A method and system for monitoring the exhaust state of a vehicle

Abstract

This invention relates to the field of automotive testing and diagnostic technology, and discloses a method for monitoring the state of automotive exhaust systems, comprising the following steps: S1: Arranging a physical quantity sensor group at at least two key monitoring points of the automotive exhaust system, wherein the key monitoring points include at least the intake end and the exhaust end of a three-way catalytic converter, and the physical quantity sensor group includes at least a first type of sensor for monitoring gas concentration and a second type of sensor for monitoring temperature; by pre-storing benchmark parameters locally in the on-board processing unit and performing real-time data comparison and logical judgment, the system completely eliminates the dependence on cloud servers and continuous network connections. The system can immediately complete the analysis and trigger an early warning after data acquisition, with a fast response speed. Based on the direct comparison of physical quantities with the pre-stored benchmark range, and combined with the real-time engine status for logical judgment, the diagnostic path is clear and explicit. This method avoids problems such as model distortion and overfitting that may exist in complex algorithms.

Description

Technical Field

[0001] This invention relates to the field of automotive testing and diagnostic technology, specifically to a method and system for monitoring the exhaust status of automobiles. Background Technology

[0002] Effective monitoring of automotive exhaust systems is crucial for ensuring vehicle emissions compliance, improving engine efficiency, and preventing malfunctions. Traditional exhaust condition monitoring methods have many limitations. For example, Chinese invention patent CN120313927A discloses an IoT-based automotive exhaust condition monitoring method and system. It proposes to deploy sensors in the exhaust system, receive data through an onboard data acquisition module, and upload the data to a cloud server after packaging and encrypting it using IoT communication. In the cloud, algorithms such as multiple linear regression are used to build models for data analysis, and finally the results are fed back to the onboard equipment for alerts.

[0003] While this type of solution, based on the Internet of Things and cloud-based intelligent analysis, achieves remote data monitoring to a certain extent, its core reliance on stable network connections and the computing power of cloud servers results in the following significant drawbacks: 1. Real-time monitoring and early warning cannot be achieved in areas with poor or interrupted network signals, making it difficult to meet the need for rapid response to sudden malfunctions during driving; Second, cloud-based data processing has inherent latency, making it difficult to achieve millisecond-level local real-time diagnosis; Third, the overall system is complex and costly, involving data encryption, cloud resource maintenance, etc., and the adaptability of complex algorithms depends on a large amount of high-quality data, making it cumbersome to adjust the universality for different vehicle models and working conditions. Fourth, its fault judgment logic is mostly based on indirect, complexly processed data conclusions, rather than directly triggering actions through simple and direct comparison of physical quantities, making the fault judgment logic less intuitive and reliable. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for monitoring the exhaust status of automobiles, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for monitoring the exhaust status of an automobile, comprising the following steps: S1: Physical quantity sensor groups are arranged at at least two key monitoring points in the vehicle exhaust system. The key monitoring points include at least the intake end and the exhaust end of the three-way catalytic converter. The physical quantity sensor groups include at least a first type of sensor for monitoring gas concentration and a second type of sensor for monitoring temperature. S2: The signal from the physical quantity sensor group is received in real time through a local vehicle-mounted processing unit. The vehicle-mounted processing unit has a pre-stored reference parameter range under normal operating conditions of the exhaust system corresponding to the vehicle model. The reference parameter range includes the gas concentration reference range and temperature reference range of each monitoring point. S3: The vehicle-mounted processing unit will directly compare the gas concentration signal and temperature signal received in real time from each monitoring point with the pre-stored gas concentration reference range and temperature reference range of the corresponding monitoring point. S4: When the real-time gas concentration value of any monitoring point continuously exceeds its corresponding gas concentration reference range for a first preset time, and / or when the real-time temperature value of any monitoring point continuously exceeds its corresponding temperature reference range for a second preset time, the vehicle-mounted processing unit immediately generates a preliminary abnormal signal. S5: The vehicle processing unit is further provided with a status logic judgment module. This module receives the preliminary abnormal signal and simultaneously acquires the real-time engine operating status parameters sent by the engine control unit through the vehicle controller local area network bus. The real-time engine operating status parameters include at least engine speed and load. S6: The state logic judgment module is based on a set of predefined fault-state mapping relationships. It combines the monitoring point location and abnormal physical quantity type corresponding to the preliminary abnormal signal with the engine real-time operating status parameters for logical judgment. The fault-state mapping relationship defines the correspondence between different monitoring point combination abnormal modes and specific exhaust system component faults or engine operating status abnormalities. S7: If the result of the combined logic judgment points to a potential fault or performance degradation of a specific component in the exhaust system, the state logic judgment module outputs a specific component fault identification code. S8: The vehicle-mounted processing unit drives the vehicle-mounted human-machine interface to provide graded visual and auditory warnings based on the received component fault identification code. At the same time, it stores a diagnostic data frame containing the component fault identification code and the corresponding timestamp through the vehicle's built-in diagnostic communication interface, making it readable by external standard diagnostic equipment.

[0006] As a preferred embodiment of the present invention, in step S1: The first type of sensor in the physical quantity sensor group is a wide-range oxygen sensor, which is arranged at the inlet and outlet of the three-way catalytic converter to monitor the oxygen concentration in the exhaust gas. The second type of sensor is a thermocouple temperature sensor, which is also arranged at the intake and exhaust ends of the three-way catalytic converter to monitor the exhaust temperature. In step S2, the reference parameter range includes the normal fluctuation range of oxygen concentration at the intake end of the three-way catalytic converter, the stable low value range of oxygen concentration at the outlet end, the engine load-related range of the intake end temperature, and the reasonable temperature difference range between the outlet end temperature and the intake end temperature.

[0007] As a preferred embodiment of the present invention, the combinational logic judgment performed by the state logic judgment module in step S6 includes: When the real-time oxygen concentration at the outlet of the three-way catalytic converter is continuously higher than its stable low value range, and the real-time temperature difference between the inlet and outlet is continuously lower than the lower limit of the reasonable temperature difference range, the three-way catalytic converter is determined to have insufficient conversion efficiency, regardless of the engine's operating state, and the corresponding component fault code is output. When the real-time oxygen concentration value at the intake end of the three-way catalytic converter is detected to continuously exceed its normal fluctuation range, accompanied by non-command fluctuations in engine speed under steady-state conditions, it is first determined that the upstream air-fuel ratio control related sensors or actuators are abnormal, and the corresponding component fault identification code is output.

[0008] As a preferred embodiment of the present invention, the method further includes a sensor self-calibration step S0 after step S1 and before step S2: S0: Each time the vehicle starts, the on-board processing unit controls a standard gas release device integrated in the exhaust pipe to release a standard gas of known concentration to a designated calibration point; a physical quantity sensor arranged at the calibration point measures the standard gas; the on-board processing unit compares the measured value with the known concentration value of the standard gas, and if the deviation exceeds the allowable tolerance range, it determines that the sensor reading is unreliable and generates a sensor calibration failure flag; in the subsequent step S6, the state logic judgment module will ignore the data from the sensor or assign a lower confidence weight to its data.

[0009] As a preferred technical solution of the present invention, the determination of the first preset duration and the second preset duration in step S4 includes the following sub-steps: S4.1: The on-board processing unit pre-stores a duration-operating condition mapping table, which defines different duration combinations corresponding to different engine speeds and load ranges; S4.2: During the monitoring process, the on-board processing unit acquires the current engine speed and load in real time; S4.3: Based on the current engine speed and load, query the duration-condition mapping table, dynamically determine and apply the corresponding first preset duration and second preset duration.

[0010] As a preferred embodiment of the present invention, the graded visual and auditory warnings in step S8 specifically include: When the fault code of the component indicates a fault level of Level 1, which means a fault that does not affect short-term driving safety but needs to be repaired as soon as possible, a yellow indicator light will flash and an intermittent single tone will be triggered. When the fault code of the component indicates a fault level of level two, which may lead to excessive emissions or component damage, a yellow indicator light will be constantly lit and a continuous single tone will be triggered. When the fault code of the component indicates a fault level of three, which may lead to serious emissions exceeding standards or safety hazards, a red indicator light will remain on and a rapid beeping sound will be triggered as a warning.

[0011] As a preferred embodiment of the present invention, the method further includes a baseline parameter adaptive update step S9 after step S8: S9.1: When the vehicle is determined to be in a stable and normal driving condition, the on-board processing unit continuously records the physical quantity data of each monitoring point to form a historical normal data set. S9.2: When the amount of data accumulated in the historical normal data set reaches a preset threshold, the vehicle processing unit determines the central tendency range and discrete fluctuation range of the values ​​of each physical quantity data in the set. S9.3: Compare the determined central tendency range and discrete fluctuation range with the currently stored benchmark parameter range; S9.4: If the deviation between the determined central tendency range and discrete fluctuation range and the current benchmark parameter range exceeds a preset adaptation threshold, the boundary values ​​of the benchmark parameter range are updated based on the central tendency range and discrete fluctuation range.

[0012] 8. A vehicle exhaust condition monitoring system for implementing the above method, the system comprising: A sensor module for performing step S1 includes a physical quantity sensor group arranged at at least two key monitoring points of the vehicle exhaust system, the physical quantity sensor group including at least a first type of sensor for monitoring gas concentration and a second type of sensor for monitoring temperature; A local vehicle-mounted processing module, electrically connected to the sensor module, is used to execute steps S2 to S9. The local vehicle-mounted processing module includes: The signal conditioning unit is used to amplify and convert sensor signals from analog to digital. The data storage unit pre-stores the reference parameter range of the exhaust system under normal operating conditions corresponding to the vehicle model; The real-time comparison unit is used to execute steps S3 and S4, compare the converted sensor data with the reference parameter range in real time, and generate a preliminary abnormal signal. The state logic judgment unit is used to execute steps S5, S6 and S7. It has a pre-stored fault-state mapping relationship and is used to perform combined logic judgment based on the preliminary abnormal signal and the real-time operating status parameters of the engine, and output the component fault identification code. The parameter adaptive unit is used to execute step S9, which determines the central tendency range and discrete fluctuation range of the physical quantity data based on the historical normal data set, and updates the reference parameter range accordingly. The vehicle bus interface module is used to obtain real-time engine operating status parameters from the vehicle controller area network bus. The human-machine interaction module is connected to the local vehicle-mounted processing module and is used to execute the graded warning in step S8. The diagnostic communication interface module is connected to the local vehicle-mounted processing module and is used to perform diagnostic data frame output and storage in step S8.

[0013] As a preferred embodiment of the present invention, the system further includes a standard gas self-calibration module integrated on the exhaust pipe for performing step S0. This module includes: A gas cylinder containing a standard gas of known concentration; A solenoid valve controlled by the local on-board processing module is used to control the release of standard gas; A dedicated calibration chamber in which the sensing portion of at least one sensor in the physical quantity sensor group is exposed for measuring the released standard gas when the solenoid valve is opened.

[0014] As a preferred technical solution of the present invention, the real-time comparison unit is configured to: access the duration-operating condition mapping table pre-existing in the data storage unit, and query and determine the first preset duration and the second preset duration to be used based on the real-time engine speed and load obtained by the vehicle bus interface module.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. By pre-storing baseline parameters locally in the on-board processing unit and performing real-time data comparison and logical judgment, the system completely eliminates the dependence on cloud servers and continuous network connections. The system can complete the analysis and trigger the warning immediately after data collection, with a fast response speed. It is especially suitable for the immediate diagnosis of sudden failures in the exhaust system, ensuring the real-time performance of driving safety and emission control.

[0016] 2. It eliminates the need for complex cloud data processing centers, remote communication modules, and the deployment and maintenance of advanced algorithm models, simplifying the system structure. This not only reduces hardware costs but also decreases the complexity of system operation and maintenance and long-term costs, making it more conducive to large-scale promotion and application in various vehicle models.

[0017] 3. Based on the direct comparison of physical quantities with pre-stored benchmark ranges and combined with the real-time status of the engine for logical judgment, the diagnostic path is clear and explicit. This method avoids problems such as model distortion and overfitting that may exist in complex algorithms, has stronger anti-interference ability, and higher reliability and credibility of the results.

[0018] 4. Through the adaptive update mechanism of the benchmark parameters, the system can slowly adjust the monitoring threshold according to the actual data of the vehicle's long-term operation, effectively compensating for the impact caused by vehicle aging, slow performance degradation of components, or slight sensor drift. This enables the monitoring system to maintain high accuracy throughout the entire life cycle of the vehicle, improving the long-term stability and durability of the system.

[0019] 5. The graded visual and auditory warning mechanism provides clear prompts based on the fault level, making it easy for drivers to quickly understand the vehicle status and take appropriate measures. At the same time, the diagnostic data frames output by the standard diagnostic interface provide maintenance personnel with accurate fault information, greatly facilitating subsequent vehicle maintenance and fault diagnosis, forming a complete closed loop of monitoring, early warning, diagnosis, and maintenance.

[0020] 6. By dynamically adjusting the duration of anomaly detection through a duration-operating condition mapping table, the system can maintain high sensitivity and low false alarm rate under different engine operating conditions, achieving refined operating condition adaptation and further ensuring the accuracy of monitoring results.

[0021] 7. The standard gas self-calibration module integrated into the system can automatically calibrate key sensors when the vehicle starts or periodically, ensuring the accuracy of monitoring data from the source and avoiding system performance degradation due to sensor performance decay, thus laying a solid foundation for the reliable operation of the entire monitoring system. Attached Figure Description

[0022] Figure 1 This is an overall flowchart of a method for monitoring the exhaust status of an automobile according to the present invention; Figure 2 This is a schematic diagram of the internal module structure of the vehicle-mounted processing unit in this invention; Figure 3 This is a logical diagram illustrating the fault diagnosis performed by the state logic judgment module in this invention. Figure 4 This is a schematic diagram of the structural composition of the standard gas self-calibration module in this invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example 1: Exhaust Condition Monitoring System Based on Local Logic Judgment (Applicable to Ordinary Passenger Vehicles) System Configuration: Monitoring points: Inlet and outlet of the three-way catalytic converter; Sensors: Wide-range oxygen sensor (Bosch LSU 4.9), K-type thermocouple temperature sensor; Onboard processing unit: An embedded system based on ARM Cortex-M7, with pre-stored reference parameter range; Communication interface: CAN 2.0B; Diagnostic interface: OBD-II; Software modules: real-time comparison unit, state logic judgment unit, parameter adaptive unit.

[0025] Implementation steps: 1. Sensor placement and self-calibration (steps S0, S1) A sensor array was installed on 10 gasoline-powered vehicles in a fleet in Chongqing. Each time the vehicle was started, the oxygen sensor underwent self-calibration via a standard gas release device (containing standard gas with a CO concentration of 1.5%) integrated into the exhaust pipe. The calibration results are shown in the table below:

[0026] Sensors that fail the verification are given lower weight in subsequent logical judgments.

[0027] 2. Real-time comparison and anomaly detection (steps S2-S4) Set the reference parameter range: Oxygen concentration at the intake end: 0.1%–0.9%; Oxygen concentration at the outlet: 0.05%–0.2%; Inlet temperature: 300℃~600℃; Outlet temperature: 350℃~650℃; Reasonable temperature difference range: 50℃~150℃.

[0028] Real-time data is compared with the baseline range, and the duration of any deviation is dynamically adjusted based on engine operating conditions (see table below):

[0029] 3. Status logic judgment and fault identification (steps S5-S7) Typical fault diagnosis logic: If the oxygen concentration at the outlet is consistently >0.2% and the temperature difference between the inlet and outlet is <50℃, it is determined that the three-way catalytic converter has insufficient conversion efficiency, and fault code P0420 is output. If the oxygen concentration at the intake end remains above 0.9% and the engine speed fluctuates by more than 5%, it is determined that the upstream air-fuel ratio control is abnormal, and fault code P0171 is output.

[0030] 4. Warnings and Data Recording (Step S8) Different warnings are triggered based on the fault severity: Level 1 fault (e.g., P0171): Yellow indicator light flashes + intermittent single tone; Level 2 fault (e.g., P0420): Yellow indicator light stays on continuously + continuous single tone; Level 3 fault (such as abnormal exhaust temperature): Red indicator light stays on + rapid beeping.

[0031] 5. Adaptive update of baseline parameters (step S9) The system records normal data during stable vehicle operation. When the data reaches 1,000 sets, the baseline range is recalculated. For example, after a vehicle has accumulated 5,000 kilometers of driving, the baseline range of oxygen concentration at the outlet end is adaptively adjusted from 0.05% to 0.2% to 0.06% to 0.18%.

[0032] Experimental Data and Analysis: Ten vehicles were subjected to a six-month follow-up test, and the accuracy and false alarm rates of fault diagnosis were recorded.

[0033] Analysis and Explanation: This embodiment achieves high-precision fault diagnosis through a localized processing unit, with an average accuracy of 96.9% and a false alarm rate of only 3.1%. The system has good adaptive capabilities and can dynamically adjust the judgment threshold according to the actual operating status of the vehicle, effectively avoiding misjudgments caused by sensor drift or vehicle aging. In addition, the graded warning mechanism improves user experience and safety performance.

[0034] Example 2: High-precision monitoring system with standard gas self-calibration module (suitable for emission monitoring stations) System Configuration: Add a standard gas self-calibration module: including a gas cylinder (for storing CO and NOx standard gases), a solenoid valve, and a dedicated calibration chamber; Sensors: High-precision infrared gas sensor (for CO, NOx), PT100 temperature sensor; Processing unit: Industrial-grade industrial control computer, with real-time data fusion and fault tracing functions.

[0035] Implementation steps: 1. Self-verification process (step S0) Standard gas is automatically released before each test to calibrate the sensor accuracy. The calibration data is as follows:

[0036] 2. Dynamic duration adjustment (step S4) The duration of the anomaly is dynamically adjusted based on the type of vehicle being detected (gasoline or diesel).

[0037] 3. Fault diagnosis and output (steps S6-S7) By combining engine data and exhaust data, multi-dimensional fault diagnosis can be achieved, such as: If the NOx concentration and intake volume are abnormal, it is determined to be a fault in the SCR system. If the CO concentration is abnormal and the air-fuel ratio fluctuates, it is determined that the fuel injection system is abnormal.

[0038] Experimental Data and Analysis: Fifty vehicles were tested at a testing station in Chengdu, and the results are as follows:

[0039] Analysis and Explanation: This embodiment significantly improves the long-term stability and measurement accuracy of the sensor by integrating a standard gas self-calibration module. Combined with a dynamic duration adjustment mechanism, the system exhibits high detection rate and low false alarm rate under different vehicle types and operating conditions, making it suitable for high-standard emission testing scenarios.

[0040] Comparison with Example 1: Traditional monitoring system without self-calibration function System Configuration: Sensors: Common oxygen sensor, thermocouple; Processing unit: a comparator based on a fixed threshold; It lacks self-checking, dynamic adjustment, and adaptive updates.

[0041] Experimental data: Simultaneous testing of 10 vehicles:

[0042] Analysis and Explanation: In the comparison example, due to the lack of self-verification and adaptive mechanisms, the system exhibited significant drift after the vehicle had been running for a period of time, resulting in a false alarm rate as high as 51.1% and an accuracy rate of only 73.3%. Furthermore, the fixed threshold could not adapt to different operating conditions, further reducing the reliability and practicality of the system.

[0043] Example 3: Adaptive monitoring system suitable for plateau regions (taking Shangri-La region of Yunnan Province as an example) System Configuration: Add a barometric pressure sensor to compensate for the oxygen concentration benchmark in high-altitude areas; The reference parameter range is dynamically adjusted according to altitude; The adaptive unit is enhanced to support the fusion of multiple environmental factors.

[0044] Implementation steps: 1. Altitude compensation for reference parameters At an altitude of 3300 meters, the baseline range for oxygen concentration at the outlet is adjusted to 0.08%–0.25%. 2. Dynamic duration adjustment Engine load changes frequently in high-altitude areas, so the preset duration has been further shortened.

[0045] Experimental data: Fifteen vehicles were tested in the Shangri-La area:

[0046] Analysis and Explanation: This embodiment effectively addresses complex working conditions in high-altitude areas by introducing environmental factor compensation and more frequent adaptive updates. The system still maintains a high detection rate and a low false alarm rate, demonstrating good regional adaptability.

[0047] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for monitoring the condition of automobile exhaust, characterized in that, Includes the following steps: S1: Physical quantity sensor groups are arranged at at least two key monitoring points in the vehicle exhaust system. The key monitoring points include at least the intake end and the exhaust end of the three-way catalytic converter. The physical quantity sensor groups include at least a first type of sensor for monitoring gas concentration and a second type of sensor for monitoring temperature. The first type of sensor in the physical quantity sensor group is a wide-range oxygen sensor, which is arranged at the inlet and outlet of the three-way catalytic converter to monitor the oxygen concentration in the exhaust gas. The second type of sensor is a thermocouple temperature sensor, which is also arranged at the intake and exhaust ends of the three-way catalytic converter to monitor the exhaust temperature. S2: The signal from the physical quantity sensor group is received in real time through a local vehicle-mounted processing unit. The vehicle-mounted processing unit has a pre-stored reference parameter range under normal operating conditions of the exhaust system corresponding to the vehicle model. The reference parameter range includes the gas concentration reference range and temperature reference range of each monitoring point. The reference parameter range includes the normal fluctuation range of oxygen concentration at the intake end of the three-way catalytic converter, the stable low value range of oxygen concentration at the outlet end, the engine load correlation range of the intake end temperature, and the reasonable temperature difference range between the outlet end temperature and the intake end temperature. S3: The vehicle-mounted processing unit will directly compare the gas concentration signal and temperature signal received in real time from each monitoring point with the pre-stored gas concentration reference range and temperature reference range of the corresponding monitoring point. S4: When the real-time gas concentration value of any monitoring point continuously exceeds its corresponding gas concentration reference range for a first preset time, and / or when the real-time temperature value of any monitoring point continuously exceeds its corresponding temperature reference range for a second preset time, the vehicle-mounted processing unit immediately generates a preliminary abnormal signal. S5: The vehicle processing unit is further provided with a status logic judgment module. This module receives the preliminary abnormal signal and simultaneously acquires the real-time engine operating status parameters sent by the engine control unit through the vehicle controller local area network bus. The real-time engine operating status parameters include at least engine speed and load. S6: The state logic judgment module is based on a set of predefined fault-state mapping relationships. It combines the monitoring point location and abnormal physical quantity type corresponding to the preliminary abnormal signal with the engine real-time operating status parameters for logical judgment. The fault-state mapping relationship defines the correspondence between different monitoring point combination abnormal modes and specific exhaust system component faults or engine operating status abnormalities. The combinational logic judgment performed by the state logic judgment module includes: When the real-time oxygen concentration at the outlet of the three-way catalytic converter is continuously higher than its stable low value range, and the real-time temperature difference between the inlet and outlet is continuously lower than the lower limit of the reasonable temperature difference range, the three-way catalytic converter is determined to have insufficient conversion efficiency, regardless of the engine's operating state, and the corresponding component fault code is output. When the real-time oxygen concentration value at the intake end of the three-way catalytic converter is detected to continuously exceed its normal fluctuation range, accompanied by non-command fluctuations in engine speed under steady-state conditions, it is first determined that the upstream air-fuel ratio control related sensors or actuators are abnormal, and the corresponding component fault identification code is output. S7: If the result of the combined logic judgment points to a potential fault or performance degradation of a specific component in the exhaust system, the state logic judgment module outputs a specific component fault identification code. S8: The vehicle processing unit drives the vehicle human-machine interface to provide graded visual and auditory warnings based on the received component fault identification code. At the same time, it stores a diagnostic data frame containing the component fault identification code and the corresponding timestamp through the vehicle's built-in diagnostic communication interface, making it readable by external standard diagnostic equipment. The method further includes a baseline parameter adaptive update step S9 after step S8: S9.1: When the vehicle is determined to be in a stable and normal driving condition, the on-board processing unit continuously records the physical quantity data of each monitoring point to form a historical normal data set. S9.2: When the amount of data accumulated in the historical normal data set reaches a preset threshold, the vehicle processing unit determines the central tendency range and discrete fluctuation range of the values ​​of each physical quantity data in the set. S9.3: Compare the determined central tendency range and discrete fluctuation range with the currently stored benchmark parameter range; S9.4: If the deviation between the determined central tendency range and discrete fluctuation range and the current benchmark parameter range exceeds a preset adaptation threshold, the boundary values ​​of the benchmark parameter range are updated based on the central tendency range and discrete fluctuation range.

2. The method for monitoring the exhaust status of an automobile according to claim 1, characterized in that, The method further includes a sensor self-calibration step S0 after step S1 and before step S2: S0: Each time the vehicle is started, the on-board processing unit controls a standard gas release device integrated in the exhaust pipe to release a standard gas of known concentration to a designated calibration point; a physical quantity sensor arranged at the calibration point measures the standard gas; the on-board processing unit compares the measured value with the known concentration value of the standard gas, and if the deviation exceeds the allowable tolerance range, it determines that the sensor reading is unreliable and generates a sensor calibration failure flag; In the subsequent step S6, the state logic judgment module will ignore the data from the sensor or assign a lower confidence weight to its data.

3. The method for monitoring the exhaust status of an automobile according to claim 1, characterized in that, The determination of the first preset duration and the second preset duration in step S4 includes the following sub-steps: S4.1: The on-board processing unit pre-stores a duration-operating condition mapping table, which defines different duration combinations corresponding to different engine speeds and load ranges; S4.2: During the monitoring process, the on-board processing unit acquires the current engine speed and load in real time; S4.3: Based on the current engine speed and load, query the duration-condition mapping table, dynamically determine and apply the corresponding first preset duration and second preset duration.

4. The method for monitoring the exhaust status of an automobile according to claim 1, characterized in that, The graded visual and auditory warnings in step S8 are specifically as follows: When the fault code of the component indicates a fault level of Level 1, which means a fault that does not affect short-term driving safety but needs to be repaired as soon as possible, a yellow indicator light will flash and an intermittent single tone will be triggered. When the fault code of the component indicates a fault level of level two, which may lead to excessive emissions or component damage, a yellow indicator light will be constantly lit and a continuous single tone will be triggered. When the fault code of the component indicates a fault level of three, which may lead to serious emissions exceeding standards or safety hazards, a red indicator light will remain on and a rapid beeping sound will be triggered as a warning.

5. A vehicle exhaust condition monitoring system, used to implement the method as described in any one of claims 1-4, characterized in that, The system includes: A sensor module for performing step S1 includes a physical quantity sensor group arranged at at least two key monitoring points of the vehicle exhaust system, the physical quantity sensor group including at least a first type of sensor for monitoring gas concentration and a second type of sensor for monitoring temperature; A local vehicle-mounted processing module, electrically connected to the sensor module, is used to execute steps S2 to S9. The local vehicle-mounted processing module includes: The signal conditioning unit is used to amplify and convert sensor signals from analog to digital. The data storage unit pre-stores the reference parameter range of the exhaust system under normal operating conditions corresponding to the vehicle model; The real-time comparison unit is used to execute steps S3 and S4, compare the converted sensor data with the reference parameter range in real time, and generate a preliminary abnormal signal. The state logic judgment unit is used to execute steps S5, S6 and S7. It has a pre-stored fault-state mapping relationship and is used to perform combined logic judgment based on the preliminary abnormal signal and the real-time operating status parameters of the engine, and output the component fault identification code. The parameter adaptive unit is used to execute step S9, which determines the central tendency range and discrete fluctuation range of the physical quantity data based on the historical normal data set, and updates the reference parameter range accordingly. The vehicle bus interface module is used to obtain real-time engine operating status parameters from the vehicle controller area network bus. The human-machine interaction module is connected to the local vehicle-mounted processing module and is used to execute the graded warning in step S8. The diagnostic communication interface module is connected to the local vehicle-mounted processing module and is used to perform diagnostic data frame output and storage in step S8.

6. The automotive exhaust condition monitoring system according to claim 5, characterized in that, The system also includes a standard gas self-calibration module integrated on the exhaust pipe for performing step S0. This module includes: A gas cylinder containing a standard gas of known concentration; A solenoid valve controlled by the local on-board processing module is used to control the release of standard gas; A dedicated calibration chamber in which the sensing portion of at least one sensor in the physical quantity sensor group is exposed for measuring the released standard gas when the solenoid valve is opened.

7. The automotive exhaust condition monitoring system according to claim 5, characterized in that, When performing step S4, the real-time comparison unit is configured to: access the duration-operating condition mapping table pre-stored in the data storage unit, and query and determine the first preset duration and the second preset duration to be used based on the real-time engine speed and load obtained by the vehicle bus interface module.

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