Automatic cut-off control method for automobile refueling and related device

Abstract

The invention discloses an automatic cut-off control method for automobile refueling and a related device, and relates to the technical field of data processing, and the method comprises the following steps: detecting real-time oil level data of an automobile oil tank based on an oil level sensor, and transmitting the real-time oil level data to a controller; the oil level difference between the real-time oil level data and a preset oil level threshold value is calculated, and whether the oil level difference is smaller than or equal to a preset oil level difference threshold value or not is judged; if yes, a target fuzzy controller is constructed, and oil gun adjusting parameters are obtained through the oil level difference; calculating a cut-off time point based on the oil gun adjustment parameters; transmitting the oil gun adjusting parameters and the cut-off time point to an oil gun control device to control the oil gun to carry out oil filling; when the oil gun is controlled to conduct oil filling, the oil gun control device records the time point, and when the recorded time point reaches the cut-off time point, the oil gun control device controls the oil gun to cut off oil filling. The precision of refueling cut-off is improved, and potential safety hazards and resource waste caused by overflow of the oil tank can be prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an automatic cut-off control method for automobile refueling and a related device. Background Art

[0002] In the existing automobile refueling process, the automobile refueling status is usually judged by relevant personnel, but this method is easily affected by subjective factors, resulting in inaccurate judgment of the automobile refueling cut-off situation, leading to the overflow of the fuel tank or insufficient refueling. In this regard, some companies have studied the automatic cut-off control system for automobile refueling, but the existing control system usually cuts off the refueling process of the refueling equipment after detecting that the oil level in the automobile tank has reached the preset oil level, but this will still lead to excessive refueling and fail to effectively improve the safety and automation level of the refueling process. At the same time, in the current refueling cut-off control, the consideration of the adjustment parameters of the refueling gun is usually generated according to a fixed strategy, and the corresponding adjustment parameters are not obtained according to real-time data. At the same time, the calculation and control of the cut-off time point are not considered, resulting in the failure to achieve precise control of the automobile refueling cut-off, so that the automatic cut-off of automobile refueling fails to achieve the expected effect. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides an automatic cut-off control method and related devices for automobile refueling, which improves the accuracy of refueling cut-off and can prevent safety hazards and waste of resources caused by fuel tank overflow.

[0004] In order to solve the above technical problems, the present invention provides an automatic cut-off control method for automobile refueling, which is applied to an oil level sensor, a controller and a refueling gun control device, wherein the controller is connected to the oil level sensor and the refueling gun control device respectively, and the method comprises:

[0005] During the refueling process of the automobile fuel tank, the real-time fuel level data of the automobile fuel tank is detected based on the fuel level sensor, and the real-time fuel level data is transmitted to the controller;

[0006] The controller calculates the oil level difference between the real-time oil level data and a preset oil level threshold, and determines whether the oil level difference is less than or equal to the preset oil level difference threshold;

[0007] When it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, a target fuzzy controller is constructed, and based on the target fuzzy controller, the oil level difference is used to obtain a fuel gun adjustment parameter;

[0008] Calculating a cut-off time point based on the fuel gun adjustment parameters;

[0009] Transmitting the refueling gun adjustment parameters and the cut-off time point to a refueling gun control device, wherein the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters;

[0010] When controlling the refueling gun to refuel based on the refueling gun adjustment parameter, the refueling gun control device records the time point, and when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

[0011] Optionally, when controlling the refueling gun to refuel based on the refueling gun adjustment parameter, the method includes:

[0012] The fueling gun control device collects refueling parameters when the fueling gun is refueling based on the fueling gun adjustment parameters, compares the refueling parameters with the fueling gun adjustment parameters, and determines whether it is necessary to control the fueling gun to cut off refueling based on the comparison result.

[0013] Optionally, constructing the target fuzzy controller includes:

[0014] Optimizing a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient based on preset system requirements to obtain an optimized proportional coefficient, an optimized integral coefficient, and an optimized differential coefficient;

[0015] constructing an initial fuzzy controller based on the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient;

[0016] Performing parameter tuning processing on the initial fuzzy controller to obtain an initial fuzzy controller after the parameter tuning processing;

[0017] The initial fuzzy controller after parameter tuning is optimized based on genetic algorithm to obtain the optimized initial fuzzy controller;

[0018] Based on the sample data, a conjugate gradient method is used to train a number of deep neural networks to obtain a number of trained deep neural networks, and a neural network matrix is ​​constructed based on the number of trained deep neural networks;

[0019] The optimized initial fuzzy controller and the neural network matrix are fused to obtain a target fuzzy controller.

[0020] Optionally, performing parameter tuning processing on the initial fuzzy controller to obtain the initial fuzzy controller after parameter tuning processing includes:

[0021] Acquire an object model of a fuel tank of a vehicle, and generate an equivalent model based on the object model;

[0022] Decomposing and calculating the equivalent model to obtain a first-order derivative and a second-order derivative, and generating an inertial transfer function based on the first-order derivative and the second-order derivative;

[0023] Calculating the basic domain and fuzzy domain of the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient in the initial fuzzy controller to obtain a quantization factor;

[0024] Constructing a state space model of the process control system, optimizing the quantization factor based on the state space model to obtain an optimized quantization factor;

[0025] The initial fuzzy controller is subjected to parameter tuning processing based on the optimized quantization factor and the inertia transfer function to obtain the initial fuzzy controller after the parameter tuning processing.

[0026] Optionally, the step of obtaining a fuel gun adjustment parameter based on the target fuzzy controller using the oil level difference includes:

[0027] The oil level difference is input into the target fuzzy controller for calculation to obtain a calculation result;

[0028] Perform coefficient setting processing based on the operation results to obtain relevant control coefficients;

[0029] The control parameters of the fueling gun are adjusted based on the relevant control coefficients to obtain the fueling gun adjustment parameters.

[0030] Optionally, the calculating the cut-off time point based on the fuel gun adjustment parameter includes:

[0031] Acquire historical refueling data, divide the historical refueling data into refueling routes, and obtain a plurality of refueling routes;

[0032] Feature extraction is performed based on several refueling paths to obtain refueling sample data;

[0033] Constructing a refueling process simulation model, and calculating the correlation time of the refueling operation process transition based on the refueling process simulation model;

[0034] Building a cut-off time calculation model based on the refueling sample data and the associated time;

[0035] The remaining refueling amount is calculated, and based on the remaining refueling amount and the refueling gun adjustment parameter, the initial cut-off time point is calculated using the cut-off time calculation model, and the initial cut-off time point is calculated with the refueling gun delay time to obtain the cut-off time point.

[0036] Optionally, comparing the refueling parameter with the refueling gun adjustment parameter, and judging whether it is necessary to control the refueling gun to cut off refueling based on the comparison result, includes:

[0037] The deviation value between the refueling parameter and the refueling gun adjustment parameter is calculated, and the deviation value is compared with a preset allowable deviation threshold value. If the deviation value exceeds the preset allowable deviation threshold value, the refueling gun is controlled to cut off refueling.

[0038] In addition, the present invention also provides an automatic cut-off control device for automobile refueling, which is applied to an oil level sensor, a controller and a refueling gun control device, wherein the controller is connected to the oil level sensor and the refueling gun control device respectively, and the device comprises:

[0039] Data transmission module: used for detecting the real-time oil level data of the automobile oil tank based on the oil level sensor during the refueling process of the automobile oil tank, and transmitting the real-time oil level data to the controller;

[0040] Oil level difference judgment module: used for the controller to calculate the oil level difference between the real-time oil level data and the preset oil level threshold, and judge whether the oil level difference is less than or equal to the preset oil level difference threshold;

[0041] A fuel gun adjustment parameter acquisition module: used to construct a target fuzzy controller when it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, and to acquire a fuel gun adjustment parameter based on the target fuzzy controller using the oil level difference;

[0042] A cut-off time point calculation module: used to calculate the cut-off time point based on the fuel gun adjustment parameters;

[0043] A refueling adjustment module: used for transmitting the refueling gun adjustment parameters and the cut-off time point to the refueling gun control device, and the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters;

[0044] Refueling cut-off module: used to control the refueling gun to refuel based on the refueling gun adjustment parameters, the refueling gun control device records the time point, when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

[0045] In addition, the present invention also provides an automatic cut-off control system for automobile refueling, the system includes an oil level sensor, a controller and a refueling gun control device, the controller is connected to the oil level sensor and the refueling gun control device, respectively, and the system is configured to execute the above-mentioned automatic cut-off control method for automobile refueling.

[0046] In addition, the present invention also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on an electronic device, the electronic device executes the above-mentioned automatic cut-off control method for automobile refueling.

[0047] In an embodiment of the present invention, the optimized initial fuzzy controller obtained by optimizing the initial fuzzy controller after parameter setting processing and the neural network matrix are fused to make the obtained target fuzzy controller more reliable. Based on the target fuzzy controller, the oil level difference is used to obtain the adjustment parameters of the refueling gun. After judging that the oil level difference is less than the preset oil level threshold, the parameters of the refueling gun are adjusted, which can effectively avoid the occurrence of over-refueling. At the same time, the refueling gun adjustment parameters are generated according to the target fuzzy controller, which can make the obtained refueling gun adjustment parameters more accurate. And the cut-off time point is calculated according to the refueling gun adjustment parameters. When the cut-off time point is reached, the refueling gun is controlled to cut off refueling, which not only improves the accuracy of refueling cut-off, but also improves the refueling efficiency, reduces human operation errors, and also prevents safety hazards and waste of resources caused by oil tank overflow. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 It is a flow chart of an automatic cut-off control method for automobile refueling in an embodiment of the present invention;

[0050] Figure 2 is a flow chart of an automatic cut-off control method for automobile refueling in another embodiment of the present invention;

[0051] Figure 3 It is a schematic diagram of the structure of the automatic cut-off control system for automobile refueling in an embodiment of the present invention;

[0052] Figure 4 It is a schematic diagram of the structure of an automatic cut-off control device for automobile refueling in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] Embodiment 1

[0055] See also Figure 1 , Figure 1: is a flow chart of an automatic cut-off control method for automobile refueling in an embodiment of the present invention, the method is applied to an oil level sensor, a controller and a refueling gun control device, the controller is connected to the oil level sensor and the refueling gun control device respectively; the method comprises:

[0056] S11: During the refueling process of the vehicle fuel tank, the real-time fuel level data of the vehicle fuel tank is detected based on the fuel level sensor, and the real-time fuel level data is transmitted to the controller;

[0057] In the specific implementation process of the present invention, the controller receives a refueling instruction and sends the refueling instruction to the refueling gun control device, and the refueling gun control device turns on the refueling gun to refuel the vehicle tank. During the refueling process of the vehicle tank, the oil level sensor detects the real-time oil level data of the vehicle tank while the refueling gun is refueling, and transmits the real-time oil level data to the controller.

[0058] S12: the controller calculates the oil level difference between the real-time oil level data and the preset oil level threshold, and determines whether the oil level difference is less than or equal to the preset oil level difference threshold;

[0059] During the specific implementation of the present invention, the controller receives real-time oil level data, calculates the oil level difference between the real-time oil level data and a preset oil level threshold, and determines whether the oil level difference is less than or equal to the preset oil level difference threshold. If the oil level difference is greater than the preset oil level difference threshold, it indicates that the vehicle's fuel tank has not yet reached the critical value of being full of oil. The real-time oil level data of the vehicle's fuel tank continues to be detected. When it is determined that the oil level difference is less than or equal to the preset oil level difference threshold, it indicates that the vehicle's fuel tank is about to reach the critical value of being full of oil. It is necessary to adjust the refueling parameters of the refueling gun and reduce the refueling rate of the refueling gun to avoid overflowing the fuel tank due to excessive refueling speed.

[0060] S13: when it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, constructing a target fuzzy controller, and obtaining a refueling gun adjustment parameter based on the target fuzzy controller and using the oil level difference;

[0061] In the specific implementation process of the present invention, the construction of the target fuzzy controller includes: optimizing the preset proportional coefficient, the preset integral coefficient and the preset differential coefficient based on the preset system requirements to obtain the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient; constructing an initial fuzzy controller based on the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient; performing parameter tuning processing on the initial fuzzy controller to obtain the initial fuzzy controller after the parameter tuning processing; optimizing the initial fuzzy controller after the parameter tuning processing based on the genetic algorithm to obtain the optimized initial fuzzy controller; training several deep neural networks based on sample data using the conjugate gradient method to obtain several trained deep neural networks, and constructing a neural network matrix based on the several trained deep neural networks; fusing the optimized initial fuzzy controller and the neural network matrix to obtain the target fuzzy controller.

[0062] Furthermore, the parameter tuning process of the initial fuzzy controller to obtain the initial fuzzy controller after the parameter tuning process includes: acquiring an object model of a car fuel tank, and generating an equivalent model based on the object model; decomposing and calculating the equivalent model to obtain first-order derivatives and second-order derivatives, and generating an inertia transfer function based on the first-order derivatives and second-order derivatives; calculating the basic domain and fuzzy domain of the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient in the initial fuzzy controller to obtain a quantization factor; constructing a state space model of a process control system, optimizing the quantization factor based on the state space model to obtain an optimized quantization factor; and parameter tuning the initial fuzzy controller based on the optimized quantization factor and the inertia transfer function to obtain the initial fuzzy controller after the parameter tuning process.

[0063] Furthermore, the method of obtaining the adjustment parameters of the refueling gun based on the target fuzzy controller using the oil level difference includes: inputting the oil level difference into the target fuzzy controller for calculation to obtain a calculation result; performing coefficient setting processing based on the calculation result to obtain a related control coefficient; and adjusting the control parameters of the refueling gun based on the related control coefficient to obtain the adjustment parameters of the refueling gun.

[0064] Specifically, when it is determined that the oil level difference is less than or equal to the preset oil level difference threshold, the preset proportional coefficient, the preset integral coefficient and the preset differential coefficient are optimized based on the preset system requirements, and the preset system requirements include the parameter optimization target of the fuel gun and the processing efficiency of the controller, etc., to obtain the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient. The initial fuzzy controller is constructed based on the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient. The object model of the automobile fuel tank is obtained. The object model is an abstraction of the automobile fuel tank entity. It is used as a controlled object. The controlled object and the corresponding function are abstracted at a preset level to form an object model, and an equivalent model is generated based on the object model. The low-order equivalent system parameters of the object model are obtained based on the frequency domain analysis method. The model is fitted through the low-order equivalent system parameters to obtain the equivalent model. Decompose and calculate the equivalent model, divide the equivalent model into several units according to the preset level, each unit contains a corresponding basis function, calculate the solution vector according to the basis function, calculate the order derivative according to the solution vector, that is, obtain the first order derivative and the second order derivative, and generate the inertia transfer function based on the first order derivative and the second order derivative, calculate the target complex variable according to the first order derivative and the second order derivative, calculate the external disturbance parameter according to the preset filter function, and generate the inertia transfer function according to the target complex variable and the external disturbance parameter. Calculate the basic domain and fuzzy domain of the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient in the initial fuzzy controller to obtain the quantization factor. Construct a state space model of the process control system, obtain the process control system, construct the process control system by combining the process output and input at several past moments with the simulation model, obtain the coefficient matrix and output error of the process control system, construct the state space model using the state vector according to the coefficient matrix and the output error, optimize the quantization factor based on the state space model, determine the optimal interval of the quantization factor according to the state space model using the prediction function, optimize the quantization factor according to the optimal interval, and obtain the optimized quantization factor. Perform parameter tuning processing on the initial fuzzy controller based on the optimized quantization factor and the inertia transfer function, that is, adjust the control unit parameters in the initial fuzzy controller by optimizing the quantization factor and the inertia transfer function, and obtain the initial fuzzy controller after parameter tuning processing. The initial fuzzy controller after parameter tuning is optimized based on a genetic algorithm, that is, the membership function and the fuzzy control rules in the initial fuzzy controller after parameter tuning are optimized by a genetic algorithm, the membership function and the fuzzy control rules are encoded, the population is determined according to the encoded membership function and the fuzzy control rules, the time integral difference function is used as the fitness function, the fitness of individuals in the population is calculated and judged according to the fitness function, the individuals are genetically operated by selection, crossover and mutation until a preset number of iterations is reached, and the optimized initial fuzzy controller is obtained.Based on the sample data, several deep neural networks are trained using the conjugate gradient method to obtain several trained deep neural networks, and a neural network matrix is ​​constructed based on the several trained deep neural networks. The optimized initial fuzzy controller and the neural network matrix are fused to obtain a target fuzzy controller, so that the obtained target fuzzy controller is more reliable. The oil level difference is input into the target fuzzy controller for calculation to obtain a calculation result; based on the calculation result, the coefficient is adjusted, that is, the nonlinear problem of the control coefficient is solved to obtain the relevant control coefficient; based on the relevant control coefficient, the control parameters of the refueling gun are adjusted, that is, the refueling rate of the refueling gun is adjusted according to the relevant control coefficient, the refueling flow rate is reduced, and excessive refueling is avoided to obtain the adjustment parameters of the refueling gun.

[0065] S14: Calculating a cut-off time point based on the fuel gun adjustment parameters;

[0066] In the specific implementation process of the present invention, the calculation of the cut-off time point based on the fuel gun adjustment parameters includes: obtaining historical fueling data, dividing the historical fueling data into fueling paths, and obtaining a plurality of fueling paths; performing feature extraction based on the plurality of fueling paths to obtain fueling sample data; constructing a fueling process simulation model, and calculating the associated time of the fueling operation process change based on the fueling process simulation model; constructing a cut-off time calculation model based on the fueling sample data and the associated time; calculating the remaining amount of fuel that can be refueled, and calculating the initial cut-off time point based on the remaining amount of fuel that can be refueled and the fuel gun adjustment parameters using the cut-off time calculation model, and calculating the initial cut-off time point with the fuel gun delay time to obtain the cut-off time point.

[0067] Specifically, historical refueling data is obtained, and the historical refueling data includes the cut-off time point and full-fuel time data at each refueling rate, etc. The historical refueling data is divided into refueling paths, that is, the historical refueling data is divided according to different refueling rates to obtain several refueling paths. Feature extraction is performed based on several refueling paths, and the historical refueling data in the several refueling paths are processed by multidimensional principal component analysis algorithm to obtain the historical refueling data in the refueling paths after dimensionality reduction processing. The historical refueling data in the refueling paths after dimensionality reduction processing are projected into Zhang subspace, and the data in Zhang subspace are processed by supervised multilinear subspace algorithm so that the projected data has the largest inter-class discreteness in Zhang subspace and the smallest intra-class discreteness. The data in Zhang subspace after processing is feature integrated by the nearest neighbor classifier to obtain refueling sample data. A refueling process simulation model is constructed, and the correlation time of the refueling operation process transition is calculated based on the refueling process simulation model, and the time distribution of each refueling operation process is calculated according to the refueling process simulation model. A corresponding random number is generated according to the time distribution, and the random number is used as the correlation time of the refueling operation process transition. Based on the refueling sample data and the associated time, a cut-off time calculation model is constructed, and index mapping and vectorization processing are preprocessed according to the refueling sample data and the associated time to obtain the preprocessed refueling sample data and the associated time data. The deep neural network model is trained by the preprocessed refueling sample data and the associated time data, and the trained model is finally the cut-off time calculation model. The remaining refueling amount is calculated according to the real-time oil level data and the automobile tank capacity. The initial cut-off time point is calculated based on the remaining refueling amount and the refueling gun adjustment parameters using the cut-off time calculation model, and the initial cut-off time point is calculated with the refueling gun delay time. Considering that the refueling gun has a corresponding reaction time, that is, a delay time, if the refueling gun is cut off, there may be a reaction time of 0.5 seconds, and the initial cut-off time point is 94 seconds, then the cut-off time point is set to 93.5 seconds, and the delay time is also added to the calculation of the cut-off time point to obtain the cut-off time point.

[0068] S15: transmitting the fuel gun adjustment parameter and the cut-off time point to a fuel gun control device, and the fuel gun control device controls the fuel gun to refuel based on the fuel gun adjustment parameter;

[0069] In the specific implementation process of the present invention, when controlling the refueling gun to refuel based on the refueling gun adjustment parameters, it includes: the refueling gun control device collects the refueling parameters of the refueling gun when refueling based on the refueling gun adjustment parameters, and compares the refueling parameters with the refueling gun adjustment parameters, and determines whether it is necessary to control the refueling gun to cut off refueling based on the comparison result.

[0070] Furthermore, the refueling parameters are compared with the refueling gun adjustment parameters, and based on the comparison result, it is determined whether it is necessary to control the refueling gun to cut off refueling, including: calculating the deviation value between the refueling parameters and the refueling gun adjustment parameters, comparing the deviation value with a preset allowable deviation threshold, and if the deviation value exceeds the preset allowable deviation threshold, controlling the refueling gun to cut off refueling.

[0071] Specifically, the refueling gun adjustment parameters and the cut-off time point are transmitted to the refueling gun control device, and the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters. When the refueling gun refuels based on the refueling gun adjustment parameters, the refueling parameters of the refueling gun when refueling based on the refueling gun adjustment parameters, such as the refueling rate, are collected, and the deviation value between the refueling parameters and the refueling adjustment parameters is calculated, and the deviation value is compared with a preset allowable deviation threshold value. If the deviation value exceeds the preset allowable deviation threshold value, it means that the refueling gun is in an abnormal state at this time, and the refueling gun is controlled to cut off refueling.

[0072] S16: When controlling the refueling gun to refuel based on the refueling gun adjustment parameters, the refueling gun control device records the time point, and when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

[0073] During the specific implementation of the present invention, when controlling the refueling gun to refuel based on the refueling gun adjustment parameters, a timer is set in the refueling gun control device, and the refueling gun control device records the time point. When the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling. This process is instantaneous and can accurately control the cut-off process to prevent safety hazards and waste of resources caused by oil tank overflow.

[0074] In an embodiment of the present invention, the optimized initial fuzzy controller obtained by optimizing the initial fuzzy controller after parameter setting processing and the neural network matrix are fused to make the obtained target fuzzy controller more reliable. Based on the target fuzzy controller, the oil level difference is used to obtain the adjustment parameters of the refueling gun. After judging that the oil level difference is less than the preset oil level threshold, the parameters of the refueling gun are adjusted, which can effectively avoid the occurrence of over-refueling. At the same time, the refueling gun adjustment parameters are generated according to the target fuzzy controller, which can make the obtained refueling gun adjustment parameters more accurate. And the cut-off time point is calculated according to the refueling gun adjustment parameters. When the cut-off time point is reached, the refueling gun is controlled to cut off refueling, which not only improves the accuracy of refueling cut-off, but also improves the refueling efficiency, reduces human operation errors, and also prevents safety hazards and waste of resources caused by oil tank overflow.

[0075] Embodiment 2

[0076] See also Figure 2 , Figure 2: is a flow chart of an automatic cut-off control method for automobile refueling in another embodiment of the present invention, the method is applied to an oil level sensor, a controller and a refueling gun control device, the controller is connected to the oil level sensor and the refueling gun control device respectively; the method comprises:

[0077] S201: During the refueling process of the vehicle fuel tank, detecting real-time fuel level data of the vehicle fuel tank based on the fuel level sensor, and transmitting the real-time fuel level data to the controller;

[0078] In the specific implementation process of the present invention, the controller receives a refueling instruction and sends the refueling instruction to the refueling gun control device, and the refueling gun control device turns on the refueling gun to refuel the vehicle tank. During the refueling process of the vehicle tank, the oil level sensor detects the real-time oil level data of the vehicle tank while the refueling gun is refueling, and transmits the real-time oil level data to the controller.

[0079] S202: The controller calculates the oil level difference between the real-time oil level data and a preset oil level threshold;

[0080] In a specific implementation process of the present invention, the controller receives real-time oil level data and calculates the oil level difference between the real-time oil level data and a preset oil level threshold.

[0081] S203: Determine whether the oil level difference is less than or equal to a preset oil level difference threshold;

[0082] In the specific implementation process of the present invention, if it is determined that the oil level difference is less than or equal to the preset oil level difference threshold, step S204 is entered; if it is determined that the oil level difference is greater than the preset oil level difference threshold, step S201 is entered to continue detecting the real-time oil level data of the automobile tank.

[0083] S204: when it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, constructing a target fuzzy controller, and obtaining a fuel gun adjustment parameter based on the target fuzzy controller and using the oil level difference;

[0084] In the specific implementation process of the present invention, when it is determined that the oil level difference is less than or equal to the preset oil level difference threshold, the preset proportional coefficient, the preset integral coefficient and the preset differential coefficient are optimized based on the preset system requirements, and the preset system requirements include the parameter optimization target of the fuel gun and the processing efficiency of the controller, etc., to obtain the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient. The initial fuzzy controller is constructed based on the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient. The object model of the automobile fuel tank is obtained. The object model is an abstraction of the automobile fuel tank entity. It is used as a controlled object. The controlled object and the corresponding function are abstracted at a preset level to form an object model, and an equivalent model is generated based on the object model. The low-order equivalent system parameters of the object model are obtained based on the frequency domain analysis method. The model is fitted through the low-order equivalent system parameters to obtain the equivalent model. Decompose and calculate the equivalent model, divide the equivalent model into several units according to the preset level, each unit contains a corresponding basis function, calculate the solution vector according to the basis function, calculate the order derivative according to the solution vector, that is, obtain the first order derivative and the second order derivative, and generate the inertia transfer function based on the first order derivative and the second order derivative, calculate the target complex variable according to the first order derivative and the second order derivative, calculate the external disturbance parameter according to the preset filter function, and generate the inertia transfer function according to the target complex variable and the external disturbance parameter. Calculate the basic domain and fuzzy domain of the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient in the initial fuzzy controller to obtain the quantization factor. Construct a state space model of the process control system, obtain the process control system, construct the process control system by combining the process output and input at several past moments with the simulation model, obtain the coefficient matrix and output error of the process control system, construct the state space model using the state vector according to the coefficient matrix and the output error, optimize the quantization factor based on the state space model, determine the optimal interval of the quantization factor according to the state space model using the prediction function, optimize the quantization factor according to the optimal interval, and obtain the optimized quantization factor. Perform parameter tuning processing on the initial fuzzy controller based on the optimized quantization factor and the inertia transfer function, that is, adjust the control unit parameters in the initial fuzzy controller by optimizing the quantization factor and the inertia transfer function, and obtain the initial fuzzy controller after parameter tuning processing. The initial fuzzy controller after parameter tuning is optimized based on a genetic algorithm, that is, the membership function and the fuzzy control rules in the initial fuzzy controller after parameter tuning are optimized by a genetic algorithm, the membership function and the fuzzy control rules are encoded, the population is determined according to the encoded membership function and the fuzzy control rules, the time integral difference function is used as the fitness function, the fitness of individuals in the population is calculated and judged according to the fitness function, the individuals are genetically operated by selection, crossover and mutation until a preset number of iterations is reached, and the optimized initial fuzzy controller is obtained.Based on the sample data, several deep neural networks are trained using the conjugate gradient method to obtain several trained deep neural networks, and a neural network matrix is ​​constructed based on the several trained deep neural networks. The optimized initial fuzzy controller and the neural network matrix are fused to obtain a target fuzzy controller, so that the obtained target fuzzy controller is more reliable. The oil level difference is input into the target fuzzy controller for calculation to obtain a calculation result; based on the calculation result, the coefficient is adjusted, that is, the nonlinear problem of the control coefficient is solved to obtain the relevant control coefficient; based on the relevant control coefficient, the control parameters of the refueling gun are adjusted, that is, the refueling rate of the refueling gun is adjusted according to the relevant control coefficient, the refueling flow rate is reduced, and excessive refueling is avoided to obtain the adjustment parameters of the refueling gun.

[0085] S205: Acquire historical refueling data, divide the historical refueling data into refueling routes, and obtain a plurality of refueling routes;

[0086] In the specific implementation process of the present invention, historical refueling data is obtained, and the historical refueling data includes the cut-off time point and full-fuel time data at each refueling rate, etc. The historical refueling data is divided into refueling paths, that is, the historical refueling data is divided according to different refueling rates to obtain several refueling paths.

[0087] S206: extracting features based on a number of refueling routes to obtain refueling sample data;

[0088] In the specific implementation process of the present invention, feature extraction is performed based on several refueling routes, and the historical refueling data in the several refueling routes are subjected to dimensionality reduction processing using a multidimensional principal component analysis algorithm to obtain the historical refueling data in the refueling routes after dimensionality reduction processing, and the historical refueling data in the refueling routes after dimensionality reduction processing are projected into Zhang subspace, and the data in Zhang subspace are processed by a supervised multilinear subspace algorithm so that the projected data has the largest inter-class discreteness in Zhang subspace and the smallest intra-class discreteness, and the features of the processed data in Zhang subspace are integrated by a nearest neighbor classifier to obtain refueling sample data.

[0089] S207: constructing a refueling process simulation model, and calculating the correlation time of the refueling operation process transition based on the refueling process simulation model;

[0090] In the specific implementation process of the present invention, a refueling process simulation model is constructed, and the associated time of the refueling operation process changes is calculated based on the refueling process simulation model. The time distribution of each refueling operation process is calculated according to the refueling process simulation model, and a corresponding random number is generated according to the time distribution, and the random number is used as the associated time of the refueling operation process changes.

[0091] S208: constructing a cut-off time calculation model based on the refueling sample data and the associated time;

[0092] In the specific implementation process of the present invention, a cut-off time calculation model is constructed based on the refueling sample data and the associated time, and index mapping and vectorization processing are pre-processed according to the refueling sample data and the associated time to obtain the pre-processed refueling sample data and the associated time data. The deep neural network model is trained with the pre-processed refueling sample data and the associated time data, and the final trained model is the cut-off time calculation model.

[0093] S209: Calculate the remaining refueling amount, calculate the initial cut-off time point using the cut-off time calculation model based on the remaining refueling amount and the refueling gun adjustment parameter, calculate the initial cut-off time point and the refueling gun delay time to obtain the cut-off time point;

[0094] In the specific implementation process of the present invention, the remaining amount of refueling is calculated according to the real-time oil level data and the vehicle's fuel tank capacity, the initial cut-off time point is calculated based on the remaining amount of refueling and the fuel gun adjustment parameters using the cut-off time calculation model, and the initial cut-off time point is calculated with the fuel gun delay time. Considering that the fuel gun has a corresponding reaction time, that is, a delay time, if there may be a reaction time of 0.5 seconds when the fuel gun is cut off, and the initial cut-off time point is 94 seconds, the cut-off time point is set to 93.5 seconds, and the delay time is also added to the calculation of the cut-off time point to obtain the cut-off time point.

[0095] S210: transmitting the fuel gun adjustment parameter and the cut-off time point to a fuel gun control device, and the fuel gun control device controls the fuel gun to refuel based on the fuel gun adjustment parameter;

[0096] In the specific implementation process of the present invention, the adjustment parameters of the refueling gun and the cut-off time point are transmitted to the refueling gun control device, and the refueling gun control device controls the refueling gun to refuel based on the adjustment parameters of the refueling gun. When the refueling gun refuels based on the adjustment parameters of the refueling gun, the refueling parameters of the refueling gun based on the adjustment parameters of the refueling gun, such as the refueling rate, are collected, and the deviation value between the refueling parameter and the refueling adjustment parameter is calculated, and the deviation value is compared with the preset allowable deviation threshold value. If the deviation value exceeds the preset allowable deviation threshold value, it means that the refueling gun is in an abnormal state at this time, and the refueling gun is controlled to cut off refueling.

[0097] S211: When controlling the refueling gun to refuel based on the refueling gun adjustment parameters, the refueling gun control device records the time point, and when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

[0098] During the specific implementation of the present invention, when controlling the refueling gun to refuel based on the refueling gun adjustment parameters, a timer is set in the refueling gun control device, and the refueling gun control device records the time point. When the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling. This process is instantaneous and can accurately control the cut-off process to prevent safety hazards and waste of resources caused by oil tank overflow.

[0099] In an embodiment of the present invention, the optimized initial fuzzy controller obtained by optimizing the initial fuzzy controller after parameter setting processing and the neural network matrix are fused to make the obtained target fuzzy controller more reliable. Based on the target fuzzy controller, the oil level difference is used to obtain the adjustment parameters of the refueling gun. After judging that the oil level difference is less than the preset oil level threshold, the parameters of the refueling gun are adjusted, which can effectively avoid the occurrence of over-refueling. At the same time, the refueling gun adjustment parameters are generated according to the target fuzzy controller, which can make the obtained refueling gun adjustment parameters more accurate. And the cut-off time point is calculated according to the refueling gun adjustment parameters. When the cut-off time point is reached, the refueling gun is controlled to cut off refueling, which not only improves the accuracy of refueling cut-off, but also improves the refueling efficiency, reduces human operation errors, and also prevents safety hazards and waste of resources caused by oil tank overflow.

[0100] Embodiment 3

[0101] See also Figure 3 , Figure 3 3 is a schematic diagram of the structure of an automatic shut-off control system for automobile refueling in an embodiment of the present invention. The system includes an oil level sensor 31, a controller 32 and a refueling gun control device 33. The controller 32 is connected to the oil level sensor 31 and the refueling gun control device 33 respectively. The system is configured to execute the automatic shut-off control method for automobile refueling in the above embodiment.

[0102] In the specific implementation process of the present invention, the oil level sensor 31 is used to collect the oil level data of the automobile oil tank. It can adopt various types such as capacitive, magnetostrictive or ultrasonic. The specific selection depends on the oil tank structure and the measurement accuracy requirements. The measurement accuracy of the oil level sensor 31 can reach ±1% full scale, and the response time is less than 100 milliseconds. The controller 32 is used to perform data analysis based on the acquired real-time oil level data. The controller 32 adopts an embedded processor based on the advanced reduced instruction set machine architecture, with an operating frequency of 1GHz and a built-in 16-bit analog-to-digital converter for processing the analog signal from the oil level sensor 31. The controller 32 communicates with the oil level sensor 31 through the RS485 interface, and the data transmission rate is 115200bps. The control parameters can be dynamically adjusted according to the relevant data to achieve accurate refueling control. The refueling gun control device 33 is used to control the state of the refueling gun. The refueling gun control device 33 adopts an electromagnetic valve with a response time of less than 10ms, which can quickly cut off the oil flow. The controller 32 communicates with the fuel gun control device 33 via the controller area network bus, and the communication rate is 500kbps, which ensures the timely transmission of control instructions.

[0103] at the same time, Figure 3 The illustrated automatic shutoff control system for automobile refueling does not constitute a limitation on all components, and may include more or less components than illustrated, or combine certain components. Specific implementation methods can be found in the above embodiments, which will not be described in detail here.

[0104] In an embodiment of the present invention, the optimized initial fuzzy controller obtained by optimizing the initial fuzzy controller after parameter setting processing and the neural network matrix are fused to make the obtained target fuzzy controller more reliable. Based on the target fuzzy controller, the oil level difference is used to obtain the adjustment parameters of the refueling gun. After judging that the oil level difference is less than the preset oil level threshold, the parameters of the refueling gun are adjusted, which can effectively avoid the occurrence of over-refueling. At the same time, the refueling gun adjustment parameters are generated according to the target fuzzy controller, which can make the obtained refueling gun adjustment parameters more accurate. And the cut-off time point is calculated according to the refueling gun adjustment parameters. When the cut-off time point is reached, the refueling gun is controlled to cut off refueling, which not only improves the accuracy of refueling cut-off, but also improves the refueling efficiency, reduces human operation errors, and also prevents safety hazards and waste of resources caused by oil tank overflow.

[0105] Embodiment 4

[0106] See also Figure 4 , Figure 4 : is a schematic diagram of the structure of an automatic cut-off control device for automobile refueling in an embodiment of the present invention, the device is applied to an oil level sensor, a controller and a refueling gun control device, the controller is connected to the oil level sensor and the refueling gun control device respectively; the device includes:

[0107] Data transmission module 41: used for detecting the real-time oil level data of the automobile oil tank based on the oil level sensor during the process of refueling the automobile oil tank, and transmitting the real-time oil level data to the controller;

[0108] The oil level difference judgment module 42 is used for the controller to calculate the oil level difference between the real-time oil level data and the preset oil level threshold, and to judge whether the oil level difference is less than or equal to the preset oil level difference threshold;

[0109] The refueling gun adjustment parameter acquisition module 43 is used to construct a target fuzzy controller when it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, and obtain the refueling gun adjustment parameter based on the target fuzzy controller using the oil level difference;

[0110] A cut-off time point calculation module 44 is used to calculate the cut-off time point based on the fuel gun adjustment parameters;

[0111] A refueling adjustment module 45 is used to transmit the refueling gun adjustment parameters and the cut-off time point to the refueling gun control device, and the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters;

[0112] The refueling cut-off module 46 is used to control the refueling gun to refuel based on the refueling gun adjustment parameters. The refueling gun control device records the time point. When the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

[0113] In the specific implementation process of the present invention, the specific implementation methods of the device items can be referred to the above embodiments, which will not be repeated here.

[0114] In an embodiment of the present invention, the optimized initial fuzzy controller obtained by optimizing the initial fuzzy controller after parameter setting processing and the neural network matrix are fused to make the obtained target fuzzy controller more reliable. Based on the target fuzzy controller, the oil level difference is used to obtain the adjustment parameters of the refueling gun. After judging that the oil level difference is less than the preset oil level threshold, the parameters of the refueling gun are adjusted, which can effectively avoid the occurrence of over-refueling. At the same time, the refueling gun adjustment parameters are generated according to the target fuzzy controller, which can make the obtained refueling gun adjustment parameters more accurate. And the cut-off time point is calculated according to the refueling gun adjustment parameters. When the cut-off time point is reached, the refueling gun is controlled to cut off refueling, which not only improves the accuracy of refueling cut-off, but also improves the refueling efficiency, reduces human operation errors, and also prevents safety hazards and waste of resources caused by oil tank overflow.

[0115] A computer-readable storage medium is provided in an embodiment of the present invention, wherein a computer program is stored on the computer-readable storage medium, and when the program is executed by a processor, the automatic shut-off control method for automobile refueling of any one of the above embodiments is implemented. The computer-readable storage medium includes, but is not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, the storage device includes any medium that can store or transmit information in a readable form by a device (for example, a computer, a mobile phone), which can be a read-only memory, a disk or an optical disk, etc.

[0116] In addition, the above is a detailed introduction to an automatic cut-off control method for automobile refueling and related devices provided by an embodiment of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for a person skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An automatic cut-off control method for automobile refueling, characterized in that: Applied to an oil level sensor, a controller and a refueling gun control device, the controller is connected to the oil level sensor and the refueling gun control device respectively, and the method comprises: During the refueling process of the automobile fuel tank, the real-time fuel level data of the automobile fuel tank is detected based on the fuel level sensor, and the real-time fuel level data is transmitted to the controller; The controller calculates the oil level difference between the real-time oil level data and a preset oil level threshold, and determines whether the oil level difference is less than or equal to the preset oil level difference threshold; When it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, a target fuzzy controller is constructed, and based on the target fuzzy controller, the oil level difference is used to obtain a fuel gun adjustment parameter; Calculating a cut-off time point based on the fuel gun adjustment parameters; Transmitting the refueling gun adjustment parameters and the cut-off time point to a refueling gun control device, wherein the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters; When controlling the refueling gun to refuel based on the refueling gun adjustment parameter, the refueling gun control device records the time point, and when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

2. The automatic cut-off control method for automobile refueling according to claim 1, characterized in that: When controlling the refueling gun to refuel based on the refueling gun adjustment parameter, the method includes: The fueling gun control device collects refueling parameters when the fueling gun is refueling based on the fueling gun adjustment parameters, compares the refueling parameters with the fueling gun adjustment parameters, and determines whether it is necessary to control the fueling gun to cut off refueling based on the comparison result.

3. The automatic cut-off control method for automobile refueling according to claim 1, characterized in that: The target fuzzy controller is constructed, comprising: Optimizing a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient based on preset system requirements to obtain an optimized proportional coefficient, an optimized integral coefficient, and an optimized differential coefficient; constructing an initial fuzzy controller based on the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient; Performing parameter tuning processing on the initial fuzzy controller to obtain an initial fuzzy controller after the parameter tuning processing; The initial fuzzy controller after parameter tuning is optimized based on genetic algorithm to obtain the optimized initial fuzzy controller; Based on the sample data, a conjugate gradient method is used to train a number of deep neural networks to obtain a number of trained deep neural networks, and a neural network matrix is ​​constructed based on the number of trained deep neural networks; The optimized initial fuzzy controller and the neural network matrix are fused to obtain a target fuzzy controller.

4. The automatic cut-off control method for automobile refueling according to claim 3, characterized in that: The step of performing parameter setting processing on the initial fuzzy controller to obtain the initial fuzzy controller after the parameter setting processing comprises: Acquire an object model of a fuel tank of a vehicle, and generate an equivalent model based on the object model; Decomposing and calculating the equivalent model to obtain a first-order derivative and a second-order derivative, and generating an inertial transfer function based on the first-order derivative and the second-order derivative; Calculating the basic domain and fuzzy domain of the optimized proportional coefficient, the optimized integral coefficient and the optimized differential coefficient in the initial fuzzy controller to obtain a quantization factor; Constructing a state space model of the process control system, optimizing the quantization factor based on the state space model to obtain an optimized quantization factor; The initial fuzzy controller is subjected to parameter tuning processing based on the optimized quantization factor and the inertia transfer function to obtain the initial fuzzy controller after the parameter tuning processing.

5. The automatic cut-off control method for automobile refueling according to claim 1, characterized in that: The method of obtaining the adjustment parameters of the fuel gun based on the target fuzzy controller using the oil level difference includes: The oil level difference is input into the target fuzzy controller for calculation to obtain a calculation result; Perform coefficient setting processing based on the operation results to obtain relevant control coefficients; The control parameters of the fueling gun are adjusted based on the relevant control coefficients to obtain the fueling gun adjustment parameters.

6. The automatic cut-off control method for automobile refueling according to claim 1, characterized in that: The calculating the cut-off time point based on the adjustment parameter of the fueling gun includes: Acquire historical refueling data, divide the historical refueling data into refueling routes, and obtain a plurality of refueling routes; Feature extraction is performed based on several refueling paths to obtain refueling sample data; Constructing a refueling process simulation model, and calculating the correlation time of the refueling operation process transition based on the refueling process simulation model; Building a cut-off time calculation model based on the refueling sample data and the associated time; The remaining refueling amount is calculated, and based on the remaining refueling amount and the refueling gun adjustment parameter, the initial cut-off time point is calculated using the cut-off time calculation model, and the initial cut-off time point is calculated with the refueling gun delay time to obtain the cut-off time point.

7. The automatic cut-off control method for automobile refueling according to claim 2, characterized in that: The comparing the refueling parameter with the refueling gun adjustment parameter and judging whether it is necessary to control the refueling gun to cut off refueling based on the comparison result includes: The deviation value between the refueling parameter and the refueling gun adjustment parameter is calculated, and the deviation value is compared with a preset allowable deviation threshold value. If the deviation value exceeds the preset allowable deviation threshold value, the refueling gun is controlled to cut off refueling.

8. An automatic cut-off control device for automobile refueling, characterized in that: Applicable to an oil level sensor, a controller and a refueling gun control device, wherein the controller is connected to the oil level sensor and the refueling gun control device respectively, and the device comprises: Data transmission module: used for detecting the real-time oil level data of the automobile oil tank based on the oil level sensor during the refueling process of the automobile oil tank, and transmitting the real-time oil level data to the controller; Oil level difference judgment module: used for the controller to calculate the oil level difference between the real-time oil level data and the preset oil level threshold, and judge whether the oil level difference is less than or equal to the preset oil level difference threshold; A fuel gun adjustment parameter acquisition module is used to construct a target fuzzy controller when it is determined that the oil level difference is less than or equal to a preset oil level difference threshold, and to acquire a fuel gun adjustment parameter based on the target fuzzy controller using the oil level difference; A cut-off time point calculation module: used to calculate the cut-off time point based on the fuel gun adjustment parameters; A refueling adjustment module: used to transmit the refueling gun adjustment parameters and the cut-off time point to the refueling gun control device, and the refueling gun control device controls the refueling gun to refuel based on the refueling gun adjustment parameters; Refueling cut-off module: used to control the refueling gun to refuel based on the refueling gun adjustment parameters, the refueling gun control device records the time point, when the recorded time point reaches the cut-off time point, the refueling gun control device controls the refueling gun to cut off refueling.

9. An automatic cut-off control system for automobile refueling, characterized in that: The system includes an oil level sensor, a controller and a fuel gun control device, wherein the controller is connected to the oil level sensor and the fuel gun control device respectively, and the system is configured to execute the automatic cut-off control method for automobile refueling as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the automatic cut-off control method for automobile refueling according to any one of claims 1 to 7.

Images