Patent Publication Number: US-7219004-B2

Title: Adaptive control for engine with electronically adjustable valve operation

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
   This application is a divisional application of U.S. patent application Ser. No. 10/417,014, filed April 16, 2003, now U.S. Pat. No. 6,755,182 and hereby incorporated by reference in its entirety for all purposes. 

   BACKGROUND AND SUMMARY OF THE INVENTION 
   When operating unthrottled (e.g., without a throttle or at or near wide-open throttle) in an electric valve actuation type engine (or a continuously variable valve lift engine), a mass airflow sensor is degraded due to reverse flow effects leading to erroneous measurement. A manifold pressure sensor (MAP) also cannot be the primary sensor for measuring airflow (e.g., using a speed density approach), as the manifold pressure is substantially near atmospheric pressure during a wide variety of engine conditions. Further, even sensors that provide directional compensation may not be functional at low loads for these engines. 
   The inventors herein have recognized one approach to overcome these disadvantages. In particular, that is to estimate airflow using engine speed, temperature, and valve timing (additional compensation from an estimate, or measurement, of atmospheric pressure can be used if desired (e.g., from a MAP during engine starting)). But, as the engine ages, this estimate can become degraded. In other words, the engine air-to-fuel ratio control performance can be significantly degraded due to aging and part-to-part variability. 
   As such, the inventors herein have developed a system to compensate for such effects. The system comprises: an engine with electronically adjustable engine valve timing or valve lift; a sensor coupled to said engine; and a controller for: determining whether a condition is present; when said condition is present, operating in a first mode where an engine air amount is determined based on a valve amount and an adaptive parameter, wherein during said first mode said controller further updates said adaptive parameter based on said sensor; and operating in a second mode where said engine air amount is determine based on said valve amount and said adaptive parameter. 
   In this way, it is possible to utilize the adaptive information across multiple engine operating modes, and even in modes where adaptation is not possible or where adaptation is limited. 

   
     BRIEF DESCRIPTION OF THE FIGURES 
     The above features, and advantages will be readily apparent from the following detailed description of an example embodiment of the invention when taken in connection with the accompanying drawings. 
       FIG. 1  is a block diagram of a vehicle illustrating various components related to the present invention; 
       FIG. 2   a  show a schematic vertical cross-sectional view of an apparatus for controlling valve actuation, with the valve in the fully closed position; 
       FIG. 2   b  shows a schematic vertical cross-sectional view of an apparatus for controlling valve actuation as shown in  FIG. 1 , with the valve in the fully open position; 
       FIG. 2   c  is a graph illustration experimental data; 
       FIGS. 3–5  are high level flowcharts for use with the present invention; and 
       FIGS. 6–7  show experimental results by operation according to various features of example embodiments of present invention. 
   

   DETAILED DESCRIPTION AND  EXAMPLE EMBODIMENT OF THE INVENTION 
   Referring to  FIG. 1 , internal combustion engine  10  is shown. Engine  10  is an engine of a passenger vehicle or truck driven on roads by drivers. Engine  10  is coupled to torque converter via crankshaft  13 . The torque converter is also coupled to transmission via turbine shaft. The torque converter has a bypass clutch, which can be engaged, disengaged, or partially engaged. When the clutch is either disengaged or partially engaged, the torque converter is said to be in an unlocked state. The turbine shaft is also known as transmission input shaft. The transmission comprises an electronically controlled transmission with a plurality of selectable discrete gear ratios. The transmission also comprises various other gears such as, for example, a final drive ratio. The transmission is also coupled to tires via an axle. The tires interface the vehicle to the road. 
   Internal combustion engine  10  comprising a plurality of cylinders, one cylinder of which, shown in  FIG. 1 , is controlled by electronic engine controller  12 . Engine  10  includes combustion chamber  30  and cylinder walls  32  with piston  36  positioned therein and connected to crankshaft  13 . Combustion chamber  30  communicates with intake manifold  44  and exhaust manifold  48  via respective intake valve  52  and exhaust valve  54 . Exhaust gas oxygen sensor  16  is coupled to exhaust manifold  48  of engine  10  upstream of catalytic converter  20 . In one example, converter  20  is a three-way catalyst for converting emissions during operation about stoichiometry. 
   As described more fully below with regard to  FIGS. 2   a  and  2   b , at least one of, and potentially both, of valves  52  and  54  are controlled electronically via apparatus  210 . 
   Intake manifold  44  communicates with throttle body  64  via throttle plate  66 . Throttle plate  66  is controlled by electric motor  67 , which receives a signal from ETC driver  69 . ETC driver  69  receives control signal (DC) from controller  12 . In an alternative embodiment, no throttle is utilized and airflow is controlled solely using valves  52  and  54 . Further, when throttle  66  is included, it can be used to reduce airflow if valves  52  or  54  become degraded. 
   Intake manifold  44  is also shown having fuel injector  68  coupled thereto for delivering fuel in proportion to the pulse width of signal (fpw) from controller  12 . Fuel is delivered to fuel injector  68  by a conventional fuel system (not shown) including a fuel tank, fuel pump, and fuel rail (not shown). 
   Engine  10  further includes conventional distributorless ignition system  88  to provide ignition spark to combustion chamber  30  via spark plug  92  in response to controller  12 . In the embodiment described herein, controller  12  is a conventional microcomputer including: microprocessor unit  102 , input/output ports  104 , electronic memory chip  106 , which is an electronically programmable memory in this particular example, random access memory  108 , and a conventional data bus. 
   Controller  12  receives various signals from sensors coupled to engine  10 , in addition to those signals previously discussed, including: measurements of inducted mass air flow (MAF) from mass air flow sensor  110  coupled to throttle body  64 ; engine coolant temperature (ECT) from temperature sensor  112  coupled to cooling jacket  114 ; a measurement of manifold pressure from MAP sensor  129 , a measurement of throttle position (TP) from throttle position sensor  117  coupled to throttle plate  66 ; a measurement of transmission shaft torque, or engine shaft torque from torque sensor  121 , a measurement of turbine speed (Wt) from turbine speed sensor  119 , where turbine speed measures the speed of shaft  17 , and a profile ignition pickup signal (PIP) from Hall effect sensor  118  coupled to crankshaft  13  indicating an engine speed (N). Alternatively, turbine speed may be determined from vehicle speed and gear ratio. 
   Continuing with  FIG. 1 , accelerator pedal  130  is shown communicating with the driver&#39;s foot  132 . Accelerator pedal position (PP) is measured by pedal position sensor  134  and sent to controller  12 . 
   In an alternative embodiment, where an electronically controlled throttle is not used, an air bypass valve (not shown) can be installed to allow a controlled amount of air to bypass throttle plate  62 . In this alternative embodiment, the air bypass valve (not shown) receives a control signal (not shown) from controller  12 . 
   Referring to  FIGS. 2   a  and  2   b , an apparatus  210  is shown for controlling movement of a valve  212  in camless engine  10  between a fully closed position (shown in  FIG. 2   a ), and a fully open position (shown in  FIG. 2   b ). The apparatus  210  includes an electromagnetic valve actuator (EVA)  214  with upper and lower coils  216 ,  218  which electromagnetically drive an armature  220  against the force of upper and lower springs  222 ,  224  for controlling movement of the valve  212 . 
   Switch-type position sensors  228 ,  230 , and  232  are provided and installed so that they switch when the armature  220  crosses the sensor location. It is anticipated that switch-type position sensors can be easily manufactured based on optical technology (e.g., LEDs and photo elements) and when combined with appropriate asynchronous circuitry they would yield a signal with the rising edge when the armature crosses the sensor location. It is furthermore anticipated that these sensors would result in cost reduction as compared to continuous position sensors, and would be reliable. 
   Controller  234  (which can be combined into controller  12 , or act as a separate controller) is operatively connected to the position sensors  228 ,  230 , and  232 , and to the upper and lower coils  216 ,  218  in order to control actuation and landing of the valve  212 . 
   The first position sensor  228  is located around the middle position between the coils  216 ,  218 , the second sensor  230  is located close to the lower coil  218 , and the third sensor  232  is located close to the upper coil  216 . 
   As described above, engine  10 , in one example, has an electro-mechanical valve actuation (EVA) with the potential to maximize torque over a broad range of engine speeds and substantially improve fuel efficiency. The increased fuel efficiency benefits are achieved by eliminating the throttle, and its associated pumping losses, (or operating with the throttle substantially open) and by controlling the engine operating mode and/or displacement, through the direct control of the valve timing, duration, and or lift, on an event-by-event basis. 
   The estimation of the airflow into the engine can be based on a static model developed from nominal engine mapping data. For example, if N is engine speed and T is intake temperature, then cylinder flow can be estimated with a static model (EQN. 1) as 
   
     
       
         
           
             
               
                 
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   Here, V IVC , V EVC , V IVO  are cylinder volumes at intake valve closing timing, exhaust valve closing timing and intake valve opening timing, respectively, and the coefficients are determined in the calibration phase, and may depend on valve mode (i.e., whether intake and/or exhaust valves are alternating or not from cycle to cycle.) Note that the term W cyl,0  represents a baseline cylinder airflow. 
     FIG. 2   c  shows that accurate prediction of the cylinder flow can be obtained with such a static cylinder flow model at nominal conditions. 
   The inventors herein have recognized that the part-to-part variability and engine aging effects render this static model inaccurate over time. A more accurate representation of the cylinder flow model over time is of the form of EQN. 2
 
 W   cyl =θ 0   W   cyl,0 +θ 1   EQN. 2
 
where θ 0 ,θ 1  are unknown parameters (scale and offset). These parameters are estimated adaptively as shown below with regard to  FIG. 3 . In this way, it is possible to provide a more accurate determination of cylinder airflow. Note that in this example, both an offset and a scalar adaptive parameter are utilized. Other alternative methods could use just one parameter, or other types of adaptive parameters such as nonlinear term.
 
   One example of the present invention advantageously utilizes throttle  66  as an acoustic flap, i.e. the throttle is closed to create vacuum during a predetermined set of engine operating conditions and thereby reduce engine noise and allow adaptation. In other words, one embodiment of engine  10  utilizes the optional throttle plate to mitigate the effects of the acoustic noise disturbances. Such a flap nominally does not create a significant pressure drop (to minimize the effect on fuel economy) in the intake manifold but is closed just slightly to reduce the escape of undesirable induction noise. In an alternative embodiment, a simple two-position type electric valve could be used as the acoustic flap. Further, still, purely mechanical valve could be used to create a depression during certain operating conditions, such as engine speed, by using, for example, a governor type valve. 
   The inventors recognized that it is possible to use this flap for an additional purpose, specifically, to create conditions under which adaptation of the cylinder flow model becomes possible. If flap is closed sufficient to create a pressure drop in the intake manifold, then the flow will change as: 
                   W   cyl     =       (         θ   0     ⁢     W     cyl   ,   0         +     θ   1       )     ⁢     p     p     a   ⁢           ⁢   tm                   EQN   .           ⁢   3               
where p is the intake manifold pressure (equal to atmospheric p atm  when flap is open). In one example, p is measured via manifold pressure sensor  129 , and p atm  is measured from the sensor when the flap is fully open. Note that the adjustment (p/p atm ) is an optional correction, and various others could be used to account for small pressure drops in the intake manifold system.
 
   If p is lower than atmospheric pressure by at least a predetermined amount (e.g., 5 kPa, or 3–7 kPa in another example), the MAF sensor (which measures throttle flow, W th ) functions sufficiently well and the intake manifold pressure dynamics are accurately described by the isothermal emptying and filling relation of EQN 4: 
   
     
       
         
           
             
               
                 
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   Although the intake manifold pressure is measured with a sensor, in an alternative embodiment, it can be also estimated based on the estimates of unknown parameters and the same isothermal intake manifold filling and emptying model of EQN. 5: 
                       p   ^     .     =         RT     V   m       ⁢     (       W   th     -       (           θ   ^     0     ⁢     W     cyl   ,   0         +       θ   ^     1       )     ⁢     p     p     a   ⁢           ⁢   tm             )       +     K   ⁡     (     p   -     p   ^       )           ,           EQN   .           ⁢   5               
where K&gt;0 is an estimator gain, selected based on engine calibration. After initial transients, the error between estimated and measured pressure should approach zero if the parameters are estimated correctly. Hence, the pressure estimation error can be used to drive parameter adaptation till the error between measured pressure and estimated pressure is eliminated.
 
   To achieve this, the following parameter update laws of EQNS 6–7 are utilized: 
                             θ     ^   .       0     =       -       L   0     ⁡     (     p   -     p   ^       )         ⁢     W     cyl   ,   0       ⁢     p     p     a   ⁢           ⁢   tm             ,                     θ     ^   .       1     =       -       L   1     ⁡     (     p   -     p   ^       )         ⁢     p     p     a   ⁢           ⁢   tm             ⁢                           EQNS   .           ⁢   6     ⁢     -     ⁢   7               
where L 0 ,L 1  are gains determining how fast adaptation of each parameter proceeds.
 
   Note that in an alternative embodiment, the right hand-sides of the adaptation laws can be normalized by dividing them, respectively, by EQN. 8. 
   
     
       
         
           
             
               
                 
                   
                     
                       
                         
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   Finally, as another alternative embodiment, adaptation is enabled on close to steady state conditions only to eliminate the error between measured throttle flow and estimated cylinder flow. In this case, EQNS. 6–7 are modified to replace (p-phat) with Wth-Wcyl_hat. Wcyl_hat is given by equation 3. 
   Referring now specifically to  FIG. 3 , a routine for performing the adaptation is shown. First, in step  310 , the routine determines whether a specific condition is present that allows for adaptation. In this example, the routine determines whether manifold pressure (measured or estimated) is less than atmospheric pressure minus a margin (5 Kpa in this example). Note, however, that various other determinations can be used to determine whether to enable (or disable) adaptive learning, such as, for example:
         if pressure estimation error is sufficiently small, then the routine can disable the parameter updates;   if the nominal cylinder flow estimate is sufficiently high (exceeds a pre-determined threshold) then the routine can disable offset adaptation (but continue scalar adaptation); and/or   if the nominal cylinder flow estimate is sufficiently low (is below a pre-determined threshold) then the routine can disable scale adaptation (but continue offset adaptation).       

   When the answer to step  310  is YES, the routine continues to step  312  where estimated manifold pressure is determined according to EQN. 5. In one case, the routine uses the mass airflow signal to estimate Wth, along with manifold pressure and atmospheric pressure (and manifold temperature T) to calculate the estimated manifold pressure ({circumflex over (p)}). 
   Then, in step  314 , the routine uses EQNS. 6–7 to update the adaptive parameters based on the measured and estimated manifold pressure, and atmospheric pressure. The adaptive gains L 0  and L 1  can be fixed, or adjusted based on various engine operating parameters, and are generally determined by engine calibration. 
   Next, in step  316 , from either step  314  or a NO from  310 , the routine calculates the cylinder flow based on the adaptive parameters and the baseline cylinder flow. In other words, the routine uses EQNS. 1–3 to calculate the cylinder airflow. Finally, in step  318  the routine determines a fuel injection amount based on the calculated cylinder airflow, along with feedback from air-fuel ratio sensors and a desired air-fuel ratio. 
   In another aspect of the invention, when the engine does not have a capability to close the flap to create a sufficient depression in the intake manifold or does not have a flap, an alternative adaptation approach can be used. In this case, the method uses UEGO sensor (air-to-fuel ratio) measurements for adaptation. 
   With the flap at wide-open conditions (or with no flap), the cylinder airflow can again be characterized as shown in EQN. 9:
 
W cyl =θ 0 W cyl,0′   EQN. 9
 
Further, the injected fueling rate is, at close to steady-state conditions, governed by EQN. 10.
 
 W   f =θ 2   +k   f   p   w ,  EQN. 10
 
   In other words, the injected fueling rate can be estimated as a sum of an unknown parameter, θ 2 , (which accounts for injector drifts or injector deposits and will be adaptively learned as shown below), and a product of a known coefficient, k f , (determined from injector calibration), and commanded injector pulse-width, p w  (or fpw). In close to steady-state conditions, the UEGO sensor reading is labeled as λ. Then as shown by EQN. 11, the following equation governs operation:
 
θ 0   W   cyl,0 −θ 2   λ−k   f   p   w λ=ε≈0,  EQN. 11
 
where ε represents an unknown noise term with a known bound |ε|≦Δ. The noise accounts for UEGO drifts and discrepancies between fully steady-state conditions and close to steady-state conditions. The bound is a tunable parameter of the algorithm, and is set in the calibration phase.
 
   Each sample, n, the engine management system (controller  12  in one example) determines that close-to-steady state conditions are entered, the UEGO measurement provide a new condition that the unknown parameters need to satisfy in the form of two linear inequalities of EQN. 12
 
−Δ≦θ 0   W   cyl,0   n −θ 2 λ n   −k   f   p   w   n λ n ≦Δ  EQN. 12
 
   Here the superscript n identifies cylinder flow estimate, injector pulse-width and UEGO sensor reading during the n-th time instant when close to steady-state conditions are entered. These two inequalities can be intersected with the inequalities obtained from the prior entering in close to steady-state conditions, 1, 2, 3, . . . , n−1, to tighten the bounds on the unknown parameters. 
   To implement the intersection of the inequalities in a computationally efficient fashion suitable for on-line implementation, different techniques can be used. One example is the use of the method of the optimal bounding ellipsoids described in J. R. Deller, M. Nayeri and M. S. Liu (1994), “Unifying the Landmark Developments in Optimal Bounding Ellipsoid Identification”,  International Journal of Adaptive Control and Signal Processing  8(1), 43–60. In addition, the method described in Fogel and Huang, or Chisci, Garulli and Zappa can also be used. (Eli Fogel and Y. F. Huang (1982), “On the Value of Information in System Identification—Bounded Noise Case”,  Automatica  18(2), 229–238); (L. Chisci, A. Garulli, and G. Zappa, Recursive State Bounding by Parallelotopes (1996),  Automatica  32(7), 1049–1055). 
   In such a method, the parameter bounds are in the form of an ellipsoid (EQN. 13), 
                   {       θ     →   ^       =       (             θ   ^     0                       ⁢       θ   ^     2             )     |           (       θ     →   ^       -       θ     →   ^       n       )     T     ⁢       P   n     ⁡     (       θ     →   ^       -       θ     →   ^       n       )         &lt;   1         }     ,           EQN   .           ⁢   13               
where P n  is a 2×2 matrix and    n  is the 2×1 vector that identifies the center of the ellipsoid. The value of    n  is used to define present parameter estimates.
 
Explicit formulas can be given for obtaining P n      n  from P n−1 ,    n−1 .
 
   Note that in each step the algorithm tightens the bounds on the unknown parameters, unlike the conventional adaptation schemes that may not always provide continuous improvement and, in initial transients, may diverge from the true parameter values. 
   While the inventors believe that adapting two parameter estimates for the cylinder flow and one parameter estimate for the injectors should be sufficient, the invention can be equally well applied to cases when more parameters are utilized in model parameterization. Furthermore, instead of the method of the optimal bounding ellipsoids, the method can use the optimal bounding parallelotopes described in L. Chisci, A. Garulli, and G. Zappa, “Recursive State Bounding by Parallelotopes,  Automatica,  32(7), 1996, pp. 1049–1055. 
   Finally, adaptation on a cylinder-by-cylinder basis is also possible, provided that the air-to-fuel ratio values for each cylinder can be reliably determined from the pulses off the air-to-fuel ratio sensor using one of the techniques known in the art. 
   Referring now to  FIG. 4 , a routine is described for implementing this alternative approach. Specifically, in step  410  a determination is made as to whether steady state conditions are present. This determination can be made based on whether feedback correction in air-fuel ratio adjustment are within prescribed ranges, or based on the rate of change of manifold pressure or mass air flow, or various other approaches. 
   When the answer to step  410  is YES, the routine continues to step  412 . In step  412 , the routine updates the adaptive parameters that solve EQNs. 12–13 based on the base-line cylinder flow, fuel pulse width, air-fuel ratio, and various constants. 
   Next, from either step  412  or step  410  (NO), the routine continues to step  414 , where the routine calculates the cylinder flow based on the baseline flow and the adaptive parameters. Then, in step  416 , the routine calculates the fuel injection based on cylinder flow and air-fuel ratio sensor feedback signals. 
   Referring now to  FIG. 5 , a routine is described for determining the requested engine torque, and engine air flow, and based thereon controlling engine valve timing. I.e., adjusts valve timing or valve lift to control estimated/measured airflow (and/or torque) to a desired value. First, in step  610 , the routine determines the driver request from signal (PP). For example, the routine determines a requested drive torque based on pedal position, and optionally adjusted based on vehicle speed. Further, various other driver requests approaches can be used. From step  610 , the routine continues to step  612 , where a determination is made as to whether the vehicle is operating in a mode other than the driver request mode. Other such modes include, for example, a cruise control mode where vehicle speed is used with a vehicle speed set point to control engine operation, traction control, where wheel slip is used to control engine output, idle speed control where engine speed is feedback controlled independent of driver input, or vehicle stability control. When the answer to step  612  is “yes”, the routine continues to step  614  and determines the desired engine torque based on the other operating mode. 
   Alternatively, when the answer to step  612  is “no”, the routine continues to step  616  and determines the desired engine torque based on the driver request in step  610 . For example, the routine can calculate desired engine torque based on the desired wheel torque and other parameters including gear ratio, and torque ratio across the torque converter. Then, the routine continues to step  618  and determines the desired airflow based on the desired engine torque. This can be performed using engine maps including parameters such as engine speed, engine coolant temperature, air-fuel ratio, and various others. Alternatively, the routine can determine the desired air amount such as an air charge value based on the desired engine torque. 
   From step  618  the routine continues to step  620  to determine whether the desired airflow is less than a first threshold A- 1  and whether engine speed is greater than a second threshold N- 1 . When the answer to step  620  is “no”, the routine continues to step  622  to operate with intake valve closing timing after bottom dead center of piston movement. Alternatively, when the answer to step  620  is “no” the routine continues to step  624  to operate with valve closing timing of the intake valve before bottom dead center of piston movement. Note that the operation according to steps  622  and  624  can be referred to as late intake valve closing and early intake valve closing depending on whether the intake valve closing timing is before or after bottom dead center of the piston movement during the intake stroke. Finally, in step  626 , the routine controls valve timing (either early or late) to provide the desired air amount, and to thereby provide the desired engine torque and finally thereby to provide the desired driver request. 
   Referring now to  FIG. 6–7 , experimental results according to the routines described above are shown. Specifically,  FIG. 6  shows variations in the parameters (θ 0  and θ 2 ), and  FIG. 7  shows the error before and after adaptation. As such, the above aspects of the present invention are able to account for variations in physical parameters through adaptation and thereby reduce estimation error. This results in increased air-fuel ratio accuracy and reduced emissions.