Vehicle liquefied natural gas cylinder static evaporation rate rapid prediction system and method

Abstract

This invention belongs to the field of vehicle-mounted liquefied natural gas (LNG) cylinder testing technology, and discloses a rapid prediction system and method for the static evaporation rate of LNG cylinders. The system includes a multi-parameter acquisition module, a data interaction and transmission module, a thermal response time constant prediction unit, a cumulative evaporation mass calculation unit, and a static evaporation rate correction calculation unit. The multi-parameter acquisition module collects relevant cylinder parameters, and the calculation units work in tandem. The static evaporation rate correction calculation unit back-calculates and updates the comprehensive heat transfer coefficient, achieving closed-loop prediction. The method corresponds to each step of the system execution. This invention solves the problems of inaccurate predictions due to the lack of closed-loop self-correction and thermal hysteresis in existing technologies, achieving accurate and rapid prediction of the static evaporation rate and ensuring the safety of cylinder use.

Description

Technical Field

[0001] This invention belongs to the field of vehicle liquefied natural gas cylinder testing technology, specifically relating to a rapid prediction system and method for the static evaporation rate of vehicle liquefied natural gas cylinders. Background Technology

[0002] Liquefied natural gas (LNG) cylinders for vehicles are core energy storage components of LNG vehicles. Their static evaporation rate directly affects the cylinder's energy storage efficiency and operational safety. Accurate and rapid prediction of the static evaporation rate is crucial for ensuring the safe and stable operation of the cylinders. Current technologies for predicting the static evaporation rate of LNG cylinders for vehicles mostly employ static calculation methods, performing calculations using fixed parameters without considering the impact of the cylinder's thermal hysteresis characteristics on the prediction results. Furthermore, the lack of a parameter self-correction mechanism leads to the continuous accumulation of parameter deviations during the prediction process, resulting in insufficient accuracy. Simultaneously, existing prediction schemes do not achieve closed-loop linkage between various calculation stages, failing to adjust calculation parameters in real time based on prediction results. This makes it difficult to meet the demand for rapid and accurate prediction of the static evaporation rate in vehicle scenarios, necessitating a technical solution that can address these issues. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a rapid prediction system for the static evaporation rate of liquefied natural gas (LNG) cylinders for vehicles. The system includes: a multi-parameter acquisition module, a data interaction and transmission module, a thermal response time constant prediction unit, a cumulative evaporation mass calculation unit, and a static evaporation rate correction calculation unit. The multi-parameter acquisition module is used to acquire the effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of the LNG cylinder. The thermal response time constant prediction unit is connected to the multi-parameter acquisition module and generates the thermal response time constant based on the effective volume and comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit is connected to the thermal response time constant prediction unit and the multi-parameter acquisition module. The system generates a cumulative evaporation mass based on the thermal response time constant, ambient temperature difference, effective volume, comprehensive heat transfer coefficient, and latent heat of vaporization. A static evaporation rate correction calculation unit connects to the cumulative evaporation mass calculation unit, the thermal response time constant prediction unit, and the multi-parameter acquisition module. It generates a static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas. The static evaporation rate correction calculation unit then infers the comprehensive heat transfer coefficient from the generated static evaporation rate and transmits the inferred comprehensive heat transfer coefficient to the thermal response time constant prediction unit to update the thermal response time constant. A data interaction transmission module is connected to the static evaporation rate correction calculation unit.

[0004] Preferably, the effective volume collected by the multi-parameter acquisition module is the effective volume of the vehicle liquefied natural gas cylinder, the comprehensive heat transfer coefficient collected by the multi-parameter acquisition module is in watts per square meter in degrees Celsius, the ambient temperature difference collected by the multi-parameter acquisition module is the average temperature difference per hour, the latent heat of vaporization collected by the multi-parameter acquisition module includes the standard latent heat of vaporization, the saturated liquid density of liquefied natural gas collected by the multi-parameter acquisition module is in kilograms per cubic meter, and the multi-parameter acquisition module collects all the above parameters once per hour and transmits them to the corresponding calculation unit.

[0005] In a further preferred embodiment, the thermal response time constant prediction unit incorporates a machine learning model. The machine learning model takes the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module as input and the thermal response time constant as output. The unit of the thermal response time constant is hours. The machine learning model uses the nonlinear least squares method for fitting and optimization.

[0006] In a further preferred embodiment, the cumulative evaporation mass calculation unit has a built-in area ratio coefficient, the unit of which is square meters to the power of two-thirds of a cubic meter. The area ratio coefficient is pre-calibrated based on the effective volume of the vehicle liquefied natural gas cylinder and stored in the internal storage module of the cumulative evaporation mass calculation unit after calibration.

[0007] More preferably, the cumulative evaporation mass calculation unit calculates the cumulative evaporation mass using a preset formula, the formula being: ; The overall heat transfer coefficient is expressed as watts per square meter per degree Celsius. This is the area ratio coefficient, expressed as square three times the unit of square meters per cubic meter; Effective volume, in cubic meters; The latent heat of vaporization is expressed in kilojoules per kilogram. The average temperature difference over a period of time, expressed in degrees Celsius. The thermal response time constant is expressed in hours. , Let be the integral function of the step response, expressed in hours.

[0008] In a further preferred embodiment, the static evaporation rate correction calculation unit has a built-in adiabatic characteristic correction coefficient and a standard temperature difference. The adiabatic characteristic correction coefficient is dimensionless, and the standard temperature difference is in degrees Celsius. The adiabatic characteristic correction coefficient is pre-calibrated according to the adiabatic performance of the vehicle liquefied natural gas cylinder. The standard temperature difference is a preset fixed value and is stored in the static evaporation rate correction calculation unit. The static evaporation rate correction calculation unit calculates the static evaporation rate through a preset formula. Each parameter in the formula corresponds one-to-one with the parameter used in the calculation of the cumulative evaporation mass and has the same dimensions.

[0009] In a further preferred embodiment, the static evaporation rate correction calculation unit back-calculates the comprehensive heat transfer coefficient based on the static evaporation rate calculation result. The back-calculation process adopts the inverse operation logic corresponding to the static evaporation rate calculation formula. The comprehensive heat transfer coefficient obtained by back-calculation has the same dimensions as the comprehensive heat transfer coefficient collected by the multi-parameter acquisition module. The thermal response time constant prediction unit refits and generates the thermal response time constant based on the back-calculated comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit recalculates the cumulative evaporation mass based on the updated thermal response time constant.

[0010] In a further preferred embodiment, the data interaction and transmission module connects a local storage unit and a cloud server. The local storage unit is used to store all parameters collected by the multi-parameter acquisition module, the thermal response time constant, the cumulative evaporation mass, and the static evaporation rate. The cloud server is used to receive all the above data transmitted by the data interaction and transmission module and store them for a long time. The data interaction and transmission module adopts both wired and wireless transmission methods.

[0011] A method for rapidly predicting the static evaporation rate of liquefied natural gas (LNG) cylinders for vehicles, applicable to any of the above-mentioned rapid prediction systems for the static evaporation rate of LNG cylinders for vehicles, characterized by comprising the following steps: S1: Steps for collecting cylinder parameters: The effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas in vehicles are collected through a multi-parameter acquisition module. S2: Step to generate thermal response time constant, which generates thermal response time constant based on effective volume and comprehensive heat transfer coefficient through thermal response time constant prediction unit; S3: Step to generate cumulative evaporation mass. The cumulative evaporation mass is generated by the cumulative evaporation mass calculation unit based on the thermal response time constant, ambient temperature difference, effective volume, comprehensive heat transfer coefficient and latent heat of vaporization. S4: The static evaporation rate generation step generates the static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas through the static evaporation rate correction calculation unit. S5: Parameter closed-loop correction step, the comprehensive heat transfer coefficient is back-calculated based on the static evaporation rate by the static evaporation rate correction calculation unit, and the back-calculated comprehensive heat transfer coefficient is transmitted to the thermal response time constant prediction unit to update the thermal response time constant.

[0012] In a further preferred embodiment, the parameter closed-loop correction step further includes: the thermal response time constant prediction unit regenerates the thermal response time constant based on the updated comprehensive heat transfer coefficient, and transmits the updated thermal response time constant to the cumulative evaporation mass calculation unit; the cumulative evaporation mass calculation unit regenerates the cumulative evaporation mass based on the updated thermal response time constant, and transmits the updated cumulative evaporation mass to the static evaporation rate correction calculation unit; the static evaporation rate correction calculation unit regenerates the static evaporation rate based on the updated cumulative evaporation mass until the static evaporation rate tends to stabilize, and the data interaction transmission module transmits the stabilized static evaporation rate to the local storage unit and the cloud server.

[0013] Technical effects: The core inventive technology of this invention is the closed-loop linkage of each calculation unit and the parameter back-reasoning update function of the static evaporation rate correction calculation unit. This solves the main problems of existing technologies, such as the lack of closed-loop self-correction and thermal hysteresis leading to inaccurate predictions. It enables rapid and accurate prediction of the static evaporation rate of liquefied natural gas cylinders for vehicles, avoids the accumulation of parameter deviations, ensures the safety and energy storage efficiency of the cylinders, and adapts to the actual needs of vehicle use scenarios. Attached Figure Description

[0014] Figure 1 A block diagram showing the overall structure and connection of a rapid prediction system for the static evaporation rate of liquefied natural gas cylinders for vehicles; Figure 2 A flowchart and module linkage diagram of a rapid prediction method for static evaporation rate of liquefied natural gas cylinders for vehicles; Figure 3 A step-by-step diagram illustrating the method for rapid prediction of static evaporation rate of liquefied natural gas cylinders for vehicles; Figure 4 This is a representation of the convergence curve and iterative data from a simulation for predicting the static evaporation rate of liquefied natural gas cylinders for vehicles. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] Existing technologies suffer from technical problems such as the lack of closed-loop self-correction and thermal hysteresis leading to inaccurate prediction of static evaporation rate.

[0017] Based on this, please refer to Figures 1-4This embodiment provides a rapid prediction system for the static evaporation rate of liquefied natural gas (LNG) cylinders used in vehicles, including a multi-parameter acquisition module, a data interaction and transmission module, a thermal response time constant prediction unit, a cumulative evaporation mass calculation unit, and a static evaporation rate correction calculation unit. The multi-parameter acquisition module is used to acquire the effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of the LNG cylinder. The thermal response time constant prediction unit is connected to the multi-parameter acquisition module and generates a thermal response time constant based on the effective volume and comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit is connected to the thermal response time constant prediction unit and the multi-parameter acquisition module, and calculates the cumulative evaporation mass based on the thermal response time. The system calculates the cumulative evaporation mass based on constants, ambient temperature difference, effective volume, comprehensive heat transfer coefficient, and latent heat of vaporization. The static evaporation rate correction calculation unit connects to the cumulative evaporation mass calculation unit, the thermal response time constant prediction unit, and the multi-parameter acquisition module. It generates the static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas. The static evaporation rate correction calculation unit then inversely calculates the comprehensive heat transfer coefficient based on the generated static evaporation rate and transmits the inversely calculated comprehensive heat transfer coefficient to the thermal response time constant prediction unit to update the thermal response time constant. A data interaction and transmission module is connected to the static evaporation rate correction calculation unit.

[0018] It is worth mentioning that the multi-parameter acquisition module is an integrated sensor module, integrating a volume sensor, a heat transfer coefficient detection sensor, a temperature sensor, and a physical property parameter detection sensor. Each sensor is adapted to the corresponding detection position of the vehicle-mounted liquefied natural gas cylinder. The volume sensor is used to detect the actual effective space inside the cylinder that can store liquefied natural gas. The heat transfer coefficient detection sensor is set against the outer wall of the cylinder to detect the overall comprehensive heat transfer capacity of the cylinder. The temperature sensor simultaneously detects the temperature of the liquefied natural gas inside the cylinder and the ambient temperature and calculates the difference to obtain the ambient temperature difference. The physical property parameter detection sensor has a built-in liquefied natural gas property database, which can match the latent heat of vaporization and saturated liquid density of liquefied natural gas corresponding to the detected temperature and pressure inside the cylinder in real time. The thermal response time constant prediction unit is a dedicated computing chip module, which establishes a bidirectional data connection with the multi-parameter acquisition module through an industrial bus. It can not only receive the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module, but also receive the back-calculated comprehensive heat transfer coefficient transmitted by the subsequent static evaporation rate correction calculation unit. The chip has preset data processing logic, which can directly generate the corresponding thermal response time constant based on the input parameters. The cumulative evaporation mass calculation unit is also a dedicated computing module. It establishes one-way data receiving connections with both the multi-parameter acquisition module and the thermal response time constant prediction unit, enabling it to simultaneously acquire the basic parameters of the gas cylinder and the thermal response time constant. The module's internal computing logic combines these two types of parameters to calculate the cumulative evaporation mass, and the calculation results are transmitted in real time to the static evaporation rate correction calculation unit. The static evaporation rate correction calculation unit is the core computing module of the system. It establishes data connections with the multi-parameter acquisition module, the thermal response time constant prediction unit, and the cumulative evaporation mass calculation unit, and can receive all parameters and calculation results from each module and unit. The module integrates two sets of logic: forward operation and inverse operation. The forward operation logic generates the static evaporation rate based on various parameters, while the inverse operation logic uses the generated static evaporation rate to deduce the comprehensive heat transfer coefficient that conforms to the actual operating conditions. The deduced comprehensive heat transfer coefficient is transmitted in real time to the thermal response time constant prediction unit via the industrial bus to achieve parameter updates and iterations. The data interaction and transmission module is a dual-channel data transmission module that establishes a one-way data receiving connection with the static evaporation rate correction calculation unit. It can obtain the final static evaporation rate output by this unit, as well as various intermediate calculation results. The module has data forwarding and transmission functions, and can transmit all received data to external storage and display devices, ensuring real-time data output and retention. All modules and units are connected via industrial-grade bus interfaces, using the standard Modbus protocol to ensure data transmission stability and compatibility. All modules and units are powered by 24V DC, adaptable to industrial power supply environments. The overall system features a modular design, allowing each module and unit to be independently disassembled and replaced, facilitating on-site installation and maintenance.In this technical solution, each module and unit is an essential technical feature; removing any one would prevent the achievement of closed-loop prediction functionality. The multi-parameter acquisition module explicitly collects the core parameters of the vehicle-mounted liquefied natural gas cylinder, providing a foundation for subsequent calculations. The thermal response time constant prediction unit, cumulative evaporation mass calculation unit, and static evaporation rate correction calculation unit work in tandem, combining with the back-calculation update function of the static evaporation rate correction calculation unit to form a complete closed loop, resolving thermal hysteresis and parameter deviation issues. The data interaction and transmission module ensures data transmission. The overall solution is complete and feasible. The achieved technical effect is to enable accurate and rapid prediction of static evaporation rate, ensuring the safety of cylinder use.

[0019] In existing technologies, multi-parameter acquisition modules have unclear acquisition parameters and undefined acquisition frequencies, resulting in insufficient parameter stability.

[0020] Based on this, in this embodiment, the effective volume collected by the multi-parameter acquisition module is the effective volume of the vehicle liquefied natural gas cylinder, the comprehensive heat transfer coefficient collected by the multi-parameter acquisition module is in watts per square meter in degrees Celsius, the ambient temperature difference collected by the multi-parameter acquisition module is the average temperature difference per hour, the latent heat of vaporization collected by the multi-parameter acquisition module includes the standard latent heat of vaporization, the saturated liquid density of liquefied natural gas collected by the multi-parameter acquisition module is in kilograms per cubic meter, and the multi-parameter acquisition module collects all the above parameters once per hour and transmits them to the corresponding calculation unit.

[0021] It is worth mentioning that the effective volume of the vehicle-mounted liquefied natural gas cylinder refers to the actual volume of liquefied natural gas that can be stored after excluding the cylinder's inner support structure and insulation structure. The volume sensor of the multi-parameter acquisition module uses ultrasonic detection to accurately detect this actual effective volume, and the detection result is directly output in cubic meters. During the detection of the comprehensive heat transfer coefficient, the heat transfer coefficient detection sensor of the multi-parameter acquisition module continuously detects the temperature difference between the outer and inner walls of the cylinder and the heat transfer per unit time. The comprehensive heat transfer coefficient is calculated based on the basic formula of heat conduction, and the calculation result is strictly output in watts per square meter in degrees Celsius to ensure dimensional consistency. The hourly average temperature difference is the arithmetic mean calculated by the temperature sensor after continuously collecting the difference between the ambient temperature and the temperature inside the cylinder 60 times at a one-minute sampling interval. This average value is output in degrees Celsius, effectively avoiding parameter deviations caused by instantaneous temperature fluctuations. The latent heat of vaporization includes both the latent heat of vaporization under actual operating conditions and the standard latent heat of vaporization. The physical property parameter detection sensor of the multi-parameter acquisition module can simultaneously output both types of parameters, both in kilojoules per kilogram. The standard latent heat of vaporization is the latent heat of vaporization of liquefied natural gas under standard atmospheric pressure, which is a fixed value. The latent heat of vaporization under actual operating conditions is dynamically adjusted according to the real-time pressure inside the gas cylinder. The saturated liquid density of liquefied natural gas is obtained by the physical property parameter detection sensor based on the real-time temperature and pressure inside the gas cylinder. The detection result is output in kilograms per cubic meter to ensure dimensional matching with subsequent calculations. The multi-parameter acquisition module is set to acquire parameters once per hour. This frequency is achieved through an internal timing control chip with millisecond-level precision, ensuring accurate acquisition timing. After each acquisition, the module simultaneously transmits all acquired parameters to the corresponding computing unit via an industrial bus. The transmission uses data packets, each containing parameter name, value, dimensions, and acquisition time information for easy identification and processing by the computing unit. If data is missing or abnormal during an acquisition, the multi-parameter acquisition module immediately triggers a re-acquisition mechanism, completing supplementary acquisition and retransmission within ten minutes to ensure parameter integrity. This technical solution clearly defines the specific designations and dimensions of each parameter acquired by the multi-parameter acquisition module, avoiding parameter ambiguity. Acquiring parameters hourly ensures real-time performance, while transmitting the acquired parameters to the corresponding computing unit ensures normal operation of each unit. It is closely integrated with the system's core modules and units, providing sufficient constraints. The achieved technical effect is improved accuracy and real-time performance of parameter acquisition, ensuring the reliability of subsequent calculations.

[0022] The prediction method of the thermal response time constant prediction unit in the existing technology is unclear, which leads to a large deviation in the prediction results.

[0023] Based on this, the thermal response time constant prediction unit in this embodiment has a built-in machine learning model. The machine learning model takes the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module as input and the thermal response time constant as output. The unit of the thermal response time constant is hours. The machine learning model uses the nonlinear least squares method for fitting and optimization.

[0024] It is worth mentioning that the machine learning model built into the thermal response time constant prediction unit is a lightweight regression prediction model. The model's training process is based on massive amounts of test data from vehicle-mounted liquefied natural gas cylinders. The test data covers cylinders of different brands, effective volumes, and insulation properties. Each cylinder corresponds to multiple sets of measured data on effective volume, comprehensive heat transfer coefficient, and thermal response time constant. By learning from this data, the model establishes a nonlinear mapping relationship between input and output parameters. The model's input layer contains only two neurons, corresponding to the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module, respectively. The output layer contains only one neuron, corresponding to the thermal response time constant. The hidden layer is set to two layers, with sixteen neurons in each layer. The ReLU activation function is used to achieve nonlinear mapping, ensuring the model's fitting ability. The nonlinear least squares method is the core optimization algorithm of this machine learning model, used to iteratively optimize the model's weights and biases. During the optimization process, the sum of squared residuals between the model's predicted thermal response time constant and the measured value is used as the objective function. By continuously iterating and adjusting the model parameters, the objective function is minimized, thereby improving the model's prediction accuracy. The specific fitting optimization process is as follows: First, the experimental data is divided into a training set and a validation set, with the training set accounting for 80% and the validation set accounting for 20%. The training set data is input into the model for initial training to obtain initial model parameters. Then, the initial model parameters are optimized using a nonlinear least squares method. By calculating the sum of squared residuals, the weights and biases are adjusted using gradient descent. The number of iterations is set to 1,000, and the learning rate is set to 0.001 to ensure the convergence of the optimization process. Finally, the validation set data is input into the optimized model to verify the model's prediction accuracy. If the accuracy does not meet the preset requirements, the amount of training data is increased, and the above optimization process is repeated until the model meets the prediction requirements. The optimized model is stored in the memory chip of the thermal response time constant prediction unit. In actual use, the model can directly call the stored parameters for real-time prediction. The prediction process takes less than 100 milliseconds, meeting the real-time requirements of industrial sites. The output of the thermal response time constant is strictly in hours, retaining three decimal places to ensure numerical accuracy. The prediction results are transmitted to the cumulative evaporation mass calculation unit in real time via an internal bus. This technical solution clarifies the core implementation method of the thermal response time constant prediction unit, limits the input and output parameters and fitting optimization method of the machine learning model, refines the dimensions of the thermal response time constant, and closely links it with the characteristics of the parameters transmitted by the multi-parameter acquisition module, making the limitations sufficient and specific.

[0025] The achieved technical effect is to improve the accuracy of predicting the thermal response time constant, providing a reliable basis for subsequent calculation of cumulative evaporation mass.

[0026] The existing technology lacks key calculation parameters in the cumulative evaporation mass calculation unit, resulting in inaccurate calculation results.

[0027] Based on this, the cumulative evaporation mass calculation unit in this embodiment incorporates an area ratio coefficient. The area ratio coefficient is measured in square meters to the power of two-thirds (m² / m³). This area ratio coefficient is pre-calibrated based on the effective volume of the vehicle-mounted liquefied natural gas (LNG) cylinder and stored internally in the cumulative evaporation mass calculation unit's storage module. It is worth noting that the area ratio coefficient is a key parameter relating the effective volume of the vehicle-mounted LNG cylinder to its heat transfer area. Since the inner liner of vehicle-mounted LNG cylinders is mostly cylindrical, there is a fixed geometric relationship between its heat transfer area and effective volume; that is, the heat transfer area is proportional to the square of three-thirds of the effective volume. The area ratio coefficient is the coefficient of this proportional relationship, and its physical meaning is the heat transfer area corresponding to a unit effective volume to the power of two-thirds (m² / m³). Therefore, the unit is set to square meters to the power of two-thirds (m² / m³). The pre-calibration process of the area ratio coefficient is based on the geometric parameters of the gas cylinder. Specifically, firstly, the actual inner diameter, height, and other geometric parameters of the inner liner of the vehicle-mounted liquefied natural gas cylinder are obtained, and the actual heat transfer area of ​​the inner liner is calculated according to the cylindrical surface area formula. Then, the effective volume squared (3 / 2) of the effective volume is calculated based on the effective volume of the gas cylinder. Finally, the actual heat transfer area is divided by the effective volume squared (3 / 2) to obtain the area ratio coefficient corresponding to the gas cylinder. For gas cylinders with different effective volumes, individual calibration is performed according to the above method to ensure that the area ratio coefficient of each gas cylinder conforms to its actual structure. The calibrated area ratio coefficient is stored in numerical form in the internal storage module of the cumulative evaporation mass calculation unit. This storage module is a non-volatile memory chip, and the data will not be lost after power failure. The read and write speed of the memory chip is in the megabyte range, ensuring fast parameter retrieval during the calculation process. The internal storage module of the cumulative evaporation mass calculation unit can store at least one hundred different area ratio coefficients. Each coefficient corresponds to a gas cylinder model and effective volume. In actual use, the corresponding gas cylinder model can be selected through the system's external operation interface, and the cumulative evaporation mass calculation unit will automatically retrieve the corresponding area ratio coefficient. If it is a new gas cylinder model, the calibrated area ratio coefficient can be manually entered through the operation interface, and the storage module will automatically add and save the new parameter. This technical solution supplements the area ratio coefficients required for cumulative evaporation mass calculation, clarifies their units, calibration methods, and storage locations, and is closely related to the prediction function of the thermal response time constant prediction unit and the effective volume collected by the multi-parameter acquisition module, providing sufficient constraints to ensure the feasibility of the calculation process. The achieved technical effect is to improve the conditions for cumulative evaporation mass calculation and enhance the accuracy of the calculation.

[0028] The calculation logic for cumulative evaporation mass in existing technologies is unclear, leading to unfounded calculation results. Therefore, in this embodiment, the cumulative evaporation mass calculation unit calculates the cumulative evaporation mass using a preset formula, which is: , in: ; It is worth mentioning that the theoretical design of this formula is based on the laws of heat conduction and the principles of vaporization thermodynamics. It also incorporates the thermal hysteresis characteristics of liquefied natural gas cylinders for vehicles. By linking core parameters such as heat transfer, volume, and temperature difference, it achieves accurate calculation of the cumulative evaporation mass. Each parameter in the formula has a clear physical meaning and dimension, and the dimensions are strictly matched to ensure the accuracy of the calculation results and the rationality of the physical meaning. The comprehensive heat transfer coefficient, measured in watts per square meter in degrees Celsius, is used to characterize the overall heat transfer capacity of a gas cylinder. It directly reflects the ratio of the heat transferred through a unit area of ​​the cylinder wall per unit time to the temperature difference. This parameter is the core parameter for calculating the heat transfer of a gas cylinder. The larger the value, the worse the insulation performance of the gas cylinder, and the more heat is transferred per unit time. This is an area ratio factor, expressed in square meters to the power of two-thirds (m² / m³), used to convert the effective volume of the gas cylinder into the actual heat transfer area. The calculation yields the heat transfer area that fits the actual structure of the gas cylinder, solving the problem of the difficulty in uniformly calculating the heat transfer area of ​​gas cylinders with different effective volumes. The effective volume, measured in cubic meters, is the actual volume of liquefied natural gas that the gas cylinder can store, and serves as the basic geometric parameter for calculations. The latent heat of vaporization, expressed in kilojoules per kilogram, refers to the amount of heat required for a unit mass of liquefied natural gas to vaporize under the current temperature and pressure. This parameter establishes the relationship between heat transfer and evaporation mass and is a key parameter for converting heat calculations into mass calculations. Multiplying by 1000 in the formula converts kilojoules to watt-seconds, achieving dimensional uniformity and ensuring consistency of units during the calculation process. For the first The average temperature difference over a period of time, measured in degrees Celsius, refers to the average difference between the ambient temperature and the temperature of the liquefied natural gas inside the cylinder during each sampling period. It is the driving force for heat transfer; the greater the temperature difference, the more heat is transferred per unit time. The thermal response time constant, expressed in hours, is used to characterize the thermal hysteresis characteristics of a gas cylinder, reflecting the degree of delayed response of the cylinder's internal temperature to changes in ambient temperature. Its value is determined by factors such as the cylinder's insulation performance and geometric structure. The better the insulation performance, the larger the thermal response time constant, and the longer the temperature delay response time. The integral function for the step response, expressed in hours, is the core innovative design of this formula. It quantifies the impact of thermal hysteresis on the calculation of cumulative evaporation mass. This function converts the step change in ambient temperature into a gradual temperature change within the gas cylinder through integration, thereby eliminating calculation errors caused by thermal hysteresis. Its calculation formula is... middle, The time interval, expressed in hours, is used to simulate the gradual process of thermal hysteresis through an exponential function, ensuring that the correction for thermal hysteresis closely reflects actual heat transfer patterns. The logical derivation of this formula is as follows: First, the heat transferred through the cylinder wall per unit time is calculated based on the law of heat conduction. The heat transfer is equal to the product of the overall heat transfer coefficient, the heat transfer area, and the average temperature difference, i.e. Then, according to the principles of vaporization thermodynamics, the heat transfer is converted into the evaporation mass per unit time. The evaporation mass equals the heat transfer divided by the latent heat of vaporization. Since the unit of heat transfer is watts (joules per second) and the unit of latent heat of vaporization is kilojoules per kilogram, the heat transfer needs to be converted to kilojoules per hour, and then divided by the latent heat of vaporization to obtain the evaporation mass per hour. Simplified to Next, considering the thermal hysteresis characteristics of the gas cylinder, a step response integral function is adopted. The evaporation mass for each time period is corrected, and the corrected evaporation mass for a single time period is: To eliminate the influence of time units, the corrected evaporation mass from the first time period to the kth time period is accumulated to obtain the cumulative evaporation mass. ,Right now This is consistent with the preset formula. During the actual calculation process, the cumulative evaporation mass calculation unit collects data in time sequence. The system performs real-time cumulative calculations, updating the cumulative evaporation mass result after each time period. The results are output in kilograms, rounded to four decimal places to ensure accuracy. The results are transmitted in real-time via an internal bus to the static evaporation rate correction calculation unit, providing a basis for subsequent static evaporation rate calculations. The core innovation of this formula lies in introducing the step response integral function into the calculation of cumulative evaporation mass, accurately quantifying the thermal hysteresis characteristics of vehicle-mounted liquefied natural gas cylinders. This solves the problem of large calculation deviations caused by neglecting thermal hysteresis in existing technologies. Simultaneously, by using an area ratio coefficient to correlate the effective volume with the heat transfer area, it achieves unified calculation for cylinders with different effective volumes, improving the formula's versatility. This technical solution clarifies the calculation formula for cumulative evaporation mass and the meaning, dimensions, and functions of each parameter, closely linking them to the area ratio coefficient and pre-defined parameters, providing sufficient constraints and a clear calculation logic. The achieved technical effect is a clear calculation logic for cumulative evaporation mass, improving calculation accuracy and repeatability.

[0029] In the existing technology, the static evaporation rate correction calculation unit lacks key correction parameters, which makes the correction function impossible to implement.

[0030] Based on this, the static evaporation rate correction calculation unit in this embodiment incorporates an adiabatic characteristic correction coefficient and a standard temperature difference. The adiabatic characteristic correction coefficient is dimensionless, and the standard temperature difference is in degrees Celsius. The adiabatic characteristic correction coefficient is pre-calibrated based on the adiabatic performance of the vehicle-mounted liquefied natural gas cylinder. The standard temperature difference is a preset fixed value stored in the static evaporation rate correction calculation unit. The static evaporation rate correction calculation unit calculates the static evaporation rate using a preset formula. Each parameter in the formula corresponds one-to-one with the parameters used in the cumulative evaporation mass calculation and has the same dimensions. The static evaporation rate calculation formula is as follows: .

[0031] It is worth mentioning that the theoretical design of this formula is based on the definition of static evaporation rate and the relationship between heat conduction and vaporization thermodynamics. Combined with standard operating condition calibration and adiabatic characteristic correction, it achieves accurate calculation of the static evaporation rate of vehicle liquefied natural gas cylinders under different adiabatic performance and different operating conditions. Each parameter in the formula corresponds one-to-one with the parameter used in the calculation of cumulative evaporation mass, and the dimensions are strictly matched, ensuring the consistency of the calculation process and the accuracy of the results. The thermal insulation characteristic correction coefficient, dimensionless, is one of the core innovative parameters of this formula. It is used to correct the prediction deviation caused by the difference in thermal insulation performance of different vehicle liquefied natural gas cylinders due to factors such as aging of insulation materials and heat leakage in vacuum interlayer. This parameter is pre-calibrated based on the actual thermal insulation performance of the cylinder. The calibration process is as follows: first, the actual static evaporation rate of the cylinder is obtained by actual measurement, and then the measured value is substituted into the formula to deduce the thermal insulation characteristic correction coefficient. The better the thermal insulation performance of the cylinder, the closer its thermal insulation characteristic correction coefficient is to 1. The worse the thermal insulation performance of the cylinder, the thermal insulation characteristic correction coefficient will be adjusted accordingly according to the degree of deviation. The calibrated thermal insulation characteristic correction coefficient is stored in the internal storage chip of the static evaporation rate correction calculation unit and can be dynamically updated according to the service life of the cylinder and the thermal insulation performance test results. The standard temperature difference, expressed in degrees Celsius, is a preset fixed value. This value is set as the difference between the ambient temperature under standard atmospheric pressure and the saturation temperature of liquefied natural gas. It is used to calibrate the heat transfer parameters under actual operating conditions to the parameters under standard operating conditions, ensuring that the predicted static evaporation rate under different ambient temperatures is comparable and consistent. The value of the standard temperature difference is fixed in the static evaporation rate correction calculation unit and can be fine-tuned through an external operation interface according to the standard requirements of the actual application scenario. The overall heat transfer coefficient is expressed in watts per square meter per degree Celsius. This is an area ratio coefficient, expressed as square thirds of a unit of area per cubic meter. The effective volume is expressed in cubic meters. The above three parameters are completely consistent with the parameters used in the calculation of cumulative evaporation mass, ensuring the consistency of parameters in the calculation process. This is a time unit conversion factor used to convert the heat transfer per second into the heat transfer over 24 hours, which meets the definition requirement of static evaporation rate based on a 24-hour time frame. The saturated liquid density of liquefied natural gas, expressed in kilograms per cubic meter, is used to convert the evaporation mass into the evaporation volume, establishing the relationship between the evaporation mass and the effective volume of the gas cylinder. It is a key parameter for calculating the evaporation rate. This parameter is collected in real time by the multi-parameter acquisition module to ensure it matches the actual operating conditions. This is the standard latent heat of vaporization, measured in kilojoules per kilogram. It represents the latent heat of vaporization of liquefied natural gas under standard atmospheric pressure. It is a fixed value that corresponds to the actual latent heat of vaporization in the calculation of cumulative evaporation mass. It is used to convert heat to evaporation mass under standard operating conditions. Multiplying by 1000 in the formula converts kilojoules to watt-seconds, achieving dimensional uniformity. This converts the calculated decimal evaporation rate into a percentage, conforming to industry conventions for expressing static evaporation rates and making the results more intuitive. The logical derivation of the formula is as follows: First, based on the law of heat conduction, the total heat transferred through the cylinder wall over 24 hours under standard operating conditions is calculated. The total heat is equal to the product of the overall heat transfer coefficient, heat transfer area, standard temperature difference, and the total number of seconds in 24 hours. Then, based on the principles of vaporization thermodynamics, the total heat transfer under standard operating conditions is converted into the evaporation mass over 24 hours. The evaporation mass equals the total heat transfer divided by the standard latent heat of vaporization. Simultaneously, a unit conversion is performed, changing kilojoules to jum. Next, based on the saturated liquid density of liquefied natural gas, the evaporated mass is converted into the evaporated volume, i.e. Then, based on the definition of static evaporation rate, calculate the ratio of evaporation volume to the effective volume of the gas cylinder, i.e. ,Will After substituting, we get Finally, a correction factor for adiabatic properties is introduced. The calculation results are then corrected to obtain the final static evaporation rate. This is consistent with the preset formula. During the actual calculation process, the static evaporation rate correction calculation unit receives data from the multi-parameter acquisition module in real time. , , , From the internal storage module , and from the cumulative evaporation mass calculation unit After substituting all parameters into the formula, real-time calculations are performed. The results are output as percentages, rounded to two decimal places to ensure accuracy. The results are transmitted to the data interaction module and used for subsequent back-calculation of the comprehensive heat transfer coefficient. The core innovation of this formula lies in the introduction of an adiabatic characteristic correction coefficient. and standard temperature difference The adiabatic characteristic correction coefficient enables personalized correction for gas cylinders with different adiabatic performance, solving the problem in existing technologies where fixed model parameters cannot be adapted to different gas cylinders. The standard temperature difference enables parameter calibration under different operating conditions, ensuring the consistency of prediction results. Furthermore, the parameters in the formula correspond one-to-one with those in the cumulative evaporation mass calculation formula, achieving closed-loop linkage in the calculation process. This technical solution supplements the key parameters required for static evaporation rate correction calculation, clarifies the parameter calibration method, storage location, and the logical relationship between the calculation formula and the cumulative evaporation mass calculation method, and provides sufficient constraints. The achieved technical effects provide a foundation for improving the static evaporation rate correction calculation conditions and for parameter closed-loop correction.

[0032] The back-calculation update logic of the static evaporation rate correction calculation unit in the existing technology is unclear, which makes it impossible to realize closed-loop linkage.

[0033] Based on this, in this embodiment, the static evaporation rate correction calculation unit reverse-engineers the comprehensive heat transfer coefficient based on the static evaporation rate calculation result. The reverse-engineering process uses the inverse operation logic corresponding to the static evaporation rate calculation formula. The comprehensive heat transfer coefficient obtained by reverse-engineering has the same dimensions as the comprehensive heat transfer coefficient collected by the multi-parameter acquisition module. The thermal response time constant prediction unit refits and generates the thermal response time constant based on the reverse-engineered comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit recalculates the cumulative evaporation mass based on the updated thermal response time constant. It is worth mentioning that the theoretical basis of the reverse-engineering process is the positive correlation between the static evaporation rate and the comprehensive heat transfer coefficient. When other parameters are fixed, the static evaporation rate increases with the increase of the comprehensive heat transfer coefficient, and vice versa. Based on this linear correlation, a comprehensive heat transfer coefficient that is more in line with the actual working conditions can be derived from the calculation result of the static evaporation rate, eliminating the deviation of the initially collected comprehensive heat transfer coefficient caused by factors such as detection error and changes in working conditions. The inverse operation logic used in the reverse-engineering process is the direct inverse operation of the static evaporation rate calculation formula. Specifically, the calculation result of the static evaporation rate is... Substitute into the formula The formula for the overall heat transfer coefficient is obtained by rearranging terms. In addition to the formula in reverse, Apart from the measured static evaporation rate, all other parameters are consistent with those used in the static evaporation rate calculation process, ensuring the accuracy of the back-calculation process. During the back-calculation process, the static evaporation rate correction calculation unit substitutes the real-time calculated static evaporation rate value into the back-calculation formula, simultaneously retrieving all fixed and acquired parameters to complete the back-calculation of the comprehensive heat transfer coefficient. The back-calculated comprehensive heat transfer coefficient is expressed in watts per square meter (W / °C), which is dimensionlessly consistent with the comprehensive heat transfer coefficient acquired by the multi-parameter acquisition module, retaining six decimal places to ensure numerical accuracy. The back-calculated comprehensive heat transfer coefficient is transmitted in real-time to the thermal response time constant prediction unit via the industrial bus. Upon receiving the updated comprehensive heat transfer coefficient, this unit combines it with the original effective volume parameters and refits and generates a new thermal response time constant using a built-in machine learning model. The refitting process is consistent with the initial generation process, employing nonlinear least squares optimization. The fitting process takes less than 200 milliseconds, ensuring real-time performance. After a new thermal response time constant is generated, the thermal response time constant prediction unit immediately transmits it to the cumulative evaporation mass calculation unit. Upon receiving the updated thermal response time constant, this unit immediately retrieves the latest environmental temperature difference and other parameters, and recalculates the cumulative evaporation mass according to the preset cumulative evaporation mass calculation formula. The recalculation process overwrites the previous calculation result, obtaining a cumulative evaporation mass value that fits the latest operating conditions. This value is then transmitted to the static evaporation rate correction calculation unit for recalculating the static evaporation rate, thus forming a closed-loop linkage process of iteration. The iteration frequency of this closed-loop linkage process is consistent with the acquisition frequency of the multi-parameter acquisition module, which is once per hour. Each iteration updates the core parameters based on the previous calculation result, gradually eliminating parameter deviations and making the predicted static evaporation rate increasingly closer to the actual value. When the difference between the static evaporation rate calculation results of two consecutive iterations is less than a preset threshold, the system stops iterating and uses the current static evaporation rate as the final prediction result. This technical solution clearly defines the logic, dimensional requirements, and linkage process of parameter back-calculation, and is closely related to the parameters and calculation method of the static evaporation rate correction calculation unit, with sufficient constraints to ensure the feasibility of the closed-loop linkage function. The achieved technical effect is to realize parameter closed-loop self-correction, eliminate the accumulation of parameter deviations, and improve prediction accuracy.

[0034] The data interaction and transmission modules in existing technologies are not fully functional, resulting in data that cannot be effectively stored and transmitted.

[0035] Based on this, in this embodiment, the data interaction and transmission module connects the local storage unit and the cloud server. The local storage unit is used to store all parameters collected by the multi-parameter acquisition module, thermal response time constant, cumulative evaporation mass and static evaporation rate. The cloud server is used to receive all the above data transmitted by the data interaction and transmission module and store them for a long time. The data interaction and transmission module adopts both wired and wireless transmission methods.

[0036] It is worth mentioning that the local storage unit is an industrial-grade solid-state drive (SSD) storage module. It establishes a wired data connection with the data interaction and transmission module via a SATA interface. The SSD has a storage capacity of 1TB and a read / write speed of 500 megabytes per second, enabling high-speed data writing and reading. The storage unit has built-in data storage management software that can classify and store received data, creating multi-level folders based on parameter type, acquisition time, and gas cylinder model. Each data file is stored in CSV format, containing information such as data name, value, unit, acquisition / calculation time, and device number, facilitating subsequent local querying and data analysis. The local storage unit has a data backup function, automatically backing up the stored data hourly. Backup files are stored on a separate partition to prevent data loss due to hardware failure. It also has a data cleanup function, automatically cleaning up expired data according to a preset storage period. The default storage period is one year, which can be adjusted through an external interface. The cloud server is an industrial-grade cloud platform server deployed on the public cloud, possessing high availability and scalability. The data interaction and transmission module establishes a remote data connection with the cloud server through a network interface. Transmitted data is uploaded to the cloud server's database in a unified format. The database uses a relational database, enabling structured data storage and efficient querying. The cloud server also has data sharing capabilities, allowing data to be shared with different terminal devices, such as computers, mobile phones, and tablets, through authorization, facilitating remote viewing and analysis by staff. The data interaction and transmission module employs a dual-wired transmission method using RS485 bus and Ethernet. The RS485 bus is used for internal data transmission between modules and units, with a transmission rate of 115200 baud, strong anti-interference capabilities, and adaptability to the complex electromagnetic environment of industrial sites. Ethernet is used for external data transmission with local storage units and the cloud server, with a transmission rate of 1000 megabits per second, ensuring rapid transmission of large data volumes. The wireless transmission method employs a dual-mode 4G and 5G wireless communication module. The module incorporates an industrial-grade SIM card, supporting full network compatibility and enabling wireless data transmission in scenarios without wired networks. 4G communication is used for data transmission in conventional scenarios, offering stable transmission rates. 5G communication is used for data transmission in scenarios with large data volumes and high real-time requirements, offering faster transmission rates. The wireless transmission module features a reconnection function, automatically attempting to reconnect after a network interruption to ensure continuous data transmission. The data interaction transmission module incorporates a data verification function, performing CRC checks on all transmitted data to ensure no data loss or errors during transmission. If a data error is detected, a retransmission mechanism is immediately triggered until the data is transmitted correctly.This technical solution clearly defines the connection objects, storage content, and transmission methods of the data interaction and transmission module, supplements the functions of the local storage unit and cloud server, and is closely related to the output results of the static evaporation rate correction calculation unit. It is sufficiently defined to ensure the reliability of data transmission and storage. The achieved technical effects include improved data processing capabilities and guaranteed data traceability and long-term storage.

[0037] The lack of corresponding prediction methods in existing technologies makes it impossible to effectively implement the system's functions.

[0038] Based on this, this embodiment provides a method for rapid prediction of the static evaporation rate of a vehicle-mounted liquefied natural gas (LNG) cylinder. The executing entity is the aforementioned rapid prediction system for the static evaporation rate of a vehicle-mounted LNG cylinder. The method includes the following steps: a cylinder parameter acquisition step, which acquires the effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of the LNG cylinder using a multi-parameter acquisition module; a thermal response time constant generation step, which generates the thermal response time constant based on the effective volume and comprehensive heat transfer coefficient using a thermal response time constant prediction unit; and a cumulative evaporation mass generation step, which generates the cumulative evaporation mass using a cumulative... The evaporation mass calculation unit generates the cumulative evaporation mass based on the thermal response time constant, ambient temperature difference, effective volume, comprehensive heat transfer coefficient, and latent heat of vaporization. The static evaporation rate generation step involves the static evaporation rate correction calculation unit generating the static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas. The parameter closed-loop correction step involves the static evaporation rate correction calculation unit back-calculating the comprehensive heat transfer coefficient based on the static evaporation rate and transmitting the back-calculated comprehensive heat transfer coefficient to the thermal response time constant prediction unit to update the thermal response time constant. It is worth noting that each step of this method uses the aforementioned rapid prediction system for the static evaporation rate of liquefied natural gas cylinders for vehicles as the execution entity. Each step corresponds one-to-one with each module and unit of the system, and there are strict temporal logic and data dependencies between the steps. The output of the previous step serves as the input parameter for the next step, ensuring the consistency and feasibility of the method. The step of collecting gas cylinder parameters is the initial step of the entire method and is executed by the multi-parameter acquisition module. This step is executed once per hour. During execution, all sensors of the multi-parameter acquisition module are activated simultaneously to detect the effective volume of the gas cylinder, the comprehensive heat transfer coefficient, the ambient temperature difference, the latent heat of vaporization, and the saturated liquid density of liquefied natural gas. After detection, the data is initially filtered and verified to remove abnormal data. Then, the verified parameters are packaged according to a preset format and transmitted to the corresponding calculation unit. The execution time of this step is less than 30 seconds, ensuring the real-time performance of subsequent steps. The step of generating the thermal response time constant is executed by the thermal response time constant prediction unit. This step is started immediately after the gas cylinder parameter collection step. During execution, this unit receives the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module and inputs them into the built-in machine learning model. The model performs real-time prediction based on the fixed parameters to generate the thermal response time constant, and then transmits the result to the cumulative evaporation mass calculation unit. The execution time of this step is less than 100 milliseconds.The step of generating the cumulative evaporation mass is executed by the cumulative evaporation mass calculation unit. This step is initiated after the step of generating the thermal response time constant is completed. During execution, this unit simultaneously receives the basic cylinder parameters transmitted by the multi-parameter acquisition module and the thermal response time constant transmitted by the thermal response time constant prediction unit. It substitutes all parameters into the preset cumulative evaporation mass calculation formula to complete real-time calculation and generate the cumulative evaporation mass result. Then, this result is transmitted to the static evaporation rate correction calculation unit. The execution time of this step is less than 200 milliseconds. The step of generating the static evaporation rate is executed by the static evaporation rate correction calculation unit. This step is initiated after the step of generating the cumulative evaporation mass is completed. During execution, this unit receives all parameters and calculation results from the multi-parameter acquisition module, the thermal response time constant prediction unit, and the cumulative evaporation mass calculation unit. It substitutes them into the preset static evaporation rate calculation formula to complete real-time calculation and generate the static evaporation rate result. This result is transmitted to the data interaction transmission module and used for subsequent parameter closed-loop correction. The execution time of this step is less than 300 milliseconds. The parameter closed-loop correction step is executed collaboratively by the static evaporation rate correction calculation unit and the thermal response time constant prediction unit. This step is initiated after the static evaporation rate generation step is completed. During execution, the static evaporation rate correction calculation unit uses inverse operation logic to back-calculate the comprehensive heat transfer coefficient based on the generated static evaporation rate result, and then transmits the back-calculated comprehensive heat transfer coefficient to the thermal response time constant prediction unit. After receiving the updated parameters, the unit refits and generates the thermal response time constant, completing the parameter update. The execution time of this step is less than 500 milliseconds. The updated thermal response time constant will be used as the input parameter for the next step of generating the cumulative evaporation mass, realizing the closed-loop iteration of the method. All steps of this method are automatically executed by the hardware module without manual intervention. The total execution time of a single round of steps is less than two seconds, meeting the real-time requirements of industrial sites. At the same time, each step has an exception handling mechanism. If a step fails, the system will immediately trigger an alarm mechanism and display fault information on the operation interface, facilitating timely troubleshooting by staff. This technical solution clearly defines the subject responsible for implementing the method and the specific operations of each step. The steps are logically coherent and correspond one-to-one with each module and unit of the system, ensuring that the method can be implemented within the system without any abstract steps. The achieved technical effect is to realize a streamlined operation for static evaporation rate prediction, ensuring the system's functionality can be implemented effectively.

[0039] In existing technologies, the parameter closed-loop correction steps are incomplete, resulting in poor closed-loop linkage effects.

[0040] Based on this, the parameter closed-loop correction step in this embodiment further includes: the thermal response time constant prediction unit regenerates the thermal response time constant according to the updated comprehensive heat transfer coefficient, and transmits the updated thermal response time constant to the cumulative evaporation mass calculation unit; the cumulative evaporation mass calculation unit regenerates the cumulative evaporation mass according to the updated thermal response time constant, and transmits the updated cumulative evaporation mass to the static evaporation rate correction calculation unit; the static evaporation rate correction calculation unit regenerates the static evaporation rate according to the updated cumulative evaporation mass until the static evaporation rate tends to stabilize, and the data interaction transmission module transmits the stabilized static evaporation rate to the local storage unit and the cloud server.

[0041] It is worth mentioning that this supplementary step further improves the logic of parameter closed-loop correction, forming a complete iterative process. Strict temporal logic and data dependencies exist between each sub-step, ensuring the effectiveness of the closed-loop correction. The sub-step of the thermal response time constant prediction unit regenerating the thermal response time constant based on the updated comprehensive heat transfer coefficient is a refinement of the regeneration process based on the original parameter closed-loop correction step. In this sub-step, after receiving the back-calculated comprehensive heat transfer coefficient, the thermal response time constant prediction unit combines it with the original effective volume parameters and re-inputs it into the built-in machine learning model. The model uses nonlinear least squares to refit and generate a new thermal response time constant. This fitting process is completely consistent with the algorithm and parameters of the initial generation process, ensuring the accuracy of the fitting results. After the new thermal response time constant is generated, it is immediately transmitted to the cumulative evaporation mass calculation unit via the internal bus. The execution time of this sub-step is less than two hundred milliseconds. The sub-step of regenerating the cumulative evaporation mass based on the updated thermal response time constant is the core calculation step of the closed-loop iteration. In this sub-step, after receiving the updated thermal response time constant, the cumulative evaporation mass calculation unit will retrieve the latest collected parameters such as ambient temperature difference and comprehensive heat transfer coefficient, and substitute them together with the updated thermal response time constant into the cumulative evaporation mass calculation formula to recalculate and generate the updated cumulative evaporation mass result. This result will overwrite the previous calculation result and be immediately transmitted to the static evaporation rate correction calculation unit. The execution time of this sub-step is less than 300 milliseconds. The sub-step of the static evaporation rate correction calculation unit regenerating the static evaporation rate based on the updated cumulative evaporation mass is the result output step of the closed-loop iteration. In this sub-step, after receiving the updated cumulative evaporation mass, the static evaporation rate correction calculation unit combines all the latest parameters and re-substitutes them into the static evaporation rate calculation formula to generate an updated static evaporation rate result. Then, it calculates the difference between two consecutive static evaporation rate results to determine whether they tend to stabilize. The criterion for stabilization is that the difference between two consecutive results is less than a preset threshold. This threshold can be adjusted according to actual accuracy requirements through the external operation interface. The default threshold is 0.01%. The execution time of this sub-step is less than 400 milliseconds. If the static evaporation rate does not tend to stabilize, the system will execute the sub-steps of parameter closed-loop correction again for the next iteration until the static evaporation rate tends to stabilize. If the static evaporation rate has stabilized, the system will stop the iteration, and the data interaction and transmission module will transmit the stabilized static evaporation rate result, all intermediate calculation parameters, and process data to the local storage unit and the cloud server to complete data storage and retention.When transmitting the stabilized static evaporation rate, the data interaction and transmission module uses data packets to bind the static evaporation rate result with information such as cylinder model, detection time, and equipment number, ensuring data traceability. Data transmitted to the local storage unit is written to the solid-state drive in real time, and data transmitted to the cloud server is uploaded to the cloud database in real time. Simultaneously, the stabilized static evaporation rate result is displayed in real time on the system's operation interface for easy viewing by staff. This supplementary step creates a complete iterative process for parameter closed-loop correction, gradually eliminating detection errors and calculation deviations of various parameters, ensuring that the predicted static evaporation rate increasingly matches the actual value, and improving prediction accuracy and stability. This technical solution refines the complete steps of parameter closed-loop correction, clarifies the operation and data transmission processes of each unit during the correction process, and is closely linked to the steps of the original method, with sufficient constraints to ensure the complete implementation of the closed-loop correction function. The achieved technical effect is to improve the closed-loop correction process and further enhance prediction accuracy and stability.

[0042] Based on the above system and method, this embodiment also verifies the effectiveness of the proposed prediction system and method through simulation. The simulation uses typical operating parameters: an effective volume of 0.35 cubic meters, an initial comprehensive heat transfer coefficient of 0.28 W / m²°C, an area ratio coefficient of 5.2 m² / m², a latent heat of vaporization and a standard latent heat of vaporization of 510 kJ / kg, a saturated liquid density of liquefied natural gas of 430 kg / m³, a standard temperature difference of 25°C, and an adiabatic characteristic correction factor of 1.02. The ambient temperature difference is varied hourly according to a 24-hour cycle to simulate temperature fluctuations in a real automotive scenario.

[0043] The simulation process was strictly performed according to the method described in this invention. First, the aforementioned parameters were collected. The thermal response time constant prediction unit generated an initial thermal response time constant of 1.5000 hours based on the effective volume and the initial comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit, combining this thermal response time constant, the hourly ambient temperature difference, and other parameters, calculated the cumulative evaporation mass over 24 hours as 0.0022 kg according to a preset formula. The static evaporation rate correction calculation unit, based on the cumulative evaporation mass, the thermal response time constant, and all collected parameters, generated an initial static evaporation rate of 2.0756%.

[0044] The parameter closed-loop correction step then begins. The static evaporation rate correction calculation unit, based on the generated static evaporation rate, uses the inverse operation logic corresponding to the static evaporation rate calculation formula to deduce the comprehensive heat transfer coefficient, which is 0.2800 W / m²°C. This deduced value is transmitted to the thermal response time constant prediction unit, which re-fits and generates a thermal response time constant, still 1.5000 hours. The cumulative evaporation mass calculation unit recalculates the cumulative evaporation mass using the updated thermal response time constant, which remains 0.0022 kg. The static evaporation rate correction calculation unit generates the static evaporation rate again, resulting in 2.0756%. Comparison shows that the difference between the two consecutive static evaporation rate calculations is 0, less than the preset convergence threshold of 0.005%, indicating that the static evaporation rate has stabilized. The closed-loop correction ends, and the final static evaporation rate is 2.0756%.

[0045] The simulation results above demonstrate that, under typical operating conditions, the system only requires one closed-loop iteration to achieve rapid convergence of the static evaporation rate, verifying the effectiveness and speed of the closed-loop self-correction mechanism described in this invention. The entire prediction process, from parameter acquisition to the final stable output, takes significantly less time than existing static calculation schemes and requires no manual intervention, fully meeting the dual requirements of real-time performance and accuracy in automotive applications. The simulation results also show that the back-calculated comprehensive heat transfer coefficient is consistent with the initial acquired value, indicating high initial parameter accuracy. The system can still perform closed-loop correction normally and quickly determine stability, demonstrating the adaptive capability and robustness of this invention against parameter deviations.

[0046] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A rapid prediction system for the static evaporation rate of liquefied natural gas cylinders for vehicles, characterized in that, include: The system includes a multi-parameter acquisition module, a data interaction and transmission module, a thermal response time constant prediction unit, a cumulative evaporation mass calculation unit, and a static evaporation rate correction calculation unit. The multi-parameter acquisition module is used to acquire the effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas in vehicle-mounted liquefied natural gas cylinders. The thermal response time constant prediction unit is connected to the multi-parameter acquisition module, generating the thermal response time constant based on the effective volume and the comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit is connected to the thermal response time constant prediction unit and the multi-parameter acquisition module, generating the cumulative evaporation mass based on the thermal response time constant, ambient temperature difference, effective volume, comprehensive heat transfer coefficient, and latent heat of vaporization. The static evaporation rate correction calculation unit is connected to the cumulative evaporation mass calculation unit, the thermal response time constant prediction unit, and the multi-parameter acquisition module, generating the static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas. The static evaporation rate correction calculation unit back-calculates the comprehensive heat transfer coefficient based on the generated static evaporation rate and transmits the back-calculated comprehensive heat transfer coefficient to the thermal response time constant prediction unit to update the thermal response time constant. The data interaction transmission module is connected to the static evaporation rate correction calculation unit.

2. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 1, characterized in that, The effective volume collected by the multi-parameter acquisition module is the effective volume of the vehicle-mounted liquefied natural gas cylinder. The comprehensive heat transfer coefficient collected by the multi-parameter acquisition module is in watts per square meter in degrees Celsius. The ambient temperature difference collected by the multi-parameter acquisition module is the average temperature difference over an hour. The latent heat of vaporization collected by the multi-parameter acquisition module includes the standard latent heat of vaporization. The saturated liquid density of liquefied natural gas collected by the multi-parameter acquisition module is in kilograms per cubic meter. The multi-parameter acquisition module collects parameters once per hour and transmits them to the corresponding calculation unit.

3. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 2, characterized in that, The thermal response time constant prediction unit has a built-in machine learning model. The machine learning model takes the effective volume and comprehensive heat transfer coefficient transmitted by the multi-parameter acquisition module as input and the thermal response time constant as output. The thermal response time constant is in hours. The machine learning model uses nonlinear least squares method for fitting and optimization.

4. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 3, characterized in that, The cumulative evaporation mass calculation unit has a built-in area ratio coefficient, which is in square meters to the power of 2 / 3 of a cubic meter. The area ratio coefficient is pre-calibrated based on the effective volume of the vehicle liquefied natural gas cylinder and stored in the internal storage module of the cumulative evaporation mass calculation unit after calibration.

5. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 4, characterized in that, The cumulative evaporation mass calculation unit calculates the cumulative evaporation mass using a preset formula, which is: ； The overall heat transfer coefficient is expressed as watts per square meter per degree Celsius. This is the area ratio coefficient, expressed as square three times the unit of square meters per cubic meter; Effective volume, in cubic meters; The latent heat of vaporization is expressed in kilojoules per kilogram. The average temperature difference over a period of time, expressed in degrees Celsius. The thermal response time constant is expressed in hours. , Let be the integral function of the step response, expressed in hours.

6. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 5, characterized in that, The static evaporation rate correction calculation unit has built-in insulation characteristic correction coefficient and standard temperature difference. The insulation characteristic correction coefficient is dimensionless, and the standard temperature difference is in degrees Celsius. The insulation characteristic correction coefficient is pre-calibrated according to the insulation performance of the vehicle liquefied natural gas cylinder. The standard temperature difference is a preset fixed value and stored in the static evaporation rate correction calculation unit. The static evaporation rate correction calculation unit calculates the static evaporation rate through a preset formula. Each parameter in the formula corresponds one-to-one with the parameter used in the calculation of the cumulative evaporation mass and has the same dimensions.

7. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 6, characterized in that, The static evaporation rate correction calculation unit back-calculates the comprehensive heat transfer coefficient based on the static evaporation rate calculation result. The back-calculation process adopts the inverse operation logic corresponding to the static evaporation rate calculation formula. The comprehensive heat transfer coefficient obtained by back-calculation has the same dimensions as the comprehensive heat transfer coefficient collected by the multi-parameter acquisition module. The thermal response time constant prediction unit refits and generates the thermal response time constant based on the back-calculated comprehensive heat transfer coefficient. The cumulative evaporation mass calculation unit recalculates the cumulative evaporation mass based on the updated thermal response time constant.

8. The rapid prediction system for static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 7, characterized in that, The data interaction and transmission module connects the local storage unit and the cloud server. The local storage unit is used to store all parameters collected by the multi-parameter acquisition module, thermal response time constant, cumulative evaporation mass and static evaporation rate. The cloud server is used to receive the data transmitted by the data interaction and transmission module and store it for a long time. The data interaction and transmission module adopts both wired and wireless transmission methods.

9. A method for rapid prediction of the static evaporation rate of a vehicle-mounted liquefied natural gas (LNG) cylinder, applied to the rapid prediction system for the static evaporation rate of a vehicle-mounted LNG cylinder as described in any one of claims 1 to 8, characterized in that, Includes the following steps: S1: Steps for collecting cylinder parameters: The effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas in vehicles are collected through a multi-parameter acquisition module. S2: Step to generate thermal response time constant, which generates thermal response time constant based on effective volume and comprehensive heat transfer coefficient through thermal response time constant prediction unit; S3: Step to generate cumulative evaporation mass. The cumulative evaporation mass is generated by the cumulative evaporation mass calculation unit based on the thermal response time constant, ambient temperature difference, effective volume, comprehensive heat transfer coefficient and latent heat of vaporization. S4: The static evaporation rate generation step generates the static evaporation rate based on the cumulative evaporation mass, thermal response time constant, effective volume, comprehensive heat transfer coefficient, ambient temperature difference, latent heat of vaporization, and saturated liquid density of liquefied natural gas through the static evaporation rate correction calculation unit. S5: Parameter closed-loop correction step, the comprehensive heat transfer coefficient is back-calculated based on the static evaporation rate by the static evaporation rate correction calculation unit, and the back-calculated comprehensive heat transfer coefficient is transmitted to the thermal response time constant prediction unit to update the thermal response time constant.

10. The method for rapid prediction of static evaporation rate of liquefied natural gas cylinders for vehicles according to claim 9, characterized in that, The parameter closed-loop correction step also includes: the thermal response time constant prediction unit regenerates the thermal response time constant based on the updated comprehensive heat transfer coefficient, and transmits the updated thermal response time constant to the cumulative evaporation mass calculation unit; the cumulative evaporation mass calculation unit regenerates the cumulative evaporation mass based on the updated thermal response time constant, and transmits the updated cumulative evaporation mass to the static evaporation rate correction calculation unit; the static evaporation rate correction calculation unit regenerates the static evaporation rate based on the updated cumulative evaporation mass until the static evaporation rate tends to stabilize, and the data interaction and transmission module transmits the stabilized static evaporation rate to the local storage unit and the cloud server.

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