Route identification methods that facilitate successful diagnosis of exhaust treatment systems

Abstract

A route identification method that facilitates successful diagnosis of exhaust treatment systems. The present disclosure proposes method steps (200) that facilitate route identification for successful diagnosis of exhaust treatment systems. In step 201, an ECU (104) in a vehicle receives GPS coordinate values from a GPS module (106). In step 202, the ECU (104) retrieves values of day, date, and time from an ECU (104) clock. In step 203, the ECU (104) monitors values of engine operating conditions with reference to the GPS coordinate values and the values of day, date, and time. In method step 203, the ECU (104) identifies a GPS coordinate segment for successful diagnosis of exhaust treatment systems based on the monitored values. Upon identification, the GPS coordinate segment is stored in an ECU (104) memory.

Description

Technical Field

[0001] This invention relates to a route identification method that facilitates successful diagnosis of exhaust treatment systems. Background Technology

[0002] The exhaust system used in combustion-driven vehicles requires diagnostics of its components for each driving cycle. One method for onboard system diagnostics of exhaust components is to actively alternating the air / fuel ratio (hereinafter referred to as lambda) to lean and rich, and assessing the characteristics of the oxygen sensor signal. However, these lambda alterations for diagnostic purposes temporarily result in high emissions. Furthermore, the diagnostic only operates when specific operating conditions (e.g., steady-state exhaust mass, engine speed, load, temperature, etc.) are maintained for a certain duration, during which the diagnostic function begins and then yields a result. Even if a desired condition is lost before it reaches a conclusion, the diagnostic must be repeated from scratch. The diagnostic duration can be measured in seconds (typically around 10 to 30 seconds), which can be difficult to achieve uninterruptedly in high-traffic urban environments, and the high probability of diagnostic interruptions leads to more emission spikes. Therefore, there is a need for predicting routes or segments that will facilitate system diagnostics of the exhaust system. Traditional methods utilize real-time navigation data from the internet or cloud-based services to predict route segments favorable for this diagnostic.

[0003] Patent application US2014019019 AA, entitled "Method for monitoring components of a motor vehicle and motorvehicle with corresponding monitoring device," discloses a method for monitoring the functionality of first and second components of a motor vehicle, with the following requirements for monitoring: for effective monitoring of the first component, predetermined operating conditions of the motor vehicle must be present; for effective monitoring of the second component, the first component must be functioning properly. According to the method of the invention, navigation data from a navigation assistance system is taken into account before travel to determine whether the predetermined operating conditions are expected to exist. Summary of the Invention

[0004] According to one aspect of the invention, a route identification method is provided to facilitate successful diagnosis of an exhaust treatment system in a vehicle, the vehicle including at least an electronic control unit (ECU (104)) communicating with components of the exhaust treatment system, the ECU (104) communicating with a global positioning system (GPS), the ECU (104) including a processing unit and at least one memory, the method comprising: receiving GPS coordinate values ​​from a GPS module (106); retrieving date and time values ​​from a clock on the ECU (104); monitoring engine operating condition values ​​with reference to the GPS coordinate values ​​and the date and time values; and identifying GPS coordinate segments for successful diagnosis of the exhaust treatment system based on the monitored values. Attached Figure Description

[0005] Embodiments of the present invention are described with reference to the following figures: Figure 1 The layout of an exhaust treatment system (100) according to an embodiment of the present invention is depicted; and Figure 2 Method steps for route identification that facilitate successful diagnosis of exhaust treatment systems are described (200). Detailed Implementation

[0006] Figure 1 The layout of an exhaust treatment system (100) according to an embodiment of the present invention is depicted. The exhaust system includes a catalytic converter (105) disposed in an exhaust path (101), an oxygen sensor (102) upstream of the catalytic converter (105), and an oxygen sensor (103) downstream of the catalytic converter (105). An engine electronic control unit (ECU (104)) communicates with at least the oxygen sensor (102) upstream of the catalytic converter (105) and the oxygen sensor (103) downstream of the catalytic converter (105). Those skilled in the art will appreciate that the ECU (104) in conventional exhaust systems also communicates with other components such as temperature sensors and differential pressure sensors. According to an embodiment of the present invention, the ECU (104) communicates with a Global Positioning System (GPS) module in the vehicle.

[0007] Diagnostic methods for exhaust components involve actively alternating the air / fuel ratio (hereinafter referred to as lambda) to lean and rich, and evaluating the characteristics of the oxygen sensor signal. These lambda alterations used for diagnostic purposes result in emission spikes. On the other hand, this diagnostic requires specific operating conditions (e.g., steady-state exhaust mass, engine speed, load, temperature, etc.) to be maintained for a certain duration during which the diagnostic function initiates and then yields a result. Even if a required condition is lost before it reaches a conclusion, the diagnostic must be repeated from scratch. The diagnostic duration can be measured in seconds (typically around 10…30 seconds), which can be difficult to achieve uninterruptedly in high-traffic urban environments, and the high probability of diagnostic interruptions leads to more emission spikes.

[0008] Figure 2 Depicting what helps as according to Figure 1 The described method steps (200) for successful route identification in the exhaust treatment system diagnosis are as follows. The vehicle includes at least an electronic control unit (ECU (104)) that communicates with components of the exhaust treatment system. The ECU (104) communicates with a Global Positioning System (GPS) and includes a processing unit and at least one memory. In step 201, the ECU (104) receives GPS coordinate values ​​from a GPS module (106). This is a continuous process initiated in each vehicle driving cycle. In step 202, the ECU (104) retrieves the day, date, and time values ​​from its clock. The retrieved values ​​correspond to the received GPS coordinate records.

[0009] In step 203, the ECU (104) monitors engine operating conditions with reference to GPS coordinates and the values ​​of day, date, and time. Engine operating parameters include, but are not limited to, the following steady-state exhaust mass, engine speed, engine load, and at least one engine temperature. For example, the conditions for monitoring the route segment to be extracted are: vehicle speed is stable and within a defined range, engine speed and load are also stable and within a defined range, exhaust catalyst temperature is not fluctuating and is within a defined temperature window, and no out-of-limit conditions are identified.

[0010] In method step 203, the ECU (104) identifies GPS coordinate segments for successful diagnosis of the exhaust treatment system based on monitored values. Identification of the GPS coordinate segments involves comparing instantaneous engine operating parameters with predetermined values ​​of engine operating parameters conducive to successful diagnosis of the exhaust treatment system. For example, for a specific exhaust system, predetermined values ​​of engine operating parameters conducive to successful diagnosis could be vehicle speed stable between 30 kmph and 70 kmph, engine speed stable between 2000 rpm and 4000 rpm, engine load stable between 30% and 70%, and exhaust catalyst temperature stable between 400°C and 600°C. Coordinate groups or segments that meet these conditions are identified and extracted as route segments conducive to successful diagnosis. After identification, the GPS coordinate segments are stored in the ECU (104) memory.

[0011] After learning regular routes and suitable route segments for diagnosis within a certain number of driving cycles, these are further stored for the prediction algorithm, and relearned within the driving cycle based on the actual success rate of the prediction algorithm. Each suitable route segment of the learned route is assigned a prediction probability, i.e., the probability of completing the diagnosis in that route segment. Based on this probability value, the ECU (104) can decide whether lambda modulation for diagnosis should be triggered.

[0012] Figure 1 The ECU (104) depicted is adapted to learn successful diagnostic routes for the exhaust treatment system. The ECU (104) includes a processing unit and at least one memory. In embodiments of the invention, the processor runs an artificial intelligence-based model. The ECU (104) is configured to: receive GPS coordinate values ​​from a GPS module (106); retrieve day and time values ​​from the ECU (104) clock; monitor engine operating conditions with reference to the GPS coordinate values ​​and the day and time values; identify GPS coordinate segments for successful diagnostics of the exhaust treatment system based on the monitored values; and store the GPS coordinate segments in the memory. Those skilled in the art will appreciate that while these methods describe only a series of steps to achieve the objective, these methods can be implemented within the ECU (104) software in a vehicle, or via the cloud or a combination thereof.

[0013] The idea of ​​developing a route identification method that facilitates successful diagnostics of exhaust treatment systems helps identify and learn route segments for a sufficient duration, where diagnostics can be completed uninterrupted. This route learning-based predictive diagnostics enablement helps reduce real-world driving emissions in high-traffic cities where maintaining enablement conditions for the required time span would be difficult.

[0014] It must be understood that the embodiments described in the above detailed description are merely illustrative and do not limit the scope of the invention. Any modifications to the route identification method that facilitates successful diagnosis of exhaust treatment systems are contemplated and form part of this invention. The scope of the invention is limited only by the claims.

Claims

1. A route identification method for successfully diagnosing an exhaust treatment system in a vehicle, the vehicle including at least an electronic control unit (ECU (104)) communicating with components of the exhaust treatment system, the ECU (104) communicating with a global positioning system (GPS), the ECU (104) including a processing unit and at least one memory, the method comprising: Receive GPS coordinate values ​​from GPS module (106); Retrieve the date and time values ​​from the ECU (104) clock; Monitor engine operating conditions using GPS coordinates, date, and time values; GPS coordinate segments used for successful diagnostics of exhaust treatment systems are identified based on monitored values.

2. The route learning method for successfully diagnosing an exhaust treatment system in a vehicle according to claim 1, wherein the engine operating parameters include steady-state exhaust mass, engine speed, engine load, and engine temperature.

3. The route learning method for successfully diagnosing an exhaust treatment system in a vehicle according to claim 1, wherein the identification of GPS coordinate segments includes comparing instantaneous engine operating parameters with predetermined values ​​of engine operating parameters that are conducive to successful diagnosis of the exhaust treatment system.

4. The route learning method for successfully diagnosing an exhaust treatment system in a vehicle according to claim 1, wherein after identification, the GPS coordinate segments are stored in the memory of the ECU (104).

5. An electronic control unit (ECU (104)) suitable for learning routes for successful diagnostics of an exhaust treatment system in a vehicle, the ECU (104) communicating with components of the exhaust treatment system, the ECU (104) communicating with a global positioning system (GPS), the ECU (104) including a processing unit and at least one memory, the ECU (104) being configured to: Receive GPS coordinate values ​​from GPS module (106); Retrieve the date and time values ​​from the ECU (104) clock; Monitor engine operating conditions by referencing GPS coordinates, date, and time. GPS coordinate segments used for successful diagnostics of exhaust treatment systems are identified based on monitored values. Store GPS coordinate segments in memory.

6. The electronic control unit (ECU (104)) of claim 5, which is suitable for learning routes for successfully diagnosing exhaust treatment systems in vehicles, wherein the processor runs an artificial intelligence-based model.

7. The electronic control unit (ECU (104)) according to claim 5, suitable for learning routes for successful diagnosis of exhaust treatment systems in vehicles, wherein engine operating parameters include steady-state exhaust mass, engine speed, engine load, and engine temperature.

8. The electronic control unit (ECU (104)) according to claim 5, which is suitable for learning routes for successful diagnosis of an exhaust treatment system in a vehicle, wherein the identification of GPS coordinate segments includes comparing instantaneous engine operating parameters with predetermined values ​​of engine operating parameters that are conducive to successful diagnosis of the exhaust treatment system.

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