A catalytic converter information processing method, device, medium, diagnostic instrument and controller

Abstract

Embodiments of the present application disclose a catalytic converter information processing method, device, medium, diagnostic instrument and controller; by transmitting catalytic converter sample data of a preset scale to a processing unit or cloud, in combination with a data mining process, the life of the catalytic converter is predicted and intervened; wherein a number of deterioration curves obtained by a data fitting method can be compared with real-time catalytic converter data to obtain corresponding life prediction information, and through analysis of abnormal deterioration curves and correlation evaluation of causes, fault detection and elimination prompt information of the catalytic converter can be obtained; by introducing the method and product of the present application, the efficiency of vehicle durability testing can be improved, the quality of vehicle maintenance can be improved, and valuable reference data for the use of the catalytic converter can be provided; and then the catalytic converter deterioration process is warned, and the failure processing state of the deteriorated catalytic converter on the tail gas is avoided; by introducing known big data analysis algorithms, the analysis of the catalytic converter aging speed and intervention factors is more accurate and effective.

Description

Technical Field

[0001] This invention belongs to the field of fault diagnosis technology, and in particular relates to a catalyst information processing method, device, medium, diagnostic instrument and controller. Background Technology

[0002] Vehicle exhaust pollution poses a significant threat to the human living environment, hence the continuous development of vehicle exhaust purification technology. Among these technologies, the installation of a three-way catalytic converter (TWC) in the exhaust pipe is one of the most important. Since the establishment of regulations in the field of on-board diagnostic (OBD) systems, there have been clear requirements for monitoring catalytic converter failures, and the standards have become increasingly stringent.

[0003] Because three-way catalytic converters (TWCs) operate in harsh environments for extended periods, their efficiency in purifying exhaust gases continuously declines, potentially leading to complete failure. If TWCs fail completely without intervention, it will severely impact the environment. Therefore, it is necessary to monitor the exhaust gas purification performance of TWCs in real time and implement early warning systems to prevent problems before they occur.

[0004] like Figure 1 The diagram shows the exhaust system structure in related technologies; however, it lacks a unit for real-time monitoring and prediction of catalytic converter lifespan. Furthermore, it lacks analytical methods for understanding the causes of catalytic converter failure. Vehicle manufacturers cannot obtain information about the lifespan of the vehicle's catalytic converter and the factors affecting it, potentially leading to a particular model always carrying an inherent defect, which is detrimental to product cycle iteration, user experience, and environmental issues. Summary of the Invention

[0005] This invention discloses a catalyst information processing method, including a first acquisition and transmission step and a second fitting and extraction step; wherein, the first acquisition and transmission step collects a first key index set of a target catalyst family; the target catalyst family includes a specified set of target catalysts intended for analysis or prediction of lifetime; in order to obtain reliable data for catalyst performance analysis or to make the fault determination of the catalyst sufficiently accurate, the target catalysts are not unique, and their number should be greater than a preset sample number threshold.

[0006] The target catalytic converter is used for exhaust treatment of different vehicles; a first key indicator set is a set of target parameters of the target catalytic converter; the target parameters include a remaining mileage parameter of different vehicles; and the detection information acquisition process is completed by transmitting the information of the first key indicator set to the first information processing unit and / or the cloud information processing unit; considering that the physical parameters of different vehicle models or different catalytic converters have many differences, the component models used by the analysis algorithm also have great differences, so they cannot be mixed in implementation; however, the scheme protected by the application can follow the same inventive concept for the treatment of different vehicle models or catalytic converters; in order to optimize the treatment effect, even if different vehicle models or different catalytic converters do not share the prediction information of the application, and each vehicle model or different catalytic converter of the same vehicle model corresponds to a set of analysis algorithms and / or controllers; however, the method or product that shares information of different vehicle models or different catalytic converters also falls within the scope of the technical scheme of the application.

[0007] On the other hand, the second fitting and extracting step fits a first relationship curve and / or a second relationship curve family of the oxygen storage capacity of the target catalytic converter and the cumulative mileage according to the information of the first key indicator set; and then the real-time oxygen storage capacity of the catalytic converter to be evaluated is obtained, and compared with the preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family, to obtain the remaining mileage life prediction value of the catalytic converter to be evaluated.

[0008] Further, the first acquisition and transmission step further obtains a first data stream of failure analysis; the first data stream is composed of intervention information affecting the service life of the catalytic converter; including environmental related parameters, catalytic converter hardware related parameters, thermal failure related parameters and / or catalyst poisoning related parameters; and then the first data stream is transmitted to the first information processing unit and / or the cloud information processing unit for further data processing.

[0009] The second fitting and extracting step comprehensively obtains the information of the first data stream and the preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family, to obtain a correlation coefficient between the intervention information and the aging speed of the target catalytic converter; the degradation curve is used to represent the relationship between the cumulative mileage of the vehicle and the oxygen storage performance or the oxygen storage capacity.

[0010] Specifically, the degradation curve can be an exponentially weighted moving average (EWMA) degradation curve, or a degradation curve based on mean value degradation and extreme value; or a rapid degradation curve and / or a sudden degradation curve.

[0011] Further, if the aging speed of the target catalytic converter is greater than a preset aging speed threshold, the intervention information corresponding to the correlation coefficient is output, prompting the relevant troubleshooting operation.

[0012] Specifically, the first key indicator set information can be filled by the driving mileage information and / or the oxygen storage amount information given by the engine management system EMS; further, the correlation coefficient between the deterioration factors and the aging speed of the target catalyst is obtained through a preset data analysis or feature extraction process; the data analysis or feature extraction process can be realized by using an existing data analysis method, and the data analysis method herein can be a multi-factor analysis method and / or a random forest method.

[0013] Further, the catalysts of the target catalyst family can be divided into a first group of catalysts and a second group of catalysts; the first group of catalysts is used on a preset endurance test vehicle or a test vehicle queue and is used for the collection of a first group of data; the second group of catalysts is used on a known vehicle queue and is used for the collection of a second group of data; wherein the known vehicle queue includes vehicles that have been in road driving or other operating states.

[0014] Further, the method of the present application can further include a third discrimination and output step; the first key indicator set is updated by predicting the remaining mileage of the preset or designated catalyst in real time and transmitting the remaining mileage information to a preset location.

[0015] Specifically, if the oxygen storage amount of the target catalyst is less than a first oxygen storage amount threshold, an alarm processing or a prompt that the target catalyst is close to failure is performed; otherwise, the first collection and transmission step is continued to be executed.

[0016] Further, the method of the present application can further include a fourth iteration and refreshing step; the first relationship curve can be continuously optimized by the information in the second group of catalysts or iteratively optimized by refreshing the distribution data obtained by the first collection and transmission step; wherein the distribution data can be the remaining mileage data.

[0017] Specifically, the remaining mileage or life parameter set of the target catalyst can be obtained by obtaining the oxygen storage amount information of the target catalyst in real time; wherein the first collection and transmission step can perform data transmission through the Internet of Vehicles, the Internet or a preset communication link.

[0018] Correspondingly, the embodiment of the present application also discloses an information processing device, which comprises a first collection and transmission unit and a second fitting and extraction unit; wherein the first collection and transmission unit collects a first key indicator set of a target catalyst family; the target catalyst family includes a target catalyst used to analyze or predict a designated set of life; the target catalyst is not unique and the number is greater than a preset sample number threshold; the target catalyst is used for exhaust treatment of different vehicles.

[0019] The first key indicator set is a set of target parameters of the target catalytic converter. The target parameters include a remaining mileage parameter of different vehicles. Information of the first key indicator set is transmitted to a first information processing unit and / or a cloud information processing unit. The second fitting and extraction unit fits a first relationship curve and / or a second relationship curve family of the oxygen storage capacity of the target catalytic converter and the cumulative mileage according to the information of the first key indicator set. If the real-time oxygen storage capacity of the catalytic converter to be evaluated is obtained and compared with the preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family, the remaining mileage life prediction value of the catalytic converter to be evaluated can be obtained.

[0020] Further, the first acquisition and transmission unit can also obtain a first data stream of failure analysis. The first data stream is composed of intervention information affecting the service life of the catalytic converter. It includes environmental related parameters, catalytic converter hardware related parameters, thermal failure related parameters and / or catalyst poisoning related parameters. Then, the first data stream is transmitted to the first information processing unit and / or the cloud information processing unit.

[0021] The second fitting and extraction unit obtains a correlation coefficient between the intervention information and the aging speed of the target catalytic converter by comprehensively fitting the information of the first data stream with the preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family. The degradation curve is used to represent the relationship between the cumulative mileage of the vehicle and the oxygen storage performance or the oxygen storage capacity.

[0022] Specifically, the degradation curve includes an EWMA degradation curve, a mean degradation curve, a maximum degradation curve, a rapid degradation curve and / or a burst degradation curve. If the aging speed of the target catalytic converter is greater than the preset aging speed threshold, the intervention information corresponding to the correlation coefficient is output, and the relevant troubleshooting operation is prompted.

[0023] The first key indicator set information can be filled with the mileage information and / or oxygen storage capacity information given by the engine management system (EMS). The correlation coefficient between the degradation factors and the aging speed of the target catalytic converter is obtained through a preset data analysis or feature extraction process. The data analysis or feature extraction process can be realized by using existing data analysis methods, which can be multi-factor analysis method, random forest and similar methods.

[0024] Further, the catalytic converters of the target catalytic converter family can be divided into a first group of catalytic converters and a second group of catalytic converters. The first group of catalytic converters is used on a preset durability test vehicle or a test vehicle queue and is used for the collection of the first group of data. The second group of catalytic converters is used on a known vehicle queue and is used for the collection of the second group of data. The known vehicle queue can be a vehicle that has been in road driving or other operating state.

[0025] Further, the device can further comprise a third discrimination and output unit; for predicting the remaining mileage of the preset or designated catalytic converter in real time, and transmitting the remaining mileage information to a preset location for updating the first set of key indicators; if the oxygen storage capacity of the target catalytic converter is less than the first oxygen storage threshold, an alarm processing or a prompt that the target catalytic converter is close to failure is performed; otherwise, the operation or processing process of the first collection and transmission unit is continued to be executed.

[0026] In addition, the device can further comprise a fourth iteration and refreshing unit; so that the first relationship curve thereof can be continuously optimized by the information in the second group of catalytic converters or iteratively optimized by refreshing the information of the first collection and transmission unit to obtain new distribution data; the distribution data thereof includes the remaining mileage data; the remaining mileage or life parameter set of the target catalytic converter is obtained by obtaining the oxygen storage capacity information of the target catalytic converter in real time; wherein the first collection and transmission unit can transmit data through the Internet of Vehicles, the Internet or a preset communication link.

[0027] In addition, the embodiments of the present application also disclose a computer storage medium adopting the same inventive concept, comprising a storage medium body for storing a computer program; the computer program can realize any catalytic converter information processing method as above when executed by a microprocessor; similarly, a diagnostic device and a controller are also disclosed, which can adopt any information processing device as above; and / or any computer storage medium as above; wherein the controller is integrated in an exhaust disposal unit or an exhaust catalytic component of a vehicle.

[0028] In summary, the method and product disclosed by the embodiments of the present application can predict and intervene the life of the catalytic converter by transmitting the sample data of the catalytic converter of a preset scale to the processing unit or the cloud and combining the data mining process; wherein the corresponding life prediction information can be obtained by comparing the several deterioration curves obtained by the data fitting method with the real-time catalytic converter data; the failure detection and elimination prompt information of the catalytic converter can be obtained by analyzing the abnormal deterioration curve and evaluating the correlation of the causes; by introducing the method and product of the present application, the efficiency of vehicle durability testing can be improved, the vehicle maintenance quality can be improved, and valuable reference data for the use of the catalytic converter can be provided; further, the deterioration process of the catalytic converter can be warned, and the failure processing state of the deteriorated catalytic converter on the exhaust gas can be avoided; by introducing the known big data analysis algorithm, the analysis of the aging speed and intervention factors of the catalytic converter is more accurate and effective.

[0029] It should be noted that the "first", "second" and similar terms used in the present text are only used to describe the elements in the technical solutions, and do not constitute a limitation on the technical solutions, nor can they be understood as an indication or implication of the importance of the corresponding elements; the elements with "first", "second" and similar terms indicate that at least one element is included in the corresponding technical solution. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to make the technical solutions of the present application clearer, and to facilitate further understanding of the technical effects, technical features and purposes of the present application, the present application will be described in detail below in conjunction with the drawings, which constitute an essential part of the description and together with the embodiments of the present application serve to illustrate the technical solutions of the present application, but do not constitute a limitation on the present application.

[0031] The same reference numerals in the drawings represent the same components.

[0032] Specifically:

[0033] Figure 1 Exhaust system structure in the related art.

[0034] Figure 2 Deterioration curve of the catalytic converter with the driving mileage in the embodiment of the present application.

[0035] Figure 3 Catalytic converter information processing flow one in the embodiment of the present application.

[0036] Figure 4 Catalytic converter information processing flow two in the embodiment of the present application.

[0037] Figure 5 Process schematic diagram of the method embodiment of the present application.

[0038] Figure 6 Schematic diagram of the component structure of the product embodiment of the present application.

[0039] Figure 7 Schematic diagram of the layout of the product embodiment of the present application Figure 1 .

[0040] Figure 8 Schematic diagram of the layout of the product embodiment of the present application Figure 2 .

[0041] Figure 9 Schematic diagram of the layout of the product embodiment of the present application Figure 3 .

[0042] Among them:

[0043] 100 - first collection and transmission step;

[0044] 101 - first group of catalytic converters;

[0045] 103 - second group of catalytic converters;

[0046] 110 - data collection step;

[0047] 119 - data synthesis step;

[0048] 120 - data transmission step;

[0049] 200 - second fitting and extraction step;

[0050] 210 - data fitting step;

[0051] 300 - third discrimination and output step;

[0052] 310 - implementation prediction step;

[0053] 320 - failure analysis step;

[0054] 330 - comprehensive analysis step;

[0055] 340 - anomaly extraction step;

[0056] 400 - fourth iteration and refresh step;

[0057] 410 - optimization iteration step;

[0058] 420 - data refresh step;

[0059] 500 - information processing device;

[0060] 510 - first acquisition and transmission unit;

[0061] 520 - second fitting and extraction unit;

[0062] 530 - third discrimination and output unit;

[0063] 540 - fourth iteration and refresh unit;

[0064] 555 - diagnostic device;

[0065] 600 - first data stream;

[0066] 700 - second data stream;

[0067] 801 - cumulative mileage (km);

[0068] 803 - oxygen storage amount (mg);

[0069] 810 - exponentially weighted moving average (EWMA) curve;

[0070] 820 - mean deterioration curve legend;

[0071] 830 - extreme value deterioration curve legend;

[0072] 840 - rapid deterioration curve legend;

[0073] 841 - rapid deterioration curve;

[0074] 850 - sudden deterioration curve legend;

[0075] 851 - burst degradation curve

[0076] 901 - controller

[0077] 900 - vehicle

[0078] 903 - computer storage medium

[0079] 960 - engine

[0080] 961 - three-way catalyst TWC

[0081] 963 - exhaust gas outlet

[0082] 965 - sensor 2

[0083] 967 - sensor 1 DETAILED DESCRIPTION

[0084] The application will be further described below in conjunction with the accompanying drawings and examples. Of course, the following specific examples described are only to explain the technical solutions of the application, but not to limit the application.

[0085] In addition, the parts expressed in the examples or the accompanying drawings are only examples of the relevant parts of the application, but not the whole of the application.

[0086] As shown in the catalytic converter information processing method, Figure 5 , Figure 7 , the catalytic converter information processing method comprises a first collection and transmission step 100 and a second fitting and extraction step 200; wherein the first collection and transmission step 100 collects a first key indicator set of a target catalytic converter family; the target catalytic converter family comprises target catalytic converters of a specified set to be used for analyzing or predicting the life; the target catalytic converters are not unique, and the number of target catalytic converters is greater than a preset sample number threshold; the target catalytic converters are used for exhaust treatment of different vehicles 900; the first key indicator set is a set of target parameters of the target catalytic converters; the target parameters comprise a remaining kilometer parameter of the different vehicles 900; and information of the first key indicator set is transmitted to a first information processing unit and / or a cloud information processing unit.

[0087] As shown in the second fitting and extraction step 200, Figure 2 and Figure 5 , the second fitting and extraction step 200 fits a first relationship curve and / or a second relationship curve family of the oxygen storage amount 803 and the cumulative mileage 801 of the target catalytic converter according to the information of the first key indicator set; obtains a real-time oxygen storage amount of a catalytic converter to be evaluated, and compares the real-time oxygen storage amount with a preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family to obtain a remaining mileage life prediction value of the catalytic converter to be evaluated.

[0088] Further, as shown in Figure 5 , Figure 7 , the first collection and transmission step 100 also acquires a first data stream 600 for failure analysis; the first data stream 600 is composed of intervention information affecting the service life of the catalyst; the first data stream 600 includes environment-related parameters, catalyst hardware-related parameters, thermal failure-related parameters, and / or catalyst poisoning-related parameters; the first data stream 600 is transmitted to the first information processing unit and / or the cloud information processing unit; the second fitting and extraction step 200 integrates the information of the first data stream 600 with the preset catalyst degradation curve in the first relationship curve and / or the second relationship curve family to obtain the correlation coefficient between the intervention information and the target catalyst aging speed; the degradation curve is used to represent the relationship between the cumulative mileage of the vehicle 900 and the oxygen storage performance or the oxygen storage amount.

[0089] Specifically, as shown in Figure 2 , the degradation curve includes an EWMA degradation curve, a mean degradation curve, a maximum degradation curve, a rapid degradation curve, and / or a burst degradation curve; if the aging speed of the target catalyst is greater than the preset aging speed threshold, the intervention information corresponding to the correlation coefficient is output, prompting the relevant troubleshooting operation.

[0090] Among them, the first key indicator set information can be filled by the driving mileage information and / or the oxygen storage amount information given by the engine management system EMS; the correlation coefficient between the degradation factors and the aging speed of the target catalyst is obtained through a preset data analysis or feature extraction process; the data analysis or feature extraction process is realized by using an existing data analysis method, and the data analysis method includes a multi-factor analysis method, a random forest method.

[0091] As shown in Figure 3 , Figure 4 , Figure 7 , the catalysts of the target catalyst family include a first group of catalysts 101 and a second group of catalysts 103; the first group of catalysts 101 is used on a preset endurance test vehicle or a test vehicle queue and is used for collection of the first group of data; the second group of catalysts 103 is used on a known vehicle queue and is used for collection of the second group of data; here, the known vehicle queue includes vehicles 900 that have been in road driving or other operating states.

[0092] Further, as shown in Figure 3 to Figure 5 , the embodiment also includes a third discrimination and output step 300; the remaining mileage of the preset or designated catalyst is predicted in real time, and the remaining mileage information is transmitted to a preset location for updating the first key indicator set; as shown in Figure 2 , if the oxygen storage amount 803 of the target catalyst is less than the first oxygen storage amount threshold, an alarm processing or a prompt that the target catalyst is close to failure is performed; otherwise, the first collection and transmission step 100 is continued to be executed.

[0093] Wherein, the embodiment further comprises a fourth iteration and refreshing step 400; the first relationship curve is continuously optimized by the information in the second set of catalytic converters or is iteratively optimized by refreshing the distribution data obtained by the first collection and transmission step 100; the distribution data thereof comprises residual mileage data; the residual mileage or life parameter set of the target catalytic converter is obtained by real-time acquisition of the oxygen storage amount information of the target catalytic converter; the first collection and transmission step 100 transmits data through vehicle networking, the Internet or a pre-set communication link.

[0094] As shown in Figure 6 , Figure 7 , an information processing device 500 is also disclosed, comprising a first collection and transmission unit 510 and a second fitting and extraction unit 520; wherein the first collection and transmission unit 510 collects a first key indicator set of a target catalytic converter family; the target catalytic converter family comprises a target catalytic converter used to analyze or predict a specified set of life; the target catalytic converter is not unique, and the number of target catalytic converters is greater than a pre-set sample number threshold; the target catalytic converter is used for exhaust treatment of different vehicles 900; the first key indicator set is a set of target parameters of the target catalytic converter; the target parameters include residual mileage parameters of different vehicles 900; the information of the first key indicator set is transmitted to the first information processing unit and / or the cloud information processing unit; the second fitting and extraction unit 520 fits the first relationship curve and / or the second relationship curve family of the oxygen storage amount 803 and the cumulative mileage 801 of the target catalytic converter according to the information of the first key indicator set; the real-time oxygen storage amount of the to-be-evaluated catalytic converter is obtained and compared with the pre-set catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family, to obtain the residual mileage life prediction value of the to-be-evaluated catalytic converter.

[0095] Wherein, the first collection and transmission unit 510 can also obtain a first data stream 600 for failure analysis; the first data stream 600 is composed of intervention information affecting the life of the catalytic converter; the first data stream 600 includes environmental related parameters, catalytic converter hardware related parameters, thermal failure related parameters and / or catalyst poisoning related parameters; the first data stream 600 is transmitted to the first information processing unit and / or the cloud information processing unit; the second fitting and extraction unit 520 combines the information of the first data stream 600 with the pre-set catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family, to obtain the correlation coefficient between the intervention information and the aging speed of the target catalytic converter; the degradation curve is used to represent the relationship between the cumulative mileage of the vehicle 900 and the oxygen storage performance or the oxygen storage amount.

[0096] Specifically, the degradation curve includes an EWMA degradation curve, a mean degradation curve, a maximum degradation curve, a rapid degradation curve and / or a burst degradation curve; if the aging speed of the target catalytic converter is greater than a pre-set aging speed threshold, the intervention information corresponding to the correlation coefficient is output, prompting the relevant troubleshooting operation.

[0097] The first key indicator set information includes driving mileage information and / or oxygen storage amount information given by an engine management system (EMS), and a correlation coefficient between a deterioration factor and an aging speed of the target catalyst is obtained through a preset data analysis or feature extraction process; the data analysis or feature extraction process is implemented using an existing data analysis method, which can be a multi-factor analysis method and / or a random forest method.

[0098] As shown in Figure 3 , Figure 4 , Figure 7 The target catalyst family can be the first group of catalysts 101 or the second group of catalysts 103; the first group of catalysts 101 is used on a preset endurance test vehicle or a test vehicle queue and is used for collection of the first group of data; the second group of catalysts 103 is used on a known vehicle queue and is used for collection of the second group of data; here, the known vehicle queue can be a vehicle 900 in a road driving or other operating state.

[0099] Further, as shown in Figure 2 , Figure 6 The device can further include a third discrimination and output unit 530; the remaining mileage of a preset or designated catalyst is predicted in real time, and the remaining mileage information is transmitted to a preset location for updating the first key indicator set; if the oxygen storage amount 803 of the target catalyst is less than the first oxygen storage amount threshold, an alarm processing or a prompt that the target catalyst is close to failure is performed; otherwise, the operation or processing process of the first collection and transmission unit 510 is continued.

[0100] On the other hand, the information processing device 500 can further include a fourth iteration and refreshing unit 540; the first relationship curve is continuously optimized by information in the second group of catalysts or is iteratively optimized by refreshing the information of the first collection and transmission unit 510 to obtain new distribution data; the distribution data includes remaining mileage data; the remaining mileage or life parameter set of the target catalyst is obtained by real-time acquisition of the oxygen storage amount information of the target catalyst; the first collection and transmission unit 510 transmits data through vehicle networking, the Internet or a preset communication link.

[0101] As described above, to overcome the deficiencies of the prior art, the present application discloses a catalyst information processing method through embodiments, and the basic principle is: uploading key indicator parameters (such as catalyst oxygen storage amount) representing catalyst performance to the cloud, obtaining the maximum value, mean value and exponentially weighted moving average (EWMA) of the oxygen storage amount of a single vehicle and multiple vehicles at different driving mileages, and then obtaining multiple deterioration curves.

[0102] As shown in Figure 2 According to the cloud data, the deterioration curve of the catalyst with the number of kilometers can be obtained, and the deterioration curves of multiple vehicles can be obtained in the same way. According to the EWMA deterioration curve or other deterioration curves of the vehicle, the complete life cycle of the catalyst equipped in the vehicle can be known, and the complete life cycle of the catalyst (from aging to critical cumulative mileage) is continuously optimized according to a large amount of cloud data. The obtained complete life cycle is used as a reference, that is, the relationship between the catalyst oxygen storage capacity and the cumulative mileage is established. When the real-time oxygen storage capacity of the catalyst is known, the remaining mileage life of the catalyst can be calculated in real time.

[0103] In addition, if it is identified that some vehicles on the market have a rapid deterioration or sudden deterioration of the catalyst, the possible causes of the failure can be inferred according to the performance characteristics of the deterioration, and then the key deterioration factor analysis can be performed.

[0104] Among them, the TWC of the durability vehicle and a large number of vehicles sold on the market will be continuously aged in the normal use process. Some possible influencing factors in the use process can be uploaded to the cloud. For example, the factors of thermal failure are considered: catalyst temperature, misfire related information, mixture lambda information, driving behavior related information, etc.; the factors of poisoning failure are also considered: refueling information, maintenance information, etc.; in addition, the catalyst itself factor information is also considered: production batch information, repair and replacement record information, etc.; other environment related information, regional information, etc. can also be used for the comprehensive analysis of the above data.

[0105] Further, the collected cloud data is calculated by a variety of big data analysis algorithms (such as multi-factor analysis method, random forest, etc.) to calculate the correlation coefficient between each possible factor affecting the deterioration of the catalyst and the aging speed of the catalyst, which can improve the accuracy of the catalyst life prediction.

[0106] At the same time, when the aging speed of the catalyst is found to be faster, the possible key influencing factors can be quickly found out to provide better and faster guidance for after-sales maintenance, and better after-sales service experience is provided for the vehicle owner.

[0107] The catalyst life curve fitted by the embodiment of the present application can be used to improve the durability test of the vehicle, identify the risk and influencing factors in advance; a large amount of cloud data can be used to improve the use state of the catalyst of the currently sold vehicle, and the vehicle maintenance efficiency can be improved accordingly; when the method of the present application is used to quickly lock the catalyst failure, the fault detection capability of the vehicle can also be improved, and better maintenance guidance can be provided for after-sales; in addition, through early warning of the catalyst deterioration process, it is more beneficial to avoid vehicle exhaust pollution and timely replace related parts.

[0108] The methods and processes that use any existing data analysis algorithms to process the factors affecting catalyst degradation are all within the scope of protection of this invention; the methods that use the discrimination method of this invention to analyze the influence of other factors on catalyst degradation are also within the scope of protection of this invention.

[0109] In addition, such as Figure 7 to Figure 9 The computer storage medium 903 shown includes a storage medium body for storing computer programs; when the computer program is executed by a microprocessor, it can implement any of the catalyst information processing methods described above.

[0110] Similarly, such as Figure 7 to Figure 9 The diagnostic device 555 or controller 901 respectively includes any of the above information processing devices 500 and / or any computer storage medium 903; wherein the information processing device 500 and / or computer storage medium 903 are integrated into the exhaust gas treatment unit or exhaust gas catalytic component of the vehicle 900.

[0111] It should be noted that the above embodiments are only for more clearly illustrating the technical solution of the present invention. Those skilled in the art will understand that the implementation of the present invention is not limited to the above content. Any obvious changes, substitutions or replacements made based on the above content do not exceed the scope of the technical solution of the present invention. Other implementations will also fall within the scope of the present invention without departing from the concept of the present invention.

Claims

1. A catalytic converter information processing method characterized by comprising: The method comprises a first collection and transmission step (100) and a second fitting and extraction step (200). The first collection and transmission step (100) collects a first set of key indicators of a target catalytic converter family. The target catalytic converter family comprises target catalytic converters of a specified set to be used for analyzing or predicting the service life. The target catalytic converters are not unique, and the number of target catalytic converters is greater than a preset sample number threshold. The target catalytic converters are used for exhaust treatment of different vehicles (900). The first set of key indicators is a set of target parameters of the target catalytic converters. The target parameters include a remaining mileage parameter of different vehicles (900). The information of the first set of key indicators is transmitted to a first information processing unit and / or a cloud information processing unit. The second fitting and extraction step (200) fits a first relationship curve and / or a second relationship curve family of the oxygen storage capacity (803) and the cumulative mileage (801) of the target catalytic converter according to the information of the first set of key indicators. The real-time oxygen storage capacity of a catalytic converter to be evaluated is obtained and compared with a preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family to obtain a remaining mileage life prediction value of the catalytic converter to be evaluated.

2. The catalytic converter information processing method of claim 1, wherein: The first collection and transmission step (100) further obtains a first data stream (600) for failure analysis. The first data stream (600) is composed of intervention information affecting the service life of the catalytic converter. The first data stream (600) includes environmental related parameters, catalytic converter hardware related parameters, thermal failure related parameters, and / or catalyst poisoning related parameters. The first data stream (600) is transmitted to the first information processing unit and / or the cloud information processing unit. The second fitting and extraction step (200) combines the information of the first data stream (600) with the preset catalytic converter degradation curve in the first relationship curve and / or the second relationship curve family to obtain a correlation coefficient between the intervention information and the aging speed of the target catalytic converter. The degradation curve is used to represent the relationship between the cumulative mileage of the vehicle (900) and the oxygen storage performance or the oxygen storage capacity.

3. The catalytic converter information processing method of claim 2, wherein: The degradation curve comprises an EWMA degradation curve, a mean degradation curve, a maximum degradation curve, a rapid degradation curve, and / or a burst degradation curve. If the aging speed of the target catalytic converter is greater than a preset aging speed threshold, the intervention information corresponding to the correlation coefficient is output to prompt relevant troubleshooting operations.

4. The catalytic converter information processing method according to claim 1, 2 or 3, wherein: The first set of key indicator information includes mileage information and / or oxygen storage capacity information provided by an engine management system (EMS). The correlation coefficient between the degradation factors and the aging speed of the target catalytic converter is obtained through a preset data analysis or feature extraction process. The data analysis or feature extraction process is realized by using an existing data analysis method, and the data analysis method includes a multi-factor analysis method and a random forest method.

5. The catalytic converter information processing method of claim 4, wherein: The target catalyst family includes a first group of catalysts (101) and a second group of catalysts (103). The first group of catalysts (101) is used on a preset endurance test vehicle or a test vehicle fleet and is used for the collection of a first set of data. The second group of catalysts (103) is used on a known vehicle fleet and is used for the collection of a second set of data. The known vehicle fleet includes vehicles (900) that have been in road driving or other operating conditions.

6. The catalyst information processing method of claim 5, further comprising a third judging and outputting step (300); real-time prediction of the remaining mileage of a preset or designated catalyst, and transmission of the remaining mileage information to a preset location for updating the first set of key indicators; If the oxygen storage amount (803) of the target catalyst is less than a first oxygen storage amount threshold, an alarm processing or a prompt is performed that the target catalyst is close to failure; otherwise, the first collection and transmission step (100) is continuously executed.

7. The catalyst information processing method of claim 6, further comprising a fourth iteration and refreshing step (400); the first relationship curve is continuously optimized by information in the second group of catalysts or iteratively optimized by refreshing the distribution data obtained by the first collection and transmission step (100); the distribution data includes remaining mileage data; By real-time acquisition of the oxygen storage amount information of the target catalyst, a set of remaining mileage or life parameters of the target catalyst is obtained; the first collection and transmission step (100) transmits data through the Internet of Vehicles, the Internet, or a preset communication link.

8. An information processing apparatus (500) comprising a first acquisition and transmission unit (510), a second fitting and extraction unit (520); wherein, The first collection and transmission unit (510) collects a first set of key indicators of a target catalyst family; the target catalyst family includes target catalysts intended to be used to analyze or predict the life of a designated set; the target catalysts are not unique, and the number of target catalysts is greater than a preset sample number threshold; the target catalysts are used for exhaust treatment of different vehicles (900); the first set of key indicators is a set of target parameters of the target catalysts; the target parameters include remaining mileage parameters of different vehicles (900); information of the first set of key indicators is transmitted to a first information processing unit and / or a cloud information processing unit; the second fitting and extraction unit (520) fits a first relationship curve of the oxygen storage amount (803) and the cumulative mileage (801) of the target catalyst and / or a second relationship curve family according to the information of the first set of key indicators; the real-time oxygen storage amount of a catalyst to be evaluated is obtained and compared with a preset catalyst degradation curve in the first relationship curve and / or the second relationship curve family to obtain a remaining mileage life prediction value of the catalyst to be evaluated.

9. The information processing apparatus (500) of claim 8, wherein: The first acquisition and transmission unit (510) also acquires a first data stream (600) for failure analysis; the first data stream (600) is composed of intervention information affecting the service life of the catalyst; the first data stream (600) includes environmental related parameters, catalyst hardware related parameters, thermal failure related parameters and / or catalyst poisoning related parameters; the first data stream (600) is transmitted to the first information processing unit and / or the cloud information processing unit; the second fitting and extraction unit (520) integrates the information of the first data stream (600) and the preset catalyst degradation curve in the first relationship curve and / or the second relationship curve family to obtain the correlation coefficient between the intervention information and the target catalyst aging speed; the degradation curve is used to represent the relationship between the cumulative mileage of the vehicle (900) and the oxygen storage performance or the oxygen storage amount.

10. The information processing apparatus (500) of claim 9, wherein: The degradation curve includes an EWMA degradation curve, a mean degradation curve, a maximum degradation curve, a rapid degradation curve and / or a burst degradation curve; if the aging speed of the target catalyst is greater than a preset aging speed threshold, the intervention information corresponding to the correlation coefficient is output, prompting the relevant troubleshooting operation.

11. The information processing apparatus (500) of claim 8, 9 or 10, wherein: The first key indicator set information includes the driving mileage information and / or the oxygen storage amount information given by the engine management system (EMS); the correlation coefficient between the degradation factors and the aging speed of the target catalyst is obtained through a preset data analysis or feature extraction process; the data analysis or feature extraction process is realized by using an existing data analysis method, and the data analysis method includes a multi-factor analysis method, a random forest method.

12. The information processing apparatus (500) according to claim 11, wherein: The catalysts of the target catalyst family include a first group of catalysts (101) and a second group of catalysts (103); the first group of catalysts (101) are used on a preset endurance test vehicle or a test vehicle queue and are used for acquisition of a first group of data; the second group of catalysts (103) are used on a known vehicle queue and are used for acquisition of a second group of data; the known vehicle queue includes vehicles (900) that have been in road driving or other operating states.

13. The information processing device (500) of claim 12, further comprising a third discrimination and output unit (530); the remaining mileage of a preset or designated catalyst is predicted in real time, and the remaining mileage information is transmitted to a preset position for updating the first key indicator set; if the oxygen storage amount (803) of the target catalyst is less than a first oxygen storage amount threshold, an alarm processing or a prompt that the target catalyst is close to failure is performed; otherwise, the operation or processing process of the first acquisition and transmission unit (510) is continued.

14. The information processing device (500) of claim 13, further comprising a fourth iteration and refresh unit (540); the first relationship curve is constantly optimized by information in the second set of catalytic converters or iteratively optimized by refreshing information of the first acquisition and transmission unit (510) to obtain new distribution data; the distribution data comprises residual mileage data; by obtaining oxygen storage amount information of a target catalytic converter in real time, a set of residual mileage or life parameters of the target catalytic converter is obtained; the first acquisition and transmission unit (510) transmits data through vehicle networking, the Internet or a preset communication link.

15. A computer storage medium (903) comprising a storage medium body for storing a computer program; the computer program, when executed by a microprocessor, implements the catalytic converter information processing method of any one of claims 1 to 7.

16. A diagnostic device (555) comprising the information processing device (500) of any one of claims 8 to 14; and / or the computer storage medium (903) of any one of claim 15.

17. A controller (901) comprising the information processing device (500) of any one of claims 8 to 14; and / or the computer storage medium (903) of any one of claim 15; the information processing device (500) and / or the computer storage medium (903) are integrated into an exhaust gas disposal unit or an exhaust gas catalytic component of a vehicle (900).

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