System and method for diagnosing component failure

Abstract

A system and method for diagnosing at least one component of an exhaust aftertreatment system is provided. The system includes an exhaust aftertreatment system coupled to an engine system, at least one sensor, and at least one processing circuit configured to: receive initial sensor data; determine an initial parameter value based on the initial sensor data; determine that the initial parameter value does not satisfy an initial threshold value; perform an operation to diagnose at least one component of the exhaust aftertreatment system including: causing the engine system to operate through a sequence of a plurality of engine outputs; receive a plurality of sensor data, each of the plurality of sensor data corresponding to at least one of the plurality of engine outputs; compare each of the plurality of sensor data to a corresponding threshold value; and diagnose the at least one component based on the comparison.

Description

Technical Field

[0001] This disclosure relates to exhaust aftertreatment systems. More specifically, this disclosure relates to systems and methods for diagnosing component failures or potential component failures in exhaust aftertreatment systems using an on-board controller or control system. Background Technology

[0002] Many engines are connected to exhaust aftertreatment systems that reduce harmful emissions such as nitrogen oxides (NOx), sulfur oxides, particulate matter, etc. One or more components of an exhaust aftertreatment system may degrade in performance over time and require maintenance and / or replacement. Onboard sensors and diagnostic systems can be used to monitor the performance of one or more components to determine when maintenance may be needed. Timely and accurate diagnostics and maintenance can be important to help keep exhaust aftertreatment systems and their various systems and devices functioning as required. Summary of the Invention

[0003] One embodiment relates to a system. The system includes an exhaust aftertreatment system coupled to an engine system such that the exhaust aftertreatment system receives exhaust gas from the engine system, at least one sensor, and at least one processing circuit. The at least one processing circuit is configured to: receive initial sensor data from the at least one sensor; determine the initial parameter value based on the initial sensor data; determine that the initial parameter value does not meet the initial threshold; and, in response to determining that the initial parameter value does not meet the initial threshold, perform operations to diagnose at least one component of the exhaust aftertreatment system, the operations including: causing the engine system to operate through a sequence of multiple engine outputs; receiving multiple sensor data from the at least one sensor, each of the multiple sensor data corresponding to at least one of the multiple engine outputs; comparing each of the multiple sensor data with a corresponding threshold of a plurality of thresholds; and diagnosing the at least one component based on the comparisons between the multiple sensor data and the multiple thresholds, the diagnosis indicating a fault type.

[0004] Another embodiment relates to a method for diagnosing at least one component in an exhaust aftertreatment system. The method includes: receiving initial sensor data; determining initial parameter values ​​based on the initial sensor data; determining that the initial parameter values ​​do not meet the initial threshold; and, in response to determining that the initial parameter values ​​do not meet the initial threshold, performing operations to diagnose at least one component of the exhaust aftertreatment system, the operations including: causing an engine to pass through a sequence of multiple engine outputs; receiving multiple sensor data, each of the multiple sensor data corresponding to at least one of the multiple engine outputs; comparing each of the multiple sensor data with a corresponding threshold of a plurality of thresholds; and diagnosing the at least one component based on the comparisons between the multiple sensor data and the multiple thresholds, the diagnosis indicating a fault type.

[0005] Another embodiment relates to an apparatus for diagnosing at least one component in an exhaust aftertreatment system. The apparatus includes at least one processor and at least one memory device storing instructions, which, when executed by the at least one processor, cause the at least one processor to: receive initial sensor data; determine initial parameter values ​​based on the initial sensor data; and determine that the initial parameter values ​​do not meet the initial threshold; and, in response to determining that the initial parameter values ​​do not meet the initial threshold, perform operations to diagnose the at least one component of the exhaust aftertreatment system, the operations including: causing an engine to pass through a sequence of multiple engine outputs; receiving multiple sensor data, each of the multiple sensor data corresponding to at least one of the multiple engine outputs; comparing each of the multiple sensor data with a corresponding threshold of a plurality of thresholds; and diagnosing the at least one component based on the comparisons between the multiple sensor data and the multiple thresholds, the diagnosis indicating a fault type.

[0006] Numerous specific details are provided to provide a thorough understanding of embodiments of the subject matter of this disclosure. In one or more embodiments and / or implementations, the features described in the subject matter of this disclosure may be combined in any suitable manner. In this regard, one or more features of one aspect of the invention may be combined with one or more features of different aspects of the invention. Furthermore, additional features that may not be present in all embodiments or implementations may be identified in certain embodiments and / or implementations. Attached Figure Description

[0007] Figure 1 This is a schematic diagram of a vehicle system according to an exemplary embodiment.

[0008] Figure 2 According to an example embodiment Figure 1 Block diagram of the controller.

[0009] Figure 3A Monitoring according to an exemplary embodiment Figure 1 A flowchart of a method for a vehicle's after-treatment system.

[0010] Figure 3B According to an example embodiment, it is used for Figure 3A The lookup table for the method.

[0011] Figure 4 Monitoring according to an exemplary embodiment Figure 1 A flowchart of a method for a vehicle's after-treatment system. Detailed Implementation

[0012] The following is a more detailed description of various concepts and implementations related to methods, apparatus, and systems for monitoring, diagnosing, reporting, and / or correcting component failures or potential component failures in exhaust aftertreatment systems. Before turning to the accompanying drawings, which illustrate certain exemplary embodiments in detail, it should be understood that this disclosure is not limited to the details or methods set forth in the specification or shown in the drawings. It should also be understood that the terminology used herein is for descriptive purposes only and should not be considered limiting.

[0013] As described herein, an exhaust aftertreatment system may include one or more components, such as a particulate filter configured to remove particulate matter, such as soot, from exhaust gas flowing in an exhaust duct system; a metering module (e.g., a metering feeder) configured to supply metered feed fluid to the exhaust gas flowing in the exhaust system; and one or more catalytic devices (e.g., diesel oxidation catalysts, selective catalytic reduction systems, three-way catalysts, etc.) configured to promote the conversion of exhaust components (e.g., NOx) into less harmful elements (e.g., water). A control system or controller may use one or more sensors (e.g., real sensors and / or virtual sensors) to collect and / or determine sensor data to monitor one or more parameters of the components of the exhaust aftertreatment system. The control system may analyze the sensor data and compare the analyzed sensor data to one or more thresholds. The control system may determine that one or more components of the exhaust aftertreatment system may have failed or may fail, and may further determine that maintenance is required based on the analyzed sensor data exceeding a maximum threshold, falling below a minimum threshold, or otherwise not falling within the expected / acceptable range. The control system may initiate diagnostic operations to determine, based on this determination, which(s) of the exhaust aftertreatment system have failed and / or the type of failure. As described herein, the components may be SCRs, metering units, and / or other components.

[0014] Technically and advantageously, the systems, methods, and apparatus described herein provide an improved control system that uses sensor data to determine whether a component of an aftertreatment system has failed and the type of failure. The control system described herein advantageously utilizes specific control strategies to diagnose one or more components of the exhaust aftertreatment system while the vehicle is in operation. That is, the systems and methods described herein provide technical solutions to technical problems in diagnosing aftertreatment system components by using specific computer-based processes, which advantageously occur while the vehicle is in operation and do not interrupt normal vehicle operation. Advantageously, the diagnosis of one or more components of the exhaust aftertreatment system can be provided to vehicle mechanics (e.g., original equipment manufacturers, vehicle dealers, vehicle repair services, etc.) located away from the vehicle to facilitate potentially necessary repairs or maintenance.

[0015] In an example scenario, a control system (e.g., a controller, vehicle controller, etc.) utilizes one or more sensors (e.g., real sensors and / or virtual sensors) to detect one or more operating parameters of exhaust aftertreatment system components (e.g., particulate filters, selective catalytic reduction (SCR) systems, and / or metering modules or units). The control system may analyze sensor data collected and / or generated by the one or more sensors. Analyzing the sensor data may include using one or more statistical models (such as regression models, machine learning models, etc.) to determine one or more parameters of the components. The control system may compare one or more parameters to corresponding thresholds and, based on this comparison (e.g., parameters exceeding corresponding maximum thresholds or falling below minimum thresholds), determine that one or more exhaust aftertreatment system components have failed or may have failed. The control system may initiate diagnostic operations to determine which component has failed and the type of failure. Diagnostic operations may include adjusting one or more engine outputs, using one or more sensors to detect sensor data including one or more parameters of the exhaust aftertreatment system components(s), and analyzing the sensor data to determine the failed or potentially failed component and the type of failure.

[0016] Furthermore, the improved control system described herein can be part of a hybrid vehicle system. Advantageously, the control system can regulate the operation of the hybrid engine system, for example, by adjusting the reliability of the electric motor in the hybrid vehicle. More specifically, if an aftertreatment system component (e.g., SCR) has failed or is likely to fail, the control system can advantageously increase the use of the electric motor to propel the hybrid vehicle. Increasing the use of the electric motor advantageously reduces the use of the internal combustion engine, thereby reducing exhaust emissions produced by the internal combustion engine.

[0017] Now for reference Figure 1The diagram illustrates a system 100 according to an exemplary embodiment. System 100 includes an engine 101, an aftertreatment system 120 communicating with the engine 101 for exhaust gas reception, an operator input / output (I / O) device 130, and a controller 140, wherein the controller 140 is communicatively coupled to each of the aforementioned components. Figure 1 In this configuration, system 100 is included in a vehicle, particularly a hybrid vehicle. The vehicle can be any type of on-road or off-road vehicle, including but not limited to wheel loaders, forklifts, long-haul trucks, medium-duty trucks (e.g., light cargo vans), four-door sedans, coupes, tanks, aircraft, boats, and any other type of vehicle. In another embodiment, system 100 may be embodied in a stationary device, such as a generator or generator set. All these variations are intended to fall within the scope of this disclosure.

[0018] Engine 101 can be any type of engine that produces exhaust gas, such as a gasoline, natural gas, or diesel engine, and / or any other suitable engine. In the depicted example, engine 101 is part of a hybrid power system having a combination of an internal combustion engine and an electric motor 102 coupled to at least one battery 104. In some embodiments, the hybrid power system can be configured as a mild hybrid system, a parallel hybrid system, a series hybrid system, or a series-parallel power system. In any of these embodiments, battery 104 can be electrically coupled to engine 101, electric motor 102, and / or another component of system 100 (e.g., a regenerative braking system, an alternator, etc.) such that battery 104 is operable to provide power to the electric motor and / or receive power from another component of system 100.

[0019] The aftertreatment system 120 is in exhaust reception communication with the engine 101. In the depicted example, the aftertreatment system includes a diesel oxidation catalyst (DOC) 121, a diesel particulate filter (DPF) 122, and a selective catalytic reduction (SCR) system 123. In some embodiments, the aftertreatment system 120 includes an ammonia slip catalyst (ASC) (not shown). The DOC 121 is configured to receive exhaust gas from the engine 110 and oxidize hydrocarbons and carbon monoxide in the exhaust gas. The DPF 122 is arranged or positioned downstream of the DOC 121 and is configured to remove particulate matter, such as soot, from the exhaust gas flowing in the exhaust stream. The DPF 122 includes an inlet and an outlet, receiving exhaust gas at the inlet and exiting the exhaust gas from the outlet after the particulate matter has been substantially filtered out. In some embodiments, the DPF 122 or other components may be omitted and / or other components may be added (e.g., a second SCR system with additional metering units or modules, multiple DOCs, etc.). Additionally, although in Figure 1The diagram illustrates a specific arrangement of the aftertreatment system 120, but the arrangement of components within the aftertreatment system 120 may differ in other embodiments (e.g., DPF 122 is positioned downstream of SCR 123 and ASC). DOC 121, DPF 122, and SCR 123 may be fluidly connected via exhaust ducts.

[0020] The aftertreatment system 120 may further include a reducing agent delivery system, which may include a decomposition chamber (e.g., a decomposition reactor, reactor pipe, decomposition tube, reactor tube, etc.) to convert the reducing agent into ammonia, shown as a metering module or unit 124. The reducing agent may be, for example, urea, diesel exhaust fluid (DEF). Urea aqueous solution (UWS), urea-containing aqueous solution (e.g., AUS32), and other similar fluids. The metering module 124 may include a reservoir, a pump, and a nozzle (and potentially other components or devices). The reservoir may be configured to store the reducing agent. The pump is fluidly connected to the reservoir and the nozzle via a metering line and is configured to pump the reducing agent from the reservoir to the nozzle. The nozzle may supply the reducing agent to exhaust gas within an exhaust manifold. Adding the reducing agent fluid to the exhaust gas stream aids in catalytic reduction. Figure 1 As shown, the reducing agent can typically be injected upstream of the SCR 123 (or specifically, the SCR catalyst) via a metering module 124, allowing the SCR catalyst to receive the mixture of the reducing agent and the exhaust gas. The reducing agent droplets then undergo evaporation, pyrolysis, and hydrolysis to form gaseous ammonia in the decomposition chamber, the SCR catalyst, and / or the exhaust piping system, which exits the aftertreatment system 120.

[0021] As described above, the aftertreatment system 120 may further include an oxidation catalyst (e.g., DOC 121) fluidly connected to the exhaust piping system to oxidize hydrocarbons and carbon monoxide in the exhaust gas. To properly facilitate this reduction, the DOC 121 may be required to be at a specific operating temperature. In some embodiments, this specific operating temperature is approximately between 200 and 500°C. In other embodiments, the specific operating temperature is the temperature at which the conversion efficiency of the DOC 121 (e.g., the conversion of HC to less harmful compounds, referred to as HC conversion efficiency) exceeds a predetermined threshold.

[0022] SCR 120 is configured to assist in NOx emission reduction by accelerating the NOx reduction process between ammonia and NOx in exhaust gas, which transforms into diatomic nitrogen and water. If the SCR catalyst is not at or above a specific temperature, the acceleration of the NOx reduction process is limited, and the SCR 120 may not operate at the desired conversion efficiency level (i.e., a value indicating the amount of NOx emissions reduced). In some embodiments, this specific temperature is approximately 200-600°C. The SCR catalyst can be made from a combination of inactive materials and an active catalyst, such that the inactive material (e.g., a ceramic substrate) directs exhaust gas to the active catalyst, which is any type of material suitable for catalytic reduction (e.g., metal-exchanged zeolites (Fe or Cu / zeolite), such as base metal oxides like vanadium, molybdenum, and tungsten).

[0023] When ammonia in the exhaust gas does not react with the SCR catalyst (because the SCR 120 is below its operating temperature or because the amount of ammonia being metered far exceeds the amount of NOx), unreacted ammonia can bind to the SCR catalyst and become stored in the SCR 120. When the SCR 120 temperature increases, this stored ammonia is released from the SCR 120, which can cause problems if the amount of ammonia released is greater than the amount of NOx passing through (i.e., more ammonia than the amount of NOx required, which can lead to ammonia slip). In some embodiments, an ASC is included and configured to address ammonia slip by removing at least some of the excess ammonia from the treated exhaust gas before it is released into the atmosphere. As the exhaust gas passes through the ASC, some of the unreacted ammonia remaining in the exhaust gas (i.e., not reacted with NOx) is partially oxidized to NOx, which then reacts with the remaining unreacted ammonia to form N2 gas and water. However, similar to SCR catalysts, if the ASC is not at or above a certain temperature, the acceleration of the NH3 reduction process is limited, and the ASC may not be able to operate at the efficiency level required to meet regulatory or desired parameters. In some embodiments, this specific temperature is approximately 250-300°C.

[0024] As shown in the figure, the aftertreatment system 120 includes multiple sensors 125. The number, placement, and type of sensors included in the aftertreatment system 120 are shown for illustrative purposes only. That is, in other configurations, the number, placement, and type of sensors may differ. Sensors 125 may be NOx sensors, temperature sensors, particulate matter (PM) sensors, flow sensors, other exhaust component sensors, pressure sensors, some combinations thereof, etc. PM sensors are configured to acquire data indicating the PM value (e.g., concentration, such as parts per million) at each location where the PM sensor is located. Temperature sensors are configured to acquire data indicating the temperature value at each location where the temperature sensor is located.

[0025] Sensor 125 may be located in or near engine 101, after engine 101 and before after-treatment system 120, after after-treatment system 120, as shown in the figure within the after-treatment system (e.g., connected to DPF and / or DOC, connected to SCR, etc.), or upstream of engine 101. It should be understood that the sensor's location can vary. In one embodiment, sensors 125 may be present both before and after after-treatment system 120. In one embodiment, at least one of the sensors is configured as an exhaust component sensor (e.g., CO, NOx, PM, SOx, etc.). In another embodiment, at least one of the sensors 125 is configured as a non-exhaust component sensor for estimating exhaust emissions (e.g., temperature, flow rate, pressure, etc.). Additional sensors may also be included in system 100. Sensors may include engine-related sensors (e.g., torque sensor, speed sensor, pressure sensor, flow sensor, temperature sensor, etc.). Sensors may also be sensors associated with other components of the vehicle (e.g., turbocharger speed sensor, fuel quantity and injection rate sensor, fuel rail pressure sensor, etc.).

[0026] Sensor 125 can be real or virtual (i.e., a non-physical sensor configured as program logic in controller 140 to perform various estimations or determinations). For example, an engine speed sensor can be a real or virtual sensor arranged to measure or otherwise acquire data, values, or information indicating the speed of engine 101 (typically expressed in revolutions per minute). The sensor is coupled to the engine (when configured as a real sensor) and configured to send a signal indicating the speed of engine 101 to controller 140. When configured as a virtual sensor, controller 140 can use at least one input in an algorithm, model, lookup table, etc., to determine or estimate engine parameters (e.g., power output, etc.). Any sensor 125 described herein can be real or virtual.

[0027] The controller 140 is coupled, particularly communicatively coupled, to the sensor 125. Therefore, the controller 140 is configured to receive data from one or more sensors 125 and to provide instructions / information to one or more sensors 125. The received data may be used by the controller 140 for one or more components in the control system 100 and / or for monitoring and diagnostic purposes.

[0028] Still referencing Figure 1 Operator input / output (I / O) device 130 is also shown. Operator I / O device 130 can be coupled to controller 140, allowing information to be exchanged between controller 140 and I / O device 130, wherein the information may involve... Figure 1The determination of one or more components or controllers 140 (described below). Operator I / O device 130 enables the operator of system 100 to communicate with controller 140 and Figure 1 The system 100 communicates with one or more components. For example, operator input / output device 130 may include, but is not limited to, an interactive display, a touchscreen device, one or more buttons and switches, a voice command receiver, etc. In this way, operator input / output device 130 can provide the operator with one or more indications or notifications, such as a fault indicator light (MIL). Additionally, the vehicle may include a port that allows controller 140 to connect to or be coupled to a scanning tool, enabling the acquisition of fault codes and other information about the vehicle.

[0029] Controller 140 is configured to at least partially control the operation of system 100 and associated subsystems (such as engine 101 and operator I / O devices 130). Communication between and within components can be achieved via any number of wired or wireless connections. For example, wired connections may include serial cables, fiber optic cables, CAT5 cables, or any other form of wired connection. In contrast, wireless connections may include the Internet, Wi-Fi, cellular, radio, Bluetooth, ZigBee, etc. In some embodiments, 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 controller 140 is communicatively coupled to... Figure 1 The system and components in system 100, so controller 140 is configured to receive from Figure 1 Data for one or more of the components shown. (Refer to...) Figure 2 The structure and function of controller 140 are further described.

[0030] because Figure 1 The components shown are embodied in system 100, and controller 140 may be configured as one or more electronic control units (ECUs), such as one or more microcontrollers. Controller 140 may be separate from or included in at least one of a transmission control unit, an exhaust aftertreatment control unit, a powertrain control module, an engine control module, etc.

[0031] Now for reference Figure 2 This illustrates an exemplary embodiment. Figure 1 A schematic diagram of the controller 140 of system 100. (See diagram below.) Figure 2As shown, controller 140 includes at least one processing circuit 202 having at least one processor 204 and at least one memory device 206, sensor management circuit 210, after-treatment control circuit 212, engine control circuit 214, and communication interface 216. Controller 140 is configured to monitor, diagnose, and report component failures or potential failures in the after-treatment system 120 of system 100. More specifically, controller 140 can determine that system 100 is operating abnormally (e.g., one or more parameters are below a minimum threshold, above a maximum threshold, or outside a predetermined acceptable threshold range), adjust the output parameters of system 100 (e.g., engine 101) to diagnose operation (e.g., by adjusting the use of the internal combustion engine and the electric motor of engine 101), so that system 100 operates at a target output (e.g., target exhaust temperature, target operating point, and / or target exhaust flow rate).

[0032] In one configuration, sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 are embodied as a machine- or computer-readable medium storing instructions executable by a processor (such as processor 204). As described herein and in other uses, the machine-readable medium facilitates the execution of specific operations to achieve the reception and transmission of data. For example, the machine-readable medium can provide instructions (e.g., commands, etc.) to, for example, acquire data. In this respect, the machine-readable medium may include programmable logic defining the data acquisition frequency (or data transmission). The computer-readable medium instructions may include code that can be written in any programming language, including but not limited to Java, and any conventional procedural programming language (such as the "C" programming language or similar programming languages). The computer-readable program code can be executed on one processor or multiple remote processors. In the latter case, the remote processors can be connected to each other via any type of network (e.g., CAN bus, etc.).

[0033] In another configuration, sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 are embodied as hardware units, such as one or more electronic control units. Therefore, sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 can be implemented as one or more circuit components, including but not limited to processing circuitry, network interfaces, peripherals, input devices, output devices, sensors, etc. In some embodiments, sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 can take the form of one or more analog circuits, electronic circuits (e.g., integrated circuits (ICs), discrete circuits, system-on-a-chip (SoC) circuits, microcontrollers, etc.), telecommunication circuits, hybrid circuits, and any other type of "circuit". In this respect, sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 can include any type of components for implementing or facilitating the implementation of the operations described herein. For example, the circuitry 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, etc. Sensor management circuitry 210, afterprocessing control circuitry 212, and / or engine control circuitry 214 may also include programmable hardware devices, such as field-programmable gate arrays, programmable array logic, programmable logic devices, etc. Sensor management circuitry 210, afterprocessing control circuitry 212, and / or engine control circuitry 214 may include one or more memory devices for storing instructions executable by the processor of sensor management circuitry 210, afterprocessing control circuitry 212, and / or engine control circuitry 214. The one or more memory devices and (one or more) processors may have the same definitions as provided below regarding memory device 206 and processor 204. In some hardware unit configurations, sensor management circuitry 210, afterprocessing control circuitry 212, and / or engine control circuitry 214 may be geographically distributed in separate locations within the vehicle. Alternatively, and as shown in the figure, the sensor management circuit 210, the aftertreatment control circuit 212, and / or the engine control circuit 214 may be embodied in a single unit / housing or internally, which is shown as controller 140.

[0034] In the illustrated example, controller 140 includes processing circuitry 202 having a processor 204 and a memory device 206. Processing circuitry 202 may be configured or constructed to execute or implement the instructions, commands, and / or control processes described herein with respect to sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214. The depicted configuration indicates that sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 are embodied in a machine- or computer-readable medium storing instructions. However, as noted above, this description is not intended to be limiting, as other embodiments are contemplated in this disclosure, wherein at least one circuit of sensor management circuitry 210, after-processing control circuitry 212, and / or engine control circuitry 214 is configured as a hardware unit. All such combinations and variations are intended to fall within the scope of this disclosure.

[0035] Processor 204 may be implemented as one or more single-chip or multi-chip processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and / or suitable processors (e.g., other programmable logic devices, discrete hardware components, etc., to perform the functions described herein). The processor may be a microprocessor, a set of processors, etc. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors incorporating a DSP core, or any other such configuration. In some embodiments, one or more processors may be shared by multiple circuits (e.g., sensor management circuitry 210, afterprocessing control circuitry 212, and / or engine control circuitry 214 may include or otherwise share the same processor, which in some example embodiments may execute stored or otherwise accessed via different regions of memory). Optionally or additionally, one or more processors may be configured to perform or otherwise perform certain operations independently of one or more coprocessors. In other example embodiments, two or more processors may be bus-connected to enable independent, parallel, pipelined, or multithreaded instruction execution. All these variations are intended to fall within the scope of this disclosure.

[0036] Memory device 206 (e.g., memory, memory cell, storage device) may include one or more devices (e.g., RAM, ROM, flash memory, hard disk storage) for storing data and / or computer code to perform or facilitate the various processes, layers, and modules described herein. For example, memory device 206 may include dynamic random access memory (DRAM). Memory device 206 may be communicatively connected to processor 204 to provide processor 204 with computer code or instructions to perform at least some of the processes described herein. Furthermore, memory device 206 may be or include tangible, non-transient volatile memory or non-volatile memory. Therefore, memory device 206 may include database components, object code components, scripting components, or any other type of information structure for supporting the various activities and information structures described herein.

[0037] Communication interface 216 may include any combination of wired and / or wireless interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wired terminals) for data communication with various systems, devices, or networks configured to enable in-vehicle communication (e.g., between and within vehicle components) and out-of-vehicle communication (e.g., communication with a remote server). For example, and regarding out-of-vehicle / system communication, communication interface 216 may include Ethernet cards and ports for sending and receiving data via Ethernet-based communication networks and / or Wi-Fi transceivers for communication via wireless communication networks. Communication interface 216 may be configured to communicate via a local area network or a wide area network (e.g., the Internet) and may use various communication protocols (e.g., IP, LON, Bluetooth, ZigBee, radio, cellular, near-field communication).

[0038] Sensor management circuitry 210 is configured or constructed to control the operation of sensor 125. For example, sensor management circuitry 210 may be configured to generate one or more control signals and send these control signals to one or more sensors 125 (e.g., to acquire data, etc.). The control signals may cause one or more sensors 125 to sense and / or detect sensor data and / or provide the sensor data to sensor management circuitry 210. In some embodiments, sensor management circuitry 210 may be configured to estimate sensor data (e.g., when sensor 125 is a dummy sensor). "Sensor data" may include temperature data (e.g., exhaust temperature, component temperature such as engine temperature, etc.), flow data (e.g., exhaust flow rate data, boost air flow rate, etc.), pressure data (e.g., engine cylinder pressure, coolant pressure, etc.), and / or other data related to the operation of system 100.

[0039] The post-processing control circuit 212 is configured to control the operation of one or more components (e.g., systems, devices, etc.) of the post-processing system 120. For example, the post-processing control circuit 212 may be configured to control the operation of the metering module 124. More specifically, the post-processing control circuit 212 may be configured to control the operation of the pump of the metering module 124, such that the post-processing control circuit 212 can control the injection amount (e.g., the amount of reducing agent supplied to the post-processing system 120), the injection frequency, the injection concentration, and / or other parameters associated with the operation of the metering unit.

[0040] Engine control circuit 214 is configured to at least partially control the operation of engine 101. For example, engine control circuit 214 may be configured to control engine 101 to a desired output value. More specifically, engine control circuit 214 may be configured to control engine 101 to output an approximate specific exhaust temperature value, an approximate exhaust flow rate value (e.g., mass flow rate, volumetric flow rate, etc.), an engine speed value (e.g., RPM), an engine torque value, and / or other engine output values. In some embodiments, the desired output value may be one of a plurality of predetermined engine output values. The predetermined engine output value may be stored by memory device 206.

[0041] In some embodiments, the controller 140 or components therein (e.g., engine control circuitry 214) may set predetermined engine output values ​​based on a desired range for diagnosing component failures in the exhaust aftertreatment system 120. For example, the controller 140 may control one or more input parameters of the engine 101 corresponding to predetermined parameters of the desired engine output. More specifically, the controller 140 may control engine parameters (e.g., air-fuel ratio) including one or more of engine speed, fuel injection quantity, fuel injection timing, etc., corresponding to at least one of the desired engine NOx output, desired engine exhaust temperature, etc. For example, the controller 140 may control or limit the engine speed to a first value corresponding to the desired engine exhaust temperature. In this way, increasing engine speed (and engine torque) can increase exhaust temperature, such that maintaining or keeping the engine speed at or below a first predetermined level can help maintain the exhaust temperature at or below the first predetermined level.

[0042] In some embodiments, engine control circuitry 214 may adjust the energy control strategy of engine 101 to change one or more engine output values. "Energy control strategy" refers to controlling engine 101 and electric motor 102 to output desired power, torque, etc., and may include regulating the use of the internal combustion engine and / or electric motor 102. More specifically, "energy control strategy" refers to controlling electric motor 102 and engine 101 to meet various operational requirements and / or to implement one or more diagnostic or predictive processes, such as those described herein. In one exemplary embodiment, engine control circuitry 214 performs these operations during normal operation of system 100.

[0043] In some embodiments, engine control circuitry 214 may increase the use of the internal combustion engine to increase exhaust temperature, exhaust flow rate, engine speed, and / or one or more other engine output values. In these embodiments, increasing the use of the internal combustion engine may include causing an electrical system (such as a battery system for powering electric motor 102) to receive electric charge from the internal combustion engine. Furthermore, in these embodiments, engine control circuitry 214 may reduce the use of electric motor 102 to additionally and / or alternatively increase the use of the internal combustion engine, for example, by increasing exhaust temperature. In some embodiments, electric motor 102 may be disabled to additionally and / or alternatively increase the use of the internal combustion engine.

[0044] In some embodiments, engine control circuitry 214 may reduce the use of the internal combustion engine to reduce exhaust temperature, exhaust flow rate, and / or other engine output values ​​(e.g., reduce fuel consumption, etc.). In these embodiments, reducing the use of the internal combustion engine may include at least partially using electric motor 102 to propel the vehicle.

[0045] In some embodiments, engine control circuit 214 can decouple the internal combustion engine from the vehicle's drivetrain, allowing system 100 to rely on electric motor 102 to propel the vehicle. In these embodiments, engine control circuit 214 can increase or decrease the use of engine 101 without propelling the vehicle.

[0046] Such as about Figure 3A and 4 In further detail, the controller can determine when to increase or decrease the use of engine 101 relative to electric motor 102 based on a predetermined control sequence for diagnosing the exhaust aftertreatment system 120. The amount of power provided by engine 101 relative to electric motor 102 may depend on at least one of the predetermined control sequence, the amount of power or torque requested by system 100 for propelling the vehicle, or a combination thereof.

[0047] In an alternative embodiment, when system 100 is in a service facility, controller 140 may adjust energy control strategies.

[0048] As described in detail herein, predetermined engine output values ​​can be used to assist in diagnosing component failures in the exhaust aftertreatment system 120. For example, predetermined engine output values ​​may correspond to aftertreatment system parameter values. Aftertreatment system parameter values ​​refer to parameters or information regarding the operation of the aftertreatment system 120 and may include, for example, NOx reduction (deNOx) values ​​(e.g., NOx reduction efficiency is determined by the amount of NOx received per SCR 123, the amount of NOx reduced by SCR 123, sometimes expressed as a percentage, also referred to as conversion efficiency (CE) or inefficiency value), reductant values ​​(e.g., the amount and / or concentration of reductant supplied by the metering module 124), ammonia-to-NOx ratio values ​​(e.g., the ratio of ammonia to NOx, "ANR"), engine output values ​​consistent with input values ​​or approximate input values ​​of the aftertreatment system 120 (e.g., engine output NOx value, "EONOx"), the temperature of one or more components of the aftertreatment system 120, and / or other parameter values ​​regarding the operation of the aftertreatment system 120. In some embodiments, one or more thresholds may be associated with one or more of the aforementioned parameter values. For example, a desired NOx reduction threshold (e.g., CE threshold), an ANR threshold, an EONOx threshold, etc. In some embodiments, a threshold may be a single threshold (e.g., a maximum, minimum, or target value) and / or a range of thresholds (e.g., a maximum and a minimum value).

[0049] As described herein, controller 140 is configured to diagnose component failures in exhaust aftertreatment system 120. For example, controller 140 may analyze sensor data (e.g., data received from sensor 125 and / or determined via sensor management circuitry 210) to determine one or more parameters of exhaust aftertreatment system 120 and / or its components (e.g., DPF 122, metering module 124, etc.). In some embodiments, sensor data includes one or more parameters relating to the operation of exhaust aftertreatment system 120. In some embodiments, controller 140 may determine parameter values ​​including exhaust component values, such as NOx values ​​(e.g., NOx concentration, CE value, EONOx value, etc.), by measuring and / or estimating these values ​​using sensor 125 or by providing information to enable controller 140 to determine these values. In other embodiments, controller 140 may determine parameter values, including one or more fluid parameters of fluid (e.g., exhaust) flowing through exhaust aftertreatment system 120 and / or its components, including but not limited to flow rate (e.g., volumetric flow rate, mass flow rate, etc.), pressure changes across one or more components, and / or flow resistance (e.g., the ratio of pressure change to volumetric flow rate), by using sensor 125 to measure and / or estimate these values ​​or information used to determine these values.

[0050] Controller 140 may compare one or more parameter values ​​with corresponding thresholds to diagnose components of post-processing system 120. Controller 140 may determine that a component of post-processing system 120 has failed and / or may fail based on determining that a parameter value exceeds a corresponding maximum threshold, is below a minimum threshold, or is outside the threshold range. In one example embodiment, controller 140 may compare a deNOx efficiency value with a deNOx efficiency threshold (e.g., minimum deNOx efficiency). The terms deNOx efficiency and conversion efficiency (CE) are used interchangeably herein. Controller 140 may determine that at least one component of post-processing system 120 has failed or may have failed based on a deNOx efficiency value below a minimum deNOx efficiency value, which indicates that less than a minimum expected amount of NOx has been converted to a less harmful element. Controller 140 may determine at least one of (1) a failed component and (2) a failure type. References herein Figure 3A and Figure 4 The logic used to diagnose component failures is described in more detail.

[0051] Now for reference Figures 3A-3B and Figure 4 This illustrates methods 300 and 400 for monitoring and diagnosing components of a post-processing system 120 according to an exemplary embodiment. In some embodiments, methods 300 and 400 represent different control processes for determining which components(s) have failed and the type of failure. In other embodiments, methods 300 and 400 may be performed simultaneously, partially simultaneously, or sequentially. For example, in Figure 3A and Figure 4 In the illustrated embodiment, method 400 is executed sequentially after method 300.

[0052] Based on the foregoing and firstly referring to Figure 3A A flowchart illustrating a method 300 for monitoring and diagnosing one or more components of an aftertreatment system 120 according to an exemplary embodiment is shown. In some embodiments, a controller 140 and / or one or more components thereof (such as sensor management circuitry 210, aftertreatment control circuitry 212, and / or engine control circuitry 214) are configured to perform method 300. For example, the controller 140 and / or one or more components thereof may be configured to perform method 300 individually or in combination with other means such as sensors 125 and / or other components of system 100. Method 300 may include inputs to / from one or more user devices (such as operator I / O devices 130). Figure 3A In the illustrated embodiment, method 300 is executed by controller 140.

[0053] As an overview of method 300, at process 302, controller 140 receives initial sensor data. At process 304, controller 140 compares the initial sensor data with a first threshold. If the initial sensor data is higher than a maximum threshold, lower than a minimum threshold, or outside a predetermined threshold range, method 300 proceeds to process 306. If the initial sensor data is not higher than a maximum threshold, lower than a minimum threshold, or outside a threshold range, method 300 returns to process 302. At process 306, controller 140 controls engine 101 to a first engine output. At process 308, controller 140 receives the first sensor data. At process 310, controller 140 controls engine 101 to a second engine output. At process 312, controller 140 receives second sensor data. At process 314, controller 140 controls the engine to a third engine output. At process 316, controller 140 controls the engine to a first engine output. At process 318, controller 140 receives third sensor data. At process 320, controller 140 controls the engine to the second engine output. At process 322, controller 140 receives data from the fourth sensor. At process 324, controller 140 determines a diagnosis. In some embodiments, method 300 may continue to... Figure 4 The process 402 of method 400. In some embodiments, the process of method 300 can be consistent with... Figure 3A The different execution sequences shown. In some embodiments, method 300 may include a sequence that is different from the one shown. Figure 3A The process may be more or less as shown. In some embodiments, the processes of method 300 may be performed simultaneously, partially simultaneously, or sequentially.

[0054] Referring more specifically to method 300, at process 302, controller 140 receives initial sensor data. Controller 140 may determine one or more parameter values ​​of post-processing system 120 based on the initial sensor data. For example, the initial sensor data may include information indicating at least one of deNOx value, reducing agent value, ANR value, ENOx value, and / or other parameter values ​​relating to the operation of post-processing system 120. In one example embodiment, the initial sensor data includes information indicating a deNOx value. As described above, the initial sensor data may include data from sensor 125, and the initial sensor data may be data sensed by a real sensor, determined by a virtual sensor, or a combination thereof.

[0055] At process 304, controller 140 compares the initial sensor data with a first threshold. More specifically, controller 140 may compare an initial parameter value with the first threshold. The first threshold may correspond to a type of parameter value determined based on the initial sensor data. For example, if the initial sensor data includes information indicating a deNOx value, the first threshold may be a first deNOx threshold. As described above, the first threshold may include a maximum threshold, a minimum threshold, and / or a threshold range. In one example embodiment, the initial sensor data includes information indicating a deNOx value, and the first threshold is a minimum deNOx value (e.g., a minimum deNOx efficiency value of 90%, 85%, 80%, etc.). The deNOx value may be determined at a specific location in the aftertreatment system 120. For example, the deNOx value may be determined at the outlet of the aftertreatment system 120, at the outlet of the SCR 123, and / or at another location (e.g., tailpipe emission). The deNOx value can be determined by the NOx value at the inlet of the aftertreatment system 120 (NOx in ) and the NOx value at the outlet of the post-treatment system 120 (NOx out Difference between NOx and NOx in The value determines NOx. in Values ​​and NOx out The value can be a value included in the initial sensor data (e.g., sensor data detected and / or determined by sensor 125). If the initial parameter value does not meet a first threshold (e.g., above the maximum threshold, below the minimum threshold, or outside the threshold range), method 300 proceeds to process 306. For example, if the deNOx value is less than the minimum deNOx value, method 300 proceeds to process 306. If the initial sensor data meets the first threshold (e.g., below the maximum threshold, above the minimum threshold, or within the threshold range), method 300 returns to process 302. For example, if the deNOx value is greater than the minimum deNOx value, method 300 returns to process 302.

[0056] At process 306, controller 140 controls engine 101 to the first engine output. For example, engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs the first engine output value, as mentioned above. Figure 2The engine output value may include at least one of the following: exhaust temperature value, exhaust flow rate value (e.g., mass flow rate, volumetric flow rate, etc.), engine speed value (e.g., RPM), or other engine output values. In one exemplary embodiment, the engine control circuit 214 may adjust the engine operation to obtain or attempt to obtain a first exhaust temperature value at the engine output (which may be determined by an engine output temperature sensor). The first exhaust temperature value may be a low temperature value (e.g., less than 300°C, less than 280°C, etc.), a low temperature range (e.g., between 250°C and 360°C, between 270°C and 290°C, etc.), or a target temperature value with an error range (e.g., 280°C ± 25°C).

[0057] At process 308, controller 140 receives first sensor data. The first sensor data may include sensor data from sensor 125. The sensor data may include information indicating a first deNOx value corresponding to a first engine output value, such that controller 140 can determine the first deNOx value based on the first sensor data. In some embodiments, the first sensor data is received, collected, and / or otherwise determined in response to engine 101 operating at the first engine output value.

[0058] At process 310, controller 140 controls engine 101 to output a second engine output. For example, engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs a second engine output value, as described above. Figure 2 The engine output values ​​may include at least one of the following: exhaust temperature value, exhaust flow rate value (e.g., mass flow rate, volumetric flow rate, etc.), engine speed value (e.g., RPM), or other engine output values. In one exemplary embodiment, the engine control circuit 214 may adjust the engine operation to a second temperature value. The second temperature value may be a moderate temperature value (e.g., less than 400°C, less than 350°C, etc.), a moderate temperature range (e.g., between 300°C and 400°C, between 340°C and 360°C, etc.), or a target temperature value with an error range (e.g., 350°C ± 25°C).

[0059] At process 312, controller 140 receives second sensor data. The second sensor data may include sensor data from sensor 125. The sensor data may include information indicating a second deNOx value corresponding to a second engine output value, such that controller 140 can determine the second deNOx value based on the second sensor data. In some embodiments, the second sensor data is received, collected, and / or otherwise determined in response to engine 101 operating at a second engine output value.

[0060] At process 314, controller 140 controls the engine to output a third engine output. For example, engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs a third engine output value, as mentioned above. Figure 2 The engine output values ​​may include at least one of the following: exhaust temperature value, exhaust flow rate value (e.g., mass flow rate, volumetric flow rate, etc.), engine speed value (e.g., RPM), or other engine output values. In one exemplary embodiment, the engine control circuit 214 may adjust the engine operation to a third exhaust temperature value. The third exhaust temperature value may be a high temperature value (e.g., greater than 400°C, greater than 450°C, etc.), a high temperature range (e.g., between 400°C and 500°C, between 425°C and 475°C, etc.), or a target temperature value with an error range (e.g., 450°C ± 25°C).

[0061] At process 316, controller 140 controls the engine to the first engine output. As described above regarding process 306, the engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs the first engine output value.

[0062] At process 318, controller 140 receives third sensor data. The third sensor data may include sensor data from sensor 125. The third sensor data may include information indicating a third deNOx value corresponding to the first engine output value after the engine has previously operated at a third engine output value, such that controller 140 can determine the third deNOx value based on the third sensor data. In some embodiments, the third sensor data is received in response to engine 101 operating at a first engine output value after the engine has recently operated at a third engine output value (e.g., within 1 minute, 30 minutes, 1 hour, etc.).

[0063] At process 320, controller 140 controls the engine to output a second engine output. As described above, regarding process 310, the engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs a second engine output value.

[0064] At process 322, controller 140 receives fourth sensor data. The fourth sensor data may include sensor data from sensor 125. The fourth sensor data may include information indicating a fourth deNOx value corresponding to the second engine output value after the engine has previously been at a third engine output, such that controller 140 can determine the fourth deNOx value based on the fourth sensor data. In some embodiments, the fourth sensor data is received in response to engine 101 operating at the second engine output value (e.g., within 1 minute, 30 minutes, 1 hour, after a steady-state condition at the second engine output value, where the value fluctuates within a predetermined acceptable amount, etc.).

[0065] At process 324, controller 140 identifies or otherwise determines a diagnosis. In one embodiment, controller 140 may determine the diagnosis based on first sensor data, second sensor data, third sensor data, and fourth sensor data. In another embodiment, controller 140 may determine the diagnosis based on one or more (a predetermined combination) of the first sensor data, second sensor data, third sensor data, and fourth sensor data. In some embodiments, controller 140 compares each of the first sensor data, second sensor data, third sensor data, and fourth sensor data with a corresponding corresponding threshold. As described above, the corresponding threshold may be a maximum threshold, a minimum threshold, or a threshold range. Controller 140 may determine whether each of the first sensor data, second sensor data, third sensor data, and fourth sensor data is above a predetermined maximum threshold, below a predetermined minimum threshold, or outside a predetermined acceptable threshold range. In some embodiments, the diagnosis may be a preliminary diagnosis indicating the need for further data to determine the type of fault or potential fault. In other embodiments, the diagnosis may be a final diagnosis based on data received by controller 140 indicating the most probable fault type and requiring no additional data. (See also: [link to document]) Figure 3B Examples of identifying diagnostic and fault types are described.

[0066] In one embodiment, controller 140 may use one or more of statistical models, machine learning models, lookup tables, etc., to determine a diagnosis. In an example embodiment, controller 140 uses a lookup table to determine a diagnosis. For example, and referring to... Figure 3B The lookup table includes inputs of first sensor data, second sensor data, third sensor data, and fourth sensor data, as well as outputs of faulty components and / or fault types. Specifically, the lookup table includes inputs determining whether each of the sensor data satisfies a corresponding threshold (e.g., a parameter higher than a maximum threshold, lower than a minimum threshold, or outside a predetermined threshold range).

[0067] Now for reference Figure 3BAccording to one example embodiment, a lookup table 350 is shown that includes one or more inputs providing indications as to whether first sensor data, second sensor data, third sensor data, and fourth sensor data each satisfy a corresponding threshold. Figure 3B As shown and as this article relates Figure 3A The first sensor data and the second sensor data are measured (or determined) before the engine operates at a third engine output value. More specifically, the first sensor data and the second sensor data are measured (or determined) before predetermined high-temperature operating conditions. For example, the first data is measured (or determined) at a low engine output temperature (e.g., at or about 280°C) and the second data is measured (or determined) at a medium engine output temperature (e.g., at or about 350°C). Controller 140 may determine a first CE (CE1) based on the first sensor data and a second CE (CE2) based on the second sensor data. In this example, low engine output temperature and medium engine output temperature refer to the engine output exhaust temperature, which may be determined by an engine output temperature sensor (located in or near the exhaust manifold). After measuring (or determining) the first data and the second data, controller 140 causes engine 101 to operate under high-temperature operating conditions (e.g., a high-temperature event or a third engine output). High-temperature operating conditions may be high exhaust temperatures, high aftertreatment system component temperatures, etc. In some embodiments, high temperature is defined as a temperature greater than 450°C (which may be the exhaust temperature entering aftertreatment system 120). In some embodiments, a high-temperature event causes deposits on the DPF 122 to burn off and / or sulfur to burn off in the SCR system 123. In this regard, “high temperature” can be a high-temperature threshold (e.g., exhaust temperature, exhaust aftertreatment system component temperature, or a combination thereof) or a high-temperature event, such as a regeneration event (which may depend on the regeneration intent (e.g., deep cleaning to burn off sulfur and other particulate matter, etc.)).

[0068] The third and fourth sensor data are measured (or determined) after the engine operates at a third output. More specifically, the third and fourth sensor data are measured (or determined) after a high-temperature event. In some embodiments, the third and fourth sensor data are measured (or determined) after a steady-state condition is reached (e.g., after a predetermined time period following a predetermined high-temperature event or after a high-temperature event when sensor data indicates that a steady-state condition has been reached). For example, the third data is measured (or determined) at a low engine output temperature (e.g., at or about 280°C) after a high-temperature event, and the fourth data is measured (or determined) at a medium engine output temperature (e.g., at or about 350°C) after a high-temperature event. Controller 140 may determine a third CE (CE3) based on the third sensor data and a fourth CE (CE4) based on the fourth sensor data. As described in more detail herein, lookup table 350 compares the first sensor data with a first threshold, the second sensor data with a second threshold, the third sensor data with a third threshold, and the fourth sensor data with a fourth threshold. Each of the first, second, third, and fourth sensor data includes a parameter value. In some embodiments, each of the first sensor data, second sensor data, third sensor data, and fourth sensor data includes or is a CE value. In these embodiments, the first threshold, second threshold, third threshold, and fourth threshold may be predetermined CE thresholds (e.g., a minimum CE value). In other embodiments, the sensor data and thresholds may correspond to different parameters (e.g., NOx value, EONOx value, temperature value, etc.).

[0069] like Figure 3BAs shown, in a first scenario, when the first sensor data does not meet the first threshold, the second sensor data meets the second threshold, the third sensor data meets the third threshold, and the fourth sensor data meets the fourth threshold, the controller 140 determines that the aftertreatment system 120 has failed with a first fault type. For example, if CE1 is less than 85%, CE2 is greater than 85%, CE3 is greater than 85%, and CE4 is greater than 85%, then the controller 140 determines that the aftertreatment system 120 has failed with a first fault type. In an exemplary embodiment, the first fault type is a high-sulfur poisoning fault type. The high-sulfur poisoning fault type may be caused by poor or low-quality fuel, based on the fuel having a high sulfur concentration (the sulfur concentration is higher than a predetermined threshold, which indicates poor or low-quality fuel). The high sulfur concentration in the fuel, in turn, results in a higher concentration of sulfur oxides (SOx) in the engine exhaust. The increased SOx can "poison" one or more components of the aftertreatment system 120, such as DOC 121 and / or SCR 123. As used herein, “sulfur poisoning” of an aftertreatment system component can include an increase in the amount (e.g., quantity, concentration, etc.) of sulfur oxides at, on, or inside the component. An increased sulfur oxide value can lead to the formation of ammonium sulfate at low temperatures (e.g., temperatures below a predetermined threshold, such as 300°C). An increased sulfur oxide value can also cause one or more components to adsorb at least a portion of SOx, for example, at the active sites of the SCR along with the formation of copper sulfate. This adsorption, in turn, can reduce the effectiveness of one or more components (e.g., impair the SCR’s ability to convert NOx into less harmful elements). In some embodiments, high sulfur poisoning fault types can be mitigated or remedied by increasing the exhaust temperature within the exhaust aftertreatment system 120 to above a threshold temperature (e.g., greater than 550°C). These relatively high exhaust temperatures over a specific period can act to restore the SCR activity of the sulfation catalyst.

[0070] In the second scenario, when the first sensor data does not meet the first threshold, the second sensor data meets the second threshold, the third sensor data does not meet the third threshold, and the fourth sensor data meets the fourth threshold, the controller 140 determines that the post-processing system 120 has failed with a second fault type. For example, if CE1 is less than 85%, CE2 is greater than 85%, CE3 is less than 85%, and CE4 is greater than 85%, then the controller 140 determines that the post-processing system 120 has experienced a second fault type. In an exemplary embodiment, the second fault type is an over-aged component failure type. For example, one or more components of the post-processing system 120 have been over-aged (e.g., degraded) to the point that the component is no longer effective. For example, one or more components may be hydrothermally aged. Hydrothermal aging may be caused by prolonged exposure to high temperatures (e.g., greater than 550°C) and / or repeated exposure to high temperatures. Hydrothermally aged components may not be recoverable.

[0071] In the third scenario, when the first sensor data does not meet the first threshold, the second sensor data does not meet the second threshold, the third sensor data meets the third threshold, and the fourth sensor data meets the fourth threshold, the controller 140 determines that the after-treatment system 120 has failed under the third fault type. For example, if CE1 is less than 85%, CE2 is less than 85%, CE3 is greater than 85%, and CE4 is greater than 85%, the controller 140 determines that the after-treatment system 120 has failed under the third fault type. In one example embodiment, the third fault type is a deposit fault type. For example, contaminants such as soot may accumulate and “deposit” on one or more components of the after-treatment system 120. More specifically, soot deposits may accumulate on the DPF 122, causing a degrade in the performance of the DPF 122 (e.g., the differential pressure on the DPF 122 exceeds a predetermined threshold, indicating a flow restriction through the DPF 122). The increased exhaust temperature resolves the deposit fault type by burning off the deposits and allowing the DPF 122 to operate normally.

[0072] In the fourth scenario, when the data from the first sensor fails to meet the first threshold, the data from the second sensor fails to meet the second threshold, the data from the third sensor fails to meet the third threshold, and the data from the fourth sensor fails to meet the fourth threshold, the controller 140 determines that the post-processing system 120 has failed with a fourth fault type. For example, if CE1 is less than 85%, CE2 is less than 85%, CE3 is less than 85%, and CE4 is less than 85%, then the controller 140 determines that the post-processing system 120 has failed with a fourth fault type. In one exemplary embodiment, the fourth fault type is a metering failure type. In some embodiments, the controller 140 requires more data to determine a specific type of metering failure. The controller 140 is configured to use references herein. Figure 4 The described method 400 is used to determine the specific type of quantitative feeding failure.

[0073] Now for reference Figure 4 This illustrates monitoring according to an exemplary embodiment. Figure 1 A flowchart of method 400 for a vehicle's after-treatment system. In some embodiments, controller 140 and / or one or more components thereof (such as after-treatment control circuitry 212 and / or engine control circuitry 214) are configured to perform method 400. For example, controller 140 and / or one or more components thereof may be configured to perform method 400 individually or in combination with other means such as sensors 125 and / or other components of system 100. Method 400 may include inputs and / or outputs to / from one or more user devices (such as operator I / O devices 130). Figure 4 In the illustrated embodiment, method 400 is executed by controller 140.

[0074] As an overview of method 400, at process 402, controller 140 controls the engine to a fourth engine output. At process 404, controller 140 receives fifth sensor data. At process 406, controller 140 compares the fifth sensor data with a fifth threshold. If the fifth sensor data is at or below the fifth threshold (depending on the parameter threshold, the fifth sensor data may fail to meet the fifth threshold by, for example, being above a maximum threshold or below a minimum threshold), method 400 continues to process 414. If the fifth sensor data meets the fifth threshold (e.g., below the maximum threshold, above the minimum threshold, within the threshold range), method 400 continues to process 408. At process 408, controller 140 requests an override sequence. At process 410, controller 140 estimates the feed concentration based on the sensor data from the override sequence. At process 412, controller 140 compares the feed concentration with a sixth threshold. At process 414, controller 140 determines a diagnosis. In some embodiments, the process of method 400 can be compared with... Figure 4 The different sequences of execution are shown. In some embodiments, method 400 may include a sequence of executions. Figure 4 The process may be more or less as shown. In some embodiments, the processes of method 400 may be performed simultaneously, partially simultaneously, or sequentially.

[0075] Referring more specifically to method 400, at process 402, controller 140 controls engine 101 to a fourth engine output. For example, engine control circuit 214 of controller 140 can adjust the operation of engine 101 so that engine 101 outputs a fourth engine output value, as described above. Figure 2 The engine output value may include at least one of the following: exhaust temperature value, exhaust flow rate value (e.g., mass flow rate, volumetric flow rate, etc.), engine speed value (e.g., RPM), or other engine output values. In one exemplary embodiment, the fourth engine output is a predetermined engine output corresponding to a predetermined EONOX value or a range of EONOX values.

[0076] At process 404, controller 140 receives fifth sensor data. The fifth sensor data may include sensor data from sensor 125. The sensor data may include a first EONOx value, corresponding to sensor data acquired when engine 101 operates at a fourth engine output value. In some embodiments, the fifth sensor data including the first EONOx value is measured downstream of engine 101. In some embodiments, the fifth sensor data including the first EONOx value is measured or determined upstream of aftertreatment system 120 and / or upstream of a first component of aftertreatment system 120.

[0077] At process 406, controller 140 compares the fifth sensor data with a fifth threshold. If the fifth sensor data does not meet the fifth threshold (e.g., above the maximum threshold, below the minimum threshold, or outside the threshold range), method 400 proceeds to process 414. If the fifth sensor data meets the fifth threshold (e.g., below the maximum threshold, above the minimum threshold, or within the threshold range), method 400 proceeds to process 408. In some embodiments, the fifth threshold is a threshold range. More specifically, the fifth threshold is a range of EONOx values ​​corresponding to the fourth engine output value. If the fifth sensor data is outside the threshold range, method 400 proceeds to process 414. If the fifth sensor data is within the threshold range, method 400 proceeds to process 408.

[0078] At process 408, controller 140 requests and initiates an overrun procedure for system operation. The overrun procedure may include causing the metering module 124 to overrun a standard metering value and providing at least one, and particularly multiple, metering values ​​according to an overrun sequence. For example, controller 140 may cause the metering module 124 to output multiple ANR values. In one exemplary embodiment, the overrun sequence includes a first metering value of approximately 0.8 Å ANR, a second metering value of approximately 1.0 Å ANR, and a third metering value of approximately 1.2 Å ANR. In other embodiments, the overrun sequence may include more, different, or fewer metering values ​​corresponding to ANR values ​​between 0 and predetermined values, such as between 0.5 and 1.5.

[0079] For each metered feed value in the overclocking sequence, controller 140 may receive overclocking sequence sensor data (e.g., from sensor 125). The overclocking sequence sensor data may include information indicating a deNOx value (e.g., deNOx efficiency) for each metered feed value. More specifically, controller 140 may receive sensor data indicating a first deNOx value corresponding to a first metered feed value (e.g., approximately 0.7 ANR–0.8 ANR), a second deNOx value corresponding to a second metered feed value (e.g., approximately 1.0 ANR), and a third deNOx value corresponding to a third metered feed value (e.g., approximately 1.2 ANR).

[0080] In some implementations, the deNOx CE value determined at each feed rate can be compared with one or more expected deNOx values ​​to determine whether the post-treatment system 120 is operating under normal, negative, or positive conditions. The controller 140 can determine the condition of the post-treatment system 120 based on the difference between the deNOx value at at least one predetermined feed rate and the expected deNOx CE value.

[0081] In one exemplary embodiment, one or more expected deNOx values ​​for a first feed rate may include a first normal condition value (e.g., 0.68 deNOx CE), a first negative condition value (0.58 deNOx CE), and a first positive condition value (e.g., 0.78 deNOx CE). One or more expected deNOx values ​​for a second feed rate may include a second normal condition value (e.g., 0.97 deNOx CE), a second negative condition value (0.87 deNOx CE), and a second positive condition value (e.g., 0.97 deNOx CE). One or more deNOx values ​​for a third feed rate may include a third normal condition value (e.g., 0.95 deNOx CE), a second negative condition value (0.96 deNOx CE), and a first positive condition value (e.g., 0.90 deNOx CE). In this example, three predetermined feed rates with three associated expected deNOx CE values ​​are used by controller 140 to determine the normal, negative, or positive conditions of the system. If the determined deNOx value is within a predetermined amount (e.g., 10%, 15%, etc.) of the expected deNOx value at each quantitative feed value, the controller 140 can determine the status of the system.

[0082] At process 410, controller 140 estimates or otherwise determines the metering concentration based on sensor data from the overdrive sequence. The metering concentration may be determined based on a combination of engine NOx emission values, metering command values, and system NOx emission values. Specifically, the metering or urea concentration may be determined based on data acquired during the overdrive sequence. Specifically, the metering concentration may be determined based on one or more sensor values ​​and / or one or more metering commands. For example, controller 140 may determine a first value (“M1”) indicating an EONOx mass flow rate. M1 may be determined based on data from one or more sensors 125 (e.g., NOx sensors located at the outlet of engine 101). Controller 140 may determine a second value (“M2”) indicating a system NOx (SONOx) mass flow rate. M2 may be determined based on data from one or more sensors 125 (e.g., NOx sensors at the outlet of aftertreatment system 120, i.e., the system NOx emission value). The third value (“M3”) can be a metering command value (e.g., metering expressed in mass) commanded by controller 140. Controller 140 can determine a fourth value (“M4”) indicating the mass of NOx reacting. M4 can be determined as the difference between M1 and M2. Controller 140 can determine a fifth value (“M5”) indicating the amount (e.g., mass) of the metering fluid reacting with the reaction based on the amount of NOx reacting. For example, based on M1 and M2, controller 140 can determine the amount of NOx reacting with the metering fluid. More specifically, controller 140 can determine the mass of NOx reacting with the metering fluid based on the difference between M1 and M2. Controller 140 can determine the molar amount of NOx reacting with the metering fluid. Controller 140 can determine the molar amount of the metering fluid based on the molar amount of NOx. In some embodiments, the metering fluid is ammonia (NH3). In these embodiments, the molar ratio between NOx and NH3 is 1:1 or approximately 1:1, as shown in Equations 1-4 below.

[0083]

[0084]

[0085]

[0086]

[0087] The controller 140 can determine the mass of the metered feed fluid for the reaction based on the molar amount of the metered feed fluid. Subsequently, the controller 140 can determine the metered feed concentration based on the ratio of the amount of the metered feed fluid for the reaction to the amount of the commanded metered feed fluid (e.g., M5 divided by M3). These formulas can be stored in a lookup table or other searchable algorithm within the controller 140 for selective execution.

[0088] At process 412, controller 140 compares the metered feed concentration with a sixth threshold. The sixth threshold can be a threshold range for the metered feed concentration. Controller 140 can determine a diagnosis based on the metered feed concentration that meets or does not meet the sixth threshold. Specifically, at process 414, controller 140 determines a diagnosis. As described above, controller 140 can determine the type of metered feed variation (e.g., as referenced herein). Figure 3B (The fourth type of fault described).

[0089] In a first exemplary embodiment, based on the determination at process 406 that the EONOX value does not meet a fifth threshold, controller 140 can determine that the post-processing system 120 has failed with a first quantitative feed change fault type. The first quantitative feed change fault type is a sensor drift fault type. For example, because engine 101 is operating at a predetermined engine output value, if sensor 125 detects an EONOX value different from the expected EONOX value, controller 140 can determine that sensor 125 has failed due to sensor drift. "Sensor drift" refers to a decrease in the accuracy of a sensor (such as sensor 125) over time. Sensor drift can be caused by damage to the sensor (e.g., corrosion, electrical damage, particle ingress, water damage, etc.), normal wear and tear over time, or other factors.

[0090] In a second exemplary embodiment, based on the determination that the feed concentration does not meet a sixth threshold (e.g., outside the threshold range), the controller 140 may determine that the post-processing system 120 has failed under a second feed change fault type. The second feed change fault type is a feed concentration fault type. For example, if the expected amount of feed fluid is used to achieve the ANR value of the overrun sequence, but the estimated feed concentration does not meet the sixth threshold, the controller 140 may determine that the feed fluid is too concentrated or too dilute.

[0091] In a third exemplary embodiment, based on determining that the metering concentration meets a sixth threshold (e.g., within the threshold range), the controller 140 can determine that the post-processing system 120 has failed with a second metering change fault type. The second metering change fault type is a metering leak or metering drift fault type. For example, if the estimated metering concentration meets the sixth threshold, and the desired amount of metering fluid is used to achieve the ANR value of the overrun sequence, the controller 140 can determine at least one of the following: (i) the metering module 124 has failed due to metering drift, or (ii) the metering module 124 is leaking metering fluid. Metering drift refers to a situation where the commanded metering value (e.g., metering amount, metering volume, etc.) differs from the transmitted metering value, wherein the difference increases over time. Metering drift may be caused by damage to sensors, pumps, or other components of the metering module 124.

[0092] In any of the above embodiments, controller 140 may be configured to generate an alarm indicating that one or more components of the after-processing system 120 have failed. The indication may further include the failed component and / or the type of failure. This indication may be provided to a user via operator I / O device 130. In some embodiments, the indication may be provided to a remote computing system (e.g., a fleet operator computing system, etc.).

[0093] In some embodiments, the indication may also include suggested or recommended actions to remedy a faulty component or mitigate future faults. In one example, to mitigate a high-sulfur poisoning fault type, the indication may include a suggestion to operate engine 101 at high temperatures to burn off accumulated sulfur. In another example, to mitigate an over-aged component fault, the indication may include a suggestion to repair or replace one or more components of the aftertreatment system 120. In another example, to mitigate a deposit fault, the indication may include a suggestion to operate engine 101 at high temperatures to burn off accumulated deposits. In another example, to mitigate a sensor drift fault, the indication may include a suggestion to calibrate or replace one or more of sensors 125. In another example, to mitigate a metering concentration fault, the indication may include a suggestion to replace the metering fluid. In another example, to mitigate metering leakage or metering drift, the indication may include a suggestion to repair or replace the metering module 124.

[0094] In some embodiments, controller 140 may be configured to automatically provide indications to a remote computing system. For example, controller 140 may provide a fault code or other notification indicating the type of fault to the remote computing system. In some embodiments, controller 140 may also provide recommended action procedures to remedy the faulty component or mitigate future faults.

[0095] In some embodiments, controller 140 may be configured to control engine 101 based on diagnostics. For example, controller 140 may automatically increase engine exhaust temperature (e.g., by increasing engine speed) to burn off deposits accumulated on DPF 122. In another example, controller 140 may make system 100 rely more heavily on electric motor 102 to mitigate emissions by utilizing a relatively small amount of internal combustion engine power based on identified faulty components.

[0096] As used herein, the terms “about,” “approximately,” “substantially,” and similar terms are intended to have a broad meaning and are consistent with common and accepted usage by one of ordinary skill in the art to which the subject matter of this disclosure pertains. Those skilled in the art who read this disclosure will understand that these terms are intended to allow for the description and claim of certain features without limiting the scope of those features to the precise numerical ranges provided. Therefore, these terms should be interpreted as indicating that non-substantial or irrelevant modifications or alterations to the described and claimed subject matter are considered to be within the scope of this disclosure as set forth in the appended claims.

[0097] It should be noted that the term "example" and its variations, as used herein to describe various embodiments, are intended to indicate possible examples, representations, or illustrations of possible embodiments (and such terms are not intended to imply that such embodiments must be extraordinary or optimal examples).

[0098] As used herein, the term "connection" and its variations refer to the direct or indirect linking of two components to each other. Such a connection can be static (e.g., permanent or fixed) or movable (e.g., removable or releasable). This connection can be achieved by directly linking the two components to each other, by using one or more separate intermediate components, or by using an intermediate component integrally formed with one of the two components as a single unit. If "connection" or its variations are modified by the additional term (e.g., direct connection), the general definition of "connection" provided above will be modified by the simple linguistic meaning of the additional term (e.g., "direct connection" refers to the connection of two components without any separate intermediate components), resulting in a narrower definition than the general definition of "connection" provided above. Such a connection can be mechanical, electronic, or fluid. For example, circuit A communicatively "connected" to circuit B can mean that circuit A communicates directly with circuit B (i.e., without an intermediate medium) or indirectly with circuit B (e.g., through one or more intermediate media).

[0099] References to element positions (e.g., "top", "bottom", "above", "below") herein are used only to describe the orientation of the various elements in the figures. It should be noted that the orientation of the various elements may differ according to other exemplary embodiments, and these variations are intended to be covered by this disclosure.

[0100] Although Figure 2 Various circuits with specific functions are illustrated herein; however, it should be understood that controller 140 may include any number of circuits for performing the functions described herein. For example, the activities and functions of sensor management circuitry 210 and / or post-processing modeling circuitry 212 may be combined in multiple circuits or presented as a single circuit. Additional circuitry with additional functions may also be included. Furthermore, controller 140 may control other activities beyond the scope of this disclosure.

[0101] As described above, in one configuration, the "circuit" can be implemented in a machine-readable medium so that it can be processed by various types of processors (e.g., Figure 2 The processor 204 executes the executable code. The executable code may include one or more computer instructions, for example, which may be organized into physical or logical blocks of objects, processes, or functions. However, the executable does not need to be physically located together, but may include scattered instructions stored in different locations that, when logically connected together, constitute a circuit and achieve the circuit's stated purpose. In practice, the circuit of computer-readable program code can be a single instruction or many instructions, and can even be distributed across several different code segments, different programs, and several memory devices. Similarly, operational data can be identified and described within the circuit, and can be implemented in any suitable form and organized within any suitable type of data structure. Operational data may be collected as a single dataset or distributed across different locations including different storage devices, and may exist at least partially as electronic signals on a system or network.

[0102] Although the term "processor" has been briefly defined above, the terms "processor" and "processing circuitry" are intended to be interpreted broadly. In this regard, and as stated above, a "processor" can be implemented as one or more processors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), or other suitable electronic data processing components configured to execute instructions provided by memory. One or more processors can take the form of a single-core processor, a multi-core processor (e.g., a dual-core processor, a triple-core processor, a quad-core processor, etc.), a microprocessor, etc. In some embodiments, one or more processors can be external to the device; for example, one or more processors can be remote processors (e.g., cloud-based processors). Preferably or additionally, one or more processors can be internal and / or local to the device. In this respect, a given circuitry or its components can be arranged locally (e.g., as part of a local server, a local computing system, etc.) or remotely (e.g., as part of a remote server, such as a cloud-based server). For this purpose, a "circuitry" as described herein can include components distributed across one or more locations.

[0103] Embodiments within the scope of this disclosure include program products comprising computer or machine-readable media for carrying or storing computer or machine-executable instructions or data structures thereon. Such machine-readable media can be any available medium accessible by a computer. A computer-readable medium can be a tangible computer-readable storage medium storing computer-readable program code. A computer-readable storage medium can be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor systems, apparatuses, or devices, or any suitable combination of the foregoing. More specific examples of computer-readable media may include, but are not limited to, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable optical disc read-only memory (CD-ROM), digital versatile optical disc (DVD), optical storage devices, magnetic storage devices, holographic storage media, micromechanical storage devices, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium can be any tangible medium that can contain and / or store computer-readable program code for use by and / or connected to an instruction execution system, apparatus, or device. Machine-executable instructions include, for example, instructions and data that cause a computer or processor to perform a function or a set of functions.

[0104] Computer-readable media can also be computer-readable signal media. A computer-readable signal medium may include, for example, a propagated data signal having computer-readable program code therein (e.g., in baseband or as part of a carrier wave). Such a propagated signal can take any of a variety of forms, including but not limited to electrical, electromagnetic, magnetic, optical, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium that is not a computer-readable storage medium and can communicate, propagate, or transmit computer-readable program code for use by or connection to an instruction execution system, apparatus, or device. The computer-readable program code embodied on a computer-readable signal medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency (RF), or any suitable combination thereof.

[0105] In one embodiment, a computer-readable medium may include a combination of one or more computer-readable storage media and one or more computer-readable signal media. For example, computer-readable program code may be both propagated as an electromagnetic signal via optical fiber for execution by a processor and stored on a RAM storage device for processor execution.

[0106] Computer-readable program code used to perform the operations of various aspects of this disclosure may be written in any combination of one or more other programming languages, including object-oriented programming languages ​​such as Java, Simaltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone computer-readable package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)) or may be connected to an external computer (e.g., via the Internet through an Internet service provider).

[0107] Program code may also be stored in a computer-readable medium that can instruct a computer, other programmable data processing apparatus or other device to operate in a particular manner, such that the instructions stored in the computer-readable medium produce instructions including those that implement the functions / actions specified in or in the schematic flowcharts and / or schematic block diagram blocks.

[0108] Although the accompanying drawings and description may show a specific order of method steps, the order of these steps may differ from that depicted and described unless otherwise specified above. Furthermore, unless otherwise specified above, two or more steps may be performed simultaneously or partially simultaneously. This variation may, for example, depend on the chosen software and hardware system and the designer's choices. All such variations are within the scope of this disclosure. Similarly, standard programming techniques with rule-based logic and other logic can be used to implement the described method in software to perform various connection steps, processing steps, comparison steps, and decision steps.

[0109] It is important to note that the construction and arrangement of the apparatuses and systems illustrated in the various exemplary embodiments are merely illustrative. Furthermore, any element disclosed in one embodiment may be combined with or utilized in any other embodiment disclosed herein.

Claims

1. A system for diagnosing at least one component in an exhaust aftertreatment system, characterized in that, include: An exhaust aftertreatment system, the exhaust aftertreatment system being connected to an engine system, such that the exhaust aftertreatment system receives exhaust gas from the engine system; At least one sensor; as well as At least one processing circuit connected to the at least one sensor and the exhaust aftertreatment system, the at least one processing circuit being configured to: Receive initial sensor data from the at least one sensor; Determine initial parameter values ​​based on the initial sensor data; It is determined that the initial parameter value does not meet the initial threshold; In response to determining that the initial parameter value does not meet the initial threshold, an operation is performed to diagnose at least one component of the exhaust aftertreatment system, the operation including: The engine system is operated sequentially through the outputs of multiple engines; Receive multiple sensor data from the at least one sensor, each of the multiple sensor data corresponding to at least one of the multiple engine outputs; Each of the plurality of sensor data is compared with a corresponding threshold from a plurality of thresholds; and The at least one component is diagnosed based on a comparison between the multiple sensor data and the multiple thresholds, and the diagnosis indicates the type of fault.

2. The system according to claim 1, characterized in that, The sequential operations that enable the engine system to output from the plurality of engines include: The engine system is operated with the first engine output; To enable the engine system to operate with the second engine output; and The engine system is operated with the third engine output; Wherein, at least one of the first engine output, the second engine output, or the third engine output is different from at least one of the first engine output, the second engine output, and the third engine output.

3. The system according to claim 2, characterized in that, The multiple sensor data include: The first sensor data received in response to the output of the first engine; Second sensor data received in response to the output of the second engine; and Third sensor data received in response to the first engine output following the third engine output; and Fourth sensor data received in response to the output of the second engine following the output of the third engine.

4. The system according to claim 3, characterized in that, The fault type is at least one of the following: A first fault type is determined by the at least one processing circuit based on the first sensor data not meeting a first threshold among the plurality of thresholds, the second sensor data meeting a second threshold among the plurality of thresholds, the third sensor data meeting a third threshold among the plurality of thresholds, and the fourth sensor data meeting a fourth threshold among the plurality of thresholds, wherein the first fault type indicates a high sulfur poisoning fault type; A second fault type is determined by the at least one processing circuit based on the first sensor data not meeting the first threshold, the second sensor data meeting the second threshold, the third sensor data not meeting the third threshold, and the fourth sensor data meeting the fourth threshold, wherein the second fault type indicates an over-aged part fault type; A third fault type is determined by the at least one processing circuit based on the first sensor data not meeting the first threshold, the second sensor data not meeting the second threshold, the third sensor data meeting the third threshold, and the fourth sensor data meeting the fourth threshold, wherein the third fault type indicates a sediment fault type; or A fourth fault type is determined by the at least one processing circuit based on the first sensor data not meeting the first threshold, the second sensor data not meeting the second threshold, the third sensor data not meeting the third threshold, and the fourth sensor data not meeting the fourth threshold, the fourth fault type indicating a quantitative feeding fault type.

5. The system according to claim 2, characterized in that: The first engine output corresponds to the first temperature value; The second engine outputs a second temperature value that is greater than the first temperature value; as well as The third engine outputs a third temperature value that is greater than the second temperature value; Each of the first temperature value, the second temperature value, and the third temperature value is an exhaust temperature value.

6. The system according to claim 1, characterized in that, The fault type is at least one of the following: The first type of fault indicating high sulfur poisoning; The second type of failure was indicated for the aged parts; The third type of fault indicating sediment failure; or The fourth type of fault indicating quantitative feeding failure.

7. The system according to claim 6, characterized in that, The at least one processing circuit is further configured to: In response to determining that the fault type is the fourth fault type, the engine system is operated with the fourth engine output; Receive additional sensor data from the at least one sensor; as well as The at least one component is diagnosed by comparing the additional sensor data with the corresponding threshold.

8. The system according to claim 7, characterized in that, The fourth engine output corresponds to a predetermined engine output exhaust component value.

9. The system according to claim 7, characterized in that, The at least one processing circuit is further configured to initiate a process of the exhaust aftertreatment system in response to determining that the additional sensor data meets the corresponding threshold, the process including: The quantitative feeder of the exhaust aftertreatment system outputs multiple quantitative feed values; and Sensor data for each of the plurality of quantitative feed values ​​is received from the at least one sensor.

10. A method for diagnosing at least one component in an exhaust aftertreatment system, characterized in that, The method includes: Receive initial sensor data; Determine initial parameter values ​​based on the initial sensor data; It is determined that the initial parameter value does not meet the initial threshold; In response to determining that the initial parameter value does not meet the initial threshold, an operation is performed to diagnose at least one component of the exhaust aftertreatment system, the operation including: To enable the engine to operate in a sequence of outputs from multiple engines; Receive data from multiple sensors, each of which corresponds to at least one of the multiple engine outputs; Each of the plurality of sensor data is compared with a corresponding threshold from a plurality of thresholds; and The at least one component is diagnosed based on a comparison between the multiple sensor data and the multiple thresholds.

11. The method according to claim 10, characterized in that, The sequence of operations that cause the engine to output through the plurality of engines includes: The engine is operated with a first engine output, the first engine output corresponding to a first temperature value; The engine is operated with a second engine output, the second engine output corresponding to a second temperature value greater than the first temperature value; and The engine is operated with a third engine output, the third engine output corresponding to a third temperature value greater than the second temperature value; Each of the first temperature value, the second temperature value, and the third temperature value is an exhaust temperature value.

12. The method according to claim 11, characterized in that, The multiple sensor data include: The first sensor data received in response to the output of the first engine; Second sensor data received in response to the output of the second engine; Third sensor data received in response to the first engine output following the third engine output; and Fourth sensor data received in response to the output of the second engine following the output of the third engine.

13. The method according to claim 12, characterized in that, The fault type is at least one of the following: A first fault type is determined based on the first sensor data not meeting the first threshold among the plurality of thresholds, the second sensor data meeting the second threshold among the plurality of thresholds, the third sensor data meeting the third threshold among the plurality of thresholds, and the fourth sensor data meeting the fourth threshold among the plurality of thresholds. The first fault type indicates a high sulfur poisoning fault type. A second fault type is determined based on the first sensor data not meeting the first threshold, the second sensor data meeting the second threshold, the third sensor data not meeting the third threshold, and the fourth sensor data meeting the fourth threshold. The second fault type indicates an over-aged part fault type. A third fault type is determined based on the first sensor data not meeting the first threshold, the second sensor data not meeting the second threshold, the third sensor data meeting the third threshold, and the fourth sensor data meeting the fourth threshold. This third fault type indicates a sediment fault type. A fourth fault type is determined based on the fact that the first sensor data does not meet the first threshold, the second sensor data does not meet the second threshold, the third sensor data does not meet the third threshold, and the fourth sensor data does not meet the fourth threshold. The fourth fault type indicates a quantitative feeding fault type.

14. The method according to claim 13, characterized in that, Also includes: In response to determining that the fault type is the fourth fault type, the engine is operated as a fourth engine output; Receive data from additional sensors; as well as The at least one component is diagnosed by comparing the additional sensor data with the corresponding threshold.

15. The method according to claim 14, characterized in that, The fourth engine output corresponds to a predetermined engine output exhaust component value.

16. The method according to claim 14, characterized in that, It also includes a process for activating the exhaust aftertreatment system in response to determining that the additional sensor data meets the corresponding threshold, the process comprising: The quantitative feeder of the exhaust aftertreatment system outputs multiple quantitative feed values; and Receive overcurrent sequence sensor data for each of the plurality of quantitative feed values; and The at least one component is diagnosed by comparing the supercontrol sequence sensor data with another threshold.

17. An apparatus for diagnosing at least one component in an exhaust aftertreatment system, characterized in that, The device includes: At least one processor; and At least one memory device is coupled to the at least one processor, the at least one memory device storing instructions that, when executed by the at least one processor, cause the at least one processor to: Receive initial sensor data; Determine initial parameter values ​​based on the initial sensor data; It is determined that the initial parameter value does not meet the initial threshold; In response to determining that the initial parameter value does not meet the initial threshold, an operation is performed to diagnose at least one component of the exhaust aftertreatment system, the operation including: To enable the engine to operate in a sequence of outputs from multiple engines; Receive data from multiple sensors, each of which corresponds to at least one of the multiple engine outputs; Each of the plurality of sensor data is compared with a corresponding threshold from a plurality of thresholds; and The at least one component is diagnosed based on a comparison between the multiple sensor data and the multiple thresholds, and the diagnosis indicates the type of fault.

18. The apparatus according to claim 17, characterized in that, The sequence of operations that cause the engine to output through the plurality of engines includes: The engine is operated with a first engine output, the first engine output corresponding to a first temperature value; The engine is operated with a second engine output, the second engine output corresponding to a second temperature value greater than the first temperature value; and The engine is operated with a third engine output, the third engine output corresponding to a third temperature value greater than the second temperature value; Wherein, each of the first temperature value, the second temperature value, and the third temperature value is an exhaust temperature value; and The multiple sensor data include: The first sensor data received in response to the output of the first engine; Second sensor data received in response to the output of the second engine; Third sensor data received in response to the first engine output following the third engine output; and Fourth sensor data received in response to the output of the second engine following the output of the third engine.

19. The apparatus according to claim 18, characterized in that, The fault type is at least one of the following: A first fault type is determined based on the first sensor data not meeting the first threshold among the plurality of thresholds, the second sensor data meeting the second threshold among the plurality of thresholds, the third sensor data meeting the third threshold among the plurality of thresholds, and the fourth sensor data meeting the fourth threshold among the plurality of thresholds. The first fault type indicates a high sulfur poisoning fault type. A second fault type is determined based on the first sensor data not meeting the first threshold, the second sensor data meeting the second threshold, the third sensor data not meeting the third threshold, and the fourth sensor data meeting the fourth threshold. The second fault type indicates an over-aged part fault type. A third fault type is determined based on the first sensor data not meeting the first threshold, the second sensor data not meeting the second threshold, the third sensor data meeting the third threshold, and the fourth sensor data meeting the fourth threshold. This third fault type indicates a sediment fault type. A fourth fault type is determined based on the fact that the first sensor data does not meet the first threshold, the second sensor data does not meet the second threshold, the third sensor data does not meet the third threshold, and the fourth sensor data does not meet the fourth threshold. The fourth fault type indicates a quantitative feeding fault type.

20. The apparatus according to claim 19, characterized in that, The instruction also causes the at least one processor to: In response to determining that the fault type is the fourth fault type, the engine is operated as a fourth engine output; Receive data from additional sensors; as well as The at least one component is diagnosed by comparing the additional sensor data with corresponding thresholds; The fourth engine output corresponds to a predetermined engine output exhaust component value.

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