Patent Publication Number: US-2012031080-A1

Title: Method and apparatus for predicting peak temperature in a vehicle particulate filter

Description:
TECHNICAL FIELD 
     The present invention relates to a method and apparatus for predicting peak temperature in a particulate filter in a vehicle exhaust stream. 
     BACKGROUND 
     Particulate filters are designed to remove microscopic particles of soot, ash, metal, and other suspended matter from an exhaust stream of a vehicle. Over time, the particulate matter accumulates on the substrate within the filter. In order to extend the life of the particulate filter and to further optimize engine functionality, some filters are designed to be selectively regenerated using heat. 
     Temperatures within the particulate filter can be temporarily increased to between approximately 450° C. to 600° C. by directly injecting and igniting fuel, either in the engine&#39;s cylinder chambers or in the exhaust stream upstream of the filter. The spike in exhaust gas temperature may be used in conjunction with a suitable catalyst, e.g., palladium or platinum, wherein the catalyst and heat act together to break down any accumulated particulate matter into relatively inert carbon soot via a simple exothermic oxidation process. 
     SUMMARY 
     A vehicle as disclosed herein includes an engine, a regenerable particulate filter, and a host machine. The particulate filter receives an exhaust stream from the engine&#39;s exhaust port, in some embodiments via an upstream oxidation catalyst. The host machine calculates a predicted peak temperature that will be reached within the particulate filter under current vehicle operating conditions, i.e., absent any control actions. The host machine may predict the peak temperature in part by referencing one or more models and extracting required values, such as estimated filter soot loading rates and corresponding burn rates. 
     The host machine compares the predicted peak temperature to a calibrated threshold, recording a diagnostic code to reflect the result. The host machine may then automatically execute an engine control action or another suitable control action when the predicted peak temperature exceeds the threshold. In following the methodology set forth herein, the host machine may prevent the predicted peak temperature from being realized, thereby protecting the substrate of the particulate filter from temperature spikes exceeding the filter&#39;s test-verified thermal boundary. 
     A system and method are also provided for use aboard a vehicle. The system includes the particulate filter and host machine noted above. The host machine calculates a predicted peak temperature in the particulate filter, and automatically executes a control action when the predicted peak temperature exceeds a calibrated threshold. 
     The method may be embodied as an algorithm which is executable via the host machine. The method includes using the host machine to calculate a predicted peak temperature in the particulate filter using a model, e.g., a soot model and/or a thermal model which provide estimated soot loads, particulate filter qualities, and corresponding burn rates. The method may also include using the predicted peak temperature to initiate an engine management action or another suitable control action as needed. 
     The above features and advantages and other features and advantages of the present invention are readily apparent from the following detailed description of the best modes for carrying out the invention when taken in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic illustration of a vehicle having an internal combustion engine and a heat-regenerable particulate filter; and 
         FIG. 2  is a flow chart describing a method for predicting a peak temperature of the particulate filter used aboard the vehicle shown in  FIG. 1 . 
     
    
    
     DESCRIPTION 
     Referring to the drawings, wherein like reference numbers correspond to like or similar components throughout the several figures, a vehicle  10  is shown schematically in  FIG. 1 . Vehicle  10  includes a host machine  40  and an algorithm  100 . Algorithm  100  may be selectively executed by host machine  40  in order to calculate a predicted peak temperature within an oxidation catalyst (OC) system  13  aboard the vehicle  10  under current vehicle operating conditions, and to thereafter prevent the predicted peak temperature from being realized in order to protect portions of the OC system from temperature spikes. Algorithm  100  is described in further detail below with reference to  FIG. 2 . 
     Vehicle  10  includes an internal combustion engine  12 , such as a diesel engine or a direct injection gasoline engine, the OC system  13 , and a transmission  14 . Engine  12  combusts fuel  16  drawn from a fuel tank  18 . In one possible embodiment, the fuel  16  is diesel fuel and the OC system  13  is a diesel oxidation catalyst (DOC) system, although other fuel types may be used depending on the design of the engine  12 . 
     A throttle  20  may be used to selectively admit a mix of fuel  16  and air into the engine  12  as needed. Combustion of fuel  16  generates an exhaust stream  22 , which is ultimately discharged into the surrounding atmosphere once filtered through the OC system  13 . Energy released by the combustion of fuel  16  produces torque on an input member  24  of the transmission  14 . The transmission  14  in turn transfers the torque from engine  12  to an output member  26  in order to propel the vehicle  10  via a set of wheels  28 , only one of which is shown in  FIG. 1  for simplicity. 
     OC system  13  cleans and conditions the exhaust stream  22  as it passes from an exhaust port(s)  17  of engine  12  through the vehicle&#39;s exhaust system. The OC system  13  may include an oxidation catalyst  30  and a particulate filter  34 . According to one possible embodiment, the particulate filter  34  may be configured as a diesel particulate filter (DPF) when the fuel  16  is diesel fuel. An optional selective catalytic reduction (SCR) device  32  may be positioned between the oxidation catalyst  30  and the particulate filter  34  to convert nitrogen oxides (NOx) gasses into water and nitrogen as by products using an active catalyst, e.g., a ceramic brick or a ceramic honeycomb structure, a plate structure, or any other suitable design. 
     Particulate filter  34  is selectively regenerable using heat regardless of the composition of fuel  16 . Regeneration of particulate filter  34  may be active or passive. As understood in the art, passive regeneration requires no additional control action for regeneration. Instead, the particulate filter  34  is installed in place of a muffler, and particulate matter is collected on a substrate within the filter at idle or low power operations. As exhaust temperature increases, the collected material within the particulate filter  34  is burned or oxidized by the exhaust stream  22 . Active regeneration by contrast uses an external source of heat to aid regeneration, along with additional control methodology. 
     Still referring to  FIG. 1 , particulate filter  34  includes a substrate  35  which may be constructed of ceramic, metal mesh, pelletized alumina, or any other temperature and application-suitable material(s). As the engine exhaust stream temperature increases, the collected material in or on the substrate  35  of particulate filter  34  is burned or oxidized by the exhaust stream  22 , as noted above. Some possible regeneration methods include coating the filter substrate  35  with a base or precious metal, thereby reducing the temperature needed for oxidation of the particulate matter, installing a catalyst such as oxidation catalyst  30  upstream of the particulate filter, using fuel-borne catalysts to reduce the burn-off temperature of the collected particulates, etc. 
     Particulate filter  34  may be connected to or formed integrally with the oxidation catalyst  30  in those embodiments in which the oxidation catalyst  30  is used. In other embodiments, a fuel injection device  36  may be placed in fluid communication with host machine  40  and controlled via control signals  15 . Fuel injection device  36  selectively injects fuel  16  drawn from fuel tank  18  into the oxidation catalyst  30  or into engine cylinders (not shown) when determined by host machine  40 . Injected fuel  16  is burned in a controlled manner in order to generate sufficient levels of heat for regenerating the particulate filter  34 . 
     However, temperatures within the particulate filter  34  may at times reach levels exceeding a calibrated threshold. Therefore, host machine  40  is also configured to calculate a predicted peak temperature within the particulate filter  34  using temperature and soot modeling, and to take any necessary control actions preemptively in order to prevent the predicted peak temperature from being realized. 
     Host machine  40  may be configured as a digital computer acting as a vehicle controller, and/or as a proportional-integral-derivative (PID) controller device having a microprocessor or central processing unit (CPU), read-only memory (ROM), random access memory (RAM), electrically erasable programmable read only memory (EEPROM), a high-speed clock, analog-to-digital (A/D) and/or digital-to-analog (D/A) circuitry, and any required input/output circuitry and associated devices, as well as any required signal conditioning and/or signal buffering circuitry. Algorithm  100  and any required reference calibrations are stored within or readily accessed by host machine  40  to provide the functionality described below with reference to  FIG. 2 . 
     Host machine  40  receives signals  11  from various sensors  42  positioned to measure exhaust qualities, e.g., temperature, pressure, oxygen level, etc., at different locations within OC system  13 , including directly upstream and downstream of the oxidation catalyst  30  and the particulate filter  34 . Host machine  40  is also in communication with the engine  12  to receive feedback signals  44  that identify current vehicle operating conditions, e.g., throttle position, engine speed, accelerator pedal position, fueling quantity, requested engine torque, etc. 
     Algorithm  100  may be executed by host machine  40  in order to calculate a predicted peak temperature within the particulate filter  34  under current vehicle operating conditions. Host machine  40  may reference a temperature model  50  and a soot model  60  in making this prediction, extracting calibrated information from each model as needed. Host machine  40  uses the rate of energy input into the substrate of the particulate filter  34 , and the energy released and transferred into the substrate, i.e., by convection, oxidation of hydrocarbons and carbon soot, etc., with information from models  50  and  60 , and then calculates a predicted peak temperature within the particulate filter  34 . 
     Such an approach relies on the predictive accuracy of temperature and soot models  50 ,  60 , respectively, and not on a use of the measured inlet temperature to the particulate filter  34  in a closed-loop feedback control process of the conventional mode. Host machine  40  compares the predicted peak temperature to a calibrated threshold. If the predicted peak temperature exceeds the threshold, the host machine may prevent the predicted peak temperature from being realized in various ways via one or more control actions. 
     Referring to  FIG. 2 , execution of algorithm  100  by host machine  40  calculates a predicted peak temperature, abbreviated T PF, PEAK , inside of particulate filter  34  under current vehicle operating conditions so that the host machine  40  can preemptively request a suitable control action, thereby reducing the probability that the predicted peak temperature will ever be realized. 
     Algorithm  100  begins with step  102 . At this step, the energy input rate {dot over (Q)} IN  into the OC system  13  is calculated by host machine  40  using the equation: 
     
       
         
           
             
               
                 
                   Q 
                   . 
                 
                 IN 
               
               = 
               
                 
                   T 
                   g 
                 
                 
                   
                     C 
                     g 
                   
                    
                   
                     
                       M 
                       . 
                     
                     g 
                   
                 
               
             
             , 
           
         
       
     
     where T g  is the measured exhaust gas temperature, C g  is the known specific heat of the exhaust gas  22 , and {dot over (M)} g  is the mass flow rate of the exhaust gas  22 . The algorithm  100  then proceeds to step  104 . 
     At step  104 , host machine  40  solves for the net energy output rate {dot over (Q)} OUT  of the exhaust stream  22  exiting the particulate filter  34 , e.g., using temperature model  50 . The value {dot over (Q)} OUT  can then be transformed into an output temperature value, i.e., by multiplying by (C g {dot over (M)} g ). Then, E OUT −E IN ={dot over (Q)} OUT −{dot over (Q)} IN . This basic energy balance equation can then be applied to determine the total energy transfer with respect to the particulate filter  34 . 
     That is, energy transfer with respect to substrate  35  can be determined using information extracted from the temperature model  50  by the host machine  40 , with the temperature model populated using the following equation: 
         E   PF,TOTAL =( E   PF,OUT   −E   PF,IN )+ E   SOOT , 
     where E SOOT  may be determined via the equation: 
         Hv   CARBON ( {dot over (R)}   O2   −{dot over (R)}   NO2 ), 
     with Hv CARBON  being the heating value of the particulate matter in the particulate filter  34 , and with the values {dot over (R)} O2 , {dot over (R)} NO2  representing the soot mass consumption rates through oxidation in the particulate filter. Algorithm  100  then proceeds to step  106 . 
     At step  106 , the predicted peak temperature is calculated by host machine  40 . Host machine  40  may access models  50  and  60  and extract information such as burn rates and specific heat values, and uses the energy balance equations from the models to calculate the predicted peak temperature, i.e., T PF, PEAK  as follows: 
     
       
         
           
             
               
                 T 
                 
                   PF 
                   , 
                   PEAK 
                 
               
               = 
               
                 
                   T 
                   0 
                 
                 + 
                 
                   
                     
                       ( 
                       
                         E 
                         
                           PF 
                           , 
                           TOTAL 
                         
                       
                       ) 
                     
                      
                     
                       ( 
                       
                         t 
                         ZSOOT 
                       
                       ) 
                     
                   
                   
                     
                       ( 
                       
                         C 
                         pPF 
                       
                       ) 
                     
                      
                     
                       ( 
                       
                         M 
                         PF 
                       
                       ) 
                     
                   
                 
               
             
             , 
           
         
       
     
     where T 0  is the current temperature of the particulate filter  34 , C pPF  is the specific heat of the substrate  35 , and M PF  is the mass of the substrate  35 . The value t ZSOOT  is the time remaining, per the soot model  60 , until substantially no soot remains in the particulate filter  34 , a value which may be pre-calculated and stored in the soot model using the following equation: 
     
       
         
           
             
               t 
               zSOOT 
             
             = 
             
               
                 
                   M 
                   SOOT 
                 
                 
                   
                      
                     
                       M 
                       SOOT 
                     
                   
                   
                      
                     T 
                   
                 
               
               = 
               
                 
                   
                     M 
                     SOOT 
                   
                   
                     
                       
                         η 
                         f 
                       
                        
                       P 
                        
                       
                         
                           M 
                           . 
                         
                         
                           eng 
                           , 
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                       ( 
                       
                         
                           
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                             O 
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                              
                             2 
                           
                         
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                              
                             2 
                           
                         
                       
                       ) 
                     
                   
                 
                 . 
               
             
           
         
       
     
     Information may then be extracted from the soot model  60  by host machine  40  in calculating the predicted peak temperature as explained below. In the two equations appearing immediately above, M SOOT  is the mass of soot, η f  is the filtration efficiency of the particulate filter  34 , and P{dot over (M)} is the accumulation rate of soot or particulate matter, i.e., PM, in the particulate filter. 
     The predicted peak temperature T PF, PEAK , of the particulate filter  34  at the calculated time t ZSOOT  is then determined using the equation appearing immediately above by knowing the properties of the substrate  35  and storing these known or calibrated values in the temperature model  50 . 
     At step  108 , the host machine  40  compares the predicted peak temperature (T PF, PEAK ) to a calibrated threshold and records a flag reflecting the result, e.g., setting a diagnostic code or a flag of 0 when the threshold is not exceeded, and a different diagnostic code or a flag of 1 when the threshold is exceeded. After the results of the comparison are recorded, the algorithm  100  proceeds to step  110 . 
     At step  110 , host machine  40  may execute a preemptive control action when the predicted peak temperature (T PF, PEAK ) exceeds the calibrated threshold. As used herein, preemptive control action means a control action executed well before the predicted peak temperature (T PF, PEAK ) is realized, such that the control action prevents temperature in the particulate filter  34  from ever reaching the predicted level. One possible preemptive control action is an engine management action such as but not limited to reducing the levels of O2 in the exhaust stream, selective cylinder deactivation, reduction in hydrocarbon injection rate, etc. 
     Using algorithm  100  and host machine  40  as set forth above, protection modes may be entered only when necessary to protect the particulate filter  34 . The calibrated threshold may be determined beforehand via testing and validation for a given vehicle  10  under expected operating conditions to optimize the accuracy of the soot model  60 , the temperature model  50 , and the algorithm  100 . That is, during the design phase the thermal boundaries of the particulate filter  34  are accurately defined, and then subjected to rigorous testing to gain an understanding of the statistical distribution of various failure modes, such as face or internal cracks in the substrate  35 . 
     Approaches such as finite element analysis can be used to gain an understanding of the probability of failure in the lifetime of the particulate filter  34  at a given temperature distribution. Steps may then be taken in the design phase to increase the robustness of the substrate material and optimize the thermal boundaries, with the present method enforcing these well-defined boundaries. 
     While the best modes for carrying out the invention have been described in detail, those familiar with the art to which this invention relates will recognize various alternative designs and embodiments for practicing the invention within the scope of the appended claims.