Engine misfire diagnosis method, system, vehicle and medium for a hybrid electric vehicle

Abstract

The present application relates to a kind of engine misfire diagnostic method, system, vehicle and medium of oil-electric hybrid car, comprising: the frequency of calculating speed fluctuation and engine ignition frequency, based on speed fluctuation frequency and engine ignition frequency whether the speed fluctuation is caused by engine combustion is judged, if yes, engine misfire diagnosis is carried out, if no, indicate that misfire diagnosis is inaccurate, then misfire diagnosis is prohibited;The engine misfire diagnosis is specifically as follows: when misfire rate is greater than mixed gas change limit, whether there is mixed gas unburning according to excess air coefficient is judged, if no mixed gas unburning, then it is not true misfire fault, misfire diagnosis is inaccurate at this time, and misfire fault is not output;Otherwise, misfire fault is output.The present application solves the problem that oil-electric hybrid vehicle appears false engine misfire due to generator torque change, drive motor torque change, engine torque change.

Description

Technical Field

[0001] This invention relates to the field of engine technology, and specifically to a method, system, vehicle, and medium for diagnosing engine misfire in a hybrid vehicle. Background Technology

[0002] Traditional gasoline vehicles determine whether the engine has misfired based on changes in the engine crankshaft angular velocity. In hybrid vehicles, the torque intervention of the generator and drive motor can affect the engine crankshaft angular velocity, making it easy to misjudge engine misfire.

[0003] For example, the engine misfire diagnosis method for hybrid vehicles disclosed in patent document CN112065582A includes: reading the current engine speed; finding the maximum and minimum BSG torque at the current engine speed, and simultaneously reading the actual BSG torque; calculating the first deceleration threshold at different engine speeds and engine torques under the maximum BSG torque, the second deceleration threshold at different engine speeds and engine torques under the minimum BSG torque, and the third deceleration threshold at different engine speeds and engine torques under a BSG torque of 0; obtaining a fourth or fifth deceleration threshold using the maximum BSG torque, minimum BSG torque, actual BSG torque, first deceleration threshold, second deceleration threshold, and third deceleration threshold; determining whether the actual deceleration is greater than the fourth or fifth deceleration threshold; and if so, determining that the engine is misfired. However, this method only compares the maximum and minimum values ​​of the generator torque to determine whether the engine is misfired, which cannot avoid incorrectly determining engine misfire when the engine torque changes frequently or when the torque of the generator and drive motor intervenes.

[0004] For example, patent document CN113202627B describes an engine misfire detection method and controller. This method includes acquiring the engine compensation torque calculated by the motor controller when an engine misfire occurs; combining the engine compensation torque to obtain the actual engine speed fluctuation "NESINR" caused by the misfire; converting the actual engine speed fluctuation "NESINR" into a syn_segment time sequence to obtain the actual engine speed fluctuation under the syn_segment time sequence; obtaining the corresponding real segment time "tsk_NESINR" based on the actual engine speed fluctuation under the syn_segment time sequence; determining whether the condition for activating the real segment time "tsk_NESINR" is met. If the activation condition is met, the original "segment time" is replaced with the real segment time "tsk_NESINR"; if the activation condition is not met, the original "segment time" is maintained, thus obtaining the actual "segment time"; calculating the misfire characteristic signal based on the actual "segment time"; and performing engine misfire detection based on the misfire characteristic signal, thereby enabling real-time and accurate detection of the engine misfire state. This method compensates for the diagnostic segment time based on the premise that the generator control is normal, and it is highly dependent on the control accuracy of the generator. When the generator control is abnormal or there are other torque interventions in the transmission system, this detection method may fail or even falsely report a misfire fault.

[0005] Therefore, it is necessary to develop a new method, system, vehicle, and medium for diagnosing engine misfires in hybrid vehicles. Summary of the Invention

[0006] The purpose of this invention is to provide a method, system, vehicle, and storage medium for diagnosing engine misfire in hybrid electric vehicles, in order to solve the problem of incorrect engine misfire diagnosis in hybrid electric vehicles caused by changes in generator torque, drive motor torque, and engine torque.

[0007] In a first aspect, the present invention provides a method for diagnosing engine misfire in a hybrid vehicle, comprising the following steps:

[0008] The engine speed fluctuation is acquired to determine whether it is caused by engine combustion. If so, engine misfire diagnosis is performed. If not, it indicates that the misfire diagnosis is inaccurate and misfire diagnosis is prohibited.

[0009] The engine misfire diagnosis specifically includes:

[0010] When the misfire rate exceeds the limit for mixture change, the excess air coefficient is used to determine whether there is unburned mixture. If there is no unburned mixture, it is considered not a real misfire fault. In this case, the misfire diagnosis is inaccurate and no misfire fault is output; otherwise, a misfire fault is output.

[0011] Optionally, the engine speed fluctuation is acquired, and it is determined whether the engine speed fluctuation is caused by engine combustion, including:

[0012] S11: Get the current rotation speed;

[0013] S12: Calculate the engine speed fluctuation frequency and engine ignition frequency;

[0014] S13: Calculate the frequency ratio of engine ignition frequency to speed fluctuation frequency;

[0015] S14: Determine whether the calculated frequency ratio is within the frequency ratio threshold range. If yes, it means that the speed fluctuation is caused by engine combustion, perform engine misfire diagnosis, and return to step S11. If no, it means that the speed fluctuation is not caused by engine combustion, and proceed to step S15.

[0016] S15: Fire diagnosis is prohibited.

[0017] This invention ensures the accuracy of fire detection.

[0018] Optionally, the engine misfire diagnosis includes:

[0019] S31: Obtain the excess air coefficient, rapid fuel self-learning value, target excess air coefficient, misfire rate, speed, and load. Use the speed and load to look up the threshold table for the misfire rate of the mixture to obtain the threshold for the misfire rate of the mixture under the current speed and load.

[0020] S32: Determine whether the misfire rate is greater than the threshold for changing the misfire rate of the mixture. If yes, proceed to step S33; otherwise, the process ends.

[0021] S33: Calculate the actual excess air coefficient before fast fuel self-learning value correction;

[0022] S34: Calculate the difference between the actual excess air coefficient before correction and the target excess air coefficient;

[0023] S35: Determine whether the difference between the actual excess air coefficient and the target excess air coefficient exceeds the threshold Δ. λ1 If yes, proceed to step S36; otherwise, proceed to step S37.

[0024] S36: Output of fire fault, process ends;

[0025] S37: The engine is deemed not to have misfired, no misfire fault is output, and the process ends.

[0026] Optionally, it also includes:

[0027] After a misfire diagnosis is disabled, determine whether to restore the misfire diagnosis. If yes, proceed with the engine misfire diagnosis; otherwise, continue to determine whether to restore the misfire diagnosis.

[0028] Optionally, after a misfire diagnosis is disabled, it is determined whether to restore the misfire diagnosis. If yes, engine misfire diagnosis is performed; otherwise, the determination continues. This includes:

[0029] S21: Obtain the fire diagnosis status;

[0030] S22: Determine whether to prohibit fire diagnosis based on the fire diagnosis status. If yes, proceed to S23; otherwise, return to step S21.

[0031] S23: Calculate the frequency ratio of engine ignition frequency to speed fluctuation frequency, and determine whether the frequency ratio is within the frequency ratio threshold range. If yes, proceed to step S24; otherwise, continue to step S23.

[0032] S24: Record the rotational speed A when the first condition is met in step S23;

[0033] S25: Calculate the absolute value of the difference between the current speed and speed A;

[0034] S26: Determine whether the absolute value of the difference between the current speed and speed A is greater than the preset speed. If yes, proceed to step S27; otherwise, continue to proceed to step S26.

[0035] S27: Restore fire diagnosis.

[0036] Optionally, in step S12, the formula for calculating the rotational speed fluctuation frequency is as follows:

[0037] f2 = 1 / T;

[0038] Where f2 is the rotational speed fluctuation frequency; T is the period of rotational speed fluctuation.

[0039] Optionally, in step 14, the frequency ratio threshold range is: Let Δ be the number of all combinations of taking i elements from K distinct elements, where K is the number of engine cylinders, i is 1, 2, 3, ..., K; and Δ is the sampling and calculation bias.

[0040] Optionally, step S33, calculating the actual excess air coefficient before rapid fuel self-learning value correction, specifically involves:

[0041] λ = λ1 * a;

[0042] Where: λ is the actual excess air coefficient before the fast fuel self-learning value correction; λ1 is the actual excess air coefficient; and a is the fast fuel self-learning value.

[0043] Optionally, step S34, calculating the difference between the actual excess air coefficient before correction and the target excess air coefficient, specifically involves:

[0044] Δ λ =λ-λ set ;

[0045] Where, Δ λ λ is the difference between the actual excess air coefficient before correction and the target excess air coefficient; set The target excess air coefficient.

[0046] Secondly, the present invention provides an engine misfire diagnosis system for a hybrid electric vehicle, comprising a controller and a memory, wherein the memory stores a computer-readable program, and the computer-readable program, when invoked by the controller, can execute the steps of the engine misfire diagnosis method for a hybrid electric vehicle as described in the present invention.

[0047] In this invention, the computer-readable program is divided into functional modules, including an acquisition module, a signal processing module, and a judgment module. The signal processing module is connected to both the acquisition module and the judgment module. The acquisition module acquires excess air coefficient, rapid fuel self-learning value, target excess air coefficient, misfire rate, engine speed, and load. The signal processing module calculates the ratio of engine ignition frequency to engine speed fluctuation frequency and the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient. The judgment module compares the relationship between engine speed fluctuation frequency and engine ignition frequency to determine whether the speed fluctuation is caused by engine misfire. In cases of high misfire rate, it obtains the true excess air coefficient from the oxygen sensor signal before the catalytic converter to determine if a real misfire has occurred. The signal processing module includes a first processing unit and a second processing unit. The first processing unit transforms the engine speed signal to obtain the ratio of engine ignition frequency to engine speed fluctuation frequency and records the engine speed A when the frequency ratio is satisfied for the first time after a misfire prevention diagnosis due to the frequency ratio exceeding a threshold. The second processing unit transforms the actual excess air coefficient to obtain the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient. The first processing unit is specifically used for: calculating the engine ignition frequency from the speed signal; comparing the speed before and after each sampling period, finding two adjacent peaks in the engine speed signal, calculating the time interval between the two peaks to obtain the speed fluctuation period, and calculating the speed fluctuation frequency based on the engine ignition frequency and the speed fluctuation period; and recording the speed A when the frequency ratio first meets the limit (i.e., the frequency ratio is within the frequency ratio threshold range) after misfire diagnosis is prohibited due to the frequency ratio being outside the frequency ratio threshold range. The second processing unit is specifically used for: multiplying the actual excess air coefficient by the rapid fuel self-learning correction value to obtain the actual excess air coefficient before rapid fuel self-learning correction; and subtracting the target excess air coefficient from the actual excess air coefficient before rapid fuel self-learning correction to obtain the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient. The judgment module is specifically used for: when the frequency ratio is not within the frequency ratio threshold range, determining that the speed fluctuation is not caused by engine misfire and that there is external torque intervention, in which case misfire diagnosis is unreliable and misfire diagnosis is prohibited; after misfire diagnosis is prohibited because the frequency ratio is not within the frequency ratio threshold range, when the frequency ratio is again within the frequency ratio threshold range and the speed change exceeds 500 Rpm, determining that there is no longer external intervention and resuming misfire diagnosis; when the misfire rate is greater than the mixture change limit, when the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient exceeds the threshold Δ λ1 If the engine misfires, a misfire fault is reported; if the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient is less than or equal to the threshold Δ... λ1If the engine misfires, it will be determined that the misfire is not a real misfire and no misfire fault will be reported.

[0048] This invention eliminates the influence of variations in engine torque, drive motor torque, and engine torque on engine misfire diagnosis in hybrid electric vehicles, thus improving the accuracy of engine misfire diagnosis. This invention can be applied to all configurations of hybrid electric vehicles, such as range-extended, P2, and P13 models.

[0049] Thirdly, the vehicle described in this invention employs the engine misfire diagnosis system for hybrid vehicles as described in this invention.

[0050] Fourthly, the present invention provides a storage medium storing a computer-readable program, which, when invoked, can execute the steps of the engine misfire diagnosis method for a hybrid vehicle as described in the present invention.

[0051] This invention has the following advantages: By comparing the relationship between the frequency of engine speed fluctuations and the engine ignition frequency, this invention determines whether the speed fluctuations are caused by engine misfire, thus confirming whether the engine has actually misfired. This invention can eliminate the influence of speed fluctuations caused by changes in engine torque, drive motor torque, and engine torque on engine misfire diagnosis in hybrid vehicles, improving the accuracy of engine misfire diagnosis in hybrid vehicles. At high misfire rates, by judging whether the oxygen sensor signal before the catalytic converter is lean, it further determines whether the engine has actually misfired, making the misfire fault diagnosis more accurate. This invention is not limited by hybrid configuration and can be applied to all drive forms of hybrid vehicles of all configurations, such as range-extended, P2, and P13 series and parallel modes, making its application wide-ranging. Attached Figure Description

[0052] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is one of the main flowcharts of this embodiment;

[0054] Figure 2 This is the second main flowchart of this embodiment;

[0055] Figure 3 This is the fire diagnosis logic diagram in this embodiment;

[0056] Figure 4 This embodiment shows the logic diagram for restoring fire diagnosis.

[0057] Figure 5 This is the fire fault output logic diagram in this embodiment;

[0058] Figure 6 This is a schematic diagram illustrating the calculation of rotational speed fluctuation frequency in this embodiment;

[0059] Figure 7 This is the engine misfire detection device in this embodiment;

[0060] In the diagram: 1. Acquisition module, 2. Signal processing module, 3. Judgment module. Detailed Implementation

[0061] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0062] The period and frequency of engine speed fluctuations caused by engine misfire should be integer multiples of the engine's ignition cycle and frequency. At a high misfire rate (generally above 11%), a large amount of unburned oxygen enters the exhaust, resulting in a leaner air-fuel mixture at the oxygen sensor. This invention determines whether an engine has actually misfired by judging the relationship between the period and frequency of engine speed fluctuations and the engine's ignition cycle and frequency, as well as the air-fuel ratio at a high misfire rate.

[0063] like Figure 1 As shown in this embodiment, a method for diagnosing engine misfire in a hybrid vehicle includes the following steps:

[0064] Calculate the engine speed fluctuation frequency and engine ignition frequency. Based on the engine speed fluctuation frequency and engine ignition frequency, determine whether the engine speed fluctuation is caused by engine combustion. If so, perform engine misfire diagnosis. If not, it means that the misfire diagnosis is inaccurate and misfire diagnosis is prohibited.

[0065] In this embodiment, the engine misfire diagnosis specifically includes:

[0066] When the misfire rate exceeds the limit for mixture change, the excess air coefficient is used to determine whether there is unburned mixture. If there is no unburned mixture, it is considered not a real misfire fault. In this case, the misfire diagnosis is inaccurate and no misfire fault is output; otherwise, a misfire fault is output.

[0067] like Figure 2 As shown in this embodiment, a method for diagnosing engine misfire in a hybrid vehicle further includes:

[0068] After a misfire diagnosis is disabled, determine whether to restore the misfire diagnosis. If yes, proceed with the engine misfire diagnosis; otherwise, continue to determine whether to restore the misfire diagnosis.

[0069] like Figure 3 As shown, in this embodiment, acquiring speed fluctuations and determining whether the speed fluctuations are caused by engine combustion specifically includes:

[0070] S11: Get the current rotational speed.

[0071] S12: Calculate the speed fluctuation frequency and engine ignition frequency.

[0072] During engine operation, speed fluctuations are noted. Figure 6 The system will collect the engine speed every 2ms, that is Figure 6 The diagram illustrates the calculation of the rotational speed fluctuation frequency, showing dots and comparing the magnitudes of two consecutive sampled rotational speeds. If the current rotational speed is greater than the previous one, it indicates that the rotational speed is increasing; if, after an increase, the first detected rotational speed is less than the previous one, it indicates that the previous rotational speed was a peak. Using the same method, the system will detect the next peak, and the time elapsed between the two peaks is the period of rotational speed fluctuation.

[0073] In this embodiment, the formula for calculating the rotational speed fluctuation frequency is as follows:

[0074] f2 = 1 / T;

[0075] Where T is the period of the speed fluctuation; f2 is the frequency of the speed fluctuation.

[0076] In this embodiment, the formula for calculating the engine ignition frequency is as follows:

[0077] f1 = n * K / 30;

[0078] Where f1 is the engine ignition frequency; n is the engine speed; and K is the number of engine cylinders.

[0079] S13: Calculate the frequency ratio of the engine ignition frequency to the speed fluctuation frequency, specifically:

[0080] X = f1 / f2;

[0081] Where X represents the frequency ratio of the engine ignition frequency to the speed fluctuation frequency.

[0082] S14: Compare the frequency ratio of the engine ignition frequency to the speed fluctuation frequency calculated in step S13 with the frequency ratio threshold range. Determine whether the calculated frequency ratio is within the frequency ratio threshold range. If the calculated frequency ratio is within the frequency ratio threshold range, it indicates that the speed fluctuation is caused by engine combustion, and engine misfire diagnosis is performed. At the same time, return to step S11. If the calculated frequency ratio is not within the frequency ratio threshold range, it indicates that the speed fluctuation is not caused by engine combustion, and proceed to step S15.

[0083] In this embodiment, the frequency ratio threshold range is: in, Δ represents the number of all combinations of selecting i elements from K distinct elements; K is the number of engine cylinders, and i is 1, 2, 3, ..., K; Δ is the sampling and calculation bias.

[0084] For example, in a certain instance, the frequency ratio threshold range of a four-cylinder engine is [1-Δ, 1+Δ], or [2-Δ, 2+Δ], or [4-Δ, 4+Δ].

[0085] In this embodiment, Δ is obtained by: without misfire, normal driving, including the operating conditions of all engines, and the upper and lower limits of the statistical frequency ratio. To obtain Δ1, create a random single misfire (e.g., a misfire every 28 ignitions), and drive normally, including all engine operating conditions. Subtract the nearest integer from the upper and lower limits of the statistical frequency ratio (e.g., if the frequency ratio is within 1 ± 0.01, Δ1 = 0.01). To obtain Δ2, create a continuous misfire in one cylinder (e.g., in a four-cylinder engine, create continuous misfires in cylinders 1, 2, 3, and 4 respectively), and drive normally, including all engine operating conditions. Subtract the nearest integer from the upper and lower limits of the statistical frequency ratio. To obtain Δ3, randomly combine two cylinders (e.g., in a four-cylinder engine, 1&2, 1&3, 1&4, 2&3, 2&4, 3&4) to create continuous misfires, and drive normally, including all engine operating conditions. Subtract the nearest integer from the upper and lower limits of the statistical frequency ratio. To obtain Δ3, use the same method to randomly combine 3, 4, 5…j cylinders to create continuous misfires. j j represents the number of cylinders in the engine that cannot operate normally, Δ = MAX(Δ1, Δ2, Δ3, ..., Δ j ).

[0086] In this embodiment, the determination method is as follows: when the frequency ratio (i.e., X) is in If the frequency ratio falls within any range, it is considered to be within the frequency ratio threshold range; otherwise, it is considered to be outside the frequency ratio threshold range.

[0087] S15: Fire diagnosis is prohibited.

[0088] like Figure 4As shown, in this embodiment, after misfire diagnosis is disabled, the system continues to determine whether to restore misfire diagnosis. If yes, engine misfire diagnosis is performed; otherwise, the system continues to determine whether to restore misfire diagnosis. Specifically, this includes the following steps:

[0089] S21: Obtain the fire diagnosis status.

[0090] S22: Determine whether to prohibit fire diagnosis based on the fire diagnosis status. If yes, proceed to S23; otherwise, return to step S21.

[0091] S23: Calculate the frequency ratio of engine ignition frequency to speed fluctuation frequency, and determine whether the frequency ratio is within the frequency ratio threshold range. If yes, proceed to step S24; otherwise, continue to proceed to step S23.

[0092] S24: Record the rotational speed A when the condition is met for the first time in step S23.

[0093] S25: Calculate the absolute value of the difference between the current speed and speed A.

[0094] S26: Determine whether the absolute value of the difference between the current speed and speed A is greater than the preset speed (e.g., 500 Rpm). If yes, proceed to step S27; otherwise, continue to step S26.

[0095] S27: Restore fire diagnosis.

[0096] like Figure 5 As shown, in this embodiment, when the misfire rate (obtained through existing misfire diagnosis statistics) is greater than the mixture change limit, the excess air coefficient is used to determine whether there is unburned mixture. If there is no unburned mixture, it is considered not a true misfire fault, and the misfire diagnosis is inaccurate, so no misfire fault is output; otherwise, a misfire fault is output, as follows:

[0097] S31: Read the excess air coefficient (i.e., λ1, where λ1 is the oxygen sensor reading), the rapid fuel self-learning value (i.e., a, where a is the control correction value, obtained from the oxygen sensor correction, which is existing technology), and the target excess air coefficient (i.e., λ). set , λ set The values ​​are preset, misfire rate (obtained by referring to the calculation method specified in regulations, which is the prior art), speed, and load. The threshold for changing the misfire rate of the mixture under the current speed and load is obtained by looking up the threshold table for changing the misfire rate of the mixture (i.e., Table 1) using the speed and load.

[0098] Table 1: Thresholds for Changing the Misfire Rate of Gas-Gas Mixture

[0099]

[0100]

[0101] In the table, b11-b130 represent the threshold values ​​at which the mixture changes the misfire rate.

[0102] S32: Determine whether the misfire rate is greater than the threshold for changing the misfire rate of the mixture. If yes, proceed to step S33; otherwise, the process ends.

[0103] In this embodiment, the method for obtaining the threshold for changing the misfire rate of the gas mixture is as follows:

[0104] Under different speed and load conditions, misfires are induced, and the misfire rate is gradually increased until the difference Δ between the actual excess air coefficient before correction and the target excess air coefficient is reached. λ (Calculation method is shown in step S33) Exceeds the threshold Δ λ1 (See step S35 for the method of obtaining the information), and fill the misfire rate at this time into the corresponding speed and load position in the threshold table for changing the misfire rate of the mixture.

[0105] S33: Calculate the actual excess air coefficient before fast fuel self-learning correction, specifically:

[0106] λ = λ1 * a;

[0107] Where: λ is the actual excess air coefficient before the fast fuel self-learning value correction; λ1 is the actual excess air coefficient; and a is the fast fuel self-learning value.

[0108] S34: Calculate the difference between the actual excess air coefficient before correction and the target excess air coefficient, specifically:

[0109] Δ λ =λ-λ set ;

[0110] Where, Δ λ λ is the difference between the actual excess air coefficient before correction and the target excess air coefficient; set The target excess air coefficient.

[0111] S35: Determine whether the difference between the actual excess air coefficient and the target excess air coefficient exceeds the threshold Δ. λ1 If yes, proceed to step S36; otherwise, proceed to step S37.

[0112] In this embodiment, the threshold Δ λ1 It should be clearly distinguishable from normal non-misfire operating conditions. After the emissions data are solidified, the vehicle should be driven aggressively (including rapid acceleration, rapid deceleration, and RPM increasing by 1000 RPM and then decreasing by 500 RPM up to 6000 RPM), and the ΔE ratio under normal non-misfire conditions should be calculated. λ The maximum value, Δ λ The maximum value plus 0.05 can be used as Δ.λ threshold Δ λ1 .

[0113] S36: Output of fire fault, process ends.

[0114] S37: The engine is deemed not to have misfired, no misfire fault is output, and the process ends.

[0115] In this embodiment, an engine misfire diagnosis system for a hybrid electric vehicle includes a controller and a memory. The memory stores a computer-readable program, which, when invoked by the controller, can execute the steps of the engine misfire diagnosis method for a hybrid electric vehicle as described in this invention.

[0116] like Figure 7 As shown in this embodiment, the computer-readable program is divided according to functional modules, including an acquisition module 1, a signal processing module 2, and a judgment module 3. The signal processing module 2 is connected to the acquisition module 1 and the judgment module 3, respectively.

[0117] like Figure 7 As shown, in this embodiment, the acquisition module 1 is used to acquire the excess air coefficient, rapid fuel self-learning value, target excess air coefficient, misfire rate, speed and load.

[0118] like Figure 7 As shown, in this embodiment, the signal processing module 2 is used to calculate the ratio of engine ignition frequency to speed fluctuation frequency, and to calculate the difference between the actual excess air coefficient and the target excess air coefficient before rapid fuel self-learning correction.

[0119] like Figure 7 As shown, in this embodiment, the judgment module 3 is used to compare the relationship between the speed fluctuation frequency and the engine ignition frequency to determine whether the speed fluctuation is caused by engine misfire. When the misfire rate is high, the oxygen sensor signal before the catalyst (i.e., steps S31 to S37) is used to determine whether there is a real misfire.

[0120] In this embodiment, the signal processing module 2 includes a first processing unit and a second processing unit; wherein, the first processing unit is used to transform the speed signal to obtain the ratio of the engine ignition frequency to the engine speed fluctuation frequency, and record the speed A when the frequency ratio is satisfied for the first time after the misfire prevention diagnosis due to the frequency ratio exceeding the threshold; the second processing unit is used to transform the actual excess air coefficient to obtain the difference between the actual excess air coefficient and the target excess air coefficient before rapid fuel self-learning correction.

[0121] In this embodiment, the first processing unit is specifically used to: calculate the engine ignition frequency from the speed signal; compare the speed before and after each sampling period, find two adjacent peaks of the engine speed signal, calculate the time interval between the two peaks to obtain the speed fluctuation period, calculate the speed fluctuation frequency based on the engine ignition frequency and the speed fluctuation period; and record the speed A when the frequency ratio first meets the limit after the misfire diagnosis is prohibited because the frequency ratio is not within the frequency ratio threshold range.

[0122] In this embodiment, the second processing unit is specifically used to: multiply the actual excess air coefficient by the rapid fuel self-learning correction value to obtain the actual excess air coefficient before rapid fuel self-learning correction; and subtract the target excess air coefficient from the actual excess air coefficient before rapid fuel self-learning correction to obtain the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient.

[0123] In this embodiment, the judgment module 3 is specifically used to: when the frequency ratio is not within the frequency ratio threshold range, determine that the speed fluctuation is not caused by engine misfire, indicating that there is external torque intervention. At this time, misfire diagnosis is unreliable, and misfire diagnosis is prohibited; after misfire diagnosis is prohibited because the frequency ratio is not within the frequency ratio threshold range, and the frequency ratio is again within the frequency ratio threshold range and the speed change exceeds 500 Rpm, determine that there is no longer external intervention, and resume misfire diagnosis. When the misfire rate is greater than the mixture change limit, when the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient exceeds the threshold Δ... λ1 If the engine misfires, a misfire fault is reported; if the difference between the actual excess air coefficient before rapid fuel self-learning correction and the target excess air coefficient is less than or equal to the threshold Δ... λ1 If the engine misfires, it will be determined that the misfire is not a real misfire and no misfire fault will be reported.

[0124] In this embodiment, the engine's current speed is read, along with the engine's actual excess air coefficient, rapid fuel self-learning value, and target excess air coefficient. The engine speed fluctuation frequency, the ratio of the engine ignition frequency to the engine speed fluctuation frequency, and the deviation between the actual excess air coefficient and the target excess air coefficient before rapid fuel correction are calculated. It is determined whether the ratio of the ignition frequency to the engine speed fluctuation frequency is within a frequency ratio threshold range. If it is, the speed fluctuation is caused by a real engine misfire; otherwise, the speed fluctuation is not caused by a real engine misfire, and misfire diagnosis is suppressed until the frequency ratio of the ignition frequency to the engine speed fluctuation frequency during speed changes is within the frequency ratio threshold range. When the misfire rate exceeds a limit, it is determined whether the deviation between the actual excess air coefficient and the target excess air coefficient before rapid fuel correction exceeds an excess air coefficient deviation threshold. If so, a real engine misfire is considered, and a misfire fault is output; otherwise, no real engine misfire is considered, and no misfire fault is output. This invention eliminates the influence of variations in engine torque, drive motor torque, and engine torque on engine misfire diagnosis in hybrid electric vehicles, thus improving the accuracy of engine misfire diagnosis. This invention can be applied to all configurations of hybrid electric vehicles, such as range-extended, P2, and P13 models.

[0125] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0126] As used in this embodiment, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0127] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for diagnosing engine misfire in a hybrid vehicle, characterized in that, Includes the following steps: Calculate the engine speed fluctuation frequency and engine ignition frequency. Based on the engine speed fluctuation frequency and engine ignition frequency, determine whether the engine speed fluctuation is caused by engine combustion. If so, perform engine misfire diagnosis. If not, it means that the misfire diagnosis is inaccurate and misfire diagnosis is prohibited. The engine misfire diagnosis specifically includes: When the misfire rate is greater than the threshold for changing the misfire rate of the mixture, it is determined whether there is unburned mixture based on the excess air coefficient. If there is no unburned mixture, it is considered not a real misfire fault. At this time, the misfire diagnosis is inaccurate and no misfire fault is output; otherwise, a misfire fault is output. Determining whether engine speed fluctuations are caused by engine combustion includes the following steps: S11: Get the current rotation speed; S12: Calculate the engine speed fluctuation frequency and engine ignition frequency; S13: Calculate the frequency ratio of engine ignition frequency to speed fluctuation frequency; S14: Determine whether the calculated frequency ratio is within the frequency ratio threshold range. If yes, it means that the speed fluctuation is caused by engine combustion, perform engine misfire diagnosis, and return to step S11; if no, it means that the speed fluctuation is not caused by engine combustion, and proceed to step S15. S15: Fire diagnosis is prohibited.

2. The method for diagnosing engine misfire in a hybrid vehicle according to claim 1, characterized in that: The engine misfire diagnosis includes the following steps: S31: Obtain the excess air coefficient, rapid fuel self-learning value, target excess air coefficient, misfire rate, speed, and load. Use the speed and load to look up the threshold table for the misfire rate of the mixture to obtain the threshold for the misfire rate of the mixture under the current speed and load. S32: Determine whether the misfire rate is greater than the threshold for changing the misfire rate of the mixture. If yes, proceed to step S33; otherwise, the process ends. S33: Calculate the actual excess air coefficient before fast fuel self-learning value correction; S34: Calculate the difference between the actual excess air coefficient before correction and the target excess air coefficient; S35: Determine whether the difference between the actual excess air coefficient before correction and the target excess air coefficient exceeds the threshold Δ. λ1 If yes, proceed to step S36; otherwise, proceed to step S37. S36: Output fire fault, process ends; S37: The engine is deemed not to have misfired, no misfire fault is output, and the process ends.

3. The method for diagnosing engine misfire in a hybrid vehicle according to claim 1, characterized in that, Also includes: After a misfire diagnosis is disabled, determine whether to restore the misfire diagnosis. If yes, proceed with the engine misfire diagnosis; otherwise, continue to determine whether to restore the misfire diagnosis.

4. The method for diagnosing engine misfire in a hybrid vehicle according to claim 3, characterized in that: After a misfire diagnosis is disabled, determine whether to restore the misfire diagnosis. If yes, perform an engine misfire diagnosis; otherwise, continue to determine whether to restore the misfire diagnosis. This includes the following steps: S21: Obtain the fire diagnosis status; S22: Determine whether to prohibit fire diagnosis based on the fire diagnosis status. If yes, proceed to S23; otherwise, return to step S21. S23: Calculate the frequency ratio of engine ignition frequency to speed fluctuation frequency, and determine whether the frequency ratio is within the frequency ratio threshold range. If yes, proceed to step S24; otherwise, continue to step S23. S24: Record the rotational speed A when the first condition is met in step S23; S25: Calculate the absolute value of the difference between the current speed and speed A; S26: Determine whether the absolute value of the difference between the current speed and speed A is greater than the preset speed. If yes, proceed to step S27; otherwise, continue to proceed to step S26. S27: Restore fire diagnosis.

5. The method for diagnosing engine misfire in a hybrid vehicle according to claim 1, characterized in that: In step S12, the formula for calculating the rotational speed fluctuation frequency is as follows: f2 = 1 / T; Where f2 is the rotational speed fluctuation frequency; T is the period of rotational speed fluctuation.

6. The method for diagnosing engine misfire in a hybrid vehicle according to claim 5, characterized in that: In step 14, the frequency ratio threshold range is: ];in, Let Δ be the number of all combinations of taking i elements from K distinct elements; K is the number of engine cylinders; i is 1, 2, 3, ..., K; Δ is the sampling and calculation bias.

7. The method for diagnosing engine misfire in a hybrid vehicle according to claim 2, characterized in that: Step S33, calculating the actual excess air coefficient before rapid fuel self-learning correction, specifically involves: λ = λ1 * a; Where: λ is the actual excess air coefficient before the fast fuel self-learning value correction; λ1 is the actual excess air coefficient; and a is the fast fuel self-learning value.

8. The method for diagnosing engine misfire in a hybrid vehicle according to claim 7, characterized in that: Step S34, calculating the difference between the actual excess air coefficient before correction and the target excess air coefficient, specifically involves: D λ =λ-λ set ; Where, Δ λ λ is the difference between the actual excess air coefficient before correction and the target excess air coefficient; set The target excess air coefficient.

9. A misfire diagnosis system for a hybrid electric vehicle, characterized in that, It includes a controller and a memory, wherein the memory stores a computer-readable program that, when invoked by the controller, can perform the steps of the engine misfire diagnosis method for a hybrid vehicle as described in any one of claims 1 to 8.

10. A vehicle, characterized in that: The engine misfire diagnosis system for hybrid vehicles as described in claim 9 is adopted.

11. A storage medium, characterized in that: It contains a computer-readable program that, when invoked, can perform the steps of the engine misfire diagnosis method for a hybrid vehicle as described in any one of claims 1 to 8.

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