Abstract:
An improved closed-loop feedback fuel control with a model-based A/F ratio estimator, wherein the estimator, controller and portions of the model are updated on a fixed time interval basis, thereby minimizing the impact of the control on event-based throughput. Engine transport delays and oxygen sensor dynamics are modeled to estimate the sensed A/F ratio, and the estimate is compared with the sensed A/F ratio to adaptively adjust the model and to develop a closed-loop adjustment of the commanded fuel amount. The engine transport delay model is carried out on an engine event basis, but the sensor dynamics model is carried out on a time basis to accurately reflect the analog nature of the sensor. The estimator and the controller are also carried out on a time basis to reduce throughput requirements at higher engine speeds, and the control gain is scheduled to account for differences between the engine event and time update rates. The control enables numerous control enhancements, including flexibility to topology variations (such as sensor placement, sensor type and sensor characteristics), ease of calibration, and the ability to easily calibrate and schedule A/F ratio perturbations for catalytic conversion efficiency optimization.

Description:
TECHNICAL FIELD 
     This invention relates to closed-loop fuel control for an internal combustion engine, and more particularly to a control based on a system model and air/fuel (A/F) ratio error estimator. 
     BACKGROUND OF THE INVENTION 
     The need for precise control of A/F ratio in motor vehicles has let to the development of controllers in which all or a portion of the engine air flow and exhaust system dynamics are mathematically modeled to estimate the sensed A/F ratio, and to adaptively adjust both the model and the base fuel control based on deviations of the estimated A/F ratio from the sensed A/F ratio. See, for example, SAE Paper N. 950846, by Fekete, Guden and Powell, entitled Model-Based Air-Fuel Ratio Control of a Lean Multi-Cylinder Engine. However, such controls tend to be complex, and when updated in time with the engine firing events, present excessive computational throughput requirements at higher engine speeds. Accordingly, such control strategies tend to be cost-prohibitive for most applications. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to an improved closed-loop feedback fuel control with a model-based A/F ratio estimator, wherein the estimator, controller and portions of the model are updated on a fixed time interval basis, thereby minimizing the impact of the control on event-based throughput. Engine transport delays and oxygen sensor dynamics are modeled to estimate the sensed A/F ratio, and the estimate is compared with the sensed A/F ratio to adaptively adjust the model and to develop a closed-loop adjustment of the commanded fuel amount. The engine transport delay model is carried out on an engine event basis, but the sensor dynamics model is carried out on a time basis to accurately reflect the analog nature of the sensor. The estimator and the controller are also carried out on a time basis to reduce throughput requirements. at higher engine speeds, and the control gain is scheduled to account for differences between the exhaust gas measurements, which occur at the engine event frequency, and the controller time update frequency. 
     The subject control strategy enables numerous control enhancements, including flexibility to topology variations (such as sensor placement, sensor type and sensor characteristics), ease of calibration, and the ability to easily calibrate and schedule A/F ratio perturbations for catalytic conversion efficiency optimization. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a diagram showing an engine fuel control strategy according to this invention, including an A/F ratio perturbation controller, a model-based A/F ratio estimator, and a closed-loop fuel controller. 
     FIG. 2 is a diagram detailing the A/F ratio perturbation controller of FIG.  1 . 
     FIG. 3 is a diagram detailing the A/F ratio estimator of FIG.  1 . 
     FIGS. 4A and 4B are diagrams detailing an alternate embodiment of the A/F ratio estimator of FIG.  3 . 
     FIG. 5 is a diagram detailing the closed-loop fuel controller of FIG.  1 . 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring to FIG. 1, the fuel control of this invention is principally described in the context of an automotive internal combustion engine  10  having an electronically controlled fuel delivery system  12 , and an exhaust system  14  including a three-way catalytic converter  16 , an upstream universal exhaust gas oxygen (UEGO) sensor  18  (also known as an analog or wide-range air/fuel sensor), and a downstream switching oxygen sensor  20 . In certain other embodiments, discussed below, the locations of the UEGO and switching sensors  18 ,  20  may be swapped, or switching sensors may be used both upstream and downstream of catalytic converter  16 . Other sensors depicted in FIG. 1 include a mass air flow (MAF) sensor  22  coupled to the engine intake manifold  24 , and an engine speed (RPM) sensor  26  coupled to the engine output shaft  28 . Also in the illustrated embodiment, the engine  10  has a throttle  30  positioned within the manifold  24  by a motor-driven (or alternatively, cable-driven) throttle actuator  32 , under the control of a driver torque command (DTC) circuit  34  via line  36 . The DTC circuit  34  may be responsive to various un-depicted elements such as a driver-manipulated accelerator pedal, a cruise control circuit, a traction control circuit, and so on. 
     The remaining elements (also referred to herein as circuits) depicted in FIG. 1 relate to the fuel control of engine  10 , a represent functional blocks of hardware and/or software residing within a microprocessor-based engine control module  40 . In the illustrated embodiment, the engine control module  40  is responsible for suitably activating the engine fuel delivery system  12  via control lines  42 . The fuel control acts primarily in response to the DTC signal, which is applied as one of several inputs to an Open-Loop Fuel Control (OLFC) circuit  44  via line  46 . The OLFC circuit also receives the MAF signal via line  48 , and operates in an open-loop and generally conventional manner to produce a commanded A/F ratio (CAFR) signal on line  50 , and a corresponding fuel injection base pulse width (BPW) signal on line  52 . Alternate control strategies based on engine speed and intake manifold pressure (instead of MAF) are also conventional and well known. Various methods of scheduling the commanded A/F ratio CAFR are also well known in the art, and not described here. The BPW signal on line  52  is modified by a vector of multipliers  54  to produce an adjusted pulse width (PAPW) signal on line  56 , as described below. In turn, the APW signal is corrected for transient fueling conditions by the Transient Fuel Controller (TFC)  58  (which alternatively, may be implemented within the OLFC  44 ), and further adjusted for cylinder-to-cylinder variations of engine  10  by the Individual Cylinder Fuel Controller (ICFC)  60 , which generates the individual fuel control signals on lines  42 . The controllers  58  and  60  may implement any of a number of known and conventional control strategies, and are not particularly relevant or critical to the control of the present invention. 
     The control of this invention is concerned primarily with the development of a suitable closed-loop feedback term which is applied to the multiplier  54  for the purpose of adjusting the delivered fuel quantity so that the A/F ratio at the catalytic converter  16  will actually correspond to the commanded A/F ratio CAFR, or in the preferred embodiment, to a perturbated version (CAFR′) of CAFR. The control involves utilizing a model-based estimator  62  to estimate the A/F ratio that should be sensed by the UEGO sensor  18 , and to develop a leading control error (CE) signal on line  63  based on the deviation between the estimated and sensed A/F ratios; and a controller  64  for developing a closed-loop multiplier (CLM) on line  65  based on the control error CE signal on line  63  and the engine speed signal RPM on line  27 . The estimator  62  and controller  64  are described in detail below in reference to FIGS. 3 and 4, respectively. In the illustrated embodiment, the closed-loop multiplier CLM is applied as an input to a block learn module (BLM)  66 , which includes a number of fuel correction tables that are adaptively adjusted based on the CLM, resulting in the generation of a closed-loop feedback signal on line  67  for application to multiplier  54 . 
     Perturbation of the CAFR is customarily practiced in automotive engine controls as a means of enhancing the conversion efficiency of a catalytic converter. The perturbation frequency and amplitude characteristics are typically determined experimentally and indirectly via control gains for a given powertrain configuration, but the techniques employed to identify the optimal characteristics vary widely, and typically entail considerable calibration effort. Accordingly, a significant aspect of this invention resides in the implementation of perturbation circuits  68  in the overall control strategy described above. As fully described below in reference to FIG. 2, the perturbation circuit (PERT)  68  enables direct control of the perturbation frequency, amplitude, and bias offset. The PERT circuit  68  generates a perturbated commanded A/F ratio (CAFC′) signal on line  69  for application to the estimator  62 , and a corresponding perturbation multiplier (PM) on line  70  for application to the multiplier  54 . As a result, the estimator  62  and controller  64  cooperate to produce a closed-loop multiplier (CLM) that causes the scheduled A/F perturbations to occur at the sensing location of UEGO  18 . An additional, but related, function of perturbation circuit  68  concerns an on-board development tool for sweeping various combinations of perturbation frequency and amplitude in order to streamline the calibration process. 
     Referring specifically to FIG. 2, the perturbation circuit  68  includes a square-wave generator  72  and an amplitude sweep tool  74 . The output of the square-wave generator on line  76  is added to the commanded A/F ratio CAFR in summer  78  to form the perturbated version CAFR′ on line  69 . The perturbation multiplier PM on line  70  is obtained by dividing CAFR by CAFR′ in the arithmetic block  80 . The various inputs designated PF, BO and PA are calibration constants utilized by the square-wave generator  72 , and correspond to the desired perturbation frequency (PF), perturbation amplitude (PA) and bias offset (BO). The perturbation frequency PF is applied to a frequency generator  82 , which generates a corresponding clock signal (C) to trigger a state change of the components within the boses  74  and  84 . The coupled memory  86  and flip-flop  88  provide a first input of alternating polarity to the multiplier  90 , and the perturbation amplitude PA forms a second input. The alternating polarity output of multiplier  90  is added to the bias offset BO by summer  92  to form the square-wave generator output on line  76 . With this simple arrangement, the calibration engineer can independently adjust the PF, BO and PA to achieve the best catalytic conversion efficiency, thereby significantly reducing the calibration effort, compared to prior control arrangements. In practice, PF, BO and PA are scheduled by table look up as a function of engine operating conditions, such as exhaust gas flow rate and temperature. 
     The amplitude sweep tool  74  is calibration tool that provides a perturbation amplitude signal on line  94  for selectively overriding the calibrated perturbation amplitude PA. The switch  96  is used to select the desired perturbation amplitude input for square-wave generator  72 ; in the indicated position, the calibrated PA value is selected, while in the opposite position, the amplitude signal on line  94  is selected. The amplitude sweep tool  74  is designed to sweep the amplitude signal on line  94  between base and maximum amplitude values BA, MA, upon activation of the amplitude reset (AR) input. The calibration engineer can use the amplitude sweep tool  74  to quickly determine the optimum combination of PF and PA by sweeping the amplitude signal for each of a number of PF settings, while monitoring the conversion efficiencies for specified exhaust gas constituents. When the optimum settings are determined, the optimum PA and PF settings are stored, and the switch  96  is positioned as shown in FIG.  2 . 
     Within the amplitude sweep tool  74 , a multiplier  98  is reset to zero by either of the AR input and the compare circuit  100 . The multiplier output is supplied to a memory  102 , and the output of memory  102  is supplied along with the step rate (SR)  104  to the summer  106 . The output of summer  106  is supplied as an input to multiplier  98 , and is added to the base amplitude (BA) by summer  110  to form the perturbation amplitude signal on line  94 . When the perturbation amplitude signal on line  94  reaches the maximum amplitude (MA)  112 , the compare circuit  100  resets multiplier  98 , to begin a new amplitude sweep. 
     Referring now to FIG. 3, the estimator  62  comprises an engine delay mode  120 , a UEGO sensor dynamics model  122  and a bias estimator  124 . The engine delay model imparts a variable engine event-based delay to the perturbated command A/F ratio CAFR′ on line  50 , producing a delayed version CAFR′(d) on line  126  corresponding to the expected A/F ratio upstream of catalytic converter  16  at the location of the upstream sensor  18 . The signal CAFR′(d) is adjusted by summer  128  in accordance with a bias estimator feedback signal on line  130 , forming a corrected estimate of the A/F ratio in the exhaust upstream of the catalytic converter  16 , designated as EAFRexh. The output of summer  128  is then applied as an input to sensor model  122 , which models the sensor dynamics and produces a signal EAFRsen on line  132  corresponding to the estimated A/F ratio at the location of UEGO sensor  18 . The actual output voltage of sensor  18  (designated as V 18 ) is sampled on an engine firing event basis, and is combined in summer  134  with a rear trim bias voltage (RBV) developed by the rear trim circuit  136  in response to the output voltage of downstream switching sensor  20  (designated as V 20 ). The rear trim circuit  136  may be conventional in nature, and serves to calibrate the UEGO sensor  18  relative to the voltage target of rear switching sensor  20 . The table  138  converts the trimmed oxygen sensor voltage on line  140  to a measured A/F ratio, designated as AFRm. In bias estimator  124 , the summer  142  determines and A/F ratio error (AFRerr) according to the difference between AFRm and EAFRsen. Integral and proportional feedback terms based on AFRerr are combined in summer  144  to form the above-mentioned bias estimator feedback signal on line  130 . And finally, the integral feedback term is divided by CAFR′(d) in arithmetic circuit  146  to form the control error CE signal on line  63 . 
     The engine delay model is engine event based, and constructs a variable delayed version of CAFR′ by storing successive samples of CAFR′ in successive registers of delay unit  150 , and selecting an appropriate sample for application to line  126  via selector  152 . The selector  152 , in turn, is controlled by a calibrated front sensor delay FSD value (0, 1 . . . N) on line  154 . The FSD values are selected by the calibration engineer based on measured on estimated independent parameters of engine  10 , and in practice, are scheduled by table look up as a function of engine operating conditions representative of exhaust mass flow rate. This calibration can be facilitate by setting the perturbation frequency PF of perturbation circuit  68  to a very low frequency, and counting the number of engine events required for the perturbations to reach the UEGO or switching sensors  18 ,  20 . 
     The sensor model  122  mimics the dynamics of UEGO sensor  18  by filtering EAFRexh with a time-based first-order filter defined by the calibration values ΔT and TC. The term ΔT is the filter update time increment (corresponding to clock frequency C), and TC is the filter time constant. The block  155  (U) represents a unity offset. The arithmetic unit  156  divides the update time increment ΔT by TC, and supplies the result to multiplier  158  and summer  160 . The summer forms a difference between ΔT/TC and the offset U, and supplies the result to multiplier  162 , which also receives a previous value of the model output from memory  164 . The model input EAFRexh is multiplied by ΔT/TC with multiplier  158 , and the result is summed with the output of multiplier  162  in summer  166  to form the output signal EAFRsen on line  132 . 
     As mentioned above, the estimator bias feedback signal on line  130  is formed in bias estimator  124  by combining proportional and integral feedback terms in summer  144 . The proportional term is simply obtained by applying the proportional gain (Gp)  170  to the error AFRerr. The integral term is obtained by applying the integral (Gi) gain  172  to the error AFRerr, and summing the result in summer  174  with a previous value of the integral term, supplied by memory (M)  176 . The arithmetic unit  146  normalizes the integral term relative to CAFR(d) to form the control error signal CE. As a result, the control error signal CE represents a percentage A/F ratio error, allowing the controller  64  to use the same gains for A/F ratio operating range. 
     FIGS. 4A and 4B, taken together, depict an alternate embodiment of estimator  62 , designated as  62 ′, which is adaptable to mechanizations in which the UEGO sensor  18  is located either upstream or downstream of the catalytic converter  16 . In certain instances, locating the sensor  18  downstream of the converter  16  facilitates combining the senor  18  with a NOX sensor, for example. FIG. 4A mirrors FIG. 3, except for the simplification of elements  120 ,  122 ,  124  and the addition of a catalytic converter model  180  and a switch  182 . In common respects, the reference numerals used in FIG. 3 have been repeated. FIG. 4B depicts the catalytic converter model  180  in detail. With the switch  182  in the position indicated in FIG. 4A, the bias estimator  62 ′ is equivalent to the bias estimator  62  depicted in FIG.  3 . However, when the switch  182  is positioned to contact the terminal  184 , the catalytic converter model  180  is interposed between summer  128  and the sensor model  122 . In such event, the input into sensor model  122  on line  185 , represents the estimated A/F ratio at the outlet of catalytic converter  16 , on EAFRcatout. 
     Referring to FIG. 4B, the catalytic converter model  180  mimics the dynamics of catalytic converter  16  by filtering EAFRexh with a time-based first-order filter defined by the calibration values ΔT and TC. The term ΔT is the filter update time increment, TC is the filter time constant (which of course is different than the time constant used in sensor model  122 ). The arithmetic unit  186  divides the update time increment ΔT by TC, and supplied the result to multiplier  188  and summer  190 . The summer forms a difference between ΔT/TC and the unity offset (U)  191 , and supplies the result to multiplier  192 , which also receives a previous value of the model output from memory  194 . The model input EAFRexh is multiplied by ΔT/TC with multiplier  188 , and the result is summed with the output of multiplier  192  in summer  196  to form the output signal EAFRcatout on line  185 . 
     Referring to FIG. 5, the controller  64  develops a time-based closed-loop feedback multiplier CLM on line  65  for modifying the base fuel pulse width BPW, forcing the A/F ratio at the senor  18  to conform with the CAFR′. The feedback multiplier comprises proportional and integral terms, which are applied to the summer  200 . The proportional term is obtained simply by applying the proportional gain Gp  202  to the control error CE signal on line  63 . The integral gain term is formed by applying an integral gain to the control error CE in multiplier  204 , and summing the result in summer  206  with a previous value of the integral term, supplied by memory  208 . The previous integral term value supplied by memory  208  is limited to predefined minimum and maximum values, as indicated by limiter  210 . The output of summer  200  (and hence, the output of controller  64 ) is also limited to predefined minimum and maximum values by the limiter  212 , and the output of limiter  212  is applied to an arithmetic unit  214 , which converts the limited feedback signal into the closed-loop multiplier CLM. 
     The integral gain comprises first and second components determined respectively as a function of the control error CE and the engine speed RPM. The first component, Gi(err), generated by table  216 , is high for large values of control error CE, but rapidly decreases when the magnitude of the control error CE falls below a threshold, as indicated by the table graph. Thus, the feedback is high for aggressive closed-loop fuel correction when fast dynamic response is needed, and low for stability enhancement when the A/F ratio is at or near the commanded value. The second component, Gi(rpm), generated by table  218 , progressively increases with engine speed RPM so that the closed-loop multiplier CLM generated by the time-based controller  64  matches the dynamics of the fuel delivery system  14  (and the corresponding rate of new information at UEGO  18 ), which is inherently engine event-based. Thus, the integral gain component Gi(rpm) is low at low engine speeds when the time increment rate of the controller  64  exceeds the event rate of engine  10 , and high at high engine speeds when the event rate of engine  10  exceeds the time increment rate of the controller  64 . 
     Calibration of the controller gains for disturbance rejection can be facilitated by replacing the perturbated input CAFR′ to estimator  62  on line  69  with the un-perturbated signal CAFR on line  50 , while retaining the perturbation multiplier input PM to multiplier  54  on line  70 . This produces a known and controllable (via perturbation circuit  68 ) A/F ratio disturbance for judging the suitability of the controller gains. 
     In summary, the control of this invention provides a practical and cost-efficient implementation of a model-based A/F ratio estimator by carrying out the slow and calculation-intensive portions of the control on a time basis, adjusting the response of the control to match the event-based engine fuel delivery system. In addition to accurate A/F ratio control, the control topology allows an easily calibrated method of perturbation the controlled A/F ratio, and permits the flexibility to adapt the control to different powertrain mechanizations. Calibration of the perturbation schedule is also facilitated by the on-board catalyst sweep tool, which eliminates the need for special external equipment during development. Further, direct control of the perturbation characteristics facilitates calibration of the engine delay model and the controller gains. While the present invention has been described in reference to the illustrated embodiments, it is expected that various modification in addition to those mentioned above will occur to those skilled in the art. For example, the various sensor models may be enhanced to represent more complex dynamic behavior, the calibration sweep tool could be designed to sweep frequency instead of amplitude, and so on. Thus, it will be understood that methods incorporating these and other modifications may fall within the scope of this invention, which is defined by the appended claims.