Post-processing system control strategy for NOx and ammonia

Abstract

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] Cross-reference 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 to one or more desired values of the aftertreatment system; and responsive to the comparison, command at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more desired values. In some implementations, the controller is further configured to: determine a gradient between one or more sensed values from at least one sensor upstream of the one or more sections and one or more sensed values from at least one sensor downstream of the one or more sections; and assign new modeled values to the one or more sections based on the determined gradient.

[0007] In some implementations, the controller is further configured to: compare one or more modeled values from the spatially resolved model to one or more desired values of the catalyst; and identify a fault in the aftertreatment system based on a difference between the one or more modeled values and the 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 doser fluidly coupled to the first SCR catalyst and a second reductant doser fluidly coupled to the second SCR catalyst. In some implementations, the controller is further configured to: control a dosing command of the first reductant doser based on one or more modeled values of a spatially resolved model for the first SCR catalyst and the second SCR catalyst. In some implementations, the one or more modeled values are indicative of an amount of stored ammonia of one or more sections of the first SCR catalyst and the second SCR catalyst, and the dosing command of the first reductant doser is based on a comparison of the one or more modeled values to an ammonia storage threshold, the one or more modeled values being indicative of the amount of stored ammonia of the one or more sections of the first SCR catalyst and the second SCR catalyst.

[0008] In some implementations, the controller is further configured to: control a dosing command of the second reductant doser based on one or more modeled values of a spatially resolved model for the first SCR catalyst and the second SCR catalyst. The one or more modeled values can be indicative of an amount of stored ammonia of one or more sections of the first SCR catalyst and the second SCR catalyst. The dosing command for the second reductant doser is based on a comparison of the one or more modeled values indicative of the amount of stored ammonia of the one or more sections of the first SCR catalyst and the second SCR catalyst to an ammonia storage threshold.

[0009] Another embodiment relates to a method. The method includes generating, by a controller coupled to an aftertreatment system, a spatially resolved model of a catalyst of the aftertreatment system. The spatially resolved model divides the catalyst into one or more portions. The method also includes adjusting, by the controller, 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.

[0010] In some implementations, the method further includes comparing, by the controller, one or more modeled values from the spatially resolved model to one or more desired values of the aftertreatment system; and commanding, by the controller, at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more desired values in response to the comparing. In some implementations, adjusting the spatially resolved model includes determining, by the controller, a gradient between the one or more sensed values from the at least one sensor upstream of the one or more portions and the one or more sensed values from the at least one sensor downstream of the one or more portions; and assigning, by the controller, new modeled values to the one or more portions based on the determined gradient.

[0011] In some implementations, the method further includes comparing, by the controller, one or more modeled values from the spatially resolved model to one or more desired values of the catalyst; and identifying, by the controller, a fault in the aftertreatment system based on a difference between the one or more modeled values and the one or more desired values exceeding an error threshold. In some implementations, the catalyst is a selective catalytic reduction (SCR) catalyst.

[0012] Yet another embodiment relates to a system. The system includes processing circuitry including at least one processor coupled to a memory. The memory stores therein instructions that, when executed by the at least one processor, cause the processing circuitry to generate a spatially resolved model of a catalyst of an aftertreatment system, the spatially resolved model dividing the catalyst into one or more portions; and 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. The instructions, when executed by the at least one processor, further cause the processing circuitry to compare one or more modeled values from the spatially resolved model to one or more desired values of the aftertreatment system; and responsive to the comparison, command at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more desired values. The instructions, when executed by the at least one processor, further cause the processing circuitry to determine a gradient between the one or more sensed values from the at least one sensor upstream of the one or more portions and the one or more sensed values from the at least one sensor downstream of the one or more portions; and assign new modeled values to the one or more portions based on the determined gradient.

[0013] One embodiment relates to a controller coupled to an aftertreatment system, the controller configured to generate a spatially resolved model of a catalyst of the aftertreatment system, the spatially resolved model dividing the catalyst into one or more portions. The controller is 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.

[0014] This summary is illustrative only and is not intended to be limiting in any way. In conjunction with the drawings and the detailed description set forth below, additional aspects, inventive features, and advantages of the devices or processes described herein will be apparent from the description herein. Accordingly, what is desired to be secured by Letters Patent is set forth in the appended claims, and the foregoing description is intended for purposes of illustration only. In one or more embodiments and / or implementations, the described features can be combined in any suitable manner. One or more features of one aspect of the disclosure can be combined with one or more features of a different aspect of the disclosure. Further, additional features can be recognized in connection with the certain embodiments and / or implementations and can be added to those described herein without departing from the scope of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a schematic diagram of a system having a controller in accordance with an example embodiment.

[0016] Figure 2 is a schematic diagram of a controller of the system of Figure 1 in accordance with an example embodiment.

[0017] Figure 3 is a graphical depiction of discretized axial cross sections of an SCR catalyst and an AMOx catalyst generated by a controller of Figures 1-2

[0018] Figure 4 is a flowchart of a method of managing NOx and ammonia in an exhaust aftertreatment system according to an example embodiment.

[0019] Figure 5 is a schematic diagram of an alternative aftertreatment system for the system of Figure 1

[0020] Figure 6 is a flowchart of a process for adjusting a model of the system of Figure 1 DETAILED DESCRIPTION

[0021] The following is a more detailed description of various concepts and implementations related to methods, apparatuses, and systems for managing NOx and ammonia output via an onboard integrated model management system. Before turning to the figures, which illustrate certain example embodiments in detail, it should be understood that the disclosure is not limited to the details or methodology set forth in the description or illustrated in the figures. It should also be understood that the terminology used herein is for the purpose of description only and should not be considered limiting.

[0022] ​​​With general reference to the drawings, various embodiments disclosed herein relate to systems, devices, and methods for outputting NOx (SONOx) and ammonia (particularly ammonia slip) via a controller's on-board integrated model management system. Exhaust aftertreatment systems are designed to treat exhaust gas and mitigate undesirable exhaust emissions, such as NOx emissions. An exhaust aftertreatment system can 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 gas passes through these different components, harmful pollutants and particulates are removed from the exhaust gas. For example, an SCR can utilize a two-step process: a doser injects a reductant into the exhaust stream, and then the exhaust stream passes through an SCR catalyst that converts the exhaust gas into less harmful constituents (particularly, converts NOx into less harmful compounds) that can be released into the atmosphere. However, if too much of this reductant (in one embodiment, ammonia) is present in the exhaust gas or on the SCR catalyst (i.e., in the reservoir), the ammonia cannot fully react with the catalyst and is released into the atmosphere. "Ammonia slip" refers to excess ammonia that does not react with the catalyst, which can build up in the aftertreatment system and / or be released into the atmosphere. Some aftertreatment systems include an AMOX in order to reduce any unreacted ammonia in the exhaust, but these AMOXs can not be fully effective. Further, in those embodiments that omit an AMOX, proper management of the SCR and reductant is desirable in order to reduce or eliminate the amount of ammonia slip. The systems, devices, and methods of the present disclosure are operable to reduce the amount of ammonia slip while maintaining the desired level of NOx reduction.

[0023] Reference will now be made to Figure 1 , a system 100 according to example embodiments is shown. The system 100 includes an engine 110, an aftertreatment system 120, an operator input / output (I / O) device 130, and a controller 140, where the controller 140 is communicably coupled to each of the aforementioned components. In the configuration shown, Figure 1 The system 100 is included in a vehicle in the configuration shown. The vehicle can be any type of on-highway or off-highway vehicle, including but not limited to a wheel loader, a forklift, an over-the-road truck, a mid-range truck (e.g., a pickup truck, etc.), a sedan, a sedan coupe, a tank, an airplane, a boat, and any other type of vehicle. In another embodiment, the system 100 is embodied in a stationary piece of equipment, such as a generator or a genset.

[0024] The engine 110 can be any type of engine that produces exhaust gas, 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, the engine 110 is a diesel-powered compression-ignition engine.

[0025] The aftertreatment system 120 is coupled to the engine 110, particularly in exhaust receiving communication with the engine 110. 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 gas from the engine 110 and oxidize hydrocarbons and carbon monoxide in the exhaust gas. The DPF 121 is disposed or positioned upstream of the DOC 122 and is configured to remove particulates, such as soot, from the exhaust gas flowing in the exhaust stream. The DPF 121 includes an inlet at which the exhaust gas is received and an outlet at which the exhaust gas is expelled after substantially filtering out particulate matter and / or converting the particulate matter to carbon dioxide. In some implementations, the DPF 121 can be omitted.

[0026] The aftertreatment system 120 can also include a reductant delivery system, which can include a decomposition chamber (e.g., a decomposition reactor, a reactor conduit, a decomposition tube, a reactor tube, etc.) to convert a reductant into ammonia. The reductant can be, for example, urea, diesel exhaust fluid (DEF), Adblue®, urea water solution (UWS), an aqueous urea solution (e.g., AUS32, etc.), and other similar fluids. Diesel exhaust fluid (DEF) is added to the exhaust stream to help catalytic reduction. The reductant can generally be injected upstream of the SCR 123 (or particularly the SCR catalyst 126) by a DEF doser such that the SCR catalyst 126 receives a mixture of reductant and exhaust gas. However, in other embodiments, the DEF doser can inject the reductant at any point in the aftertreatment system, including within the SCR catalyst 126 itself. The reductant droplets then undergo evaporation, pyrolysis, and hydrolysis processes to form gaseous ammonia within the decomposition chamber, the SCR catalyst 126, and / or the exhaust conduit system, which exits the aftertreatment system 120. The doser can have any configuration and structure for injecting the reductant into the exhaust aftertreatment system. The aftertreatment system 120 can also include an oxidation catalyst (e.g., the DOC 122) fluidly coupled to the exhaust conduit system to oxidize hydrocarbons and carbon monoxide in the exhaust gas. To properly assist in this reduction, the DOC 122 can need to be at a particular operating temperature. In some embodiments, this particular operating temperature is between approximately 200°C - 500°C. In other embodiments, the particular operating temperature is a temperature at which the conversion efficiency of the DOC 122 exceeds a predefined threshold (e.g., HC conversion to less harmful compounds, which is referred to as HC conversion efficiency).

[0027] 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 exhaust gas that turns the 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 particular temperature, the acceleration of the NOx reduction process is limited, and the SCR 123 can not operate at or can not operate at a level of efficiency that meets or can meet regulations. In some embodiments, the particular temperature is approximately 200-300 °C. The SCR catalyst 126 can be made of a combination of an inactive material, such as a ceramic metal, that directs the exhaust gas to an 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, an AMOX 124 is included in the aftertreatment system. The AMOX 124 is structured to address the ammonia slip problem by removing or attempting to remove excess ammonia from the treated exhaust gas before the treated exhaust gas is released into the atmosphere.

[0028] In some embodiments, the aftertreatment system 120 is structured as a dual-SCR system. Referring now to Figure 1 FIG. 5 shows an example dual-catalyst (shown as a dual-SCR catalyst) aftertreatment system 520, according to example embodiments. 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 a “light-off SCR system”) that is positioned relatively closer to the engine 110 (i.e., upstream) than the (second) SCR 123 and the DPF 121. Due to primary space constraints, the first SCR system 523 is relatively smaller in size (e.g., packaging / container and catalyst size) compared to the SCR 123. The first SCR system 523 is fluidly coupled to its own dedicated DEF doser. The DEF doser can have similar structure and functionality as the reductant doser described above. The SCR 123 is a relatively larger SCR system and is fluidly coupled to its own dedicated DEF doser 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. In turn, the first SCR system 523 can quickly convert NOx due to its smaller size, but packaging constraints make the first SCR system 523 too small to be the only SCR system on the engine because the smaller catalyst is not sufficient to convert the desired amount of NOx associated with standard engine 110 operation. The SCR system 123 is similar to the SCR system in a single-SCR architecture, meaning that the larger SCR system takes more time to heat up to operating temperature, but is subsequently able to convert the amount of NOx associated with standard engine 110 operation.

[0029] In some embodiments, the heater 125 is located in the exhaust flow path before the aftertreatment system 120 and is configured to controllably heat exhaust gas upstream of the aftertreatment system 120. In some embodiments, the heater 125 is located directly before the DOC 122, while in other embodiments, the heater 125 is located directly before the SCR 123 or is incorporated directly into the SCR catalyst. The heater 125 can be any kind of external heat source that can be configured to increase the temperature through the exhaust gas, which in turn increases the temperature of components in the aftertreatment system 120, such as the DOC 122 or the SCR 123. Thus, the heater can be an electric heater, an induction heater, a microwave, or a heater that burns a fuel (e.g., HC fuel). As shown here, the heater 125 is an electric heater that draws power from the battery (or another power source, such as an alternator, supercapacitor, etc.) of the system 100. The heater 125 can be controlled by the controller 140 (e.g., turned on, turned off, turned to a different degree of power to change the heater output power, etc.). The heater 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 the structure of each heater can be the same or different (e.g., conduction, convection, etc.).

[0030] Still referring to Figure 5 An operator input / output (I / O) device 130 is also shown with the system 100. The operator I / O device 130 can be communicably coupled to the controller 140 such that information can be exchanged between the controller 140 and the I / O device 130, where the information can relate to Figure 1 one or more components of the system 100 or determinations (described below) of the controller 140. The operator I / O device 130 enables an operator of the system 100 to communicate with the controller 140 and Figure 1 one or more components of the system 100. For example, the operator input / output device 130 can include, but is not limited to, an interactive display, a touch screen device, one or more buttons and switches, a voice command receiver, etc.

[0031] The system 100 includes a plurality of sensors. The sensors are coupled to the controller 140 such that the controller 140 can monitor and acquire data indicative of the operation of the system 100. In this regard, the sensors include a NOx sensor 128 and a temperature sensor 127. The NOx sensor 128 is configured to acquire data indicative of the amount of NOx at or about the location at which it is disposed. The temperature sensor 127 acquires data indicative of the approximate temperature of the exhaust gas at or about the location at which it is disposed. In one embodiment, a first temperature sensor 127 is located upstream of the portion of the SCR catalyst 126 being modeled and a second temperature sensor 127 is located downstream of the portion of the SCR catalyst 126 being modeled. In some of these embodiments, the first and second temperature sensors 127 are located external to the SCR catalyst 126 such that the first temperature sensor 127 is located upstream of the entire SCR catalyst 126 and the second temperature sensor 127 is located downstream of the entire SCR catalyst 126. In other of these embodiments, 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 can be located upstream of the particular portion of the SCR catalyst 126 being modeled, rather than the entire SCR catalyst 126, and / or the second temperature sensor 127 can be located downstream of the particular portion of the SCR catalyst 126 being modeled, rather than the entire SCR catalyst 126. Further, the system 100 includes at least one sensor for a gas species (i.e., NOx or ammonia) located downstream of at least one portion of the SCR catalyst 126, and one or more sensors can be included upstream of the SCR catalyst 126 in order 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 of the exhaust gas at the SCR catalyst 126 inlet, etc.). It should be appreciated, however, that the location, number, and type of sensors depicted are merely illustrative. In some embodiments, one or more of the sensors can be virtual sensors such that the one or more sensors estimate an output variable (e.g., data indicative of the amount of NOx, data indicative of the approximate temperature, etc.) based on other operating parameters within the system. In other embodiments, the sensors can be positioned in other locations, there can be more or fewer sensors than shown, and / or different / additional sensors can be included in the system 100 (e.g., pressure sensors, ammonia sensors, flow sensors, etc.).

[0032] 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 1 The structure and function of controller 140 are further described.

[0033] because Figure 2 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 1 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.

[0034] Now for reference Figure 2 This illustrates an example embodiment. Figure 2 A schematic diagram of the controller 140 of system 100. (See diagram below.) Figure 1 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.

[0035] In one configuration, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 are embodied as a machine or computer-readable medium storing instructions executable by a processor (e.g., the processor 204). As described herein and among other uses, the machine-readable medium facilitates performance of certain operations to enable 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 can include programmable logic that defines a data acquisition (or data transmission) frequency. The computer-readable medium instructions can include code that 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 connected to one another through any type of network (e.g., a CAN bus, etc.).

[0036] In another configuration, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 are embodied as hardware units, such as an electronic control unit. Thus, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can be embodied as one or more circuit components, including but not limited to processing circuitry, network interfaces, peripherals, input devices, output devices, sensors, etc. In some embodiments, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (ICs), discrete circuits, system-on-chip (SOC) circuits, microcontrollers, etc.), telecommunication circuits, hybrid circuits, and any other type of “circuit.” In this regard, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can include any type of component for accomplishing 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, wires, etc. The modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can also include programmable hardware devices, such as field-programmable gate arrays, programmable array logic, programmable logic devices, etc. The modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can include one or more memory devices for storing instructions executable by the processors of the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224. The one or more memory devices and processors can have the same definitions as provided below with respect to the memory 206 and the processor 204. In some hardware unit configurations, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can be geographically dispersed in various locations in the vehicle. Alternatively and as shown, the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can be embodied in or within a single unit / housing, which is shown as the controller 140.

[0037] In the illustrated example, the controller 140 includes a processing circuit 202 having a processor 204 and a memory 206. The processing circuit 202 can be structured or configured to execute or implement the instructions, commands, and / or control processes described herein with respect to the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224. The depicted configuration represents the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 as machine- or computer-readable media that store instructions. However, as noted above, this illustration is not meant to be limiting, as the present disclosure contemplates other embodiments in which the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224, or at least one of the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224, are configured as hardware units. All such combinations and variations are intended to fall within the scope of the present disclosure.

[0038] The processor 204 can be implemented as a single- 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 can be a microprocessor. The processor can also be implemented as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In some embodiments, one or more processors can be shared by multiple circuits (e.g., the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can include or otherwise share the same processor, which in some example embodiments can execute instructions stored or otherwise accessed via different regions of memory). Alternatively or additionally, the one or more processors can be structured to perform or otherwise execute certain operations independently of one or more co-processors. In other example embodiments, two or more processors can 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 the present disclosure.

[0039] The memory 206 (e.g., memory, memory unit, storage device) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage) for storing data and / or computer code for completing or facilitating the various processes, layers and modules described in the present disclosure. The memory 206 can be communicably connected to the processor 204 such that the processor 204 can provide computer code or instructions to the memory 206 for execution. Additionally, the memory 206 can be or include a tangible, non-transitory, volatile memory or non-volatile memory. Thus, the memory 206 can include a database component, a target code component, a script component, or any other type of information structure for supporting the various activities and information structures described herein.

[0040] The communication interface 210 can include any combination of wired and / or wireless interfaces (e.g., a plug-in, an antenna, a transmitter, a receiver, a transceiver, a wire terminal) for communicating data with various systems, devices, or networks configured to enable in-vehicle communications (e.g., between and among components of the vehicle) and, in some embodiments, out-of-vehicle communications (e.g., with a remote server via a telematics unit). For example, with respect to out-of-vehicle / system communications, the communication interface 210 can include an Ethernet card and port for transmitting and receiving data via an Ethernet-based communication network and / or a Wi-Fi transceiver for communicating via a wireless communication network. The communication interface 210 can be configured to communicate via a local or wide area network (e.g., the Internet) and can use various communication protocols (e.g., IP, LON, Bluetooth, ZigBee, radio, cellular, near-field communication).

[0041] The modeling circuit 220 is configured to generate a spatially resolved and, in particular, discretized axial model of the catalyst of the post-processing system 120. The modeling circuit 220 is configured to estimate or determine a state of the catalyst using the generated spatially vectorized model of the catalyst. The axial resolved model of the catalyst refers to a model that estimates or determines the catalyst state at different portions of the catalyst by dividing or separating the catalyst into a plurality of portions or zones. In some embodiments, the catalyst being modeled is the SCR catalyst 126. In other embodiments, the catalyst being modeled is a combination of the SCR catalyst 126 and the AMOX 124. In the model described herein, the modeling circuit 220 discretizes the catalyst model axially along an axis parallel or substantially parallel to the exhaust gas flow through the catalyst 126. As described herein, for this model, the “state” or “state of the catalyst” refers to the ammonia storage amount or temperature value of the catalyst, respectively (i.e., the ammonia storage state or temperature state of the catalyst).

[0042] Reference is now made to Figure 2FIG. 3 shows a visualization 300 of an axially resolved model (or profile) of the SCR catalyst 126 and the AMOX 124 by the modeling circuit 220, according to an example embodiment. In this example, the axially resolved model of the SCR catalyst 126 shows that the SCR catalyst 126 has been divided into three sections: a front section, a middle section, and a rear section (with the rear section being downstream relative to the direction of exhaust flow). In this embodiment where the catalyst includes the AMOX 124, the 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., another number greater than zero, etc.). Moreover, increasing the number of sections can be related to overall model accuracy. However, increasing the number of sections can increase processing power requirements on the controller 140. Moreover, many of the control strategies that utilize the sections from the model cannot target the catalyst with an accuracy beyond 3-4 sections, so there are factors that prevent increasing the number of sections beyond a certain amount, despite increasing the number of sections improving overall model accuracy.

[0043] The modeling circuit 220 is structured to receive characteristics related to the operation of the aftertreatment system 120 (e.g., the SCR catalyst 126). These characteristics include physical dimensions of the aftertreatment system 120 (or components thereof, such as the decomposition reactor tube), physical dimensions of the SCR 123, thermal mass of the SCR catalyst 126, mass of the SCR catalyst 126, and other characteristics of the aftertreatment system 120 that can affect performance. Generally, these characteristics are set or fixed such that they do not change over the life of the model.

[0044] The modeling circuit 220 is also configured to construct and adjust the state of the model (i.e., the amount of ammonia stored on the catalyst, the temperature values of the catalyst) based on the sensed values from the sensors. As described above and with respect to temperature, the temperature sensors 127 can provide data indicative of the temperature of the components or exhaust gases on which they are placed. For example, the temperature sensors 127 can provide sensed values of the exhaust temperature upstream and downstream of a particular portion of the SCR catalyst 126, and the modeling circuit 220 uses these sensed values to inform the model. In one embodiment, based on the sensed values, the modeling circuit 220 assigns modeled values of temperature to each portion based on the distance from the upstream and downstream sensors, such that the portion that is most in the middle (i.e., equidistant from the upstream and downstream sensors) is assigned an average of the sensed value of the upstream sensor and the sensed value of the downstream sensor. In this regard, the modeled values can be assigned to the portions based on a gradient between the sensed value of the upstream sensor and the sensed value of the downstream sensor. In one embodiment, the gradient is linear, such that the assigned modeled values have a linear relationship with the distance of the catalyst portion from the sensor. In other embodiments, the gradient is a non-linear relationship (e.g., an exponential relationship), such that the assigned modeled values are assigned a weighting value that gives more weight to being closer to the upstream sensor or to the downstream sensor (e.g., the portion that is most in the middle is assigned a value that is closer to the sensed value from the upstream sensor).

[0045] In those embodiments in which there are sensors embedded within the catalyst in addition to the upstream and downstream sensors, the modeling circuit 220 can also assign modeled values to the portions based on proximity to the embedded sensors. These values are in turn closer to the actual values. In this regard, any portion that is directly adjacent to an embedded sensor can be assigned the sensed value from the embedded sensor as the modeled value, and portions that are close but not directly adjacent are assigned modeled values based on the sensed value from the embedded sensor and the sensed values from the upstream and / or downstream sensors. Thus, the modeling circuit 220 is able to utilize any number of sensors to assign modeled values to portions of the catalyst.

[0046] The modeling circuit 220 can also receive sensed values from one or more NOx sensors 128. These sensed 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 sensed values from a NOx sensor 128 upstream of the catalyst and a NOx sensor 128 downstream of the catalyst. The modeling circuit 220 then assigns modeled values for the amount of NOx at each section based on the distance from the upstream and downstream sensors, such that the middle-most section (i.e., the section equidistant from the upstream and downstream sensors) is assigned an average of the sensed value from the upstream sensor and the sensed value from the downstream sensor. In this regard, the modeled values can be assigned to the sections based on a gradient between the sensed value of the upstream sensor and the sensed value of the downstream sensor. In one embodiment, the gradient is directly linear, such that the assigned modeled values have a linear relationship with the distance of the section from the sensors. In another embodiment, the gradient has a non-linear relationship (e.g., an exponential relationship), such that the assigned modeled values are assigned a weighting value that gives more weight to being closer to the upstream sensor or to the downstream sensor (e.g., the middle-most sensor is assigned a value closer to the sensed value from the upstream sensor). Using the modeled values for NOx for each section of the catalyst, the modeling circuit 220 can model, estimate, or otherwise determine the amount of ammonia stored for each section of the catalyst. Specifically, for an SCR catalyst 126, NOx in the exhaust gas reacts with ammonia stored on the SCR catalyst 126, such that by modeling the amount of NOx at each section, the modeling circuit 220 can determine an approximate amount of ammonia stored at each section based on how much NOx is reduced from one section to another. This determination can also include other factors, such as engine output NOx, dosing amount, etc.

[0047] Thus, in other words, the modeling circuit 220 utilizes sensed values from sensors disposed in the aftertreatment system to generate a“modeled value” (i.e., an estimated value based on the sensed value) for each section of the catalyst. When a sensor is not directly disposed in the section, the modeling circuit 220 extrapolates the sensed value to determine or estimate the corresponding value in the respective section of the catalyst (thus, the“modeled value”). The modeled value can be determined in various ways based on the placement of the sensors (e.g., a sensor reading can be assigned to a section within a predefined distance of the sensor, an average of two sensor readings can be assigned to a section between the two sensors, a gradient can be applied, etc.).

[0048] In some embodiments, modeling circuit 220 limits the portions of the catalytic converter model that are of the same size (i.e., length) based on the size of the catalytic converter. In other embodiments, modeling circuit 220 limits the portions of the catalytic converter model that are of unequal sizes (i.e., lengths), such as by limiting a shorter portion at the front of the catalytic converter in order to increase the model resolution (i.e., model accuracy) toward the front of the catalytic converter and decrease the model resolution toward the back of the catalytic converter. In these embodiments, by increasing the model resolution of the front portion, modeling circuit 220 balances the computational burden on controller 140 in a desired manner. In other embodiments, modeling circuit 220 limits the portions of the catalytic converter model based on the location of the sensors (temperature sensor 127 or NOx sensor 128) throughout the catalytic converter. In this case, the temperature sensor locations (or NOx or other sensor locations) dictate the breakpoints of the portions of the catalytic converter model.

[0049] While the references to modeling circuit 220 are primarily directed to aftertreatment system 120 having a single SCR architecture, modeling circuit 220 is configured to develop models for those embodiments in which aftertreatment system 120 has a dual SCR architecture. In these embodiments, modeling circuit 220 is structured 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 described above. In some of these embodiments, the models for each of the smaller SCR system and the larger SCR system are utilized by other circuits (e.g., predictor circuit 222, corrector circuit 224) independently of one another such that controller 140 issues commands that affect the smaller SCR system without regard to the model of the larger SCR system, and vice versa. In other embodiments of these embodiments, the models for each of the smaller SCR system and the larger SCR system are used in combination by other circuits such that controller 140 issues commands based on inputs from the models for the smaller SCR system and the larger SCR system.

[0050] Predictor circuit 222 is structured to compare the determined modeled value of each portion of the catalytic converter to a predetermined value and issue commands to components of system 100 in response to the comparison. The determined modeled value of SCR catalytic converter 126 can be the temperature of SCR catalytic converter 126 (or a portion thereof) or the amount of ammonia stored on SCR catalytic converter 126 (or a portion thereof). The modeled catalytic converter (or component) can be SCR catalytic converter 126, AMOX 124, DOC 122, and / or DPF 121. In this regard, the determined modeled value of SCR catalytic converter 126 can be the determined modeled value of a particular portion of SCR catalytic converter 126 or a cumulative or average of the determined modeled values of multiple portions of SCR catalytic converter 126.

[0051] The predictor circuit 222 compares the determined modeled value to a predetermined value. In some embodiments, the predetermined value is a target value for a state (e.g., ammonia storage amount, temperature), a threshold value for a state (e.g., ammonia storage amount, temperature), or a combination of both. A threshold value for a state refers to a value of the state that the determined modeled value is to remain above (if the threshold value is a minimum value) or below (if the threshold value is a maximum value), while a target value refers to a specific value of the state that the determined modeled value is attempting to reach. As discussed later with reference to the corrector circuit 224, the predetermined value can be dynamic and adjusted throughout the operation of the system 100 such that the predetermined value more closely represents the current performance. Thus, in addition to the methods described below for updating the predetermined value, the predetermined value can 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 desired operation of the SCR 123. For example, if the state in question is temperature, the target value can be a temperature value at which the NOx conversion efficiency of the SCR 123 is at or above a certain value (e.g., 95%), or can be a desired temperature value for the system. Alternatively, if the state in question is ammonia storage amount, the target value can be set to an ammonia storage amount sufficient for the NOx conversion efficiency to reach or exceed a certain value (e.g., 95%).

[0052] Similarly, if the predetermined value is a threshold value, the threshold value can be set based on desired operation of the SCR 123. For example, if the state in question is temperature, the threshold value can be set to a temperature value below which the SCR 123 cannot achieve a desired NOx conversion efficiency (e.g., 95%). Alternatively, if the state in question is ammonia storage amount, the threshold value can be an ammonia slip threshold value.

[0053] In those embodiments where the predictor circuit 222 utilizes a combination of target values and threshold values, the predictor circuit 222 utilizes both a target value and a threshold value from one or more states. For example, the predictor circuit 222 can compare the state of the SCR catalyst 126 to a temperature target value and an ammonia storage amount threshold value, an ammonia storage amount target value and a temperature threshold value.

[0054] The predictor circuit 222 is configured to take action or issue a command in response to a comparison of the determined modeled value of the SCR catalyst 126 to a predetermined value. This command can be one or more of changing the amount of DEF from the doser (i.e., increasing the dosed amount of reductant or decreasing the dosed amount of reductant), changing the amount of engine out NOx (EONOx) by reducing power output (e.g., increasing the amount of EGR), and activating the heater 125. Changing the amount of EONOx (i.e., the amount of NOx in the exhaust gas as it enters the aftertreatment system 120) can include changing the air / fuel ratio (where increasing the ratio by increasing the proportion of air in the intake will decrease the amount of EONOx, and vice versa), adjusting the amount of fueling (where increasing the amount of fueling will increase the amount of EONOx, and vice versa), and / or changing the timing of fuel injection (where delaying the timing will decrease EONOx). The command can also include adjusting engine operation, such as changing the load on the engine 110 (where an increased load results in a higher engine out exhaust temperature, and vice versa), changing the amount of exhaust gas redirected back to the engine (e.g., via an EGR system) (where increased EGR decreases the combustion temperature in the engine 110, thereby decreasing the engine out exhaust temperature, and vice versa), and the like.

[0055] In the illustrative example where the monitored condition is temperature, if the comparison of the temperature of a portion of the SCR catalyst 126 to a target temperature value indicates that the portion of the SCR catalyst is too cold (i.e., the temperature is below a temperature threshold), 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 components to command and the commands to issue based on the relative location of the portion along the SCR catalyst. For example, if the too-cold portion of the SCR catalyst 126 is toward the front of the SCR catalyst 126 (i.e., close to the exhaust intake), the predictor circuit 222 can prioritize commands that more effectively affect the front of the SCR catalyst 126, such as increasing the engine out exhaust temperature via affecting the amount of EGR. In another example, if the affected portion of the SCR catalyst is toward the middle or rear of the SCR catalyst 126 (i.e., away from the exhaust intake), the predictor circuit 222 can prioritize commands that more effectively affect the middle or rear of the SCR catalyst 126, such as the heater 125, or can prioritize commands that more effectively affect the front of the SCR catalyst 126 while increasing the effect so as to affect the middle and rear of the SCR catalyst 126 (e.g., increasing the engine out exhaust temperature to a relatively greater extent).

[0056] Alternatively, in this same example, the predictor circuit 222 can issue a command to reduce the amount of EONOx in response to determining that a portion of the SCR catalyst 126 is too cold, thereby maintaining a lower SONOx even if the SCR 123 reduces NOx at a potentially lower efficiency than desired. In this case, the predictor circuit 222 can vary 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 affected portion of the SCR catalyst 126 that is too cold is located at the front of the SCR catalyst 126 (i.e., close to the exhaust gas intake), the predictor circuit 222 can issue a command to reduce EONOx more drastically than if the affected portion of the SCR catalyst is located at the back of the SCR catalyst 126 (i.e., far from the exhaust gas intake), as the front of the SCR catalyst 126 performs a greater portion of the NOx reduction. In this case, a less efficient front portion has a greater negative impact on the reduction efficiency of the entire SCR 123.

[0057] In another example example where the monitored condition is the amount of ammonia stored, if a comparison of the amount of ammonia stored in a portion of the SCR catalyst 126 to the ammonia storage amount threshold indicates that the portion of the SCR catalyst has too little ammonia (i.e., the amount stored is below the desired threshold amount), the predictor circuit 222 commands one or more components of the system 100 to increase the amount of ammonia stored on the affected portion of the SCR catalyst 126. These commands can be, for example, to increase the dosing amount of DEF or by reducing the amount of EONOx, which will indirectly increase the amount of ammonia by reducing the amount of ammonia removed by the reaction (assuming the dosing amount of DEF is unchanged). The predictor circuit 222 can vary the commands or prioritize the commands based on the relative location of the portion along the SCR catalyst 126. For example, if the portion of the SCR catalyst 126 with too little stored ammonia is toward the front of the SCR catalyst 126 (i.e., close to the exhaust gas intake), the predictor circuit 222 can prioritize those commands that directly add ammonia to the SCR catalyst 126 (e.g., increase the DEF dosing amount) because the affected portion is one of the first portions to receive exhaust gas, which means the affected portion is the first to receive any other contents included in the exhaust gas (e.g., ammonia from DEF). Alternatively, if the affected portion is toward the middle or rear of the SCR catalyst 126 (i.e., away from the exhaust gas intake), the predictor circuit 222 can prioritize those commands that indirectly affect the amount of stored ammonia (e.g., reduced EONOx) because these commands are more likely to have the intended effect on portions of the SCR catalyst 126 away from the exhaust gas intake because these commands have less of a connection to the contents carried in the exhaust stream (e.g., ammonia from DEF). Further, if the affected portion is toward 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 for an affected portion facing the front, in order to account for the exhaust gas carrying the ammonia passing through other portions of the SCR catalyst 126 before reaching the affected portion.

[0058] In another illustrative example in which the monitored state is a combination of temperature and ammonia storage, the predictor circuit 222 can prioritize commands that affect both of these states in order to more effectively manage the performance of the SCR 123 and ammonia slip. For example, if the predictor circuit determines that a portion of the SCR catalyst 126 is too cold and has too much stored ammonia based on a comparison of the state of that portion of the SCR catalyst 126 to predetermined values for temperature and ammonia storage, the predictor circuit 222 can issue a command to increase the temperature and decrease the ammonia storage. In this example, the predictor circuit 222 can command an increase in fueling of the engine 110, which not only increases the combustion temperature (and thus the engine out exhaust temperature), but also increases the amount of EONOx. The higher engine out exhaust temperature increases the temperature of the affected portion of the SCR catalyst 126, while the greater amount of EONOx reacts with the stored ammonia, decreasing the total amount of ammonia stored on the affected portion.

[0059] The predictor circuit 222 can also monitor multiple catalyst portions and issue commands that affect multiple catalyst portions simultaneously. For example, the predictor circuit 222 can determine that a first portion of the SCR catalyst 126 is too cold (e.g., temperature is below a threshold) and that a second portion of the SCR catalyst 126 has too little stored ammonia (below a threshold) based on a comparison of the state of the first portion to predetermined values and a comparison of the state of the second portion to predetermined values. In this example, the predictor circuit 222 can prioritize a heating command (e.g., engage the heater 125) that can not increase or attempt to increase EONOx in order to warm the first portion, while not impeding the limited reduction capabilities of the second portion. Similarly, the predictor circuit 222 can prioritize an ammonia increasing command that does not decrease or attempt to decrease exhaust temperature (e.g., increase the DEF dosing level) in order to increase the amount of stored ammonia on the second portion, without impeding the ability of the first portion to warm.

[0060] In some embodiments, the predictor circuit 222 establishes different predetermined values for each portion of the SCR catalyst 126 (which can be the same or different for each portion). For example, with respect to ammonia storage, the target value for a front portion of the SCR catalyst 126 can be relatively high in order to account for the increase in NOx reduction that occurs at the front portion of the SCR catalyst. However, the target value for a rear portion of the SCR catalyst 126 can be relatively low (or even zero) to act as a buffer for any excess ammonia that remains in the exhaust stream through the majority of the SCR catalyst 126, thereby absorbing some of those unreacted ammonia into the reservoir, rather than allowing ammonia slip.

[0061] The predictor circuit 222 can also issue commands based on modeled values of one or more portions of the catalyst compared to one or more predetermined values (e.g., expected values, threshold values, target values). For example, as described above, the aftertreatment system can be configured as a dual catalyst aftertreatment system 520 that includes a first SCR system 523 located proximate to the engine 110 and having a 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 positioned proximate to the first SCR system 523 to obtain modeled values (e.g., ammonia storage amounts) for portions of the first SCR system 523, similar to that described above for a catalyst (e.g., SCR catalyst 123). The downstream SCR catalyst 123 can be divided into portions and modeled values determined for the portions. Based on the determined modeled values for the portions of the upstream and downstream catalysts (in this case, SCR catalysts), the predictor circuit 222 can issue various commands. For example, the predictor circuit 222 can control dosing amounts of reductant to the upstream catalyst differently than to the downstream catalyst based on the ammonia load experienced by the upstream catalyst relative to the ammonia load experienced by the downstream catalyst as determined by the modeled values. As an example, the modeled values for a front portion of the upstream catalyst can indicate a low ammonia storage amount (i.e., below a threshold value) while the modeled values for a front portion of the downstream catalyst indicate a high ammonia storage amount (i.e., above a threshold value). Accordingly, the controller commands an increase in the dosing amount for the upstream catalyst and a decrease in the dosing amount for the downstream catalyst in order to build up ammonia storage in the front portion of the upstream catalyst. Additionally, as described above, similar commands can be provided for the upstream catalyst (e.g., based on temperature). In some embodiments, the other catalyst (e.g., first SCR system 523) can have a dedicated controller for controlling the doser and potentially other components. Thus, in this embodiment, there can be one controller for each SCR catalyst system. Each of these controllers can have the same or similar structure as described herein with respect to the controller 140. In this embodiment, the controllers "talk" to / communicate with each other to optimize overall system performance. In other words, the upstream controller knows the storage amount of the downstream catalyst and the downstream controller knows the storage information of the upstream catalyst and commands are provided that are adjusted to optimize overall performance.

[0062] With respect to dual catalytic converter aftertreatment system 520, predictor circuit 222 can issue a command to prioritize one SCR system or otherwise utilize one SCR system over the other until a particular condition is obtained. In one embodiment, the particular condition is that a catalytic converter (or one or more desired portions of a catalytic converter) reaches a desired operating temperature. In another embodiment, the particular condition is an amount of ammonia storage on a catalytic converter (or one or more portions thereof) relative to an ammonia storage amount threshold. In yet another embodiment, the particular condition is a combination of temperature and ammonia or reductant storage amount. As noted above, the size and location of first SCR system 523 can allow first SCR system 523 to reach operating temperature relatively earlier than downstream SCR 123. Generally, it is desirable for high concentrations of NOx to enter DPF 121 in order to passively regenerate the filter. In this manner, DPF 121 cleans itself rather than requiring system 100 to enter a high-heat mode to burn off accumulated soot. If first SCR system 523 is used to convert a large amount of EONOx, there is not much NOx available to help clean DPF 121. This results in more frequent high-temperature regeneration events to keep DPF 121 clean, which results in fuel loss and increased water thermal aging / degredation of the catalytic converters.

[0063] In one example, predictor circuit 222 issues a command to utilize first SCR system 523 until downstream SCR 123 is at operating temperature (e.g., during an initial warm-up period of system 100), at which point predictor circuit 222 issues a command to close DEF dosing of first SCR system 523. However, if SCR 123 does not have any (or more than a threshold amount) of stored ammonia amount when the "switch" (i.e., the reduction or closing of dosing to first SCR system 523) is made, there can be poor total S ONOx until enough ammonia storage amount is accumulated on SCR 123. To address this issue, predictor circuit 222 is configured to delay the dosing close command (or dosing reduction command) to first SCR system 523 until downstream SCR 123 has enough ammonia storage amount (greater than a predefined threshold amount). For example, if a modeled value of the temperature of SCR 123 is above a predefined threshold for operation, but a modeled value of the ammonia storage amount of SCR 123 is below a predefined threshold for operation, predictor circuit 222 determines to delay the dosing close command. Predictor circuit 222 can send a dosing close command to upstream first SCR system 523 when the modeled value of the ammonia storage amount for SCR 123 is above a predefined threshold for operation. In this case, predictor circuit 222 can also command a lower EONOx (e.g., during the initial warm-up period) due to the lower total reductant capability of first SCR system 523.

[0064] Further, in this example embodiment, the predictor circuit 222 can determine to re-engage the first SCR system 523 based on modeled and / or sensed values for the system 100. For example, if current conditions are particularly challenging due to a sharp temperature or EONOx transient (e.g., sharply increasing due to frequent hard accelerations), or if the downstream catalyst (i.e., SCR 123) has degraded functionality due to hydrothermal aging or chemical poisoning, the predictor circuit 222 can re-engage the first SCR system 523 (e.g., issue a command to resume DEF dosing to the first SCR system 523) in order to balance the burden of NOx reduction between both the first SCR system 523 and the SCR 123. In this way, the predictor circuit 222 still allows the system to maintain a desired overall system output emission (e.g., SONOx) in the event of component degradation or failure. In another example, if it is desired to run the engine at higher EONOx levels, the predictor circuit 222 can utilize both the first SCR system 523 and the SCR 123 to maintain the desired SONOx. This can be the case if there is an engine component failure that causes the engine 110 to run in a “guard mode” with higher EONOx, which enables the system 100 to maintain emissions performance until the vehicle can be serviced.

[0065] The corrector circuit 224 is configured to adjust expected values of the aftertreatment system 120 states based on feedback from sensors and compare the adjusted values to expected values in order to identify faults in the system 100. These expected values can be predetermined values (i.e., target values, threshold values) of the predictor circuit 222, although the corrector circuit 224 and the predictor circuit 222 can operate independently of one another. These expected values of the states (i.e., reference values for comparison) can be established when the system 100 is first started in the life cycle of the system, when the system 100 is first started during use, or at any other time in the life cycle of the system 100. In some embodiments, the expected values of the states are established by a user command (i.e., via the I / O device 130). These states include temperature and ammonia storage.

[0066] As used for the corrector circuit 224, a desired value of a state refers to a value of the state that the aftertreatment system 120 (and, in particular embodiments, the SCR 123 and the SCR catalyst 126) is expected to perform at. For example, a desired value of temperature is a value of temperature at which the SCR 123 has an acceptable or desired NOx conversion efficiency (e.g., 95%). If the state is an amount of ammonia storage, then the desired value is an amount of stored ammonia on the SCR catalyst 126 (or on a portion of the SCR catalyst 126) and / or an amount of ammonia slip (i.e., ammonia that remains unreacted in the exhaust stream and is released into the atmosphere) that remains at an acceptable or desired level (e.g., XX%) at which the SCR 123 has an acceptable or desired conversion efficiency (e.g., 95%).

[0067] The corrector circuit 224 adjusts the desired values after setting the desired values of the states and then based on feedback from the sensors. Because the desired values represent values of the states at which the aftertreatment system 120 is expected to operate, the desired values can be adjusted as components in the aftertreatment system 120 age or wear out so as to continue to represent values of the states at which the aftertreatment system 120 is expected to operate. For example, over time as the SCR catalyst 126 is used, the SCR catalyst 126 is prone to wear and lose some conversion efficiency, requiring a higher temperature (i.e., higher than 250°C) to achieve an acceptable NOx conversion efficiency. Thus, if the desired value of temperature is not adjusted during the life of the SCR catalyst 126, the desired value will no longer represent a value of the state at which the SCR catalyst 126 is expected to reduce NOx.

[0068] The corrector circuit 224 determines adjustments to the desired values based on a comparison of the desired values for the sensed values and the actual values for the sensed values. For example, if the temperature of the SCR catalyst 126 (which can generally be given as the temperature of the SCR catalyst 126, the temperature of most of the SCR catalyst 126, or an average of the temperatures of portions of the SCR catalyst 126) is at the desired value (e.g., 250°C), then the corrector circuit 224 can expect that the NOx conversion efficiency sensed by the NOx sensor 128 is at or near the desired value (e.g., 95%). Thus, if the actual sensed value from the NOx sensor 128 is different from this expected value (e.g., 85%), then the corrector circuit 224 determines that the desired value is 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 value. The threshold value can be an absolute amount (e.g., 0.001 grams of difference) or a relative amount (e.g., 10% difference). The amount of adjustment is determined based on an algorithm incorporated into the corrector circuit 224.

[0069] Reference is now made to Figure 3An 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.

[0070] Once the corrector circuit 224 has selected a nominal model, the corrector circuit 224 can compare the modeled values of temperature or ammonia storage to sensed values and modify one or more parameters (e.g., reaction rate, thermal mass of the SCR 123, material properties of the aftertreatment system 120 components, etc.) based on the comparison. Further, the corrector circuit 224 can modify one or more modeled values (e.g., ammonia storage level, temperature) based on the comparison. The corrector circuit 224 determines which modeled values to adjust based on the compared values in order to determine whether the error is more likely due to ammonia slip or NOx slip. For example, if the algorithm initially determines (from the comparison) that it is ammonia slip, the corrector circuit 224 will increase the modeled value of ammonia storage. Alternatively, if the initial determination is NOx slip (i.e., above an acceptable level of SONOx), the corrector circuit 224 will decrease the modeled value of ammonia storage. Functionally, the difference amount results in a relatively equal adjustment (i.e., the greater the difference, the greater the adjustment).

[0071] Once the corrector circuit 224 determines an adjustment value, in some embodiments, the corrector circuit 224 uses the adjustment value in order to diagnose a faulty component in the aftertreatment system 120. Because the adjustment value captures the current state of the aftertreatment system 120, by comparing the adjustment value to an expected value that captures the state of the aftertreatment system 120 at a previous point in time, a difference between the current state and the previous state of the aftertreatment system 120 can be determined. Although the corrector circuit 224 can expect to see a certain amount of difference over time due to expected aging of components, if the corrector circuit 224 determines that the difference is dramatic (i.e., greater than a predefined error threshold), the corrector circuit 224 can determine that there is an error in the system 100 and raise 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 can issue a command to utilize the first SCR system 523 and the SCR 123 in response to the determination that there is an error in order to address some of the issues that can accompany the error in the system 100 (e.g., higher EONOx due to engine 110 component failure).

[0072] In some of these embodiments, the error threshold is a dynamic threshold such that the corrector circuit 224 can adjust and change the error threshold in order to account for operational changes through aging, ambient environment, or some other expected event. For example, as components of the aftertreatment system 120 age, the corrector circuit 224 can increase the error threshold (i.e., need a greater difference to be met) in order to account for expected changes in performance of the SCR catalyst 126 that accompany aging. The amount of increase to the error threshold can be based on a lookup table that provides values based on expected differences in component aging.

[0073] Alternatively, the corrector circuit 224 can maintain a substantially constant error threshold throughout the life 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 in order to provide a more relevant rate of change. As described above, because the adjusted value can change over the life of the system 100 due to expected aging, the corrector circuit 224 can expect a certain amount of change in the adjusted value on a near-constant basis. However, because this amount of change is expected, any amount of change that greatly exceeds this expected amount can indicate an error or faulty component in the system 100.

[0074] Once the corrector circuit 224 determines that there is an error or faulty component, the corrector circuit 224 can work in conjunction with the sensors to determine the particular component or class of components (i.e., aftertreatment system 120 components, engine 110 components, etc.). For example, if the ammonia storage state has exceeded the error threshold and the NOx sensor 128 indicates an unacceptably high SONOx value, the corrector circuit 224 can determine that the SCR catalyst 126 is degrading due to an abnormally high level of stored ammonia, while still not reducing NOx to an acceptable level.

[0075] In some embodiments, the corrector circuit 224 works in conjunction with the predictor circuit 222 by providing the adjusted value to the predictor circuit 222, which then uses the adjusted value to update the predetermined value that establishes the target value or threshold for the SCR catalyst 126 state. As a result, the predictor circuit 222 is able to more effectively issue commands to the various system 100 components in order to manage the performance of the aftertreatment system 120, because the predetermined value used to make decisions regarding these commands is more closely aligned with the current performance of the system 100.

[0076] Reference is now made to Figure 6FIG. 4, shows a flowchart of a method of managing NOx and ammonia in an exhaust aftertreatment system, according to an example embodiment. The method 400 begins at step 410, where the controller 140 receives information about the operation of the system 100, including sensed values from sensors (e.g., NOx, temperature, exhaust flow, etc.), load on the engine 110, information about environmental conditions (e.g., temperature, humidity, etc.), and / or other information about the operation of the system 100. The information from step 410 is used as input to steps 420 and 430. At step 420, the controller 140 uses the input from step 410 to generate or inform an axially resolved model of the catalyst (in this example, the SCR catalyst 126) via the modeling circuit 220. At step 430, the controller 140 uses the input from step 410 to update the model to improve the overall utility of the method 400 via the corrector circuit 224. The method then proceeds to step 440, where the controller 140 actively manages the aftertreatment system 120 (specifically, the SCR catalyst 126) based on the modeling circuit 220 via the predictor circuit 222 in order to maintain acceptable SONOx levels and reduce ammonia slip. Finally, the method 400 advances to step 450, where the controller 140 issues commands to components of the system 100 based on determinations made by the predictor circuit 222 at step 440. In some embodiments, steps 440 and 450 can be combined in a single step.

[0077] Further, while primarily referencing modeling circuit 220 providing a model of SCR catalyst 126, the model having a monitored state generally for NOx reduction and ammonia storage, modeling circuit 220 can be configured to generate a similar axially resolved model of DOC 122, the model having a monitored state generally for soot accumulation on DOC 122 and related regeneration events. In these soot-related embodiments, the monitored state is the amount of soot accumulation, such that the monitored state of modeling DOC 122 is the amount of soot accumulation on each portion. Modeling circuit 220 develops and updates the axially resolved model of DOC 122 based on sensed values from sensors, the sensed values relating to exhaust flow and pressure through the portions of DOC 122 (as soot accumulation restricts flow and increases pressure). Thus, in these soot-related embodiments, the commands issued by predictor circuit 222 are primarily thermal management commands directed to removing soot (i.e., increasing the temperature of the exhaust gas passing through aftertreatment system 120 in order to burn off accumulated soot). As discussed above with respect to the NOx reduction and ammonia storage embodiments, predictor circuit 222 can utilize additional utility from modeling multiple portions of DOC 122 in order to more effectively regenerate those portions of DOC 122 most affected by soot accumulation. For example, if there is a greater amount of soot accumulation on a rear portion of DOC 122 than on a front portion, then increasing exhaust gas temperature would not be an effective regeneration strategy, as hot exhaust gas would most directly affect the front portion of DOC 122, which in this example does not need regeneration.

[0078] Similarly, the principles and methods discussed herein also apply to generating an axially resolved model of the DPF 121 that focuses on hydrocarbon (HC) accumulation, for example, on portions of the DPF 121. In these HC-related embodiments, the monitored state is the amount of HC accumulation, so that the monitored state of the modeled DPF 121 is the amount of HC accumulation on each portion. The modeling circuit 220 develops and updates the axially resolved model of the DPF 121 based on sensed values from the sensors related to exhaust flow and pressure on portions of the DPF 121 (as HC accumulation restricts flow and increases pressure). Thus, in these HC-related embodiments, the commands issued by the predictor circuit 222 are primarily directed to thermal management commands (i.e., increasing the temperature of the exhaust gas passing through the aftertreatment system 120 in order to burn off accumulated HC). As discussed above with respect to the NOx reduction and ammonia storage embodiments and the soot-related embodiments, the predictor circuit 222 can exploit additional utility from modeling multiple portions of the DPF 121 in order to more effectively regenerate those portions of the DPF 121 most affected by soot accumulation. For example, if there is a greater amount of soot accumulation on a front portion of the DPF 121 than on a rear portion, then increasing the exhaust gas temperature would be a particularly effective regeneration strategy because hot exhaust gas would most directly affect the front portion of the DOC 122, which in this example is the portion most in need of regeneration.

[0079] As used herein, the terms "approximately," "about," "substantially" and similar terms are intended to have a broad meaning in harmony with the common and accepted usage of these terms by those of ordinary skill in the art to which the subject matter of this present disclosure pertains. It is to be understood that such terms are intended to be employed as specified with respect to modifying a particular stated feature or function when such terms are used in connection with a description of certain novel and useful embodiments of the present disclosure. At the very least, therefore, these terms are to be understood as indicating that a stated feature or function is not to be taken literally and is to be interpreted to encomass not only the stated feature or function recited directly from any claims issued on the present disclosure but also equivalent, functionally or structurally similar features or functions that would have been claimed by one of ordinary skill in the art who prepared this present disclosure and which pertain to several if not all of the novel and useful embodiments of the present disclosure.

[0080] It should be noted that the terms "exemplary," and variations thereof, as used herein to describe various embodiments, are intended to set a reciprocal example. It should be understood that these terms are not intended to imply that a certain embodiment is necessarily an exemplary embodiment or that an exemplary embodiment is necessarily exceptional, unique or superior.

[0081] As used herein, the term "coupled" and variations thereof, means the two members are directly or indirectly connected to one another. Such connection can be permanent (e.g., permanent or fixed) or removable (e.g., removable or releasable). Such connection can be achieved either by direct coupling of the two members to one another, by coupling of the two members to one another using one or more intervening members, or by coupling of the two members to one another using an intervening member that is integrally formed with one of the two members as a single unitary body. If "coupled" or variations thereof are modified by an additional term (e.g., directly coupled), the generic definition of "coupled" provided above is modified by the plain language meaning of the additional term (e.g., "directly coupled" means the connection of two members without any intervening member), resulting in a narrower definition of "coupled" than the generic definition provided above. Such coupling can be mechanical, electrical, or fluidic. For example, circuit A is communicatively "coupled" to circuit B can mean that circuit A is in direct communication with circuit B (i.e., no intermediaries) or in indirect communication with circuit B (e.g., through one or more intermediaries).

[0082] References herein to the position of elements (e.g., "top," "bottom," "above," "below") are used only to describe the orientation of the various elements in the drawings. It should be noted that the orientation of the various elements can differ according to other example embodiments, and such variations are intended to be encompassed within the present disclosure.

[0083] Although a variety of circuits having specific functionality are shown in Figure 4 the controller 140 can include any number of circuits for accomplishing the functionality described herein. For example, the activities and functionality of the modeling circuit 220, the predictor circuit 222, and the corrector circuit 224 can be combined into multiple circuits or as a single circuit. Additional circuits having additional functionality can also be included. Furthermore, the controller 140 can further control other activities beyond the scope of the present disclosure.

[0084] As described above, and in one configuration, "circuitry" can be implemented in a machine-readable medium for execution by various Figure 2 Figure 2The various types of processors of the processor 204 execute the executable code. For example, the executable code can include one or more physical or logical blocks of computer instructions that may, for instance, be organized as an object, procedure, or function. However, the executable need not be physically located together, but can include different instructions stored in different locations which, when joined logically together, comprise the circuit and achieve the stated purpose of the circuit. Indeed, a circuit of computer readable program code can be a single instruction, or many instructions, and can even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data can be identified and illustrated herein within the circuit, and can be embodied in any suitable form and organized within any suitable type of data structure. The operational data can be collected as a single data set, or can be distributed over different locations including over different storage devices, and can exist, at least partially, merely as electronic signals on a system or network.

[0085] While the term "processor" is briefly defined above, the terms "processor" and "processing circuitry" should be interpreted broadly. In this regard, and as described 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 structured to execute instructions provided by memory. The one or more processors can take the form of a single core processor, multi-core processor (e.g., dual-core processors, triple-core processors, quad-core processors, etc.), microprocessors, etc. In some embodiments, the one or more processors can be external to the apparatus, e.g., the one or more processors can be a remote processor (e.g., a cloud-based processor). Alternatively or additionally, the one or more processors can be internal and / or local to the apparatus. In this regard, a given circuit or component thereof can be arranged locally (e.g., as part of a local server, local computing system, etc.) or remotely (e.g., as part of a remote server such as a cloud-based server). To this end, a "circuit" as described herein can include components that are distributed over one or more locations.

[0086] Although the flow diagrams and associated descriptions can show a specific order of method steps, the order of these steps can differ from what is depicted and described, unless specified differently above. Also, two or more steps can be performed concurrently or with partial concurrence. Such variation can depend, for example, on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps, and decision steps.

Claims

1. A system comprising: an aftertreatment system; and a controller coupled to the aftertreatment system, the controller configured to: generate a spatially resolved model of a catalyst of the aftertreatment system, the spatially resolved model dividing the catalyst into one or more portions; and 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, wherein the catalyst is a first selective catalytic reduction (SCR) catalyst, and wherein the aftertreatment system includes a second selective catalytic reduction (SCR) catalyst upstream of the first selective catalytic reduction (SCR) catalyst.

2. The system of claim 1, wherein, the controller further configured to: compare one or more modeled values from the spatially resolved model to one or more desired values of the aftertreatment system; and in response to the comparison, command at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more desired values.

3. The system of claim 2, wherein, adjust the spatially resolved model, the controller further configured to: determine a gradient between the one or more sensed values from at least one sensor upstream of the one or more portions and the one or more sensed values from at least one sensor downstream of the one or more portions; and assign new modeled values to the one or more portions based on the determined gradient.

4. The system of claim 1, wherein, the controller further configured to: compare one or more modeled values from the spatially resolved model to one or more desired values of the catalyst; and identify a fault in the aftertreatment system based on a difference between the one or more modeled values and the one or more desired values exceeding an error threshold.

5. The system of any one of claims 1 to 4, wherein, the catalyst is a combination of the first selective catalytic reduction (SCR) catalyst and an ammonia oxidation catalyst (AMOX).

6. The system of any one of claims 1 to 4, wherein, the second selective catalytic reduction (SCR) catalyst is relatively smaller than the first selective catalytic reduction (SCR) catalyst.

7. The system of claim 1, further comprising a first reductant doser fluidly coupled to the first selective catalytic reduction (SCR) catalyst and a second reductant doser fluidly coupled to the second selective catalytic reduction (SCR) catalyst.

8. The system of claim 7, wherein, the controller further configured to: control dosing commands for the first reductant doser based on one or more modeled values for spatially resolved models of the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst.

9. The system of claim 8, wherein, The one or more modeled values are indicative of an amount of stored ammonia of one or more portions of the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst, and wherein the dosing command of the first reductant doser is based on a comparison of the one or more modeled values indicative of the amount of stored ammonia of the one or more portions of the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst to an ammonia storage threshold value.

10. The system of claim 7, wherein, The controller is further configured to: control a dosing command for the second reductant doser based on one or more modeled values of a spatially resolved model for the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst.

11. The system of claim 10, wherein, The one or more modeled values are indicative of an amount of stored ammonia of one or more portions of the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst, and wherein the dosing command of the second reductant doser is based on a comparison of the one or more modeled values indicative of the amount of stored ammonia of the one or more portions of the first selective catalytic reduction (SCR) catalyst and the second selective catalytic reduction (SCR) catalyst to an ammonia storage threshold value.

12. A method comprising: generating, by a controller coupled to an aftertreatment system, a spatially resolved model of a catalyst of the aftertreatment system, the spatially resolved model dividing the catalyst into one or more portions; and adjusting, by the controller, 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, wherein the catalyst is a first selective catalytic reduction (SCR) catalyst, and wherein the aftertreatment system includes a second selective catalytic reduction (SCR) catalyst upstream of the first selective catalytic reduction (SCR) catalyst.

13. The method of claim 12, further comprising: comparing, by the controller, one or more modeled values from the spatially resolved model to one or more desired values of the aftertreatment system; and in response to the comparison, commanding, by the controller, at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more desired values.

14. The method of claim 13, wherein, Adjusting the spatially resolved model includes: determining, by the controller, a gradient between the one or more sensed values from at least one sensor upstream of the one or more portions and the one or more sensed values from at least one sensor downstream of the one or more portions; and assigning, by the controller, new modeled values to the one or more portions based on the determined gradient.

15. The method of claim 12, further comprising: comparing, by the controller, one or more modeled values from the spatially resolved model to one or more expected values of the catalyst; and identifying, by the controller, a fault in the aftertreatment system based on a difference between the one or more modeled values and the one or more expected values exceeding an error threshold.

16. The method of any one of claims 12 to 15, wherein, the catalyst is a combination of the first selective catalytic reduction (SCR) catalyst and an ammonia oxidation catalyst (AMOX).

17. A system comprising: processing circuitry including at least one processor coupled to a memory having instructions stored therein that, when executed by the at least one processor, cause the processing circuitry to: generate a spatially resolved model of a catalyst of an aftertreatment system, the spatially resolved model dividing the catalyst into one or more portions; and 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, wherein the catalyst is a first selective catalytic reduction (SCR) catalyst, and wherein the aftertreatment system includes a second selective catalytic reduction (SCR) catalyst positioned upstream of the first selective catalytic reduction (SCR) catalyst.

18. The system of claim 17, wherein, the instructions, when executed by the at least one processor, further cause the processing circuitry to: compare one or more modeled values from the spatially resolved model to one or more expected values of the aftertreatment system; and in response to the comparison, command at least one of an engine, a heater, or a doser of the aftertreatment system to achieve the one or more expected values.

19. The system of claim 18, wherein, the instructions, when executed by the at least one processor, further cause the processing circuitry to: determine a 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 assign new modeled values to the one or more portions based on the determined gradient.

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