A fuel injection law prediction method and system
By predicting the back pressure of the constant volume chamber and dynamically adjusting the back pressure, the problem of inaccurate measurement of the injection pattern caused by back pressure fluctuation in high-flow injectors is solved, and accurate calculation of the injection pattern is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- MASCH TECH DEV CO LTD
- Filing Date
- 2026-06-01
- Publication Date
- 2026-07-14
Smart Images
Figure CN122383571A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of fuel injection testing technology, and in particular to a method and system for predicting fuel injection patterns. Background Technology
[0002] Injection patterns (injection quantity, injection rate, injection duration, etc.) are core parameters of high-pressure common rail injectors, directly determining the power, economy, and emission characteristics of diesel engines. Among existing injection pattern measurement technologies, the Zeuch method can infer the injection pattern from the pressure changes in the constant volume chamber, featuring high accuracy and fast dynamic response.
[0003] In existing methods for measuring fuel injection in a constant-volume chamber using the Zeuch method, cavitation can easily occur due to back pressure fluctuations caused by fuel injection after a high-flow fuel injector. This significantly interferes with the measurement of the constant-volume chamber pressure signal. Furthermore, due to the nonlinear changes in temperature and pressure within the constant-volume chamber, directly calculating the injection pattern based on the Zeuch method results in a significant reduction in accuracy, failing to meet the testing requirements for high-flow fuel injectors. Summary of the Invention
[0004] This invention provides a method and system for predicting fuel injection patterns, which solves the technical problems in the prior art where back pressure fluctuations caused by fuel injection in the cavity after high-flow fuel injectors easily lead to cavitation, causing significant interference to the measurement of constant-volume cavity pressure signals. At the same time, due to the nonlinear changes in factors such as temperature and pressure in the constant-volume cavity, directly calculating the fuel injection pattern based on the Zeuch method will result in a significant reduction in the accuracy of the fuel injection pattern results, which cannot meet the detection requirements of high-flow fuel injectors.
[0005] To achieve the above and other related objectives, the present invention provides a method for predicting fuel injection patterns, comprising: acquiring real-time parameters of the injector before the start of fuel injection into the back pressure assembly, the real-time parameters including the injection parameters corresponding to the injector and the first measured parameters within the back pressure assembly; predicting the back pressure of the constant-volume cavity based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant-volume cavity of the back pressure assembly, to obtain a predicted back pressure; comparing the predicted back pressure with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed exhaust valve, so as to control the first real-time back pressure to the predicted back pressure; dynamically correcting the fuel elastic modulus based on the controlled first measured parameters, to obtain a corrected elastic modulus; and predicting the fuel injection pattern based on the controlled first measured parameters and the corrected elastic modulus, to obtain a corresponding fuel injection pattern.
[0006] In one embodiment of the present invention, the first measured parameters include the first real-time temperature and the first real-time back pressure of the constant-volume cavity; predicting the back pressure of the constant-volume cavity based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant-volume cavity of the back pressure component to obtain the predicted back pressure includes: obtaining the volume increment of the constant-volume cavity based on the first real-time temperature and the first real-time back pressure; dynamically adjusting the initial volume based on the volume increment to obtain the real-time corrected volume corresponding to the constant-volume cavity; and predicting the back pressure of the constant-volume cavity based on the injection parameters and the real-time corrected volume to obtain the predicted back pressure.
[0007] In one embodiment of the present invention, the volume increment of the constant-volume cavity is obtained based on the first real-time temperature and the first real-time back pressure, including: obtaining the expansion temperature based on the first real-time temperature and the reference temperature value; obtaining the expansion coefficient corresponding to the back pressure component based on the expansion temperature and the expansion increment factor; and obtaining the volume increment of the constant-volume cavity based on the first real-time back pressure, the reference pressure value, and the expansion coefficient; the formula for calculating the volume increment is: ;in, Indicates the volume increment. Indicates the first real-time temperature. Indicates the reference temperature value. Indicates the expansion increment factor. Indicates the first real-time back pressure. This indicates the reference pressure value.
[0008] In one embodiment of the present invention, the injection parameters include the real-time rail pressure and injection pulse width of the injector; predicting the back pressure of the constant volume cavity based on the injection parameters and the real-time correction volume to obtain the predicted back pressure includes: obtaining the cumulative pressure on the constant volume cavity based on the real-time rail pressure and the injection pulse width; obtaining the predicted back pressure based on the cumulative pressure, the real-time correction volume, the back pressure matching coefficient, and the first real-time back pressure of the constant volume cavity; the calculation formula for the predicted back pressure is: ;in, Indicates predicted back pressure, Indicates the first real-time back pressure. Indicates the back pressure matching coefficient. Indicates real-time rail pressure. Indicates the pulse width of the jet. Indicates the pulse width of the jet. Every moment inside, This indicates that the volume is adjusted in real time.
[0009] In one embodiment of the present invention, the predicted back pressure is compared with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure. This includes: calculating the difference between the predicted back pressure and the first real-time back pressure to obtain the back pressure deviation; obtaining the deviation change rate corresponding to the current back pressure deviation based on the current back pressure deviation at the current moment and the previous back pressure deviation at the previous moment; and generating control parameters for the high-speed oil discharge valve based on the cumulative deviation value of the back pressure deviation, the current back pressure deviation, and the deviation change rate, so as to control the first real-time back pressure to the predicted back pressure.
[0010] In one embodiment of the present invention, control parameters for the high-speed oil discharge valve are generated based on the cumulative value of the back pressure deviation, the current back pressure deviation, and the deviation change rate to adjust the first real-time back pressure to the predicted back pressure. This includes: performing integral calculations based on the back pressure deviations at different times to obtain a cumulative deviation value; weighting and fusing the cumulative deviation value, the current back pressure deviation, and the deviation change rate to obtain a deviation adjustment amount; looking up a table to obtain the corresponding dynamic fuzzy compensation amount based on the current back pressure deviation and the deviation change rate; and generating control parameters for the high-speed oil discharge valve based on the deviation adjustment amount and the dynamic fuzzy compensation amount to adjust the first real-time back pressure to the predicted back pressure. The calculation formula for the control parameters is as follows: ; Indicates the control parameter, This represents the coefficient for the proportional control item. Represents the coefficient of the integral control term. Represents the coefficient of the differential control term. Indicates the current back pressure deviation. This indicates the back pressure deviation at different times. Indicates the pre-adjustment time before fuel injection. This indicates the corresponding time for each back pressure deviation. Indicates the rate of change of deviation. This represents the amount of dynamic fuzzy compensation.
[0011] In one embodiment of the present invention, the second measured parameters include the second real-time temperature and the second real-time back pressure of the constant volume chamber; the fuel elastic modulus is dynamically corrected according to the adjusted second measured parameters to obtain a corrected elastic modulus, including: generating a first correction amount for the fuel elastic modulus based on the second measured parameters and the corresponding reference value; performing feature adaptation analysis based on the component design model corresponding to the back pressure component and the second measured parameters to obtain a second correction amount for the fuel elastic modulus; and dynamically correcting the fuel elastic modulus according to the first correction amount, the second correction amount, and the corresponding correction coefficient to obtain the corrected elastic modulus; the calculation formula for the corrected elastic modulus is: ;in, This indicates the modified elastic modulus. Indicates the elastic modulus of fuel. Indicates the second measured parameter. This represents the baseline value corresponding to the second measured parameter. This represents the correction factor corresponding to the second measured parameter. This indicates the first weight ratio corresponding to the first correction amount. This indicates the second correction amount. This indicates the second weighting ratio corresponding to the second correction amount.
[0012] In one embodiment of the present invention, feature adaptation analysis is performed based on the component design model corresponding to the back pressure component and the second measured parameters to obtain a second correction amount for the fuel elastic modulus. This includes: adjusting the active area of the component design model by querying and adjusting the real-time corrected volume of the constant-volume cavity of the back pressure component according to the second measured parameters to obtain an updated component model; obtaining all key influence features and their corresponding design influence benchmark parameter values by looking up a table based on the second measured parameters; detecting abnormal design features based on the key influence features and their corresponding design influence benchmark parameter values; calculating the difference between the feature parameter values corresponding to the abnormal design features and the corresponding design influence benchmark parameter values corresponding to the key influence features to obtain a feature difference; and obtaining the second correction amount for the fuel elastic modulus based on the feature difference and the corresponding correction factor. The calculation formula for the second correction amount is as follows: ;in, This indicates the second correction amount. This represents each dimension corresponding to the abnormal design features. The correction factor below, Represent each dimension The characteristic parameter values below, Represent each dimension The design affects the baseline parameter values.
[0013] In one embodiment of the present invention, the active area of the component design model is queried and adjusted according to the real-time corrected volume of the fixed-volume cavity of the back pressure component based on the second measured parameters to obtain the component update model. This includes: generating a volume correction amount for each active area based on the coordinate range, active weight, and real-time corrected volume of each active area of the component design model; and adjusting the component design model according to the volume correction amount to obtain the component update model.
[0014] To achieve the above and other related objectives, the present invention also provides a fuel injection pattern prediction system, comprising: an acquisition unit for acquiring real-time parameters of the injector before fuel injection into the back pressure assembly, the real-time parameters including the injection parameters corresponding to the injector and the first measured parameters within the back pressure assembly; a back pressure prediction unit for predicting the back pressure of the constant-volume cavity based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant-volume cavity of the back pressure assembly, thereby obtaining a predicted back pressure; a deviation comparison unit for comparing the predicted back pressure with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed exhaust valve, thereby controlling the first real-time back pressure to the predicted back pressure; a modulus correction unit for dynamically correcting the fuel elastic modulus based on the second measured parameters during fuel injection after back pressure control, thereby obtaining a corrected elastic modulus; and a pattern generation unit for predicting the fuel injection pattern based on the second measured parameters and the corrected elastic modulus, thereby generating a corresponding fuel injection pattern.
[0015] The beneficial effects of this invention are as follows: The fuel injection pattern prediction method and system proposed in this invention utilize the injection parameters of the injector before injection and the first measured parameters detected in the back pressure assembly to predict the back pressure in the constant volume chamber. The predicted back pressure is then compared with the first real-time back pressure from the first measured parameters. Based on the back pressure deviation, the control parameters for regulating the high-speed exhaust valve are determined to adjust the first real-time back pressure to the predicted back pressure, ensuring that the initial back pressure in the constant volume chamber remains relatively stable during each injection process. This resolves cavitation during injection, allowing for the acquisition of a second measured parameter after dynamic exhaust regulation, ensuring the accuracy and reliability of the acquired second measured parameter in the constant volume chamber. Furthermore, the second measured parameter after exhaust regulation is used to dynamically correct the fuel elastic modulus. The corrected elastic modulus is then used in conjunction with the second measured parameter to determine the fuel injection pattern. This method effectively eliminates the influence of back pressure fluctuations and property changes on the prediction results during fuel injection pattern calculation, achieving accurate calculation of the fuel injection pattern and improving the accuracy of the results. Attached Figure Description
[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.
[0017] In the attached diagram: Figure 1 This is a flowchart illustrating the fuel injection pattern prediction method provided in an embodiment of the present invention.
[0018] Figure 2The diagram shown is a structural block diagram of an injection pattern prediction system provided in an embodiment of the present invention.
[0019] Figure 3 The diagram shown is a structural schematic of an electronic device according to an embodiment of the present invention.
[0020] The attached figures are labeled as follows: Electronic device 1; Oil pattern prediction system 11; Memory 12; Processor 13; Acquisition unit 111; Back pressure prediction unit 112; Deviation comparison unit 113; Modulus correction unit 114; Pattern generation unit 115. Detailed Implementation
[0021] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.
[0022] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.
[0023] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.
[0024] This invention provides a method for predicting fuel injection patterns. By utilizing the injection parameters of the injector before injection and the first measured parameters detected within the back pressure assembly, the back pressure within the constant volume chamber is first predicted. The predicted back pressure is then compared with the first real-time back pressure from the first measured parameters. Based on the back pressure deviation, control parameters for regulating the high-speed exhaust valve are determined to adjust the first real-time back pressure to the predicted back pressure. This ensures that the initial back pressure of the constant volume chamber remains relatively stable during each injection process, mitigating cavitation during injection. This allows for the acquisition of a second measured parameter after dynamic exhaust regulation, ensuring the accuracy and reliability of the acquired second measured parameter within the constant volume chamber. The second measured parameter after exhaust regulation is then used to dynamically correct the fuel elastic modulus. This corrected elastic modulus is then used in conjunction with the second measured parameter to determine the fuel injection pattern. This method effectively eliminates the influence of back pressure fluctuations and property changes on the prediction results during fuel injection pattern calculation, achieving accurate calculation of the fuel injection pattern and improving the accuracy of the results.
[0025] Figure 1 A flowchart of an exemplary embodiment of the fuel injection pattern prediction method of this application is shown, applied to a fuel injection pattern prediction system, including steps S10-S50. The following will be combined with... Figure 1 The technical solution of this application will be described in detail below.
[0026] First, step S10 is executed to obtain the real-time parameters of the injector before the injection of fuel into the back pressure assembly. The real-time parameters include the injection parameters corresponding to the injector and the first measured parameters in the back pressure assembly.
[0027] When the injection pattern prediction system acquires real-time parameters of the injector before the start of injection into the back pressure assembly, it can be that the injection pattern prediction system actively collects the data, or the injector and back pressure assembly can upload the relevant injection parameters and the first measured parameters to the injection pattern prediction system.
[0028] Next, step S20 is executed, and the back pressure of the constant volume cavity is predicted based on the injection parameters, the first measured parameters and the initial volume corresponding to the constant volume cavity of the back pressure component, so as to obtain the predicted back pressure.
[0029] After the injection pattern prediction system obtains the injection parameters and the first measured parameters, in order to better evaluate the rationality of the current constant volume cavity back pressure, the back pressure of the constant volume cavity can be predicted by first using the injection parameters, the first measured parameters, and the initial volume. This allows for accurate prediction of the predicted back pressure of the constant volume cavity. Furthermore, by comparing the predicted back pressure with the first real-time back pressure, the system can determine and adjust control parameters such as the discharge time of the high-speed discharge valve. By dynamically controlling the discharge of the high-speed discharge valve, or closing the high-speed discharge valve and controlling the replenishment when the first real-time back pressure is low, the back pressure in the constant volume cavity can be kept relatively stable. This solves the problem that the reliability of the predicted injection pattern is greatly reduced due to unstable back pressure.
[0030] The first measured parameter may include the first real-time temperature and the first real-time back pressure of the constant volume chamber, and of course, may also include other measured parameters. The first real-time temperature may be the real-time fuel temperature in the constant volume chamber measured by a temperature sensor, and the first real-time back pressure may be the first real-time back pressure formed in the constant volume chamber before fuel injection measured by a pressure sensor.
[0031] In step S20, the back pressure of the constant-volume cavity is predicted based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant-volume cavity of the back pressure assembly, resulting in the predicted back pressure, including: The volume increment of the constant-volume cavity is obtained based on the first real-time temperature and the first real-time back pressure. The initial volume is dynamically adjusted based on the volume increment to obtain the real-time corrected volume corresponding to the fixed-volume cavity; The predicted back pressure is obtained by predicting the back pressure of the constant volume cavity based on the injection parameters and the real-time correction volume.
[0032] In the process of evaluating and predicting the predicted back pressure, the volume increment of the constant volume cavity can be calculated based on the first real-time temperature and the first real-time back pressure in the first measured parameters. This volume increment can then be used as the initial volume increment to dynamically correct the initial volume. Furthermore, the corrected real-time volume can be combined with the injection parameters of the injector to the back pressure component to predict the back pressure of the constant volume cavity. The predicted back pressure is then compared with the first real-time back pressure in the first measured parameters to generate more reliable control parameters for the high-speed exhaust valve. This allows for exhaust control or shutting off the exhaust valve to control the replenishment of the constant volume cavity, ensuring that the constant volume cavity quickly recovers to a stable back pressure (i.e., the target back pressure).
[0033] The volume increment of the constant-volume cavity is obtained based on the first real-time temperature and the first real-time back pressure, including: The expansion temperature is obtained based on the first real-time temperature and the reference temperature value; Based on the expansion temperature and expansion increment factor, the expansion coefficient corresponding to the back pressure component is obtained; The volume increment of the constant-volume cavity is obtained based on the first real-time back pressure, the reference pressure value, and the expansion coefficient.
[0034] Preferably, the formula for calculating the volume increment can be expressed as: ; in, Indicates the volume increment. Indicates the first real-time temperature. Indicates the reference temperature value. Indicates the expansion increment factor. Indicates the first real-time back pressure. This indicates the reference pressure value.
[0035] In the process of calculating the volume increment, it can be based on the first real-time temperature. and reference temperature value The difference yields the expansion temperature. Then, the expansion temperature is combined with an expansion increment factor corresponding to the corresponding back pressure component, which is based on experience and pre-calibrated. The expansion coefficient corresponding to the back pressure component was calculated. Then, through the first real-time back pressure and reference pressure value The difference is used to calculate the pressure effect. Finally, the coefficient of thermal expansion... Combined with the influence of pressure The volume increment of the constant-volume cavity is calculated, expressed by the formula: .
[0036] The injection parameters of the injector may include the real-time rail pressure and injection pulse width of the injector, which can be obtained based on the actual output of the injector when it is about to inject fuel into the back pressure assembly for testing.
[0037] Based on the injection parameters and real-time corrected volume, the back pressure of the constant volume cavity is predicted to obtain the predicted back pressure, which may further include: The cumulative pressure on the constant volume cavity is obtained based on the real-time rail pressure and injection pulse width; The predicted back pressure is obtained based on the cumulative pressure, real-time corrected volume, back pressure matching coefficient, and the first real-time back pressure of the constant volume cavity.
[0038] The formula for predicting back pressure is: ; in, Indicates predicted back pressure, Indicates the first real-time back pressure. Indicates the back pressure matching coefficient. Indicates real-time rail pressure. Indicates the pulse width of the jet. Indicates the pulse width of the jet. Every moment inside, This indicates that the volume is adjusted in real time.
[0039] When calculating predicted back pressure, the real-time rail pressure and injection pulse width of the injector can be used to calculate the pressure accumulation in the constant-volume chamber. The real-time rail pressure represents the high-pressure energy storage level of the fuel within the injector, and the injection pulse width represents the duration of the injector's operation. By multiplying these two values, the pressure and time released during a single injection can be integrated, thus reflecting the cumulative injection quantity, i.e., the pressure accumulation in the constant-volume chamber. Furthermore, this is based on the core formula of the Zeuch method. , This indicates the pressure change in the constant volume chamber caused by the injection of fuel. Indicates the elastic modulus of fuel. Indicates the volume of fuel injected. This represents the volume of the constant-volume cavity. Furthermore, using a manually calibrated back pressure matching coefficient, the accumulated pressure can be converted into the change in back pressure within the constant-volume cavity using real-time volume correction. Finally, by combining the first real-time back pressure of the constant-volume cavity, the predicted back pressure is calculated, expressed by the formula: By using this predicted back pressure, it is possible to compare it with the first real-time back pressure to determine whether the current first real-time back pressure is reliable. This allows for dynamic oil discharge control of the high-speed oil discharge valve to compensate for the back pressure of the control system, thereby stabilizing the back pressure during the injection process and ensuring the detection requirements of high-flow injectors.
[0040] In addition, when calculating the predicted back pressure, the aforementioned formula for calculating the volume increment should be used. The formula for predicting back pressure can be expressed as: ,in, This represents the initial volume.
[0041] Next, step S30 is executed, which compares the predicted back pressure with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure.
[0042] After calculating the predicted back pressure, the fuel injection pattern prediction system can better determine whether the back pressure during fuel injection meets the injection requirements. This can be achieved by comparing the predicted back pressure with the first real-time back pressure in the first measured parameter to generate control parameters for the high-speed exhaust valve. By controlling the exhaust of the high-speed exhaust valve or by closing the fuel replenishment when the constant volume chamber oil pressure is low, the back pressure of the constant volume chamber of the entire back pressure assembly can be made to meet the back pressure requirements during fuel injection.
[0043] In step S30, the predicted back pressure is compared with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure, including: The difference between the predicted back pressure and the first real-time back pressure is calculated to obtain the back pressure deviation; Based on the current back pressure deviation at the current moment and the previous back pressure deviation at the previous moment, the deviation change rate corresponding to the current back pressure deviation is obtained. Based on the cumulative value of the back pressure deviation, the current back pressure deviation, and the deviation change rate, control parameters for the high-speed oil discharge valve are generated to adjust the first real-time back pressure to the predicted back pressure.
[0044] In the process of calculating the control parameters, it is possible to first base them on the predicted back pressure. With the first real-time back pressure The difference is calculated to obtain the back pressure deviation between the predicted back pressure and each first real-time back pressure. Then, based on the back pressure deviation at each moment... The back pressure deviation change curve is generated, and the slope based on the difference between the current back pressure deviation at the current moment and the previous back pressure deviation at the previous moment is determined by dividing the difference between the current moment and the previous moment, which serves as the corresponding deviation change rate. Finally, by using the cumulative back pressure deviation, the current back pressure deviation, and the deviation change rate, the control parameters of the high-speed exhaust valve are calculated. Based on the calculated control parameters, the high-speed exhaust valve is dynamically controlled to adjust the valve opening, ensuring stable injection and improving the accuracy of injection pattern calculation.
[0045] The control parameter can be represented as the duty cycle of the high-speed discharge valve. This means that the valve opening can be adjusted using the dynamically calculated duty cycle, thereby adjusting the discharge volume. This ensures that the first real-time back pressure of the back pressure assembly remains stable based on the injection parameters, thus solving the problem of cavitation and pressure signal noise during injection caused by unstable back pressure in the constant-volume chamber, which affects the waveform of the injection pattern and significantly reduces reliability. Specifically, for example, under low back pressure conditions (i.e., the predicted back pressure is greater than the first real-time back pressure), there are many air bubbles in the constant-volume chamber of the back pressure assembly, causing drastic fluctuations in the pressure change curve and affecting the waveform of the injection pattern. Furthermore, without proper back pressure control, high back pressure injection will increase the cost of measuring the injection pattern.
[0046] The process of generating control parameters for the high-speed oil discharge valve based on the cumulative value of the back pressure deviation, the current back pressure deviation, and the rate of change of the deviation, in order to adjust the first real-time back pressure to the predicted back pressure, may further include: The cumulative deviation is obtained by integrating the back pressure deviation at different times. The cumulative deviation, the current back pressure deviation, and the rate of change of deviation are weighted and fused to obtain the deviation adjustment amount; Based on the current back pressure deviation and the rate of change of deviation, the corresponding dynamic fuzzy compensation amount is obtained by looking up the table. Based on the deviation adjustment amount and the dynamic fuzzy compensation amount, the control parameters for the high-speed oil discharge valve are generated to adjust the first real-time back pressure to the predicted back pressure.
[0047] Preferably, the formula for calculating the control parameter can be expressed as: ; Indicates the control parameter, This represents the coefficient for the proportional control item. Represents the coefficient of the integral control term. Represents the coefficient of the differential control term. Indicates the current back pressure deviation. This indicates the back pressure deviation at different times. Indicates the pre-adjustment time before fuel injection. This indicates the corresponding time for each back pressure deviation. Indicates the rate of change of deviation. This represents the amount of dynamic fuzzy compensation.
[0048] When calculating the control parameters using the cumulative back pressure deviation, the current back pressure deviation, and the rate of change of deviation, the back pressure deviation at different times can be used first. By integrating, the cumulative deviation caused by back pressure deviation during the fuel injection process is calculated. Based on the current back pressure deviation The corresponding rate of change of deviation is denoted as Based on the current back pressure deviation and the cumulative deviation value, the resulting deviation adjustment amount is calculated, expressed by the formula as follows: Among them, for back pressure deviation This can include the current back pressure deviation at the current moment. Historical back pressure deviations corresponding to historical moments in the fuel injection process After determining the deviation adjustment amount, the dynamic fuzzy compensation amount corresponding to the current back pressure deviation and deviation change rate can be found by referring to the correspondence table between the back pressure deviation and deviation change rate and the fuzzy compensation amount. This is to compensate for nonlinear interference during the fuel injector injection process. For example, when a large deviation occurs, the robustness can be enhanced by increasing the fuzzy compensation amount. Finally, based on the dynamic fuzzy compensation amount... Through calculation formula This is used to calculate the control parameters for the high-speed oil discharge valve. For example, when the first real-time back pressure... greater than predicted back pressure At that time, the adjustment parameters can be used. The output is sent to the high-speed drain valve driver to increase the drain valve opening, accelerate the drain pressure reduction, and when the first real-time back pressure... Less than the predicted back pressure If necessary, the drain valve can be closed, and oil can be added as needed to raise the pressure to the predicted back pressure.
[0049] Next, step S40 is executed, and the fuel elastic modulus is dynamically corrected based on the second measured parameter during fuel injection after back pressure regulation, so as to obtain the corrected elastic modulus.
[0050] The fuel injection pattern prediction system, by dynamically regulating the high-speed fuel discharge valve through parameter adjustment, can stabilize the back pressure of the constant-volume chamber during the fuel injection process, thereby obtaining the corresponding second measured parameter. Then, based on this second measured parameter, further correction of the fuel elastic modulus is needed when determining the fuel injection pattern. This ensures that the fuel elastic modulus used to calculate the injection rate and quantity overcomes interference from physical properties such as temperature and pressure within the constant-volume chamber, guaranteeing the accuracy of the injection rate and quantity calculations.
[0051] Based on the second real-time temperature and second real-time back pressure of the constant-volume cavity in the second measured parameters, the fuel elastic modulus is dynamically corrected according to the adjusted first measured parameters to obtain the corrected elastic modulus, which may further include: Based on the second measured parameter and the corresponding benchmark value, a first correction amount for the fuel elastic modulus is generated; Based on the component design model corresponding to the back pressure component and the second measured parameters, feature adaptation analysis is performed to obtain the second correction amount for the fuel elastic modulus. The fuel elastic modulus is dynamically corrected based on the first correction amount, the second correction amount, and the corresponding correction coefficient to obtain the corrected elastic modulus.
[0052] The formula for calculating the modified elastic modulus is: ; in, This indicates the modified elastic modulus. Indicates the elastic modulus of fuel. Indicates the second measured parameter. This represents the baseline value corresponding to the second measured parameter. This represents the correction factor corresponding to the second measured parameter. This indicates the first weight ratio corresponding to the first correction amount. This indicates the second correction amount. This indicates the second weighting ratio corresponding to the second correction amount.
[0053] In the process of correcting the fuel elastic modulus, a first correction amount can be determined by calculating the difference between a second measured parameter, such as a second real-time temperature or a second real-time back pressure, and the corresponding benchmark value. Additionally, for the structural design of the back pressure assembly, a component design model can be constructed first. Then, abnormal design features can be detected and queried on the component design model. Based on the anomalies in these abnormal design features, a second correction amount for the fuel elastic modulus can be generated. Finally, the first correction amount is calibrated using an empirically determined first weighting ratio. The second weight ratio corresponding to the second correction amount Through formula The total correction amount required is calculated and combined with the initial fuel elastic modulus. Using calculation formula The corrected elastic modulus is calculated using this method. For the component design model, multiple first correction values corresponding to the second measured parameters can exist simultaneously. Each first correction value... By combining the correction coefficient corresponding to the second measured parameter set based on empirical values The fused value of all the first corrections is obtained by superimposing them. Therefore, the first weight ratio corresponding to the fusion value of the first correction amount is used. This is then used to perform a fusion calculation with the second correction amount.
[0054] Furthermore, based on the component design model corresponding to the back pressure component and the second measured parameters, a feature adaptation analysis is performed to obtain a second correction amount for the fuel elastic modulus, which may further include: Based on the real-time correction volume of the fixed-volume cavity of the back pressure component according to the second measured parameters, the active area of the component design model is queried and adjusted to obtain the updated component model. Based on the second measured parameter, all key impact features and the corresponding design impact benchmark parameter values are obtained by referring to the table. The component update model is tested based on key impact characteristics and design impact baseline parameter values to obtain abnormal design characteristics; The difference between the characteristic parameter value corresponding to the abnormal design feature and the design influence benchmark parameter value corresponding to the corresponding key influence feature is calculated to obtain the feature difference value. Based on the characteristic difference and the corresponding correction factor, the second correction amount for the elastic modulus of fuel is obtained.
[0055] The formula for calculating the second correction amount is: ; in, This indicates the second correction amount. This represents each dimension corresponding to the abnormal design features. The correction factor below, Represent each dimension The characteristic parameter values below, Represent each dimension The design affects the baseline parameter values.
[0056] During the calculation of the second correction amount, the real-time correction volume, calculated based on the second measured parameters and corrected for the constant-volume cavity volume of the back pressure component, can be used to locate the effective area of the component design model. The real-time correction volume is then allocated to each effective area according to its proportional effect, and the component design model is updated to obtain an updated component model that accurately reflects the shape of the constant-volume cavity structure. Next, using the current second measured parameters, such as the second real-time temperature and the second real-time back pressure, the key influencing features affecting the fuel elastic modulus and their corresponding design influence benchmark parameter values are located through a table corresponding to the design influence benchmark parameter values. Subsequently, the difference between the corresponding feature parameters of the updated component model and the design influence benchmark parameter values corresponding to the key influencing features is calculated. Design features with differences greater than a preset value are considered abnormal design features. The difference between the feature parameters of the abnormal design features and the design influence benchmark parameter values corresponding to the key influencing features is then used as the feature difference, combined with empirically set dimensions for each dimension. The correction factor is calculated using the formula. The second correction component for each anomalous design feature is calculated. Finally, by combining all anomalous design features in the component update model, the calculation formula is applied. The second correction amount corresponding to all abnormal design features is calculated.
[0057] Specifically, based on the real-time correction volume of the constant-volume cavity of the back pressure component according to the second measured parameters, the active area of the component design model is queried and adjusted to obtain the updated component model, which may further include: Based on the coordinate range, action weight, and real-time correction volume of each action area in the component design model, generate the volume correction amount for each action area; The component design model is adjusted based on the volume correction amount to obtain the updated component model.
[0058] When calculating the volume correction for each action zone, it can be based on the preset action weight for each action zone. and real-time corrected volume Perform a product calculation to obtain the volume correction amount corresponding to the coordinate range of each action area. The formula can be expressed as Finally, the component design model was adjusted based on the volume correction amount for each functional region to update the component update model, ensuring the accuracy of the second correction amount calculation.
[0059] Next, step S50 is executed to predict the oil injection pattern based on the second measured parameters and the corrected elastic modulus, thereby obtaining the corresponding oil injection pattern.
[0060] After adjusting the back pressure at constant volume, the fuel injection pattern prediction system obtains the second measured parameter during fuel injection. It can then combine the corrected elastic modulus to calculate the instantaneous fuel injection rate and the amount of fuel injected per injection, thereby generating the corresponding fuel injection pattern.
[0061] Specifically, in step S50, the oil injection pattern is predicted based on the second measured parameter and the corrected elastic modulus, and the corresponding oil injection pattern is generated, including: Based on the second measured parameters, the corrected elastic modulus, the fuel density, and the real-time corrected volume of the constant volume chamber of the back pressure component based on the second measured parameters, the instantaneous injection rate and the single injection quantity are obtained. Based on the instantaneous injection rate and the amount of fuel injected in a single injection, a corresponding injection pattern is generated.
[0062] The formula for calculating the instantaneous injection rate can be expressed as: ; in, Indicates the instantaneous fuel injection rate. Indicates real-time volume adjustment. This indicates the modified elastic modulus. Indicates fuel density, Indicates time The second real-time back pressure, This represents the second real-time back pressure change rate.
[0063] The formula for calculating the amount of fuel injected in a single injection can be expressed as: ; in, Indicates the initial moment of fuel injection. Indicates the end time of fuel injection. This indicates the pressure in the constant volume chamber before fuel injection. This indicates the pressure in the constant volume chamber after oil injection.
[0064] By calculating and measuring the injection pattern using the above methods, the influence of back pressure fluctuations and changes in physical properties on the prediction results can be effectively eliminated, thereby improving the accuracy of the injection pattern results.
[0065] Please see Figure 2The present invention also provides a fuel injection pattern prediction system 11, comprising: an acquisition unit 111, used to acquire real-time parameters of the injector before the start of fuel injection into the back pressure assembly, the real-time parameters including the injection parameters corresponding to the injector and the first measured parameters in the back pressure assembly; a back pressure prediction unit 112, used to predict the back pressure of the constant volume cavity based on the injection parameters, the first measured parameters and the initial volume corresponding to the constant volume cavity of the back pressure assembly, to obtain the predicted back pressure; a deviation comparison unit 113, used to compare the predicted back pressure with the first real-time back pressure in the first measured parameters, to generate control parameters for the high-speed exhaust valve, so as to control the first real-time back pressure to the predicted back pressure; a modulus correction unit 114, used to dynamically correct the fuel elastic modulus based on the second measured parameters during fuel injection after back pressure control, to obtain the corrected elastic modulus; and a pattern generation unit 115, used to predict the fuel injection pattern based on the controlled second measured parameters and the corrected elastic modulus, to generate the corresponding fuel injection pattern.
[0066] It should be noted that the fuel injection pattern prediction system 11 provided in the above embodiments and the fuel injection pattern prediction method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the fuel injection pattern prediction system 11 provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.
[0067] Please see Figure 3 The electronic device 1 may include a memory 12, a processor 13 and a bus, and may also include a computer program stored in the memory 12 and capable of running on the processor 13, such as an injection pattern prediction program.
[0068] The memory 12 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 12 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 1. Furthermore, the memory 12 can include both internal and external storage units of the electronic device 1. The memory 12 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for predicting fuel injection patterns, but also to temporarily store data that has been output or will be output.
[0069] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the electronic device 1, connecting various components of the electronic device 1 through various interfaces and lines. It executes programs or modules (such as fuel injection pattern prediction programs) stored in the memory 12, and calls data stored in the memory 12 to perform various functions and process data of the electronic device 1.
[0070] The processor 13 executes the operating system of the electronic device 1 and various installed applications. The processor 13 executes the applications to implement the steps in the above-described fuel injection pattern prediction method.
[0071] For example, the computer program may be divided into one or more modules, which are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the electronic device 1. For example, the computer program may be divided into units in an injection pattern prediction system.
[0072] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium, which can be non-volatile or volatile. The software functional module stored in the storage medium includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute some functions of the fuel injection pattern prediction method described in the various embodiments of this application.
[0073] In summary, the fuel injection pattern prediction method and system disclosed in this invention utilizes the injection parameters of the injector before injection and the first measured parameters detected in the back pressure assembly to predict the back pressure in the constant volume chamber. The predicted back pressure is then compared with the first real-time back pressure from the first measured parameters. Based on the back pressure deviation, control parameters for regulating the high-speed exhaust valve are determined to adjust the first real-time back pressure to the predicted back pressure, ensuring that the initial back pressure in the constant volume chamber remains relatively stable during each injection process. This addresses cavitation during injection, allowing for the acquisition of a second measured parameter after dynamic exhaust regulation, ensuring the accuracy and reliability of the acquired second measured parameter in the constant volume chamber. Furthermore, the second measured parameter after exhaust regulation is used to dynamically correct the fuel elastic modulus. The corrected elastic modulus is then used in conjunction with the second measured parameter to determine the fuel injection pattern. This method effectively eliminates the influence of back pressure fluctuations and property changes on the prediction results during fuel injection pattern calculation, achieving accurate calculation of the fuel injection pattern and improving the accuracy of the results. Therefore, this invention effectively overcomes the various shortcomings of the prior art and has high industrial application value.
[0074] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.
Claims
1. A method for predicting fuel injection patterns, characterized in that, include: The real-time parameters of the injector before the start of fuel injection into the back pressure assembly are obtained. The real-time parameters include the injection parameters corresponding to the injector and the first measured parameters in the back pressure assembly. Based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant volume cavity of the back pressure assembly, the back pressure of the constant volume cavity is predicted to obtain the predicted back pressure. The predicted back pressure is compared with the first real-time back pressure in the first measured parameters to generate the control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure. The fuel elastic modulus is dynamically corrected based on the second measured parameter during fuel injection after back pressure regulation, and the corrected elastic modulus is obtained. Based on the second measured parameter and the modified elastic modulus, the oil injection pattern is predicted, and the corresponding oil injection pattern is obtained.
2. The method for predicting fuel injection patterns according to claim 1, characterized in that, The first measured parameters include the first real-time temperature and the first real-time back pressure of the constant volume cavity; Based on the injection parameters, the first measured parameters, and the initial volume corresponding to the constant-volume cavity of the back pressure assembly, the back pressure of the constant-volume cavity is predicted to obtain the predicted back pressure, including: The volume increment of the constant-volume cavity is obtained based on the first real-time temperature and the first real-time back pressure. The initial volume is dynamically adjusted based on the volume increment to obtain the real-time corrected volume corresponding to the fixed-volume cavity; The predicted back pressure is obtained by predicting the constant volume cavity back pressure based on the injection parameters and the real-time corrected volume.
3. The method for predicting fuel injection patterns according to claim 2, characterized in that, Based on the first real-time temperature and the first real-time back pressure, the volume increment of the constant-volume cavity is obtained, including: The expansion temperature is obtained based on the first real-time temperature and the reference temperature value; Based on the expansion temperature and expansion increment factor, the expansion coefficient corresponding to the back pressure component is obtained; The volume increment of the constant-volume cavity is obtained based on the first real-time back pressure, the reference pressure value, and the expansion coefficient. The formula for calculating the volume increment is: ； in, Indicates the volume increment. Indicates the first real-time temperature. Indicates the reference temperature value. Indicates the expansion increment factor. Indicates the first real-time back pressure. This indicates the reference pressure value.
4. The method for predicting fuel injection patterns according to claim 2, characterized in that, The injection parameters include the real-time rail pressure and injection pulse width of the injector; Based on the injection parameters and the real-time corrected volume, the back pressure of the constant volume cavity is predicted to obtain the predicted back pressure, including: The cumulative pressure on the constant volume cavity is obtained based on the real-time rail pressure and the injection pulse width. The predicted back pressure is obtained based on the accumulated pressure, the real-time corrected volume, the back pressure matching coefficient, and the first real-time back pressure of the constant volume cavity; The formula for calculating the predicted back pressure is as follows: ； in, Indicates predicted back pressure, Indicates the first real-time back pressure. Indicates the back pressure matching coefficient. Indicates real-time rail pressure. Indicates the pulse width of the jet. Indicates the pulse width of the jet. Every moment inside, This indicates that the volume is adjusted in real time.
5. The method for predicting fuel injection patterns according to claim 1, characterized in that, The predicted back pressure is compared with the first real-time back pressure in the first measured parameters to generate control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure, including: The difference between the predicted back pressure and the first real-time back pressure is calculated to obtain the back pressure deviation. Based on the current back pressure deviation at the current moment and the previous back pressure deviation at the previous moment, the deviation change rate corresponding to the current back pressure deviation is obtained. Based on the cumulative value of the back pressure deviation, the current back pressure deviation, and the deviation change rate, control parameters for the high-speed oil discharge valve are generated to adjust the first real-time back pressure to the predicted back pressure.
6. The method for predicting fuel injection patterns according to claim 5, characterized in that, Based on the cumulative value of the back pressure deviation, the current back pressure deviation, and the rate of change of the deviation, control parameters for the high-speed oil discharge valve are generated to adjust the first real-time back pressure to the predicted back pressure, including: The cumulative value of the deviation is obtained by integrating the back pressure deviation at different times. The cumulative deviation value, the current back pressure deviation, and the deviation change rate are weighted and fused to obtain the deviation adjustment amount; Based on the current back pressure deviation and the rate of change of the deviation, the corresponding dynamic fuzzy compensation amount is obtained by looking up the table. Based on the deviation adjustment amount and the dynamic fuzzy compensation amount, control parameters for the high-speed oil discharge valve are generated to adjust the first real-time back pressure to the predicted back pressure. The formula for calculating the control parameter is as follows: ； Indicates the control parameter, This represents the coefficient for the proportional control item. Represents the coefficient of the integral control term. Represents the coefficient of the differential control term. Indicates the current back pressure deviation. This indicates the back pressure deviation at different times. Indicates the pre-adjustment time before fuel injection. This indicates the corresponding time for each back pressure deviation. Indicates the rate of change of deviation. This represents the amount of dynamic fuzzy compensation.
7. The method for predicting fuel injection patterns according to claim 1, characterized in that, The second measured parameters include the second real-time temperature and the second real-time back pressure of the constant volume cavity; The fuel elastic modulus is dynamically corrected based on the second measured parameter during fuel injection after back pressure regulation, resulting in a corrected elastic modulus, including: Based on the second measured parameter and the corresponding benchmark value, a first correction amount for the elastic modulus of the fuel is generated; Based on the component design model corresponding to the back pressure component and the second measured parameters, feature adaptation analysis is performed to obtain the second correction amount for the fuel elastic modulus. The fuel elastic modulus is dynamically corrected based on the first correction amount, the second correction amount, and the corresponding correction coefficient to obtain the corrected elastic modulus. The formula for calculating the modified elastic modulus is: ； in, This indicates the modified elastic modulus. Indicates the elastic modulus of fuel. Indicates the second measured parameter. This represents the baseline value corresponding to the second measured parameter. This represents the correction factor corresponding to the second measured parameter. This indicates the first weight ratio corresponding to the first correction amount. This indicates the second correction amount. This indicates the second weighting ratio corresponding to the second correction amount.
8. The method for predicting fuel injection patterns according to claim 7, characterized in that, Based on the component design model corresponding to the back pressure component and the second measured parameters, feature adaptation analysis is performed to obtain a second correction amount for the fuel elastic modulus, including: Based on the real-time correction volume of the fixed-volume cavity of the back pressure component according to the second measured parameters, the active area of the component design model is queried and adjusted to obtain the updated component model; Based on the second measured parameters, all key impact features and the corresponding design impact benchmark parameter values are obtained by looking up the table. The component update model is detected based on the key impact features and the design impact benchmark parameter values to obtain abnormal design features; The difference between the feature parameter value corresponding to the abnormal design feature and the design influence benchmark parameter value corresponding to the corresponding key influence feature is calculated to obtain the feature difference; Based on the characteristic difference and the corresponding correction factor, a second correction amount for the elastic modulus of the fuel is obtained; The formula for calculating the second correction amount is: ； in, This indicates the second correction amount. This represents each dimension corresponding to the abnormal design features. The correction factor below, Represent each dimension The characteristic parameter values below, Represent each dimension The design affects the baseline parameter values.
9. The method for predicting fuel injection patterns according to claim 8, characterized in that, Based on the real-time correction volume of the constant-volume cavity of the back pressure component according to the second measured parameters, the active area of the component design model is queried and adjusted to obtain the updated component model, including: Based on the coordinate range, action weight, and real-time correction volume of each action region in the component design model, a volume correction amount for each action region is generated. The component design model is adjusted based on the volume correction amount to obtain the updated component model.
10. A fuel injection pattern prediction system, characterized in that, include: The acquisition unit is used to acquire real-time parameters of the injector before the injection of fuel into the back pressure assembly begins. The real-time parameters include the injection parameters corresponding to the injector and the first measured parameters in the back pressure assembly. The back pressure prediction unit is used to predict the back pressure of the constant volume cavity based on the injection parameters, the first measured parameters and the initial volume corresponding to the constant volume cavity of the back pressure assembly, so as to obtain the predicted back pressure. The deviation comparison unit is used to compare the predicted back pressure with the first real-time back pressure in the first measured parameters to generate the control parameters for the high-speed oil discharge valve, so as to control the first real-time back pressure to the predicted back pressure. The modulus correction unit is used to dynamically correct the fuel elastic modulus based on the second measured parameter during fuel injection after back pressure regulation, so as to obtain the corrected elastic modulus. as well as The pattern generation unit is used to predict the oil injection pattern based on the second measured parameters and the modified elastic modulus, and generate the corresponding oil injection pattern.