Pressurized closed loop end intervention opportunity prediction method, device and equipment and storage medium

Abstract

The invention discloses a pressurization closed loop end intervention opportunity prediction method and device, equipment and a storage medium, and relates to the technical field of vehicle control. According to the method, when the parameters of the supercharging control system do not meet the closed-loop enabling condition any more, the throttle control parameters are obtained in real time, the initial maintaining duration of the supercharging actuator is predicted, the predicted value is corrected in combination with the real-time change trend and quantity of the EGR rate, and therefore the intervention opportunity is accurately determined. According to the process, the control precision is improved, smooth transition from closed-loop control to open-loop control is ensured, different working conditions are adapted by dynamically adjusting the learning coefficient, and the stability of the system is enhanced. Besides, unnecessary fluctuation of engine performance is reduced through accurate control of intervention time, driving experience is optimized, meanwhile, harmful emission is reduced, fuel efficiency is improved, and double improvement of engine performance and environmental protection performance is achieved by integrating the factors.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a method, device, equipment and storage medium for predicting the timing of ending intervention in a boost closed loop. Background Art

[0002] With the increasing global attention to environmental protection and energy efficiency, modern automobile engine technology is facing severe challenges. In order to reduce emissions while maintaining or improving power performance, turbocharging technology and exhaust gas recirculation (EGR) technology have been widely promoted and applied. How to accurately control these systems to ensure that the engine can operate efficiently and environmentally friendly under various working conditions has become an important issue in the automotive industry.

[0003] In modern engines, supercharging technology and EGR system are key technologies to improve efficiency and reduce emissions. The supercharging system increases the engine's power output by increasing the intake volume, while the EGR system reduces nitrogen oxide emissions by reintroducing part of the exhaust gas into the intake system to reduce the combustion temperature. However, the integration of these two technologies brings new control challenges. Especially when the vehicle enters or exits the boost closed-loop control stage, the system needs to accurately determine the intervention timing to ensure a smooth transition between the two different control modes to avoid affecting the engine's performance and driving smoothness due to sudden changes in control parameters. In the boost control system, improper intervention timing may cause a sharp change in engine performance, affect the driving experience, and may even cause damage to the engine.

[0004] Therefore, how to determine the intervention timing in the transition from the engine charging closed-loop control stage to the intervention control stage, so as to ensure the stability and smoothness during the intervention control, is a technical problem that needs to be solved urgently in this field. Solving this problem can significantly improve the control accuracy of the engine, optimize driving performance, reduce emissions, and meet the increasingly stringent environmental regulations. Summary of the invention

[0005] The main purpose of this application is to provide a method, device, equipment and storage medium for predicting the timing of intervention at the end of the boost closed loop, aiming to solve the technical problem of how to determine the timing of intervention in the transition from the engine charging closed loop control stage to the intervention control stage, so as to ensure stability and smoothness during intervention control.

[0006] To achieve the above-mentioned purpose, the present application provides a method for predicting the timing of ending intervention of a boost closed loop, the method comprising the following steps: When the boost control system parameters do not meet the boost closed loop enabling conditions, obtaining the current throttle control parameters; According to the throttle control parameter, a predicted value of the initial maintenance time of the boost actuator at the target opening is obtained; The initial maintenance time prediction value is corrected according to the real-time engine parameters to obtain a maintenance time prediction value.

[0007] Optionally, the boost closed-loop enabling condition includes: If the compressor outlet target pressure of the boost control system is less than the boost pressure lower limit, or the engine speed is less than a preset speed, it is deemed that the boost closed-loop enabling condition is not met.

[0008] Optionally, obtaining the throttle control parameter at the current moment includes: Get the actual throttle outlet pressure and inlet pressure at the current moment; According to the actual outlet pressure and the actual inlet pressure, a ratio of the inlet and outlet pressures is obtained; The inlet and outlet pressure ratio, engine speed and boost actuator target opening are used as throttle control parameters at the current moment.

[0009] Optionally, obtaining the predicted value of the initial maintenance time of the boost actuator at the target opening according to the throttle control parameter includes: According to the actual outlet pressure and the actual inlet pressure, the inlet and outlet pressure difference is obtained; According to the inlet and outlet pressure difference, a pressure difference filter coefficient is obtained; The initial maintenance time prediction value is obtained according to the pressure difference filter coefficient, the engine speed, the inlet and outlet pressure ratio and the maintenance time prediction table.

[0010] Optionally, before obtaining the initial maintenance time prediction value according to the pressure difference filter coefficient, the engine speed and the inlet and outlet pressure ratio, the method further includes: Obtain a test engine of the same specification, and control the test engine to operate according to a preset target opening and a preset speed, wherein the operation mode of the boost control system is a boost closed-loop control mode; When the test engine runs stably, the boost closed-loop control is terminated, and the throttle outlet pressure data and the throttle inlet pressure data of the boost control system after the boost closed-loop control is terminated are acquired; According to the throttle outlet pressure data and the throttle inlet pressure data, a maintenance time test value at a preset target opening and a preset speed is obtained; A maintenance time prediction table is obtained according to the preset target opening, the preset rotation speed and the maintenance time test value.

[0011] Optionally, obtaining a maintenance time test value at a preset target opening and a preset speed according to the throttle outlet pressure data and the throttle inlet pressure data includes: According to the throttle outlet pressure data and the throttle inlet pressure data, the outlet pressure change rate, the inlet pressure change rate and the initial pressure difference are obtained; Determining a pressure change threshold value according to the initial pressure difference; When the outlet pressure change rate and / or the inlet pressure change rate is greater than the pressure change threshold, the maintenance time test value is obtained according to the time from the current moment to the moment when the boost closed-loop control is terminated.

[0012] Optionally, the initial maintenance duration prediction value is corrected according to the real-time engine parameters to obtain the maintenance duration prediction value, including: According to the real-time engine parameters, the EGR rate change trend and the EGR rate change amount within a preset sampling time period are obtained; Determining a maintenance time learning coefficient according to the EGR rate change trend and the EGR rate change amount; The initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain a maintenance duration prediction value.

[0013] Optionally, obtaining the EGR rate change trend and the EGR rate change amount within a preset sampling time period according to the real-time engine parameters includes: According to the real-time engine parameters, the engine speed is obtained; Determining the equivalent number of cycles of a preset sampling time period according to the engine speed; When the boost closed-loop enabling condition is not met, obtaining the EGR rate within a preset sampling time period before the time point; According to the EGR rate within the preset sampling time period, the EGR rate change trend and the EGR rate change amount are obtained.

[0014] Optionally, after the initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain the maintenance duration prediction value, the method further includes: Obtaining a modified change amount according to the initial maintenance duration prediction value and the maintenance duration prediction value; Determining a correction parameter of the maintenance duration learning coefficient according to the correction change amount, wherein the correction parameter includes a correction ratio and a data adjustment direction; The maintenance duration learning coefficient is updated and adjusted according to the correction parameter to obtain an adjusted maintenance duration learning coefficient.

[0015] Optionally, determining a correction parameter of the maintenance duration learning coefficient according to the correction change includes: If the correction change is greater than the first correction threshold, the maintenance time learning coefficient is adjusted downward according to the first correction ratio; If the correction change is less than the second correction threshold, the maintenance time learning coefficient is increased according to the second correction ratio; If the corrected change amount is less than the first correction threshold and greater than the second correction threshold, the maintenance duration learning coefficient is adjusted according to a third correction ratio based on the positive or negative nature of the corrected change amount.

[0016] In addition, to achieve the above-mentioned purpose, the present application also provides a boost closed loop end intervention timing prediction device, the boost closed loop end intervention timing prediction device comprising: A data acquisition module, used to obtain the throttle control parameters at the current moment when the boost control system parameters do not meet the boost closed loop enabling conditions; A data processing module, used for obtaining a predicted value of the initial maintenance time of the boost actuator at a target opening according to the throttle control parameter; The data processing module is also used to correct the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

[0017] In addition, to achieve the above-mentioned purpose, the present application also provides a boost closed-loop intervention end timing prediction device, the device comprising: a memory, a processor, and a boost closed-loop intervention end timing prediction program stored on the memory and executable on the processor, the boost closed-loop intervention end timing prediction program being configured to implement the steps of the boost closed-loop intervention end timing prediction method as described above.

[0018] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, on which is stored a boost closed-loop intervention end timing prediction program, and when the boost closed-loop intervention end timing prediction program is executed by a processor, the steps of the boost closed-loop intervention end timing prediction method as described above are implemented.

[0019] The present application obtains the throttle control parameters at the current moment when the boost control system parameters do not meet the boost closed-loop enabling conditions; obtains the initial maintenance time prediction value of the boost actuator at the target opening according to the throttle control parameters; and corrects the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

[0020] In summary, this application obtains the throttle control parameters in real time and predicts the initial maintenance time of the boost actuator when the boost control system parameters no longer meet the closed-loop enabling conditions, and then corrects the predicted value in combination with the real-time change trend and amount of the EGR rate, thereby accurately determining the intervention timing. This process not only improves the control accuracy and ensures a smooth transition from closed-loop to open-loop control, but also enhances the stability of the system by dynamically adjusting the learning coefficient to adapt to different working conditions. In addition, precise control reduces unnecessary fluctuations in engine performance, optimizes the driving experience, reduces harmful emissions, and improves fuel efficiency. Combining these factors, a dual improvement in engine performance and environmental performance is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0023] Figure 1 This is a flow chart of the first embodiment of the method for predicting the timing of ending intervention in a boost closed loop of the present application; Figure 2 This is a flow chart of a second embodiment of the method for predicting the timing of ending intervention in a boost closed loop of the present application; Figure 3 This is a flow chart of a third embodiment of the method for predicting the timing of ending intervention in a boost closed loop of the present application; Figure 4 This is a schematic diagram of the functional modules of the boost closed loop end intervention timing prediction device of this application; Figure 5 It is a structural diagram of a terminal device in the hardware operating environment involved in the embodiment of the present application.

[0024] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0026] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0027] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a boost closed loop end intervention timing prediction device, etc. The following takes the boost closed loop end intervention timing prediction device as an example to illustrate this embodiment and the following embodiments.

[0028] The present application embodiment provides a method for predicting the timing of the intervention of the boost closed loop end, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the present application.

[0029] In this embodiment, the boost closed loop intervention termination timing prediction method includes: Step S10: When the boost control system parameters do not meet the boost closed-loop enabling conditions, the current throttle control parameters are obtained.

[0030] It should be noted that the boost closed loop enabling condition here refers to: the compressor outlet target pressure of the supercharger assembly is greater than the minimum boost pressure; the engine speed is greater than the preset speed value; the electronic pressure relief valve of the supercharger assembly is not opened. Only when these three conditions are met at the same time can the current boost control system parameters be considered to meet the boost closed loop enabling conditions, that is, the current boost control system has not yet left the boost closed loop control stage.

[0031] It is understandable that when any of the above conditions is not met, the boost system can be considered to be operating by system inertia. At this time, the system needs to predict and determine a suitable intervention time in time to ensure a smooth transition between the end of boost closed-loop control and the intervention of the new control strategy. In this case, the inertial operation of the system may lead to a decrease in control accuracy and fluctuations in engine performance. Therefore, it is particularly important to accurately predict the intervention time.

[0032] It should be understood that by real-time monitoring of throttle control parameters, including throttle inlet and outlet pressures, engine speed, and target opening of the boost actuator, the system can evaluate the current operating state and predict the initial maintenance time of the boost actuator at the target opening. Combined with the changing trend and amount of the EGR rate, the system further corrects the predicted value to adapt to the real-time changing engine operating conditions. This dynamic prediction and correction mechanism based on real-time data enables the system to more accurately determine when intervention control is needed, so that at the end of the boost closed-loop control, the control strategy can be adjusted in time to ensure that the engine continues to operate with optimal performance and lowest emissions.

[0033] Step S20: obtaining a predicted value of the initial maintenance time of the boost actuator at the target opening according to the throttle control parameter.

[0034] It should be noted that the predicted value of the initial maintenance time of the boost actuator at the target opening refers to the maintenance time of the current boost actuator opening still maintained at the actuator target opening when it is out of closed-loop control, that is, the total maintenance time of the actuator target opening in the last sampling cycle of the boost closed-loop condition. The initial value of this time is counted from the first sampling cycle when the boost closed-loop condition is not met.

[0035] It can be understood that the maintenance time of the boost actuator is based on the current control parameters and the engine state, which is equivalent to a specific result of a complex system operating according to certain initial conditions. This embodiment indirectly estimates the time that the boost actuator can maintain a stable working state at the target opening through a plurality of throttle control parameters, thereby determining the most suitable time point for intervention control.

[0036] It should be understood that the throttle control parameters that affect the maintenance time include the actual throttle outlet pressure, the actual inlet pressure, the engine speed and the target opening of the boost actuator at the time of exiting the boost closed-loop control. These parameters jointly determine the length of time the boost actuator can maintain a stable working state at the current opening. The ratio of the two pressure values, the actual throttle outlet pressure and the actual inlet pressure, reflects the flow characteristics of the throttle and the current intake efficiency. The change in the pressure ratio directly affects the target opening that the boost actuator needs to maintain in order to maintain the required intake pressure. The engine speed is the factor that affects the intake volume and combustion. The key factor of efficiency is that the engine has different requirements for intake pressure at different speeds. The predicted value of the maintenance time needs to be adjusted according to the current speed. It is understandable that under the same set of throttle parameters, when the boost closed-loop control is exited, the maintenance time is the same, and can be calibrated one by one through bench tests. Therefore, the initial maintenance time is based on the initial setting of the above parameters when the boost closed-loop control is exited and the calibration test on the engine bench. After obtaining the initial results, it is necessary to further optimize and adjust the predicted time in combination with other parameters on this basis.

[0037] Step S30: According to the real-time engine parameters, the initial maintenance time prediction value is corrected to obtain a maintenance time prediction value.

[0038] It should be noted that the initial maintenance duration prediction value is corrected using the real-time engine parameters to obtain a more accurate maintenance duration prediction value.

[0039] In one embodiment, the initial maintenance duration prediction value is corrected according to the real-time engine parameters to obtain the maintenance duration prediction value, including: obtaining the EGR rate change trend and the EGR rate change amount within a preset sampling time period according to the real-time engine parameters; determining the maintenance duration learning coefficient according to the EGR rate change trend and the EGR rate change amount; and correcting the initial maintenance duration prediction value according to the maintenance duration learning coefficient to obtain the maintenance duration prediction value.

[0040] It is understandable that after exiting the boost closed-loop control, the trend and amount of change of the EGR (exhaust gas recirculation) rate are of great significance in engine management. The amount of change of the EGR rate is calculated by taking the difference between the maximum and minimum values ​​of the EGR rate in multiple sampling cycles near the current moment, and the trend of the EGR change is determined by the order of the maximum and minimum values ​​of the EGR rate in multiple sampling cycles. If the time when the maximum value of the EGR rate occurs is later than the time when the minimum value of the EGR rate occurs, the amount of change of the EGR rate is positive; if the time when the maximum value of the EGR rate occurs is earlier than the time when the minimum value of the EGR rate occurs, the amount of change of the EGR rate is negative; the positive and negative and size of the change of the EGR rate are used to update the predicted value of the optimized maintenance time.

[0041] In one embodiment, the EGR rate change trend and the EGR rate change amount within a preset sampling time period are obtained based on the real-time engine parameters, including: obtaining the engine speed based on the real-time engine parameters; determining the equivalent cycle number of the preset sampling time period based on the engine speed; when the boost closed-loop enabling condition is not met, obtaining the EGR rate within a preset sampling time period before this time point; and obtaining the EGR rate change trend and the EGR rate change amount based on the EGR rate within the preset sampling time period.

[0042] It should be understood that the number of cycles in the overall sampling time is determined by the engine speed. Due to the long EGR pipe, the EGR rate reacts slowly to the influence of pressure. The higher the speed, the longer the overall sampling time is required to maintain data accuracy, that is, the larger the number of equivalent cycles in the sampling time period. For example, when the speed is 1000rpm, the span of the sampling time period is 4 cycles, and each cycle is the preset value of 10ms. When the speed is 2500rpm, the span of the sampling time period is 6 cycles. In this way, the changes in the EGR rate can be accurately monitored.

[0043] In one embodiment, after the initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain the maintenance duration prediction value, it also includes: obtaining a correction change amount according to the initial maintenance duration prediction value and the maintenance duration prediction value; determining correction parameters of the maintenance duration learning coefficient according to the correction change amount, the correction parameters including a correction ratio and a data adjustment direction; updating and adjusting the maintenance duration learning coefficient according to the correction parameters to obtain an adjusted maintenance duration learning coefficient.

[0044] It should be noted that the use of the maintenance time learning coefficient to correct the initial maintenance time prediction value is to obtain a more accurate maintenance time prediction value. The correction principle is to correct the learning coefficient according to the deviation between the actual value of each maintenance time and the predicted value. The learning coefficient is a coefficient of the prediction time, which is used to adjust the prediction time result each time. Since the condition of the vehicle changes with its use, the prediction using the prediction time table set at the factory will gradually become inaccurate as the years of use increase. Therefore, it is chosen to set a learning coefficient and gradually adjust it according to the size of each deviation. This can keep the predicted time close to the actual maintenance time for a longer period of time.

[0045] In one embodiment, after the initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain the maintenance duration prediction value, it also includes: obtaining a correction change amount according to the initial maintenance duration prediction value and the maintenance duration prediction value; if the correction change amount is greater than a first correction threshold, the maintenance duration learning coefficient is adjusted down according to a first correction ratio; if the correction change amount is less than a second correction threshold, the maintenance duration learning coefficient is adjusted up according to a second correction ratio; if the correction change amount is less than the first correction threshold and greater than the second correction threshold, the maintenance duration learning coefficient is adjusted according to a third correction ratio based on the positivity of the correction change amount.

[0046] It should be noted that the formula for the correction process is: tcorrected = toriginal * (1 + rt). Since the conditions for the vehicle to exit the closed-loop control are different each time, the maintenance time learning coefficient rt is additionally added to the original control logic, where the learning of the maintenance time learning coefficient rt is as follows: If tcorrected - toriginal is greater than the preset value (0.5s in this example, it means that the ignition angle efficiency is adjusted too much, which is easy to cause ignition), and the number of consecutive occurrences (the initial value is 0, which can be saved after the vehicle is powered off) exceeds the preset value (5 in this example), it means that the influence of the ignition angle efficiency has caused the duration t to increase continuously. In order to avoid pressure fluctuations during the adjustment process of the ignition angle efficiency, the self-learning state of time t is set to the upward learning state 1, that is, rt needs to be increased proportionally. Similarly, when the influence of the ignition angle efficiency causes the duration t to decrease continuously, it needs to be reduced proportionally. When the difference between the correction result and the original result is not large, the change in the learning rate can be adjusted at a smaller proportion.

[0047] The present application obtains the throttle control parameters at the current moment when the boost control system parameters do not meet the boost closed-loop enabling conditions; obtains the initial maintenance time prediction value of the boost actuator at the target opening according to the throttle control parameters; and corrects the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

[0048] In summary, this application obtains the throttle control parameters in real time and predicts the initial maintenance time of the boost actuator when the boost control system parameters no longer meet the closed-loop enabling conditions, and then corrects the predicted value in combination with the real-time change trend and amount of the EGR rate, thereby accurately determining the intervention timing. This process not only improves the control accuracy and ensures a smooth transition from closed-loop to open-loop control, but also enhances the stability of the system by dynamically adjusting the learning coefficient to adapt to different working conditions. In addition, precise control reduces unnecessary fluctuations in engine performance, optimizes the driving experience, reduces harmful emissions, and improves fuel efficiency. Combining these factors, a dual improvement in engine performance and environmental performance is achieved.

[0049] Reference Figure 2 , Figure 2 This is a flow chart of a second embodiment of a method for predicting the timing of ending intervention in a boost closed loop of the present application. Based on the above first embodiment, a second embodiment of a method for predicting the timing of ending intervention in a boost closed loop of the present application is proposed.

[0050] In this embodiment, the step S20 includes: Step S201: Obtain the inlet and outlet pressure difference according to the actual outlet pressure and the actual inlet pressure.

[0051] It is understandable that the inlet and outlet pressure difference directly reflects the degree of control of the throttle valve over the air flow. A larger pressure difference usually means that the throttle valve is throttled more, the air flow is restricted, and the duration of maintaining the status quo will be longer. A smaller pressure difference means that the throttle valve is more open, the air flow is larger, and the duration of maintenance will be shorter. On the other hand, as the sampling time goes by, the trend of the inlet and outlet pressure difference changes in adjacent sampling cycles will reflect the combustion efficiency and stability of the engine when the current control parameters remain unchanged. Generally speaking, a stable pressure difference trend usually means good combustion control.

[0052] Step S202: Obtaining a pressure difference filter coefficient according to the inlet and outlet pressure difference.

[0053] It should be noted that the pressure difference filter coefficient is calculated based on the inlet and outlet pressure difference. This coefficient is used to smooth the impact of pressure changes on the target opening maintenance time of the boost actuator. Through filtering, the control error caused by pressure fluctuations can be reduced and the control accuracy and stability can be improved.

[0054] It can be understood that the filtering equation in this embodiment is: P AfThrErrFilter (N) = K AftThrErr *[P AfThrErr (N)-P AfThrErr (N-1)]+P AfThrErr (N-1); It should be understood that N is the number of cycles from the start of exiting the closed-loop control to the current moment, where P AfThrErr (N) is the pressure difference after filtering in the Nth sampling period. Similarly, P AfThrErr (N-1) is the pressure difference after filtering in the N-1th sampling period, and P AfThrErrFilter (N) is P AfThrErr (N) is the pressure difference after the first-order low-pass filter, so K in the above formula is AftThrErr That is the pressure difference filter coefficient.

[0055] in, .

[0056] In the above formula, n is the engine speed, k is AftThrErr is the filter coefficient setting value, which can be adjusted manually. In this embodiment, the sampling period is 10ms, k AftThrErr Take 0.25. On this basis, the correction amount of the pressure difference by the first-order filter should not exceed P AfThrErrFilter (N) within the preset ratio, for example, the upper limit of the correction should be 0.1 times the original value, whether it is an upward correction or a downward correction, it should not exceed this ratio.

[0057] Step S203: Obtaining the initial maintenance time prediction value according to the pressure difference filter coefficient, the engine speed and the inlet and outlet pressure ratio.

[0058] It should be noted that, since the specific calibrated maintenance time is determined by the ratio of the engine speed to the inlet and outlet pressures in this embodiment, the initial maintenance time prediction value can be obtained by combining the pressure difference filter coefficient calculated in real-time sampling.

[0059] It is understandable that the pressure difference filter coefficient is obtained by real-time sampling and filtering of the pressure difference between the engine inlet and outlet, which reflects the pressure change characteristics of the engine under different working conditions. This coefficient is introduced to make the prediction of the maintenance time more accurate and to adapt to the actual needs of the engine under different working conditions. Its function is to smooth the noise in the real-time data and extract useful trend information. The calculation of this coefficient needs to take into account the timing characteristics and change rules of the data to ensure that the filtered data can truly reflect the actual working conditions of the engine.

[0060] It should be understood that the initial maintenance duration prediction value is calculated based on the current real-time data, which means that the prediction value will be dynamically adjusted as the engine operating conditions change. This dynamic adjustment mechanism is the key to ensuring that the engine can maintain optimal performance under different operating conditions.

[0061] This embodiment first obtains the inlet and outlet pressure difference based on the actual outlet pressure and the actual inlet pressure; obtains the pressure difference filter coefficient based on the inlet and outlet pressure difference; obtains the initial maintenance time prediction value based on the pressure difference filter coefficient, the engine speed and the inlet and outlet pressure ratio.

[0062] In summary, by calculating the actual pressure difference between the engine outlet and inlet, we can get the pressure difference. This difference directly reflects the degree of control of the throttle valve on the air flow, which in turn affects the combustion efficiency and stability of the engine. Then, we use the pressure difference filter coefficient to smooth the pressure change, reduce the control error caused by pressure fluctuations, and improve the accuracy and stability of control. Finally, we calculate the initial maintenance time prediction value by combining the pressure difference filter coefficient, engine speed, and inlet and outlet pressure ratio. This prediction value can be dynamically adjusted to adapt to the timing of engine intervention under different working conditions, so that the engine management system can more accurately predict and adjust the timing of intervention at the end of the boost closed loop, ensuring the best combustion efficiency and power output under various operating conditions.

[0063] Reference Figure 3 , Figure 3 This is a flow chart of a third embodiment of a method for predicting the timing of ending intervention in a boost closed loop of the present application. Based on the above first embodiment, a third embodiment of a method for predicting the timing of ending intervention in a boost closed loop of the present application is proposed.

[0064] In this embodiment, before step S10, the following steps are further included: Step S001: obtaining a test engine of the same specification, and controlling the test engine to run according to a preset target opening and a preset speed.

[0065] It should be noted that in this embodiment, it is necessary to quantitatively obtain the system's stability maintenance time at the song-in-song speed and target opening through the test bench. First, an engine with the same specifications as in this system is installed on the test bench, and the engine's operating parameters are adjusted through the control system to achieve the preset target opening (opening of the boost actuator) and speed. This is to simulate specific working conditions in actual operation, and then the intervention of the control program is suspended, and the system is timed to maintain stability at the current speed and opening, and the maintenance time test result can be obtained.

[0066] It is understandable that before the boost closed-loop control is turned off, closed-loop control is the system's pressure management mode for most of the time, which means that the system will adjust the actuator's action based on real-time feedback (such as data from the pressure sensor) to maintain the pressure within the set target range.

[0067] Step S002: When the test engine runs stably, the boost closed-loop control is terminated, and the throttle outlet pressure data and the throttle inlet pressure data of the boost control system after the boost closed-loop control is exited are obtained.

[0068] It should be noted that when the engine runs stably at the set target opening and speed, the boost closed-loop control will be stopped. After the boost closed-loop control is exited, the pressure data at the throttle outlet and inlet will be recorded. These data will be used for subsequent analysis to determine the stability changes of the system after the control is exited.

[0069] Step S003: According to the throttle outlet pressure data and the throttle inlet pressure data, a maintenance time test value at a preset target opening and a preset speed is obtained.

[0070] It should be noted that by analyzing the pressure data at the throttle outlet and inlet, key parameters such as pressure difference and pressure change rate can be calculated. These parameters are important indicators for evaluating system stability.

[0071] In one embodiment, the maintenance time test value at a preset target opening and a preset speed is obtained based on the throttle outlet pressure data and the throttle inlet pressure data, including: obtaining the outlet pressure change rate, the inlet pressure change rate and the starting pressure difference based on the throttle outlet pressure data and the throttle inlet pressure data; determining the pressure change threshold value based on the starting pressure difference; when the outlet pressure change rate and / or the inlet pressure change rate is greater than the pressure change threshold value, obtaining the maintenance time test value based on the time from the current moment to the moment when the boost closed-loop control is terminated.

[0072] It is understandable that the criterion for judging whether the system remains stable is the rate of change of the bilateral pressures in a short period of time, that is, the pressure change rate, and the pressure change rate is objectively related to the pressure difference when the closed-loop control ends. Therefore, in this embodiment, the starting pressure difference is used to determine the pressure change threshold, and the pressure change rate of the outlet and inlet is monitored. If any pressure change rate exceeds the previously set pressure change threshold, this indicates that the system may be experiencing an unstable state.

[0073] It should be understood that the pressure change rate is an important indicator to measure the stability of the system. In the boost control system, the rate of change of the outlet and inlet pressures in a short period of time can reflect the system's response to disturbances. The starting pressure difference is the initial pressure difference at the end of the closed-loop control. It provides a benchmark for determining the pressure change threshold. The pressure change threshold is set based on the starting pressure difference and is used to determine whether the pressure change is within an acceptable range. If the pressure change rate exceeds this threshold, the system may not be able to maintain stability.

[0074] Step S004: obtaining a maintenance time prediction table according to the preset target opening, the preset speed and the maintenance time test value.

[0075] It can be understood that the maintenance time data obtained from the above tests are integrated with the corresponding preset target opening and speed to create a prediction table to quickly predict and adjust the time the system remains stable under different operating conditions, thereby optimizing the control strategy and improving the stability and performance of the entire boost system.

[0076] This embodiment first obtains a test engine of the same specification, controls the test engine to operate according to a preset target opening and a preset speed, wherein the operation mode of the boost control system is a boost closed-loop control mode; when the test engine runs stably, terminates the boost closed-loop control, and obtains the throttle outlet pressure data and the throttle inlet pressure data of the boost control system after the boost closed-loop control is exited; obtains a maintenance time test value at a preset target opening and a preset speed based on the throttle outlet pressure data and the throttle inlet pressure data; obtains a maintenance time prediction table based on the preset target opening, the preset speed and the maintenance time test value.

[0077] In summary, the maintenance time prediction table obtained by the above test process in this embodiment significantly improves the design and operation efficiency of the boost control system: it enables engineers to quickly predict and adjust the time required for the system to maintain stability at a specific target opening and speed, thereby optimizing control parameters and improving system stability; at the same time, the prediction table also provides a basis for fault diagnosis, reduces the debugging time in actual operation, ensures the reliability and performance of the system under changing environments and operating conditions, and ultimately achieves cost-effectiveness and improved driving experience.

[0078] Reference Figure 4 The present application also provides a boost closed loop end intervention timing prediction device, the boost closed loop end intervention timing prediction device comprising: The data acquisition module 10 is used to obtain the throttle control parameters at the current moment when the boost control system parameters do not meet the boost closed loop enabling conditions; The data processing module 20 is used to obtain a predicted value of the initial maintenance time of the boost actuator at the target opening according to the throttle control parameter; The data processing module 20 is further used to correct the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

[0079] In one embodiment, the data processing module 20 is also used to deem that the boost closed-loop enabling condition is not met if the compressor outlet target pressure of the boost control system is less than the boost pressure lower limit, or the engine speed is less than a preset speed.

[0080] In one embodiment, the data acquisition module 10 is also used to obtain the actual throttle outlet pressure and the actual inlet pressure at the current moment; obtain the inlet and outlet pressure ratio based on the actual outlet pressure and the actual inlet pressure; and use the inlet and outlet pressure ratio, the engine speed and the target opening of the boost actuator as the throttle control parameters at the current moment.

[0081] In one embodiment, the data processing module 20 is also used to obtain the inlet and outlet pressure difference based on the actual outlet pressure and the actual inlet pressure; obtain the pressure difference filter coefficient based on the inlet and outlet pressure difference; obtain the initial maintenance time prediction value based on the pressure difference filter coefficient, the engine speed and the inlet and outlet pressure ratio.

[0082] In one embodiment, the data processing module 20 is also used to obtain a test engine of the same specification, and control the test engine to operate according to a preset target opening and a preset speed, wherein the operation mode of the boost control system is a boost closed-loop control mode; when the test engine runs stably, the boost closed-loop control is terminated, and the throttle outlet pressure data and the throttle inlet pressure data of the boost control system after the boost closed-loop control is exited are obtained; based on the throttle outlet pressure data and the throttle inlet pressure data, a maintenance time test value at a preset target opening and a preset speed is obtained; based on the preset target opening, the preset speed and the maintenance time test value, a maintenance time prediction table is obtained.

[0083] In one embodiment, the data processing module 20 is also used to obtain the outlet pressure change rate, the inlet pressure change rate and the starting pressure difference based on the throttle outlet pressure data and the throttle inlet pressure data; determine the pressure change threshold value based on the starting pressure difference; when the outlet pressure change rate and / or the inlet pressure change rate is greater than the pressure change threshold value, obtain the maintenance time test value based on the time from the current moment to the moment when the boost closed-loop control is terminated.

[0084] In one embodiment, the data processing module 20 is also used to obtain the EGR rate change trend and the EGR rate change amount within a preset sampling time period based on the real-time engine parameters; determine the maintenance time learning coefficient based on the EGR rate change trend and the EGR rate change amount; and correct the initial maintenance time prediction value based on the maintenance time learning coefficient to obtain the maintenance time prediction value.

[0085] In one embodiment, the data processing module 20 is also used to obtain the engine speed based on the real-time engine parameters; determine the equivalent cycle number of the preset sampling time period based on the engine speed; when the boost closed-loop enabling condition is not met, obtain the EGR rate within the preset sampling time period before the time point; based on the EGR rate within the preset sampling time period, obtain the EGR rate change trend and the EGR rate change amount.

[0086] In one embodiment, the data processing module 20 is also used to obtain a corrected change amount based on the initial maintenance duration prediction value and the maintenance duration prediction value; determine a correction parameter of the maintenance duration learning coefficient based on the corrected change amount, and the correction parameter includes a correction ratio and a data adjustment direction; update and adjust the maintenance duration learning coefficient according to the correction parameter to obtain an adjusted maintenance duration learning coefficient.

[0087] In one embodiment, the data processing module 20 is also used to obtain a corrected change amount based on the initial maintenance duration prediction value and the maintenance duration prediction value; if the corrected change amount is greater than a first correction threshold, the maintenance duration learning coefficient is lowered according to a first correction ratio; if the corrected change amount is less than a second correction threshold, the maintenance duration learning coefficient is increased according to a second correction ratio; if the corrected change amount is less than the first correction threshold and greater than the second correction threshold, the maintenance duration learning coefficient is adjusted according to a third correction ratio based on the positivity of the corrected change amount.

[0088] An embodiment of the present application also provides a device for predicting the timing of ending intervention in a boost closed loop, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for predicting the timing of ending intervention in a boost closed loop in the above-mentioned embodiment one.

[0089] Reference below Figure 5 , which shows a schematic diagram of the structure of a boost closed loop end intervention timing prediction device suitable for implementing the embodiment of the present application. The boost closed loop end intervention timing prediction device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The boost closed-loop end intervention timing prediction device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0090] like Figure 5As shown, the boost closed loop end intervention timing prediction device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the boost closed loop end intervention timing prediction device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the boost closed-loop end intervention timing prediction device to communicate wirelessly or wired with other devices to exchange data. Although the boost closed-loop end intervention timing prediction device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0091] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0092] The boost closed loop end intervention timing prediction device provided in the present application adopts the boost closed loop end intervention timing prediction method in the above embodiment, which can solve the technical problem of how to determine the intervention timing in the transition from the engine charging closed loop control stage to the intervention control stage in the field, thereby ensuring the stability and smoothness during intervention control. Compared with the prior art, the beneficial effects of the boost closed loop end intervention timing prediction device provided in the present application are the same as the beneficial effects of the boost closed loop end intervention timing prediction method provided in the above embodiment, and the other technical features of the boost closed loop end intervention timing prediction device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0093] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0094] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0095] The present application also provides a storage medium, on which is stored a boost closed-loop intervention termination timing prediction program, which, when executed by a processor, implements the steps of the boost closed-loop intervention termination timing prediction method as described above.

[0096] The storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: RandomAccess Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0097] The above storage medium may be included in the pressurization closed loop end intervention timing prediction device; or may exist independently without being assembled into the pressurization closed loop end intervention timing prediction device.

[0098] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the boost closed-loop end intervention timing prediction device, the boost closed-loop end intervention timing prediction device: when the boost control system parameters do not meet the boost closed-loop enabling conditions, obtains the throttle control parameters at the current moment; obtains the initial maintenance time prediction value of the boost actuator at the target opening according to the throttle control parameters; and corrects the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

[0099] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0100] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0101] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0102] The storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned method for predicting the timing of intervention at the end of the boost closed loop, and can solve the technical problem of how to determine the intervention timing in the transition from the engine charging closed loop control stage to the intervention control stage, thereby ensuring the stability and smoothness during intervention control. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the method for predicting the timing of intervention at the end of the boost closed loop provided in the above-mentioned embodiment, and will not be elaborated here.

[0103] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for predicting the timing of ending intervention in a boost closed loop, characterized in that: The method for predicting the timing of ending intervention of a boost closed loop comprises: When the boost control system parameters do not meet the boost closed loop enabling conditions, obtaining the current throttle control parameters; According to the throttle control parameter, a predicted value of the initial maintenance time of the boost actuator at the target opening is obtained; The initial maintenance time prediction value is corrected according to the real-time engine parameters to obtain a maintenance time prediction value.

2. The method for predicting the timing of ending intervention of a boost closed loop according to claim 1, characterized in that: The boost closed loop enabling condition includes: If the compressor outlet target pressure of the boost control system is less than the boost pressure lower limit, or the engine speed is less than a preset speed, it is deemed that the boost closed-loop enabling condition is not met.

3. The method for predicting the timing of ending intervention of a boost closed loop according to claim 1, characterized in that: The obtaining of the throttle control parameter at the current moment includes: Get the actual throttle outlet pressure and inlet pressure at the current moment; According to the actual outlet pressure and the actual inlet pressure, a ratio of the inlet and outlet pressures is obtained; The inlet and outlet pressure ratio, engine speed and boost actuator target opening are used as throttle control parameters at the current moment.

4. The method for predicting the timing of ending intervention of a boost closed loop according to claim 1, characterized in that: The step of obtaining a predicted value of the initial maintenance time of the boost actuator at the target opening according to the throttle control parameter includes: According to the actual outlet pressure and the actual inlet pressure, the inlet and outlet pressure difference is obtained; According to the inlet and outlet pressure difference, a pressure difference filter coefficient is obtained; The initial maintenance time prediction value is obtained according to the pressure difference filter coefficient, the engine speed, the inlet and outlet pressure ratio and the maintenance time prediction table.

5. The method for predicting the timing of ending intervention of a boost closed loop according to claim 4, characterized in that: Before obtaining the initial maintenance time prediction value according to the pressure difference filter coefficient, the engine speed and the inlet and outlet pressure ratio, the method further includes: Obtain a test engine of the same specification, and control the test engine to operate according to a preset target opening and a preset speed, wherein the operation mode of the boost control system is a boost closed-loop control mode; When the test engine runs stably, the boost closed-loop control is terminated, and the throttle outlet pressure data and the throttle inlet pressure data of the boost control system after the boost closed-loop control is terminated are acquired; According to the throttle outlet pressure data and the throttle inlet pressure data, a maintenance time test value at a preset target opening and a preset speed is obtained; A maintenance time prediction table is obtained according to the preset target opening, the preset rotation speed and the maintenance time test value.

6. The method for predicting the timing of ending intervention of a boost closed loop according to claim 5, characterized in that: The method of obtaining a maintenance time test value at a preset target opening and a preset speed according to the throttle outlet pressure data and the throttle inlet pressure data includes: According to the throttle outlet pressure data and the throttle inlet pressure data, the outlet pressure change rate, the inlet pressure change rate and the initial pressure difference are obtained; Determining a pressure change threshold value according to the initial pressure difference; When the outlet pressure change rate and / or the inlet pressure change rate is greater than the pressure change threshold, the maintenance time test value is obtained according to the time from the current moment to the moment when the boost closed-loop control is terminated.

7. The method for predicting the timing of ending intervention of a boost closed loop according to claim 1, characterized in that: The method of correcting the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value includes: According to the real-time engine parameters, the EGR rate change trend and the EGR rate change amount within a preset sampling time period are obtained; Determining a maintenance time learning coefficient according to the EGR rate change trend and the EGR rate change amount; The initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain a maintenance duration prediction value.

8. The method for predicting the timing of ending intervention of a boost closed loop according to claim 7, characterized in that: The method of obtaining the EGR rate change trend and the EGR rate change amount within a preset sampling time period according to the real-time engine parameters includes: According to the real-time engine parameters, the engine speed is obtained; Determining the equivalent number of cycles of a preset sampling time period according to the engine speed; When the boost closed-loop enabling condition is not met, obtaining the EGR rate within a preset sampling time period before the time point; According to the EGR rate within the preset sampling time period, the EGR rate change trend and the EGR rate change amount are obtained.

9. The method for predicting the timing of ending intervention of a boost closed loop according to claim 7, characterized in that: After the initial maintenance duration prediction value is corrected according to the maintenance duration learning coefficient to obtain the maintenance duration prediction value, the method further includes: Obtaining a modified change amount according to the initial maintenance duration prediction value and the maintenance duration prediction value; Determining a correction parameter of the maintenance duration learning coefficient according to the correction change amount, wherein the correction parameter includes a correction ratio and a data adjustment direction; The maintenance duration learning coefficient is updated and adjusted according to the correction parameter to obtain an adjusted maintenance duration learning coefficient.

10. The method for predicting the timing of ending intervention of a boost closed loop according to claim 9, characterized in that: The step of determining the correction parameter of the maintenance duration learning coefficient according to the correction change comprises: If the correction change is greater than the first correction threshold, the maintenance time learning coefficient is adjusted downward according to the first correction ratio; If the correction change is less than the second correction threshold, the maintenance time learning coefficient is increased according to the second correction ratio; If the corrected change amount is less than the first correction threshold and greater than the second correction threshold, the maintenance duration learning coefficient is adjusted according to a third correction ratio based on the positive or negative nature of the corrected change amount.

11. A device for predicting the timing of ending intervention in a boost closed loop, characterized in that: The boost closed loop intervention termination timing prediction device comprises: A data acquisition module, used to obtain the throttle control parameters at the current moment when the boost control system parameters do not meet the boost closed loop enabling conditions; A data processing module, used for obtaining a predicted value of the initial maintenance time of the boost actuator at a target opening according to the throttle control parameter; The data processing module is also used to correct the initial maintenance time prediction value according to the real-time engine parameters to obtain the maintenance time prediction value.

12. A device for predicting the timing of intervention of a boost closed loop, characterized in that: The boost closed-loop intervention end timing prediction device comprises: a memory, a processor and a boost closed-loop intervention end timing prediction program stored in the memory and executable on the processor, wherein the boost closed-loop intervention end timing prediction program is configured to implement the steps of the boost closed-loop intervention end timing prediction method as described in any one of claims 1 to 10.

13. A storage medium, characterized in that: The storage medium stores a boost closed-loop intervention termination timing prediction program, which, when executed by a processor, implements the steps of the boost closed-loop intervention termination timing prediction method as claimed in any one of claims 1 to 10.

Images