Patent Publication Number: US-8527187-B2

Title: Systems and methods for digital signal processing

Description:
FIELD 
     The present disclosure relates to methods and systems for processing digital signals in a vehicle control system. 
     BACKGROUND 
     The statements in this section merely provide background information related to the present disclosure and may not constitute prior art. 
     Vehicles include an internal combustion engine that generates drive torque. More specifically, the engine draws in air and mixes the air with fuel to form a combustion mixture. The combustion mixture is compressed and ignited to drive pistons that are disposed within the cylinders. The pistons rotatably drive a crankshaft that transfers drive torque to a transmission and wheels. A knock sensor generates a knock signal based on a vibration of the engine. Disturbances in the knock signal, such as from background noise, can cause inaccurate engine knock determinations and, therefore, may cause one or more vehicle subsystems to operate inefficiently. 
     Conventional methods of processing the knock signal for background noise include moving averages methods, first order lag filters, and a full standard deviation computation. The use of a full standard deviation computation method provides superior description of the sample distribution to the moving averages methods and the first order lag filters. A commonly known equation for the full standard deviation includes: 
                     Standard   ⁢           ⁢   Deviavtion     =         [         ∑     i   =   1       i   =   N       ⁢       (       d   i     -     d   _       )     2         (     N   -   1     )       ]       .             (   1   )               
Where d i  is a sample point,  d  is the average of the sample points, and N represents the number of sample points. This full standard deviation computation method requires a buffering for every point that is part of the distribution or alternatively using highly throughput-intensive data manipulation in order to produce an average and standard deviation. Thus, to achieve superior signal processing, large amounts of controller memory and throughput must be added. Increased processor throughput and additional memory can be costly to the controller.
 
     SUMMARY 
     Accordingly, a control system for a vehicle is provided. The control system includes a signal processing module that receives a sensor signal and extracts a plurality of sample points from the sensor signal. A computation module computes a summation of the sample points, computes a summation of squares of the sample points, and computes a standard deviation based on the summation of the sample points and the summation of the squares of the sample points. A control module generates a control signal based on the sensor signal and the standard deviation. 
     In other features, a method of processing a sensor signal for a vehicle is provided. The method includes: processing a plurality of sample points from a sensor signal; computing a summation of the sample points; computing a summation of squares of the sample points; computing a standard deviation based on the summation of the sample points and the summation of the squares of the sample points; and generating a control signal based on the sensor signal and the standard deviation. 
     Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. 
    
    
     
       DRAWINGS 
       The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way. 
         FIG. 1  is a functional block diagram illustrating a vehicle including an engine system. 
         FIG. 2  is a dataflow diagram illustrating digital signal processing system in accordance with various aspects of the present teachings. 
         FIG. 3  is a flowchart illustrating a digital signal processing method in accordance with various aspects of the present teachings. 
     
    
    
     DETAILED DESCRIPTION 
     The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. As used herein, the term module refers to an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. 
     Referring now to  FIG. 1 , a vehicle  10  includes various electronically-controlled systems. For example, an engine system  12  includes an engine  13  that combusts an air and fuel mixture to produce drive torque. Air is drawn into an intake manifold  14  through a throttle  16 . The throttle  16  regulates mass air flow into the intake manifold  14 . Air within the intake manifold  14  is distributed into cylinders  18 . Although four cylinders  18  are illustrated, it can be appreciated that the engine  13  can have a plurality of cylinders  18 , including, but not limited to, 2, 3, 5, 6, 8, 10, 12, and 16 cylinders. It is also appreciated that the engine  13  may, in the alternative, include a V-type cylinder configuration. 
     The air within the cylinders  18  is mixed with fuel and combusted therein. The combustion process drives a crankshaft (not shown) to produce drive torque. Combustion exhaust within the cylinders  18  is forced out through an exhaust manifold  20 . The combustion exhaust is treated in an exhaust system (not shown). The engine system  12  includes various sensors that generate digital signals based on sensed information from the engine system  12 . For example, an engine speed sensor  22  generates a digital engine speed signal  24  based on a rotational speed of the crankshaft. A knock sensor  26  generates a digital knock signal  28  indicating a vibration of the engine  13 . A temperature sensor  30  generates a digital temperature signal  32  indicating a temperature of air entering the engine  13 . As can be appreciated, the engine system  12  can include various other digital sensors. Hereinafter, one or more of the sensors discussed above will be commonly referred to as a digital sensor  36  that generates a digital signal  38 . 
     A control module  34  receives one or more of the digital signals  38  from the digital sensors  36  of the engine system  12  and processes the digital signals  38  based on digital signal processing methods of the present disclosure. More particularly, the control module  34  computes a partial standard deviation for background noise picked up by the digital sensor  36  and generated in the digital signal  38 . The partial standard deviation is then used to differentiate between normal noise and unwanted operation condition events. Based on the differentiation, the control module  34  can more efficiently interpret the digital signal  38  and control one or more components of the engine system  12 . Similarly, the digital signal processing systems and methods of the present disclosure can apply to other electronically-controlled systems in the vehicle  10  that include digital sensors  36 , such as, but not limited, a transmission system, a body system, and a throttle system. For ease of the discussion, the disclosure will be discussed in the context of an engine system  12 . 
     Referring now to  FIG. 2 , a dataflow diagram illustrates various embodiments of a digital signal processing system that may be embedded within the control module  34 . Various embodiments of digital signal processing systems according to the present disclosure may include any number of sub-modules embedded within the control module  34 . As can be appreciated, the sub-modules shown may be combined and/or further partitioned to similarly process the digital signal  38 . Inputs to the system may be sensed from the vehicle  10  ( FIG. 1 ), received from other control modules (not shown) within the vehicle  10  ( FIG. 1 ), and/or determined by other sub-modules (not shown) within the control module  34 . In various embodiments, the control module  34  of  FIG. 2  includes a signal processing module  40 , a first summation module  42 , a second summation module  44 , a subtraction module  46 , and a square-root module  48 . 
     The signal processing module  40  receives as input the digital signal  38 . The signal processing module  40  extracts a number  50  of sample points  52  from the digital signal  38 . A first summation module  42  receives as input the sample points  52 . The first summation module  42  computes a square of each sample point  52  and a summation of the squares  54  of each sample point  52 . A second summation module  44  receives as input the number  50  and the sample points  52 . The second summation module  44  computes a summation of points  56  by computing a summation of the sample points  52 , computing a square of the summation, and dividing the square by the number  50  of points. 
     The subtraction module  46  receives as input the sum of squares  54  and the sum of points  56 . The subtraction module  46  computes a difference  58  between the sum of squares  54  and the sum of points  56 . The square-root module  48  receives as input the difference  58 . The square-root module  48  computes a partial standard deviation  60  by computing a quotient by dividing the difference by the number  50  of points minus one, and taking a square root of the quotient. The partial standard deviation  60  can then be used to calculate a signal-to-noise ratio. The signal-to-noise ratio is then used to process the digital signal  38  for controlling one or more components of the engine system  12  ( FIG. 1 ). 
     Referring now to  FIG. 3 , a flowchart illustrates various embodiments of a digital signal processing method that may be performed by the digital signal processing system of  FIG. 2 . In various embodiments, the digital signal processing method is scheduled to run periodically during vehicle operation. As can be appreciated, the digital signal processing method of the present disclosure is not limited to the sequential execution as shown in  FIG. 3 . In one example, the method may begin at  100 . A presence of the digital signal  38  ( FIG. 2 ) is evaluated at  110 . If a digital signal  38  ( FIG. 2 ) is received at  110 , a number N of sample points d i  are extracted from the digital signal  38  at  120 . Otherwise, the method continues to monitor for the presence of the digital signal  38  at  110 . 
     Once the number N of sample points d i  are extracted from the digital signal  38  at  120 , the partial standard deviation  60  is computed at  130 . In various embodiments, the partial standard deviation  60  is computed based on the following equation: 
     
       
         
           
             
               
                 
                   
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     The digital signal  38  can then be processed based on the partial standard deviation  60  to determine the actual signal-to-noise ratio at  140 . Based on the signal-to-noise ratio and the digital signal  38 , one or more components of the engine system  12  ( FIG. 1 ) are controlled at  150 . The method may end at  160 . 
     Those skilled in the art can now appreciate from the foregoing description that the broad teachings of the present disclosure can be implemented in a variety of forms. Therefore, while this disclosure has been described in connection with particular examples thereof, the true scope of the disclosure should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, specification, and the following claims.