and, optionally, determine how severe these malfunctions are.
An exemplary way to determine a malfunction is shown in
An exemplary test module may be operable to test each sensor per se with built-in self-test modules 304 described above in connection with
Acceleration sensors 402-407 generate sense signals in response to physical stimuli such as vehicle movement. Microprocessor 408 receives the sense signals representative of the accelerations that act on acceleration sensors 402-407 and that represent the noise and vibrations. Microprocessor 408 processes these inputs (e.g., in an algorithm) to decide whether each sense signal generated by acceleration sensors 402-407 can be considered valid or invalid. The algorithm may include a plausibility check of the sense signals. The plausibility may depend upon expected physical stimuli acting on acceleration sensors 402-407 or on any other appropriate sensors in the vehicle. For example, a mechanical impulse of a certain strength (e.g., mechanical impact on the tires when driving on a bumpy road) sensed by a multiplicity of sensors can be considered sufficient to stimulate all sensors. If one or more sensors do not respond to such stimuli, it appears as though this sensor or these sensors have malfunctioned.
In yet another exemplary sensor, the sensor sensitivity may be used as a fault indicator. Above a certain vehicle speed (e.g., 80 km/h), the road vibrations are sufficient to generate 1 g of vibration on the chassis so that an evaluation module can compare the output of the sensor to a stored sensitivity value of the sensor, which represents the output of a sensor at the certain speed.
Another way to detect malfunctioning sensors includes calculating a damped integration of each sense signal. The damped integration entails integrating the respective sense signal to produce an integrated value and subtracting an offset value at each iteration step to produce a damped value. The offset value is preset to correspond to expected normal driving conditions(e.g., from collected driving data over a variety of terrains, driving conditions and specified sensor tolerances). Microprocessor 408 may compare the damped integration to a fixed threshold value. If the damped integration exceeds the threshold value, microprocessor 408 concludes that the respective sensor has malfunctioned.
As the sensors employed are acceleration sensors 402-407 (e.g., accelerometers), the integration of their acceleration signal results in velocity. Integrating the acceleration with a small offset produces a damped velocity. If the vehicle's damped velocity change is too large (i.e., exceeds a threshold), microprocessor 408 concludes that the sensor under investigation has malfunctioned. In other words, if the sensor measures accelerations beyond the normal expected physical limitations of the vehicle, the sensor has malfunctioned. For example, assume an offset value for an accelerometer is 2 g and the failure threshold for the damped velocity is set to 100 mph. There are only two ways the vehicle's accelerometer can achieve a damped velocity of 100 mph. One way involves a severe crash and the other involves a malfunctioning sensor.
If microprocessor 408 determines that any one of sensors 402-407 has malfunctioned, microprocessor 408 may set a failure code in non-volatile memory 409, and it may prevent the sensor's signal from being used by a subsequent active road-noise control algorithm.
In another example, the damped integration algorithm is modified in that the vehicle speed is used to determine the method of integration. Information represent a of the vehicle speed may be supplied to microprocessor 408, and this information may be used to determine whether the vehicle is moving. If the vehicle's speed information indicates to microprocessor 408 that the vehicle is not moving, microprocessor 408 uses a different integration method by using the absolute value of the sense signals. Since the vehicle is not moving, there is no oscillation of the sense signals between positive and negative values. By using the absolute value, the calculated damped integration can grow toward the threshold value regardless of the sign of the sense signal. This provides for the quick detection of malfunctioning sensors that oscillate around a zero point.
An alternative way to detect malfunctioning sensors includes monitoring the sense signals relative to threshold zones and relative to all other sensors in the system. In one example, a sensor's fail counter is increased when its sense signal is outside of its corresponding threshold zone. The threshold zone for each sensor may be preset, depending upon expected driving conditions and specified sensor tolerances. If the sense signal re-enters the threshold zone, the sensor's fail counter is decreased. The sensor's fail counter is reset when one of the other sense signals leaves its respective threshold zone. Thus, when the counter of a sensor exceeds its predetermined counter threshold, the other sensors remain inside their respective threshold zones. Once the sensor's fail counter exceeds a predetermined counter threshold, microprocessor 408 identities this sensor as malfunctioning.
In yet another (additional or alternative) diagnostic method, a malfunction detection module may compare the sense signal or signals from at least one noise and vibration sensor with the sense signal or signals from at least one microphone to evaluate the operational state of the sensors. Besides simply comparing amplitudes, the time structures of sense signals may also be compared. As can be seen in
Referring to
Referring to
When at least one malfunctioning sensor is detected, the active road-noise control module (e.g., an active road-noise control modules 115 and 205 shown in
In another example, an adaptive filter 901, which may replace adaptive filter 116 in the single-channel active road-noise control system shown in
Referring to
In a procedure 1004, provisions are made for evaluating the operational state of the sensor arrangement and controlling the processing of the first sense signal and the second sense signal so that the first sense signal and the second sense signal are processed in the first mode of operation when the sensor arrangement is in a proper operational state and in the second mode of operation when a malfunction of the sensor arrangement has been detected.
The description of embodiments has been presented for purposes of illustration and description. Suitable modifications and variations to the embodiments may be performed in light of the above description or may be acquired by practicing the methods. For example, unless otherwise noted, one or more of the described methods may be performed by a suitable device and/or combination of devices. The described methods and associated actions may also be performed simultaneously, in parallel and/or in orders varied from the order described in this application. The described systems are exemplary in nature; they may include additional elements and/or omit elements.
As used in this application, an element or step denoted in the singular and preceded with the word a or an should be understood as not excluding the plural of said elements or steps, unless such exclusion is stated. Furthermore, references to “one embodiment” and “one example” of the present disclosure are not intended to be interpreted to exclude the existence of additional embodiments that also incorporate the described features. The terms first, second, third, etc. are used merely as labels, and are not intended to impose numerical requirements or a particular positional order on their objects.
Number | Date | Country | Kind |
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15190987 | Oct 2015 | EP | regional |
Filing Document | Filing Date | Country | Kind |
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PCT/IB2016/056044 | 10/10/2016 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2017/068455 | 4/27/2017 | WO | A |
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