A fuel tank fuel level estimation method for fuel surface sloshing and consumption scenarios

Abstract

The application discloses a kind of fuel liquid level sloshing and consumption scene-oriented fuel tank fuel residual quantity estimation method, first, the mapping relationship prior model of different liquid filling ratio and sloshing signal is constructed, and liquid level sloshing mode identification is carried out;Afterwards, the type of sloshing signal is determined based on the mapping relationship model of different liquid filling ratio and sloshing signal and liquid level sloshing mode;Finally, the estimated value of sloshing amplitude and the real-time fuel residual quantity estimation value are determined.The scheme of the application is realized in combination with prior model and conditional statement, the requirement for computing power is lower, and the requirement for hardware sensor equipment is lower, only needs rod type liquid level meter and other equipment, without erecting other various sensors, can further reduce the cost of fuel residual quantity estimation system, engineering implementation and application difficulty are very small, have certain popularization and industrialization potential.

Description

Technical Field

[0001] This invention belongs to the field of signal processing, specifically relating to a method for estimating the remaining fuel level in a fuel tank for scenarios involving fuel level sloshing and consumption. Background Technology

[0002] Due to payload limitations, spacecraft can only carry a limited amount of fuel. Therefore, precise monitoring of remaining fuel levels is crucial to help personnel and systems promptly determine the remaining fuel status in the tanks, estimate fuel consumption rates and remaining operational time, and prevent accidents caused by fuel depletion.

[0003] Current detection solutions primarily rely on liquid level sensors to obtain fuel remaining information. However, the equipment itself undergoes maneuvering during operation, causing some degree of sloshing of the fuel level within the tank. Simultaneously, due to continuous operation, fuel is constantly consumed, resulting in a time-varying downward trend in the liquid level. This trend, combined with the sloshing, creates unavoidable time-varying sloshing interference signals, posing a significant challenge to the real-time accurate detection of liquid level and fuel remaining by current height sensors. Furthermore, the performance of flow rate sensors in some devices deteriorates over long-term use, leading to inaccurate flow rate measurements and making it impossible to estimate the remaining fuel mass based on the initial liquid level, flow rate, and operating time. Existing solutions primarily rely on methods such as mean filtering to mitigate errors caused by liquid level sloshing and external disturbances, but their effectiveness is limited, and the estimated liquid level data still deviates somewhat from the true value.

[0004] Therefore, there is an urgent need for a method for estimating the remaining fuel level in a storage tank based on data detected by a liquid level sensor, which is applicable to scenarios involving fuel level sloshing and consumption. Summary of the Invention

[0005] To address the aforementioned problems, the present invention aims to provide a method for estimating the remaining fuel level in a storage tank under scenarios involving fuel level sloshing and consumption, so as to accurately estimate the remaining fuel level under such conditions.

[0006] The specific technical solution for achieving the objective of this invention is as follows:

[0007] A method for estimating the remaining fuel level in a fuel tank under scenarios involving fuel level sloshing and consumption includes the following steps:

[0008] Step 1: Construct a priori model of the mapping relationship between different filling ratios and swaying signals;

[0009] Step 2: Identify the liquid level sloshing pattern;

[0010] Step 3: Combine the mapping relationship model between different filling ratios and sloshing signals in Step 1, and the liquid level sloshing mode in Step 2, to determine the type of sloshing signal;

[0011] Step 4: Determine the estimated value of the sway amplitude;

[0012] Step 5: Determine the estimated real-time fuel balance.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0014] (1) The present invention proposes a sloshing pattern recognition method and a liquid sloshing signal modeling method. The former can be used to determine whether the actual liquid level is higher or lower than the sensor level by analyzing the trend and mechanism of the 0 or 1 signal of the sensor measurement point over time; the latter modeling method can be applied to the analysis and construction of sloshing signal models of tanks of different shapes under different filling ratios.

[0015] (2) The solution of the present invention combines prior models and conditional statements, which has low requirements for computing power and hardware sensor equipment. Only rod level gauges and other equipment are needed. There is no need to install other sensors such as visual cameras and ultrasonic level gauges. This can further reduce the cost of the fuel balance estimation system. The engineering implementation and application are very easy, and it has certain potential for promotion and industrialization.

[0016] (3) The present invention combines the real-time liquid level height estimate, the previous liquid level height estimate and the corresponding time point to calculate the flow velocity estimate, providing users with an optional solution or reference input for calibrating the accuracy of the flow meter.

[0017] The present invention will be further described below with reference to specific embodiments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the process for estimating the remaining fuel level in a storage tank according to the present invention, which addresses the scenarios of fuel level sloshing and consumption.

[0019] Figure 2 This is a schematic diagram illustrating the principle of measuring the remaining fuel level in the storage tank according to the present invention.

[0020] Figure 3 This is a schematic diagram of the sloshing discrete signal measured by the liquid level sensor in an embodiment of the present invention.

[0021] Figure 4 This is a schematic diagram of continuous signal fitting through shaking data interpolation in an embodiment of the present invention.

[0022] Figure 5 This is a schematic diagram of the prior model of the mapping relationship between different filling ratios and shaking signals in an embodiment of the present invention.

[0023] Figure 6 This is a schematic diagram illustrating the correspondence between the liquid level sensor measurement point signal and the liquid level fluctuation in an embodiment of the present invention.

[0024] Figure 7 This is a schematic diagram of shaking mode 1 in an embodiment of the invention.

[0025] Figure 8 This is a schematic diagram of shaking mode 2 in an embodiment of the invention.

[0026] Figure 9 This is a schematic diagram of shaking mode 3 in an embodiment of the invention.

[0027] Figure 10 This is a schematic diagram illustrating the shaking pattern recognition principle in an embodiment of the invention. Detailed Implementation

[0028] Example

[0029] Combination Figure 1 A method for estimating the remaining fuel level in a fuel tank under scenarios involving fuel level sloshing and consumption includes the following steps:

[0030] Step 1: Construct a priori model of the mapping relationship between different filling ratios and sloshing signals. For different tank fuel filling ratio scenarios, while maintaining no fuel consumption, based on liquid level sensor measurement signals or simulation data, construct liquid level sloshing trend models under different filling ratios, analyze the patterns of signal frequency and amplitude, and finally construct a priori model of the mapping relationship between different filling ratios and sloshing signals, which can be used for subsequent analysis. Specifically:

[0031] Step 1-1: Based on the shape of the tank, under a fixed filling ratio and without fuel consumption, apply a shaking excitation to the fuel in the tank and collect the corresponding liquid level sensor measurement values.

[0032] This embodiment is based on Figure 2 The tank shape is as follows. In this embodiment, taking a filling ratio of 60% as an example, without fuel consumption, fuel is agitated in the tank, and the liquid level sensor readings are collected. The time-series discrete signal of the measured values ​​is as follows: Figure 3 As shown, the discrete data is in the form of [[t1,h(t1)],[t2,h(t2)],...[t i ,h(t i )]],Right now

[0033]

[0034] The filling ratio δ represents the percentage of the remaining fuel mass in the tank relative to the mass of fuel in the tank when it is fully loaded. n M represents the current remaining fuel mass in the tank. tThis refers to the full load mass of fuel in the storage tank;

[0035] Step 1-2: Based on the data collected in Step 1-1, a time-series-based model of tank level sloshing is fitted using interpolation.

[0036] Based on the discrete data of the liquid level sensor measurements in step 1-1, this embodiment uses Lagrange interpolation to fit a time-series-based liquid level sloshing trend model L(t), as shown in the following equation.

[0037]

[0038] Steps 1-3: Repeat steps 1-2 for different tank fuel filling ratio scenarios to construct liquid level sloshing trend models under different filling ratios. This allows for the creation of a priori models of the mapping relationship between different filling ratios and sloshing signals, which can be used for subsequent analysis. In this embodiment, the mapping relationship prior model is established at 10% intervals of filling ratio, as shown below. Figure 5 As shown.

[0039] Step 2: Recognize the liquid level sloshing pattern:

[0040] By installing multiple liquid level sensors inside the tank, the signal on the sensor is 0 when submerged in liquid and 1 when exposed. During a smooth descent without sloshing, the signal typically changes from 0 to 1. However, when fuel sloshing occurs, the submerged (or exposed) points on the sensors may be briefly exposed (or submerged) due to sloshing, resulting in a brief 1 (or 0) signal. Therefore, based on the changing trend of the liquid level sensor signal, the real-time liquid level can be analyzed to determine whether it is higher or lower than the sensor measurement point, thus identifying the current liquid level sloshing pattern. Figure 6 As shown;

[0041] In this embodiment, the sloshing mode is divided into three types. During the liquid sloshing mode discrimination process, the three sloshing modes correspond to the three signal change modes that each height sensor node will face, and also represent the sloshing patterns of the liquid surface under three consumption states:

[0042] If the sensor signal characteristics change from a stable 1 signal to a stable 0 signal (it should be noted that "stable" here and below means a continuous number of 1 or 0 signals greater than or equal to a certain threshold, which can be set according to the required sensitivity of the swaying pattern recognition), it indicates that the liquid is in a relatively stable state when passing through the height sensor node during the consumption process, without obvious swaying. This is identified as swaying pattern 1. Figure 7 As shown;

[0043] If the sensor signal is not in sway mode 1, but instead exhibits characteristics of maintaining a stable 0 signal followed by cyclical fluctuations between 0 and 1 signals, and then returning to a relatively stable 0 signal, it indicates that during the consumption process, swaying caused the current height sensor node to be exposed. After the swaying stabilized, the sensor returned to its submerged state, meaning the current liquid level is higher than the sensor measurement point. In this case, it is identified as sway mode 2. Figure 8 As shown;

[0044] If the sensor signal is not in shaking mode 1 or mode 2, but instead exhibits characteristics of maintaining a stable 1 signal, then cyclically fluctuating between 1 and 0 signals, and subsequently returning to a relatively stable 1 signal, it indicates that the shaking caused the exposed node to be submerged again, and after the shaking stabilized, the node became exposed again. This means the current liquid level is lower than the sensor measurement point, and this is identified as shaking mode 3. Figure 9 As shown.

[0045] In this embodiment, the process for determining the three liquid level sloshing modes is as follows: Figure 10 As shown:

[0046] a. When the current sensor shows a 0-1 transition, calculate the 0-1 transition time interval and the number of transitions 'a' of the liquid level sensor that caused the signal change; if the time interval is less than or equal to 1.6 seconds, no judgment is made; if the time interval is greater than 1.6 seconds, proceed to the next step.

[0047] b. Determine if the number of transitions a is greater than 1. If not, output mode 1; if yes, proceed to the next step.

[0048] c. Determine whether the proportion of the 1 signal is greater than 60% during the 0-1 signal change process. If yes, output bit mode 2; otherwise, proceed to the next step.

[0049] d. Determine whether the proportion of the 1 signal is less than 37% during the 0-1 signal change process. If yes, output bit mode 3; otherwise, proceed to the next step.

[0050] e. Determine if the number of 0 signals after the first 0-1 change is greater than 30. If yes, output mode 2; otherwise, output mode 3.

[0051] Step 3: Combining the mapping relationship model between different filling ratios and sloshing signals from Step 1, and the sloshing patterns from Step 2, determine the type of sloshing signal:

[0052] Step 3-1: When the liquid level sensor signal first jumps from 0 to 1, estimate the filling ratio based on the position of the liquid level sensor in the tank, and round it down to match the mapping relationship model in Step 1.

[0053] For example, if the calculated filling ratio is 67.2%, then the filling ratio at that moment is taken as 70%; if the calculated filling ratio is 64.3%, then the filling ratio at that moment is taken as 60%.

[0054] Step 3-2: Based on the current filling ratio and the prior model of the mapping relationship between different filling ratios and swaying signals obtained in Step 1, determine the type of swaying signal at this time.

[0055] If the estimated filling ratio is 60%, then the liquid level sloshing trend model is L6(t), which is used to obtain the corresponding sloshing signal type at this time.

[0056] Step 4: Determine the estimated value of the sway amplitude:

[0057] Step 4-1: Based on the swaying pattern identified in Step 2, obtain the time point t0 at which the liquid level sensor first changes from 0 to 1;

[0058] In this embodiment, 60% is used as an example. If the shaking mode is identified as mode 2 at this time, such as Figure 6 As shown, the time point t0 at which the liquid level sensor first changes from 0 to 1 can be obtained;

[0059] Step 4-2: Based on the sway signal type obtained in Step 3, which is L6(t) in this embodiment, the estimated value ΔA of the sway amplitude is determined:

[0060] ΔA=L6(t0)

[0061] Step 5: Determine the estimated real-time fuel balance.

[0062] Step 5-1: Based on the corresponding height h of the liquid level sensor measurement signal, and combined with the sloshing pattern type identified in Step 2, determine the positional relationship between the liquid surface and the liquid level sensor, and determine the actual liquid level height h':

[0063] If it is shaking mode 1, then:

[0064] h' = h

[0065] If it is shaking mode 2, then:

[0066] h'=h+ΔA

[0067] If it is shaking mode 3, then:

[0068] h'=h-ΔA

[0069] Step 5-2: Based on the correspondence between tank height, volume, and mass, and combined with fuel density parameters, determine the current estimated fuel balance value:

[0070] m=h'Sρ

[0071] Where S is the bottom area of ​​the storage tank and ρ is the fuel density of the storage tank.

[0072] Step 5-3: Combining the actual liquid level height measured at the previous point, the measurement time at the previous point, the actual height at the current point, and the measurement time, determine the estimated current fuel flow rate.

[0073]

[0074] Where h l 't' represents the actual liquid level height measured at the previous point. l t represents the measurement time at the previous point, and t represents the measurement time at the current point.

[0075] A fuel level estimation system for fuel tanks, designed for scenarios involving fuel level sloshing and consumption, includes the following modules:

[0076] Prior model building module for mapping relationship between different filling ratios and sloshing signals: used to build prior models for mapping relationship between different filling ratios and sloshing signals;

[0077] Liquid level sloshing pattern recognition module: used for recognizing liquid level sloshing patterns;

[0078] Sloshing signal type determination module: used to determine the sloshing signal type by combining the mapping relationship model between different filling ratios and sloshing signals, as well as the liquid level sloshing mode;

[0079] Real-time fuel balance estimation module: used to determine the estimated value of the sloshing amplitude and the estimated value of the real-time fuel balance.

[0080] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps:

[0081] Step 1: Construct a priori model of the mapping relationship between different filling ratios and swaying signals;

[0082] Step 2: Identify the liquid level sloshing pattern;

[0083] Step 3: Combine the mapping relationship model between different filling ratios and sloshing signals in Step 1, and the liquid level sloshing mode in Step 2, to determine the type of sloshing signal;

[0084] Step 4: Determine the estimated value of the sway amplitude;

[0085] Step 5: Determine the estimated real-time fuel balance.

[0086] A computer-storable medium having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0087] Step 1: Construct a priori model of the mapping relationship between different filling ratios and swaying signals;

[0088] Step 2: Identify the liquid level sloshing pattern;

[0089] Step 3: Combine the mapping relationship model between different filling ratios and sloshing signals in Step 1, and the liquid level sloshing mode in Step 2, to determine the type of sloshing signal;

[0090] Step 4: Determine the estimated value of the sway amplitude;

[0091] Step 5: Determine the estimated real-time fuel balance.

[0092] This solution can accurately estimate the remaining fuel in the tank during the shaking and consumption process, and has low requirements for computing power and hardware setup, which can further reduce the cost of the fuel remaining estimation system. It is easy to implement and apply in engineering, and has certain potential for promotion and industrialization.

[0093] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for estimating the remaining fuel level in a fuel tank under scenarios involving fuel level sloshing and consumption, characterized in that, Includes the following steps: Step 1: Construct a priori model of the mapping relationship between different filling ratios and swaying signals: Step 1-1: Based on the shape of the tank, under a fixed filling ratio and without fuel consumption, apply a shaking excitation to the fuel in the tank and collect the corresponding liquid level sensor measurement values. The filling ratio refers to the percentage of the remaining fuel mass in the tank relative to the mass of fuel in the tank when it is fully loaded. Step 1-2: Based on the data collected in Step 1-1, a time-series-based model of tank level sloshing is fitted using interpolation. Steps 1-3: Repeat steps 1-2 for different tank fuel filling ratio scenarios to construct liquid level sloshing trend models under different filling ratios, thereby constructing a priori model of the mapping relationship between different filling ratios and sloshing signals. Step 2: Identify the liquid level sloshing pattern; Step 3: Combine the mapping relationship model between different filling ratios and sloshing signals in Step 1, and the liquid level sloshing mode in Step 2, to determine the type of sloshing signal; Step 4: Determine the estimated value of the sway amplitude; Step 5: Determine the estimated real-time fuel balance.

2. The method for estimating the remaining fuel level in a storage tank for scenarios involving fuel level sloshing and consumption, as described in claim 1, is characterized in that... In step 2, during the liquid level sloshing pattern identification, multiple liquid level sensors are installed in the tank. Based on the changing trend of the liquid level height sensor point measurement signals, the real-time liquid level is analyzed to determine whether it is higher or lower than the sensor measurement point, in order to identify the current liquid level sloshing pattern. Specifically: If the sensor signal characteristics change from a stable 1 signal to a stable 0 signal, it indicates that the liquid is in a relatively stable state when passing through the height sensor node during the liquid consumption process, without obvious shaking. At this time, it is identified as shaking mode 1. If the sensor signal is not in shaking mode 1, but the sensor signal is characterized by maintaining a stable 0 signal, generating a fluctuating signal between 0 and 1 signals, and then returning to a relatively stable 0 signal, it indicates that the sensor node at the current height is exposed due to shaking during the consumption process. After the shaking stabilizes, it returns to the submerged state, that is, the current liquid level is higher than the sensor measurement point. At this time, it is identified as shaking mode 2. If the sensor signal is not in shaking mode 1 or mode 2, but the sensor signal characteristics are that after maintaining a stable 1 signal, a cyclical fluctuation between 1 and 0 signals is generated, and then it is in a relatively stable 1 signal, it indicates that the shaking caused the exposed node to be submerged again, and after the shaking stabilized, the node was exposed again, that is, the current liquid level is lower than the sensor measurement point. At this time, it is identified as shaking mode 3.

3. The method for estimating tank fuel balance in scenarios of fuel level sloshing and consumption according to claim 2, characterized in that, Determining the type of shaking signal in step 3 specifically involves: Step 3-1: When the liquid level sensor signal first jumps from 0 to 1, estimate the filling ratio based on the position of the liquid level sensor in the tank. Step 3-2: Based on the current filling ratio and the prior model of the mapping relationship between different filling ratios and swaying signals obtained in Step 1, determine the type of swaying signal at this time.

4. The method for estimating the remaining fuel level in a storage tank for scenarios involving fuel level sloshing and consumption, as described in claim 2, is characterized in that... The estimated value of the sway amplitude in step 4 is determined as follows: Step 4-1: Based on the swaying pattern identified in Step 2, obtain the time point t0 at which the liquid level sensor first changes from 0 to 1; Step 4-2: Based on the type of sway signal obtained in Step 3, determine the estimated value of the sway amplitude. : ； Here, i = 1, 2, 3, ..., n, which correspond to the n different swaying signal types in the prior model of the mapping relationship between different filling ratios and swaying signals constructed in step 1. A model representing the liquid level sloshing trend under different filling ratios.

5. The method for estimating the remaining fuel level in a storage tank for scenarios involving fuel level sloshing and consumption, as described in claim 2, is characterized in that... The determination of the real-time fuel balance estimate in step 5 is specifically as follows: Step 5-1: Based on the corresponding height h of the liquid level sensor measurement signal, and combined with the sloshing pattern type identified in Step 2, determine the positional relationship between the liquid surface and the liquid level sensor, and determine the actual liquid level height. : If it is shaking mode 1, then: ； If it is shaking mode 2, then: ； If it is shaking mode 3, then: ； Step 5-2: Based on the correspondence between tank height, volume, and mass, and combined with fuel density parameters, determine the current estimated fuel balance value: ； Where S is the bottom area of ​​the storage tank, and ρ is the fuel density of the storage tank; Step 5-3: Combining the actual liquid level height measured at the previous point, the measurement time at the previous point, the actual height at the current point, and the measurement time, determine the estimated current fuel flow rate. ； in This refers to the actual liquid level height measured at the previous point. For measuring the time at the previous point, The measurement time is for the current location.

6. A tank fuel balance estimation system for scenarios involving fuel level sloshing and consumption, characterized in that, Includes the following modules: Prior model building module for mapping relationship between different filling ratios and sloshing signals: Used to build a prior model for mapping relationship between different filling ratios and sloshing signals, including: Based on the shape of the tank, under a fixed filling ratio and without fuel consumption, a shaking excitation is applied to the fuel in the tank, and the corresponding liquid level sensor measurement value is collected. The filling ratio refers to the percentage of the remaining fuel mass in the tank relative to the mass of fuel in the tank when it is fully loaded. Based on the collected data, a time-series-based model of tank level sloshing trend was fitted using interpolation. The above fitting process was repeated for different tank fuel filling ratio scenarios to construct liquid level sloshing trend models under different filling ratios, thereby constructing a priori model of the mapping relationship between different filling ratios and sloshing signals. Liquid level sloshing pattern recognition module: used for recognizing liquid level sloshing patterns; Sloshing signal type determination module: used to determine the sloshing signal type by combining the mapping relationship model between different filling ratios and sloshing signals, as well as the liquid level sloshing mode; Real-time fuel balance estimation module: used to determine the estimated value of the sloshing amplitude and the estimated value of the real-time fuel balance.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-5.

8. A computer-storable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-5.

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