User-initiated setting-based hydrogen filling method, hydrogen filling device, hydrogen filling dispenser device, hydrogen filling protocol identification method, and hydrogen filling protocol negotiation method

Abstract

Propose a process and protocol to support user-driven fill volume setting functionality [Solution] The method of fueling a hydrogen-fueled mobility with hydrogen includes receiving user input related to setting a hydrogen filling target, determining a target state of charge (SOC) for hydrogen filling of the mobility based on the user input, and receiving a supply of hydrogen through a hydrogen filling control sequence to reach the target state of charge.

Description

[Technical Field]

[0001] The present invention relates to a control technology for hydrogen fueling / supply of hydrogen vehicles, and more particularly to a hydrogen fueling process and a platform for the process that improves the efficiency, convenience, speed, and real-timeness of hydrogen fueling / supply. [Background technology]

[0002] The material described in this section merely provides background information for the present embodiment and does not constitute prior art.

[0003] A hydrogen vehicle, hydrogen electric vehicle, or fuel cell electric vehicle (FCEV) is a non-polluting vehicle that runs on electrical energy generated when high-pressure hydrogen stored in the vehicle meets atmospheric air.

[0004] The concept of a hydrogen vehicle includes not only hydrogen electric vehicles or fuel cell vehicles that use hydrogen as an energy source and a fuel cell system, but also any mobility that uses hydrogen as fuel to generate power and run on an internal combustion engine (ICE).

[0005] As is well known, hydrogen electric vehicles not only emit pure water (H2O) during the electricity generation process, but also have the function of removing ultrafine dust particles from the atmosphere while in operation, making them garnering attention as an environmentally friendly form of future mobility. Given that hydrogen, the fuel, is infinitely available on Earth and the energy production process is environmentally friendly, hydrogen electric vehicles are attracting widespread attention as a technology with potential for use across industries.

[0006] A hydrogen electric vehicle generates electrical energy by transferring high-pressure hydrogen stored safely in a hydrogen fuel tank and oxygen supplied through an air supply system to a fuel cell stack, where an electrochemical reaction occurs between the hydrogen and oxygen. The generated electrical energy is converted into kinetic energy by the drive motor to power the hydrogen electric vehicle, and the hydrogen electric vehicle has the advantage of emitting only pure water through the exhaust while in motion.

[0007] Fuel cell systems power hydrogen electric vehicles instead of the engines used in internal combustion vehicles. Fuel cells are devices that generate the electrical energy needed for driving, and are sometimes called "tertiary batteries." Fuel cells convert thermal energy into electrical energy using an electrochemical reaction between oxygen and hydrogen. The electrical energy generated is the result of a purely chemical reaction, and unlike fossil fuels, does not produce exhaust gases such as carbon dioxide. There are various types of fuel cell systems, such as PEMFC, SOFC, and MCFC, depending on the fuel and material. The components that generate power using fuel cells in hydrogen electric vehicles include a fuel cell stack, hydrogen supply system, air supply system, and thermal management system.

[0008] The fuel cell stack needs the help of operating devices to efficiently generate electrical energy. Among these, the hydrogen supply system converts the hydrogen safely stored in the hydrogen tank from a high-pressure state to a low-pressure state and transfers it to the fuel cell stack. It also increases the efficiency of the hydrogen supply through a recirculation line.

[0009] A thermal management system is a device that releases heat generated during electrochemical reactions in a fuel cell stack to the outside and circulates coolant to maintain a constant temperature in the fuel cell stack. The thermal management system can affect the output and lifespan of a fuel cell stack.

[0010] The concept of a hydrogen fueled car, which is not a hydrogen electric car, is also a vehicle that uses hydrogen as fuel, but a hydrogen fueled car uses the heat generated by directly burning hydrogen in the engine to drive the electric motor. The method of filling / supplying hydrogen for a hydrogen fueled car is not much different from the method of filling / supplying hydrogen for a hydrogen electric car.

[0011] The ultimate goal of the control technique for filling / supplying hydrogen to vehicles that use hydrogen as fuel is to control the temperature (T) and pressure (P) of the compressed hydrogen storage system (CHSS) on the fuel cell side so that it operates within the limit temperature / pressure conditions for safety.

[0012] The hydrogen filling / supply process, control techniques, and protocols for conventional hydrogen electric vehicles were established at a time when wired / wireless communication technologies and control computing techniques were not yet mature, and therefore do not adequately reflect recent advances in information and communications technology (ICT). Summary of the Invention [Problem to be solved by the invention]

[0013] SUMMARY OF THE INVENTION In order to solve the above problems, an object of the present invention is to provide a function for setting the filling amount according to the user's request. It is also an object of the present invention to propose a process and protocol for underpinning the user-initiated fill volume setting function. Another object of the present invention is to propose an appropriate filling amount determination and hydrogen filling / supply process according to the surrounding circumstances and conditions at the time of filling. It is also an object of the present invention to propose a two-way communication protocol that supports user-initiated filling and hydrogen filling / dispensing processes. [Means for solving the problem]

[0014] To achieve the above object, a user-driven setting-based hydrogen filling method according to one embodiment of the present invention may include a step of receiving user input related to setting a hydrogen filling target, a step of determining a target state of charge (SOC) for hydrogen filling of a mobility based on the user input, and a step of receiving a supply of hydrogen according to a hydrogen filling control sequence to reach the target state of charge.

[0015] At this time, the user input may include a target filling rate for hydrogen filling of the mobility. The step of determining the target filling rate may determine the target filling rate based on at least one of a current filling state of the mobility and filling-related status information of the mobility, based on a user input.

[0016] A user-driven setting-based hydrogen filling method according to one embodiment of the present invention may further include a step of acquiring progress data of the hydrogen filling process of the mobility during the hydrogen filling process between the starting filling rate and the target filling rate of hydrogen filling, and a step of transmitting the progress data of the mobility to a dispenser or filling control system that supplies hydrogen to the mobility so that the progress data of the mobility can be monitored.

[0017] The step of receiving a supply of hydrogen according to a hydrogen filling control sequence to reach the target filling rate may include the step of generating a hydrogen filling control request for at least one intermediate filling rate between the starting filling rate of hydrogen filling and the target filling rate.

[0018] Another embodiment of the present invention provides a user-driven setting-based hydrogen filling method that includes receiving user input related to hydrogen filling target setting, determining a target state of charge (SOC) for hydrogen filling of a mobility vehicle based on the user input, and providing a hydrogen filling control sequence for reaching the target state of charge.

[0019] At this time, the user input may include a target filling rate for hydrogen filling of the mobility.

[0020] The step of determining the target filling rate may determine the target filling rate based on at least one of a current filling state of the mobility and filling-related status information of the mobility, based on a user input.

[0021] The step of providing a hydrogen filling control sequence for reaching a target filling rate may involve determining a target hydrogen filling control sequence corresponding to the target filling rate from among a group of candidate hydrogen filling control sequences for reaching individual target filling rates.

[0022] The step of providing a hydrogen filling control sequence for reaching the target filling rate can predict a hydrogen filling control sequence for reaching the target filling rate based on existing hydrogen filling data between the mobility and a dispenser that supplies hydrogen to the mobility.

[0023] The step of providing a hydrogen filling control sequence for reaching the target filling rate may generate hydrogen filling control commands for at least one intermediate filling rate between the starting hydrogen filling rate and the target filling rate.

[0024] The step of providing a hydrogen filling control sequence to reach the target filling rate may be performed using an artificial neural network that receives an input of a first intermediate filling rate among at least one or more intermediate filling rates and predicts a hydrogen filling control sequence to reach the next intermediate filling rate, a second intermediate filling rate.

[0025] The artificial neural network can receive an input of a first intermediate fill rate using a model predictive control technique and generate a series of future predictions of a hydrogen filling control sequence to reach a second intermediate fill rate.

[0026] The step of providing a hydrogen filling control sequence for reaching the target filling rate may provide the hydrogen filling control sequence based on field data in which the relationship between the hydrogen filling control command and the change in filling rate during the process of reaching the target filling rate from the starting filling rate is recorded.

[0027] A user-driven setting-based hydrogen filling method according to one embodiment of the present invention may further include a step of acquiring progress data of the hydrogen filling process between the dispenser that supplies hydrogen to the mobility and the mobility through two-way communication during the hydrogen filling process from the starting filling rate to the target filling rate, and a step of monitoring the hydrogen filling process based on the comparison result between the predicted data for reaching the target filling rate from the starting filling rate and the progress data.

[0028] The user-initiated setting-based hydrogen filling method according to an embodiment of the present invention may further include identifying whether the mobility can receive hydrogen supply through communication with the mobility.

[0029] A user-driven setting-based hydrogen filling method according to one embodiment of the present invention may further include a step of obtaining a target filling rate through communication with a mobility, and a step of providing predicted data of a hydrogen filling control sequence for reaching the target filling rate to the mobility.

[0030] In a user-driven setting-based hydrogen filling method according to one embodiment of the present invention, if the user input includes changes related to the hydrogen filling target setting, the step of determining the target filling rate may determine a new target filling rate that has been changed based on the changes.

[0031] A user-driven setting-based hydrogen filling method according to one embodiment of the present invention may further include providing the mobility with prediction data of a modified hydrogen filling control sequence for reaching a new target filling rate through communication with the mobility.

[0032] The hydrogen-fueling device installed in a hydrogen-fueled mobility according to one embodiment of the present invention is a user-driven configuration-based hydrogen-fueling device, and may include a memory that stores at least one instruction, and a processor that executes at least one instruction.

[0033] At this time, the processor can receive user input related to setting a hydrogen filling target through at least one instruction, determine a target state of charge (SOC) for hydrogen filling of the mobility based on the user input, and receive hydrogen supply through a hydrogen filling control sequence to reach the target state of charge.

[0034] At this time, the user input may include a target filling rate for hydrogen filling of the mobility.

[0035] The processor may determine the target fill rate based on user input and at least one of a current fill state of the mobility and fill-related status information of the mobility.

[0036] The processor can acquire progress data of the hydrogen filling process of the mobility during the hydrogen filling process between the start filling rate and the target filling rate.

[0037] The processor may transmit the mobility progress data to a dispenser or filling control system that supplies hydrogen to the mobility so that the mobility progress data may be monitored.

[0038] The processor can generate a hydrogen filling control request for at least one intermediate filling rate between the starting filling rate and the target filling rate of hydrogen filling.

[0039] A user-driven configuration-based hydrogen filling dispenser device according to one embodiment of the present invention is a dispenser device for filling hydrogen into hydrogen-fueled mobility, and may include a memory for storing at least one or more instructions and a processor for executing at least one or more instructions.

[0040] The processor, with at least one instruction, can receive user input related to setting a hydrogen filling target, determine a target state of charge (SOC) for hydrogen filling of the mobility based on the user input, and provide a hydrogen filling control sequence to reach the target state of charge.

[0041] The processor can acquire progress data of the hydrogen filling process of the mobility and the dispenser that supplies hydrogen to the mobility through two-way communication during the hydrogen filling process from the start filling rate to the target filling rate.

[0042] The processor can monitor the hydrogen filling process based on a comparison between the predicted data and the progress data from the starting fill rate to the target fill rate.

[0043] A user-driven setting-based hydrogen filling protocol identification method according to one embodiment of the present invention may include a step of identifying a filling protocol supported between a dispenser that fills hydrogen into a mobility and the mobility through communication between the dispenser and the mobility, and a step of determining whether the identified filling protocol is a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility.

[0044] A user-driven setting-based hydrogen filling protocol negotiation method according to one embodiment of the present invention may include a step of identifying at least one filling protocol supported between a dispenser that fills hydrogen into a mobility and the mobility through communication between the dispenser and the mobility, and a step of selecting and negotiating as a preferred filling protocol a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility from among the at least one filling protocol identified through communication between the dispenser that fills hydrogen into the mobility and the mobility. [Effects of the Invention]

[0045] According to one embodiment of the present invention, a user-requested filling amount setting function can be provided. According to one embodiment of the present invention, processes and protocols can be implemented to support a user initiated fill volume setting function. According to an embodiment of the present invention, it is possible to determine an appropriate filling amount and implement a hydrogen filling / supply process according to the surrounding circumstances and conditions during filling. According to one embodiment of the present invention, a two-way communication protocol can be implemented to support user-initiated filling amount setting and hydrogen filling / supply process. [Brief explanation of the drawings]

[0046] [Figure 1] 1 is a conceptual diagram illustrating an example of a hydrogen filling process for a hydrogen fueled mobility / vehicle to which an embodiment of the present invention is applied. [Figure 2] 1 is a conceptual diagram illustrating an example of a state change that occurs during a hydrogen filling process for a hydrogen vehicle / hydrogen mobility to which an embodiment of the present invention is applied. [Figure 3] FIG. 1 is a conceptual diagram illustrating a hydrogen filling process platform or test platform according to one embodiment of the present invention. [Figure 4] FIG. 4 is a block diagram illustrating in detail a portion of the configuration of FIG. 3. [Figure 5] FIG. 1 is a conceptual diagram illustrating a hydrogen filling process platform or test platform according to one embodiment of the present invention. [Figure 6] FIG. 10 is a conceptual diagram illustrating a hydrogen filling process platform or test platform according to another embodiment of the present invention. [Figure 7] 2 is an operational flowchart illustrating a user-initiated setting-based hydrogen filling method according to an embodiment of the present invention. [Figure 8] 1A-1C are conceptual diagrams illustrating various embodiments of a user-driven configuration-based hydrogen filling process. [Figure 9] 1A-1C are conceptual diagrams illustrating various embodiments of user-driven configuration-based hydrogen filling processes and control methods. [Figure 10]1 is a conceptual diagram illustrating the concept of an artificial neural network (ANN) for hydrogen filling control for a hydrogen vehicle according to one embodiment of the present invention. [Figure 11] 1 is a conceptual diagram illustrating the concept of model predictive control for hydrogen filling control for a hydrogen vehicle according to one embodiment of the present invention. [Figure 12] 1 is an operational flowchart illustrating a training process of an artificial neural network for hydrogen filling control according to one embodiment of the present invention. [Figure 13] 1 is a conceptual diagram illustrating a two-way communication protocol for a user-driven configuration-based hydrogen filling process according to one embodiment of the present invention. [Figure 14] FIG. 2 is a conceptual diagram illustrating a communication protocol and operational flow chart for a user-driven configuration-based hydrogen filling process according to one embodiment of the present invention. [Figure 15] 15 is a conceptual diagram illustrating an example of a generalized hydrogen filling control device, hydrogen filling control system, hydrogen filling test platform, hydrogen filling test system, or computing system capable of performing at least a portion of the processes of FIGS. 1 to 14. DETAILED DESCRIPTION OF THE INVENTION

[0047] The present invention can be modified in various ways and can have various embodiments, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to the specific embodiments, and it should be understood that the present invention includes all modifications, equivalents, and alternatives that fall within the spirit and technical scope of the present invention. In the description of each drawing, similar reference numerals are used to refer to similar components. Terms such as "first," "second," "A," and "B" may be used to describe various components, but the components should not be limited by these terms. These terms are used only to distinguish one component from another. For example, a first component may be designated as a second component, and similarly, a second component may be designated as a first component, without departing from the scope of the present invention. The term "and / or" includes a combination of multiple associated listed items or any of multiple associated listed items.

[0048] In the examples of this application, "at least one of A and B" may mean "at least one of A or B" or "at least one of a combination of one or more of A and B." Also, in the examples of this application, "one or more of A and B" may mean "one or more of A or B" or "one or more of a combination of one or more of A and B." When a component is said to be "coupled" or "connected" to another component, it should be understood that it may be directly coupled or connected to the other component, but that there may be other components in between. Conversely, when a component is said to be "directly coupled" or "directly connected" to another component, it should be understood that there are no other components in between.

[0049] The terms used in this application are merely used to describe specific embodiments and are not intended to limit the present invention. The singular expressions include the plural expressions unless the context clearly dictates otherwise. In this application, the terms "comprise" or "have" are intended to specify the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, and should be understood not to preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0050] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which this invention pertains. Terms as defined in commonly used dictionaries should be interpreted to have a meaning consistent with the meaning they have in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense unless expressly defined in this application.

[0051] Some terms used in this specification are defined as follows: Hydrogen vehicles generally include not only hydrogen electric vehicles or hydrogen fuel cell electric vehicles (FCEVs) that use fuel cells, but also all ICE (Internal Combustion Engine)-based vehicles that use hydrogen as fuel.

[0052] The hydrogen fluid fuel may include gaseous hydrogen fuel or liquid hydrogen fuel. A Compressed Hydrogen Storage System (CHSS) is a device that compresses and stores hydrogen as part of a vehicle.

[0053] A pressure relief device (PRD) is a device placed in a CHSS that can isolate stored hydrogen from the rest of the fuel system and the environment, or conversely, can release hydrogen to the outside.

[0054] The hydrogen fueling process refers to the process of transferring high-pressure hydrogen from a hydrogen filling station and storing it in a hydrogen tank. The pressure ramp rate (PRR) is expressed in MPa / min and refers to the rate at which the pressure of the CHSS increases. Average Pressure Ramp Rate (APRR) refers to the average value of the pressure ramp rate from the start to the end of hydrogen fueling.

[0055] Pre-cooling refers to the process of cooling hydrogen at a hydrogen filling station before filling it. The dispenser is the component that delivers pre-cooled hydrogen to the CHSS. A nozzle is a device that is connected to the hydrogen dispensing system of a hydrogen filling station and is coupled to a receptacle of a hydrogen electric vehicle to allow the delivery of hydrogen fuel.

[0056] However, even technologies that were publicly known prior to the filing date of this application may be included as part of the present invention, as necessary, and will be described herein to the extent that the gist of the present invention is not obscured. However, in describing the gist of the present invention, detailed descriptions of technologies that were publicly known prior to the filing date and that would be obvious to those skilled in the art will be omitted because such detailed descriptions may obscure the gist of the present invention. For example, technologies that utilize a thermodynamic model for hydrogen filling control, technologies that apply model prediction control (MPC) techniques for generalized dynamic control, and technologies that configure and control an artificial neural network for training and inference of the artificial neural network may utilize technologies that were publicly known prior to the filing of this application, and at least some of these publicly known technologies may be applied as elemental technologies necessary to implement the present invention.

[0057] However, the gist of the present invention is not to claim rights over these known techniques, and the content of known techniques may be included as part of the present invention within the scope of the present invention.

[0058] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. FIG. 1 is a conceptual diagram illustrating an example of a hydrogen filling process for a hydrogen fueled mobility / vehicle to which an embodiment of the present invention is applied.

[0059] Referring to Figure 1, pre-cooled hydrogen gas from a hydrogen filling station (200) is supplied to a hydrogen fueled mobility vehicle (300) via a dispenser 100. The hydrogen filling process can be described by parameters including the mean pressure rise rate (APRR).

[0060] Generally, hydrogen storage systems attached to vehicles can be broadly divided into a high-pressure hydrogen tank, a pressure control mechanism, high-pressure piping, and an external frame. High-pressure hydrogen tanks have been developed and commercialized with capacities of tens or hundreds of liters, and for vehicles, small and lightweight storage tanks are connected in parallel to achieve high capacities.

[0061] High-pressure hydrogen tanks are commonly known as compressed hydrogen storage systems (CHSS) 310, and for the sake of convenience in this specification, the term "tank" refers to a CHSS 310.

[0062] In a typical hydrogen storage system, hydrogen storage is controlled by using a boss unit that allows hydrogen gas to enter and exit the CHSS310. Since hydrogen cannot be injected and used simultaneously, hydrogen storage is controlled by attaching a valve, pressure reducing mechanism, and various measurement sensors to one boss unit.

[0063] The interface between the hydrogen filling station 200 and the hydrogen-fueled mobility 300 is handled by the dispenser 100, which combines vehicle storage tank information and fuel supply information from the hydrogen filling station 200 to control the target pressure, injection rate, etc. An example of the control logic currently used is control logic that complies with the SAE J2601 (2020-05) standard.

[0064] In the prior art, there are two methods for transmitting information from the hydrogen fuel mobility 300 to the dispenser 100: a communication method and a non-communication method. Even when communication is used, in the prior art, the temperature and pressure values ​​of the CHSS 310 are simply transmitted unidirectionally to the dispenser 100, and the dispenser 100 does not actively use the information, but simply uses it as a safety standard such as an emergency stop at the limit temperature and pressure.

[0065] All filling logic for safe and fast filling is managed by the dispenser 100, and the CHSS 310 has only a minimum safety control device that automatically releases hydrogen under conditions such as overheating through the pressure relief device (PRD) 320 without any active safety control method.

[0066] 2, the hydrogen filling station 200 includes a high-pressure hydrogen storage unit 220 and a pre-cooler 210 to deal with the phenomenon of the temperature of hydrogen gas rising during hydrogen filling, which will be described later. The pre-cooler 210 pre-cools the hydrogen gas to a low temperature, and supplies the hydrogen gas to the hydrogen electric vehicle 300 via the dispenser 100.

[0067] In one embodiment of the present invention, a basic configuration similar to that of the prior art is used, but the filling control logic 110 inside the dispenser 100 actively controls the hydrogen fueling process by utilizing status information such as temperature and pressure received from the hydrogen fuel mobility 300 and the hydrogen filling station 200, and filling status information such as the filling rate (SOC, State of Charge) of the CHSS 310.

[0068] According to one embodiment of the present invention, the filling speed is controlled in real time using real-time temperature data from the CHSS 310. It is designed to operate at the highest filling speed that satisfies the conditions below the safety limit, and can reduce the filling time within the usable range.

[0069] The conventional filling protocol has excessive boundary conditions set for safety, which means that the temperature of most CHSS310 is measured at around 40-50°C at the end of filling, resulting in the problem of excessive pre-cooling before supply. According to one embodiment of the present invention, the cooling load of the hydrogen filling station 200 can be optimized by actively adjusting the pre-cooling demand and supply, thereby increasing the operational efficiency of the hydrogen filling station 200.

[0070] Conventional protocols, which are designed for lightweight hydrogen electric vehicles, have the problem that when a new mobility vehicle is filled, all variables must be reset and reflected to the standard.

[0071] According to one embodiment of the present invention, a control technique is used in which the ANN-based learnable filling logic updates the logic itself through a certain learning and training process when applied to new devices, and can be widely expanded to various mobility areas.

[0072] The only measure to prevent overheating of the storage tank of a conventional hydrogen electric vehicle is to release gas through a pressure relief device (PRD) 320 when the tank overheats above a certain temperature.

[0073] According to one embodiment of the present invention, the CHSS 310 itself is provided with a cooling system 330 (described later) to increase the filling speed and actively deal with overheating of the CHSS 310, thereby improving the safety of the hydrogen-fueled mobility 300.

[0074] According to one embodiment of the present invention, it is possible to safely fill / supply hydrogen fuel while improving the efficiency of the hydrogen filling / supply process, thereby improving the speed and real-timeness of the hydrogen filling / supply process. According to one embodiment of the present invention, a hydrogen filling control technique that ensures real-time performance based on model predictive control (MPC) can be provided. According to one embodiment of the present invention, a control technique that improves the accuracy of hydrogen filling result prediction based on an artificial neural network (ANN) model can be provided. The accuracy of the prediction result can be improved by incorporating real-time measurements into an ANN model that uses actual filling data along with theoretical simulation results.

[0075] According to one embodiment of the present invention, the efficiency of hydrogen filling control can be improved by using an intelligent meta-system (IMS) to integrate and manage actually measured data and state information predicted from a model.

[0076] As mentioned above, in the conventional hydrogen filling process, the dispenser 100 is responsible for control between the hydrogen-fueled mobility 300 and the hydrogen filling station 200, and the dispenser 100 is equipped with a protocol that is a method for injecting hydrogen into the hydrogen-fueled mobility 300 in accordance with established regulations, and this protocol is used to oversee the control.

[0077] An example of a protocol that can be installed in the dispenser 100 is a protocol based on the international standard SAE-J2601 (2020-05), which also applies to embodiments of the present invention within the scope consistent with the purpose of the present invention.

[0078] Simulations are carried out through thermodynamic modeling for various situations to meet minimum safety requirements, and the parameters derived through this are used to implement a table-based single injection method and an MC-formula-based partial real-time correction method. Minimum safety requirements include upper limits for temperature and pressure conditions for CHSS310 and guidelines for State of Charge (SOC).

[0079] The simulation can be performed through thermodynamic modeling using boundary conditions including best and worst cases. Such a configuration can be applied to the configuration of the embodiment of the present invention within the scope consistent with the object of the present invention.

[0080] 1, the following problems are found in the prior art in which the state value is not actively controlled by the dispenser 100. The following problems also appear in the prior art that relies on simulations using a simple thermodynamic model.

[0081] Because the injection rate is predetermined assuming the worst possible boundary conditions (excessive boundary conditions), unnecessary pre-cooling occurs, resulting in a decrease in the overall filling rate. In this case, in conventional technology, the injection rate is simply determined by the average pressure ramp rate (APRR), which can hinder active response according to the situation. Unnecessary pre-cooling can lead to excessive energy and operating costs.

[0082] Since it depends on the results of the simulation platform, there are limitations on the capacity and form of applicable CHSS310, and in the case of new systems, there are problems such as requiring additional resources for new development and application, which limits the scope of application. Thermodynamic models require a lot of time to derive the results of mathematical calculations, and are a method that indirectly utilizes variables derived through the model. This means that their application is limited when there are no pre-calculated variables, and they lack flexibility in terms of detailed adjustments to the method itself.

[0083] The conventional table-based method is extremely inefficient because it does not utilize the temperature of pre-cooled hydrogen provided at the hydrogen filling station 200 or the temperature of the CHSS 310 measured by the hydrogen fuel mobility 300, and has the problem of being difficult to flexibly respond to changes in the surrounding conditions. The conventional MC-Formula-based method corrects the pre-cooling temperature in real time, but the calculation and application method are complicated and there are limitations on the objects that can be applied, making it difficult to expand.

[0084] Because the protocol was developed with the primary goal of completing the safe filling, there was no alternative way to actively control unexpected situations such as excessive pre-cooling or overheating of CHSS310. This resulted in problems such as increased operating costs due to overcooling and filling delays due to overheating.

[0085] The present invention has been developed to solve the problems of the prior art, and is characterized by reducing the dependency on simulation and attempting to actively control state variables by reflecting real-time measurement data.

[0086] FIG. 2 is a conceptual diagram illustrating an example of state changes that occur during a hydrogen filling process for a hydrogen-fueled mobility 300 to which an embodiment of the present invention is applied. Referring to FIG. 2, when hydrogen is injected into the CHSS 310, the internal temperature rises due to the heat of compression, which causes the temperature of the hydrogen gas inside the CHSS 310 to rise.

[0087] Temperature control during the hydrogen filling process is achieved by receiving pre-cooled hydrogen gas and controlling the internal temperature of the CHSS310 to be 85°C or less at the time of final filling completion. The CHSS310 is designed to have low heat transfer efficiency through the carbon fiber that surrounds the dome and body of the CHSS310, in order to block heat exchange between the outside atmosphere and the hydrogen gas stored inside while driving.

[0088] When the temperature of the hydrogen gas inside the CHSS 310 rises during the filling process, the temperature rise on the surface of the CHSS 310 is weak compared to the internal temperature rise until the filling is completed due to the low heat transfer characteristics of the CHSS 310.

[0089] These characteristics prevent heat exchange with the outside air, which can mitigate the rapid temperature rise inside CHSS310 that occurs during filling, so a separate temperature control measure is required. However, the prior art does not include any separate cooling means other than receiving pre-cooled hydrogen gas from the hydrogen filling station 200.

[0090] The hydrogen buffer time is managed by pre-cooling the vehicle hydrogen storage tank at the hydrogen filling station 200 and controlling the hydrogen injection rate to maintain the temperature below 85°C, which is the upper limit of temperature management for the vehicle hydrogen storage tank. However, there are currently no separate temperature management measures for the CHSS 310 of the hydrogen fuel mobility 300. As a result, especially in summer when the outside air temperature is high, it is difficult to control the temperature of the CHSS 310 at the hydrogen filling station 200, causing problems such as filling delays.

[0091] In an embodiment of the present invention, the characteristic curve of Figure 2 is used as a basic model, but unlike conventional technology, real-time data based on variables that appear in the actual surrounding environment (outside air temperature, air pressure, weather conditions, etc.) is taken into consideration to optimize the operating load of the hydrogen filling station 200 in the Phase I pre-cooling stage and the filling rate (pressure rise rate, PRR) control that occurs during the filling process from Phase II to Phase IV, thereby deriving optimal control conditions that are suited to the actual environment.

[0092] Figure 3 is a conceptual diagram illustrating a hydrogen filling process platform or test platform according to one embodiment of the present invention. Referring to Figure 3, an embodiment is shown in which a mobility part 300, a hydrogen filling station 200, and a dispenser part 100 are all simulation models. While a simulation model-centered embodiment is illustrated in Figure 3, the concept of the present invention is not limited to the embodiment of Figure 3. The mobility part 300, the filling station part 200, and the dispenser part 100 may be embodied by merging, combining, or competing between a simulation model and a data-based model based on real-time on-site dynamic data.

[0093] FIG. 4 is a block diagram illustrating in detail a portion of the configuration of FIG. Referring to both Figures 3 and 4, when a pre-cooling target temperature is provided to the filling station part 200 as a control request and / or feedback control in the dispenser part 100, temperature and pressure data can be output and transmitted to the artificial neural network model 120 through simulation or field data acquisition that takes the pre-cooler 210 into account.

[0094] In addition, when a temperature drop signal for the temperature of the CHSS 310 is provided to the mobility part 300 as a control request from the dispenser part 100, temperature and pressure data can be output by simulation considering the cooling system 330 or by acquiring on-site data and transmitted to the artificial neural network model 120. In this case, the mobility part 300 can regard the temperature drop signal as a kind of cooling load (CL).

[0095] Referring to FIG. 4, within the dispenser part 100, the output predicted by the artificial neural network model 120 is transmitted to the charging control system 130, and the charging control system 130 can transmit a pre-cooling target temperature to the filling station part 200 as a control request and / or feedback control, or can transmit a temperature drop signal of the CHSS 310 to the mobility part 300 as a control request.

[0096] In this case, the charging control system 130 of Fig. 4 can function as a kind of controller that controls the hydrogen filling test process. For convenience of explanation, an embodiment in which the charging control system 130 of Fig. 4 is independent hardware or software installed in the dispenser 100 is illustrated, but in other embodiments of the present invention, the charging control system 130 that performs the controller function may be embodied in the form of a cloud and / or a remote server.

[0097] Furthermore, although embodiments centered on the artificial neural network model 120 have been illustrated in this specification, other embodiments of the present invention need not be limited by the artificial neural network model 120 or model predictive control techniques. In other embodiments of the present invention, after hydrogen filling control-related information and / or feedback control based on a hydrogen filling protocol is transmitted, real-time on-site data may be fed back in response, and the hydrogen filling control-related information and / or feedback control may be updated or the next hydrogen filling control-related information and / or feedback control may be generated based on the real-time on-site data. According to another embodiment of the present invention, a test method and test platform for testing a hydrogen filling protocol and a hydrogen filling system that do not rely on model predictive control or an artificial neural network model 120 may also be proposed.

[0098] A plurality of hydrogen storage cylinders may be installed in the hydrogen filling station 200 and operated as a bank system. The real-time on-site information that the dispenser 100 requests and receives as feedback from the hydrogen filling station 200 may include temperature and pressure information for each bank. The multiple banks can be switched and connected to the dispenser 100 at the request of the dispenser 100 and / or at the selection of the hydrogen filling station 200. In this case, the bank-specific temperature and pressure information included in the real-time on-site information that the dispenser 100 requests and receives as feedback from the hydrogen filling station 200 can affect the bank selection and / or switching.

[0099] At this time, the dispenser 100 may adjust the state of at least one bank in the bank system based on bank-specific temperature and pressure information included in real-time on-site information that is requested and fed back from the hydrogen filling station 200.

[0100] For example, as a preparation step, at least one of the banks may be adjusted to have a temperature and pressure suitable for filling based on current status information for the banks in the hydrogen filling station 200. Such adjustment may be performed at the request of the dispenser 100 or by the control logic of the hydrogen filling station 200.

[0101] FIG. 5 is a conceptual diagram illustrating a hydrogen filling process platform or test platform according to one embodiment of the present invention. 5, a communication interface (module C) 160 may be provided between the dispenser part 100 and the mobility part 300, allowing two-way communication. Also, a communication interface (module B) 150 may be provided between the dispenser part 100 and the filling station part 200, allowing two-way communication.

[0102] When the filling station part 200 functions as a simulation model, the mobility part 300 can function as a modulation and optimization means for the temperature of the CHSS 310. When the mobility part 300 functions as a simulation model, the filling station part 200 can function as a means for stabilizing and controlling the pre-cooling temperature.

[0103] FIG. 6 is a schematic diagram illustrating a hydrogen filling process platform or test platform according to another embodiment of the present invention. 5 and 6, the charging control system 130 of FIG. 6 can function as a kind of controller that controls the hydrogen filling test process.

[0104] The predicted output of the artificial neural network model 120 may be transmitted to the charging control system 130. The charging control system 130 may transmit a control request for the state of hydrogen in the vehicle tank of the hydrogen vehicle 300 to the hydrogen vehicle 300 via the communication interface (module C) 160. The control request for the state of hydrogen in the vehicle tank of the hydrogen vehicle 300 may be a request to reduce the temperature of the hydrogen in the vehicle tank. Such a temperature reduction control request may be provided as a temperature reduction signal.

[0105] The charging control system 130 can transmit a control request for the state of hydrogen supplied from the hydrogen filling station 200 to the dispenser 100 via the communication interface (module B) 150 to the hydrogen filling station 200. The control request for the state of hydrogen supplied from the hydrogen filling station 200 to the dispenser 100 can be a pre-cooling request. The pre-cooling request can include a pre-cooling target temperature.

[0106] The charging control system 130 can transmit, via the communication interface (module A) 140, information related to a control command / request for the hydrogen filling process in which hydrogen is supplied from the hydrogen filling station 200 to the vehicle tank of the hydrogen vehicle 300 via the dispenser 100, and hydrogen filling control-related information as dispenser 100 status information reflecting the result of the dispenser 100 performing the control command / request for the hydrogen filling process. At this time, the hydrogen filling control-related information can include at least one of information on a control command for a pressure ramp rate (PRR) for filling hydrogen into the vehicle tank and status information on the dispenser 100 as a result of the execution of the control command. In addition, the hydrogen filling control-related information can include at least one of information on variables that may affect the state change of hydrogen in the vehicle tank of the hydrogen vehicle 300, such as the real-time pressure ramp rate (PRR) or the mass flow rate of compressed hydrogen (kg / s) (m_dot) derived during the feedback control process, and information on the result of the execution of control based on the variable. These hydrogen filling control related information may also influence the weights or parameters of the hidden layers of the artificial neural network model 120 .

[0107] A thermodynamic model such as H2FillS (Hydrogen Filling Simulation) can be used as the theoretical simulation. The thermodynamic model can include a model and / or software designed to track and report transient changes in at least one of hydrogen temperature, pressure, and mass flow and / or transient changes in the state of hydrogen in the vehicle tank when filling a hydrogen fueled vehicle / mobility with hydrogen. Of course, the concept of the present invention is not limited to the implementation of a specific thermodynamic model.

[0108] The hydrogen filling protocol may include, for example, the hydrogen filling protocol defined in SAE J2601. Of course, the concepts of the present invention are not limited to any particular embodiment.

[0109] The thermodynamic model can generate output data based on modeling and simulation when input data similar to that of an artificial neural network is input, and the variables of the thermodynamic model can be adjusted according to the hydrogen filling protocol, so that different output data can be derived for different hydrogen filling protocols for the same input data.

[0110] In one embodiment of the present invention, the artificial neural network may be trained by providing on-site data collected by a test platform as input data and output data of the artificial neural network instead of input / output data of a thermodynamic model. That is, a portion of the on-site data collected by the test platform may be provided as input data of the artificial neural network, and another portion may be provided as ground truth data corresponding to the output data of the artificial neural network.

[0111] The internal parameters of the artificial neural network may be trained without initialization, or may be initialized to predetermined values ​​and then trained based on field data. For example, the artificial neural network may be trained based on a thermodynamic model, with input and output data (ground truth data) being provided, and the internal parameters of the artificial neural network may be initialized. The learning of artificial neural networks does not necessarily have to be deep learning; it can also be shallow learning.

[0112] A test platform according to one embodiment of the present invention can rely on dynamic field data to optimize the hydrogen filling process. One embodiment of the present invention can predict the next state using an artificial neural network-based model predictive control (MPC) technique, where the artificial neural network model can be trained using theoretical results, on-site data, or both.

[0113] If the pre-cooling function of the hydrogen filling station 200 or the cooling system 330 of the vehicle 300 is not available, module A (140) can independently or independently perform the control process.

[0114] To analyze process state changes between the dispenser 100 and the hydrogen filling station 200, a learning model based on field data between the dispenser 100 and the vehicle 300 can serve as a reference for the process between the dispenser 100 and the vehicle 300.

[0115] Conversely, to analyze process state changes between the dispenser 100 and the vehicle 300, a learning model based on field data between the dispenser 100 and the hydrogen filling station 200 can serve as a reference for the process between the dispenser 100 and the hydrogen filling station 200.

[0116] Big data is collected for each type and individual ID of dispenser 100, type and individual ID of hydrogen filling station 200, type and individual ID of vehicle 300, control target state (temperature, pressure, SOC), initial state (temperature, pressure), and type of hydrogen filling protocol, and the test platform learns using the dynamic changes in on-site data corresponding to each case, thereby deriving standardized items that can optimize and accurately describe the hydrogen filling process.

[0117] A hydrogen filling test system according to one embodiment of the present invention is a hydrogen fueling test system for a hydrogen fueled vehicle, and includes a communication interface (module A, 140) that transmits hydrogen filling control-related information affecting the state of hydrogen in the vehicle tank of the hydrogen fueled mobility 300 to the hydrogen fueled mobility 300 and receives on-site data on changes in the state of hydrogen in the vehicle tank as feedback corresponding to the hydrogen filling control-related information; and a charging control system 130 or controller that updates a model for the hydrogen filling process for the hydrogen fueled mobility 300 corresponding to the hydrogen filling control-related information based on the on-site data on changes in the state of hydrogen in the vehicle tank corresponding to the hydrogen filling control-related information.

[0118] The charging control system 130 may include a controller function. In this specification, the term "controller" may refer to a configuration corresponding to the controller function of the charging control system 130. An operation by the controller may refer to an operation performed by the controller function of the charging control system 130.

[0119] The charging control system 130 or the controller can obtain the difference between the simulation result for the change in the state of hydrogen in the vehicle tank corresponding to the hydrogen filling control related information and the field data for the change in the state of hydrogen in the vehicle tank.

[0120] The charging control system 130 or controller can update the model 120 for the hydrogen filling process for hydrogen vehicles corresponding to the hydrogen filling control related information based on the difference between the simulation results and the field data. The charging control system 130 or controller can obtain simulation results for changes in the state of hydrogen in the vehicle tank corresponding to control requests by using a thermodynamic model that tracks transient changes in at least one of the temperature, pressure, and mass flow of hydrogen in the vehicle tank.

[0121] The charging control system 130 or controller can obtain simulation results for changes in the state of hydrogen in the vehicle tank corresponding to the hydrogen filling control request using a model predictive control (MPC) technique by inputting future predicted hydrogen filling control requests into a model for the hydrogen filling process.

[0122] The model 120 for the hydrogen filling process corresponding to the hydrogen filling control related information may be a model trained to predict changes in the state of hydrogen in the vehicle tank upon input of hydrogen filling control related information related to the result of executing a hydrogen filling control request and information on the state of hydrogen in the vehicle tank.

[0123] In this case, the model 120 for the hydrogen filling process corresponding to the hydrogen filling control related information may be a model trained to predict future changes in the state of hydrogen in the vehicle tank based on input of the hydrogen filling control related information, the current state of hydrogen in the vehicle tank, the state of hydrogen being supplied to the vehicle by the dispenser, and the ambient temperature.

[0124] The model 120 for the hydrogen filling process corresponding to the hydrogen filling control-related information may be a model trained to predict the target state of the hydrogen state in the vehicle tank targeted by the hydrogen filling control-related information and the change in the state of hydrogen in the vehicle tank due to each hydrogen filling protocol.

[0125] The model 120 may be an artificial neural network model. The charging control system 130 or the controller may receive hydrogen filling control-related information and hydrogen state information in the vehicle tank as input, and may update parameters in the model 120 by training a function to predict changes in the state of hydrogen in the vehicle tank using field data on changes in the state of hydrogen in the vehicle tank as ground truth data.

[0126] The model 120 may be a model trained to predict changes in the state of hydrogen in a vehicle tank using a model predictive control technique.

[0127] After updating the model 120, the charging control system 130 or the controller can replace the hydrogen-fueled mobility 300 side with the model 120 and acquire at least one of simulation data and on-site data of the change in the state of hydrogen supplied from the hydrogen filling station 200 to the dispenser 100 corresponding to a second control request between the dispenser 100 that supplies hydrogen to the hydrogen-fueled mobility 300 and the hydrogen filling station 200 that supplies hydrogen to the dispenser 100.

[0128] After updating the model 120, the charging control system 130 or the controller can use the model 120 to replace the hydrogen filling station 200 and acquire at least one of simulation data and on-site data of the change in the state of hydrogen in the vehicle tank of the hydrogen-fueled mobility 300 that receives hydrogen from the dispenser 100 and corresponds to the third control request between the dispenser 100.

[0129] The charging control system 130 or the controller can identify whether the hydrogen-fueled mobility 300 is actively controlling changes in the state of hydrogen in the vehicle tank in response to hydrogen filling control-related information or a control request for a change in the state of hydrogen via the communication interface (module A, 140). At this time, through communication between the hydrogen-fueled mobility 300 and the dispenser 100 and / or the hydrogen filling station 200, the communication protocol and control protocol that the hydrogen vehicle 300 can support and the communication protocol and control protocol that the dispenser 100 can support are mutually shared, and the commonly supported protocols can be selected as the communication protocol and control protocol.

[0130] The hydrogen filling control request based on the hydrogen filling protocol may include a control command for the pressure ramp rate (PRR) for filling hydrogen in the vehicle tank. The hydrogen filling control-related information may include at least one of information on a hydrogen filling control request and status information based on the execution result of the hydrogen filling control request, and the control request for a change in the hydrogen status may include a control request for at least one of the temperature and pressure of the hydrogen in the vehicle tank.

[0131] The state changes of the hydrogen in the vehicle tank may include at least one of temperature, pressure, and state of charge (SOC).

[0132] Conventional hydrogen filling processes or hydrogen filling control techniques have the problem of difficulty in controlling the final SOC, the temperature / pressure of the final nozzle, and the CHSS 310 as targeted. Additionally, due to pressure variability, unstable flow rates, and high environmental variability, theoretical simulation-based hydrogen filling techniques do not match actual field data.

[0133] Discrepancies between simulation results and actual field data are easily influenced by device characteristics and environmental variations that are difficult to fully consider in theoretical simulations. Even when the same hydrogen filling protocol is used, the final field data may vary depending on the initial values ​​and final target values. Conversely, even when the same final target values ​​and initial values ​​are assumed, the final field data may vary depending on different hydrogen filling protocols.

[0134] To solve these problems of the prior art, one embodiment of the present invention can utilize real-time on-site data, two-way communication between devices, predictive control techniques, integrated control of the entire system including stations and vehicles, and utilization and standardization of hydrogen filling data based on user requirements.

[0135] When a hydrogen filling process is tested, the filling protocol to be tested may be internal to the charging control system 130 or may be external to the charging control system 130 . Additionally, an embodiment of the present invention may enable enhancement of existing hydrogen fueling protocols, standardization of on-site fueling data formats, and compilation and diagnosis of dynamic field data.

[0136] In relation to enhancing existing hydrogen filling protocols, one embodiment of the present invention may include the following. An existing hydrogen filling protocol can be selected for testing.

[0137] In one embodiment of the present invention, an artificial neural network-based model predictive control (ANN-MPC) is implemented to run an existing hydrogen filling protocol under the same filling conditions, and the results of filling control using the ANN-MPC are compared with the results of filling control using the existing hydrogen filling protocol, thereby enabling the existing hydrogen filling protocol to be strengthened or improved.

[0138] The charging control system 130 can have a protocol 131 to be tested embedded therein, can request charging control based on the embedded protocol, and can compare the control value with the "predicted output" input from the ANN-MPC.

[0139] The charging control system 130 or controller can transmit hydrogen filling control related information to the hydrogen fueled mobility 300 via the communication interfaces 140, 160 by executing an existing hydrogen filling protocol, and can obtain on-site data on changes in the state of hydrogen in the vehicle tank via the communication interfaces 140, 160.

[0140] The charging control system 130 or controller can obtain the hydrogen filling control sequence according to the model 120 for the hydrogen filling process (if the ANN-MPC technique is used, future time series control sequence inputs can be predicted), and can enhance existing hydrogen filling protocols based on the hydrogen filling control sequence according to the model 120 for the hydrogen filling process.

[0141] The charging control system 130 or controller can obtain result data from the execution of the hydrogen filling control sequence according to a model for the hydrogen filling process, and can use the hydrogen filling control sequence to enhance part of the existing hydrogen filling protocol based on the comparison results between the result data from the execution of the hydrogen filling control sequence and field data from the existing hydrogen filling protocol.

[0142] In this case, the filling control results using the artificial neural network model 120 may be obtained by running the model 120 or may be obtained from a pre-built database. The basic specifications used in the testing filling protocol 131 remain unchanged, but the details, i.e., the filling table or logic, may be strengthened / improved by referring to the filling control values ​​of the artificial neural network model 120. In this case, the filling control results using the artificial neural network model 120 may be compared with field data obtained by executing the testing filling protocol 131, and if the performance of the filling control results using the artificial neural network model 120 is superior, the details of the testing filling protocol 131 may be partially improved. The comparison between the filling control results and the execution results of the testing filling protocol 131 may also be made for the entire hydrogen filling process or a part of it.

[0143] In one embodiment of the present invention, a Lumped Thermodynamic Model for Artificial Neural Networks for Dispenser-Vehicle Interaction may be utilized taking into account the following characteristics:

[0144] -0-Dimensional Unsteady State Mass & Energy Balance -1-Dimensional Heat Transfer for Vehicle Tank Wall -CoolProp for Evaluation of Hydrogen Properties

[0145] One embodiment of the present invention can perform comparative analysis between theoretical simulation results and real on-site data. An embodiment of the present invention can perform predictive analysis under specific conditions in addition to the conditions assumed in the hydrogen filling protocol. One embodiment of the present invention can improve the reliability of the hydrogen filling process by collecting and processing in-situ hydrogen filling data.

[0146] The on-site data of the change in the state of hydrogen in the vehicle tank can be acquired first on the vehicle side. That is, the on-site data of the change in the state of hydrogen in the vehicle tank can be acquired on the vehicle side regardless of whether the control request is transmitted to the hydrogen vehicle. Alternatively, in another embodiment of the present invention, the control request can include a on-site data request, and the on-site data can be acquired on the vehicle side in response to the control request / on-site data request.

[0147] Acquisition of on-site data can be performed not only by the vehicle but also by the filling station. Similarly, on-site data can be collected at the filling station regardless of a control request, and the control request may include a on-site data request, and the filling station may acquire on-site data regarding the status of the hydrogen stored at the filling station and / or the hydrogen supplied to the dispenser from the filling station in response to the control request / on-site data request.

[0148] On-site data refers to data obtained at the filling station and / or vehicle during the actual hydrogen filling / supply process. In this case, on-site data can include data obtained from an actual filling station and actual vehicle, as well as data obtained in a partial or full test environment.

[0149] The field data may include data obtained in a test environment or test environment configured with a device capable of reacting (feedback) on the hydrogen vehicle side, a test environment or device capable of reacting (feedback) on the hydrogen storage cylinder and dispenser side at a filling station, and / or a test environment or test environment configured with an execution device to which Module A on the dispensing control system side can be attached.

[0150] In this case, the field data may include data obtained at a filling site or test environment where all the devices are in the above three test environments or test environments configured with the devices, or where any one of the devices is included. For example, the field data may include data obtained at a test environment or filling site configured with a simulation model linked to modules B 150 and C 160 illustrated in FIG.

[0151] In this case, the reaction (feedback) capable device may refer to a device that includes a database built based on actual field data and can respond according to the case requested by module A. The field data can include static data and dynamic data, which can be classified into static data (e.g., vehicle tank type, vehicle tank volume, number of vehicle tank modules / banks) and dynamic data (e.g., vehicle tank hydrogen temperature, pressure).

[0152] FIG. 7 is an operational flowchart illustrating a user-driven setting-based hydrogen filling method according to one embodiment of the present invention. Referring to FIG. 7, a user-driven setting-based hydrogen filling method according to one embodiment of the present invention is a method of filling hydrogen into a mobility 300 that uses hydrogen as fuel, and may include a step of receiving user input related to hydrogen filling target setting (S410); a step of determining a target state of charge (SOC) for hydrogen filling of the mobility 300 based on the user input (S420); and a step of receiving a supply of hydrogen according to a hydrogen filling control sequence to reach the target state of charge (S430).

[0153] 7 (S410 to S430) is performed on the mobility 300 side. In this case, the mobility 300 side can be understood to refer to at least one of a control device (ECU or vehicle MCU) in the mobility 300, an electric vehicle communication controller (EVCC) in the mobility 300, or a controller of a filling system in the mobility 300.

[0154] In this case, in one embodiment of the present invention, the user input may include a target filling rate for hydrogen filling of the mobility. For example, the driver may determine the SOC directly through the interface of the mobility 300 or through a driving application program.

[0155] The step of determining the target charging rate (S420) may determine the target charging rate based on user input, based on at least one of the current charging state of the mobility 300 and charging-related status information of the mobility 300. For example, instead of the dispenser 100 or the charging control system 130, the mobility 300 may determine the final target SOC based on the charging rate or charging amount intended by the user.

[0156] A user-driven setting-based hydrogen filling method according to one embodiment of the present invention may further include a step of acquiring progress data of the hydrogen filling process of the mobility 300 during the hydrogen filling process between the starting filling rate and the target filling rate of the hydrogen filling, and a step of transmitting the progress data of the mobility 300 to the dispenser 100 that supplies hydrogen to the mobility 300 or the filling control system 130 so that the progress data of the mobility 300 can be monitored.

[0157] At this time, the dispenser 100 or the filling control system 130 can share data from the mobility 300 side for monitoring the filling process using real-time two-way communication with the mobility 300 side.

[0158] The step of receiving hydrogen supply according to the hydrogen filling control sequence to reach the target filling rate (S430) may include a step of generating a hydrogen filling control request for at least one intermediate filling rate between the starting filling rate of hydrogen filling and the target filling rate.

[0159] At this time, the mobility 300 can request filling (or request derivation of a filling protocol) based on the input / output relationship for each individual pressure between the filling start point and the end point.

[0160] 7 illustrates an embodiment of a method performed on the mobility 300 side, but each step of FIG. 7 may be understood to be equivalent to a method performed on the dispenser 100 side. In this case, in the method performed on the dispenser 100 side, the provider and receiver in each step of FIG. 7 may be changed to fit the purpose of the method performed on the dispenser 100.

[0161] In addition, operations performed in this specification on either the mobility 300 side or the dispenser 100 side may be performed on the opposite side of the mobility 300 side or the dispenser 100 side in other embodiments, or may be performed through mutual cooperation between the mobility 300 side and the dispenser 100 side.

[0162] Another embodiment of the user-driven setting-based hydrogen filling method of the present invention is a method performed on the dispenser 100 side that supplies hydrogen, unlike the embodiment of Figure 7, and can include steps of receiving user input related to setting a hydrogen filling target, determining a target state of charge (SOC) for hydrogen filling of a mobility based on the user input, and providing a hydrogen filling control sequence to reach the target state of charge.

[0163] In this case, the user input may include a target filling rate for hydrogen filling of the mobility. The user input may correspond to an input after the driver directly determines the SOC through the interface of the mobility 300 or a driving application program. In this case, the SOC based on the user input may be transmitted to the dispenser 100 via a wired / wireless communication network. In this case, the dispenser 100 may refer to at least one of the controller of the dispenser 100, the charging control system 130, and / or a device capable of electronic communication related to the dispenser 100.

[0164] The step of determining the target charging rate may determine the target charging rate based on user input, based on at least one of the current charging state of the mobility 300 and charging-related status information of the mobility 300. At this time, the dispenser 100 or the charging control system 130 may determine the final target SOC based on the user input.

[0165] In conventional technology, hydrogen filling is often carried out with the goal of full filling (100% SOC). However, in reality, full filling is physically difficult to achieve. In addition, the filling process can be difficult due to boundary condition issues inherent in the protocol itself. Problems with conventional technology include difficulty in accurately determining the SOC due to issues such as a lower SOC than the target value and a low final temperature at the end of filling.

[0166] Conventional standards have not allowed for the adjustment of the filling amount according to user requirements. However, there is an increasing demand for the determination of the filling amount for each user that matches the situation and user requirements due to differences in vehicle type, fees at each filling station, driving patterns by drivers, and distance traveled by operators.

[0167] For example, in the case of a personal car, the user may request daily / weekly / monthly mileage for each individual driver, the location / price of a filling station, and the amount of fuel to be filled according to personal preferences.

[0168] In the case of commercial vehicles such as buses and trucks, it is expected that the time required for filling at a garage will increase due to large-volume filling, so adjustment of the filling amount for each vehicle may be required. In this case, in the case of commercial vehicles, it may be necessary to adjust the filling amount profile depending on the vehicle's travel distance, travel time, and travel mode.

[0169] In terms of operation of the hydrogen filling station 200, proper filling rather than full filling may be advantageous for increasing efficiency. Standard filling of required amount can be applied relatively advantageously to fuel consumption and the life of major parts such as storage tanks.

[0170] The embodiment of the present invention can utilize the following improvement ideas to solve the problems of the prior art and to implement a fill control sequence based on a user-driven fill amount setting.

[0171] The filling amount can be determined under the user's initiative, and the hydrogen filling station 200 can be presented with the filling amount value set by the user. The information that must be determined by the user or transmitted to the hydrogen filling station 200 includes the amount (a fixed value), the quantity (a fixed kg), the target value (a fixed pressure, a fixed kg / m 2 ), and at least one of the determined filling amounts.

[0172] Example 1 When a driver determines and inputs a target filling amount in the vehicle or in a filling app, information related to the input filling amount can be transmitted to the dispenser 100 .

[0173] Example 2: When the user inputs the intended amount through a screen provided by the hydrogen filling station 200, the dispenser 100 or the system controlling the filling will determine the final planned amount to be filled based on the filling status of the mobility 300 and filling-related status information (including surrounding information such as ambient temperature), and can set a target value based on this.

[0174] At this time, whether or not to fill is determined through communication with the dispenser 100, and the filling target and progress status can be confirmed via the interface of the mobility 300.

[0175] In order to implement a user-driven filling amount setting based filling control sequence in an embodiment of the present invention, the following techniques may be required as a prerequisite. -Setting of filling targets and progress according to vehicle and individual conditions -Improved current protocol functionality for full filling criteria -Added function to convert SOC, CHSS hydrogen amount (kg), temperature / pressure relationship

[0176] FIG. 8 is a conceptual diagram illustrating various embodiments of a user-driven configuration-based hydrogen filling process. Referring to FIG. 8, the user-driven configuration-based hydrogen filling sequence of the present invention may include the following embodiments. Example A. Improving an existing filling protocol Example B. Novel Protocol Technology with User-Defined Fill Capacity Example C: Improving communication methods for real-time control

[0177] 8, when the mobility 300 enters the hydrogen filling station 200, a filling target and process selection process for each selected protocol may be performed. This step may correspond to steps S410 and S420 of FIG.

[0178] A pairing process and basic information confirmation process between the mobility 300 and the dispenser 100 may be performed (S520). Thereafter, the state of the mobility 300 (temperature T, pressure P, and other specific points) and the user's requirements for the mobility 300 can be grasped (S530). After step S530, an optimal or preferred protocol can be selected.

[0179] A user-specific preferred protocol can be selected, or an optimal protocol can be determined based on system suggestions. The filling rate setting method and process for each protocol may differ, and such conditions must be taken into consideration when selecting a preferred or optimal protocol.

[0180] After step S530, step S430 may be performed. In steps S530 and S430, embodiment C. real-time two-way communication may be used. Also, in step S430, for the control of the hydrogen filling process, Example A. Improvement of an existing protocol or Example B. Proposal of a new protocol may be utilized.

[0181] FIG. 9 is a conceptual diagram illustrating various embodiments of a user-driven configuration-based hydrogen filling process and control method. In embodiment (1) of Figure 9, at the stage of providing a hydrogen filling control sequence for reaching a target filling rate by the dispenser 100 or the charging control system 130, a target hydrogen filling control sequence corresponding to the target filling rate can be determined from a group of candidate hydrogen filling control sequences for reaching an individual target filling rate.

[0182] Example (1) of FIG. 9 is equivalent to Example B of FIG. 8. Filling efficiency can be improved through the development of a new protocol. In another embodiment of the present invention, in embodiment (2) of Figure 9, at the stage of providing a hydrogen filling control sequence for reaching a target filling rate by the dispenser 100 or the charging control system 130, the hydrogen filling control sequence for reaching the target filling rate can be predicted based on existing hydrogen filling data between the dispenser 100 that supplies hydrogen to the mobility 300 and the mobility 300.

[0183] Example (2) of Figure 9 is a method of controlling the filling process by utilizing predicted filling time based on existing data, and can be achieved through improvement of the existing protocol in Example A of Figure 8, and the achievable filling efficiency is expected to be lower than that of Example (1) of Figure 9.

[0184] In the graphs of Examples (1) and (2) of Figure 9, the slope of the pressure change itself is the filling rate, and the average filling rate APRR, the instantaneous filling rate PRR, etc. can be used for filling control. In both Examples (1) and (2) of Figure 9, a target value corresponding to the user-set filling amount within the limit criteria is set, and control parameters for filling can be determined in stages.

[0185] In the case of conventional protocols such as SAE J2601, which are recognized as prior art in the present invention, the relationship between the start and end points of filling is derived based on a simulation, and the filling process is controlled accordingly. In this case, it is difficult to instantly change the end point, and since the target speed is set based on a complete filling standard, there are problems with inefficiency when the target volume is reduced. Furthermore, it is practically impossible to specify individual speeds for each individual target pressure.

[0186] In order to solve the problems of the prior art, the improvement proposed by the present invention embodies a filling process so that optimized control can be achieved according to various target values.

[0187] A filling protocol can be proposed based on the relationship between input / output for each individual pressure, as well as the entire filling process from the start point to the end point of filling. For example, if the input is P0=100 bar and T0=25°C, and the state after 1 second is given as the output as a limiting condition, an output of P1=102 bar and T1=26°C can be obtained.

[0188] A state of P1=102 bar and T1=26°C is given as input, and again one second later a state of P2=103 bar and T2=27°C can be obtained as output. A state of P2=103 bar and T2=27°C is given as input, and again one second later a state of P3=104 bar and T3=27°C can be obtained as output.

[0189] In an embodiment of the present invention, the entire filling process can be reconstructed by combining small filling sequences that reach intermediate filling rates or intermediate state values ​​for each given limiting condition (e.g., 1 second), and a filling protocol that can accommodate this can be proposed. According to one embodiment of the present invention, the step of providing a hydrogen filling control sequence to reach a target filling rate by the dispenser 100 or the charging control system 130 may generate hydrogen filling control commands for at least one intermediate filling rate between the starting filling rate of hydrogen filling and the target filling rate.

[0190] In order to implement a hydrogen filling method according to an embodiment of the present invention, the following conditions may be met. a) ANN model development and utilization of protocols related to ANN models b) Collect data on the actual filling process, classify it by case, and analyze it c) By utilizing the above a) and b), the field data required for the ANN model can be secured, making it possible to utilize it for a variety of use cases.

[0191] Meanwhile, as a prerequisite for providing a user-driven set-filling-amount-based hydrogen filling method, tests on the performance of the field data and ANN model according to a) and b) above can be performed. Such tests can be performed by implementing a test platform with reference to the embodiments of FIGS. 1 to 6.

[0192] Furthermore, with reference to the embodiments of FIGS. 1 to 6, the present invention can include the following optimization type embodiments.

[0193] Example: Optimization Type 1 In relation to the charging control system 130 in the dispenser 100, an independent optimization case may be provided. The ANN-MPC model can optimize the hydrogen charging parameters without controlling the pre-cooler or CHSS.

[0194] Example: Optimization Type 2 An integrated optimizing case may be provided in which the dispenser 100 and the mobility 300 are associated. The ANN-MPC model can be linked to the pre-cooler and the mobility 300, and can be involved in the process of adaptively controlling the pre-cooling temperature of the mobility 300. In particular, this optimization can be performed using the temperature drop signal of the CHSS of the mobility 300.

[0195] According to one embodiment of the present invention, the step of providing a hydrogen filling control sequence for reaching a target filling rate by the dispenser 100 or the charging control system 130 may be performed using an artificial neural network 120 that receives an input of a first intermediate filling rate among at least one or more intermediate filling rates and predicts a hydrogen filling control sequence for reaching the next intermediate filling rate, that is, a second intermediate filling rate.

[0196] The artificial neural network 120 can receive an input of the first intermediate fill rate using a model predictive control technique and generate a series of future predictions of the hydrogen filling control sequence to reach the second intermediate fill rate.

[0197] According to one embodiment of the present invention, the step of providing a hydrogen filling control sequence for reaching a target filling rate by the dispenser 100 or the charging control system 130 can provide the hydrogen filling control sequence based on field data that records the relationship between hydrogen filling control commands and filling rate changes in the process of reaching the target filling rate from the starting filling rate.

[0198] According to one embodiment of the present invention, a user-driven setting-based hydrogen filling method according to one embodiment of the present invention by the dispenser 100 or the charging control system 130 may further include a step of acquiring progress data of the hydrogen filling process of the dispenser 100 and the mobility 300 that supplies hydrogen to the mobility 300 through two-way communication during the hydrogen filling process from the starting filling rate to the target filling rate, and a step of monitoring the hydrogen filling process based on the comparison result between the predicted data and the progress data for reaching the target filling rate from the starting filling rate.

[0199] A user-driven setting-based hydrogen filling method by the dispenser 100 or the charging control system 130 according to one embodiment of the present invention may further include a step of identifying whether the mobility 300 can receive hydrogen supply through communication with the mobility 300.

[0200] A user-driven setting-based hydrogen filling method by the dispenser 100 or charging control system 130 according to one embodiment of the present invention may further include a step of obtaining a target filling rate through communication with the mobility 300, and a step of providing predicted data of a hydrogen filling control sequence for reaching the target filling rate to the mobility 300.

[0201] In a user-driven setting-based hydrogen filling method using a dispenser 100 or a charging control system 130 according to one embodiment of the present invention, if the user input includes changes related to the hydrogen filling target setting, the step of determining the target filling rate can determine a new target filling rate that has been changed based on the changes.

[0202] A user-driven setting-based hydrogen filling method by the dispenser 100 or the charging control system 130 according to one embodiment of the present invention may further include a step of providing the mobility 300 with prediction data of a modified hydrogen filling control sequence for reaching a new target filling rate through communication with the mobility 300.

[0203] In the above embodiments, an embodiment has been illustrated in which the hydrogen filling process or the control operations for hydrogen filling are performed by one of the mobility 300 or the dispenser 100, but the operation of the mobility 300 may be replaced by a corresponding operation by the dispenser 100, and conversely, the operation of the dispenser 100 may be replaced by a corresponding operation by the mobility 300. Furthermore, at least a portion of the hydrogen filling process or the control operations for hydrogen filling may be performed by the mobility 300 and the dispenser 100 in cooperation with each other.

[0204] FIG. 10 is a conceptual diagram illustrating an artificial neural network (ANN) concept for hydrogen filling control for hydrogen-fueled mobility 300 according to one embodiment of the present invention.

[0205] Referring to FIG. 10, the input layer receives measurements of the current state. At this time, the ambient temperature Tamb, the pre-cooled gas temperature Tpre, and the pre-cooled gas pressure Tpre can be measured at the nozzle of the dispenser 100 or the hydrogen filling station 200.

[0206] The hydrogen gas temperature Tgas and the hydrogen gas pressure Pgas are values ​​measured on the CHSS 310 side of the hydrogen fuel mobility 300, and the actual measured values ​​can be input to the input layer.

[0207] During the training process of an artificial neural network, the actual current measurement value is transmitted to the input layer, and the next measurement value is transmitted to the output layer, and these can be used as ground truth data in the learning process of the artificial neural network. At this time, the learning process of the artificial neural network can be a process of learning a function that can predict the next measurement value of the output layer based on a combination of input measurements. The correlation between the data input to the input layer and the data provided to the output layer is learned, and through this, predictions can be made using theoretical results as well as real dynamic fueling data.

[0208] In the inference or output process using an artificial neural network, actual on-site measurements are transmitted to the input layer, and a predicted value for the next measurement can be obtained as an output from the operation of the artificial neural network.

[0209] The learning process of the artificial neural network used in the embodiments of the present invention may be either shallow learning or deep learning, and the artificial neural network may be any type of neural network that is suitable for the purpose of the present invention among known neural networks.

[0210] The values ​​input through the input layer are transmitted to the output layer after undergoing weight-based calculations in the hidden layer. The state values ​​(predicted values ​​for the next state) output by the output layer may be used to calculate a state of charge variable, such as the fraction of charge (SOC), using at least a portion of a thermodynamic model.

[0211] In the present embodiment, hybrid control combining a theoretical simulation model and an artificial neural network is also possible, so that desired results can be achieved even through learning using a small amount of data, and performance that meets the objectives of the present invention can be derived even through a lightweight artificial neural network.

[0212] The real-time pressure rise rate (PRR) or mass flow rate of compressed hydrogen (kg / s) (m_dot) derived in the feedback control process can affect the weights or parameters of the hidden layer of the artificial neural network.

[0213] The artificial neural network-based hydrogen filling method of the present invention can improve the accuracy of filling result predictions through models. By utilizing actual filling data along with theoretical simulation results, real-time measurements can be reflected, further improving the accuracy of prediction results.

[0214] While the conventional control protocol calculates and predicts results through simulation tailored to individual situations, the present invention differs in that it utilizes a process of improving accuracy through repeated training for various situations. Due to this difference, in the embodiment of the present invention, as various theoretical values ​​and empirical results are added, the accuracy gradually improves through updates. Even if a new filling process using a new CHSS310 configuration or a change in flow rate is introduced, the model's functions can be updated by adding actual data and training, making it widely applicable to various mobility fields.

[0215] In a hydrogen filling control technique for a hydrogen filling test for a hydrogen-fueled mobility 300 according to an embodiment of the present invention, Model Prediction Control (MPC) may be used.

[0216] FIG. 11 is a conceptual diagram illustrating the concept of model predictive control for hydrogen filling control for a hydrogen vehicle according to one embodiment of the present invention. In an embodiment of the present invention, while the accuracy of the hydrogen filling model is ensured at a considerable level, future filling results are predicted from the hydrogen filling model and current measurement values, and the pressure increase rate (PRR) can be controlled in real time based on the predicted value and filling value so that specific variables, such as the hydrogen gas temperature Tgas or hydrogen gas pressure Pgas of the CHSS 310, reach the optimal filling target without violating constraints.

[0217] Referring to FIG. 11, in an embodiment of the present invention, MPC-based control is used to calculate future output values ​​based on current measurements and model prediction values, and the operation parameter / variable can be adjusted so that the predicted future response moves to the setpoint (or target) in an optimal manner.

[0218] For example, n model predictions can be derived at current time i. These n model-based predictions form a prediction horizon.

[0219] Each model-based prediction, i.e., prediction horizon, corresponds to a control horizon, i.e., the n control commands / control actions required to make n model predictions can form the control horizon.

[0220] In reality, the first (i+1) control action among the n model predictions and control actions derived at the current time i can be transmitted to the system. As time passes, new n model predictions and control actions are derived again at the current time i+1, which form new prediction horizons and control horizons, respectively. This technique of controlling the system while expanding / moving the horizon is called MPC, and in the present embodiment, MPC-based control can be performed using measured and predicted values ​​of state information (state values) including the temperature and pressure of the hydrogen gas in the CHSS 310.

[0221] FIG. 12 is an operational flowchart illustrating the process of training an artificial neural network for hydrogen filling control according to one embodiment of the present invention. Referring to FIG. 12, a process of training an artificial neural network considering an artificial neural network-model predictive control (ANN-MPC) technique according to one embodiment of the present invention is illustrated.

[0222] In Figure 12, we assume an artificial neural network that has learned the function of acquiring an MPC-based prediction horizon and control horizon, and in particular, an artificial neural network that has learned the function of acquiring n future predictions and corresponding control commands so that the process of future responses reaching the set point through MPC is optimized.

[0223] Referring to both Figures 11 and 12, in an embodiment of the present invention, a control system can be configured based on an ANN model 120, and a test platform system for real-time control based on model predictive control can be configured by ensuring the accuracy of the ANN model 120.

[0224] The test platform system for real-time control predicts future filling results and compares them with actual measurements to control the filling speed / pressure increase rate / pressure increase speed. It can control within optimal values ​​by separately setting limitations, control time intervals, sensitivity, etc. within the system logic.

[0225] While optimal control is primarily performed based on real-time data from the hydrogen filling station 200 and hydrogen-fueled mobility 300, if a specific event occurs during system operation, the system can directly control the pre-cooling temperature of the pre-cooler 210 and the cooling system of the hydrogen-fueled mobility 300, thereby increasing the overall efficiency of the hydrogen filling process.

[0226] 12, the control process begins with receiving a specified SOCsp input from the customer (t=0, S710). For example, the current SOC may be 50% and the SOCsp may be 85%.

[0227] SOC(t) is given as a function of Tgas(t) and Pgas(t), and this process can be carried out based on a general kinetic model. If the current SOC(t) is greater than or equal to SOCsp (S720), hydrogen filling can be stopped. If the current SOC(t) is less than SOCsp (S720), set i=t and perform moving horizon prediction using an artificial neural network (S730).

[0228] Step S730 may be performed by generating MPC predictions using, for example, the artificial neural network 120. In step S740, it may be determined whether the resulting n predictions are optimized and consistent with the intended purpose.

[0229] If the obtained n predictions are optimized predictions, a control command PRR(t) can be obtained based on the n predictions and the control command, and the PRR(t) can be applied to the dispenser 100-CHSS310 (S750).

[0230] Thereafter, time t is incremented and new measured values ​​Tgas(t) and Pgas(t) are obtained and transferred to the input of step S720.

[0231] If the n predictions obtained in step S730 are not optimized predictions, step S730 can be performed again to obtain new n predictions and control commands.

[0232] In step S730 of FIG. 12, a state prediction (T, P) may be generated that satisfies the temperature and pressure constraints for all arbitrary i and k. Using the current time i (= t) as a reference, n predicted state values ​​and corresponding control commands can be derived.

[0233] Step S740 in FIG. 12 can be understood as a process of searching for a set of n predictions that minimizes a cost function indicating whether the final control target, SOCsp, has been reached.

[0234] State measurements including temperature and pressure of the CHSS 310 at the output of the hydrogen fueled mobility 300 may be provided as feedback inputs to the artificial neural network model 120 .

[0235] State measurements including temperature and pressure of the pre-cooled hydrogen gas as outputs of the hydrogen filling station 200 may be provided as feedback inputs to the artificial neural network model 120 .

[0236] The artificial neural network model 120 transmits the predicted output to the hydrogen filling control logic 110, and the charging control system 130 can input future input obtained by simulation or model-based prediction to the artificial neural network model 120 via module A 140.

[0237] The ANN-MPC based control process is a control technique that utilizes both simulation and actual measurement data, and performs simulation at least partially using an artificial neural network model 120 and uses the predicted results in the control process.

[0238] The embodiment of the present invention aims to construct a real-time data-based integrated hydrogen filling control protocol, and the system is realized by utilizing various elemental technologies.

[0239] The protocol installed in the dispenser 100 utilizes the pre-cooled hydrogen gas data provided by the hydrogen filling station 200 and the CHSS 310 data provided by the hydrogen fuel mobility 300 as real-time input values, and can control the filling speed / pressure increase rate / pressure increase speed (PRR or (m_dot)) as output depending on the installed model.

[0240] When an event such as an external environmental change occurs, the pre-cooling temperature of the hydrogen filling station 200 and the cooling system of the hydrogen fuel mobility 300 can be directly controlled to control the filling rate / pressure increase rate / pressure increase rate (PRR or (m_dot)) and process efficiency in general.

[0241] To complement the control protocol, the pre-cooling system / pre-cooler 210 of the hydrogen filling station 200 may be independently equipped with its own cooling stabilization system.

[0242] In terms of temperature stabilization, the cooling stabilization system of the pre-cooler 210 can be independently controlled, and the control target value can be changed integrally with the protocol of the dispenser 100 .

[0243] To complement the economics of the hydrogen filling station 200 and the functionality of the integrated control protocol, the pre-cooler 210 may be provided with additional functionality related to temperature stabilization.

[0244] The pre-cooling temperature varies depending on the initial temperature and flow rate of the hydrogen gas supplied to the pre-cooler 210. To compensate for this, a novel pre-cooler structure for stabilizing the temperature is proposed as one embodiment of the present invention.

[0245] The pre-cooler 210 according to an embodiment of the present invention may include control logic for its own temperature control and linkage with protocols.

[0246] A forced cooling system may be installed in the CHSS 310 of the hydrogen-fueled mobility 300 to cool some of the compression heat generated during hydrogen filling, thereby improving the filling speed, and the operation / control of the forced cooling system of the CHSS 310 may also be involved in the protocol.

[0247] In one embodiment of the present invention, the CHSS 310 of the hydrogen fueled mobility 300 may be provided with thermal management functionality to complement the hydrogen filling rate enhancement and integrated control protocol functionality.

[0248] In one embodiment of the present invention, the CHSS 310 configures a system for self-cooling to increase the overall filling speed and improve the safety of the hydrogen-fueled mobility 300, and may include control logic for self-driving the system and linking with protocols.

[0249] In one embodiment of the present invention, such integrated control not only improves the efficiency of the current filling, but also facilitates preparation for the next filling.

[0250] In the case of T40, where the pre-cooling temperature of the pre-cooler 210 is set to -40°C, if the pre-cooling temperature reaches the target value but the outside air temperature is higher than the set value and the temperature rise on the CHSS 310 side is greater than expected, a control signal or current status information can be transmitted to the hydrogen fuel mobility 300 / CHSS 310 side so that the self-cooling system of the CHSS 310 can be activated.

[0251] Conversely, if the pre-cooling temperature of the pre-cooler 210 is set to -40°C, but is determined to be excessive cooling when considering the external environment and actual data, the target value of the pre-cooling temperature can be adjusted (e.g., -35°C).

[0252] If additional pre-cooling target temperature and temperature control on the CHSS 310 side is required, control information or control commands may be communicated from the dispenser 100 to both the hydrogen-fueled mobility 300 and the hydrogen filling station 200 .

[0253] According to an embodiment of the present invention, the self-cooling systems of the hydrogen fueled mobility 300 and the hydrogen filling station 200 may be controlled independently, or may be controlled by transmitting a signal from the dispenser 100 .

[0254] The integrated control method for hydrogen filling according to an embodiment of the present invention may further include evaluating whether the measurement value of the current state satisfies a constraint condition. The constraint may be that the temperature and pressure of the compressed hydrogen storage system on the hydrogen vehicle side do not exceed a limit temperature and limit pressure, respectively.

[0255] According to an embodiment of the present invention, it is possible to safely fill / supply hydrogen fuel, while improving the efficiency of the hydrogen filling / supply process, and improving the speed and real-timeness of the hydrogen filling / supply process.

[0256] According to one embodiment of the present invention, a test method and test platform can be implemented that can precisely model the hydrogen filling / supply process based on real-time on-site dynamic data.

[0257] According to one embodiment of the present invention, a test method and test platform can be implemented that provides a model that can precisely control the hydrogen filling / supply process by taking into account the difference between modeling and simulation results based on a theoretical model and real-time field data, or by taking into account all of the modeling and simulation results and real-time field data.

[0258] According to one embodiment of the present invention, a test method for hydrogen filling control that ensures real-time performance based on model predictive control (MPC) can be implemented.

[0259] According to one embodiment of the present invention, a test technique for control with improved accuracy in predicting hydrogen filling results based on an artificial neural network (ANN) model can be implemented.

[0260] The user can input the filling amount (e.g., SOC) directly, and hydrogen can be filled / supplied until the target amount is reached through control logic based on real-time communication and calculation using sequences such as those shown in Figures 11 and 12. Various variables such as SOC, target pressure, time, and temperature can be used to set the fill volume, and the fill rate can be controlled for increased efficiency.

[0261] FIG. 13 is a conceptual diagram illustrating a two-way communication protocol for a user-driven configuration-based hydrogen filling process according to one embodiment of the present invention. Referring to FIG. 13, an example of communication data required for real-time control is shown.

[0262] In FIG. 13, the user-proposed fill target based two-way communication process and protocol is illustrated. Through two-way communication, basic information confirmation, forecast data for the presented target amount, and progress data can be provided in both directions between the mobility 300 and the dispenser 100.

[0263] Step S610 illustrates information provided from the mobility 300 to the dispenser 100. As basic information for the dispenser 100 to check, the mobility 300 may provide the dispenser 100 with the CHSS type, capacity, and other restrictions of the mobility 300.

[0264] As monitoring information for the dispenser 100 to check, the temperature (T) / pressure (P), SOC, and emergency status information of the CHSS of the mobility 300 can be provided from the mobility 300 to the dispenser 100.

[0265] The target filling amount of the mobility 300 can be provided from the mobility 300 to the dispenser 100 as control information for the dispenser 100 to return a result value.

[0266] In step S620, information provided from the dispenser 100 to the mobility 300 is illustrated.

[0267] As basic information, the dispenser 100 may respond to the mobility 300 with information about the hydrogen filling station 200 and whether or not the mobility 300 is compatible. As a predicted value, the predicted progress result relative to the target filling amount can be provided from the dispenser 100 to the mobility 300. As control information, fluctuation information relative to the target amount and progress values ​​of the filling process can be provided from the dispenser 100 to the mobility 300 .

[0268] FIG. 14 is a conceptual diagram illustrating a communication protocol and operational flow chart for a user-driven configuration-based hydrogen filling process according to one embodiment of the present invention. Referring to FIG. 14, when the vehicle / mobility 300 enters the hydrogen filling station 200 (S510), it is checked whether basic information matches between the vehicle / mobility 300 and the dispenser 100 (S520). At this time, if the basic information matches, bidirectional communication is performed between the vehicle / mobility 300 and the dispenser 100, and step S530 is performed.

[0269] (1) A fill target (quantity, price, etc.) may be provided to the dispenser 100 from the vehicle / mobility 300 . (2) Forecast data (time, price, etc.) may be provided from the dispenser 100 to the vehicle / mobility 300. (3) The temperature, pressure, SOC, and specific information of the hydrogen tank of the vehicle / mobility 300 can be transmitted from the vehicle / mobility 300 to the dispenser 100. In response, the dispenser 100 may provide the vehicle / mobility 300 with a (3) fill rate, variable value for hydrogen filling.

[0270] When the target SOC is reached as a result of filling, an end signal (4) may be transmitted from the dispenser 100 to the vehicle / mobility 300. In response to this, (5) a request for a fill completion procedure may be transmitted from the vehicle / mobility 300 to the dispenser 100.

[0271] At this time, the sequences (3) to (5) can be linked to the safety field by step S540. Also, the check result of step S520 can be transmitted to step S540.

[0272] If the basic information does not match as a result of the determination in step S520, the filling process is stopped (S550). After the filling process is stopped, the safety personnel may be reconfirmed (S560). At this time, if the safety personnel are reconfirmed, it may be confirmed again whether the basic information matches (S520). At this time, if the safety personnel are not reconfirmed, it may be determined that filling is not possible.

[0273] A user-initiated setting-based hydrogen filling protocol identification method by a mobility 300 according to one embodiment of the present invention may be performed by step S520. The protocol identification method according to one embodiment of the present invention may include the steps of identifying a filling protocol supported between a dispenser 100 that fills hydrogen into the mobility 300 and the mobility 300 through communication with the dispenser 100; and determining whether the identified filling protocol is a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility 300.

[0274] A user-initiated setting-based hydrogen filling protocol identification method by the dispenser 100 according to another embodiment of the present invention may also be performed by step S520. The protocol identification method according to one embodiment of the present invention may include the steps of identifying a filling protocol supported between the dispenser 100 and the mobility 300 by communicating with the mobility 300; and determining whether the identified filling protocol is a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility 300.

[0275] A user-driven setting-based hydrogen filling protocol negotiation method by a mobility 300 according to an embodiment of the present invention may be performed by step S520. The protocol negotiation method according to an embodiment of the present invention may include the steps of identifying at least one filling protocol supported between a dispenser 100 that fills hydrogen into the mobility 300 and the mobility 300 through communication with the dispenser 100, and selecting and negotiating a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility 300 from among the at least one identified filling protocol through communication with the dispenser 100 as a preferred filling protocol.

[0276] A user-driven setting-based hydrogen filling protocol negotiation method by a dispenser 100 according to another embodiment of the present invention may also be performed by step S520. The protocol negotiation method according to an embodiment of the present invention may include the steps of identifying at least one filling protocol supported between the dispenser 100 and the mobility 300 through communication with the mobility 300, and selecting a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility 300 as a preferred filling protocol through communication with the mobility 300, and negotiating the same.

[0277] In step S520, basic information can be exchanged through communication between the dispenser 100 and the mobility 300. At this time, the basic information can include information on whether the dispenser 100 and the mobility 300 each support a hydrogen filling process based on a user-set filling amount.

[0278] The basic information may include a hydrogen filling protocol supported by the mobility 300 and a communication protocol linked to the hydrogen filling protocol. The basic information may also include a hydrogen filling protocol supported by the dispenser 100 and a communication protocol linked to the hydrogen filling protocol. By sharing basic information between the mobility 300 and the dispenser 100, interoperability of the hydrogen filling protocols supported by the mobility 300 and the dispenser 100 can be determined.

[0279] At this time, the criteria for selecting a filling protocol between the mobility 300 and the dispenser 100 may be interoperability and whether or not the hydrogen filling process based on the user-defined filling amount of the present invention is supported.

[0280] In one embodiment of the present invention, in step S520, based on basic information, it can be determined whether a filling protocol that satisfies interoperability among multiple hydrogen filling protocols is a filling protocol that supports a user-defined filling amount-based hydrogen filling process.

[0281] In another embodiment of the present invention, a filling protocol negotiation process can be performed in step S520 based on basic information so that a filling protocol that supports a user-set filling amount-based hydrogen filling process is preferentially selected from among multiple filling protocols that satisfy interoperability.

[0282] In one embodiment of the present invention, information regarding the filling protocol supported by the mobility 300 is transmitted to the dispenser 100 as basic information, and the dispenser 100 can select a hydrogen filling protocol that supports interoperability and a user-set filling amount-based hydrogen filling process.

[0283] In another embodiment of the present invention, information regarding the filling protocol supported by the dispenser 100 is transmitted to the mobility 300 as basic information through bidirectional communication, and the mobility 300 can select a hydrogen filling protocol that supports interoperability and a user-set filling amount-based hydrogen filling process.

[0284] In yet another embodiment of the present invention, through bidirectional communication, information regarding the filling protocols supported by the dispenser 100 and the mobility 300 is shared as basic information, and a hydrogen filling protocol that supports interoperability and a user-set filling amount-based hydrogen filling process can be selected / determined through negotiation between the dispenser 100 and the mobility 300.

[0285] In a user-driven setting-based hydrogen filling method using a dispenser 100, a charging control system 130, or a mobility 300 according to one embodiment of the present invention, if the user input transmitted in step S530 includes changes related to hydrogen filling target settings, the step of determining the target filling rate can determine a new target filling rate that has been changed based on the changes.

[0286] A user-driven setting-based hydrogen filling method using a dispenser 100, a charging control system 130, or a mobility 300 according to one embodiment of the present invention may further include a step of providing the mobility 300 with predicted data of a modified hydrogen filling control sequence for reaching a new target filling rate through communication between the dispenser 100 and the mobility 300 in step S530.

[0287] Figure 15 is a conceptual diagram illustrating an example of a generalized hydrogen filling control device, hydrogen filling control system, hydrogen filling test platform, hydrogen filling test system, or computing system capable of performing at least some of the processes of Figures 1 to 14.

[0288] A controller or charging control system 130 that controls the hydrogen filling test process may be located on the dispenser 100 side. Communication interfaces 140, 150, 160 that control the hydrogen filling test process may be distributed among the dispenser 100, the hydrogen filling station 200, and the hydrogen-fueled mobility 300 or may be located in at least some of them to control the operation of at least some of the dispenser 100, the hydrogen filling station 200, and the hydrogen-fueled mobility 300.

[0289] The controllers or communication interfaces 130 , 140 , 150 , 160 that make up the hydrogen filling test platform and / or system may be embodied in the form of a computing system that includes a processor 1100 electronically coupled to a memory 1200 .

[0290] At least some of the steps of the hydrogen filling process, hydrogen filling control method, and / or testing method according to one embodiment of the present invention may be performed by the computing system 1000 of FIG.

[0291] Referring to FIG. 15, a computing system 1000 according to one embodiment of the present invention may be configured to include a processor 1100, a memory 1200, a communication interface 1300, a storage device 1400, an input interface 1500, an output interface 1600, and a bus 1700.

[0292] A computing system 1000 according to an embodiment of the present invention may include at least one processor 1100 and a memory 1200 storing instructions for instructing the at least one processor 1100 to perform at least one step. At least some steps of a method according to an embodiment of the present invention may be performed by the at least one processor 1100 loading and executing instructions from the memory 1200.

[0293] The processor 1100 may refer to a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor on which methods according to embodiments of the present invention are performed.

[0294] The memory 1200 and the storage device 1400 may each be composed of at least one of a volatile storage medium and a non-volatile storage medium, for example, the memory 1200 may be composed of at least one of a read only memory (ROM) and a random access memory (RAM).

[0295] The computing system 1000 may also include a communication interface 1300 for effecting communications over a wireless network. The computing system 1000 may further include a storage device 1400, an input interface 1500, an output interface 1600, and the like.

[0296] Furthermore, the components included in the computing system 1000 are connected to each other by a bus 1700 to perform communication.

[0297] Examples of the computing system 1000 of the present invention may include a communications-enabled desktop computer, a laptop computer, a notebook computer, a smartphone, a tablet PC, a mobile phone, a smart watch, smart glasses, an e-book reader, a portable multimedia player (PMP), a portable game console, a navigation device, a digital camera, a digital multimedia broadcasting (DMB) player, a digital audio recorder, a digital audio player, a digital video recorder, a digital video player, a personal digital assistant (PDA), and the like.

[0298] The hydrogen-fueling device mounted on the hydrogen-fueled mobility 300 according to one embodiment of the present invention is a user-driven setting-based hydrogen-fueling device, and may include a memory 1200 for storing at least one or more instructions, and a processor 1100 for executing at least one or more instructions.

[0299] At this time, the processor 1100 can receive user input related to setting a hydrogen filling target through at least one instruction, determine a target state of charge (SOC) for hydrogen filling of the mobility 300 based on the user input, and receive hydrogen supply through a hydrogen filling control sequence to reach the target state of charge. At this time, the user input may include a target filling rate for hydrogen filling of the mobility 300. That is, the driver may determine the SOC directly in the mobility 300 or in the driving app.

[0300] The processor 1100 can determine the target filling rate based on user input and at least one of the current filling status of the mobility 300 and filling-related status information of the mobility 300. The mobility 300 can determine the final target SOC instead of the dispenser 100 or the filling control system 130 based on the amount intended by the user.

[0301] The processor 1100 can acquire progress data of the hydrogen filling process of the mobility 300 during the hydrogen filling process from the start filling rate to the target filling rate.

[0302] The processor 1100 can transmit the progress data of the mobility 300 to the dispenser 100 or the fill control system 130 that supplies hydrogen to the mobility 300 so that the progress data of the mobility 300 can be monitored.

[0303] At this time, real-time two-way communication can be used between the mobility 300 and the dispenser 100 to share data from the mobility 300 for monitoring the filling process.

[0304] The processor 1100 can generate a hydrogen filling control request for at least one intermediate filling rate between the start filling rate and the target filling rate of hydrogen filling.

[0305] The processor 1100 may request filling based on the input / output relationship for each individual pressure between the filling start point and the filling end point, or may request derivation of a protocol for filling based on the input / output relationship for each individual pressure.

[0306] The user-driven configuration-based hydrogen filling dispenser device according to one embodiment of the present invention is a dispenser device 100 that fills hydrogen into a mobility 300 that uses hydrogen as fuel, and may include a memory 1200 that stores at least one or more instructions, and a processor 1100 that executes at least one or more instructions.

[0307] The processor 1100 can, through at least one or more instructions, receive user input related to setting a hydrogen filling target, determine a target state of charge (SOC) for hydrogen filling of the mobility 300 based on the user input, and provide a hydrogen filling control sequence to reach the target state of charge.

[0308] The processor 1100 can acquire progress data of the hydrogen filling process of the dispenser 100 that supplies hydrogen to the mobility and the mobility 300 through bidirectional communication during the hydrogen filling process from the start filling rate to the target filling rate.

[0309] The processor 1100 can monitor the hydrogen filling process based on the comparison between the predicted data and the progress data from the starting fill rate to the target fill rate.

[0310] The operations of the methods according to the embodiments of the present invention may be embodied as a computer-readable program or code stored in a computer-readable recording medium. The computer-readable recording medium includes all types of storage devices that store information that can be read by a computer system. The computer-readable recording medium may also be distributed among computer systems connected to a network, so that the computer-readable program or code may be stored and executed in a distributed manner.

[0311] Additionally, the computer-readable recording medium may include a hardware device specially configured to store and execute program instructions, such as a ROM, RAM, flash memory, etc. The program instructions may include not only machine language code, such as that produced by a compiler, but also high-level language code that can be executed by a computer using an interpreter, etc.

[0312] Although some aspects of the invention have been described in the context of an apparatus, they may also be described in terms of a corresponding method, where a block or apparatus corresponds to a method step or feature of a method step. Similarly, aspects described in the context of a method may also be described in terms of a corresponding block or item or feature of a corresponding apparatus. Some or all of the method steps may be performed by (or using) a hardware device, such as, for example, a microprocessor, a programmable computer, or electronic circuitry. In some embodiments, at least one or more of the most significant method steps may be performed by such a device.

[0313] In some embodiments, a programmable logic device (e.g., a field programmable gate array) may be used to perform some or all of the functions of the methods described herein. In some embodiments, a field programmable gate array may operate in conjunction with a microprocessor to perform one of the methods described herein. In general, it is preferred that the methods be performed by some hardware device.

[0314] Although the present invention has been described above with reference to preferred embodiments, it will be understood that those skilled in the art can make various modifications and changes to the present invention without departing from the spirit and scope of the present invention as set forth in the claims below. [Explanation of symbols]

[0315] 100 Dispensers 110 Filling control logic 120 Artificial Neural Network Models 130 Filling Control System 140 Communication Interface (Module A) 150 Communication Interface (Module B) 160 Communication Interface (Module C) 200 Hydrogen Filling Station 210 Pre-cooler 220 High-pressure hydrogen storage unit 300 Hydrogen Vehicles 310 Compressed Hydrogen Storage System (CHSS) 320 Pressure Relief Device (PRD) 330 Cooling System 1000 Computing Systems 1100 processor 1200 memory 1300 Communication Interface 1400 Storage device 1500 Input Interface 1600 Output Interface

Claims

1. A method of fueling hydrogen-fueled mobility with hydrogen, comprising: receiving user input related to setting a hydrogen filling goal; determining a target state of charge (SOC) for hydrogen refueling of the mobility based on the user input; and receiving a supply of hydrogen according to a hydrogen filling control sequence for reaching the target filling rate.

2. The user-initiated setting-based hydrogen filling method according to claim 1 , wherein the user input includes the target filling rate for hydrogen filling of the mobility.

3. The step of determining the target filling rate comprises:

2. The user-driven setting-based hydrogen filling method of claim 1, wherein the target filling rate is determined based on at least one of the current filling status of the mobility and filling-related status information of the mobility based on the user input.

4. acquiring progress data of the hydrogen filling process of the mobility during the hydrogen filling process from the start filling rate to the target filling rate; and 2. The user-initiated setting-based hydrogen filling method of claim 1, further comprising transmitting the progress data of the mobility to a dispenser or filling control system that supplies hydrogen to the mobility so that the progress data of the mobility can be monitored.

5. The step of receiving a supply of hydrogen according to a hydrogen filling control sequence for reaching the target filling rate includes:

2. The user-initiated setting-based hydrogen filling method of claim 1, further comprising generating a hydrogen filling control request for at least one intermediate filling rate between a start filling rate of hydrogen filling and the target filling rate.

6. A method of fueling hydrogen-fueled mobility with hydrogen, comprising: receiving user input related to setting a hydrogen filling goal; determining a target state of charge (SOC) for hydrogen refueling of the mobility based on the user input; and providing a hydrogen filling control sequence for reaching the target filling rate.

7. The user-initiated setting-based hydrogen filling method of claim 6, wherein the user input includes the target filling rate for hydrogen filling of the mobility.

8. The step of determining the target filling rate comprises: The user-driven setting-based hydrogen filling method of claim 6, wherein the target filling rate is determined based on at least one of the current filling status of the mobility and filling-related status information of the mobility based on the user input.

9. providing a hydrogen filling control sequence to reach the target filling rate, The user-driven setting-based hydrogen filling method of claim 6, further comprising determining a target hydrogen filling control sequence corresponding to the target filling rate from among a group of candidate hydrogen filling control sequences for reaching an individual target filling rate.

10. providing a hydrogen filling control sequence to reach the target filling rate, 7. The user-driven setting-based hydrogen filling method of claim 6, further comprising predicting a hydrogen filling control sequence for reaching the target filling rate based on existing hydrogen filling data between the dispenser that supplies hydrogen to the mobility and the mobility.

11. providing a hydrogen filling control sequence to reach the target filling rate, 7. The user-initiated setting-based hydrogen filling method according to claim 6, wherein a hydrogen filling control command is generated for at least one intermediate filling rate between a starting filling rate and the target filling rate.

12. providing a hydrogen filling control sequence to reach the target filling rate, 12. The user-initiated setting-based hydrogen filling method of claim 11, wherein the method is performed using an artificial neural network that receives input of a first intermediate filling rate among the at least one intermediate filling rate and predicts a hydrogen filling control sequence to reach the next intermediate filling rate, which is a second intermediate filling rate.

13. 13. The user-initiated setting-based hydrogen filling method of claim 12, wherein the artificial neural network receives the first intermediate filling rate as an input and generates a series of future predicted values ​​of the hydrogen filling control sequence that reaches the second intermediate filling rate using a model predictive control technique.

14. providing a hydrogen filling control sequence to reach the target filling rate, 12. The user-initiated setting-based hydrogen filling method of claim 11, wherein the hydrogen filling control sequence is provided based on field data in which the relationship between the hydrogen filling control command and the change in the filling rate during the process of reaching the target filling rate from the starting filling rate is recorded.

15. During the hydrogen filling process from the start filling rate to the target filling rate, a dispenser that supplies hydrogen to the mobility and progress data of the hydrogen filling process of the mobility are acquired through bidirectional communication; and 7. The user-initiated setting-based hydrogen filling method of claim 6, further comprising the step of monitoring the hydrogen filling process based on a comparison result between the progress data and predicted data for reaching the target filling rate from the starting filling rate.

16. The user-initiated setting-based hydrogen filling method according to claim 6, further comprising: identifying whether the mobility can receive a supply of hydrogen through communication with the mobility.

17. obtaining the target fill rate through communication with the mobility; and The user-initiated setting-based hydrogen filling method according to claim 6, further comprising the step of providing the mobility with predicted data of a hydrogen filling control sequence for reaching the target filling rate.

18. If the user input includes a change related to the hydrogen filling target setting, The step of determining the target filling rate comprises:

7. The method of claim 6, further comprising determining a new target filling rate based on the changes.

19. 20. The user-initiated setting-based hydrogen filling method of claim 18, further comprising: providing the mobility with predicted data of a modified hydrogen filling control sequence for reaching the new target filling rate through communication with the mobility.

20. In a hydrogen fueling device mounted on a hydrogen-fueled mobility vehicle, a memory for storing at least one instruction; and a processor for executing the at least one instruction; The processor, in response to the at least one instruction, receiving user input related to setting a hydrogen filling goal; determining a target state of charge (SOC) for hydrogen refueling of the mobility based on the user input; A user-initiated setting-based hydrogen filling device, characterized in that hydrogen is supplied according to a hydrogen filling control sequence for reaching the target filling rate.

21. 21. The user-initiated setting-based hydrogen filling device of claim 20, wherein the user input includes the target filling rate for hydrogen filling of the mobility.

22. The processor: The user-driven setting-based hydrogen filling device of claim 20, wherein the target filling rate is determined based on at least one of the current filling status of the mobility and filling-related status information of the mobility based on the user input.

23. The processor: Acquiring progress data of the hydrogen filling process of the mobility during the hydrogen filling process from the start filling rate to the target filling rate; The user-driven setting-based hydrogen filling device of claim 20, wherein the progress data of the mobility is transmitted to a dispenser or filling control system that supplies hydrogen to the mobility so that the progress data of the mobility can be monitored.

24. The processor:

21. The user-initiated setting-based hydrogen filling device of claim 20, wherein a hydrogen filling control request is generated for at least one intermediate filling rate between a starting filling rate of hydrogen filling and the target filling rate.

25. A dispenser device for filling hydrogen into hydrogen-fueled mobility, a memory for storing at least one instruction; and a processor for executing the at least one instruction; The processor, in response to the at least one instruction, receiving user input related to setting a hydrogen filling goal; determining a target state of charge (SOC) for hydrogen refueling of the mobility based on the user input; A user-initiated setting-based hydrogen filling dispenser device that provides a hydrogen filling control sequence for reaching the target filling rate.

26. The processor During the hydrogen filling process between the start filling rate of hydrogen filling and the target filling rate, data on a dispenser that supplies hydrogen to the mobility and progress data on the hydrogen filling process of the mobility are acquired through bidirectional communication; 26. The user-initiated setting-based hydrogen filling dispenser device of claim 25, wherein the hydrogen filling process is monitored based on a comparison result between the progress data and predicted data for reaching the target filling rate from the starting filling rate.

27. 1. A method for identifying a hydrogen filling protocol for fueling a hydrogen-fueled mobility vehicle, comprising: A step of identifying a filling protocol supported between a dispenser that fills the mobility with hydrogen and the mobility through communication between the dispenser and the mobility; and A user-driven setting-based hydrogen filling protocol identification method, comprising a step of determining whether the identified hydrogen filling protocol is a filling protocol that supports a function that allows a user to set a target state of charge (SOC) for hydrogen filling of the mobility.

28. 1. A method for negotiating a hydrogen filling protocol for fueling a hydrogen-fueled mobility vehicle, comprising: Identifying at least one or more filling protocols supported between a dispenser that fills the mobility with hydrogen and the mobility through communication between the dispenser and the mobility; and A user-driven setting-based hydrogen filling protocol negotiation method, comprising: a step of selecting and negotiating, through communication between the mobility and a dispenser that fills the mobility with hydrogen, a filling protocol that supports a function that allows a user to set a target filling rate (SOC) for hydrogen filling of the mobility from among the at least one identified filling protocol as a preferred filling protocol.

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