Optimization control method for closed-loop enabling of EGR (Exhaust Gas Recirculation) system

Abstract

The invention relates to an optimization control method for closed-loop enabling of an EGR (exhaust gas recirculation) system. The optimization control method comprises the following steps: determining whether an EGR closed-loop enabling minimum EGR rate condition is met or not; if the EGR closed-loop enabling minimum EGR rate condition is met, whether the engine rotating speed, the air inlet temperature, the engine water temperature, the atmospheric temperature and the atmospheric pressure meet preset conditions or not is judged, and if the preset conditions are met, EGR closed-loop control is conducted; and the preset conditions of the atmospheric temperature and the atmospheric pressure are updated in a self-learning mode. According to the method, the EGR enabling threshold values of the atmospheric temperature and the atmospheric pressure are optimized and learned, so that the EGR rate control stability during EGR closed-loop is improved, and the EGR closed-loop control performance is improved.

Description

Technical Field

[0001] The invention relates to the field of engine control, and more particularly to an optimization control method for closed-loop enabling of an EGR system. Background Art

[0002] Exhaust gas recirculation (EGR) takes exhaust gas from the exhaust and enters the intake system. Studies have shown that the EGR system has certain advantages in improving emissions, reducing fuel consumption and improving anti-knock capabilities. The control of the mixing valve in the low-pressure EGR system is particularly important as it improves the effect of the EGR rate. The closed-loop enabling control condition parameters of the existing EGR system are fixed, resulting in poor stability in the EGR rate control. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide an optimized control method for closed-loop enabling of an EGR system, which can improve the EGR closed-loop control performance.

[0004] The technical solution adopted by the present invention to solve the technical problem is: constructing an optimization control method for closed-loop enabling of an EGR system, comprising:

[0005] Determine whether the minimum EGR rate condition for enabling EGR closed loop is met;

[0006] If the EGR closed-loop enabling minimum EGR rate condition is met, it is determined whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions. If the preset conditions are met, EGR closed-loop control is performed;

[0007] The preset conditions of atmospheric temperature and atmospheric pressure are updated by self-learning.

[0008] According to the above scheme, the method for determining whether the atmospheric temperature meets the preset conditions includes:

[0009] If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered. It is necessary to ensure that the minimum atmospheric temperature is not lower than the minimum atmospheric temperature. AmbTempMinEnbl , T AmbTempMin Enbl =C1×(1+r AmbTempMin EnblLrn ), where C1 is the initial value, r AmbTempMinEnblLrn To enable minimum atmospheric temperature learning coefficient;

[0010] If the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires ensuring that the temperature is lower than the minimum atmospheric temperature, that is, the exit enabling minimum atmospheric temperature T AmbTempMinDsbl , T AmbTempMin Dsbl =C2×(1+r AmbTempMin DsblLrn ), where C2 is the initial value, r AmbTempMinDsblLrn To exit enable the minimum atmospheric temperature learning coefficient;

[0011] If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered. It is necessary to ensure that the maximum atmospheric temperature does not exceed the maximum atmospheric temperature. AmbTempMaxEnbl , T AmbTempMax Enbl =C3×(1+r AmbTempMax EnblLrn ), where C3 is the initial value, r AmbTempMaxEnblLrn To enable learning coefficients for maximum atmospheric temperature;

[0012] If the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires that the maximum atmospheric temperature be exceeded, i.e., the exit-enabled maximum atmospheric temperature T AmbTempMaxDsbl , T AmbTempMax Dsbl =C4×(1+r AmbTempMax DsblLrn ), where C4 is the initial value, r AmbTempMaxDsblLrn Enable the maximum atmospheric temperature learning coefficient for exit.

[0013] According to the above scheme, the method for determining whether the atmospheric pressure meets the preset conditions includes:

[0014] The atmospheric pressure exceeds the preset minimum atmospheric pressure p AmbPreMinEnbl =D1×(1+r AmbPreMinEnblLrn ), then the EGR closed loop enabling condition is allowed, D1 is the initial value, r AmbPreMinEnblLrn To enable minimum atmospheric pressure learning coefficient;

[0015] The atmospheric temperature is lower than the preset exit enabling minimum atmospheric pressure p AmbPreMinDsbl =D2×(1+r AmbPreMinDsblLrn ), then it is necessary to exit the EGR closed loop enabling condition, D2 is the initial value, r AmbPreMinDsblLrn Enable minimum atmospheric pressure learning coefficient for exit.

[0016] According to the above scheme, the method of updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning includes:

[0017] If the atmospheric temperature meets the minimum atmospheric temperature T within the time t0 AmbTempMinEnbl The difference between the atmospheric pressure and the preset minimum atmospheric pressure p does not exceed the preset value, and the atmospheric pressure is AmbPreMinEnbl The difference exceeds the preset value;

[0018] Read the average atmospheric temperature T during time t0 AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg0 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial0 ;

[0019] Update and learn the average atmospheric temperature T of the working condition AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 The minimum atmospheric temperature learning coefficient is enabled and the minimum atmospheric temperature learning coefficient is disabled at the same time.

[0020] According to the above scheme, update the minimum atmospheric temperature learning coefficient r AmbTempMinEnblLrn and exit to enable the minimum atmospheric temperature learning coefficient r AmbTempMinDsblLrn The methods include:

[0021] If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≥0.03, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.05, where r AmbTempMinEnblLrn (z) is the learning value updated by the last self-learning;

[0022] If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≥0.03, and the number of consecutive times CNT0 exceeds the preset number, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.01, r AmbTempMinDsblLrn =r AmbTempMinDsblLrn (z)+0.1, and clear CNT0 to zero, where r AmbTempMinDsblLrn (z) is the learning value updated by the last self-learning;

[0023] If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≤0.01, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z) -0.01;

[0024] If | r EGRErrAvg0 |≤|r EGRErrInitial0 |≤0.01, and the number of consecutive times CNT1 exceeds the preset number, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)-0.005, r AmbTempMinDsblLrn =r AmbTempMinDsblLrn (z) -0.05, and CNT1 is cleared to zero;

[0025] In other cases, r AmbTempMinEnblLrn and r AmbTempMinDsblLrn Not updated.

[0026] According to the above scheme, the method for updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning also includes:

[0027] If the maximum atmospheric temperature T is met within t0 AmbTempMaxEnbl The difference between the atmospheric temperature and the preset value does not exceed the preset value, and the atmospheric pressure is equal to the preset minimum atmospheric pressure p AmbPreMinEnbl The difference exceeds the preset value;

[0028] Read the average atmospheric temperature T during time t0 AmbTempAvg1 , average atmospheric pressure p AmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg1 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial1 ;

[0029] Update and learn the average atmospheric temperature T of the working condition AmbTempAvg1 , average atmospheric pressure p AmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 The maximum atmospheric temperature learning coefficient is enabled and the maximum atmospheric temperature learning coefficient is disabled at the same time.

[0030] According to the above scheme, update the maximum atmospheric temperature learning coefficient r AmbTempMaxEnblLrn and exit to enable the maximum atmospheric temperature learning coefficient r AmbTempMaxDsblLrn The methods include:

[0031] If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.03, where r AmbTempMaxEnblLrn (z) is the learning value updated by the last self-learning;

[0032] If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, and the number of consecutive times CNT2 exceeds the preset number, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.005, r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn (z)+0.08, where r AmbTempMaxDsblLrn (z) is the learning value updated by the last self-learning;

[0033] If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≤0.01, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z) -0.005;

[0034] If | r EGRErrAvg1 |≤|r EGRErrInitial1|≤0.01, and the number of consecutive times CNT3 exceeds the preset number, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)-0.003, r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn (z) -0.03;

[0035] In other cases, r AmbTempMaxEnblLrn and r AmbTempMaxDsblLrn Not updated.

[0036] According to the above scheme, the method for updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning also includes:

[0037] If the maximum atmospheric temperature T is met within t0 AmbTempMaxEnbl The difference between the atmospheric temperature and the ambient temperature exceeds the preset value, and the atmospheric temperature is equal to the minimum atmospheric temperature T AmbTempMinEnbl The difference between the atmospheric pressure and the preset minimum atmospheric pressure p AmbPreMinEnbl The difference does not exceed the preset value;

[0038] Read the average atmospheric temperature T during time t0 AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial2 ;

[0039] Update and learn the average working air temperature T AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 The minimum atmospheric pressure learning coefficient enabled and the minimum atmospheric pressure learning coefficient disabled at the same time.

[0040] According to the above scheme, update the minimum atmospheric pressure learning coefficient r AmbPreMinEnblLrn and exit to enable the minimum atmospheric pressure learning coefficient r AmbPreMinDsblLrn The methods include:

[0041] If | r EGRErrAvg2 |≥|r EGRErrInitial2 |≥0.03, then r AmbPreMinEnblLrn =r AmbPreMinEnblLrn (z)+0.02, where r A mb Pr e M in E nbl Lrn(z) is the learning value updated by the last self-learning;

[0042] If | r EGRErrAvg2 |≥|r EGRErrInitial2 |≥0.03, and the number of consecutive times CNT4 exceeds the preset number, then r A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)+0.004,r A mb Pr e M in D sbl L rn=r A mb Pr e M in D sbl L rn(z)+0.06, where r A mb Pr e M in D sbl L rn(z) is the learning value updated by the last self-learning;

[0043] If | r EGRErrAvg2 |≤|r EGRErrInitial2 |≤0.01, then r AmbPreMinEnblLrn =r AmbPreMinEnblLrn (z) -0.004;

[0044] If | r EGRErrAvg2 |≤|r EGRErrInitial2 |≤0.01, and the number of consecutive times CNT5 exceeds the preset number, then r A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)-0.002, r A mb Pr e M in D sbl L rn=r A mb Pr e M inD sbl L rn(z)-0.02;

[0045] In other cases, AmbPreMinEnblLrn and r AmbPreMinDsblLrn Not updated.

[0046] The present invention also provides an optimization control device for closed-loop enabling of an EGR system, comprising:

[0047] A first judgment module is used to determine whether the EGR closed-loop enabling minimum EGR rate condition is met;

[0048] The second judgment module is used to judge whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions, and if the preset conditions are met, the EGR closed-loop control is performed;

[0049] The self-learning module is used to update the preset conditions of the atmospheric temperature and atmospheric pressure by self-learning.

[0050] The present invention also provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a computer program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of the optimization control method for closed-loop enabling of the EGR system.

[0051] The present invention also provides a computer-readable storage medium on which executable instructions are stored. When the instructions are executed by a processor, the processor implements the optimization control method for closed-loop enabling of the EGR system.

[0052] The present invention also provides an automobile provided with the optimization control device for closed-loop enabling of the EGR system.

[0053] The optimization control method for closed-loop enabling of the EGR system of the present invention has the following beneficial effects:

[0054] The present invention optimizes and learns the atmospheric temperature and atmospheric pressure at the EGR enabling threshold value, thereby improving the EGR rate control stability during EGR closed loop, thereby improving the EGR closed loop control performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:

[0056] Figure 1 It is a schematic diagram of the system structure with EGR;

[0057] Figure 2It is a flow chart of the optimization control method of the EGR system closed-loop enabling of the present invention;

[0058] Figure 3 It is a logic block diagram of the optimization control method for closed-loop enabling of the EGR system of the present invention;

[0059] In the figure: 1. Air filter; 2. Mixing valve; 3. Compressor; 4. Throttle; 5. Engine; 6. Turbine; 7. Catalyst; 8. Particulate matter collector; 9. EGR cooler; 10. EGR valve; 11. Temperature sensor; 12. Pressure difference sensor. DETAILED DESCRIPTION

[0060] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described in detail with reference to the accompanying drawings.

[0061] like Figure 1 As shown, the system structure with EGR of the present invention includes: an air filter 1 and a mixing valve 2 connected to the air filter, the mixing valve 2 is used to adjust the pressure at the outlet of the EGR valve 10, increase the pressure difference at both ends of the EGR valve 10, and extend two air flow paths from the mixing valve 2. A compressor 3, a throttle 4 connected to the compressor 3 and an engine 5 connected to the throttle 4 are provided on one of the air flow paths of the mixing valve 2, which are used to compress fresh air for supercharging. A turbine 6 connected to the engine 5 is used to control the opening of the exhaust gas bypass valve. A catalyst 7 connected to the turbine 6 and a particle collector 8 connected to the catalyst 7. An EGR cooler 9 installed on another air flow path of the mixing valve 2 is used to receive and cool the exhaust gas output by the particle collector 8 to increase the exhaust gas flow. The EGR valve 10 connected to the EGR cooler 9 at one end and the mixing valve 2 at the other end is used to control the exhaust gas flow entering the cylinder. A temperature sensor 11 installed between the EGR valve 10 and the EGR cooler 9 is used to detect the temperature of the exhaust gas entering the EGR valve 10. The differential pressure sensor 12 connected to the EGR valve 10 is used to detect the pressure at the inlet and outlet of the EGR valve 10 .

[0062] Embodiment 1

[0063] like Figure 2-3 As shown, the present invention provides an optimization control method for closed-loop enabling of an EGR system, comprising the following steps:

[0064] S1. Determine whether the minimum EGR rate condition for enabling EGR closed loop is met.

[0065] When the difference between the target EGR rate and the minimum EGR rate is greater than the preset value A, which is 0.02 in this example, the EGR closed loop enables the minimum EGR rate condition to be met. The minimum EGR rate can be found in Chinese patent CN115585070A "Minimum EGR rate adjustment method, device, equipment and storage medium".

[0066] When the difference between the target EGR rate and the minimum EGR rate is not greater than the preset value B, which is 0.01 in this example; and the absolute value of the difference between the target EGR rate and the actual EGR rate is not greater than the preset value, which is 0.1 in this example; then the EGR closed loop enabling minimum EGR rate condition is not met;

[0067] In other cases, the EGR closed loop enabling minimum EGR rate condition maintains the previous state. When the vehicle is powered on, it is the default state, and the default state is that the EGR closed loop enabling minimum EGR rate condition is not met.

[0068] S2. If the minimum EGR rate condition for EGR closed loop enabling is met, determine whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions. If the preset conditions are met, perform EGR closed loop control. The specific conditions for determining EGR closed loop enabling are as follows:

[0069] (1) No faults related to the EGR system components occur;

[0070] (2) No fuel cut request occurs and the fuel cut recovery time exceeds the preset time, which is 0.3s in this example;

[0071] (3) The minimum EGR rate condition for EGR closed loop is met;

[0072] (4) The engine speed is within a preset speed range, which in this example is 750 rpm to 5500 rpm;

[0073] (5) The intake air temperature is within the preset range. If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered, and the minimum intake air temperature must be no less than 10°C. If the current state is that the EGR closed loop is enabled, then the EGR system closed loop enabled state must be exited, and the minimum intake air temperature must be 7°C. If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered, and the maximum intake air temperature must be no more than 60°C. If the current state is that the EGR closed loop is enabled, then the EGR system closed loop enabled state must be exited, and the maximum intake air temperature must be exceeded by 65°C.

[0074] (6) The engine water temperature is within the preset range. If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered, and the minimum water temperature must be no less than 60°C. If the current state is that the EGR closed loop is enabled, then the EGR system closed loop enabled state must be exited and the minimum water temperature must be less than 55°C. If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered, and the maximum water temperature must be no more than 115°C. If the current state is that the EGR closed loop is enabled, then the EGR system closed loop enabled state must be exited and the maximum water temperature must be exceeded by 120°C.

[0075] (7) The atmospheric temperature is within the preset range. If the current state is that the EGR closed loop is not enabled, the EGR closed loop state is entered. It is necessary to ensure that the atmospheric temperature is not lower than the minimum atmospheric temperature, that is, the minimum atmospheric temperature T AmbTempMinEnbl , T AmbTempMin Enbl =C1×(1+r AmbTempMin EnblLrn ), where C1 in this example is 5°C, r AmbTempMinEnblLrn To enable the minimum atmospheric temperature learning coefficient, the default value is 0, which can be continuously learned and saved after the vehicle is powered off; if the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires ensuring that the temperature is lower than the minimum atmospheric temperature, that is, exiting the enabled minimum atmospheric temperature T AmbTempMinDsbl , T AmbTempMin Dsbl =C2×(1+r AmbTempMin DsblLrn ), where C2 in this example is 3°C, r AmbTempMinDsblLrn To exit the minimum atmospheric temperature learning coefficient, the default value is 0, which can be continuously learned and saved after the vehicle is powered off; if the current state is that the EGR closed loop is not enabled, it enters the EGR closed loop state, and it is necessary to ensure that the maximum atmospheric temperature does not exceed the maximum atmospheric temperature. AmbTempMaxEnbl , T AmbTempMax Enbl =C3×(1+r AmbTempMax EnblLrn ), where C3 in this example is 55°C, r AmbTempMaxEnblLrn To enable the maximum atmospheric temperature learning coefficient, the default value is 0, which can be continuously learned and saved after the vehicle is powered off; if the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires ensuring that the maximum atmospheric temperature exceeds the maximum atmospheric temperature, that is, exiting the enabled maximum atmospheric temperature T AmbTempMaxDsbl , TAmbTempMaxDsbl＝C4× ( 1+rAmbTempMaxDsblLrn ), where C4 in this example is 60°C, r AmbTempMaxDsblLrn To exit and enable the maximum atmospheric temperature learning coefficient, the default value is 0, which can be learned continuously and saved after the vehicle is powered off;

[0076] (8) The atmospheric pressure exceeds the preset minimum atmospheric pressure p AmbPreMinEnbl , p AmbPreMinEnbl =D1×(1+r AmbPreMinEnblLrn ), allowing the EGR closed loop to be enabled. In this example, D1 is 66 kPa, r AmbPreMinEnblLrn To enable the minimum atmospheric pressure learning coefficient, the default value is 0, which can be continuously learned and saved after the vehicle is powered off; the atmospheric temperature is lower than the preset exit enabling minimum atmospheric pressure p AmbPreMinDsbl , p AmbPreMinDsbl =D2×(1+r AmbPreMinDsblLrn ), it is necessary to exit the EGR closed loop enabling condition. In this example, D2 is 64kPa, r AmbPreMinDsblLrnTo exit and enable the minimum atmospheric pressure learning coefficient, its default value is 0, which can be learned continuously and saved after the vehicle is powered off.

[0077] The EGR closed loop is enabled only when the above conditions (1) to (8) are met at the same time. If the EGR closed loop is not enabled, the EGR actuator does not work.

[0078] S3. Update the preset conditions of atmospheric temperature and atmospheric pressure through self-learning. The following is a detailed description of enabling the minimum atmospheric temperature learning coefficient r AmbTempMinEnblLrn , exit and enable the minimum atmospheric temperature learning coefficient r AmbTempMinDsblLrn , Enable the maximum atmospheric temperature learning coefficient r AmbTempMaxEnblLrn , exit and enable the maximum atmospheric temperature learning coefficient r AmbTempMaxDsblLrn , Enable minimum atmospheric pressure learning coefficient r AmbPreMinEnblLrn , Exit to enable the minimum atmospheric pressure learning coefficient r AmbPreMinDsblLrn The self-learning acquisition method, with a default value of 0, can be continuously updated through self-learning and can be saved after the vehicle is powered off.

[0079] First, the following conditions must be met:

[0080] (1) The EGR system is in the closed-loop enabled state;

[0081] (2) When the EGR system enters the closed-loop state, the difference between the target EGR rate and the minimum EGR rate exceeds the preset value E (E in this example is 0.05) to ensure that the EGR rate is large enough to avoid the learning accuracy being affected by the EGR rate being too small;

[0082] (3) Engine speed fluctuation is within ±15 rpm;

[0083] (4) The density of the air entering the cylinder fluctuates within ±25mg / l

[0084] (5) The target boost pressure fluctuation is ±2 kPa;

[0085] (6) The difference between the target boost pressure and the actual boost pressure is within ±2 kPa;

[0086] (7) The mixing valve opening fluctuation range is within ±1%;

[0087] (8) The target EGR rate fluctuation is within a preset range, which is ±0.01 in this example;

[0088] (9) The EGR valve inlet temperature fluctuation range is within ±5°C.

[0089] (10) The atmospheric temperature fluctuation range is within ±1°C;

[0090] (11) The atmospheric pressure fluctuation range is within ±0.5 kPa;

[0091] When all the above conditions are met for a period exceeding the preset time t0, in this example t0 is 1s, there are four cases as follows.

[0092] In the first mode, if all of the following conditions (1) and (2) are satisfied within t0:

[0093] (1) Atmospheric temperature and enabling minimum atmospheric temperature T AmbTempMinEnbl The difference does not exceed the preset value, which is 1°C in this example;

[0094] (2) Atmospheric pressure and preset minimum atmospheric pressure p AmbPreMinEnbl The difference exceeds the preset value, which is 4 kPa in this example.

[0095] Read the average atmospheric temperature T during time t0 AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg0 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial0 The initial value refers to the difference between the target EGR rate and the actual EGR rate when the first condition is just enabled.

[0096] Update only the learning condition, that is, the average atmospheric temperature T AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 When the learning coefficient is the same, other working conditions will not be updated.

[0097] If it appears:

[0098] A. | r EGRErrAvg0| ≥|r EGRErrInitial0 |≥0.03, that is, the EGR rate deviation is increasing, indicating that the EGR closed-loop enabling conditions need to be strict at this time, and the minimum enabling atmospheric temperature needs to be appropriately increased. AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.05, where r AmbTempMinEnblLrn (z) is the learning value of the last self-learning update.

[0099] B. |r EGRErrAvg0 |≥|r EGRErrInitial0 |≥0.03, and the number of consecutive times CNT0 exceeds the preset number, which is 5 in this example, that is, the EGR rate control accuracy, that is, the EGR rate deviation, has been increasing, indicating that the EGR closed-loop enabling conditions need to be more stringent at this time, and the minimum enabling atmospheric temperature needs to be appropriately increased. AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.01, rAmbTempMinDsblLrn =r AmbTempMinDsblLrn (z)+0.1, and clear CNT0 to zero, where r AmbTempMinDsblLrn (z) is the learning value of the last self-learning update. The default value of CNT0 is 0, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if the B condition is not met in the first case, but other conditions are met, CNT0 is also not accumulated. CNT0 is updated at most once each time the B condition is met in this mode.

[0100] C.|r EGRErrAvg0 |≤|r EGRErrInitial0 |≤0.01, that is, the EGR rate deviation is very small, indicating that the EGR closed-loop enabling conditions can be appropriately less stringent at this time, and the enabling minimum atmospheric temperature can be appropriately lowered. AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)-0.01.

[0101] D. |r EGRErrAvg0 |≤|r EGRErrInitial0 |≤0.01, and the number of times CNT1 is continuously satisfied exceeds the preset number, which is 5 in this example, that is, the EGR rate deviation has been very small, indicating that the conditions for entering the EGR closed loop can be widened, and the minimum atmospheric temperature for enabling needs to be further reduced. AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)-0.005, r AmbTempMinDsblLrn =r AmbTempMinDsblLrn (z)-0.05, and clear CNT1; the default value of CNT1 is 1, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if the D condition is not met in the first case, but other conditions are met, CNT1 is also not accumulated. CNT1 is updated at most once each time the D condition is met in this case.

[0102] E. In other cases, r AmbTempMinEnblLrn 、r AmbTempMinDsblLrn None are updated.

[0103] The second mode is if all of the following conditions (1) and (2) are satisfied within t0:

[0104] (1) Enable the maximum atmospheric temperature T AmbTempMaxEnbl The difference with the atmospheric temperature does not exceed the preset value, which is 1°C in this example;

[0105] (2) Atmospheric pressure and preset minimum atmospheric pressure p AmbPreMinEnbl The difference exceeds the preset value, which is 4 kPa in this example.

[0106] Read the average atmospheric temperature T during time t0 AmbTempAvg1 , average atmospheric pressure pAmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg1 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial1 The initial value refers to the difference between the target EGR rate and the actual EGR rate when the second mode is just satisfied.

[0107] Update only the learning condition, that is, the average atmospheric temperature T AmbTempAvg1 , average atmospheric pressure p AmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 When the learning coefficient is the same, other working conditions will not be updated.

[0108] If it appears:

[0109] A. |r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, that is, the EGR rate control accuracy (EGR rate deviation) has been increasing, indicating that the EGR closed-loop enabling conditions need to be more stringent at this time, and the maximum enabling atmospheric temperature needs to be appropriately increased. AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.03. The reason why this update rate is lower than that in the first mode A is that the engine is prone to knock when the atmospheric temperature is high. At this time, it is easier to allow EGR to be enabled, thereby suppressing the tendency of knock. AmbTempMaxEnblLrn (z) is the previous learning value.

[0110] B. |r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, and the number of consecutive satisfaction times CNT2 exceeds the preset number (5 in this example), that is, the EGR rate control accuracy has been increasing, indicating that the EGR closed-loop enabling conditions need to be more stringent at this time, then it is necessary to further increase the enabling maximum atmospheric temperature, and clear CNT2. The default value of CNT2 is 0, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if it is not the case that condition B in the second mode is met at this time, but other conditions are met, CNT2 is also not accumulated. CNT2 is updated at most once each time condition B is met in this mode.

[0111] r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.005. The reason why this update rate is lower than that in the first mode B is that the engine is prone to knock when the atmospheric temperature is high. At this time, it is easier to allow EGR to be enabled, thereby suppressing the tendency of knock.

[0112] r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn(z)+0.08. The reason why this update rate is lower than that in the first mode B is that the engine is prone to knock when the atmospheric temperature is high. At this time, it is easier to allow EGR to be enabled, thereby suppressing the tendency of knock. AmbTempMaxDsblLrn (z) is the previous learning value.

[0113] C.|r EGRErrAvg1 |≤|r EGRErrInitial1 |≤0.01, that is, the EGR rate control deviation is very small, indicating that the EGR closed-loop enabling conditions can be widened at this time, and the enabling maximum atmospheric temperature can be appropriately reduced. AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z) -0.005. The reason why this update rate is lower than that of the first mode C is that the engine is prone to knock when the atmospheric temperature is high, and at this time, EGR can be more easily enabled, thereby suppressing the tendency of knock.

[0114] D. |r EGRErrAvg1 |≤|r EGRErrInitial1 |≤0.01, and the number of times CNT3 is continuously satisfied exceeds the preset number, which is 5 in this example, that is, the EGR rate deviation has been very small, indicating that the conditions for entering the EGR closed loop can be further broadened, and the maximum atmospheric temperature can be appropriately reduced. AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)-0.003, r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn (z)-0.03, and clear CNT3; the default value of CNT3 is 1, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if it is not the D condition in the second mode that is satisfied at this time, but other conditions are satisfied, CNT3 is also not accumulated. CNT3 is updated at most once each time the B condition is satisfied in this mode.

[0115] E. In other cases, r AmbTempMaxEnblLrn 、r AmbTempMaxDsblLrn None are updated.

[0116] The third mode is if all of the following conditions (1) and (2) are satisfied within t0:

[0117] (1) Enable the maximum atmospheric temperature T AmbTempMaxEnbl The difference with the atmospheric temperature does not exceed the preset value, which is 2°C in this example;

[0118] (2) Atmospheric temperature and enabling minimum atmospheric temperature T AmbTempMinEnbl The difference exceeds the preset value, which is 2℃ in this example;

[0119] (3) Atmospheric pressure and preset minimum atmospheric pressure p AmbPreMinEnbl The difference does not exceed the preset value, which is 2kPa in this example.

[0120] Read the average atmospheric temperature T during time t0 AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial2 , the initial value refers to the difference between the target EGR rate and the actual EGR rate when the third mode is just satisfied.

[0121] Update only the learning condition, that is, the average atmospheric temperature T AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 The learning coefficient is the same when the other operating conditions are not updated. The reason why this update rate is lower than the update rate of the second mode is that the influence of atmospheric pressure on the EGR system is relatively small.

[0122] If it appears:

[0123] A. |r EGRErrAvg2 |≥|r EGRErrInitial2 |≥0.03, that is, the EGR rate control accuracy has been increasing, indicating that the EGR closed-loop enabling conditions need to be more stringent at this time, and the minimum enabling atmospheric pressure needs to be appropriately increased. A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)+0.02,r A mb Pr e M in E nbl L rn(z) is the previous learning value.

[0124] B. |r EGRErrAvg2 |≥|r EGRErrInitial2|≥0.03, and the number of consecutive satisfactions CNT4 exceeds the preset number (5 in this example), that is, the EGR rate control accuracy has been increasing, indicating that the EGR closed-loop enabling conditions need to be more stringent at this time, and the minimum enabling atmospheric pressure needs to be appropriately increased. The default value of CNT4 is 0, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if it is not the case of B in the third mode that is satisfied at this time, but other conditions are satisfied, CNT4 is also not accumulated. CNT4 is updated at most once each time condition B is satisfied in this mode.

[0125] r A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)+0.004,r A mb Pr e M in D sbl L rn=r A mb Pr e M in D sbl L rn(z)+0.06,

[0126] r A mb Pr e M in D sbl L rn(z) is the last learned value, and CNT4 is cleared.

[0127] C.|r EGRErrAvg2 |≤|r EGRErrInitial2 |≤0.01, that is, the EGR rate deviation is small, indicating that the conditions for entering the EGR closed loop can be widened, and the minimum atmospheric temperature for enabling can be appropriately lowered. A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)-0.004.

[0128] D. |r EGRErrAvg2 |≤|r EGRErrInitial2|≤0.01, and the number of times CNT5 is met continuously exceeds the preset number, which is 5 in this example, that is, the EGR rate deviation has been very small, indicating that the conditions for entering the EGR closed loop can be further widened, and the minimum atmospheric pressure for enabling can be further reduced. A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)-0.002, r A mb Pr e M in D sbl L rn=r A mb Pr e M in D sbl L rn(z)-0.02, and CNT5 is cleared; the default value of CNT5 is 1, which can be continuously updated and saved after the vehicle is powered off. Continuous satisfaction means that if it is not the D condition in the third mode that is satisfied at this time, but other conditions are satisfied, CNT5 is also not accumulated. CNT5 is updated at most once each time the B condition is satisfied in this mode.

[0129] E. In other cases, r AmbPreMinEnblLrn 、r AmbPreMinDsblLrn None are updated.

[0130] In the fourth case, i.e., the other cases, no learning coefficients are updated.

[0131] Embodiment 2

[0132] The present invention further provides an optimization control device for closed-loop enabling of an EGR system according to a second embodiment, comprising:

[0133] A first judgment module is used to determine whether the EGR closed-loop enabling minimum EGR rate condition is met;

[0134] The second judgment module is used to judge whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions, and if the preset conditions are met, the EGR closed-loop control is performed;

[0135] The self-learning module is used to update the preset conditions of the atmospheric temperature and atmospheric pressure by self-learning.

[0136] Embodiment 3

[0137] The present invention also provides an automobile, comprising the optimization control device for closed-loop enabling of the EGR system of the second embodiment.

[0138] Embodiment 4

[0139] The present invention also provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a computer program is stored in the memory, and when the program is executed by the processor, the processor executes the steps of the optimization control method for closed-loop enabling of the EGR system of the second embodiment.

[0140] Embodiment 5

[0141] The present invention also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the optimization control method for closed-loop enabling of the EGR system of the second embodiment.

[0142] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0143] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0144] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0146] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. An optimization control method for closed-loop enabling of an EGR system, characterized in that: include: Determine whether the minimum EGR rate condition for enabling EGR closed loop is met; If the EGR closed-loop enabling minimum EGR rate condition is met, it is determined whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions. If the preset conditions are met, EGR closed-loop control is performed; The preset conditions of atmospheric temperature and atmospheric pressure are updated by self-learning.

2. The optimization control method for closed-loop enabling of the EGR system according to claim 1, characterized in that: Methods for determining whether the atmospheric temperature meets the preset conditions include: If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered. It is necessary to ensure that the minimum atmospheric temperature is not lower than the minimum atmospheric temperature. AmbTempMinEnbl , T AmbTempMinEnbl =C1×(1+r AmbTempMinEnblLrn ), where C1 is the initial value, r AmbTempMinEnblLrn To enable minimum atmospheric temperature learning coefficient; If the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires ensuring that the temperature is lower than the minimum atmospheric temperature, that is, the exit enabling minimum atmospheric temperature T AmbTempMinDsbl , T AmbTempMinDsbl =C2×(1+r AmbTempMinDsblLrn ), where C2 is the initial value, r AmbTempMinDsblLrn To exit enable the minimum atmospheric temperature learning coefficient; If the current state is that the EGR closed loop is not enabled, then the EGR closed loop state is entered. It is necessary to ensure that the maximum atmospheric temperature does not exceed the maximum atmospheric temperature. AmbTempMaxEnbl , T AmbTempMaxEnbl =C3×(1+r AmbTempMaxEnblLrn ), where C3 is the initial value, r AmbTempMaxEnblLrn To enable learning coefficients for maximum atmospheric temperature; If the current state is the EGR closed-loop enabled state, then exiting the EGR system closed-loop enabled state requires that the maximum atmospheric temperature be exceeded, i.e., the exit-enabled maximum atmospheric temperature T AmbTempMaxDsbl , T AmbTempMaxDsbl =C4×(1+r AmbTempMaxDsblLrn ), where C4 is the initial value, r AmbTempMaxDsblLrn Enable the maximum atmospheric temperature learning coefficient for exit.

3. The optimization control method for closed-loop enabling of the EGR system according to claim 2, characterized in that: Methods for determining whether the atmospheric pressure meets the preset conditions include: The atmospheric pressure exceeds the preset minimum atmospheric pressure p AmbPreMinEnbl =D1×(1+r AmbPreMinEnblLrn ), then the EGR closed loop enabling condition is allowed, D1 is the initial value, r AmbPreMinEnblLrn To enable minimum atmospheric pressure learning coefficient; The atmospheric temperature is lower than the preset exit enabling minimum atmospheric pressure p AmbPreMinDsbl =D2×(1+r AmbPreMinDsblLrn ), then it is necessary to exit the EGR closed loop enabling condition, D2 is the initial value, r AmbPreMinDsblLrn Enable minimum atmospheric pressure learning coefficient for exit.

4. The optimization control method for closed-loop enabling of the EGR system according to claim 3, characterized in that: The method of updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning includes: If the atmospheric temperature meets the minimum atmospheric temperature T within the time t0 AmbTempMinEnbl The difference between the atmospheric pressure and the preset minimum atmospheric pressure p does not exceed the preset value, and the atmospheric pressure is AmbPreMinEnbl The difference exceeds the preset value; Read the average atmospheric temperature T during time t0 AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg0 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial0 ; Update and learn the average atmospheric temperature T of the working condition AmbTempAvg0 , average atmospheric pressure p AmbTempAvg0 、Target EGR rate average value r EGRDsrdAvg0 The minimum atmospheric temperature learning coefficient is enabled and the minimum atmospheric temperature learning coefficient is disabled at the same time.

5. The optimization control method for closed-loop enabling of the EGR system according to claim 4, characterized in that: Update to enable the minimum atmospheric temperature learning coefficient r AmbTempMinEnblLrn and exit to enable the minimum atmospheric temperature learning coefficient r AmbTempMinDsblLrn The methods include: If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≥0.03, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.05, where r AmbTempMinEnblLrn (z) is the learning value updated by the last self-learning; If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≥0.03, and the number of consecutive times CNT0 exceeds the preset number, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)+0.01, r AmbTempMinDsblLrn =r AmbTempMinDsblLrn (z)+0.1, and clear CNT0 to zero, where r AmbTempMinDsblLrn (z) is the learning value updated by the last self-learning; If | r EGRErrAvg0 |≥|r EGRErrInitial0 |≤0.01, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z) -0.01; If | r EGRErrAvg0 |≤|r EGRErrInitial0 |≤0.01, and the number of consecutive times CNT1 exceeds the preset number, then r AmbTempMinEnblLrn =r AmbTempMinEnblLrn (z)-0.005, r AmbTempMinDsblLrn =r AmbTempMinDsblLrn (z) -0.05, and CNT1 is cleared to zero; In other cases, AmbTempMinEnblLrn and r AmbTempMinDsblLrn Not updated.

6. The optimization control method for closed-loop enabling of the EGR system according to claim 3, characterized in that: The method for updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning also includes: If the maximum atmospheric temperature T is met within t0 AmbTempMaxEnbl The difference between the atmospheric temperature and the preset value does not exceed the preset value, and the atmospheric pressure is equal to the preset minimum atmospheric pressure p AmbPreMinEnbl The difference exceeds the preset value; Read the average atmospheric temperature T during time t0 AmbTempAvg1 , average atmospheric pressure p AmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg1 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial1 ; Update and learn the average atmospheric temperature T of the working condition AmbTempAvg1 , average atmospheric pressure p AmbTempAvg1 、Target EGR rate average value r EGRDsrdAvg1 The maximum atmospheric temperature learning coefficient is enabled and the maximum atmospheric temperature learning coefficient is disabled at the same time.

7. The optimization control method for closed-loop enabling of the EGR system according to claim 6, characterized in that: Update to enable the maximum atmospheric temperature learning coefficient r AmbTempMaxEnblLrn and exit to enable the maximum atmospheric temperature learning coefficient r AmbTempMaxDsblLrn The methods include: If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.03, where r AmbTempMaxEnblLrn (z) is the learning value updated by the last self-learning; If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≥0.03, and the number of consecutive times CNT2 exceeds the preset number, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)+0.005, r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn (z)+0.08, where r AmbTempMaxDsblLrn (z) is the learning value updated by the last self-learning; If | r EGRErrAvg1 |≥|r EGRErrInitial1 |≤0.01, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z) -0.005; If | r EGRErrAvg1 |≤|r EGRErrInitial1 |≤0.01, and the number of consecutive times CNT3 exceeds the preset number, then r AmbTempMaxEnblLrn =r AmbTempMaxEnblLrn (z)-0.003, r AmbTempMaxDsblLrn =r AmbTempMaxDsblLrn (z) -0.03; In other cases, AmbTempMaxEnblLrn and r AmbTempMaxDsblLrn Not updated.

8. The optimization control method for closed-loop enabling of the EGR system according to claim 3, characterized in that: The method for updating the preset conditions of atmospheric temperature and atmospheric pressure by self-learning also includes: If the maximum atmospheric temperature T is met within t0 AmbTempMaxEnbl The difference between the atmospheric temperature and the preset value is exceeded, and the atmospheric temperature is equal to the minimum atmospheric temperature T AmbTempMinEnbl The difference between the atmospheric pressure and the preset minimum atmospheric pressure p AmbPreMinEnbl The difference does not exceed the preset value; Read the average atmospheric temperature T during time t0 AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 and the initial value r of the difference between the target EGR rate and the actual EGR rate EGRErrInitial2 ; Update and learn the average working air temperature T AmbTempAvg2 , average atmospheric pressure p AmbTempAvg2 、Target EGR rate average value r EGRDsrdAvg2 , the average value of the difference between the target EGR rate and the actual EGR rate r EGRErrAvg2 The minimum atmospheric pressure learning coefficient enabled and the minimum atmospheric pressure learning coefficient disabled at the same time.

9. The optimization control method for closed-loop enabling of the EGR system according to claim 8, characterized in that: Update the minimum atmospheric pressure learning coefficient r AmbPreMinEnblLrn and exit to enable the minimum atmospheric pressure learning coefficient r AmbPreMinDsblLrn The methods include: If | r EGRErrAvg2 |≥|r EGRErrInitial2 |≥0.03, then r AmbPreMinEnblLrn =r AmbPreMinEnblLrn (z)+0.02, where r A mb Pr e M in E nbl L rn(z) is the learning value updated by the last self-learning; If | r EGRErrAvg2 |≥|r EGRErrInitial2 |≥0.03, and the number of consecutive times CNT4 exceeds the preset number, then r A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)+0.004,r A mb Pr e M in D sbl L rn=r A mb Pr e M in D sbl L rn(z)+0.06, where r A mb Pr e M in D sbl L rn(z) is the learning value updated by the last self-learning; If | r EGRErrAvg2 |≤|r EGRErrInitial2 |≤0.01, then r AmbPreMinEnblLrn =r AmbPreMinEnblLrn (z) -0.004; If | r EGRErrAvg2 |≤|r EGRErrInitial2 |≤0.01, and the number of consecutive times CNT5 exceeds the preset number, then r A mb Pr e M in E nbl L rn=r A mb Pr e M in E nbl L rn(z)-0.002, r A mb Pr e M in D sbl L rn=r A mb Pr e M in D sbl L rn(z)-0.02; In other cases, AmbPreMinEnblLrn and r AmbPreMinDsblLrn Not updated.

10. An optimization control device for closed-loop enabling of an EGR system, characterized in that: include: A first judgment module is used to determine whether the EGR closed-loop enabling minimum EGR rate condition is met; The second judgment module is used to judge whether the engine speed, intake air temperature, engine water temperature, atmospheric temperature and atmospheric pressure meet the preset conditions, and if the preset conditions are met, the EGR closed-loop control is performed; The self-learning module is used to update the preset conditions of the atmospheric temperature and atmospheric pressure by self-learning.

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