Egr high flow fault diagnosis method and device

Abstract

The application discloses an EGR high-flow fault diagnosis method and device, which is used for diagnosing a fault that the actual flow of circulating exhaust gas is always higher than the target flow due to EGR valve body gas leakage, and comprises the following steps: obtaining P1 motor parameters in the engine operation process; calculating the P1 motor actual torque Tq real based on the P1 motor parameters; calculating the torque deviation ΔTq and the gas leakage amount self-learning value La based on the P1 motor actual torque Tq real ; judging whether there is a high-flow fault, if the torque deviation ΔTq is greater than or equal to the first threshold value and the gas leakage amount self-learning value La is greater than or equal to the second threshold value, there is a high-flow fault, otherwise, there is no high-flow fault. The application can diagnose whether there is an EGR high-flow fault without relying on the EGR temperature sensor by comparing the average deviation of the actual torque and the model torque with the set threshold value and combining the engine gas leakage amount self-learning, and solves the problem that the fault cannot be accurately reported due to the unobvious EGR temperature rise when the EGR high-flow fault is diagnosed based on the temperature rise of the EGR temperature sensor.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a method and apparatus for diagnosing high-flow EGR faults. Background Technology

[0002] Under the guidance of national policies, hybrid technology has become one of the mainstream development routes in the current automotive landscape. Compared with traditional fuel vehicles, in order to create a more energy-efficient hybrid system, a dedicated hybrid engine has been developed, employing new engine technologies such as the Atkinson cycle, high compression ratio, and Exhaust Gas Recirculation (EGR). The China VI emission standard requires that for vehicles equipped with EGR systems, the on-board diagnostic (OBD) system must monitor for faults such as excessively low or high EGR flow. The OBD system should detect the fault before the EGR flow exceeds or falls below the manufacturer's specified flow, causing the vehicle's emissions to exceed the corresponding OBD threshold.

[0003] Excessive EGR flow mainly manifests in two ways: First, the EGR valve is stuck in a certain open position. In this case, the EGR valve cannot close, resulting in high flow. The EMS system will report a valve-related control fault and alert the user by illuminating the MILM indicator. Second, there is valve leakage, causing the actual flow to consistently exceed the target flow. For the second type of fault, current diagnostics primarily use the temperature rise method. The diagnostic principle is as follows: For a fault-free EGR system, if the EGR valve is not open after engine start, the EGR inlet temperature will not rise significantly within a certain time. For a system with a high flow fault (valve leakage), exhaust gas can still enter the intake manifold through the EGR valve even without a target flow requirement, causing the EGR inlet temperature to rise. The specific diagnostic method involves enabling the diagnostic, recording the initial EGR inlet temperature, and integrating the deviation between the EGR inlet temperature and its initial sampling temperature with the EGR valve closed. After a certain period, the average of the integrated temperature deviation is calculated. When the average temperature rise exceeds the calibrated threshold, an EGR high flow fault is reported.

[0004] The shortcomings of the EGR high flow diagnosis method based on the temperature rise of the EGR temperature sensor for the above-mentioned high flow faults are: (1) Hybrid vehicles equipped with EGR are basically cooled EGRs, which are cooled through the battery cooling circuit. The EGR cooling intensity is relatively large. During the high flow diagnosis time after the engine starts, the EGR temperature rise is not obvious, resulting in little distinction between the temperature rise of faulty parts and normal parts; (2) Hybrid vehicles are now basically equipped with electronic water pumps. The operating conditions of the electronic water pump are related to the vehicle driving conditions. When the electronic water pump speed is high, the EGR cooling intensity increases, and the temperature rise of the EGR temperature sensor weakens. Therefore, under extreme conditions, it is impossible to obtain an accurate temperature rise to describe the EGR high flow fault; (3) In order to take into account NVH performance, the catalyst heating speed is set to high, medium and low according to the operating conditions. Under low operating conditions, the EGR temperature rise is small, which makes it impossible to accurately report the fault. Summary of the Invention

[0005] To address the shortcomings of the prior art, the technical problem to be solved by the present invention is to provide a method and apparatus for diagnosing EGR high flow faults in hybrid power systems with a P1 topology, which can accurately diagnose the fault where the actual flow rate of the circulating exhaust gas is always higher than the target flow rate due to EGR valve leakage, without relying on an EGR temperature sensor.

[0006] To solve the above-mentioned technical problems, one technical solution adopted by the present invention is: to provide an EGR high flow fault diagnosis method, used to diagnose a fault in which the actual flow rate of the circulating exhaust gas is always higher than the target flow rate due to leakage in the EGR valve body, comprising the following steps:

[0007] Obtain the parameters of P1 motor during engine operation;

[0008] Calculate the actual torque Tq of motor P1 based on its parameters. real ;

[0009] Based on the actual torque Tq of P1 motor real Calculate the torque deviation ΔTq and the self-learning value of air leakage La;

[0010] To determine if a high flow fault exists, if the torque deviation ΔTq is greater than or equal to the first threshold and the self-learning value of leakage La is greater than or equal to the second threshold, then a high flow fault exists; otherwise, a high flow fault does not exist.

[0011] Furthermore, before calculating the torque deviation ΔTq and the self-learning value La of the leakage, the following steps are also included:

[0012] The timer records the torque monitoring time T and determines whether the torque monitoring time T is greater than or equal to the time threshold; when the torque monitoring time T is greater than or equal to the time threshold, the torque monitoring ends.

[0013] Furthermore, before obtaining the P1 motor parameters during engine operation, the following steps are also included: determining that the P1 motor has no control fault, that the P1 motor and engine CAN communication are normal, and that the vehicle parameters meet the diagnostic conditions.

[0014] The diagnostic conditions are: vehicle speed greater than the first speed threshold and less than the second speed threshold; water temperature greater than the temperature threshold; no EMS-related faults affecting torque; battery charge greater than the charge threshold; and the power drive mode is series mode.

[0015] Furthermore, after determining that the P1 motor has no control fault, the P1 motor and engine CAN communication are normal, and the vehicle parameters meet the diagnostic conditions, the following steps are also included: the power control unit requests the engine to run under a fixed operating condition to generate electricity, and the number of requests is counted as N; when the number of requests N is greater than or equal to the third threshold, the diagnosis is exited; when the number of requests N is less than the third threshold, the P1 motor parameters during engine operation are obtained.

[0016] Furthermore, the parameters of the P1 motor include the P1 motor voltage, current, speed, power generation efficiency, and communication signal;

[0017] The actual torque Tq of motor P1 real It is obtained through the following formula:

[0018]

[0019] In equation (1), P represents the power of motor P1, and n represents the speed of motor P1.

[0020] The motor power P of P1 is obtained by the following formula:

[0021]

[0022] In equation (ii), U represents the operating voltage of motor P1, I represents the operating current of motor P1, and η represents the power generation efficiency.

[0023] Furthermore, the torque deviation ΔTq is obtained by the following formula:

[0024] ΔTq=Tq modv -Tq real'v (three)

[0025] In equation (iii), Tq modv Tq represents the integral average of the engine model torque. real'v This represents the average integral value of the engine's actual torque.

[0026] The engine model torque integral average value Tq modv It is obtained through the following formula:

[0027]

[0028] In equation (iv), Tq mod This represents the engine model torque, and T represents the torque monitoring time.

[0029] The engine's actual integral average value Tq real'v It is obtained through the following formula:

[0030]

[0031] In equation (5), Tq real' This represents the actual engine torque, Tq. real' Equal to the actual torque Tq of motor P1 real .

[0032] Furthermore, the engine model torque Tq mod It is obtained through the following formula:

[0033] Tq mod =Tq miopt *etazwist (VI)

[0034] In equation (vi), Tq miopt This represents the optimal torque at the current operating point, and etazwist represents the ignition angle efficiency.

[0035] Furthermore, the self-learning value La of the leakage rate is obtained by the following formula:

[0036] La=integrator(old)+in*dL / K(seven)

[0037] In equation (VII), integrator(old) represents the self-learning value of leakage at the previous moment, in represents the self-learning change, dL represents the calculation frequency, and K represents the integration coefficient.

[0038] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is: to provide an EGR high-flow fault diagnosis device, comprising:

[0039] The acquisition module is used to acquire the parameters of the P1 motor during engine operation;

[0040] The first calculation module is used to calculate the actual torque Tq of motor P1 based on the parameters of motor P1. real ;

[0041] The second calculation module is used to calculate the torque deviation ΔTq and the self-learning value of leakage La.

[0042] The judgment module is used to determine whether the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold.

[0043] The fault reporting module is used to report a high flow fault when the judgment module determines that the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold; otherwise, it does not report a high flow fault.

[0044] Furthermore, the second computing module includes:

[0045] The first calculation submodule is used to calculate the torque deviation ΔTq;

[0046] The second calculation submodule is used to calculate the self-learning value La of the leakage.

[0047] The EGR high flow fault diagnosis method and device of the present invention have at least the following beneficial effects: The present invention calculates the actual torque of the engine by back-calculating the actual torque of the P1 motor, and then compares the average deviation between the engine model torque and the actual engine torque with a set threshold. This allows for the diagnosis of the presence of an EGR high flow fault without relying on an EGR temperature sensor, solving the problem that the EGR temperature rise is not significant enough to accurately report the fault when diagnosing an EGR high flow fault based on the temperature rise of the EGR temperature sensor. Furthermore, combining engine leakage self-learning to determine the presence of an EGR high flow fault reduces the possibility of false alarms and improves diagnostic accuracy. By limiting the number of times the power control unit requests the engine to operate under a fixed condition for power generation, power depletion can be avoided. The present invention's diagnosis of EGR high flow faults helps maintenance personnel to promptly detect and repair engine faults, improving vehicle fuel economy and environmental performance. Attached Figure Description

[0048] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0049] Figure 1 This is a flowchart of one embodiment of the EGR high flow fault diagnosis method of the present invention.

[0050] Figure 2 This is a structural block diagram of the EGR high-flow fault diagnosis device of the present invention. Detailed Implementation

[0051] The invention will now be further described with reference to the accompanying drawings.

[0052] The EGR high flow fault diagnosis method of the present invention is only applicable to series operation. In series operation, the engine does not participate in direct drive, and the engine only acts on the P1 motor to drive the P1 motor to generate electricity. At this time, the engine is equivalent to a generator. The actual torque of the engine can be calculated from the actual torque of the P1 motor. The average deviation between the calculated actual torque and the model torque is compared with the set threshold. Combined with the engine leakage self-learning, it can be determined whether there is a high flow fault in the EGR. The diagnostic scheme of the present invention can be used in EGR systems without EGR temperature sensors, and can also be used in EGR systems where faults cannot be determined by EGR temperature rise.

[0053] Please see Figure 1 This is a flowchart of an embodiment of the EGR high-flow fault diagnosis method of the present invention. This embodiment specifically includes the following steps:

[0054] S1. Determine that there is no control fault in motor P1, that the CAN communication between motor P1 and engine is normal, and that the vehicle parameters meet the diagnostic conditions.

[0055] P1 motor control faults are determined internally by the P1 motor controller and then obtained by reading the P1 motor controller through the engine management system. Whether the P1 motor and engine CAN communication is normal is determined by communication-related parameters. For example, communication response timeout or incorrect checksum indicates a P1 motor and engine CAN communication fault. Only when the P1 motor control is normal and the P1 motor and engine CAN communication is normal can the transmitted P1 motor parameters be used for EGR high flow diagnosis.

[0056] The diagnostic conditions that the vehicle parameters need to meet are: vehicle speed greater than a first speed threshold and less than a second speed threshold; water temperature greater than a temperature threshold; no faults affecting torque in the engine management system; battery charge greater than a charge threshold; and the power drive mode is series mode. These relevant thresholds can be set reasonably according to the vehicle.

[0057] S2, The power control unit requests the engine to operate under a fixed condition to generate electricity.

[0058] During engine operation, diagnostics must be performed under a fixed operating condition. This fixed operating condition refers to a defined engine speed and load. For example, if the fixed operating condition is an engine speed of 1500 rpm and a torque of 60 N, then stable power generation and diagnostics will be conducted under this condition. This fixed operating condition is determined by analyzing emissions from different faulty components of the EGR system and considering the fault differentiation rate. For instance, when the operating condition is 1500 rpm and 40 N, the differentiation between faulty components and normal components in the 20% faulty component analysis is relatively low. If the power generation torque is increased to 60 N, the differentiation between the 20% faulty components and normal components becomes relatively higher. Therefore, the operating condition of 1500 rpm and 60 N is preferred as the fixed operating condition.

[0059] The number of requests to run the engine under a fixed operating condition is counted as N. When the number of requests N is greater than or equal to the third threshold, the diagnostic process is terminated. When the number of requests N is less than the third threshold, the P1 motor parameters during engine operation are obtained. If multiple requests are made under series operating conditions, the engine will generate electricity under a fixed operating condition multiple times, which will result in power loss. Therefore, the number of requests must be limited.

[0060] S3. Obtain the P1 motor parameters during engine operation.

[0061] The parameters of the P1 motor include its voltage, current, speed, power generation efficiency, and communication signals.

[0062] S4. Calculate the actual torque Tq of motor P1 based on the parameters of motor P1. real .

[0063] The actual torque Tq of motor P1 real The calculation formula is as follows:

[0064]

[0065] Where P represents the power of motor P1, and n represents the speed of motor P1; the power P of motor P1 is expressed by the formula... We obtain that U represents the operating voltage of motor P1, I represents the operating current of motor P1, and η represents the power generation efficiency.

[0066] S5, the timer records the torque monitoring time T.

[0067] The torque monitoring time here is the time for actual torque integration. It is determined whether the torque monitoring time T is greater than or equal to the time threshold. When the torque monitoring time T is greater than or equal to the time threshold, the torque monitoring ends and the average value of the actual torque integral and the average value of the model torque integral are obtained within the time T. The time threshold can be set according to the actual situation.

[0068] S6, Based on the actual torque Tq of motor P1 realCalculate the torque deviation ΔTq and the self-learning value of leakage La.

[0069] The formula for calculating the torque deviation ΔTq is as follows:

[0070] ΔTq=Tq modv -Tq real ' v

[0071] Among them, Tq modv Tq represents the integral average of the engine model torque. real'v The value represents the average integral of the actual engine torque; the average integral of the engine model torque, Tq, represents... modv Through formula Received, Tq mod The torque of the engine model is represented by T, where T represents the torque monitoring time. mod Through the formula Tq mod =Tq miopt *etazwist obtained, Tq miopt The value represents the optimal torque at the current operating point, etazwist represents the ignition angle efficiency; the actual integral average value of the engine torque Tq real'v Through formula Received, Tq real' This represents the actual torque of the engine. Because in series operation, the engine only drives the P1 motor to generate electricity, and the engine's effect is only on the P1 motor. Therefore, the calculated actual torque Tq of the P1 motor is... real This is equal to the actual engine torque Tq. real' Therefore, the actual torque Tq of the engine is... real' The actual torque Tq of motor P1 calculated above is equal to the torque calculated above. real .

[0072] The formula for calculating the self-learning value La of the leakage rate is as follows:

[0073] La = integrator(old) + in * dL / K

[0074] Where integrator(old) represents the self-learned value of leakage at the previous moment, in represents the self-learned change, dL represents the calculation frequency, and K represents the integration coefficient.

[0075] S7. Determine if a high-flow fault exists.

[0076] If the torque deviation ΔTq is greater than or equal to the first threshold and the leakage self-learning value La is greater than or equal to the second threshold, then a high flow fault exists; otherwise, no high flow fault exists. This embodiment uses two conditions, torque deviation ΔTq and leakage self-learning value La, to determine the EGR high flow fault. To simplify the judgment process, in some embodiments, only the torque deviation ΔTq can be used to determine whether an EGR high flow fault exists. However, this method can lead to false alarms. For example, in some operating conditions, the actual torque may be calculated too low, resulting in a large difference between the actual torque and the model torque, leading to misjudgment. Therefore, this embodiment adds the leakage self-learning value La to eliminate false judgments.

[0077] Please see Figure 2 This is a structural block diagram of the EGR high-flow fault diagnosis device of the present invention. The EGR high-flow fault diagnosis device includes:

[0078] The acquisition module 100 is used to acquire the P1 motor parameters during engine operation. The P1 motor parameters include P1 motor voltage, current, speed, power generation efficiency, and communication signals.

[0079] The first calculation module 200 is used to calculate the actual torque Tq of motor P1 based on the parameters of motor P1. real .

[0080] The second calculation module 300 is used to calculate the torque deviation ΔTq and the self-learning value of leakage La.

[0081] The second calculation module 300 includes the following sub-modules:

[0082] The first calculation submodule 310 is used to calculate the torque deviation ΔTq.

[0083] The second calculation submodule 320 is used to calculate the self-learning value La of the leakage.

[0084] The judgment module 400 is used to determine whether the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold.

[0085] The fault reporting module 500 is used to report a high flow fault when the judgment module 400 determines that the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold; otherwise, it does not report a high flow fault.

[0086] Preferably, this EGR high flow fault diagnosis device also includes a first judgment module, used to determine whether the following conditions are met: no control fault in P1 motor, normal CAN communication between P1 motor and engine, and vehicle parameters meet the diagnostic conditions.

[0087] This invention calculates the actual engine torque by back-calculating the actual torque of the P1 motor, and then compares the average deviation between the engine model torque and the actual engine torque with a set threshold. This allows for the diagnosis of high EGR flow faults without relying on an EGR temperature sensor, solving the problem of inaccurate fault reporting when using EGR temperature sensor-based high EGR flow fault diagnosis due to the insignificant temperature rise. Furthermore, combining engine leakage self-learning to determine the presence of high EGR flow faults reduces the possibility of false alarms and improves diagnostic accuracy. By limiting the number of times the power control unit requests the engine to operate under a fixed condition for power generation, power depletion can be avoided. This invention's diagnosis of high EGR flow faults helps maintenance personnel promptly detect and repair engine faults, improving vehicle fuel economy and environmental performance.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for diagnosing high-flow-rate EGR faults, used to diagnose faults where the actual flow rate of the circulating exhaust gas is consistently higher than the target flow rate due to leakage in the EGR valve body, characterized in that, Includes the following steps: Obtain the parameters of the P1 motor during engine operation; Calculate the actual torque Tq of motor P1 based on its parameters. real ; Based on the actual torque Tq of P1 motor real Calculate the torque deviation ΔTq and the self-learning value of air leakage La; To determine if a high flow fault exists, if the torque deviation ΔTq is greater than or equal to the first threshold and the self-learning value of leakage La is greater than or equal to the second threshold, then a high flow fault exists; otherwise, a high flow fault does not exist.

2. The EGR high-flow fault diagnosis method as described in claim 1, characterized in that, Before calculating the torque deviation ΔTq and the self-learning value of leakage La, the following steps are also included: The timer records the torque monitoring time T and determines whether the torque monitoring time T is greater than or equal to the time threshold; when the torque monitoring time T is greater than or equal to the time threshold, the torque monitoring ends.

3. The EGR high-flow fault diagnosis method as described in claim 1, characterized in that, Before obtaining the P1 motor parameters during engine operation, the following steps are also included: determining that the P1 motor has no control fault, that the P1 motor and engine CAN communication are normal, and that the vehicle parameters meet the diagnostic conditions. The diagnostic conditions are: vehicle speed greater than the first speed threshold and less than the second speed threshold; water temperature greater than the temperature threshold; no EMS-related faults affecting torque; battery charge greater than the charge threshold; and the power drive mode is series mode.

4. The EGR high-flow fault diagnosis method as described in claim 3, characterized in that, After determining that the P1 motor has no control fault, the P1 motor and engine CAN communication are normal, and the vehicle parameters meet the diagnostic conditions, the following steps are also included: the power control unit requests the engine to run under a fixed operating condition to generate electricity, and the number of requests is counted as N; when the number of requests N is greater than or equal to the third threshold, the diagnosis is exited; when the number of requests N is less than the third threshold, the P1 motor parameters during engine operation are obtained.

5. The EGR high-flow fault diagnosis method as described in claim 1, characterized in that, The parameters of the P1 motor include the P1 motor voltage, current, speed, power generation efficiency, and communication signal. The actual torque Tq of motor P1 real It is obtained through the following formula: In equation (1), P represents the power of motor P1, and n represents the speed of motor P1. The motor power P of P1 is obtained by the following formula: In equation (ii), U represents the operating voltage of motor P1, I represents the operating current of motor P1, and η represents the power generation efficiency.

6. The EGR high-flow fault diagnosis method as described in claim 5, characterized in that, The torque deviation ΔTq is obtained by the following formula: ΔTq=Tq modv -Tq real'v (3) In equation (iii), Tq modv Tq represents the integral average of the engine model torque. real'v This represents the average integral value of the engine's actual torque. The engine model torque integral average value Tq modv It is obtained through the following formula: In equation (iv), Tq mod This represents the engine model torque, and T represents the torque monitoring time. The engine's actual integral average value Tq real'v It is obtained through the following formula: In equation (5), Tq real' This represents the actual engine torque, Tq. real' Equal to the actual torque Tq of motor P1 real .

7. The EGR high-flow fault diagnosis method as described in claim 6, characterized in that, The engine model torque Tq mod It is obtained through the following formula: Tq mod =Tq miopt *etazwist(VI) In equation (vi), Tq miopt This represents the optimal torque at the current operating point, and etazwist represents the ignition angle efficiency.

8. The EGR high-flow fault diagnosis method as described in claim 1, characterized in that, The self-learning value of leakage La is obtained by the following formula: La=integrator(old)+in*dL / K(seven) In equation (VII), integrator(old) represents the self-learned value of leakage at the previous moment, in represents the self-learned change, dL represents the calculation frequency, and K represents the integral coefficient.

9. An EGR high-flow fault diagnosis device, characterized in that, include: The acquisition module is used to acquire the parameters of the P1 motor during engine operation; The first calculation module is used to calculate the actual torque Tq of motor P1 based on the parameters of motor P1. real ; The second calculation module is used to calculate the torque deviation ΔTq and the self-learning value of leakage La. The judgment module is used to determine whether the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold. The fault reporting module is used to report a high flow fault when the judgment module determines that the torque deviation ΔTq is greater than or equal to the first threshold and the air leakage self-learning value La is greater than or equal to the second threshold; otherwise, a high flow fault is not reported.

10. The EGR high-flow fault diagnosis device as described in claim 9, characterized in that, The second calculation module includes: The first calculation submodule is used to calculate the torque deviation ΔTq; The second calculation submodule is used to calculate the self-learning value La of the leakage.

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