Electrical audio signal processing systems and devices – Acoustical noise or sound cancellation – Within cabin or compartment of vehicle
Reexamination Certificate
1999-03-10
2004-04-27
Mei, Xu (Department: 2644)
Electrical audio signal processing systems and devices
Acoustical noise or sound cancellation
Within cabin or compartment of vehicle
C381S071100, C381S071110, C381S071120, C381S086000
Reexamination Certificate
active
06728380
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention concerns a system and method for the suppression of noise infiltrating a signal from a sensor. More particularly, the invention concerns an algorithm-based approach for suppressing cyclic noise.
Most modern vehicles utilize some form of microprocessor for controlling the operation of various functional components of the vehicle. For instance, automotive vehicles utilize an engine control module that carries out instructions for controlling the performance of the engine, as well as for monitoring that performance. More specifically, the control microprocessor implements a set of algorithms that receive information concerning the current state of the engine, and that use the information for determining subsequent action for each of the functional components.
For example, as shown in
FIG. 1
, a typical vehicle electronic control system can include an engine control module (ECM)
10
that implements a number of engine control and protection routines as described above. The ECM
10
receives signals from various sensors disposed throughout the vehicle. For example, a speed sensor
12
determines the rotational speed of the engine. In a typical installation, the speed sensor
12
constitutes a Hall-type sensor that registers the passage of teeth on a tone wheel
14
. In some applications, the array of sensors can also include a torque sensor
16
that measures the torque at the engine crankshaft. An array of pressure sensors
18
and temperature sensors
20
can transmit corresponding signals from various locations in the engine, such as at the intake and exhaust manifolds.
After receiving the signals from these various sensors
12
,
16
,
18
and
20
, the ECM
10
provides output signals to various functional components. For instance, a cruise control module
22
can receive and return signals from the ECM to maintain a particular vehicle speed. A fuel control module
24
controls the amount of air and liquid fuel introduced into the engine combustion cylinders. An injection timing module
26
can determine the timing of injection, and ultimately ignition, in a multiple cylinder engine. Finally, an array of signals and alarms
28
can alert the vehicle operator of engine operating parameters that exceed predetermined thresholds.
As with any electronic or software based system, the function of the ECM
10
relies upon the integrity of the information provided to the ECM. Thus, if data from each of the sensors is suspect, the control signal provided by the ECM
10
to each of the functional elements
22
,
24
, or
26
, may be erroneous. For example, bad data from the speed sensor
12
may lead to vehicle speed surges when the cruise control module
22
is in operation. Discrepancies in the signals from the pressure sensors
18
or temperature sensors
20
may cause errors in airflow calculations, which will affect the signals presented to the fuel control component
22
or injection timing component
26
. These types of errors can lead to poor combustion, and even engine knock. Moreover, bad data from the various sensors can severely effect the fuel economy and operating efficiency of an engine.
One external phenomenon that has a significant effect on the integrity of sensor data is noise generated by various components of the engine. The noise can include electrical noise or EMF associated with electrical components of the engine and vehicle. In addition, the periodic engine combustion event generates its own type of cyclic noise that infiltrates the signals from most sensors disposed throughout the engine and vehicle. In order to preserve the integrity of the sensor data, it is necessary to account for this extraneous noise. Preferably, the noise is removed from the sensor signals so that a noise-free signal is provided to and utilized by the ECM
10
.
In one approach, the sensor signals are passed through an array of band pass filters. One detriment of these filters is that they tend to reduce the response time of the sensor signals as they are being provided to the control module. In addition, band path filters reduce the bandwidth of the signals that can be received from each sensor, which can lead to clipping and attenuation problems. In another approach, a moving average filter is utilized over each engine cycle. Again, this type of filter causes delay and can reduce the signal bandwidth.
Another prior art approach is depicted in the block diagram of FIG.
2
. In this approach, the sensor signal
32
is subject to an adaptive least means square algorithm. The signal
32
is provided to a mean remover
34
that essentially eliminates any DC or non-cyclic component of the signal, leaving substantially all of the cyclic noise component of the sensor signal. In an important aspect of this prior art approach, a noise base function generator
36
generates sine and cosine functions at given frequencies. The noise function generator
36
is based on the principle that any fixed frequency signal with known magnitude and phase delay can be obtained by the linear combination of several sine and cosine functions. Thus, these prior art devices utilize essentially a noise signal generator that produces cyclic signals corresponding to the expected components of the noise infiltrating the sensor signal
32
.
The sensor signal, after it has had its DC component removed by element
34
, together with the noise signals from the component
36
, are fed to an adaptive least means square algorithm module
38
. The adaptive module can include a multiplexer to sequentially provide the various sine and cosine noise signals generated by the component
36
. In addition, the adaptive module
38
performs a series of multiplications and additions to produce the least means square output signal that is ultimately subtracted from the sensor signal
32
at a summing node
44
. The result of this subtraction is the conditioned signal
46
that is, in essence, a “noiseless” sensor signal.
The adaptive feature of this prior art approach is that the output from the adaptive algorithm component
38
is subtracted from the sensor signal
32
after it has had its DC component removed in element
34
for input to the least mean square component
38
. Thus, a summing node
40
subtracts the output of the adaptive component from the sensor signal to yield an adaptive input signal
42
.
While the adaptive least means square algorithm approach of the prior art shown in
FIG. 2
adequately suppresses fixed frequency noise, it suffers from certain problems. For instance, in order to obtain the moving average at the mean remover component
34
, as well as the adaptive algorithm output from component
38
, up to fourteen multiplications are required for each data sampling cycle, based upon an assumption that the noise signal includes six cyclic components. This intensive computational throughput makes it difficult for the adaptive LMS filter to be implemented in a real-time environment.
What is needed, therefore, is a noise suppression system and method that can adequately address cyclic noise that infiltrates sensor signals. This system and method must have only minimal computational requirements so that it can be implemented in a real-time environment.
SUMMARY OF INVENTION
In view of these needs, the present invention contemplates an engine control system comprising a number of condition sensor disposed throughout an internal combustion engine, each sensor operable to generate a sensor signal at predetermined sampling intervals that includes a cyclic noise component to be removed. A noise compensation filter receives the sensor signal and includes means for adaptively suppressing at least a portion of the cyclic noise component within said sensor signal to generate a corrected signal at each sampling interval.
In one embodiment, the noise compensation filter generates an error compensation signal that is subtracted from the sampled sensor signal to produce a corrected signal. A moving average of the sampled sensor signal, or sensor error signal, is obtained that corr
Gangopadhyay Anupam
Zhu G. George
Barnes & Thornburg
Cummins Inc.
Grier Laura A.
Mei Xu
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