Adaptive high pressure fuel pump system and method of predicting pumping quality

Abstract

The present invention relates to an adaptive high pressure fuel pump system and a method of predicting pumped quantity. There is provided a method of predicting a quantity of fuel ("Q pump ") pumped by a pump during a pumping event to a fuel accumulator to control operation of the pump, the method comprising: generating a model of operation of the pump, generating the model of operation of the pump comprising: estimating a start of pumping ("SOP") position of a plunger of the pump, estimating Q pump , determining a converged value of the estimated SOP position and determining a converged value of the estimated Q pump ; predicting Q pump using the model by inputting the converged value of the estimated SOP position, a measured fuel pressure in the fuel accumulator and a measured fuel temperature in the fuel accumulator to the model; and controlling operation of the pump in response to the predicted Q pump .

Description

[0001] This application is a divisional application of the parent application number 201880092251.3 (International application number PCT / US2018 / 026891) filed on April 10, 2018, entitled Adaptive High Pressure Fuel Pump System and Method of Predicting Pumped Fuel Quality. TECHNICAL FIELD

[0002] The present invention relates generally to fuel pumps, and more particularly to methods and systems for adaptively modeling the operation of a high pressure fuel pump to predict pumped fuel quality for control and diagnostic applications. BACKGROUND

[0003] In an internal combustion engine, one or more fuel pumps deliver fuel to a fuel accumulator. Fuel is delivered by fuel injectors from the accumulator to cylinders of the engine for combustion to power the operation of systems driven by the engine. It is desirable to accurately characterize the amount of fuel delivered by the fuel pump to the accumulator for a variety of reasons. In conventional fuel delivery systems, the operation of the fuel pump is characterized periodically by shutting down the fuel pump and measuring various variables of the fuel delivery system. This approach disrupts the operation of the engine and provides inaccurate results. Accordingly, there is a need for an improved method to predict the amount of fuel pumped by the fuel pump during the operation of the pump. SUMMARY

[0004] According to one embodiment, the present disclosure provides a method of adaptively predicting a mass of fuel pumped by a pump during a pumping event to a fuel accumulator (“Q pump ”) during the operation of the pump to control the operation of the pump, the method comprising: generating an adaptive model of the operation of the pump, generating the adaptive model of the operation of the pump comprising: estimating a start of pumping (“SOP”) position of a plunger of the pump, estimating Q pump , determining a converged value of the estimated SOP position, and determining a converged value of the estimated Q pump ; predicting Q pump using the adaptive model by inputting the converged value of the estimated SOP position, a measured fuel pressure in the fuel accumulator, and a measured fuel temperature in the fuel accumulator to the adaptive model; and controlling the operation of the pump in response to the predicted Q pumpTo control the operation of the pump. In a first aspect of this embodiment, estimating the SOP position includes: receiving a raw measurement of the fuel pressure in the fuel accumulator; identifying a quiet segment in the raw measurement; fitting a model to the identified quiet segment; using the fitted model to determine an output representing the propagation of the fuel pressure in the fuel accumulator undisturbed by a pumping event; and identifying the difference between the output of the fitted model and the raw measurement of the fuel pressure in the fuel accumulator. In a variation of this aspect, identifying the quiet segment includes: filtering the raw measurement using a median filter, the length of which corresponds to the oscillation frequency of the fuel pressure in the fuel accumulator. In another variation, the median filter is tuned to the oscillation frequency, the speed of sound of the fuel, and the geometry of the fuel accumulator. In yet another variation, identifying the quiet segment further includes: evaluating the derivative of the filtered raw measurement to identify a segment with an approximately zero slope of the derivative. In yet another variation, fitting a model to the identified quiet segment includes: using the following relationship: In another aspect of this implementation, Q is estimated. pump This includes calculating the pressure difference between the average pressure before and after the pumping event. A variation of this involves estimating Q. pump This also includes converting the calculated pressure difference into mass. In another aspect, the adaptive model uses the following relationship: Qpump = fcam(EOP - SOP) * A * δ(P,T) - t * L(P,T), where fcam is the relationship between the plunger position and the engine crank angle, EOP is the endpoint of the plunger's pumping position, A is the area of ​​the plunger, δ(P,T) is the density of the fuel in the fuel accumulator, t is the duration of the pumping event, and L(P,T) is the fuel leakage of the fuel pump. In a variant of this aspect, (P,T) is modeled using a first-order polynomial in the fuel temperature dimension or at least a second-order polynomial in the fuel pressure dimension. In another variant, L(P,T) is modeled using a first-order polynomial in the fuel temperature dimension or at least a second-order polynomial in the fuel pressure dimension. In yet another aspect, controlling the pump's operation includes adjusting either the timing of the pumping event or the duration of the pumping event.

[0005] In another embodiment of this disclosure, a method is provided to adaptively predict the mass of fuel pumped by the pump during a pumping event to a fuel accumulator (“Q”). pump") to control operation of a pump, the system comprising: a pressure sensor positioned to measure fuel pressure in a fuel accumulator; a temperature sensor positioned to measure fuel temperature in the fuel accumulator; and a processor in communication with the pressure sensor to receive a pressure value representative of the measured fuel pressure in the fuel accumulator and in communication with the temperature sensor to receive a temperature value representative of the measured fuel temperature in the fuel accumulator; wherein the processor is configured to: generate an adaptive model of operation of the pump by estimating a start of pump ("SOP") position of a plunger of the pump, estimating Q pump , determining a converged value of the estimated SOP position, and determining a converged value of the estimated Q pump ; predict Q pump using the adaptive model by inputting the converged value of the estimated SOP position, the pressure value, and the temperature value to the model; and control operation of the pump in response to the predicted Q pump . In one aspect of the embodiment, the processor is configured to estimate the SOP position by receiving the pressure value; identifying a quiet section in the pressure value; fitting a model to the identified quiet section; determining an output using the fitted model, the output representative of propagation of fuel pressure in the fuel accumulator without disturbance by a pumping event; and identifying a difference between the output of the fitted model and the pressure value. In a variation of this aspect, the processor is configured to identify the quiet section by filtering the pressure value with a median filter, a length of the median filter corresponding to an oscillation frequency of the fuel pressure in the fuel accumulator. In another variation, the processor is configured to identify the quiet section by evaluating a derivative of the filtered pressure value to identify a section of the derivative having an approximately zero slope. In another aspect, the processor is configured to estimate Q pump by calculating a pressure difference between an average pressure before a pumping event and an average pressure after the pumping event. In yet another aspect, the adaptive model uses the following relationship: Qpump = fcam(EOP-SOP)*A*δ(P,T)-t*L(P,T), where fcam is a table of relationship of position of the plunger to crank angle of the engine, EOP is an end of pump position of the plunger, A is an area of the plunger, δ(P,T) is a density of fuel in the fuel accumulator, t is a duration of the pumping event, and L(P,T) is a fuel leakage of the fuel pump. In a variation of this aspect, at least one of (P,) and (P,T) is modeled by a first order polynomial in fuel temperature dimension or at least a second order polynomial in fuel pressure dimension. In yet another aspect, the processor is configured to control operation of the pump by adjusting one of timing of the pumping event or duration of the pumping event.

[0006] While multiple embodiments are disclosed, still other embodiments of the application will become apparent to those skilled in the art from the following detailed description, which shows and describes illustrative embodiments of the application. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature rather than restrictive. BRIEF DESCRIPTION OF DRAWINGS

[0007] The above and other features of the present disclosure, as well as the manner of attaining them, will become more apparent and the disclosure itself will be better understood by reference to the following description of embodiments of the present disclosure taken together with the accompanying drawings.

[0008] Figure 1 is a schematic diagram of a fuel supply system;

[0009] Figure 2 is a plot showing measured rail pressure and a median filtered representation of measured rail pressure;

[0010] Figure 3 is a plot similar to Figure 2 showing quiet sections of measured rail pressure;

[0011] Figure 4 is a plot showing output traces of a model according to the present disclosure similar to Figure 3 ;

[0012] Figure 5 is a plot showing estimated start of pumping positions of a fuel pump similar to Figure 4 ;

[0013] Figure 6 is a plot of the difference between measured rail pressure of Figure 4 and output traces of Figure 4 ; and

[0014] Figure 7 is a plot showing average rail pressure before and after a pumping event.

[0015] While the present disclosure can take various forms, specific embodiments thereof have been shown by way of example in the drawings and will hereinafter be described in detail; it being understood that the present disclosure is not limited to the particular embodiments described. Rather, the present disclosure is intended to cover all modifications, equivalents, and alternatives falling within the scope of the appended claims. DETAILED DESCRIPTION

[0016] Those of ordinary skill in the art will realize that the implementations provided can be implemented in a variety of ways, in hardware, software, firmware, and / or combinations thereof. For example, the controllers disclosed herein can form part of a processing subsystem that includes one or more computing devices with memory, processing, and communication hardware. The controllers can be single devices or distributed devices, and the functionality of the controllers can be performed by hardware and / or as computer instructions on a non-transitory computer-readable storage medium. For example, the computer instructions or programming code in the controllers (e.g., an electronic control module (“ECM”)) can be implemented in any workable programming language, such as C, C++, HTML, XTML, JAVA, or any other workable high-level programming language or a combination of high-level and low-level programming languages.

[0017] As used herein, the modifier “about” used in connection with a quantity is inclusive of the stated value and has the meaning dictated by the context (e.g., it includes at least an amount that is the degree of error associated with a particular measurement of the quantity). When used in connection with a range, the modifier “about” should also be considered to disclose the range defined by the absolute values of the two endpoints. For example, a range of “from about 2 to about 4” also discloses a range of “from 2 to 4.”

[0018] Referring now to Figure 1 , a schematic view of a portion of a high-pressure pump is shown. As is known in the art, the pump 10 includes a plunger 12 reciprocating within a barrel 14. Fuel is supplied through an inlet 18 to a chamber 16 within the barrel 14, is compressed by upward movement of the plunger 12, increasing the pressure of the fuel, and is supplied through an outlet 20 to an outlet check valve (OCV) 22 and to a fuel reservoir, such as a common rail accumulator (hereinafter rail 24). Fuel from the rail 24 is periodically delivered by a plurality of fuel injectors 25 to a corresponding plurality of cylinders (not shown) of an internal combustion engine (not shown). A small circumferential gap 26 exists between an outer surface 28 of the plunger 12 and an inner surface 30 of the barrel 14 to permit reciprocation of the plunger 12 within the barrel 14.

[0019] As the plunger 12 moves in a pumping cycle, the plunger 12 moves between a start of pump (SOP) position and an end of pump (EOP) position. The SOP position is after the plunger 12 moves past its bottom dead center (BDC) position, and the EOP position is before the top dead center (TDC) position of the plunger 12.

[0020] As described above, during the compression stroke of the plunger 12 (i.e., as it moves from the BDC position to the TDC position), the fuel in the chamber 16 is compressed, causing the pressure in the chamber 16 to increase to the point where the force on the chamber side of the OCV 22 is equal to the force on the rail side of the OCV 22. As a result, the OCV 22 opens, and fuel begins to flow to the rail 24 via the outlet 20 and the OCV 22. As the plunger 12 continues to travel toward the TDC position, fuel continues to flow to the rail 24 in this manner. As a result, the pressure of the fuel in the rail 24 increases. The processor 21 receives the fuel pressure within the rail 24 from the pressure sensor 23 and the fuel temperature within the rail 24 from the temperature sensor 27. As described herein, the processor 21 also controls the operation of the injector 25.

[0021] The present disclosure provides a model of the high-pressure pump 10 that is particularly useful for predicting the mass of fuel pumped by the pump 10 to the rail 24, which provides benefits to the fuel control system described herein. For the purposes of the model, it is assumed that, during the pumping operation of the pump 10, fuel can only flow to the rail 24 via the outlet 20 and the OCV 22 as supplied fuel, and / or to the return line 32 (which routes the fuel back to a fuel tank (not shown)) as leakage. This characteristic of the pump 10 can be mathematically described by the following equation:

[0022] Qpump = fcam(EOP-SOP) * A * δ(P,T) - t*L(P,T) (1)

[0023] where Qpump is the output mass from the pump 10 to the rail 24, fcam is a polynomial or table describing the relationship between crank angle (in degrees) and plunger 12 lift. More specifically, when the pump 10 is coupled to the engine crankshaft by a gear assembly and is driven in operation by the rotation of the crankshaft, the crank angle of the crankshaft is directly related to the position of the plunger 12 of the pump 10. Thus, the positions of the SOP and EOP can be expressed in terms of crank angle. Once the SOP is determined, the swept height of the plunger 12 during the pumping cycle (and thus, the swept volume of the chamber 16) can be determined given the geometry of the pump 10. The table expressed by fcam can be a lookup table that is specific to a particular pump 10 and relates crank angle to the position of the plunger 12.

[0024] (EOP-SOP) describes the crank angle degrees between the SOP position and the EOP position. It should be understood that there is a difference between the TDC position and the EOP position. The TDC position is when the plunger 12 physically reaches its top position, while the EOP position is the end of the pumping stroke as observed by the pressure sensor 23. As understood by those skilled in the art, the relationship between the TDC position and the EOP position depends on the speed of sound of the fuel and the geometry of the high pressure system (i.e., rail 24).

[0025] Further with reference to equation (1) above, A is the area of the plunger 12. The area A, together with fcam(EOP-SOP), determines the swept volume of fuel pumped to the rail 24. (P,) is the density of the fuel, which can be modeled as a first order polynomial in T (fuel temperature) and a second order polynomial in P (pressure of the rail 24). t (time) is used to represent the duration of the pumping stroke when the OCV 22 is open. Finally, L(P,T) represents the fuel leakage (i.e., between the barrel 14 and the plunger 12), and can be described as a first order polynomial in T and a high order polynomial in P. In certain embodiments, P 2.5 It should be understood that there can be cross terms between temperature and pressure.

[0026] Given the SOP position of the plunger 12 (determination of which is described below), the pressure from the pressure sensor 23, and the temperature from the temperature sensor 27, the model can be used to predict the output mass of the pump 10 under any set of operating conditions. Also usefully, the model described above relies on known values of leakage, fuel density, and EOP position. Unfortunately, leakage varies with changes between parts (e.g., plunger 12 and barrel 14) and wear of parts over time. Fuel density is different for different types and sources of fuel. Additionally, the EOP position is not typically known for a particular pump 10 on a particular engine. In accordance with the principles of the present disclosure, the pump model can be made adaptive by estimating the unknown variables using an Extended Kalman filter.

[0027] As described above, the rail pressure sensor 23 and the rail temperature sensor 27 provide the processor 21 with measurements of the fuel pressure in the rail 24 and the fuel temperature in the rail 24, respectively. In addition to these inputs, the adaptive pump model described above requires estimation of the SOP position and Qpump. As described above, the SOP position can be indicated by the occurrence of a trace increase in the fuel pressure in the rail 24 (i.e., rail pressure) due to the pumping action of the pump 10. To identify the SOP position in this manner, one can first determine quiet sections in the buffer of rail pressure measurements. These quiet sections correspond to instances where no fuel is being pumped into or injected from the rail 24. The quiet sections can be determined by processing the rail pressure measurements with a median filter having a length corresponding to the time period of the operating mode of the rail 24. This operating mode corresponds to one or more oscillation frequencies of the pressure within the rail 24. There can be one or more sinusoidal modes that are produced by the median filter to remove oscillations and identify when pumping and quiet sections occur. If there are multiple oscillation frequencies, the median filter will be run multiple times with different filter lengths corresponding to the different frequencies.

[0028] Referring now to Figure 2 , the original rail pressure is shown as trace 34, and a median filtered version of the trace 34 is depicted as trace 36. As shown by trace 36, the median filter effectively removes noise and oscillations from the trace 34 while maintaining the injection and pumping characteristics of the original data without losing any important high frequency information. The filter is similar to a moving average centered, but uses median pressure instead of average pressure. The filter is tuned to the oscillation frequency predicted for the particular rail pressure, speed of sound of the fuel, and geometry of the rail 24.

[0029] Referring now to Figure 3 , the processor 21 can identify quiet sections from the output of the median filter by evaluating the derivative of the trace 36 (i.e., the filtered rail pressure signal). The quiet sections are highlighted as sections 38 in Figure 3 . It should be understood that the quiet sections 38 are simply those portions of the original data trace 34 that correspond to the horizontal or flat portions of the filtered data trace 36. In other words, the quiet sections of the original data trace 34 correspond in time to sections of the filtered data trace 36 that have an approximately zero slope.

[0030] According to the present disclosure, the processor 21 next fits a 2-mode model to the identified quiet sections 38. This model is described by equation (2) below.

[0031]

[0032] where the damping factor and the angular velocity ω i(both depending on the speed of sound) are known. As will be appreciated by those skilled in the art having the benefit of the present disclosure, equation (2) can be modified to include any number of modes by including additional sinusoidal terms. Equation (2) can be rewritten using the trigonometric identity to:

[0033]

[0034] Equation (3) can be further rewritten as a linear system that processor 21 can use to obtain the least squares estimate of Pmean, and a i The values of Pmean, can be found by solving the following linear system:

[0035]

[0036] which has the solution:

[0037]

[0038]

[0039] As such, the amplitude, phase, damping, and frequency of the free response dynamics are known, and can represent the propagation of rail pressure dynamics in the absence of pumping events. The output of this model is plotted as trace 40 (along with the data on which it is based) in Figure 4

[0040] In the next step, processor 21 can use the difference between the original rail pressure data (trace 34) and the model (trace 40) to obtain an estimate of the SOP location. Referring to Figure 5 , the estimated SOP location is indicated as point 42. The estimated SOP location 42 is the location at which the original data and the fitted model diverge from one another. Figure 6 The difference between the original rail pressure data (trace 34) and the fitted model (trace 40) is shown.

[0041] The fuel mass delivered from pump 10 to rail 24 (i.e., Q pump ) can be estimated in a manner similar to conventional fuel injection quantity estimation. ΔΡ is measured by pressure sensor 23, read by processor 21, and then converted to mass using the knowledge of the pressurized volume in the fuel and the speed of sound. As shown in Figure 7 ΔΡ is calculated by processor 21 as the difference between the average pressure before and after the pumping event. The average pressure is obtained using the same least squares method as was used to obtain the SOP location estimate (as described above), where the average pressure is one of the estimates.

[0042] ​After the adaptive pump model converges, the pumping quality can be predicted by feeding the model with the SOP position, rail pressure, and rail temperature. Using the model of the present disclosure, fuel injection measurements can be obtained without disabling the high pressure pump 10. Further details of this application of the model according to the present disclosure are described in co-pending patent application S / N PCT / US2018 / 026874, filed April 10, 2018, entitled “SYSTEM AND METHOD FOR MEASURING FUEL INJECTION DURING PUMP OPERATION” (hereinafter, referred to as “the injection measurement application”), the entire disclosure of which is expressly incorporated herein by reference. In this sense, the present disclosure provides a non-intrusive measurement method, as the data is collected during normal operation. Also, the model can be used to estimate the fuel density, which can be used to determine the type of fuel (diesel, winter diesel, biodiesel, etc.) being pumped by the pump 10. Furthermore, the model can be used in a feed forward application to provide better control of the fuel pressure in the rail 24. As the injectors 25 inject fuel from the rail 24, the fuel in the rail 24 needs to be replaced to maintain mass balance in the system. As such, the time and extent of the pump 10 operation can be controlled according to the principles of the present disclosure to maintain mass balance, as determined by the adaptive model described herein. Also, the model can be used to monitor the fuel injection quantity, pump output, and / or leakage for diagnostic purposes.

[0043] It should be appreciated that the teachings of the present disclosure provide a mechanism for understanding the performance of the pump 10 (e.g., the extent of its leakage, etc.). In the injection measurement application, the pump performance determined by the present application is used to determine the amount of fuel injected for each fuel injection event, and to control the fuel injectors and perform diagnostics.

[0044] Additionally, the adaptive model of the present disclosure permits the calculation of fuel efficiency (e.g., miles per gallon), as the fuel density, injection quantity, and leakage can be estimated. Furthermore, as the EOP can be identified, the synchronization or timing of the pumping event relative to the fuel injection event can be determined. This information can be used to control the characteristics (timing and / or duration) of the pumping event, to determine if the pump is installed incorrectly, and to adjust the operation of the pump to increase its useful life.

[0045] It should be understood that the connecting lines shown in the various figures contained herein are intended to represent exemplary functional relationships and / or physical couplings between the various elements. It should be noted that many alternatives or additional functional relationships or physical connections can be present in a practical system. However, benefits, advantages, solutions to problems, and any element(s) that can cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as critical, required, or essential features or elements. Therefore, the scope of the disclosure is, in relevant part, limited solely by the appended claims, wherein the singular forms "a", "an", and "the" are intended to mean "one or more" unless expressly specified otherwise. Furthermore, to the extent that the terms "includes", "including", "has", "having" or variants thereof are used in either the detailed description or the claims, such terms are intended to be inclusive in a manner similar to the term "comprising". Additionally, where a choice of alternatives is present, the use of "or" as a conjunction is intended to present one of the alternatives, but not require exclusion of the other alternative(s) unless explicitly indicated otherwise.

[0046] In the detailed description of the disclosure, references are made to "one embodiment", "an embodiment", "an example embodiment", etc. indicating that a described embodiment can include a particular feature, structure, or characteristic, but each embodiment can not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, where a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of those skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described, in combination with other embodiments. After reading the specification, skilled artisans will be well aware of how to make and use the present disclosure in view of alternatives they will conceive to the ready practice made possible by the disclosure, as set forth herein.

[0047] Further, no element, component, or method step in the present disclosure is intended to be dedicated to the public, regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element recited in any claim of this patent is intended to be a recurring element, multitude of the recited element or elements, or list of recited elements of any particular claim element unless expressly recited by the language "one or more" or "at least one" or some other technical conjunction. None of the claims are intended to invoke 35 U.S.C. § 112(f) unless the language "means" or "step for" is expressly recited in the claim. As used herein, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0048] Various modifications and additions can be made to the exemplary embodiments discussed without departing from the scope of the disclosure. For example, while the embodiments discussed above refer to particular features, the scope of this disclosure also includes embodiments having different combinations of features and embodiments that do not include all of the described features. It is intended, therefore, that the scope of the disclosure encompass all alternatives, modifications and variations falling within the scope of the claims below.

Claims

1. A method for predicting the mass of fuel pumped by a pump during a pumping event to a fuel accumulator in order to control the operation of the pump, the method comprising: Generate a model of the pump's operation, including determining a convergence value for the estimated pumping start position of the pump's plunger; The model is used to predict the mass of fuel pumped by the pump during the pumping event to the fuel accumulator by inputting the estimated convergence value of the pumping start position, the measured fuel pressure in the fuel accumulator, and the measured fuel temperature in the fuel accumulator into the model. as well as The operation of the pump is controlled in response to the predicted mass of fuel pumped by the pump during the pumping event to the fuel accumulator.

2. The method according to claim 1, wherein, The estimated pumping start position includes: Receive the raw measurement value of the fuel pressure in the fuel accumulator; Identify quiet segments within the raw measurements; Fit the model to the identified quiet areas; The fitted model is used to determine the output, which represents the propagation of the fuel pressure in the fuel accumulator undisturbed by pumping events; and Identify the difference between the output of the fitted model and the original measurement of fuel pressure in the fuel accumulator.

3. The method according to claim 2, wherein, Identifying quiet sections includes filtering the raw measurements using a median filter, the length of which corresponds to the oscillation frequency of the fuel pressure in the fuel accumulator.

4. The method according to claim 3, wherein, The median filter is tuned to the oscillation frequency, the speed of sound of the fuel, and the geometry of the fuel accumulator.

5. The method according to claim 3, wherein, Identifying quiet sections also includes evaluating the derivative of the filtered original measurements to identify sections where the derivative has an approximate zero slope.

6. The method according to claim 1, wherein, Estimating the mass of fuel transferred from the pump to the fuel accumulator includes calculating the pressure difference between the average pressure before the pumping event and the average pressure after the pumping event.

7. The method according to claim 6, wherein, Estimating the mass of fuel transferred from the pump to the fuel accumulator also includes converting the calculated pressure difference into mass.

8. The method according to claim 1, wherein, The model uses the following relationship: Qpump=fcam(EOP-SOP)*A*δ(P,T)-t*L(P,T), where Qpump is the predicted mass of fuel pumped by the pump during the pumping event to the fuel accumulator, fcam is the relationship between the plunger position and the crank angle of the engine, EOP is the end point of the plunger's pumping position, SOP is the start point of the plunger's pumping position, P is the fuel pressure, T is the fuel temperature, A is the area of ​​the plunger, δ(P,T) is the density of the fuel in the fuel accumulator, t is the duration of the pumping event, and L(P,T) is the fuel leakage of the pump.

9. The method according to claim 8, wherein, δ(P,T) is modeled by a first-order polynomial in the fuel temperature dimension or at least a second-order polynomial in the fuel pressure dimension.

10. The method according to claim 8, wherein, L(P,T) is modeled by a first-order polynomial in the fuel temperature dimension or at least a second-order polynomial in the fuel pressure dimension.

11. The method according to claim 1, wherein, Controlling the operation of the pump includes adjusting either the timing of the pumping event or the duration of the pumping event.

12. A system for predicting the quality of fuel pumped by a pump during a pumping event to a fuel accumulator in order to control the operation of the pump, the system comprising: A pressure sensor, which is configured to measure the fuel pressure in the fuel accumulator; A temperature sensor, the temperature sensor being positioned to measure the fuel temperature in the fuel accumulator; as well as The processor communicates with the pressure sensor to receive a pressure value representing the measured fuel pressure in the fuel accumulator, and the processor communicates with the temperature sensor to receive a temperature value representing the measured fuel temperature in the fuel accumulator. The processor is configured as follows: A model of the pump's operation is generated by determining the convergence value of the estimated pumping start position of the pump's plunger. The model is used to predict the mass of fuel pumped by the pump during the pumping event to the fuel accumulator by inputting the estimated convergence value, pressure value, and temperature value of the pumping start location into the model. and The operation of the pump is controlled in response to the predicted mass of fuel pumped by the pump during the pumping event to the fuel accumulator.

13. The system according to claim 12, wherein, The processor is configured to estimate the pumping start position by: receiving the pressure value; identifying a quiet segment within the pressure value; fitting a model to the identified quiet segment; using the fitted model to determine an output representing the propagation of the fuel pressure in the fuel accumulator undisturbed by a pumping event; and identifying the difference between the output of the fitted model and the pressure value.

14. The system according to claim 13, wherein, The processor is configured to identify the quiet zone by filtering the pressure value using a median filter, the length of which corresponds to the oscillation frequency of the fuel pressure in the fuel accumulator.

15. The system according to claim 14, wherein, The processor is configured to identify the quiet section by evaluating the derivative of the filtered pressure value to identify sections of the derivative with an approximate zero slope.

16. The system according to claim 12, wherein, The processor is configured to estimate the mass of fuel delivered to the fuel accumulator by the pump by calculating the pressure difference between the average pressure before the pumping event and the average pressure after the pumping event.

17. The system according to claim 12, wherein, The model uses the following relationship: Qpump=fcam(EOP-SOP)*A*δ(P,T)-t*L(P,T), where Qpump is the predicted mass of fuel pumped by the pump during the pumping event to the fuel accumulator, fcam is the relationship between the plunger position and the crank angle of the engine, EOP is the end point of the plunger's pumping position, SOP is the start point of the plunger's pumping position, P is the fuel pressure, T is the fuel temperature, A is the area of ​​the plunger, δ(P,T) is the density of the fuel in the fuel accumulator, t is the duration of the pumping event, and L(P,T) is the fuel leakage of the pump.

18. The system according to claim 17, wherein, At least one of δ(P,T) and L(P,T) is modeled by a first-order polynomial in the fuel temperature dimension or at least a second-order polynomial in the fuel pressure dimension.

19. The system according to claim 12, wherein, The processor is configured to control the operation of the pump by adjusting either the timing of the pumping event or the duration of the pumping event.

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