Post-processing system control strategy for NOx and ammonia

Abstract

The present application relates to a control strategy for NOx and ammonia in an aftertreatment system. A system includes an aftertreatment system and a controller coupled to the aftertreatment system. The controller is configured to generate a spatially resolved model of a catalyst of the aftertreatment system. The controller is further configured to adjust the spatially resolved model based on one or more sensed values from at least one sensor upstream of the one or more portions and at least one sensor downstream of the one or more portions.

Description

[0001] This application is a divisional application of the application filed on December 17, 2021, with application number 202180085746.5 and entitled "Control Strategy for NOx and Ammonia in Aftertreatment System". Cross-references to related applications

[0002] This application claims the benefit and priority of U.S. Provisional Application No. 63 / 199,307, filed December 18, 2020, entitled “AFTERTREATMENT SYSTEM NOx ANDAMMONIA CONTROL STRATEGY,” which is incorporated herein by reference in its entirety. Technical Field

[0003] This disclosure relates to systems and methods for dynamically managing and controlling engine exhaust aftertreatment systems. In particular, this disclosure relates to managing and controlling ammonia (i.e., a reducing agent) and system output NOx via an onboard integrated model for a controller of the system. background

[0004] Exhaust aftertreatment systems are typically designed to reduce emissions of particulate matter, nitrogen oxides (NOx), hydrocarbons, and other environmentally harmful pollutants such as greenhouse gases and sulfur oxides. This reduction is achieved through a combination of a catalyst (e.g., an SCR catalyst) within the aftertreatment system and a reducing agent (e.g., ammonia) added to the exhaust gas stream. In the presence of some catalysts, the reducing agent injected into the exhaust gas reacts to convert harmful emissions into less harmful ones (e.g., NOx is converted to nitrogen and water). However, unused reducing agent may be released into the atmosphere or otherwise accumulate within the aftertreatment system (or other components), adversely affecting its effectiveness. Overview

[0005] One embodiment relates to a system including an aftertreatment system and a controller coupled to the aftertreatment system. The controller is configured to generate a spatially resolved model of the catalyst of the aftertreatment system. The controller is also configured to adjust the spatially resolved model based on one or more sensing values ​​from at least one sensor upstream of one or more parts and at least one sensor downstream of one or more parts. By discretizing the catalyst into parts and subsequently controlling components of the system (e.g., engine, aftertreatment system heater, etc.), the system can advantageously control emissions while managing a reducing agent (e.g., ammonia) in the system.

[0006] In some implementations, the controller is further configured to: compare one or more modeled values ​​from the spatially resolved model with one or more desired values ​​from the after-processing system; and, in response to the comparison, command at least one of the engine, heater, or doser of the after-processing system to achieve the one or more desired values. In some implementations, the controller is also configured to: determine the gradient between one or more sensed values ​​from at least one sensor upstream of one or more parts and one or more sensed values ​​from at least one sensor downstream of one or more parts; and assign new modeled values ​​to one or more parts based on the determined gradient.

[0007] In some implementations, the controller is also configured to: compare one or more modeling values ​​from a spatially resolved model with one or more desired values ​​from the catalyst; and identify faults in the aftertreatment system based on the difference between one or more modeling values ​​and one or more desired values ​​exceeding an error threshold. In some implementations, the catalyst is a selective catalytic reduction (SCR) catalyst. In some implementations, the catalyst is a combination of a selective catalytic reduction (SCR) catalyst and an ammonia oxidation catalyst (AMOX). In some implementations, the catalyst is a first selective catalytic reduction (SCR) catalyst, and the aftertreatment system includes a second SCR catalyst located upstream of the first SCR catalyst. The second SCR catalyst is relatively smaller than the first SCR catalyst. In some implementations, the system includes a first reductant metering device fluidly coupled to the first SCR catalyst and a second reductant metering device fluidly coupled to the second SCR catalyst. In some implementations, the controller is also configured to: control the metering command of the first reductant metering device based on one or more modeling values ​​from a spatially resolved model for the first and second SCR catalysts. In some implementations, one or more modeling values ​​indicate the amount of ammonia stored in one or more sections of the first SCR catalyst and the second SCR catalyst, and the dosing command of the first reducing agent metering device is based on a comparison of one or more modeling values ​​with an ammonia storage threshold, one or more modeling values ​​indicating the amount of ammonia stored in one or more sections of the first SCR catalyst and the second SCR catalyst.

[0008] In some implementations, the controller is also configured to control the dosing command of the second reductant metering device based on one or more modeling values ​​from spatially resolved models of the first and second SCR catalysts. One or more modeling values ​​may indicate the amount of ammonia stored in one or more sections of the first and second SCR catalysts. The dosing command for the second reductant metering device is based on a comparison of one or more modeling values ​​indicating the amount of ammonia stored in one or more sections of the first and second SCR catalysts with an ammonia storage threshold.

[0009] Another embodiment relates to a method. The method includes generating a spatially resolved model of a catalyst in a post-treatment system via a controller coupled to the post-treatment system. The spatially resolved model divides the catalyst into one or more sections. The method further includes adjusting the spatially resolved model by the controller based on one or more sensing values ​​from at least one sensor upstream of one or more sections and at least one sensor downstream of one or more sections.

[0010] In some implementations, the method further includes: the controller comparing one or more modeling values ​​from the spatial resolution model with one or more desired values ​​from the after-processing system; and in response to the comparison, the controller commanding at least one of the engine, heater, or metering device of the after-processing system to achieve one or more desired values. In some implementations, adjusting the spatial resolution model includes: the controller determining a gradient between one or more sensed values ​​from at least one sensor upstream of one or more sections and one or more sensed values ​​from at least one sensor downstream of one or more sections; and the controller assigning new modeling values ​​to one or more sections based on the determined gradient.

[0011] In some implementations, the method further includes: having a controller compare one or more modeling values ​​from a spatially resolved model with one or more expected values ​​from a catalyst; and having the controller identify a fault in the aftertreatment system based on the difference between one or more modeling values ​​and one or more expected values ​​exceeding an error threshold. In some implementations, the catalyst is a selective catalytic reduction (SCR) catalyst.

[0012] Another embodiment relates to a system. The system includes processing circuitry including at least one processor coupled to a memory. The memory stores instructions therein that, when executed by the at least one processor, cause the processing circuitry to: generate a spatially resolved model of a catalyst in an aftertreatment system, the spatially resolved model dividing the catalyst into one or more segments; and adjust the spatially resolved model based on one or more sensing values ​​from at least one sensor upstream of one or more segments and at least one sensor downstream of one or more segments. The instructions, when executed by the at least one processor, also cause the processing circuitry to: compare one or more modeling values ​​from the spatially resolved model with one or more desired values ​​of the aftertreatment system; and, in response to the comparison, command at least one of the engine, heater, or metering device of the aftertreatment system to achieve one or more desired values. The instructions, when executed by the at least one processor, also cause the processing circuitry to: determine a gradient between one or more sensing values ​​from at least one sensor upstream of one or more segments and one or more sensing values ​​from at least one sensor downstream of one or more segments; and assign new modeling values ​​to one or more segments based on the determined gradient.

[0013] One embodiment relates to a controller coupled to an aftertreatment system, the controller being configured to generate a spatially resolved model of the catalyst of the aftertreatment system, the spatially resolved model dividing the catalyst into one or more sections. The controller is configured to adjust the spatially resolved model based on one or more sensing values ​​from at least one sensor upstream of one or more sections and at least one sensor downstream of one or more sections.

[0014] This application provides the following: 1) A system comprising: Post-processing system; and A controller, connected to the post-processing system, is configured to: Generate a spatially resolved model of the catalyst in the aftertreatment system, the spatially resolved model dividing the catalyst into one or more parts; and The spatial resolution model is adjusted based on one or more sensing values ​​from at least one sensor upstream of the one or more portions and at least one sensor downstream of the one or more portions.

[0015] 2) According to the system described in 1), wherein the controller is further configured to: Compare one or more modeling values ​​from the spatial resolution model with one or more expected values ​​from the post-processing system; and In response to the comparison, at least one of the engine, heater, or metering device of the aftertreatment system is commanded to achieve the one or more desired values.

[0016] 3) According to the system described in 2), wherein, in adjusting the spatial resolution model, the controller is further configured to: Determine the gradient between one or more sensed values ​​from at least one sensor upstream of the one or more portions and one or more sensed values ​​from at least one sensor downstream of the one or more portions; and New modeling values ​​are assigned to one or more of the components based on the determined gradient.

[0017] 4) The system according to 1), wherein the controller is further configured to: Compare one or more modeling values ​​from the spatially resolved model with one or more expected values ​​for the catalyst; and Faults in the post-processing system are identified based on the difference between one or more modeled values ​​and one or more expected values ​​exceeding an error threshold.

[0018] 5) The system according to 1), wherein the catalyst is a selective catalytic reduction (SCR) catalyst.

[0019] 6) The system according to 1), wherein the catalyst is a combination of a selective catalytic reduction (SCR) catalyst and an ammonia oxidation catalyst (AMOX).

[0020] 7) The system according to 1), wherein the catalyst is a first selective catalytic reduction (SCR) catalyst, wherein the aftertreatment system includes a second SCR catalyst located upstream of the first SCR catalyst, and wherein the second SCR catalyst is relatively smaller than the first SCR catalyst.

[0021] 8) The system according to 7) further includes a first reductant metering device fluidly connected to the first SCR catalyst and a second reductant metering device fluidly connected to the second SCR catalyst.

[0022] 9) The system according to 8), wherein the controller is further configured to: Based on one or more modeling values ​​of the spatially resolved models for the first SCR catalyst and the second SCR catalyst, control the dispensing command for the first reducing agent dispenser.

[0023] 10) The system according to 9), wherein the one or more modeling values ​​indicate the amount of ammonia stored in one or more portions of the first SCR catalyst and the second SCR catalyst, and wherein the dosing command of the first reducing agent dosing device is based on a comparison of the one or more modeling values ​​with an ammonia storage threshold, the one or more modeling values ​​indicating the amount of ammonia stored in the one or more portions of the first SCR catalyst and the second SCR catalyst.

[0024] 11) The system according to 8), wherein the controller is further configured to: Based on one or more modeling values ​​of the spatially resolved models for the first SCR catalyst and the second SCR catalyst, control the dispensing command for the second reducing agent dispenser.

[0025] 12) The system according to 11), wherein the one or more modeling values ​​indicate the amount of ammonia stored in one or more portions of the first SCR catalyst and the second SCR catalyst, and wherein the dosing command of the second reducing agent dosing device is based on a comparison of the one or more modeling values ​​with an ammonia storage threshold, the one or more modeling values ​​indicating the amount of ammonia stored in the one or more portions of the first SCR catalyst and the second SCR catalyst.

[0026] 13) A method comprising: A spatially resolved model of the catalyst in the aftertreatment system is generated by a controller connected to the aftertreatment system, the spatially resolved model dividing the catalyst into one or more parts; and The controller adjusts the spatial resolution model based on one or more sensing values ​​from at least one sensor upstream of the one or more portions and at least one sensor downstream of the one or more portions.

[0027] 14) The method according to 13) further includes: The controller compares one or more modeling values ​​from the spatial resolution model with one or more expected values ​​from the post-processing system; and In response to the comparison, the controller commands at least one of the engine, heater, or metering device of the aftertreatment system to achieve the one or more desired values.

[0028] 15) According to the method described in 14), adjusting the spatial resolution model includes: The controller determines the gradient between one or more sensed values ​​from at least one sensor upstream of the one or more portions and one or more sensed values ​​from at least one sensor downstream of the one or more portions; and The controller assigns new modeling values ​​to one or more parts based on the determined gradient.

[0029] 16) The method according to 13) further includes: The controller compares one or more modeling values ​​from the spatially resolved model with one or more expected values ​​from the catalyst; and The controller identifies faults in the post-processing system based on the difference between one or more modeled values ​​and one or more expected values ​​exceeding an error threshold.

[0030] 17) The method according to 13), wherein the catalyst is a selective catalytic reduction (SCR) catalyst.

[0031] 18) A system comprising: Processing circuitry, the processing circuitry including at least one processor coupled to a memory, the memory storing instructions that, when executed by the at least one processor, cause the processing circuitry to: A spatially resolved model of the catalyst in the post-treatment system, the spatially resolved model dividing the catalyst into one or more parts; and The spatial resolution model is adjusted based on one or more sensing values ​​from at least one sensor upstream of the one or more portions and at least one sensor downstream of the one or more portions.

[0032] 19) The system according to 18), wherein the instructions, when executed by the at least one processor, further cause the processing circuitry to: Compare one or more modeling values ​​from the spatial resolution model with one or more expected values ​​from the post-processing system; and In response to the comparison, at least one of the engine, heater, or metering device of the aftertreatment system is commanded to achieve the one or more desired values.

[0033] 20) The system according to 19), wherein the instructions, when executed by the at least one processor, further cause the processing circuitry to: Determine the gradient between one or more sensed values ​​from at least one sensor upstream of the one or more portions and one or more sensed values ​​from at least one sensor downstream of the one or more portions; and New modeling values ​​are assigned to one or more of the components based on the determined gradient.

[0034] This overview is illustrative only and is not intended to be limiting in any way. Other aspects, inventive features, and advantages of the apparatus or process described herein will become apparent from the detailed description set forth herein in conjunction with the accompanying drawings, wherein like reference numerals refer to like elements. In this regard, numerous specific details are provided to provide a thorough understanding of embodiments of the subject matter of this disclosure. In one or more embodiments and / or implementations, the features described in this disclosure may be combined in any suitable manner. One or more features of one aspect of the invention may be combined with one or more features of different aspects of the invention. Furthermore, additional features that may not be present in all embodiments or implementations may be identified in some embodiments and / or implementations. Brief description of the attached diagram

[0035] Figure 1 This is a schematic diagram of a system with a controller according to an exemplary embodiment.

[0036] Figure 2 This is according to an exemplary embodiment. Figure 1 A schematic diagram of the system's controller.

[0037] Figure 3 According to the exemplary embodiments, by Figures 1-2 Graphical descriptions of the discrete axial cross-sections of the SCR catalyst and AMOx catalyst generated by the controller.

[0038] Figure 4 This is a flowchart of a method for managing NOx and ammonia in an exhaust gas aftertreatment system according to an exemplary embodiment.

[0039] Figure 5 This is according to an exemplary embodiment. Figure 1 A schematic diagram of the alternative post-processing system.

[0040] Figure 6 It is for adjusting according to the exemplary embodiment. Figure 1 The flowchart of the process of modeling the system. Detailed description

[0041] The following is a more detailed description of various concepts and implementations related to methods, apparatuses, and systems for managing NOx and ammonia via an onboard integrated model management system. Before turning to the accompanying drawings, which illustrate certain exemplary embodiments in detail, it should be understood that this disclosure is not limited to the details or methods set forth in the specification or shown in the drawings. It should also be understood that the terminology used herein is for descriptive purposes only and should not be considered limiting.

[0042] Referring generally to the accompanying drawings, the various embodiments disclosed herein relate to systems, apparatus, and methods for outputting NOx (SONOx) and ammonia (particularly ammonia slip) via an onboard integrated model management system with a controller. Exhaust aftertreatment systems are designed to treat exhaust gases and mitigate undesirable exhaust emissions, such as NOx emissions. Exhaust aftertreatment systems may include a diesel oxidation catalyst (DOC), a diesel particulate filter (DPF), a selective catalytic reduction (SCR) system, and possibly other components, an ammonia slip (ASC) catalyst (or AMOX). As exhaust gases pass through these different components, harmful pollutants and particles are removed from the exhaust gases. For example, an SCR may utilize a two-step process: a metering device injects a reducing agent into the exhaust stream, and then the exhaust stream passes through an SCR catalyst that converts the exhaust gases into less harmful components that can be released into the atmosphere (particularly, converting NOx into less harmful compounds). However, if an excess of this reducing agent (ammonia in one embodiment) is present in the exhaust gases or on the SCR catalyst (i.e., in a reservoir), the ammonia cannot react completely with the catalyst and is released into the atmosphere. "Ammonia slip" refers to excess ammonia that has not reacted with the catalyst, which may accumulate in aftertreatment systems and / or be released into the atmosphere. Some aftertreatment systems include AMOX to reduce any unreacted ammonia in the exhaust gas, but these AMOXes may not be entirely effective. Furthermore, in those embodiments where AMOX is omitted, proper management of the SCR and reductant is desired to reduce or eliminate the amount of ammonia slip. The systems, apparatus, and methods of this disclosure are operable to reduce the amount of ammonia slip while maintaining desired levels of NOx reduction.

[0043] Now refer to Figure 1 The diagram illustrates a system 100 according to an example embodiment. System 100 includes an engine 110, an aftertreatment system 120, an operator input / output (I / O) device 130, and a controller 140, wherein the controller 140 is communicatively coupled to each of the aforementioned components. Figure 1 In this configuration, system 100 is included in a vehicle. The vehicle can be any type of on-road or off-road vehicle, including but not limited to wheel loaders, forklifts, long-haul trucks, mid-range trucks (e.g., pickup trucks), cars, sports cars, tanks, aircraft, boats, and any other type of vehicle. In another embodiment, system 100 is embodied in a fixed device such as a generator or generator set.

[0044] Engine 110 can be any type of engine that produces exhaust gases, such as a gasoline, natural gas, or diesel engine, a hybrid engine (e.g., a combination of an internal combustion engine and an electric motor), and / or any other suitable engine. In the example shown, engine 110 is a diesel-powered compression ignition engine.

[0045] An aftertreatment system 120 is coupled to an engine 110, specifically in communication with the engine 110 for receiving exhaust gases. The aftertreatment system includes a diesel particulate filter (DPF) 121, a diesel oxidation catalyst (DOC) 122, a selective catalytic reduction (SCR) system 123, an ammonia oxidation catalyst (AMOX) 124, and a heater 125. The DOC 122 is configured to receive exhaust gases from the engine 110 and oxidize hydrocarbons and carbon monoxide in the exhaust gases. The DPF 121 is arranged or positioned upstream of the DOC 122 and is configured to remove particulate matter, such as soot, from the exhaust gases flowing in the exhaust gas stream. The DPF 121 includes an inlet and an outlet, where it receives exhaust gases and, after substantially filtering out particulate matter and / or converting particulate matter into carbon dioxide, discharges the exhaust gases at the outlet. In some implementations, the DPF 121 may be omitted.

[0046] The aftertreatment system 120 may also include a reductant delivery system, which may include a decomposition chamber (e.g., a decomposition reactor, reactor conduit, decomposition pipe, reactor tube, etc.) to convert the reductant into ammonia. The reductant may be, for example, urea, diesel exhaust fluid (DEF), Adblue®, urea aqueous solution (UWS), aqueousurea solution (e.g., AUS32, etc.), and other similar fluids. Diesel exhaust fluid (DEF) is added to the exhaust gas stream to aid catalytic reduction. Typically, the reductant can be injected upstream of the SCR 123 (or particularly the SCR catalyst 126) via a DEF metering device, such that the SCR catalyst 126 receives the mixture of reductant and exhaust gas. However, in other embodiments, the DEF metering device may inject the reductant at any point in the aftertreatment system, including within the SCR catalyst 126 itself. The reducing agent droplets then undergo evaporation, pyrolysis, and hydrolysis to form gaseous ammonia within the decomposition chamber, SCR catalyst 126, and / or exhaust duct system, exiting the aftertreatment system 120. The metering dispenser can have any configuration and structure for injecting the reducing agent into the exhaust aftertreatment system. The aftertreatment system 120 may also include an oxidation catalyst (e.g., DOC 122) fluidly coupled to the exhaust duct system to oxidize hydrocarbons and carbon monoxide in the exhaust gas. To properly facilitate this reduction, DOC 122 may need to be at a specific operating temperature. In some embodiments, this specific operating temperature is approximately between 200°C and 500°C. In other embodiments, the specific operating temperature is the temperature at which the conversion efficiency of DOC 122 exceeds a predefined threshold (e.g., HC is converted to less harmful compounds, referred to as HC conversion efficiency).

[0047] SCR 123 includes an SCR catalyst 126 and is configured to help reduce NOx emissions by accelerating a NOx reduction process between ammonia and NOx in the exhaust gas, which converts ammonia and NOx in the exhaust gas into diatomic nitrogen, water, and / or carbon dioxide. If the SCR catalyst 126 is not at or above a specific temperature, the acceleration of the NOx reduction process is limited, and SCR 123 may or may not operate at a specified efficiency level. In some embodiments, this specific temperature is approximately 200°C–300°C. The SCR catalyst 126 may be made of a combination of inactive materials and an active catalyst, such that the inactive material (e.g., a ceramic metal) directs the exhaust gas toward the active catalyst, which is any kind of material suitable for catalytic reduction (e.g., base metal oxides such as vanadium, molybdenum, tungsten, etc., or noble metals such as platinum). In some embodiments, AMOX 124 is included in the aftertreatment system. AMOX 124 is configured to address the ammonia slip problem by removing or attempting to remove excess ammonia from the treated exhaust gas before it is released into the atmosphere.

[0048] In some embodiments, the post-processing system 120 is configured as a dual SCR system. Reference is now made to... Figure 5 An example dual-catalyst (shown as a dual SRC catalyst) aftertreatment system 520 according to an example embodiment is shown. The dual-catalyst aftertreatment system 520 is substantially the same as the single SCR aftertreatment system 120, but includes a first SCR system 523 (also referred to as the “ignition SCR system”), which is positioned relatively closer to the engine 110 (i.e., upstream) than the (second) SCR 123 and DPF 121. Due to primary space constraints, the first SCR system 523 is relatively smaller in size (e.g., package / container and catalyst size) compared to the SCR 123. The first SCR system 523 is fluidly coupled to its own dedicated DEF metering device. The DEF metering device may have a similar structure and function to the reducing agent metering device described above. The SCR 123 is a relatively large SCR system and is fluidly coupled to its own dedicated DEF metering device as described above. Due to its proximity to the engine 110 and its size, the first SCR system 523 heats up relatively faster than the SCR 123. Subsequently, the first SCR system 523 may be able to rapidly convert NOx due to its smaller size, but packaging constraints prevent it from being the sole SCR system on the engine, as the smaller catalyst is insufficient to convert the desired amount of NOx associated with standard engine 110 operation. SCR system 123 is similar to the SCR system in a single SCR architecture, meaning the larger SCR system requires more time to heat to operating temperature, but is subsequently able to convert the amount of NOx associated with standard engine 110 operation.

[0049] In some embodiments, heater 125 is located in the exhaust flow path preceding aftertreatment system 120 and is configured to controllably heat the exhaust gas upstream of aftertreatment system 120. In some embodiments, heater 125 is located directly preceding DOC 122, while in other embodiments, heater 125 is located directly preceding SCR 123 or directly integrated into the SCR catalyst. Heater 125 can be any kind of external heat source, which can be configured to increase the temperature of the exhaust gas passing through it, which in turn increases the temperature of components in aftertreatment system 120, such as DOC 122 or SCR 123. Thus, heater 125 can be an electric heater, an induction heater, a microwave heater, or a heater that burns fuel (e.g., HC fuel). As shown here, heater 125 is an electric heater that draws power from the battery (or another power source, such as an alternator, supercapacitor, etc.) of system 100. Heater 125 can be controlled by controller 140 (e.g., turned on, turned off, switched to different power levels to change heater output power, etc.). Heaters can be positioned near the desired component to heat the component (e.g., DPF) by conduction (and possibly convection). Multiple heaters can be used with the exhaust aftertreatment system, and each heater can have the same or different construction (e.g., conduction, convection, etc.).

[0050] Still refer to Figure 1 An operator input / output (I / O) device 130 is also shown in conjunction with system 100. Operator I / O device 130 can be communicatively coupled to controller 140, allowing information to be exchanged between controller 140 and I / O device 130, wherein the information may involve... Figure 1 The determination of one or more components or controllers 140 (described below). Operator I / O device 130 enables the operator of system 100 to communicate with controller 140 and... Figure 1 The system 100 communicates with one or more components. For example, the operator input / output device 130 may include, but is not limited to, an interactive display, a touch screen device, one or more buttons and switches, a voice command receiver, etc.

[0051] System 100 includes multiple sensors. The sensors are coupled to controller 140, enabling controller 140 to monitor and acquire data indicative of the operation of system 100. In this regard, the sensors include a NOx sensor 128 and a temperature sensor 127. NOx sensor 128 is configured to acquire data indicating the amount of NOx at or approximately at its set location. Temperature sensor 127 acquires data indicating the approximate temperature of the exhaust gas at or approximately at its set location. In one embodiment, a first temperature sensor 127 is located upstream of the modeled SCR catalyst 126 portion, and a second temperature sensor 127 is located downstream of the modeled SCR catalyst 126 portion. In some of these embodiments, the first and second temperature sensors 127 are located outside the SCR catalyst 126, such that the first temperature sensor 127 is upstream of the entire SCR catalyst 126, and the second temperature sensor 127 is downstream of the entire SCR catalyst 126. In other embodiments of these examples, at least one of the first and second temperature sensors 127 is located within the SCR catalyst 126, such that the first temperature sensor 127 may be located upstream of the specific portion of the SCR catalyst 126 being modeled, rather than upstream of the entire SCR catalyst 126, and / or the second temperature sensor 127 may be located downstream of the specific portion of the SCR catalyst 126 being modeled, rather than downstream of the entire SCR catalyst 126. Furthermore, the system 100 includes at least one sensor for gas type (i.e., NOx or ammonia) located downstream of at least one portion of the SCR catalyst 126, and one or more sensors may be included upstream of the SCR catalyst 126 to monitor conditions at the catalyst inlet (e.g., the amount of NOx, the temperature of the exhaust gas entering the SCR catalyst 126, the mass flow rate of the exhaust gas at the SCR catalyst 126 inlet, etc.). However, it should be understood that the depicted locations, numbers, and types of sensors are illustrative only. In some embodiments, one or more sensors may be virtual sensors, such that one or more sensors estimate output variables (e.g., data indicating NOx quantity, data indicating approximate temperature, etc.) based on other operating parameters within the system. In other embodiments, sensors may be located in other locations, there may be more or fewer sensors than shown, and / or different / additional sensors may also be included in system 100 (e.g., pressure sensors, ammonia sensors, flow sensors, etc.).

[0052] Controller 140 is configured to at least partially control the operation of system 100 and associated subsystems such as engine 110, aftertreatment system 120, and operator input / output (I / O) devices 130. Communication between and within components can be via any number of wired or wireless connections. For example, wired connections may include serial cables, fiber optic cables, CAT5 cables, or any other form of wired connection. In contrast, wireless connections may include the Internet, Wi-Fi, cellular, radio, etc. In one embodiment, a controller local area network (CAN) bus provides the exchange of signals, information, and / or data. The CAN bus includes any number of wired and wireless connections. Because controller 140 can communicatively connect to... Figure 1 The system and components, so the controller 140 is configured to... Figure 1 One or more components shown receive data. Regarding... Figure 2 The structure and function of controller 140 are further described.

[0053] because Figure 1 The components are shown as being included in the vehicle, therefore the controller 140 can be configured as one or more electronic control units (ECUs). Figure 2 The functionality and structure of controller 140 are described in more detail below. Controller 140 may be separate from or included in at least one of a transmission control unit, an exhaust aftertreatment control unit, a powertrain control module, an engine control module, etc. In one embodiment, the components of controller 140 are combined into a single unit. In another embodiment, one or more components may be geographically distributed throughout the system. All these variations are intended to fall within the scope of this disclosure.

[0054] Now for reference Figure 2 This illustrates an example embodiment. Figure 1 A schematic diagram of the controller 140 of system 100. (See diagram below.) Figure 2 As shown, controller 140 includes processing circuitry 202 with processor 204 and memory 206, modeling circuitry 220, predictor circuitry 222, corrector circuitry 224, and communication interface 210. Controller 140 is configured or constructed to control various components of system 100 based on an integrated catalyst model in order to improve conventional methods of managing aftertreatment system 120 to maintain acceptable emissions with reduced ammonia slip.

[0055] In one configuration, modeling circuitry 220, predictor circuitry 222, and corrector circuitry 224 are embodied as a machine- or computer-readable medium storing instructions executable by a processor (e.g., processor 204). As described herein and in other uses, the machine-readable medium facilitates the performance of certain operations to achieve the reception and transmission of data. For example, the machine-readable medium can provide instructions (e.g., commands, etc.) to, for example, acquire data. In this regard, the machine-readable medium may include programmable logic defining the frequency of data acquisition (or data transmission). The computer-readable medium instructions may include code, which can be written in any programming language, including but not limited to Java and any conventional procedural programming language, such as the "C" programming language or similar programming languages. The computer-readable program code can be executed on one processor or multiple remote processors. In the latter case, the remote processors can be interconnected via any type of network (e.g., CAN bus, etc.).

[0056] In another configuration, modeling circuit 220, predictor circuit 222, and corrector circuit 224 are embodied as hardware units, such as electronic control units. Therefore, modeling circuit 220, predictor circuit 222, and corrector circuit 224 can be embodied as one or more circuit components, including but not limited to processing circuitry, network interfaces, peripheral devices, input devices, output devices, sensors, etc. In some embodiments, modeling circuit 220, predictor circuit 222, and corrector circuit 224 can take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (ICs), discrete circuits, system-on-a-chip (SOC) circuits, microcontrollers, etc.), telecommunications circuits, hybrid circuits, and any other type of "circuit". In this respect, modeling circuit 220, predictor circuit 222, and corrector circuit 224 can include any type of component for performing or facilitating the implementation of the operations described herein. For example, the circuits described herein can include one or more transistors, logic gates (e.g., NAND, AND, NOR, OR, XOR, NOT, XNOR, etc.), resistors, multiplexers, registers, capacitors, inductors, diodes, wiring, etc. Modeling circuit 220, predictor circuit 222, and corrector circuit 224 may also include programmable hardware devices, such as field-programmable gate arrays, programmable array logic, programmable logic devices, etc. Modeling circuit 220, predictor circuit 222, and corrector circuit 224 may include one or more memory devices for storing processor-executable instructions from modeling circuit 220, predictor circuit 222, and corrector circuit 224. One or more memory devices and the processor may have the same definitions as provided below regarding memory 206 and processor 204. In some hardware unit configurations, modeling circuit 220, predictor circuit 222, and corrector circuit 224 may be geographically distributed across various locations within a vehicle. Alternatively, and as shown, modeling circuit 220, predictor circuit 222, and corrector circuit 224 may be embodied in or within a single unit / housing, shown as controller 140.

[0057] In the illustrated example, controller 140 includes processing circuitry 202 having processor 204 and memory 206. Processing circuitry 202 may be constructed or configured to execute or implement the instructions, commands, and / or control processes described herein with respect to modeling circuitry 220, predictor circuitry 222, and corrector circuitry 224. The depicted configuration represents modeling circuitry 220, predictor circuitry 222, and corrector circuitry 224 as a machine or computer-readable medium storing instructions. However, as noted above, this illustration is not intended to be limiting, as other embodiments are contemplated in this disclosure, wherein at least one of the modeling circuitry 220, predictor circuitry 222, and corrector circuitry 224 is configured as a hardware unit. All such combinations and variations are intended to fall within the scope of this disclosure.

[0058] Processor 204 may be implemented as a single-chip or multi-chip processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. The processor may be a microprocessor. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration. In some embodiments, one or more processors may be shared by multiple circuits (e.g., modeling circuitry 220, predictor circuitry 222, and corrector circuitry 224 may include or otherwise share the same processor, which in some example embodiments may execute instructions stored or otherwise accessed via different regions of memory). Alternatively or additionally, the one or more processors may be configured to perform or otherwise perform certain operations independently of one or more coprocessors. In other example embodiments, two or more processors may be coupled via a bus to enable independent, parallel, pipelined, or multithreaded instruction execution. All such variations are intended to fall within the scope of this disclosure.

[0059] Memory 206 (e.g., memory, memory cell, storage device) may include one or more devices (e.g., RAM, ROM, flash memory, hard disk storage) for storing data and / or computer code to perform or facilitate the various processes, layers, and modules described herein. Memory 206 may be communicatively connected to processor 204 to provide processor 204 with computer code or instructions for performing at least some of the processes described herein. Furthermore, memory 206 may be or include tangible, non-transient volatile memory or non-volatile memory. Therefore, memory 206 may include database components, object code components, scripting components, or any other type of information structure for supporting the various activities and information structures described herein.

[0060] Communication interface 210 may include any combination of wired and / or wireless interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wired terminals) for data communication with various systems, devices, or networks configured to enable in-vehicle communication (e.g., communication between and within components of a vehicle) and, in some embodiments, out-of-vehicle communication (e.g., communication with a remote server via a telematics unit). For example, regarding out-of-vehicle / system communication, communication interface 210 may include Ethernet cards and ports for sending and receiving data via an Ethernet-based communication network and / or Wi-Fi transceivers for communication via a wireless communication network. Communication interface 210 may be configured to communicate via a local area network or a wide area network (e.g., the Internet) and may use various communication protocols (e.g., IP, LON, Bluetooth, ZigBee, radio, cellular, near-field communication).

[0061] Modeling circuit 220 is configured to generate a spatially resolved, and particularly discretized, axial model of the catalyst of aftertreatment system 120. Modeling circuit 220 is configured to estimate or determine the state of the catalyst using the generated spatially vectorized model of the catalyst. An axially resolved model of the catalyst refers to a model that estimates or determines the state of the catalyst at different portions of the catalyst by dividing or separating the catalyst into multiple parts or regions. In some embodiments, the catalyst being modeled is an SCR catalyst 126. In other embodiments, the catalyst being modeled is a combination of SCR catalyst 126 and AMOX 124. In the model described herein, modeling circuit 220 axially discretizes the catalyst model along an axis parallel or substantially parallel to the exhaust flow through catalyst 126. As described herein, for this model, "state" or "catalyst state" refers to the ammonia storage level or temperature value of the catalyst (i.e., the ammonia storage state or temperature state of the catalyst).

[0062] Now for reference Figure 3The image shows a visualization 300 of the axially resolved model (or distribution) of the SCR catalyst 126 and AMOX 124 by the modeling circuit 220 according to an exemplary embodiment. In this example, the axially resolved model of the SCR catalyst 126 shows that the SCR catalyst 126 has been divided into three parts: front, middle, and rear (where the rear part is located downstream relative to the exhaust gas flow direction). In this embodiment where the catalyst includes AMOX 124, AMOX 124 represents its own zone or section. So this example includes four sections. In other embodiments, the number of sections can be different (e.g., other numbers greater than zero, etc.). Furthermore, increasing the number of sections can be related to the overall model accuracy. However, increasing the number of sections can increase the processing power requirements on the controller 140. In addition, many control strategies that utilize these sections from the model cannot target the catalyst with an accuracy of more than 3-4 sections, so although increasing the number of sections improves the overall model accuracy, there are factors that prevent the number of sections from being increased beyond a certain amount.

[0063] Modeling circuitry 220 is configured to receive characteristics relevant to the operation of post-processing system 120 (e.g., SCR catalyst 126). These characteristics include the physical dimensions of post-processing system 120 (or its components, such as decomposer reactor tubes), the physical dimensions of SCR 123, the thermal mass of SCR catalyst 126, the mass of SCR catalyst 126, and other characteristics of post-processing system 120 that may affect performance. Generally, these characteristics are set or fixed such that they do not change during the model's lifetime.

[0064] Modeling circuit 220 is also configured to construct and adjust the state of the model (i.e., the ammonia storage on the catalyst, the temperature value of the catalyst) based on sensed values ​​from sensors. As described above and regarding temperature, temperature sensors 127 can provide data indicating the temperature of the components or exhaust gas in which they are located. For example, temperature sensors 127 can provide sensed values ​​of the exhaust gas temperature upstream and downstream of a specific section of the SCR catalyst 126, and modeling circuit 220 uses these sensed values ​​to inform the model. In one embodiment, based on the sensed values, modeling circuit 220 assigns modeled values ​​of temperature to each section based on the distance from the upstream and downstream sensors, such that the middle section (i.e., the section equidistant from the upstream and downstream sensors) is assigned the average of the sensed values ​​from the upstream and downstream sensors. In this respect, modeled values ​​can be assigned to these sections based on the gradient between the sensed values ​​from the upstream and downstream sensors. In one embodiment, this gradient is linear, such that the assigned modeled values ​​have a linear relationship with the distance of the catalyst section from the sensors. In other embodiments, the gradient is a non-linear relationship (e.g., an exponential relationship) such that the assigned modeling values ​​are assigned weighted values ​​that give more weight to those closer to the upstream or downstream sensor (e.g., the middle part is assigned a value closer to the sensed value from the upstream sensor).

[0065] In embodiments where sensors embedded within the catalyst (in addition to upstream and downstream sensors) are present, the modeling circuit 220 can also assign modeling values ​​to portions based on their proximity to the embedded sensors. These values ​​are close to actual values. In this respect, any portion directly adjacent to the embedded sensor can be assigned a modeling value based on the sensed value from the embedded sensor, and portions that are close but not directly adjacent are assigned a modeling value based on both the sensed value from the embedded sensor and the sensed values ​​from the upstream and / or downstream sensors. Thus, the modeling circuit 220 is capable of assigning modeling values ​​to portions of the catalyst using any number of sensors.

[0066] The modeling circuit 220 can also receive sensing values ​​from one or more NOx sensors 128. These sensing values ​​indicate the amount of NOx in the exhaust gas at different points throughout the aftertreatment system 120 and can be used by the modeling circuit 220 to inform the model, similar to how the model is informed of the catalyst temperature. The modeling circuit 220 receives sensing values ​​from NOx sensors 128 upstream and downstream of the catalyst. The modeling circuit 220 then assigns modeling values ​​for the amount of NOx at each section based on the distance from the upstream and downstream sensors, such that the middle section (i.e., the section equidistant from the upstream and downstream sensors) is assigned the average of the sensing values ​​from the upstream and downstream sensors. In this respect, the modeling values ​​can be assigned to these sections based on the gradient between the sensing values ​​of the upstream and downstream sensors. In one embodiment, this gradient is directly linear, such that the assigned modeling value has a linear relationship with the distance of the section from the sensor. In another embodiment, the gradient has a non-linear relationship (e.g., an exponential relationship), such that the assigned modeling values ​​are assigned weighted values ​​that give more weight to sensors closer to the upstream or downstream sensors (e.g., the middle sensor is assigned a value closer to the sensed value from the upstream sensor). Modeling circuitry 220 can model, estimate, or otherwise determine the ammonia storage for each section of the catalyst by using modeling values ​​of NOx for each section. Specifically, for SCR catalyst 126, NOx in the exhaust gas reacts with ammonia stored in SCR catalyst 126, such that by modeling the amount of NOx at each section, modeling circuitry 220 can determine an approximate ammonia storage at each section based on how much NOx is reduced from one section to another. This determination may also include other factors such as engine output NOx, rationing, etc.

[0067] Therefore, in other words, the modeling circuit 220 uses sensed values ​​from sensors disposed in the post-processing system to generate “modeling values” (i.e., estimates based on sensed values) for each part of the catalyst. When a sensor is not directly disposed in that part, the modeling circuit 220 extrapolates the sensed values ​​to determine or estimate the corresponding values ​​(and thus, “modeling values”) in the respective parts of the catalyst. Modeling values ​​can be determined based on sensor placement in various ways as described above (e.g., sensor readings can be assigned to parts within a predefined distance of the sensor, the average of two sensor readings can be assigned to parts between the two sensors, gradients can be applied, etc.).

[0068] In some embodiments, modeling circuitry 220 defines portions of the catalyst model of the same size (i.e., length) based on the size of the catalyst. In other embodiments, modeling circuitry 220 defines portions of the catalyst model of unequal size (i.e., length), for example by defining a shorter portion at the front of the catalyst, in order to increase the model resolution (i.e., model accuracy) towards the front of the catalyst and decrease the model resolution towards the rear of the catalyst. In these embodiments, by increasing the model resolution of the front portion, modeling circuitry 220 balances the computational burden on controller 140 in a desired manner. In other embodiments, modeling circuitry 220 defines portions of the catalyst model based on the location of sensors (temperature sensor 127 or NOx sensor 128) throughout the catalyst. In this case, the temperature sensor location (or NOx or other sensor location) indicates the breakpoints of the portions of the catalyst model.

[0069] While the reference to modeling circuitry 220 is primarily directed to post-processing system 120 with a single SCR architecture, modeling circuitry 220 is configured to develop models for embodiments in which post-processing system 120 has a dual SCR architecture. In these embodiments, modeling circuitry 220 is constructed or configured to develop models for each of the smaller SCR system (as described above) and the larger SCR system based on the principles and methods previously described. In some of these embodiments, models for each system in the smaller and larger SCR systems are used independently of each other by other circuitry (e.g., predictor circuitry 222, corrector circuitry 224), such that controller 140 issues commands affecting the smaller SCR system without considering the model of the larger SCR system, and vice versa. In other embodiments of these embodiments, models for each system in the smaller and larger SCR systems are used in combination with other circuitry, such that controller 140 issues commands based on inputs from the models for the smaller and larger SCR systems.

[0070] Predictor circuit 222 is configured to compare determined modeling values ​​for each part of the catalyst with predetermined values ​​and, in response to the comparison, issue commands to components of system 100. The determined modeling values ​​for SCR catalyst 126 may be the temperature of SCR catalyst 126 (or a portion thereof) or the amount of ammonia stored in SCR catalyst 126 (or a portion thereof). The modeled catalyst (or component) may be SCR catalyst 126, AMOX 124, DOC 122, and / or DPF 121. In this respect, the determined modeling values ​​for SCR catalyst 126 may be determined modeling values ​​for a specific part of SCR catalyst 126, or a cumulative or average of determined modeling values ​​for multiple parts of SCR catalyst 126.

[0071] Predictor circuit 222 compares the determined modeling value with a predetermined value. In some embodiments, the predetermined value is a target value for a state (e.g., ammonia storage level, temperature), a threshold value for a state (e.g., ammonia storage level, temperature), or a combination of both. A threshold value for a state refers to a value at which the determined modeling value is to remain above (if the threshold is a minimum) or below (if the threshold is a maximum) a state, while a target value refers to a specific value at which the determined modeling value attempts to reach a state. As discussed later with reference to corrector circuit 224, the predetermined value can be dynamic and adjusted throughout the operation of system 100 so that the predetermined value more closely represents the current performance. Therefore, in addition to the methods for updating the predetermined value described below, the predetermined value can also be adjusted based on expected engine 110 load, environmental conditions (e.g., temperature, humidity, etc.), or sensor readings. If the predetermined value is a target value, the target value can be set based on the expected operation of SCR 123. For example, if the state under discussion is temperature, the target value could be a temperature at which the NOx conversion efficiency of SCR 123 is at or above a certain value (e.g., 95%), or it could be the desired temperature of the system. Alternatively, if the state under discussion is ammonia storage, the target value could be set as an ammonia storage level sufficient to achieve or exceed a certain value (e.g., 95%) for the NOx conversion efficiency.

[0072] Similarly, if the predetermined value is a threshold, the threshold can be set based on the expected operation of SCR 123. For example, if the state under discussion is temperature, the threshold can be set to the temperature at which SCR 123 cannot achieve the expected NOx conversion efficiency (e.g., 95%) below that temperature. Alternatively, if the state under discussion is ammonia storage, the threshold could be an ammonia slip threshold.

[0073] In those embodiments where the predictor circuit 222 utilizes a combination of target values ​​and thresholds, the predictor circuit 222 utilizes target values ​​and thresholds from one or more states. For example, the predictor circuit 222 can compare the state of the SCR catalyst 126 with a target temperature value and a threshold for ammonia storage, or a target value for ammonia storage and a temperature threshold.

[0074] Predictor circuit 222 is configured to take action or issue a command in response to a comparison of a determined modeling value of SCR catalyst 126 with a predetermined value. This command may be one or more of the following: changing the amount of DEF from the metering unit (i.e., increasing or decreasing the metered dose of reduction), changing the amount of engine output NOx (EONOx) by reducing power output (e.g., increasing EGR), and activating heater 125. Changing the amount of EONOx (i.e., the amount of NOx in the exhaust gas when it enters aftertreatment system 120) may include changing the air / fuel ratio (where increasing the ratio by increasing the proportion of air in the intake reduces the amount of EONOx, and vice versa), adjusting the fuel supply (where increasing the fuel supply increases the amount of EONOx, and vice versa), and / or changing the timing of fuel injection (where delaying the timing reduces EONOx). The command may also include adjusting engine operation, such as changing the load on engine 110 (where an increased load results in a higher engine output exhaust temperature, and vice versa), changing (e.g., via an EGR system) the amount of exhaust gas redirected back to the engine (where an increased EGR reduces the combustion temperature in engine 110, thereby reducing the engine output exhaust temperature, and vice versa), and so on.

[0075] In an illustrative example where the monitored state is temperature, if a comparison of the temperature of a portion of the SCR catalyst 126 with a target temperature value indicates that the portion of the SCR catalyst is too cold (i.e., the temperature is below a temperature threshold), then the predictor circuit 222 commands one or more components of the system 100 to increase the temperature of the affected portion of the SCR catalyst 126. The predictor circuit 222 determines the component to be commanded and the command to be issued based on the relative position of the portion along the SCR catalyst. For example, if the too-cold portion of the SCR catalyst 126 is towards the front of the SCR catalyst 126 (i.e., near the exhaust gas inlet), the predictor circuit 222 may prioritize commands that more effectively affect the front of the SCR catalyst 126, such as increasing the engine output exhaust temperature by influencing the EGR amount. In another example, if the affected portion of the SCR catalyst faces the middle or rear of the SCR catalyst 126 (i.e., away from the exhaust inlet), the predictor circuit 222 may prioritize commands that more effectively affect the middle or rear of the SCR catalyst 126, such as heater 125, or may prioritize commands that more effectively affect the front of the SCR catalyst 126, while amplifying the effect to affect both the middle and rear of the SCR catalyst 126 (e.g., increasing the engine output exhaust temperature to a relatively greater extent).

[0076] Alternatively, in the same example, predictor circuit 222 may, in response to determining that a portion of the SCR catalyst 126 is too cold, issue a command to reduce the amount of EONOx, thereby maintaining a low SONOx level even if the SCR 123 reduces NOx with potentially lower-than-expected efficiency. In this case, predictor circuit 222 may adjust the strength of the issued command (i.e., the requested amount of change) based on the location of the affected portion of the SCR catalyst 126. For example, if the overcooled affected portion of the SCR catalyst 126 is located at the front of the SCR catalyst 126 (i.e., near the exhaust gas inlet), predictor circuit 222 may issue a command to reduce EONOx by a greater margin than if the affected portion of the SCR catalyst 126 were located at the rear of the SCR catalyst 126 (i.e., away from the exhaust gas inlet), since the front of the SCR catalyst 126 performs most of the NOx reduction. In this case, the less efficient front portion has a greater negative impact on the overall reduction efficiency of the SCR 123.

[0077] In another exemplary example where the monitored state is ammonia storage, if a comparison of the ammonia storage amount in a portion of the SCR catalyst 126 with an ammonia storage threshold indicates that that portion of the SCR catalyst has too little ammonia (i.e., the storage amount is below the desired threshold amount), then predictor circuit 222 commands one or more components of system 100 to increase the amount of ammonia stored in the affected portion of the SCR catalyst 126. These commands could be, for example, increasing the amount of DEF dispensed or indirectly increasing the ammonia amount by decreasing the amount of EONOx, which would reduce the amount of ammonia removed by the reaction (assuming the amount of DEF dispensed remains constant). Predictor circuit 222 can modify or prioritize commands based on the relative position of the portion along the SCR catalyst 126. For example, if the portion of the SCR catalyst 126 with too little stored ammonia faces the front of the SCR catalyst 126 (i.e., near the exhaust gas inlet), the predictor circuit 222 can prioritize commands that directly add ammonia to the SCR catalyst 126 (e.g., increase the DEF metering), because the affected portion is one of the first parts to receive the exhaust gas, meaning it is the first part to receive any other contents included in the exhaust gas (e.g., ammonia from the DEF). Alternatively, if the affected portion faces the middle or rear of the SCR catalyst 126 (i.e., away from the exhaust gas inlet), the predictor circuit 222 can prioritize commands that indirectly affect the stored ammonia (e.g., reduce EONOx), because these commands are more likely to have the desired effect on the portion of the SCR catalyst 126 away from the exhaust gas inlet, as these commands are less related to the contents carried in the exhaust stream (e.g., ammonia from the DEF). Furthermore, if the affected portion faces the middle or rear of the SCR catalyst 126, the predictor circuit can decide to utilize the direct addition of ammonia, but at a higher volume than the affected portion facing forward, in order to account for the ammonia-carrying exhaust gas passing through other parts of the SCR catalyst 126 before reaching the affected portion.

[0078] In another illustrative example where the monitored states are a combination of temperature and ammonia storage, predictor circuit 222 can prioritize commands affecting these two states to more effectively manage the performance of SCR 123 and ammonia slip. For example, if the predictor circuit determines, based on a comparison of the state of a portion of SCR catalyst 126 with predetermined values ​​for temperature and ammonia storage, that portion of SCR catalyst 126 is too cold and has too much stored ammonia, predictor circuit 222 can issue commands to increase the temperature and decrease the ammonia storage. In this example, predictor circuit 222 can command an increase in the fuel supply to engine 110, which not only increases the combustion temperature (and thus the engine output exhaust temperature) but also increases the amount of EONOx. The higher engine output exhaust temperature raises the temperature of the affected portion of SCR catalyst 126, while a greater amount of EONOx reacts with the stored ammonia, reducing the total amount of ammonia stored in the affected portion.

[0079] The predictor circuit 222 can also monitor multiple catalytic converter sections and issue commands that simultaneously affect multiple sections. For example, the predictor circuit 222 can determine, based on a comparison of the state of the first section of the SCR catalytic converter 126 with a predetermined value and a comparison of the state of the second section of the SCR catalytic converter 126 with a predetermined value, that the first section is too cold (e.g., temperature below a threshold) and the second section has too little stored ammonia (below a threshold). In this example, the predictor circuit 222 can prioritize heating commands (e.g., engaging heater 125) that may not increase or attempt not to increase EONOx, in order to warm the first section without inhibiting the limited reduction capacity of the second section. Similarly, the predictor circuit 222 can prioritize ammonia increase commands that do not decrease or attempt not to decrease exhaust gas temperature (e.g., increasing the DEF metering level), in order to increase the amount of stored ammonia on the second section without impairing the warming capacity of the first section.

[0080] In some embodiments, the predictor circuit 222 establishes different predetermined values ​​for each section of the SCR catalyst 126 (which may be the same or different for each section). For example, the target value for the front section of the SCR catalyst 126 may be relatively high regarding ammonia storage to account for the increased NOx reduction occurring at the front section of the SCR catalyst. However, the target value for the rear section of the SCR catalyst 126 may be relatively low (or even zero) to act as a buffer against any excess ammonia remaining in the exhaust stream through the SCR catalyst 126, thereby absorbing some of that unreacted ammonia into the reservoir rather than allowing ammonia to escape.

[0081] The predictor circuit 222 can also issue commands based on modeled values ​​of one or more portions of a plurality of catalysts compared to one or more predetermined values ​​(e.g., expected values, thresholds, target values). For example, as described above, the aftertreatment system can be configured as a dual-catalyst aftertreatment system 520, comprising a first SCR system 523 located near the engine 110 and having an SCR 123 located downstream of the smaller SCR system, with a DPF 121 located between the two SCR systems. One or more sensors can be located near the first SCR system 523 to obtain modeled values ​​(e.g., ammonia storage) for portions of the first SCR system 523, similar to those described above for catalysts (e.g., SCR catalyst 123). The downstream SCR catalyst 123 can be divided into multiple portions, and modeled values ​​can be determined for these portions. Based on the determined modeled values ​​for the portions of the upstream and downstream catalysts (in this case, the SCR catalyst), the predictor circuit 222 can issue various commands. For example, predictor circuit 222 can control the amount of reductant dispensed to the upstream catalyst based on the ammonia load experienced by the upstream catalyst relative to the ammonia load experienced by the downstream catalyst, as determined by modeling values, different from the amount dispensed to the downstream catalyst. As an example, modeling values ​​for the front portion of the upstream catalyst may indicate low ammonia storage (i.e., below a threshold), while modeling values ​​for the front portion of the downstream catalyst may indicate high ammonia storage (i.e., above a threshold). Therefore, the controller commands an increase in the amount dispensed to the upstream catalyst and a decrease in the amount dispensed to the downstream catalyst to allow ammonia storage to accumulate in the front portion of the upstream catalyst. Additionally, as described above, similar commands (e.g., based on temperature) can be provided to the upstream catalyst. In some embodiments, the other catalyst (e.g., the first SCR system 523) may have a dedicated controller for controlling the dispenser and potentially other components. Thus, in this embodiment, there may be one controller for each SCR catalyst system. Each of these controllers may have the same or similar structure as described herein with respect to controller 140. In this embodiment, the controllers “talk” / communicate with each other to optimize overall system performance. In other words, the upstream controller knows the storage capacity of the downstream catalyst, and the downstream controller knows the storage information of the upstream catalyst, and provides commands to be adjusted to optimize overall performance.

[0082] Regarding the dual-catalyst aftertreatment system 520, the predictor circuit 222 can issue commands to prioritize one SCR system or otherwise utilize one SCR system instead of the other until specific conditions are met. In one embodiment, the specific condition is that the catalyst (or one or more desired sections of the catalyst) reaches a desired operating temperature. In another embodiment, the specific condition is the amount of ammonia stored on the catalyst (or one or more sections thereof) relative to an ammonia storage threshold. In yet another embodiment, the specific condition is a combination of temperature and ammonia or reductant storage. As described above, the size and location of the first SCR system 523 allow it to reach its operating temperature relatively earlier than the downstream SCR 123. Typically, it is desirable for high concentrations of NOx to enter the DPF 121 to passively regenerate the filter. In this way, the DPF 121 cleans itself rather than requiring system 100 to enter a high-heat mode to burn off accumulated soot. If the first SCR system 523 is used to convert a large amount of EONOx, not much NOx is available to help clean the DPF 121. This leads to more frequent high-temperature regeneration events in order to keep DPF 121 clean, which results in fuel loss and increased hydrothermal aging / degradation of the catalyst.

[0083] In one example, predictor circuit 222 commands to utilize the first SCR system 523 until the downstream SCR 123 reaches operating temperature (e.g., during the initial preheating cycle of system 100), at which point predictor circuit 222 commands to shut off the DEF dosing of the first SCR system 523. However, if SCR 123 has no (or more than a threshold amount) stored ammonia when a “switch” is performed (i.e., reducing or shutting off the dosing to the first SCR system 523), a poor total SONOx may exist before sufficient ammonia storage accumulates on SCR 123. To address this issue, predictor circuit 222 is configured to delay the dosing shutdown command (or dosing reduction command) to the first SCR system 523 until the downstream SCR 123 has sufficient ammonia storage (greater than a predefined threshold amount). For example, if the modeled temperature of SCR 123 is higher than a predefined threshold for operation, but the modeled ammonia storage level of SCR 123 is lower than the predefined threshold for operation, then predictor circuit 222 determines to delay the dosing shutdown command. When the modeled ammonia storage level of SCR 123 is higher than the predefined threshold for operation, predictor circuit 222 can send a dosing shutdown command to the upstream first SCR system 523. In this case, due to the lower total reduction capacity of the first SCR system 523, predictor circuit 222 can also command a lower EONOx (e.g., during the initial preheating cycle).

[0084] Furthermore, in this example embodiment, predictor circuit 222 can determine to re-engage the first SCR system 523 based on modeled and / or sensed values ​​for system 100. For example, if current conditions are particularly challenging due to abrupt temperature or EONOx transients (e.g., a sharp increase due to frequent hard acceleration), or if the downstream catalyst (i.e., SCR 123) is degraded due to hydrothermal aging or chemical poisoning, predictor circuit 222 can re-engage the first SCR system 523 (e.g., issuing a command to restore DEF dosing to the first SCR system 523) to balance the burden of NOx reduction between the first SCR system 523 and SCR 123. In this way, predictor circuit 222 allows the system to maintain the desired overall system output emissions (e.g., SONOx) even in the event of component degradation or failure. In another example, if it is desired to operate the engine at a higher EONOx level, predictor circuit 222 can utilize both the first SCR system 523 and SCR 123 to maintain the desired SONOx. This is likely the case if there is a fault in an engine component that causes engine 110 to operate in a “protection mode” with higher ENOx levels, which allows system 100 to maintain emission performance until the vehicle can be repaired.

[0085] The calibrator circuit 224 is configured to adjust the expected values ​​of the state of the post-processing system 120 based on feedback from sensors and compare the adjusted values ​​with the expected values ​​to identify faults in the system 100. These expected values ​​may be predetermined values ​​(i.e., target values, thresholds) of the predictor circuit 222, although the calibrator circuit 224 and the predictor circuit 222 may operate independently of each other. These expected values ​​of the state (i.e., setting reference values ​​for comparison) can be established when the system 100 is first started during its life cycle, when the system 100 is first started during use, or at any other time during the life cycle of the system 100. In some embodiments, the expected values ​​of the state are established via user commands (i.e., via I / O device 130). These states include temperature and ammonia storage level.

[0086] As used for corrector circuit 224, the desired state refers to the value of the state in which the aftertreatment system 120 (and in a particular embodiment, SCR 123 and SCR catalyst 126) is expected to perform. For example, the desired temperature is the temperature at which SCR 123 has an acceptable or desired NOx conversion efficiency (e.g., 95%). If the state is ammonia storage, the desired value is the amount of ammonia stored on (or a portion of) SCR catalyst 126 with SCR 123 having an acceptable or desired conversion efficiency (e.g., 95%) and / or ammonia slip (i.e., ammonia remaining unreacted and released into the atmosphere in the exhaust stream) is maintained at an acceptable or desired level (e.g., XX%).

[0087] The calibrator circuit 224 sets the desired value for the set state and then adjusts the desired value based on feedback from the sensors. Because the desired value represents the state in which the aftertreatment system 120 operates as expected, it can be adjusted to continue representing the state in which the aftertreatment system 120 operates as expected as components in the aftertreatment system 120 age or wear. For example, over time, the SCR catalyst 126 may wear down and lose some conversion efficiency, requiring higher temperatures (i.e., above 250°C) to achieve acceptable NOx conversion efficiency. Therefore, if the desired temperature value is not adjusted during the lifespan of the SCR catalyst 126, the desired value will no longer represent the state in which the SCR catalyst 126 reduces NOx as expected.

[0088] The corrector circuit 224 determines the adjustment to the desired value based on a comparison between the expected value and the actual value of the sensed value. For example, if the temperature of the SCR catalyst 126 (which can typically be given as the temperature of the SCR catalyst 126, the temperature of most parts of the SCR catalyst 126, or the average of the parts of the SCR catalyst 126) is at the desired value (e.g., 250°C), the corrector circuit 224 can expect the NOx conversion efficiency sensed by the NOx sensor 128 to be at or near the desired value (e.g., 95%). Therefore, if the actual sensed value from the NOx sensor 128 differs from this desired value (e.g., 85%), the corrector circuit 224 determines the desired value to be adjusted. In some embodiments, the corrector circuit 224 only makes adjustments when the difference between the desired value and the actual value exceeds a threshold. This threshold can be an absolute amount (e.g., 0.001 grams of difference) or a relative amount (e.g., 10% difference). The adjustment amount is determined based on an algorithm incorporated into the corrector circuit 224.

[0089] Now for reference Figure 6An example flowchart of a process 600 for adjusting a model of one or more catalysts in system 100 is provided. Process 600 may be stored in corrector circuit 224 (or, in memory 206, for execution by corrector circuit 224), and may be selectively run or executed by corrector circuit 224. Process 600 may include one or more algorithms, models, lookup tables, etc., to facilitate the execution and completion of process 600. As input, process 600 acquires sensed values ​​and compares the sensed values ​​with a “nominal” model (i.e., a model that nominally matches the currently operating system 100). The current nominal model can be selected from one or more models. Figure 6 As shown, these models include, but are not limited to: a "nominal" model, representing the previously selected nominal model; a "severely aged" model, representing a system operating with aged components; a "high DEF dispenser error" model, representing a system operating with a faulty DEF injector; and a "high NOx sensor error" model, representing a system operating with a sensor having bias or gain errors. The calibrator circuit 224 can determine which model (or models) to select as the nominal model based on the determination of which model best matches (i.e., has the lowest error) when compared with the sensed values ​​of system 100. The determination of the lowest error can be based on error calculation for a single modeling value (e.g., temperature) or the sum of errors for multiple modeling values ​​(e.g., temperature and ammonia storage). If based on the sum of errors for multiple modeling values, the determination can treat the error for each modeling value equally (i.e., 1:1), or the errors can be weighted differently (e.g., more weighted than the error in the temperature-to-ammonia storage modeling value to specifically identify the model that more accurately models ammonia storage). Furthermore, the calibrator circuit 224 can utilize an extended Kalman filter or other similar control techniques to slowly adjust model parameters and / or values ​​over time based on available sensors. In some embodiments, the calibrator circuit 224 continues to monitor the error in the modeling values ​​after selecting a nominal model and making corrections / adjustments, and if the error in the modeling values ​​continues to increase, the calibrator circuit 224 can “undo” any corrections made based on the previously selected nominal model. This continuous monitoring is particularly important for current NOx sensors, as current NOx sensors may be cross-sensitive to ammonia, so if the calibrator circuit 224 adjusts based on the impression from a high sensing value from the NOx sensor indicating a high amount of NOx (which would indicate too little ammonia in system 100), but the high sensing value actually indicates a high amount of ammonia (which would indicate too much ammonia in system 100), the calibrator circuit 224 can remedy this through continuous monitoring.

[0090] Once the calibrator circuit 224 has selected the nominal model, it can compare the modeled value of temperature or ammonia storage with the sensed value and modify one or more parameters (e.g., reaction rate, thermal mass of SCR 123, material properties of components in the aftertreatment system 120, etc.) based on the comparison. Furthermore, the calibrator circuit 224 can modify one or more modeled values ​​(e.g., ammonia storage level, temperature) based on the comparison. The calibrator circuit 224 determines which modeled values ​​to adjust based on the compared values ​​to determine whether the error is more likely due to ammonia slip or NOx slip. For example, if the algorithm initially determines (based on the comparison) that it is ammonia slip, the calibrator circuit 224 will increase the modeled value of ammonia storage. Alternatively, if it is initially determined to be NOx slip (i.e., above an acceptable SONOx level), the calibrator circuit 224 will decrease the modeled value of ammonia storage. Functionally, the difference results in a relatively equal adjustment (i.e., the greater the difference, the greater the adjustment).

[0091] Once the corrector circuit 224 determines the adjustment value, in some embodiments, it uses this value to diagnose faulty components in the post-processing system 120. Because the adjustment value captures the current state of the post-processing system 120, the difference between the current state and a previous state of the post-processing system 120 can be determined by comparing the adjustment value with an expected value that captures the state of the post-processing system 120 at a previous point in time. Although the corrector circuit 224 can expect to see a certain amount of difference over time due to the expected aging of components, if the corrector circuit 224 determines that the difference is drastic (i.e., greater than a predefined error threshold), it can determine that an error exists in the system 100 and trigger a corresponding fault flag (e.g., activate a fault code, trigger a fault indicator light, etc.). In some embodiments where the aftertreatment system 120 is a dual-catalytic converter aftertreatment system 520, the corrector circuit 224 may, in response to the determination of the presence of an error, issue a command to utilize the first SCR system 523 and SCR 123 to address some issues that may accompany the error in system 100 (e.g., higher EONOx due to a component failure in engine 110).

[0092] In some of these embodiments, the error threshold is a dynamic threshold, allowing the corrector circuit 224 to adjust and change the error threshold to account for operational changes due to aging, environmental factors, or some other anticipated event. For example, as components of the aftertreatment system 120 age, the corrector circuit 224 may increase the error threshold (i.e., require a larger difference to satisfy) to account for anticipated changes in the performance of the SCR catalyst 126 accompanying aging. The amount of increase in the error threshold may be based on a lookup table that provides values ​​based on anticipated differences in component aging.

[0093] Alternatively, the corrector circuit 224 can maintain a substantially constant error threshold throughout the entire lifespan of the system 100. The corrector circuit 224 can then monitor the rate of change of the difference between the adjusted value and the expected value, rather than the total amount of change. In this embodiment, the expected value is set or established at the beginning of each duty cycle to provide a more relevant rate of change. As mentioned above, because the adjusted value may change during the lifespan of the system 100 due to anticipated aging, the corrector circuit 224 can anticipate some amount of change in the adjusted value on a near-constant basis. However, because this amount of change is anticipated, any change that significantly exceeds the anticipated amount could indicate a faulty or malfunctioning component in the system 100.

[0094] Once the calibrator circuit 224 determines that there is an erroneous or faulty component, it can work with sensors to identify the specific component or type of component (i.e., aftertreatment system 120 components, engine 110 components, etc.). For example, if the ammonia storage level has exceeded the error threshold and the NOx sensor 128 indicates an unacceptably high SONOx value, the calibrator circuit 224 can determine that the SCR catalyst 126 is degrading due to an abnormally high level of stored ammonia, while still failing to reduce NOx to an acceptable level.

[0095] In some embodiments, the corrector circuit 224 works in conjunction with the predictor circuit 222 by providing an adjustment value to the predictor circuit 222, which then uses this adjustment value to update a predetermined value for establishing the target value or threshold of the SCR catalyst 126 state. Therefore, the predictor circuit 222 is able to more effectively issue commands to various system 100 components to manage the performance of the post-processing system 120 because the predetermined values ​​used to make decisions about these commands are more closely aligned with the current performance of the system 100.

[0096] Now for reference Figure 4This diagram illustrates a flowchart of managing NOx and ammonia in an exhaust aftertreatment system according to an exemplary embodiment. Method 400 begins at step 410, where controller 140 receives information about the operation of system 100, including sensed values ​​from sensors (e.g., NOx, temperature, exhaust flow, etc.), load on engine 110, information about environmental conditions (e.g., temperature, humidity, etc.), and / or other information about the operation of system 100. The information from step 410 serves as input to steps 420 and 430. At step 420, controller 140 uses the input from step 410 via modeling circuitry 220 to generate or inform an axially resolved model of the catalyst (in this example, SCR catalyst 126). At step 430, controller 140 uses the input from step 410 via corrector circuitry 224 to update the model to improve the overall effectiveness of method 400. The method then proceeds to step 440, where controller 140 actively manages the aftertreatment system 120 (specifically, the SCR catalyst 126) based on modeling circuitry 220 via predictor circuitry 222 to maintain acceptable SONOx levels and reduce ammonia slip. Finally, method 400 proceeds to step 450, where controller 140 issues commands to components of system 100 based on the determination made by predictor circuitry 222 at step 440. In some embodiments, steps 440 and 450 may be combined into a single step.

[0097] Furthermore, while the modeling circuit 220 primarily references the modeling circuitry providing a model of the SCR catalyst 126, which typically has monitoring states for NOx reduction and ammonia storage, the modeling circuitry 220 can be configured to generate a similar axially resolved model of the DOC 122, which typically has monitoring states for soot accumulation and associated regeneration events on the DOC 122. In these soot-related embodiments, the monitoring state is the amount of soot accumulation, such that the monitoring state of the modeled DOC 122 is the amount of soot accumulation on each section. The modeling circuitry 220 develops and updates the axially resolved model of the DOC 122 based on sensed values ​​from sensors related to the exhaust gas flow rate and pressure through the sections of the DOC 122 (because soot accumulation restricts flow and increases pressure). Therefore, in these soot-related embodiments, the commands issued by the predictor circuitry 222 are primarily thermal management commands for soot removal (i.e., increasing the temperature of the exhaust gas passing through the aftertreatment system 120 to burn off the accumulated soot). As discussed above regarding the NOx reduction and ammonia storage embodiments, the predictor circuit 222 can utilize the additional utility from modeling multiple sections of the DOC 122 to more effectively regenerate those sections of the DOC 122 most affected by soot accumulation. For example, if there is a greater amount of soot accumulation in the rear section of the DOC 122 than in the front section, increasing the exhaust temperature would not be an effective regeneration strategy, because the hot exhaust will most directly affect the front section of the DOC 122, which in this example does not require regeneration.

[0098] Similarly, the principles and methods discussed herein are also applicable to generating an axially resolved model of DPF 121 that focuses on, for example, hydrocarbon (HC) accumulation on various portions of DPF 121. In these HC-related embodiments, the monitored state is the amount of HC accumulation, such that the monitored state of the modeled DPF 121 is the amount of HC accumulation on each portion. Modeling circuit 220 develops and updates the axially resolved model of DPF 121 based on sensed values ​​from sensors related to exhaust flow and pressure on various portions of DPF 121 (when HC accumulation restricts flow and increases pressure). Therefore, in these HC-related embodiments, the commands issued by predictor circuit 222 are primarily thermal management commands (i.e., increasing the temperature of the exhaust gas passing through aftertreatment system 120 to burn off the accumulated HC). As discussed above regarding the NOx reduction and ammonia storage embodiments and the soot-related embodiments, the predictor circuit 222 can utilize the additional utility from modeling multiple sections of the DPF 121 to more effectively regenerate those sections of the DPF 121 most affected by soot accumulation. For example, if there is a greater amount of soot accumulation in the front section of the DPF 121 than in the rear section, increasing the exhaust temperature would be a particularly effective regeneration strategy, as the hot exhaust will most directly affect the front section of the DOC 122, which in this example is the section most in need of regeneration.

[0099] As used herein, the terms “approximately,” “about,” “substantially,” and similar terms are intended to have a broad meaning consistent with common and accepted usage by those skilled in the art to which the subject matter of this disclosure relates. Those skilled in the art, upon review of this disclosure, will understand that these terms are intended to allow for the description of certain features described and claimed, without limiting the scope of those features to the precise numerical ranges provided. Therefore, these terms should be interpreted as indicating that non-substantial or irrelevant modifications or alterations to the described and claimed subject matter are considered to be within the scope of the disclosure set forth in the appended claims.

[0100] It should be noted that the terms “exemplary” and their variations used herein to describe various embodiments are intended to indicate that these embodiments are possible examples, representations or illustrations of possible embodiments (and these terms are not intended to imply that these embodiments are necessarily special or superlative examples).

[0101] As used herein, the term “coupled” and its variations refer to two components being directly or indirectly connected to each other. This connection can be static (e.g., permanent or fixed) or movable (e.g., removable or releasable). Such a connection can be achieved by directly coupling two components to each other, by coupling two components to each other using one or more separate intervening components, or by coupling two components to each other using an intervening component that forms a single integral body with one of the two components. If “coupled” or its variations are modified by an additional term (e.g., directly coupled), the general definition of “coupled” provided above is modified by the simple linguistic meaning of the additional term (e.g., “directly coupled” means a connection of two components without any separate intervening component), resulting in a narrower definition than the general definition of “coupled” provided above. This coupling can be mechanical, electrical, or fluid. For example, circuit A communicatively “coupled” to circuit B can mean that circuit A communicates directly with circuit B (i.e., without an intermediary) or indirectly with circuit B (e.g., through one or more intermediaries).

[0102] References to the location of elements herein (e.g., “top,” “bottom,” “above,” “below”) are used only to describe the orientation of the various elements in the accompanying drawings. It should be noted that the orientation of the various elements may differ according to other exemplary embodiments, and such variations are intended to be included in this disclosure.

[0103] Despite Figure 2 Various circuits with specific functions are illustrated herein; however, it should be understood that controller 140 may include any number of circuits for performing the functions described herein. For example, the activities and functions of modeling circuit 220, predictor circuit 222, and corrector circuit 224 may be combined into multiple circuits or as a single circuit. Additional circuits with additional functions may also be included. Furthermore, controller 140 may further control other activities beyond the scope of this disclosure.

[0104] As described above, and in one configuration, the "circuit" can be implemented in a machine-readable medium for use by, for example Figure 2The processor 204 executes on various types of processors. For example, executable code may include one or more physical or logical blocks of computer instructions, which may be organized, for example, into objects, procedures, or functions. However, executable files do not need to be physically located together, but may include different instructions stored in different locations that, when logically connected together, constitute a circuit and achieve the circuit's stated purpose. In practice, the circuit of computer-readable program code may be a single instruction or multiple instructions, and may even be distributed across several different code segments, between different programs, and across several memory devices. Similarly, operational data may be identified and represented herein in a circuit, and may be embodied in any suitable form and organized in any suitable type of data structure. Operational data may be collected as a single dataset or may be distributed across different locations, including different storage devices, and may exist at least in part simply as electronic signals within a system or network.

[0105] While the term "processor" has been briefly defined above, the terms "processor" and "processing circuitry" should be interpreted broadly. In this regard, and as stated above, a "processor" can be implemented as one or more processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), or other suitable electronic data processing components configured to execute instructions provided by memory. One or more processors can take the form of a single-core processor, a multi-core processor (e.g., a dual-core processor, a triple-core processor, a quad-core processor, etc.), a microprocessor, etc. In some embodiments, one or more processors can be external to the device; for example, one or more processors can be remote processors (e.g., cloud-based processors). Alternatively or additionally, one or more processors can be internal to the device and / or local. In this regard, a given circuitry or its components can be arranged locally (e.g., as part of a local server, a local computing system, etc.) or remotely (e.g., as part of a remote server such as a cloud-based server). For this purpose, a "circuitry" as described herein can include components distributed in one or more locations.

[0106] Although the accompanying drawings and specifications may show a specific order of method steps, this order may differ from that depicted and described unless otherwise specified above. Furthermore, two or more steps may be performed simultaneously or partially simultaneously unless otherwise specified above. For example, such variations may depend on the chosen software and hardware system and the designer's choices. All such variations are within the scope of this disclosure. Similarly, the software implementation of the described method can be accomplished using standard programming techniques with rule-based logic and other logic to perform various connection steps, processing steps, comparison steps, and decision steps.

Claims

1. A system comprising: Post-processing system; as well as A controller, connected to the post-processing system, is configured to: Receive a model that divides the catalyst of the post-processor system into multiple parts; as well as The model is adjusted based on one or more sensing values ​​from one or more sensors located relative to the upstream and downstream portions of the plurality of parts.

2. The system according to claim 1, wherein, The model is a spatially resolved model of the catalyst, and the one or more sensors include at least one of a gas sensor, a temperature sensor, or a virtual sensor.

3. The system according to claim 1, wherein, The controller is also configured to: Receive one or more modeling values ​​from the model and one or more expected values ​​from the post-processing system; as well as Based on the one or more modeling values ​​relative to the one or more expected values, command at least one of the engine, heater, or metering device.

4. The system according to claim 1, wherein, The catalyst corresponds to one or a combination of a selective catalytic reduction (SCR) catalyst or an ammonia oxidation catalyst (AMOX).

5. The system according to claim 1, wherein, The controller is also configured to: Receive one or more modeling values ​​from the model; Determine the difference between the one or more modeled values ​​and the one or more expected values; as well as The fault in the post-processing system is detected based on the difference exceeding the error threshold.

6. The system according to claim 1, wherein, The catalyst is a first catalyst, and the system further includes: A second catalyst is located upstream of the first catalyst, wherein the second catalyst is relatively smaller than the first catalyst; A first reducing agent metering device, the first reducing agent metering device being fluidly connected to the first catalyst; and The second reducing agent metering device is fluidly connected to the second catalyst.

7. The system according to claim 6, wherein, The controller is also configured to: Based on one or more modeling values ​​of the model for at least one of the first catalyst or the second catalyst, control the dispensing command for the first reducing agent dispenser or the second reducing agent dispenser; Determine the amount of ammonia stored in the plurality of sections of the first catalyst or the second catalyst; and The shutdown command for at least one of the first reducing agent metering device or the second reducing agent metering device is delayed until the amount of stored ammonia is greater than a predetermined threshold.

8. The system according to claim 1, wherein, The controller is also configured to: Determine the gradient between one or more sensed values ​​from at least one upstream sensor located relative to the upstream portion and at least one downstream sensor located relative to the downstream position; as well as Based on the determined gradient, new modeling values ​​are assigned, and these new modeling values ​​have a linear relationship with the corresponding distances of the plurality of parts to the upstream or downstream sensor; or Based on the proximity of the plurality of parts to the upstream sensor or the downstream sensor, a new modeling value and a weighted value for the new modeling value are assigned.

9. The system according to claim 1, wherein, In order to adjust the model, the controller is configured as follows: Receive one or more modeling values ​​for temperature from the model, and assign the one or more modeling values ​​to each of the plurality of portions based on the distance between an upstream sensor relative to the upstream portion and a downstream sensor relative to the downstream portion, such that at least one portion between the upstream portion and the downstream portion is assigned the average of the sensed values ​​from the upstream sensor and the downstream sensor.

10. A method comprising: The controller connected to the post-processing system receives a model that divides the catalyst of the post-processing system into multiple parts. as well as The controller adjusts the model based on one or more sensing values ​​from one or more sensors located relative to the upstream and downstream portions of the plurality of parts.

11. The method of claim 10, further comprising: The controller receives one or more modeling values ​​from the model. The controller determines the difference between one or more modeled values ​​and one or more expected values. as well as The controller detects faults in the post-processing system based on the difference exceeding an error threshold.

12. The method according to claim 10, wherein, Adjusting the model also includes: The controller determines a gradient between one or more sensed values ​​from at least one upstream sensor located relative to the upstream portion and at least one downstream sensor located relative to the downstream position; and The controller assigns new modeling values ​​to the plurality of parts based on the determined gradient.

13. A system comprising: Processing circuitry, the processing circuitry including at least one processor coupled to a memory, the memory storing instructions that, when executed by the at least one processor, cause the processing circuitry to: The model received divides the catalyst of the aftertreatment system into multiple parts; as well as The model is adjusted based on one or more sensing values ​​from one or more sensors located relative to the upstream and downstream portions of the plurality of parts.

14. The system according to claim 13, wherein, The model is a spatially resolved model of the catalyst, and the one or more sensors include at least one of a gas sensor, a temperature sensor or a virtual sensor, and the catalyst corresponds to one or a combination of a selective catalytic reduction (SCR) catalyst or an ammonia oxidation catalyst (AMOX).

15. The system according to claim 13, wherein, To adjust the model, the instructions also cause the processing circuitry to: Determine the gradient between one or more sensed values ​​from at least one upstream sensor located relative to the upstream portion and at least one downstream sensor located relative to the downstream position; as well as Based on the determined gradient, the new modeling values ​​are assigned to the plurality of parts, wherein: - Based on a linear gradient, the processing circuit assigns the new modeling value, which has a linear relationship with the corresponding distances of the plurality of parts to the upstream or downstream sensor. - Based on nonlinear gradients, the processing circuit assigns the new modeling value and a weighted value to the new modeling value based on the proximity of the plurality of parts to the upstream sensor or the downstream sensor.

Images