Systems and methods for particulate matter estimation and aftertreatment system controls

Abstract

A system includes an aftertreatment system including a filter configured to receive an exhaust gas species, and a controller coupled to the aftertreatment system. The controller includes a memory storing instructions thereon that, when executed by a processor, cause the controller to: receive, from a first sensor, a pressure value regarding the filter, receive a flow rate of an exhaust gas species into the filter, determine a first estimated load of the exhaust gas species on the filter, determine a second estimated load of the exhaust gas species on the filter, determine, based on one or both of the first estimated load or the second estimated load, a third estimated load of the exhaust gas species on the filter, and adjust operation of an engine coupled to the aftertreatment system based on the third estimated load of the exhaust gas species on the filter.

Description

SYSTEMS AND METHODS FOR PARTICULATE MATTER ESTIMATION AND AFTERTREATMENT SYSTEM CONTROLSCROSS-REFERENCE TO RELATED PATENT APPLICATIONS|0001] This application claims the benefit of and priority to Indian Provisional Application No.202441080269, filed October 22, 2024, which is incorporated herein by reference in its entirety and for all purposes.TECHNICAL FIELD[0002) The present disclosure relates generally to the field of managing aftertreatment systems. More specifically, the present disclosure relates to managing maldistribution of particulate matter in an aftertreatment system.BACKGROUND[0003J An engine may be coupled to an exhaust aftertreatment system to reduce harmful exhaust gas emissions, such as particulate matter, nitrogen oxides (NOx), etc. In operation, particulate matter may be deposited on a filter of the aftertreatment system. In addition to adversely affecting the ability of exhaust gas to flow through the filter due to the particulate matter deposits, in some cases, the particulate matter may be non-uniformly deposited on the filter. Non-uniform distribution on the filter may cause loading imbalance on the filter, which can lead to undesirable exhaust gas flowrates through the filter and undesirable stresses on the filter. It is thus desirable to manage loading on the filter.SUMMARY

[0004] One embodiment relates to a system. The system includes an aftertreatment system. The aftertreatment system includes a filter configured to selectively receive an exhaust gas species and a controller. The controller includes at least one processing circuit including at least one memory and at least one processor, the at least one memory storing instructions thereon that, when executed by the at least one processor, cause the controller to: receive, from a first sensorconfigured to detect a pressure regarding the filer, a pressure value regarding the filter; receive a flow rate of the exhaust gas species into the filter; determine, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter; determine, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter; determine, based on one or both of the first estimated load or the second estimated load, a third estimated load of the exhaust gas species on the filter; and adjust operation of an engine coupled to the aftertreatment system based on the third estimated load of the exhaust gas species on the filter.|0005| Another embodiment relates to a method. The method includes: receiving, by one or more processors, from a first sensor configured to detect a pressure regarding a filter, a pressure value regarding the filter; receiving, by the one or more processors, a flow rate of an exhaust gas species into the filter; determining, by the one or more processors, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter; determining, by the one or more processors, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter; determining, by the one or more processors, based on one or both of the first estimated load and the second estimated load, a third estimated load of the exhaust gas species on the filter; and adjusting, by the one or more processors, operation of a component of a system including the filter based on the third estimated load of the exhaust gas species on the filter.

[0006] Still another embodiment relates to one or more non-transitory computer-readable media storing instructions thereon that, when executed by one or more processors, cause the one or more processors to perform operations including: receiving, from a first sensor configured to detect a pressure regarding a filter, a pressure value regarding the filter; receiving a flow rate of an exhaust gas species into the filter; determining, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter; determining, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter; determining, based on one or both of the first estimated load or the second estimated load, a third estimated load of the exhaust gas species on the filter; and adjusting operation of an engine based on the third estimated load of the exhaust gas species on the filter.[0007} Numerous specific details are provided to impart a thorough understanding of embodiments of the subject matter of the present disclosure. The described features of the subject matter of the present disclosure may be combined in any suitable manner in one or more embodiments and / or implementations. In this regard, one or more features of an aspect of the invention may be combined with one or more features of a different aspect of the invention. Moreover, additional features may be recognized in certain embodiments and / or implementations that may not be present in all embodiments or implementations.BRIEF DESCRIPTION OF THE FIGURES

[0008] FIG. 1 is a block diagram of a system for estimating particulate matter in an aftertreatment system, according to an exemplary embodiment.|0009| FIG. 2 is a block diagram of a controller of the system of FIG. 1, according to an exemplary embodiment.|0010| FIG. 3 is a depiction of a particulate filter with particulate matter maldistribution, according to an exemplary embodiment.

[0011] FIG. 4 is a block diagram showing a method of estimating particulate matter in an aftertreatment system, according to an exemplary embodiment.[0012) FIG. 5 is a flowchart showing a method of estimating particulate matter in an aftertreatment system, according to an exemplary embodiment.DETAILED DESCRIPTION

[0013] Following below are more detailed descriptions of various concepts related to, and implementations of, methods, apparatuses, and systems for managing emissions from engine systems with exhaust aftertreatment systems. Before turning to the Figures, which illustrate certain exemplary embodiments in detail, it should be understood that the present disclosure is not limited to the details or methodology set forth in the description or illustrated in theFigures. It should also be understood that the terminology used herein is for the purpose of description only and should not be regarded as limiting.

[0014] The systems, computer-readable media, and methods described herein are operable to accurately or relatively accurately determine or estimate particulate matter, such as soot, formed in an aftertreatment system. Soot, also referred to herein as particulate matter, forms during engine operation of a system, such as system embodied in a vehicle. The deposition of particulate matter may occur linearly as soot is deposited on a particulate filter of an aftertreatment system and a “soot cake” is formed over the particulate filter. In some operating conditions, particulate matter may be deposited non-linearly, leading to maldistribution or non-uniform distribution of particulate matter on the filter. Consequently, particulate matter may be non-uniformly oxidized and / or removed from the particulate filter during regeneration events. Additionally, a particulate filter may include one or more walls. The walls of the particulate filter may be porous and as a result, particulate matter from the engine may enter and settle into the pores of the filter. When the pores are filled, the filter may be referred to as being in a “wall plug” state. When the pores are not filled, the filter may be referred to as being in a “wall clean” state. In the wall clean state, particulate matter may still be distributed on a surface of the filter.

[0015] When particulate matter is passively removed from the particulate filter, the filter may be non-uniformly oxidized due to a temperature of the particulate filter and a NOx-to-particulate matter (PM) ratio of the particulate filter. The NOx value may refer to an outlet NOx value (e.g., a NOx value exiting the engine and entering the particulate filter). The PM value may be a value of particulate matter entering the particulate filter. Passive removal of particulate matter may refer to a process where exhaust gas temperatures are increased during normal operation of the engine / system to burn off particulate matter accumulated on the wall layer of the particulate filter. Passive removal of particulate matter may also be referred to as “passive regeneration.” In comparison, active removal / active regeneration refers to express commands to operate the engine / system at various operating points to raise exhaust aftertreatment temperatures and remove the accumulated particulate matter (e.g., increase engine speed and / or torque, command post-combustion fuel injections, activate a heater, etc.).In either situation, non-uniform oxidation may lead to data degradation because the filter may have portions with varying particulate matter concentrations. As such, for the same soot load entering the particulate filter, multiple pressure values may be determined / recorded. Varying pressure values across the particulate filter may cause various problems. For example, over time, the pressure value may indicate that a particulate matter load is decreasing, while in reality, the particulate matter load is increasing. This is due to the non-uniform distribution pressure distribution across the filter. The estimated particulate matter load is based on the pressure signal and used to determine target temperatures of the particulate filter, as well as when active regeneration should occur to clean the particulate filter. For example, a particulate matter load on the particulate filter may be above a threshold value that indicates that regeneration should occur, but a pressure sensor may be positioned at a location of the filter that indicates the particulate matter load is less than the threshold value. Based on the sensor value being below the regeneration pressure threshold, the system may set higher target temperatures of the aftertreatment system to regenerate the filter. However, because the temperatures are based on a relatively low particulate matter pressure value, the increased temperatures may cause a thermal event and / or subsequent particulate filter problems to occur. A thermal event, as applied to particulate matter on a filter in the aftertreatment system, refers to an uncontrolled combustion. In various examples, a thermal event may mean that particulate matter burns and the resulting elevated temperature may cause cracking or melting of the particulate filter.

[0016] When a particulate matter load is predicted to be lower than an actual particulate matter load at a certain time and the engine drops to a low load operating condition (e.g., an idle event) where air flow is relatively less, a controller of the vehicle may raise an oxygen level (e.g., an amount of oxygen entering the engine of the vehicle) during a regeneration time. During that time, the particulate filter may melt due to a poor particulate matter load estimation. The increased amount of oxygen may lead to higher combustion temperatures and, in turn, a susceptibility to filter melting. Further, when the particulate matter load is under predicted and hot exhaust gas moves through the particulate filter, uncontrollable combustion may occur, causing the particulate filter to crack and / or causing other errors or failure modes.

[0017] Systems with low application duty cycles (e.g., ecommerce vehicles, buses, etc.) may have a greater risk of particulate filter problems arising due to particulate matter maldistribution and improper estimation due to the system operating at a lower duty cycle where air flow is less and temperatures are lower.[00181 Therefore, systems, methods, and computer-readable media for accurately or relatively accurately estimating a particulate matter load on a particulate filter is desired to prevent such problems, and others, from occurring or likely occurring. The systems, computer-readable media, and methods described herein utilize sensor data, such as flow rates, pressure values, filter temperatures, and NOx to PM ratios, to estimate a particulate matter load. The sensor data is used as at least one input (e.g., to various processes, models, lookup tables, etc.) to determine an accurate or relatively accurate PM load on the particulate filter. Specifically, the systems, computer-readable media, and methods described herein generate a first particulate matter load estimate assuming that the particulate filter wall is clean (e.g., no PM in the pores or the pore occupancy being below a threshold limit to coincide / behave like a clean wall particulate filter), and a second particulate latter load estimate assuming the particulate filter wall is plugged (e.g., PM has filled the pores). The systems, computer-readable media, and methods determine a weighting factor based on the temperature of the filter and a NOx-to-PM ratio. The weighting factor refers to at least one weight that is applied or assigned to the first and second particulate matter load estimates in determining the final load estimation. In some embodiments, the systems, computer-readable media, and methods may perform an altitude check to determine an adjustment to the final PM load estimate based on an altitude of operation of the system.

[0019] As described herein, the systems, computer-readable media, and methods may provide a relatively more accurate estimation of particulate matter, expressed as a particulate matter load, on the particulate filter of the aftertreatment system. By generating a particulate matter estimation using a weighted value associated with each of a clean filter and a plugged filter, the estimation may be more accurate than relying solely on a pressure differential determined by a pressure sensor. In this way, the pressure sensor may be located in a single location and therefore cannot account for particulate matter maldistribution. This increased accuracy may cause fewer potential problems with the particulate filter by not adjusting temperatures of thefilter (e.g., during active regeneration) to be at or above cracking and / or melting temperatures to mitigate against a cracking or a melting of the filter. In this regard, the systems, methods, and computer-readable media described herein may protect the particulate filter and other components of an aftertreatment system from malfunctioning or damage (e.g., cracking, melting, etc.).

[0020] As described herein, a controller may include a circuit configured to estimate an amount of particulate matter in the particulate filter that is more accurate than relying solely on a pressure sensor reading. The estimation may be used by the controller to adjust operation of the vehicle (e.g., the engine). For example, the controller may utilize the estimation to lower an engine operation temperature (e.g., lowering an exhaust gas temperature by reducing a power output (e.g., speed and / or torque) of the engine to prevent or attempt to prevent a cracking of the particulate filter (or other adverse operational aspect). These and other features and benefits are described more fully herein below.

[0021] Referring now to FIG. 1, a system 100 is shown, according to an exemplary embodiment. The system 100 may be embodied in vehicle, which may be configured as an onroad or an off-road vehicle (e.g., front end loaders, bulldozers, etc.) including, but not limited to, line-haul trucks, mid-range trucks (e.g., pick-up trucks), cars (e.g., sedans), and any other type of vehicle. In other embodiments, the system 100, or portions thereof, may be embodied in non-vehicle applications, such as in generator sets. It should be also understood that in other embodiments, more, different, and / or fewer components of the system 100 may be included in the system 100 without departing from the spirit and scope of the present disclosure.

[0022] The system 100 is shown to include an engine 120, an aftertreatment system 140 in exhaust gas receiving communication with the engine 120, and sensors 160. The system 100 may also include a controller 130 (as shown in FIG. 2), where the controller 130 is communicably coupled to each of the aforementioned components.

[0023] The system 100 may be embodied in a vehicle, as in the example shown. In some embodiments, the vehicle may be structured as a hybrid vehicle, such as a series hybrid vehicle that includes one or more electric motors and one or more internal combustion engines. Thepowertrain may be a series electric / hybrid powertrain. The powertrain may include at least the electric machine and the engine 120. In various embodiments, the powertrain may include one or more batteries. In the example shown, the system 100 is driven, at least partly, by an internal combustion engine, shown as an engine 120. In this example, the system 100 is included in a non-hybrid vehicle. The engine 120 may utilize various types of fuel, such as diesel, gasoline, natural gas, dual fuel, biodiesel, E-85, or any other suitable type of fuel. According to one embodiment and as shown, the engine 120 is structured as a compression-ignition internal combustion engine that utilizes diesel fuel. However, in various alternate embodiments, the engine 120 may be structured as any other type of engine (e.g., spark-ignition) that utilizes any type of fuel (e.g., gasoline, natural gas, hydrogen, etc.). Within the engine 120, air from the atmosphere is combined with fuel, and combusted, to power the engine 120. Combustion of the fuel and air in the compression chambers of the engine 120 produces exhaust gas that is operatively vented to an exhaust manifold and to the exhaust aftertreatment system 140. The engine 120 may power and / or propel the vehicle embodying the system 100 via a powertrain.

[0024] As shown in FIG. 1, the system 100 includes an aftertreatment system, shown as exhaust aftertreatment system 140. The exhaust aftertreatment system 140 is in exhaust gasreceiving communication with the engine 120. The aftertreatment system 140 is configured to receive exhaust gas (e.g., diesel exhaust gas, etc.) from the engine 120 (e.g., internal combustion engine, etc.) and treat constituents (e.g., NOx, CO, CO2, etc.) of the exhaust gas. The engine 120 is configured to (e.g., structured to, able to, etc.) receive a fluid mixture of fuel (e.g., diesel, gasoline, hydrogen, etc.) and air, combust the fluid mixture, and provide an exhaust based on combustion of the fluid mixture. The engine 120 combusts fuel and generates an exhaust gas that includes, for example, NOx, CO, CO2, and / or other constituents.

[0025] The aftertreatment system 140 includes an exhaust conduit 102 (e.g., channel, duct, pipe, tube, chute, conduit, etc.) that is fluidly coupled to the engine 120. The exhaust conduit 102 is structured to receive exhaust gas from the engine 120 via an inlet. The exhaust conduit 102 is structured to release treated exhaust via outlet 146. Treated exhaust can include exhaust that has been treated to removed particulate matter and / or reduced constituents of the exhaust gas such as NOx gases, CO, unbumt hydrocarbons, etc.[0026} The aftertreatment system 140 includes a particulate filter 116. Because the example shows the system 100 being embodied in a vehicle with a compression-ignition engine, the particulate filter 116 may be a diesel particulate filter (DPF). In other embodiments, a different type of filter may be utilized (e.g., a catalyzed soot filter (CSF), etc.). Thus and based on the foregoing, the particulate filter 116 may be referred to throughout as the particulate filter 116. The particulate filter 116 is coupled to the exhaust conduit 102 and is configured to remove particulate matter, such as soot, from the exhaust flowing through the aftertreatment system 140. The particulate filter 116 includes an inlet, where the exhaust is received, and an outlet, where the exhaust exits after having particulate matter substantially filtered from the exhaust and / or converting the particulate matter into various other exhaust gas species.|0027) The particulate filter 116 may comprise or be composed of a porous material. In some embodiments, the particulate filter 116 may include a ceramic filter. In some embodiments, the particulate filter 116 may include a cordierite filter which can, for example, be an asymmetric filter. The particulate filter 116 may include walls made of the porous material that define channels within the particulate filter 116. The exhaust gases may flow through the porous walls of the particulate filter 116. In various embodiments, particulate matter may flow through the walls of the particulate filter 116 and / or through channels formed by the walls of the particulate filter 116.[0028| In various embodiments, particulate matter may be received, deposited, or distributed on the particulate filter 116 in a non-linear or non-uniform manner. Therefore, the particulate filter 116 may include portions with both high and low particulate matter concentrations, which may lead to non-uniform oxidation and removal of the particulate matter. In some embodiments, the deposition of particulate matter may occur linearly as soot is deposited on the particulate filter 116 and a “soot cake” is formed over the particulate filter 116. Non-linear deposition may lead to maldistribution or non-uniform distribution of particulate matter on the particulate filter 116, causing non-uniform oxidation and / or removal from the particulate filter 116, leading to potential malfunctions or problems with the particulate filter 116. Walls of the particulate filter 116 may be porous and as a result, particulate matter from the engine may enter and settle into the pores of the filter. When more than a predefined amount (e.g., amajority) of the pores are plugged or filled, this condition is referred to as a “wall plug” state herein. When less than the predefined amount of the pores are filled (i.e., a majority of the pores are not filled), the filter may be referred to as being in a “wall clean” state. In the wall clean state, particulate matter may still be distributed on a surface of the filter.

[0029] In various embodiments, the aftertreatment system 140 may additionally or alternatively include a diesel oxidation catalyst (DOC). The aftertreatment system 140 may include more than one of any of the various components positioned in any of various positions relative to each other along the exhaust flow path as desired. Therefore, the architecture of the exhaust aftertreatment system 140 shown in FIG. 1 is for illustrative purposes and should not be limiting.

[0030] The DOC may have any of various flow-through designs. Generally, the DOC is structured to oxidize at least some particulate matter, e.g., the soluble organic fraction of soot, in the exhaust and reduce unburned hydrocarbons and carbon monoxide (CO) in the exhaust to less environmentally harmful compounds. For example, the DOC may be structured to reduce the hydrocarbon and CO concentrations in the exhaust to meet the requisite emissions standards for those components of the exhaust gas. An indirect consequence of the oxidation capabilities of the DOC is the ability of the DOC to oxidize NO into NO2. In this manner, the level of NO2 the DOC is equal to the NO2 in the exhaust gas generated by the engine 120 plus the NO2 converted from NO by the DOC.

[0031] In addition to treating the hydrocarbon and CO concentrations in the exhaust gas, the DOC may also be used in the controlled regeneration of the particulate filter 116 and the catalyst system 155. This can be accomplished through the injection, or dosing, of unburned HC into the exhaust gas upstream of the DOC. Upon contact with the DOC, the unburned HC undergoes an exothermic oxidation reaction which leads to an increase in the temperature of the exhaust gas exiting the DOC and subsequently entering the particulate filter 116 and / or the catalyst system 155. The amount of unburned HC added to the exhaust gas is selected to achieve the desired temperature increase or target controlled regeneration temperature.[0032} The aftertreatment system 140 includes a decomposition chamber 118 (e.g., reactor, reactor pipe, conduit, housing, etc.) disposed downstream of the particulate filter 116. The decomposition chamber 118 is configured to receive the exhaust from the particulate filter 116. The aftertreatment system 140 further includes a fluid delivery system coupled to the decomposition chamber 118. The fluid delivery system is configured to deliver treatment fluid to the decomposition chamber 118 (e.g., reductant). When the reductant is introduced into the exhaust, reduction of emission of undesirable components (e.g., NOx, etc.) in the exhaust may be facilitated. The decomposition chamber 118 includes an inlet in fluid communication with the particulate filter 116 to receive the exhaust containing NOx emissions and an outlet for the exhaust, NOx emissions, ammonia, and / or the treatment fluid to flow to downstream components of the aftertreatment system 140.

[0033] The fluid delivery system includes a doser assembly 124 (e.g., a dosing module, etc.) configured to dose the fluid into the decomposition chamber 118 (e.g., via an injector). The doser assembly 124 is mounted to the decomposition chamber 118 such that the doser assembly 124 may dose the fluid into the exhaust flowing through the exhaust conduit 102. The doser assembly 124 includes at least one injector 132 (e.g., reductant injector). Each injector 132 is configured to inject the fluid into the exhaust (e.g., within the decomposition chamber 118, etc.). The injector 132 is configured to insert reductant (e.g., a combined flow of reductant and compressed air) into the decomposition chamber 118.

[0034] The aftertreatment system 140 includes a catalyst system 155. The catalyst system 155 is configured to decompose constituents of the exhaust gas flowing through the exhaust conduit 102. In some embodiments, the catalyst system 155 includes a catalyst member (e.g., a selective catalytic reduction (SCR) catalyst member, SCR catalyst, etc.) disposed downstream of the decomposition chamber 118. As a result, the fluid is injected upstream of the catalyst member such that the catalyst member receives a mixture of the fluid and exhaust. Droplets of the fluid undergo processes of evaporation, thermolysis, and hydrolysis to form non-NOx emissions (e.g., gaseous ammonia, etc.) when reacted with the SCR catalyst. The SCR catalyst is configured to catalyze decomposition of NOx gases into its constituents in the presence of a reductant. Any suitable SCR catalyst may be used such as, for example, platinum, palladium,rhodium, cerium, iron, manganese, copper, vanadium-based catalyst, any other suitable catalyst, or a combination thereof. The SCR catalyst may be disposed on a suitable substrate such as, for example, a ceramic (e.g., cordierite) or metallic (e.g., Kanthal) monolith core that can, for example, define a honeycomb structure. In other embodiments, the catalyst system 155 includes an ammonia oxidation catalyst (AMOx).

[0035] In some embodiments, the particulate filter 116 may be positioned downstream of the decomposition chamber 118. In other embodiments, the particulate filter 116 may be positioned upstream of the decomposition chamber 118. In still other embodiments, the particulate filter 116 and the catalyst system 155 may be combined into a single unit.

[0036] The controller 130 is structured to control, at least partly, the operation of the system 100 and associated sub-systems, such as the engine 120. Communication between and among the components may be via any number of wired or wireless connections. For example, a wired connection may include a serial cable, a fiber optic cable, a CAT5 cable, or any other form of wired connection. In comparison, a wireless connection may include the Internet, Wi-Fi, cellular, radio, etc. In one embodiment, a controller 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 the controller 130 is communicably coupled to the systems and components of FIG. 1, the controller 130 is structured to receive data from one or more of the components shown in FIG. 1. The structure and function of the controller 130 is further described in regard to FIG. 2.

[0037] As the components FIG. 1 are shown to be embodied in the vehicle, the controller 130 may be structured as one or more vehicle electronic control units (ECUs). The controller 130 may be separate from or included with at least one of a transmission control unit, an exhaust aftertreatment control unit, a powertrain control module, an engine control unit or engine control module, etc. Thus, the controller 130 may comprise one or more microcontrollers. The controller 130 will be described in greater detail with reference to FIG. 2.

[0038] As shown, the system 100 may include one or more sensors 160. In some embodiments, the system 100 may include any number, placement, or type of sensors 160. The sensors 160may be configured to acquire data regarding the operation of the system 100 (e.g., operational data of the vehicle that embodies the system 100). The sensors may include engine-related sensors (e.g., torque sensors, speed sensors, pressure sensors, flowrate sensors, temperature sensors, etc.). The sensors 160 may further include sensors associated with other components of the vehicle / system, such as the aftertreatment system 140. In various embodiments, the sensors 160 may determine an amount of a substance or receive information / data regarding an amount of a substance in the aftertreatment system 140. For example, the sensors 160 may determine an amount of ammonia, NOx, NO2, etc. in the aftertreatment system 140. The sensors 160 may be positioned at one or more locations in the aftertreatment system 140. For example, as shown in FIG. 1, sensors 160 may be placed downstream the particulate filter 116 and upstream the decomposition chamber 118. Additionally or alternatively, sensors 160 may be positioned downstream the decomposition chamber 118 and upstream the catalyst system 155. In various embodiments, the sensors 160 may be temperature sensors.

[0039] The sensors 160 may be positioned on or proximate the particulate filter 116. In various examples, the sensors 160 may include one or more pressure sensors configured to sense or determine a change in pressure (delta P) across the particulate filter 116 (i.e., the change in pressure from the inlet of the particulate filter relative to the outlet). In one embodiment, an inlet pressure sensor may determine or sense an inlet pressure while an outlet pressure sensor may determine or sense an outlet pressure. The difference between the inlet and the outlet pressure may be the change in pressure, or delta P. In other embodiments, a single pressure sensor may be utilized. In still other embodiments, a different configuration may be used to determine the pressure change across the particulate filter. The delta P may correspond to an estimated particulate matter load on the particulate filter 116. As described above, particulate matter (e.g., soot) may be non-uniformly distributed across the particulate filter 116. As a result, the pressure signal from the pressure sensor 160 may not accurately indicate pressure at every location on the particulate filter 116, thereby causing an incorrect estimation of an overall amount of particulate matter on the particulate filter 116. Further, the pressure reading may depend on the location of the sensor 160 on the particulate filter 116. For example, a sensor 160 may be positioned on or proximate to a portion of the particulate filter 116 where lessparticulate matter is distributed relative to other portions of the particulate filter 116. Thus, the pressure sensor reading may indicate that an amount of particulate matter on the filter is less than what is actually on the filter because the sensor is not determining the pressure at a location of the filter where more particulate matter has been distributed.[00401 The sensors 160 may be configured to determine or receive an air temperature, such as a temperature of air entering the engine 120 and / or regarding the aftertreatment system 140. Temperature sensors 160 may be positioned at one or more locations in the system 100. For example, sensors 160 may be positioned at or proximate the engine 120 and at various locations within and / or proximate the aftertreatment system 140. For example, the sensors 160 may determine or receive a temperature of ambient air entering the system 100. In various embodiments, the sensors 160 may determine or receive a temperature of the air exiting the engine 120. In various embodiments, the sensors 160 may determine or receive a temperature of the exhaust gas in the aftertreatment system 140. For example, the sensors 160 may determine a temperature of the exhaust gas at the exhaust conduit 102 and / or the outlet 146.|0041| The sensors 160 may be real or virtual (i.e., a non-physical sensor that is structured as program logic in the controller 130 that makes various estimations or determinations). For example, an engine speed sensor may be a real or virtual sensor arranged to measure or otherwise acquire data, values, or information indicative of a speed of an engine of the powertrain (typically expressed in revolutions-per-minute). The sensor is coupled to the engine (when structured as a real sensor) and is structured to send a signal to the controller 130 indicative of the speed of the engine 120. When structured as a virtual sensor, at least one input may be used by the controller 130 in an algorithm, model, lookup table, etc. to determine or estimate a parameter of the engine (e.g., power output, etc.). Any of the sensors 160 described herein may be real or virtual.[0042| The controller 130 is coupled, and particularly communicably coupled, to the sensors 160. Accordingly, the controller 130 is structured to receive data from one more of the sensors 160 and provide instruct ons / informati on to the one or more sensors 160. The received datamay be used by the controller 130 to control one more components in the system 100 and / or for monitoring and thermal management purposes.

[0043] Referring to FIG. 2, a schematic diagram of the controller 130 of the system 100 of FIG. 1 is shown, according to an example embodiment. As shown in FIG. 2, the controller 130 includes at least one processing circuit 210 having at least one processor 212 and at least one memory or memory device 214. The controller 130 also includes a particulate matter circuit 230 and a weighting factor circuit 240 each coupled to one another and the processing circuit 210. The controller 130 includes a communications interface 220, a particulate matter circuit 230, and a weighting factor circuit 240.[00441 In one configuration, one or more of the particulate matter circuit 230 or the weighting factor circuit 240 is embodied as machine or computer readable media that stores instructions and that is executable by a processor, such as processor 212. As described herein and amongst other uses, the machine-readable media facilitates performance of certain operations to enable reception and transmission of data. For example, the machine-readable media may provide an instruction (e.g., command, etc.) to, e.g., acquire data. In this regard, the machine-readable media may include programmable logic that defines the frequency of acquisition of the data or transmission of the data (i.e., trigger logic). The computer readable media may include code, which may be written in any programming language including, but not limited to, Java or the like and any conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program code may be executed on one processor or multiple remote processors. In the latter scenario, the remote processors may be connected to each other through any type of network (e.g., CAN bus, etc.).

[0045] In another configuration, one or more of the particulate matter circuit 230 or the weighting factor circuit 240 is embodied as a hardware unit, such as separate and distinct electronic control units. As such, the one or more of the particulate matter circuit 230 and the weighting factor circuit 240 may be embodied as one or more circuitry components including, but not limited to, processing circuitry, network interfaces, peripheral devices, input devices, output devices, sensors, etc. In some embodiments, one or more of the particulate matter circuit230 and the weighting factor circuit 240 may take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (IC), discrete circuits, system on a chip (SOCs) circuits, microcontrollers, etc.), telecommunication circuits, hybrid circuits, and any other type of “circuit.” In this regard, one or more of the particulate matter circuit 230 and the weighting factor circuit 240 may include any type of component for accomplishing or facilitating achievement of the operations described herein. For example, a circuit as described herein may include one or more transistors, logic gates (e.g., NAND, AND, NOR, OR, XOR, NOT, XNOR, etc.), resistors, multiplexers, registers, capacitors, inductors, diodes, wiring, and so on). One or more of the particulate matter circuit 230 and the weighting factor circuit 240 may also include programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like. One or more of the particulate matter circuit 230 and the weighting factor circuit 240 may include one or more memory devices for storing instructions that are executable by the processor(s) of one or more of the particulate matter circuit 230 and the weighting factor circuit 240. The one or more memory devices and processor(s) may have the same definition as provided below with respect to the memory device 214 and processor 212. In some hardware unit configurations, one or more of the particulate matter circuit 230 and the weighting factor circuit 240 may be geographically dispersed throughout separate locations in the vehicle / system relative to other components of the controller 130. Alternatively, and as shown, one or more of the particulate matter circuit 230 and the weighting factor circuit 240 may be embodied in or within a single unit / housing, which is shown as the controller 130.

[0046] In the example shown, the controller 130 includes the at least one processing circuit 210 having the at least one processor 212 and the at least one memory device 214. The at least one processing circuit 210 may be structured or configured to execute or implement the instructions, commands, and / or control processes described herein with respect to one or more of the particulate matter circuit 230 and the weighting factor circuit 240. The depicted configuration represents one or more of the particulate matter circuit 230 and the weighting factor circuit 240 as instructions stored in non-transitory machine or computer-readable media. However, as mentioned above, this illustration is not meant to be limiting as the presentdisclosure contemplates other embodiments where one or more of the particulate matter circuit 230 and the weighting factor circuit 240, or at least one circuit of one or more of the particulate matter circuit 230 and the weighting factor circuit 240, is configured as a hardware unit. All such combinations and variations are intended to fall within the scope of the present disclosure.

[0047] The at least one processor 212 may be one or more of 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. In this way, the at least one processor 212 may be a microprocessor, a state machine, or other suitable processor. The at least one processor 212 also may be implemented as a combination of computing devices, such 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, the one or more processors may be shared by multiple circuits (e g., the one or more of the particulate matter circuit 230 and the weighting factor circuit 240 may comprise or otherwise share the same processor which, in some example embodiments, may execute instructions stored, or otherwise accessed, via different areas of memory). Alternatively or additionally, the one or more processors may be structured to perform or otherwise execute certain operations independent of one or more co-processors. In other example embodiments, two or more processors may be coupled via a bus to enable independent, parallel, pipelined, or multithreaded instruction execution. All such variations are intended to fall within the scope of the present disclosure.

[0048] The at least one memory device 214 (e.g., memory, memory unit, storage device) may 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 at least one memory device 214 may be communicably connected to the at least one processor 212 to provide computer code or instructions to the at least one processor 212 for executing at least some of the processes described herein. Moreover, the at least one memory device 214 may be or include tangible,non-transient volatile memory or non-volatile memory. Accordingly, the at least one memory device 214 may include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described herein.

[0049] The controller 130 may be configured to estimate an amount of particulate matter (e.g., soot) on the particulate filter 116 (e.g., a DPF). In various embodiments, the controller 130 may determine a delta pressure-based soot load estimation (DPSLE) value by determining a pressure differential across (e.g., from the inlet face to the outlet face) the particulate filter 116.Therefore, reference may be made throughout to a DPSLE value. It should be understood that an estimation of particulate matter can be made for additional or alternative types of particulate matter beyond soot.

[0050] The particulate matter circuit 230 may determine and, particularly estimate, an amount of particulate matter on the particulate filter 116 using a combination of sensor data and / or other processes, such as lookup table values. The particulate matter circuit 230 may receive sensor data from one or more sensors 160. In one embodiment, the sensors may be positioned at an inlet and an outlet of the particulate filter 116. Sensor data may include flow rate data. Specifically, one or more sensors 160 may be configured to sense actual cubic meter per second (ACMS) data indicative of a volumetric flow rate of exhaust gas through the particulate filter 116 (e.g., based on an inlet and outlet flow rate reading where the difference represents the “through” amount, estimated based on an outlet value or an inlet flow rate value, or another methodology). One or more sensors may also be configured to sense a pressure on the particulate filter 116. In some embodiments, a first sensor may be positioned at the inlet of the particulate filter 116 and receive data indicative of conditions (e.g., a first pressure value, a first flow rate, etc.) of the particulate filter 116 at the inlet. A second sensor may be positioned at the outlet of the particulate filter 116 and receive data indicative of conditions (e.g., a second pressure value, a second flow rate, etc.) of the particulate filter 116 at the outlet. A pressure across the particulate filter 116 (e.g., a pressure differential) may be determined by determining a difference between a pressure reading at the first sensor and a pressure reading by the secondsensor. In some embodiments, a single sensor may be positioned at or proximate the particulate filter 116 configured to sense a pressure on the particulate filter 116.

[0051] As described herein, for the same particulate matter load on the particulate filter 116, two different sets of sensors positioned at the inlet and outlet of the particulate filter 116 may obtain two different pressure readings due to the maldistribution of the particulate matter. For example, a first set of sensors may be positioned at a left side of the inlet and a left side of the outlet of the particulate filter 116, and a second set of sensors may be positioned at a right side of the inlet and a right side of the outlet. Due to maldistribution of particulate matter, the pressure differential sensed by the first set of sensors may be different than the pressure differential sensed by the second set of sensors.

[0052] The flow rate data and pressure data received by the particulate matter circuit 230 from the sensors 160 may be used to estimate a particulate matter load (e.g., as inputs to one or more models, lookup tables, etc ). In one embodiment, the controller 130 may have a plurality of lookup tables stored, for example, in the memory 214. The lookup tables may be two-dimensional tables that correlate exhaust gas flow through the particulate filter 116 and pressure differential on the particulate filter 116 with estimated particulate matter load values on the particulate filter 116.

[0053] A first lookup table stored in the controller 130 may be a wall clean table. The wall clean table may include estimated particulate load values corresponding to a state of the particulate filter 116 where the filter is assumed to be a fresh, unloaded filter (or loaded but the load value is below a predefined amount). The particulate filter 116 may be capable of holding up to a threshold amount of particulate matter before adverse performance ensues, which may lead to replacement to prevent or minimize damage to the aftertreatment system 140 and / or the system 100 (e.g., vehicle). For each flow rate and pressure value, a corresponding particulate matter estimation may be output by the particulate matter circuit 230 that assumes that the particulate filter 116 in the aftertreatment system 140 is a clean filter with little to no particulate matter in the filter (e g., substantially below the threshold value). As such, for any flow rate and pressure value, particulate matter load estimations based on the wall clean lookup table may belower than an actual particulate matter load on the particulate filter 116, because the particulate matter may be non-uniformly distributed (e.g., the flow rate and pressure value sensor readings were taken at a portion of the filter with a lower distribution of particulate matter).

[0054] A second lookup table may also be stored in the controller 130. The second lookup table may be a wall plug table. The wall plug table may include estimated particulate load values corresponding to a state of the particulate filter 116 where the filter is assumed to be loaded (e.g., “plugged”) or where the load value is at or above a predefined amount. For each flow rate and pressure value, a corresponding particulate matter estimation may be output that assumes that the particulate filter 116 in the aftertreatment system 140 is a used filter with particulate matter substantially at or above the threshold value in the filter. As such, for any flow rate and pressure value, particulate matter load estimations based on the wall plug lookup table may be greater than an actual particulate matter load on the particulate filter 116, because the particulate matter may be non-uniformly distributed (e.g., the flow rate and pressure value sensor readings were taken at a portion of the filter with a higher distribution of particulate matter).

[0055] As previously stated, the flow rate sensor data and the pressure sensor data are used as inputs to each of the first and second lookup tables of the controller 130. The flow rate and pressure values are used as inputs to the wall clean table. The particulate matter circuit 230 utilizes the inputs to generate, as an output, a first particulate matter estimate. Similarly, the same flow rate and pressure values are used as inputs to the wall plug table. The particulate matter circuit 230 utilizes the inputs to generate, as an output, a second particulate matter estimate. For the same flow rate and pressure values, the first particulate matter estimate may have a lower value than the second particulate matter estimate. One or both of the first and second particulate matter estimates may be used by the particulate matter circuit 230 to determine a final particulate matter estimate. In various embodiments, the particulate matter circuit 230 may use algorithms, mathematical models, a combination thereof, a combination including lookup tables, or other method or combination of methods to estimate a particulate load value on the particulate filter 116.[0056} In various embodiments, the weighting factor circuit 240 may be used to generate at least one weighting factor, weight or weight value, weighting value, or weighting factor value. The weighting factor circuit 240 may generate and assign weights to one or both of the first and second particulate matter estimates generated by the particulate matter circuit 230 to determine how much impact each of the first and second particulate matter estimates has on the final particulate matter estimate or determination. Determining a final particulate matter estimate based only on the flow rate of exhaust gas across the particulate filter 116 and a pressure on the particulate filter 116 may cause inaccurate final estimations. For example, a sensor configured to sense the flow rate of the exhaust gas may fail or deliver an incorrect reading, so an incorrect input is used for the lookup table. Similarly, due to particulate matter maldistribution, the pressure reading may be inaccurate. Using only one of the first or second particulate matter estimates or automatically giving equal weight to each of the first and second particulate matter estimates to determine the final particulate matter estimate may also cause an inaccurate final estimation.

[0057] The weighting factor circuit 240 may receive, from one or more sensors 160, a temperature value and a ratio. Specifically, the weighting factor circuit 240 may receive a temperature value of the particulate filter 116 (e.g., a DPF bed temperature value or another type of particulate matter temperature value) and a ratio of a first exhaust gas species to a second exhaust gas species, particularly NOx to particulate matter (PM). In various embodiments, the NOx value may be determined using sensor data from an engine-out NOx sensor (e.g., a sensor positioned at an outlet of the engine 120), a NOx sensor positioned proximate an inlet and / or an outlet of the particulate filter 116, or a NOx sensor positioned elsewhere, which acquires data indicative of NOx in the exhaust gas at the particular location. Further, the PM value may be determined by a particulate matter sensor, which may be real and / or virtual. The PM value may be determined by sensing or measuring a concentration of particles at the sensor (e.g., at an inlet to the DPF, at an outlet of the DPF, at an outlet of the engine, an average or other value of PM in the aftertreatment system such as an average value based on PM readings from various PM sensors in the system, etc.). In various embodiments,the NOx to PM ratio may be calculated or otherwise determined by the weighting factor circuit 240 upon receiving the sensor data.

[0058] In one embodiment, the particulate filter bed temperature and the NOx to PM ratio may be primary factors in controlling or determining the non-linearly of particulate matter distribution across the particulate filter 116. Sensor data indicating a real-time particulate filter bed temperature and a real-time NOx to PM ratio may allow the controller 130 to determine real-time conditions of the aftertreatment system 140 and estimate a real-time particulate matter load on the particulate filter 116. In various embodiments, soot settled on the particulate filter 116 may be oxidized due to a greater (e.g., a above a certain threshold value) bed temperature value and / or NOx to PM ratio. In various embodiments, the bed temperature and / or NOx to PM ratio may be based on a catalyst-only architecture of the aftertreatment system 140, where there is a higher NOx to PM ratio operation. As such, particulate matter may be passively oxidized due to the higher ratio, and the controller 130 may be utilized to determine a weighting factor for each of the first and second particulate matter estimates.[00591 As previously stated, the weighting factor may be based on the bed temperature of the particulate filter 116 and / or the NOx to PM ratio. For example, when the bed temperature is determined to be at or above a certain threshold value, at least some of the particulate matter may be oxidized. Further, when the NOx to PM ratio is at or below a certain threshold value, a greater amount of particulate matter may be determined to be entering the particulate filter 116.

[0060] The particulate filter bed temperature and the NOx to PM ratio may be used as inputs to determine, by the weighting factor circuit 240, the weighting factors given to the first and second particulate matter estimates. The weighting factor circuit 240 may use a weighting factor lookup table, an algorithm, a mathematical model, a combination thereof, or any other method to determine the weighting factor. The lookup table, algorithm, model, etc. may be stored by the controller (e.g., in the memory device 214) and retrieved and used by the weighting factor circuit 240. In various embodiments, the weighting factor lookup table may be a two dimensional table that outputs one or more weighting factors. For example, the outputs may be a first weighting factor corresponding to a weight of the first particulate matter estimateand a second weighting factor corresponding to a weight of the second particulate matter estimate. For example, based on the bed temperature and the NOx to PM ratio (e.g., the amount of particulate matter estimated to be on the particulate filter), the first particulate matter estimate may be given a weight of X % (e.g., 30%) while the second particulate matter estimate may be given a weight of Y % (e.g., 70%). The values in the weighting factor lookup table (and / or the wall clean / wall plug lookup tables) may be based on an interpolation scheme. For example, the wall clean and wall plug lookup tables may be tables of weightings based on flow conditions and pressure values. Values may be selected by the controller from the wall clean and wall plug lookup tables and weightings may be selected from the weighting factor table for each of the estimated values corresponding to the wall clean and wall plug tables. These values may be combined to give a final estimated particulate matter value.

[0061] In various embodiments, the weighting factors may total a predefined value, such as 100%, 1, or another predefined value. For example, the first particulate matter estimate may be given a weight of 60% while the second particulate matter estimate may be given a weight of 40%, such that the total is 100%. The weighting factors may reflect a real-time estimation of particulate matter on the filter. For example, if the particulate matter circuit 230 estimates that there is a high amount of particulate matter on the filter particulate, the weighting factor circuit 240 may assign a greater weight to the second particulate matter estimate than the first particulate matter estimate when the particulate matter circuit 230 estimates the final particulate matter estimation. This is because the first particulate matter estimate estimates a particulate matter value when the particulate filter 116 is assumed to be completely or substantially clean (e.g., particulate matter in the filter is below a predefined threshold value). In various embodiments, a low bed temperature and a low NOx to PM ratio may cause the weighting factor circuit 240 to assign a heavier weight to the estimate output from the wall plug table. Further, a high bed temperature and a high NOx to PM ratio may cause the weighting factor circuit 240 to assign a heavier weight to the estimate output from the wall clean table.

[0062] In various embodiments, when one or more of the bed temperature and / or the NOx to PM ratio are at or above a first threshold value, the estimate based on the wall clean table may be given a weight of 100% and the estimate based on the wall plug table may be given a weightof 0% by the weighting factor circuit (i.e., provide and assign a relatively higher value based on the wall clean table versus the wall plug table). Conversely, when one or more of the bed temperature and / or the NOx to PM ratio are at or below a second threshold value, the estimate based on the wall clean table may be given a weight of 0% and the estimate based on the wall plug table may be given a weight of 100% by the weighting factor circuit 240. When one or more of the bed temperature and / or the NOx to PM ratio are between the first and second threshold values, the estimate based on the wall clean table and the estimate based on the wall plug table may each be given a weight between 0 and 100, depending on the specific bed temperature values and NOx to PM ratio values.

[0063] Upon determining the weighting factor, the weighting factor circuit 240 may transmit the weighting factor(s) to the particulate matter circuit 230 for use in determining the final particulate matter estimate. The particulate matter circuit 230 may determine the final particulate matter estimate by multiplying each of the first and second particulate matter estimates by the corresponding weighting factor and summing the results.[00641 In various embodiments, an altitude check may be performed by the particulate matter circuit 230 prior to and / or after calculating the final particulate matter estimate. The NOx to PM ratio may be calculated or determined using a virtual sensor. At or above a certain predefined altitude, the particulate matter value used to calculate the ratio may be inaccurate, causing an incorrect NOx to PM ratio to be generated. For example, at or above a certain altitude, less oxygen may be available in the atmosphere, leading to less NOx production. Therefore, the engine 120 may have an increased amount of particulate matter and a decreased amount of NOx in the exhaust gas as compared to when the system 100 (e.g., vehicle) is operating at sea level. Further, sensor readings of particulate matter values at altitude may have high error values associated, causing an estimate particulate matter estimate to be lower than the actual value. In various embodiments, NOx production and / or exhaust gas flow may vary with the change in altitude (e.g., linearly, exponentially, etc.).[0065) To perform an altitude check, the particulate matter circuit 230 determines or checks (e.g., using data from a sensor 160) the air density / and or altitude at the location of engineoperation of the system 100 (e.g., vehicle). When the engine 120 is determined by the particulate matter circuit 230 to be operating at or above a first altitude and / or air density value, there may be a higher possibility of greater particulate matter load generation on the particulate filter 116. As such, the particulate matter circuit 230 may estimate the final particulate matter estimate based solely on the wall plug lookup table matter (e.g., the weighting factor is 100% for the wall plug estimate and 0% for the wall clean estimate) to account for the higher likelihood of the engine having more particulate matter (e.g., a higher likelihood of a sootier engine). Conversely, when the system 100 (e.g., engine 120) is determined to be operating at or below a second altitude and / or air density value, pores of the particulate filter 116 may be unlikely to be filled. As such, the particulate matter circuit 230 may estimate the final particulate matter estimate based solely on the wall clean lookup table to account for the fact that the particulate filter 116 is unlikely to be loaded with particulate matter (e.g., the weighting factor is 100% for the wall clean estimate and 0% for the wall plug estimate). For example, when the engine 120 is operating at sea level, the particulate matter circuit 230 may use only the wall clean table to make the final particulate matter estimate. When the altitude and / or air density is determined to be between the first and second threshold values, the particulate matter circuit 230 may use a combination of the wall clean and wall plug lookup table values (and, in some embodiments, the weighting factors) to generate the final particulate matter estimate. For example, when the engine 120 operates above sea level but below an upper altitude threshold value, a weighting factor may be interpolated and used to determine the final particulate matter estimate.

[0066] Upon determination of the final particulate matter estimate by the particulate matter circuit 230, the controller 130 may adjust operation of the engine 120. For example, upon determination of the final particulate matter estimate, the controller 130 may use the final estimate to trigger one or more particulate matter-based fault codes and / or operations.Specifically, the controller 130 may initiate and perform or allow performance of an active or passive regeneration (e.g., active or passive soot removal) operation to clean the particulate filter 116 of particulate matter. For example, the particulate matter circuit 230 may determine that the final particulate matter estimate is at or above a threshold value, indicating that theparticulate filter 116 should be cleaned and a regeneration should occur. As a result, the controller 130 may cause a regeneration, which can include various operations to increase exhaust gas temperature (e.g., increasing a power output, activating an exhaust system heater, post-cylinder fuel injection, etc.) to burn or remove particulate matter from the particulate filter 116. The controller 130 may also remove or reduce vehicle and / or engine restrictions to enable a passive regeneration to occur. During a passive regeneration, operation of the system 100 (e.g., vehicle) and engine 120 may cause regeneration to occur without user input, such as when the system 100 (e.g., vehicle) is experiencing an elevated load for a long period of time (e.g., going uphill). In contrast, an active regeneration is specifically commanded.

[0067] In some embodiments, the controller 130 may, in response, generate a fault code indicating malfunctioning of the particulate filter 116 due to the estimated amount of particulate matter on the particulate filter 116. Responsive to the fault code generation, the controller 130 may initiate a particulate matter removal operation (e.g., a regeneration) to resolve the fault code and allow proper functioning of the particulate filter 116. For example, the controller 130 may raise exhaust aftertreatment temperatures and remove the accumulated particulate matter on the particulate filter 116.[0068) Referring now to FIG. 3, a particulate filter 116 is shown, according to an exemplary embodiment. The particulate filter 116 illustrates particulate matter maldistribution across a face of the particulate filter 116. Areas 310 and 320 of the particulate filter 116 show areas of low particulate matter concentration and high particulate matter concentration, separated by a boundary 330. Less particulate matter coming from the engine 120 into the particulate filter 116 may be deposited into the area 310 relative to the area 320. In various embodiments, pressure sensors may be positioned on the inlet and outlet faces of the particulate filter 116 within the area 310. The pressure differential determined by the particulate matter circuit 230 when the pressure sensors are positioned in the area 310 may determine a lower particulate matter concentration than the actual concentration within the particulate filter 116. Further, pressure sensors may be positioned on the inlet and outlet faces of the particulate filter 116 within the area 320. The pressure differential determined by the particulate matter circuit 230when the pressure sensors are positioned in the area 320 may determine a higher particulate matter concentration than the actual concentration within the particulate filter 116.

[0069] Referring now to FIG. 4, a block diagram showing a method 400 of estimating particulate matter in an aftertreatment system is shown, according to an exemplary embodiment. The processes performed in the method 400 may be performed by one or more components of the system 100. For example, the processes may be performed by the controller 130 (e.g., the particulate matter circuit 230 and / or the weighting factor circuit 240). It should be noted that although the method 400 shows a specific order and composition of method steps, it is understood that the order of these steps may differ from what is depicted. Further, some steps may be performed concurrently. Some steps that are performed as discrete steps may be combined|0070] Volumetric flow data 402 and pressure data 404 are determined by sensors 160 and used as inputs into each of the wall clean table 406 and the wall plug table 410 that are used by the particulate matter circuit 230 to estimate particulate matter on the particulate filter 116. Using the flow data 402 and the pressure data 404 in the wall clean table 406, the particulate matter circuit 230 determines a first load estimate 408. Using the flow data 402 and the pressure data 404 in the wall plug table 410, the particulate matter circuit 230 determines a second load estimate 412. In various embodiments, the flow data 402 may indicate an exhaust gas flow along a particulate filter (e.g., the particulate filter 116, a DPF, etc.) and the pressure data 404 may indicate a pressure of particulate matter (e.g., soot) on the particulate filter (e.g., a pressure differential). Further, the wall clean table 406 may include estimated load values of particulate matter on the particulate filter when the filter is assumed to be clean and the pores of the filter are assumed to be unplugged (e.g., a particulate matter load is below a predefined threshold value). The wall plug table 410 may include estimated load values of particulate matter on the particulate filter when the filter is assumed to be dirty or used and the pores of the filter are assumed to be plugged (e.g., a particulate matter load is at or above a predefined threshold value).[0071 } Further, a filter bed temperature 414 and a NOx to PM ratio 416 may be determined by sensors 160 (and / or the controller 130) and used as inputs into a weighting factor calculation 418 that is performed by the weighting factor circuit 240. In various examples, the weighting factor calculation 418 is structured as a lookup table, a model, an algorithm, etc. The output of the weighting factor calculation 418 may be the weighting factor 420. The filter temperature 414 and the NOx to PM ratio 416 may indicate an amount of particulate matter on or in the particulate filter, and may therefore affect the weight that each of the first load estimate 408 and the second load estimate 412 are assigned when the particulate matter circuit 230 determines the final load estimate 424. The weighting factor 420 may be expressed as a decimal, percentage, fraction, etc.[0072 [ In various embodiments, the weighting factor 420 may be a weight assigned to the first load estimate 408. That is, the weighting factor calculation 418 may be performed by the weighting factor circuit 240 to generate one weighting factor. In various embodiments, the weighting factor 420 may be a weight assigned to the second load estimate 412. In various other embodiments, the weighting factor calculation 418 may be performed by the weighting factor circuit 240 to generate weighting factors for both the first and second load estimates 408 and 412. In various embodiments, and as shown in FIG. 4, the weighting factor 420 may be a weight assigned to the first load estimate 408. The method 400 may then include subtracting, by the weighting factor circuit 240, the weighting factor 420 from 1 (e.g., when the factor is expressed as a decimal) to determine the weighting factor assigned to the second load estimate 412 (shown as process 426). The weighting factor circuit 240 may multiply each of the weighting factors by their respective load estimates. For example, at process 428, the weighting factor circuit 240 multiplies the first load estimate 408 by the corresponding weighting factor 420 (or the value determined at process 426 when the weighting factor 420 is subtracted from 1). At process 430, the weighting factor circuit 240 multiplies the second load estimate 412 by the corresponding weighting factor 420 (or the value determined at process 426 when the weighting factor 420 is subtracted from 1). At process 432, the weighting factor circuit 240 adds the weighted first and second load estimates together (e.g., the values determined at processes 428 and 430) to determine the final load estimate 424.[0073} At any point during operation of the method 400, an altitude check 422 may be performed by the particulate matter circuit 230. The altitude check may determine at what altitude the engine 120 of the vehicle is operating. When the altitude check 422 indicates that the engine 120 is operating at an altitude high enough that the sensor values (e.g., the NOx to PM ratio 416) are inaccurate, the method 400 may change operation. The method operation may change such that the particulate matter circuit 230 utilizes only the second load estimate 412 to determine the final load estimate 424 to account for inaccurate PM readings that indicate a sensed PM value lower than the actual PM value. When the altitude check 422 indicates that the engine 120 is operating at or near sea level, the method 400 may change operation such that the particulate matter circuit 230 utilizes only the first load estimate 408 to determine the final load estimate 424 to account for no particulate matter being located in the pores of the particulate filter 116. In various embodiments, when the altitude check 422 indicates the engine is operating between sea level and the high altitude, the particulate matter circuit 230 utilizes a combination of the first and second load estimates 408 and 412 to determine the final load estimate 424. Depending on the altitude, the determined weighting factors 420 may remain or change. As such, the particulate matter circuit 230 may perform the altitude check 422 to confirm or refute the processes performed to determine the final load estimate 424. For example, the weighting factor circuit 240 may assign weighting factors 420 of 25% and 75% to the first and second load estimates 408 and 412, respectively. Upon performance of the altitude check 422, the particulate matter circuit 230 may determine that the engine 120 is operating at an altitude high enough that the weights of the first and second load estimates 408 and 412 should be 15% and 85%, respectively.}0074| Referring now to FIG. 5, a flowchart showing a method 500 of estimating an (e.g., at least one) exhaust gas species in an aftertreatment system is shown, according to an exemplary embodiment. The aftertreatment system (e.g., the aftertreatment system 140) may include a filter (e.g., the particulate filter 116) configured to selectively receive particulate matter and / or an exhaust gas species. The aftertreatment system may be coupled to a controller (e.g., the controller 130). One or more components of the system 100 may perform the processesdescribed herein. For example, the controller 130 may perform one or more of the processes described herein.

[0075] At process 502, the particulate matter circuit 230 receives, from a first sensor (e.g., a sensor 160) configured to detect a pressure regarding a filter, a pressure value regarding the filter (e.g., the particulate filter 116). At process 504, the particulate matter circuit 230 receives, from a sensor (e.g., a sensor 160), a flow rate of an exhaust gas species into the filter. In some embodiments, the exhaust gas species is particulate matter (e.g., soot). The flow rate may be expressed as, for example, actual cubic meters per second (ACMS).

[0076] At process 506, the particulate matter circuit 230 determines or receives (e.g., from the sensors 160), based on the pressure value and the flow rate determined at processes 502 and 504, respectively, a first estimated load of the exhaust gas species on the filter. At process 508, the particulate matter circuit 230 determines or receives (e.g., from the sensors 160), based on the pressure value and the flow rate determined at processes 502 and 504, respectively, a second estimated load of the exhaust gas species on the filter.

[0077] At process 510, the particulate matter circuit 230 determines or receives (e.g., from the sensors 160), based on one or both of the first estimated load or the second estimated load estimated at processes 506 and 508, respectively, a third estimated load of the exhaust gas species on the filter.

[0078] In various embodiments, the particulate matter circuit 230 determines or receives (e.g., from the sensors 160), from the sensors 160, an altitude of the system. For example, the particulate matter circuit may receive an altitude at which the engine is operating (e.g., by a sensor 160). Based on the altitude being at or below a first threshold value, the particulate matter circuit 230 uses the first estimated load to determine the third estimated load of the exhaust gas species on the filter. In various embodiments, based on the altitude being at or above a second threshold value, the particulate matter circuit 230 uses only the second estimated load to determine the third estimated load of the exhaust gas species on the filter. The first threshold value may be less than the second threshold value. In various embodiments, based on the altitude being between the first threshold value and the second threshold value, theparticulate matter circuit 230 uses both the first estimated load and the second estimated load to determine the third estimated load of the exhaust gas species on the filter.

[0079] In various embodiments, the weighting factor circuit 240 receives a temperature regarding the filter. Further, in various embodiments, the weighting factor circuit 240 receives a value regarding another exhaust gas species relative to the particulate matter in the aftertreatment system. For example, the exhaust gas species may be a particulate matter, and the other exhaust gas species relative to the particulate matter may be a NOx to PM ratio.. The weighting factor circuit 240 may further determine, based on the temperature and the value regarding another exhaust gas species relative to the particulate matter, a weighting factor. The weighting factor may be used to determine a weight of each of the first estimated load and the second estimated load to be used in determining the third estimated load. In some embodiments, the particulate matter circuit 230 may adjust each of the first estimated load and the second estimated load based on the weighting factor to determine the third estimated load.

[0080] At process 512, the controller 130 may adjust operation of an engine (e.g., the engine 120) coupled to the aftertreatment system (e.g., the aftertreatment system 140) based on the third estimated load of the exhaust gas species on the filter that is determined by the particulate matter circuit 230 at process 510. For example, the controller 130 may adjust an engine operating temperature based on the third estimated load. The controller 130 may perform an active or allow a passive regeneration based on the third estimated load. For example, the particulate matter circuit 230 may determine that the third estimated load is at or above a threshold value indicating that the particulate filter 116 should be cleaned (e.g., particulate matter should be removed). Responsive to this determination, the controller 130 may generate a fault code indicating the particulate filter 116 should be cleaned. In some embodiments, responsive to the determination, the controller 130 may adjust operation of the engine 120 (e g., to raise exhaust aftertreatment temperatures) and remove accumulated particulate matter on the particulate filter 116.

[0081] As utilized herein, the terms “approximately,” “about,” “substantially,” and similar terms are intended to have a broad meaning in harmony with the common and accepted usageby those of ordinary skill in the art to which the subject matter of this disclosure pertains. It should be understood by those of skill in the art who review this disclosure that these terms are intended to allow a description of certain features described and claimed without restricting the scope of these features to the precise numerical ranges provided. Accordingly, these terms should be interpreted as indicating that insubstantial or inconsequential modifications or alterations of the subject matter described and claimed are considered to be within the scope of the disclosure as recited in the appended claims.

[0082] It should be noted that the term “exemplary” and variations thereof, as used herein to describe various embodiments, are intended to indicate that such embodiments are possible examples, representations, or illustrations of possible embodiments (and such terms are not intended to connote that such embodiments are necessarily extraordinary or superlative examples).

[0083] The term “coupled” and variations thereof, as used herein, means the joining of two members directly or indirectly to one another. Such joining may be stationary (e.g., permanent or fixed) or moveable (e.g., removable or releasable). Such joining may be achieved with the two members coupled directly to each other, with the two members coupled to each other using one or more separate intervening members, or with the two members coupled to each other using an intervening member that is integrally formed as a single unitary body with one of the two members. 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 joining of two members without any separate intervening member), resulting in a narrower definition than the generic definition of “coupled” provided above. Such coupling may be mechanical, electrical, or fluidic. For example, circuit A communicably “coupled” to circuit B may signify that the circuit A communicates directly with circuit B (i.e., no intermediary) or communicates indirectly with circuit B (e.g., through one or more intermediaries).

[0084] References herein to the positions of elements (e.g., “top,” “bottom,” “above,” “below”) are merely used to describe the orientation of various elements in the FIGURES. It should benoted that the orientation of various elements may differ according to other exemplary embodiments, and that such variations are intended to be encompassed by the present disclosure.

[0085] While various circuits with particular functionality are shown in FIG. 2, it should be understood that the controller 130 may include any number of circuits for completing the functions described herein. For example, the activities and functionalities of the particulate matter circuit 230 and the weighting factor circuit 240 may be combined in multiple circuits or as a single circuit. Additional circuits with additional functionality may also be included.Further, the controller 130 may further control other activity beyond the scope of the present disclosure.

[0086] As mentioned above and in one configuration, the “circuits” may be implemented in machine-readable medium for execution by one or more of various types of processors, such as the processor 212 of FIG. 2. Executable code may, for instance, comprise one or more physical or logical blocks of computer instructions, which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the circuit and achieve the stated purpose for the circuit. Indeed, a circuit of computer readable program code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within circuits, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network.

[0087] While the term “processor” is briefly defined above, the term “processor” and “processing circuit” are meant to be broadly interpreted. In this regard and as mentioned above, the “processor” may be implemented as one or more processors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), orother suitable electronic data processing components structured to execute instructions provided by memory. The one or more processors may take the form of a single core processor, multi-core processor (e.g., a dual core processor, triple core processor, quad core processor, etc.), microprocessor, etc. In some embodiments, the one or more processors may be external to the apparatus, for example the one or more processors may be a remote processor (e.g., a cloud based processor). Alternatively or additionally, the one or more processors may be internal and / or local to the apparatus. In this regard, a given circuit or components thereof may be disposed locally (e g., as part of a local server, a local computing system, etc.) or remotely (e.g., as part of a remote server such as a cloud based server). To that end, a “circuit” as described herein may include components that are distributed across one or more locations.|(H>88) Embodiments within the scope of the present disclosure include program products comprising computer or machine-readable media for carrying or having computer or machineexecutable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a computer. The computer readable medium may be a tangible computer readable storage medium storing the computer readable program code. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable medium may include but are not limited to a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), an optical storage device, a magnetic storage device, a holographic storage medium, a micromechanical storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, and / or store computer readable program code for use by and / or in connection with an instruction execution system, apparatus, or device. Machine-executable instructions include, for example, instructions and data which cause a computer or processing machine to perform a certain function or group of functions.[0089} The computer readable medium may also be a computer readable signal medium. A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electrical, electro-magnetic, magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport computer readable program code for use by or in connection with an instruction execution system, apparatus, or device.Computer readable program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, Radio Frequency (RF), or the like, or any suitable combination of the foregoing.

[0090] In one embodiment, the computer readable medium may comprise a combination of one or more computer readable storage mediums and one or more computer readable signal mediums. For example, computer readable program code may be both propagated as an electromagnetic signal through a fiber optic cable for execution by a processor and stored on RAM storage device for execution by the processor.

[0091] Computer readable program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more other programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone computer-readable package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).[0092} The program code may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function / act specified in the schematic flowchart diagrams and / or schematic block diagrams block or blocks.

[0093] Although the figures and description may illustrate a specific order of method steps, the order of such steps may differ from what is depicted and described, unless specified differently above. Also, two or more steps may be performed concurrently or with partial concurrence, unless specified differently above. Such variation may 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 of the described methods 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.|0094| It is important to note that the construction and arrangement of the apparatus and system as shown in the various exemplary embodiments is illustrative only. Additionally, any element disclosed in one embodiment may be incorporated or utilized with any other embodiment disclosed herein.

Claims

WHAT IS CLAIMED IS:

1. A system, comprising:an aftertreatment system comprising a filter configured to selectively receive particulate matter; anda controller coupled to the aftertreatment system, the controller including at least one processing circuit including at least one memory and at least one processor, the at least one memory storing instructions thereon that, when executed by the at least one processor, cause the controller to:receive, from a first sensor configured to detect a pressure regarding the filter, a pressure value regarding the filter;receive a flow rate of an exhaust gas species into the filter;determine, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter;determine, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter;determine, based on one or both of the first estimated load or the second estimated load, a third estimated load of the exhaust gas species on the filter; andadjust operation of an engine coupled to the aftertreatment system based on the third estimated load of the exhaust gas species on the filter.

2. The system of claim 1, wherein the exhaust gas species is particulate matter.

3. The system of claim 2, wherein the instructions, when executed by the at least one processor, further cause the controller to:receive a temperature regarding the filter;receive a value regarding another exhaust gas species relative to the particulate matter in the aftertreatment system; anddetermine, based on the temperature and the value regarding another exhaust gas species relative to the particulate matter, a weighting factor.

4. The system of claim 3, wherein the instructions, when executed by the at least one processor, further cause the controller to adjust each of the first estimated load and the second estimated load based on the weighting factor to determine the third estimated load.

5. The system of claim 1, wherein the instructions, when executed by the at least one processor, further cause the controller to :receive an altitude of the system;based on the altitude being at or below a first threshold value, use the first estimated load to determine the third estimated load of the exhaust gas species on the filter;based on the altitude being at or above a second threshold value, use the second estimated load to determine the third estimated load of the exhaust gas species on the filter; and based on the altitude being between the first threshold value and the second threshold value, use both the first estimated load and the second estimated load to determine the third estimated load of the exhaust gas species on the filter.

6. The system of claim 5, wherein the first threshold value is less than the second threshold value.

7. A method, comprising:receiving, by one or more processors, from a first sensor configured to detect a pressure regarding a filter, a pressure value regarding the filter;receiving, by the one or more processors, a flow rate of an exhaust gas species into the filter;determining, by the one or more processors, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter;determining, by the one or more processors, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter;determining, by the one or more processors, based on one or both of the first estimated load and the second estimated load, a third estimated load of the exhaust gas species on the filter; andadjusting, by the one or more processors, operation of a component of a system including the filter based on the third estimated load of the exhaust gas species on the filter.

8. The method of claim 7, wherein the filter is included in an aftertreatment system.

9. The method of claim 8, wherein the exhaust gas species is particulate matter.

10. The method of claim 9, further comprising:receiving, by the one or more processors, a temperature regarding the filter; receiving, by the one or more processors, a value regarding another exhaust gas species relative to the particulate matter in the aftertreatment system; anddetermining, by the one or more processors, based on the temperature and the value regarding another exhaust gas species relative to the particulate matter, a weighting factor.

11. The method of claim 10, further comprising:adjusting, by the one or more processors, each of the first estimated load and the second estimated load based on the weighting factor to determine the third estimated load.

12. The method of claim 7, further comprising:receiving, by the one or more processors, an altitude of the system;based on the altitude being at or below a first threshold value, using the first estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter;based on the altitude being at or above a second threshold value, using the second estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter; andbased on the altitude being between the first threshold value and the second threshold value, using both the first estimated load and the second estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter.

13. The method of claim 12, wherein the first threshold value is less than the second threshold value.

14. One or more non-transitory computer-readable media storing instructions thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising:receiving, from a first sensor configured to detect a pressure regarding a filter, a pressure value regarding the filter;receiving a flow rate of an exhaust gas species into the filter;determining, based on the pressure value and the flow rate, a first estimated load of the exhaust gas species on the filter;determining, based on the pressure value and the flow rate, a second estimated load of the exhaust gas species on the filter;determining, based on one or both of the first estimated load or the second estimated load, a third estimated load of the exhaust gas species on the filter; andadjusting operation of an engine based on the third estimated load of the exhaust gas species on the filter.

15. The non-transitory computer-readable media of claim 14, wherein the filter is included in an aftertreatment system and configured to selectively receive particulate matter.

16. The non-transitory computer-readable media of claim 15, wherein the exhaust gas species is particulate matter.

17. The non-transitory computer-readable media of claim 16, wherein the instructions further cause the one or more processors to perform operations comprising:receiving a temperature regarding the filter;receiving a value regarding another exhaust gas species relative to the particulate matter in the aftertreatment system; anddetermining, based on the temperature and the value regarding another exhaust gas species relative to the particulate matter, a weighting factor.

18. The non-transitory computer-readable media of claim 17, wherein the instructions further cause the one or more processors to perform operations comprising:adjusting each of the first estimated load and the second estimated load based on the weighting factor to determine the third estimated load.

19. The non-transitory computer-readable media of claim 14, wherein the instructions further cause the one or more processors to perform operations comprising:receiving, by the one or more processors, an altitude of a system comprising the filter; based on the altitude being at or below a first threshold value, using the first estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter;based on the altitude being at or above a second threshold value, using the second estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter; andbased on the altitude being between the first threshold value and the second threshold value, using both the first estimated load and the second estimated load to determine, by the one or more processors, the third estimated load of the exhaust gas species on the filter.

20. The non-transitory computer-readable media of claim 19, wherein the first threshold value is less than the second threshold value.

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