Apparatus and method for predicting lifespan of fuel cell

Abstract

An apparatus for predicting the lifespan of a fuel cell according to an embodiment of the present invention may be provided, the apparatus comprising: an information collection unit for measuring the voltage of each of multiple unit cells provided in a fuel cell stack; a cell prediction modeling unit for generating a cell degradation prediction model to define a degradation pattern of each unit cell on the basis of the voltage measured in the unit cell; a cell prediction correction unit for generating a cell degradation correction model for correcting the degradation pattern to reflect the dependency of a degradation pattern of one unit cell to that of another unit cell among degradation patterns of the multiple unit cells; and a lifespan prediction unit for predicting the lifespan of each unit cell on the basis of the cell degradation correction model, and outputting the time until the unit cell with the predicted lifespan reaches a failure determination condition.

Description

Fuel cell life prediction device and method

[0001] The present invention relates to a fuel cell life prediction device and method for predicting the life of a fuel cell.

[0002] Fuel cells, due to their complex component relationships and recent commercialization, lack the reliability of traditional products. In particular, compared to other energy sources, fuel cells are more susceptible to internal and external influences, leading to a lack of durability. Understanding internal and external interactions and dependencies is crucial for ensuring precise reliability. Therefore, ensuring precise reliability of fuel cells is challenging. To enhance the reliability of lifespan predictions, various methods of fuel cell degradation pattern analysis are being conducted.

[0003] A fuel cell stack is a device that generates electricity through the chemical reaction of hydrogen and oxygen. It consists of multiple cells arranged in series in a stack assembly to secure the electrical energy required to operate a specific system. Due to this configuration, the overall performance of the fuel cell stack is highly dependent on the performance of each individual cell. Deterioration of even one cell leads to irreversible performance degradation. This impacts the lifespan of the entire stack, making it difficult to achieve the expected stable performance. Therefore, reliable prediction of the lifespan of each individual cell, as well as the entire fuel cell stack, is crucial.

[0004] Due to the series structure of fuel cell stacks, deterioration in one cell can affect adjacent cells. Therefore, when predicting fuel cell stack deterioration, it is necessary to consider not only the data characteristics of individual cells, but also the influence of adjacent cells and other external factors.

[0005] The disclosed embodiment provides a fuel cell life prediction device and a control method thereof that improves the reliability of life prediction of each unit cell by modeling the deterioration pattern of each unit cell of a fuel cell stack.

[0006] A fuel cell life prediction device and a control method thereof are provided, which improve the reliability of life prediction of each unit cell by precisely correcting the deterioration pattern of each unit cell by considering the dependency of the deterioration pattern of the unit cell with the deterioration patterns of other adjacent unit cells.

[0007] A fuel cell life prediction device and a control method thereof are provided to improve the reliability of life prediction of a fuel cell stack in which multiple unit cells are integrated through analysis of the deterioration pattern of the unit cells.

[0008] A fuel cell life prediction device and a control method thereof are provided to prevent excessive replacement of the entire fuel cell stack by determining a failure of a unit cell and diagnosing replacement, thereby reducing costs and predicting an optimal repair cycle.

[0009] According to one embodiment, a fuel cell life prediction device includes: an information collection unit that measures voltages of a plurality of unit cells provided in a fuel cell stack; a cell prediction model unit that generates a cell deterioration prediction model to define a deterioration pattern of each unit cell based on the voltages measured in the unit cells; a cell prediction correction unit that generates a cell deterioration correction model that corrects a deterioration pattern to reflect a dependency of a deterioration pattern of one unit cell among the deterioration patterns of the plurality of unit cells on the deterioration patterns of other unit cells; and a life prediction unit that predicts the life of each unit cell based on the cell deterioration correction model and outputs a time required for the predicted life to reach a failure determination condition.

[0010] It includes a stack prediction model unit that generates an integrated deterioration prediction model to define a deterioration pattern of the fuel cell stack based on the deterioration patterns of the plurality of unit cells corrected by the cell prediction correction unit.

[0011] The life prediction unit predicts the life of the fuel cell stack based on the integrated deterioration prediction model, and outputs the time required for the predicted life to reach the deterioration judgment condition.

[0012] The above cell prediction model section is characterized by defining a cell degradation prediction model as in [Mathematical Formula 1] below.

[0013] The above cell prediction correction unit is characterized by correcting the deterioration pattern as shown in [Mathematical Formula 2] below.

[0014] It further includes a storage unit that stores information about the voltage measured in the information collection unit, the cell degradation prediction model generated in the cell prediction model unit, and the cell degradation correction model generated in the cell prediction correction unit.

[0015] The present invention comprises: an information collection unit for measuring voltages of a plurality of unit cells provided in a fuel cell stack; a cell prediction model unit for predicting a deterioration pattern of each unit cell based on the voltages measured in the unit cells; a cell prediction correction unit for correcting a deterioration pattern to reflect a dependency between the deterioration patterns of the plurality of unit cells; a stack prediction model unit for predicting a deterioration pattern of the fuel cell stack based on the corrected deterioration pattern; and a life prediction unit for predicting the lifespans of the unit cells and the fuel cell stack based on the corrected deterioration pattern of the unit cells and the deterioration pattern of the fuel cell stack, respectively.

[0016] According to another embodiment, a fuel cell life prediction method includes: an information collection step of measuring voltages of a plurality of unit cells provided in a fuel cell stack; a cell prediction step of generating a cell deterioration prediction model to define a deterioration pattern of each unit cell based on the voltages measured in the unit cells; a cell prediction correction step of generating a cell deterioration correction model that corrects the deterioration pattern of one unit cell among the deterioration patterns of the plurality of unit cells to reflect a dependency thereof on the deterioration patterns of other unit cells; and a life prediction step of predicting the life of each unit cell based on the cell deterioration correction model and outputting the time required for the predicted life to reach a failure determination condition.

[0017] The present invention further includes a stack prediction step of generating an integrated degradation prediction model based on the cell degradation correction model to define a degradation pattern of the fuel cell stack.

[0018] The above life prediction step further includes a feature of predicting the life of the fuel cell stack based on the integrated deterioration prediction model and outputting the time required for the predicted life to reach a failure determination condition.

[0019] According to a fuel cell life prediction device and a control method thereof according to one aspect, the reliability of life prediction of each unit cell of a fuel cell stack is improved through modeling of the deterioration pattern of each unit cell.

[0020] According to a fuel cell life prediction device and a control method thereof according to one aspect, the reliability of life prediction of each unit cell is improved by precisely correcting the deterioration pattern of each unit cell by considering the dependency between the deterioration pattern of the unit cell and the deterioration pattern of another adjacent unit cell.

[0021] According to a fuel cell life prediction device and a control method thereof according to one aspect, the reliability of life prediction of a fuel cell stack in which a plurality of unit cells are integrated is improved through analysis of the deterioration pattern of the unit cells.

[0022] According to a fuel cell life prediction device and its control method according to one aspect, by determining a failure of a unit cell and diagnosing replacement, excessive replacement of the entire fuel cell stack is prevented, thereby reducing costs and predicting an optimal repair cycle.

[0023] FIG. 1 is a drawing illustrating a fuel cell stack and a fuel cell life prediction device according to one embodiment of the present invention.

[0024] FIG. 2 is a diagram illustrating the configuration of a fuel cell life prediction device according to one embodiment of the present invention.

[0025] Figure 3 is a graph showing a cell degradation prediction model (M1) of a plurality of unit cells predicted by a cell degradation prediction model section of a fuel cell life prediction device of the present invention.

[0026] Figure 4 shows a graph corrected with a cell degradation correction model (M2) that reflects the dependency between unit cells in the degradation pattern of Figure 3.

[0027] Figure 5 shows an evaluation graph that predicts the life of a fuel cell without considering the dependency of the deterioration pattern of a unit cell using the fuel cell life prediction device of the present invention.

[0028] Figure 6 shows an evaluation graph that predicts the life of a fuel cell by considering the dependency of the deterioration pattern of a unit cell using the fuel cell life prediction device of the present invention.

[0029] Figure 7 is a graph showing a comparison of the predicted mean time to function (MTTF) when considering the dependency of the deterioration pattern of the most deteriorated unit cell in the fuel cell of the present invention and when considering it.

[0030] FIG. 8 is a diagram illustrating an operation flow for a fuel cell life prediction method according to one embodiment of the present invention.

[0031] Like reference numerals refer to like elements throughout the specification. This specification does not describe all elements of the embodiments, and any general information within the technical field to which the present invention pertains or any information that overlaps between the embodiments is omitted.

[0032] Throughout the specification, when a part is said to be "connected" to another part, this includes not only direct connection but also indirect connection, and indirect connection includes connection via a wireless communication network.

[0033] Additionally, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

[0034] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0035] Additionally, terms such as "~part", "~device", "~block", "~absence", and "~module" may refer to a unit that processes at least one function or operation. For example, the terms may refer to at least one hardware such as an FPGA (field-programmable gate array) / ASIC (application specific integrated circuit), at least one software stored in a memory, or at least one process processed by a processor.

[0036] The symbols attached to each step are used to identify each step and do not indicate the order of the steps, and the steps may be performed in a different order than stated unless the context clearly indicates a specific order.

[0037] Hereinafter, with reference to the attached drawings, an embodiment of a fuel cell life prediction device and a control method thereof according to one aspect will be described in detail.

[0038] FIG. 1 is a drawing illustrating a fuel cell stack and a fuel cell life prediction device according to one embodiment of the present invention.

[0039] As illustrated in FIG. 1, a fuel cell stack (10) according to one embodiment of the present invention includes a plurality of unit cells (11), and a fuel cell life prediction device (100) is connected to each unit cell (11) to predict the life of the fuel cell.

[0040] A fuel cell stack (10) can be used to provide power for driving an electric vehicle. The scope of application of the fuel cell stack (10) is not limited to vehicle systems, and can also be used to provide electrical energy to electronic equipment and household electrical systems.

[0041] A fuel cell stack (10) may be composed of a plurality of unit cells (11). Specifically, the fuel cell stack (10) may refer to a stack composed by repeatedly stacking and connecting a plurality of unit cells (11).

[0042] As charge and discharge are repeated, the fuel cell stack (10) experiences degradation and deterioration, which reduces the available capacity. At this time, since the fuel cell stack (10) has multiple unit cells (11) connected in series, the deterioration of a unit cell (11) can electrochemically and physically affect the deterioration of adjacent unit cells (11) within the stack. Therefore, in order to predict the lifespan of the fuel cell stack (10), it is necessary to consider not only the deterioration pattern of each unit cell (11), but also the dependency between the unit cells (11) within the fuel cell stack (10).

[0043] The fuel cell life prediction device (100) can collect and store information on the unit cell (11), for example, information on the current (I) and voltage (V) of the unit cell (11) in real time or at a predetermined time cycle.

[0044] A fuel cell life prediction device (100) can generate a cell deterioration prediction model (M1) that predicts the deterioration pattern of a unit cell (11) by analyzing the variability of voltage based on the voltage (V) of the stored unit cell (11). A more detailed description of the cell deterioration prediction model (M1) will be described later.

[0045] The fuel cell life prediction device (100) can generate a cell degradation correction model (M2) that corrects the degradation pattern of each unit cell (11) to accurately predict the degradation pattern by considering the degree of interdependence (dependency) of each cell degradation prediction model (M1). A more detailed description of the cell degradation correction model (M2) will be described later.

[0046] The fuel cell life prediction device (100) can obtain each corrected deterioration pattern through the cell deterioration correction model (M2), and based on this, can create an integrated deterioration prediction model (M3) that predicts the deterioration pattern of the fuel cell stack (10).

[0047] A fuel cell life prediction device (100) can quantitatively predict the deterioration of a unit cell (11) and / or a fuel cell stack (10) after a predetermined period of time based on a cell deterioration prediction model (M1) and a cell deterioration correction model (M2), and can quantitatively derive the time required until a failure determination point. At this time, a failure determination condition is set to a predetermined value, and can be defined as, for example, a point in time when the measured voltage of the unit cell (11) and / or the fuel cell stack (10) is determined to have deteriorated by 10% compared to the initial voltage.

[0048] The fuel cell life prediction device (100) according to the present invention can be implemented inside a vehicle. In this case, the fuel cell life prediction device (100) can be formed integrally with the internal control units of the vehicle, or can be implemented as a separate device and connected to the control units of the vehicle by a separate connection means. Here, the device (100) can operate in conjunction with the engine and motor of the vehicle, and can also operate in conjunction with a control unit that controls the operation of the engine or motor.

[0049] FIG. 2 is a diagram illustrating the configuration of a fuel cell life prediction device according to one embodiment of the present invention.

[0050] Referring to FIG. 2, the fuel cell life prediction device (100) may include a control unit (110), an interface unit (120), a communication unit (130), a storage unit (140), an information collection unit (150), a cell prediction model unit (160), a cell prediction correction unit (170), a stack prediction model unit (180), and a life prediction unit (190). Here, the control unit (110) may process signals transmitted between each component of the device (100).

[0051] The interface unit (120) may include an input means for receiving a control command from a user and an output means for outputting the operating status and results of the device (100).

[0052] Here, the input means may include a key button, a mouse, a joystick, a jog shuttle, a stylus pen, etc. In addition, the input means may include a soft key implemented on the display.

[0053] The output means may include a display, and may also include an audio output means such as a speaker. In this case, if a touch sensor such as a touch film, a touch sheet, or a touch pad is provided in the display, the display operates as a touch screen, and the input means and the output means may be implemented in an integrated form. In this case, the display may include at least one of a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), a flexible display, a field emission display (FED), and a 3D display.

[0054] The communication unit (130) may include a communication module that supports a communication interface with electrical components and / or control units installed in the vehicle. As an example, the communication module may be connected to a fuel cell stack (10) of the vehicle (or a system that manages information about the fuel cell stack) to receive information about the stack current and stack voltage of the fuel cell stack (10).

[0055] Here, the communication module may include a module that supports vehicle network communication such as CAN (Controller Area Network) communication, LIN (Local Interconnect Network) communication, and Flex-Ray communication.

[0056] Additionally, the communication unit (130) may include a communication module that supports a communication interface with an external device. As an example, the communication module may transmit the life prediction results of the fuel cell stack (10) of the vehicle to a vehicle management system that manages the status of the vehicle.

[0057] At this time, the communication module may include a module for wireless Internet access or a module for short-range communication. Here, wireless Internet technologies may include Wireless LAN (WLAN), Wireless Broadband (Wibro), Wi-Fi, and WiMAX (World Interoperability for Microwave Access, Wimax), and short-range communication technologies may include Bluetooth, ZigBee, UWB (Ultra Wideband), RFID (Radio Frequency Identification), and Infrared Data Association (IrDA).

[0058] The storage unit (140) can store data and / or algorithms necessary for the operation of the fuel cell life prediction device (100).

[0059] For example, the storage unit (140) may store information on the current and voltage of the unit cell (11) and the fuel cell stack (10) received through the communication unit (130). In addition, the storage unit (140) may store commands and / or algorithms for generating a life prediction model, and a cell deterioration prediction model (M1), a cell deterioration correction model (M2), and an integrated deterioration prediction model (M3) may also be stored.

[0060] In addition, the storage unit (140) may store commands and / or algorithms for predicting the life of the fuel cell stack (10), and the life prediction results of the fuel cell stack (10) using a life prediction model may also be stored.

[0061] Here, the storage unit (140) may include a storage medium such as a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), a programmable read-only memory (PROM), or an electrically erasable programmable read-only memory (EEPROM).

[0062] The information collection unit (150) collects the voltage (V) of the unit cell and the fuel cell stack (10) and stores it in the storage unit (140). The information collection unit (150) can collect current and voltage from the unit cell and the fuel cell stack (10) in real time, at a predetermined time cycle, or at an irregularly predetermined time.

[0063] The cell prediction model unit (160) extracts voltage information stored in the storage unit (140) and generates a cell degradation prediction model (M1) that defines a degradation pattern between the voltage and time of a unit cell (11). The cell prediction model unit (160) models an independent degradation pattern by individually predicting the degradation pattern of a unit cell (11).

[0064] The cell degradation prediction model (M1) can be modeled as a nonlinear stochastic process based on the relationship between accumulated voltage and time. The cell degradation prediction model (M1) can be developed as a nonlinear Wiener process that determines the relationship between voltage and time, and can be defined as shown in [Mathematical Equation 1] below.

[0065]

[0066] In [Mathematical Formula 1], i is an index for a unit cell, an integer greater than or equal to 1 and less than or equal to n; j is an arbitrary point in time, an integer greater than or equal to 1 and less than or equal to n; Y ij is time t ij Voltage at ; is the parameter γ i Transformation function for time; σ is the diffusion parameter; B(t ij) means Brownian motion.

[0067] For example, the cell prediction model unit (160) can define a cell degradation prediction model (M1) using the voltage of the accumulated unit cell (11) at each time point (1st to jth time point) that meets a predetermined condition, and store the model formula in the storage unit (140). Accordingly, the storage unit (140) stores the cell degradation prediction model (M1) for each of the i unit cells (11), and the cell degradation prediction model (M1) of each unit cell (11) can store a model generated at j time points.

[0068] The cell prediction correction unit (170) generates a cell degradation correction model (M2) that corrects the cell degradation prediction model (M1) to reflect the degree to which the degradation patterns of a plurality of unit cells (11) are mutually dependent. Specifically, the cell prediction correction unit (170) corrects the degradation patterns of a plurality of unit cells (11) to reflect the degree to which the degradation pattern of one unit cell is dependent on the degradation patterns of other unit cells, thereby improving the reliability of the life prediction of each unit cell (11).

[0069] The cell degradation correction model (M2) can correct the model to consider the dependency of the unit cells (11) within a fuel cell stack (10) through the correlation between the first difference values ​​of the actual cell degradation values ​​of multiple unit cells (11). The cell degradation correction model (M2) can be prepared as a copula model that considers the correlation between models, and can be defined as in [Mathematical Formula 2] below.

[0070]

[0071] In [Equation 2] represents the joint cumulative distribution between the first differences of the actual cell degradation values ​​modeled through the copula function C, is a transformation function of the first difference value of the actual cell degradation value at time j of the ith unit cell, and θ is a parameter that controls the correlation between the first difference values ​​of the actual cell degradation values.

[0072] Here, the cell prediction correction unit (170) generates a cell degradation correction model (M2) that derives a joint probability density function by characterizing the dependency between the peripheral density function and the peripheral distribution from the first difference value of multiple cell degradation values. Accordingly, the cell prediction correction unit (170) can define a cell degradation correction model (M2) that corrects the degradation pattern by reflecting the dependency between i unit cells and the remaining i-1 unit cells (11), and store the model formula in the storage unit.

[0073] The stack prediction model unit (180) generates an integrated degradation prediction model (M3) to define the degradation pattern of the fuel cell stack (10) based on the degradation patterns of a plurality of unit cells (11) corrected by the cell prediction correction unit (170).

[0074] The stack prediction model unit (180) models the integrated deterioration pattern of the fuel cell stack (10) based on the deterioration pattern of each unit cell (11) whose reliability has been improved by the cell deterioration correction model (M2). That is, the integrated deterioration prediction model (M3) can define the amount of change in voltage of the fuel cell stack (10) according to time change and store the model formula in the storage unit.

[0075] When a life prediction event occurs when a predetermined condition is satisfied or a user input signal, etc. occurs, the life prediction unit (190) calls the cell deterioration prediction model (M1), cell deterioration correction model (M2), and integrated deterioration prediction model (M3) stored in the storage unit (140).

[0076] The life prediction unit (190) can predict the life of each unit cell (11) through the called cell deterioration prediction model (M1) and cell deterioration correction model (M2) and output the time required for the predicted life to reach a predetermined deterioration judgment condition. In addition, the life prediction unit (190) can predict the life of the fuel cell stack through the called integrated deterioration prediction model (M3) and output the time required for the predicted life to reach a predetermined deterioration judgment condition.

[0077] The life prediction unit (190) can store the life prediction results of the unit cell (11) and the fuel cell stack (10) in the storage unit (140). In addition, the life prediction unit (190) can transmit the life prediction results of the unit cell (11) and the fuel cell stack (10) to a vehicle management system inside or outside the vehicle through the communication unit (130).

[0078] Accordingly, the fuel cell life prediction device (100) of the present invention can predict not only the life of the fuel cell stack (10), but also the life of each individual unit cell (11) within the stack, and thereby determine a failure of the unit cell and predict the replacement cycle.

[0079] FIG. 3 is a graph showing a deterioration pattern predicted by a cell deterioration prediction model (M1) of 18 unit cells in a cell prediction model section (160) of a fuel cell life prediction device of the present invention, and FIG. 4 is a graph showing a deterioration pattern of FIG. 3 corrected by a cell deterioration correction model (M2) to reflect the dependency between unit cells.

[0080] Referring to Fig. 3, in the case of an independent prediction model (M1) that does not consider the dependency between unit cells (11), the deterioration patterns of all 18 unit cells (11) move in the same pattern. On the other hand, referring to Fig. 4, in the case of a model (M2) that is corrected by considering the dependency between unit cells, it can be seen that the deterioration patterns of all 18 unit cells move in different patterns.

[0081] FIG. 5 shows an evaluation graph that predicts the life of a fuel cell without considering the dependency of the deterioration pattern of a unit cell using the fuel cell life prediction device of the present invention, and FIG. 6 shows an evaluation graph that predicts the life of a fuel cell by considering the dependency of the deterioration pattern of a unit cell using the fuel cell life prediction device of the present invention.

[0082] Referring to FIGS. 5 and 6, a cell degradation prediction model (M1) is generated that predicts a degradation pattern for up to 8,000 cycles or more based on voltage data of approximately 0 to 3,000 cycles of a unit cell. At this time, the criterion for determining a failure of a unit cell can be defined as when it reaches 0.9, which is a point where the unit cell has deteriorated by 10% compared to its initial voltage value.

[0083] Figure 7 is a graph showing a comparison of the predicted mean time to function (MTTF) when considering the dependency of the deterioration pattern of the most deteriorated unit cell in the fuel cell of the present invention and when considering it.

[0084] Referring to Fig. 7, when the dependency of the unit cell degradation pattern is not taken into account, a failure is predicted to occur at approximately 6115 cycles. On the other hand, when the dependency of the unit cell degradation pattern is taken into account, a failure is predicted to occur at approximately 6092 cycles.

[0085] Here, when considering the dependency of the deterioration pattern of the unit cell, the confidence interval (length) was estimated to be narrower than when not considering the dependency of the deterioration pattern of the unit cell, which means that the reliability of the prediction of the mean time to function (MTTF) is improved when considering the dependency of the deterioration pattern of the unit cell.

[0086] Below, a method for predicting the life of a fuel cell according to an embodiment of the present invention is described.

[0087] FIG. 8 is a diagram illustrating an operation flow for a fuel cell life prediction method according to one embodiment of the present invention.

[0088] Referring to FIG. 8, the fuel cell life prediction method (S100) includes an information collection step (S110) of measuring the voltage of each of a plurality of unit cells (11) provided in a fuel cell stack (10), a cell prediction step (S120) of generating a cell deterioration prediction model (M1) to define a deterioration pattern of each unit cell (11) based on the voltage measured in the unit cell (11), a cell prediction correction step (S130) of generating a cell deterioration correction model (M2) that corrects the dependence of the deterioration pattern of one unit cell (11) among the deterioration patterns of the plurality of unit cells (11) on the deterioration patterns of other unit cells, a stack prediction step (S140) of generating an integrated deterioration prediction model to define the deterioration pattern of the fuel cell stack (10) based on the cell deterioration correction model (M2), and predicting the life of each unit cell based on the cell deterioration correction model (M2). The predicted lifespan may include a life prediction step (S150) that outputs the time required until the failure determination condition is reached. In addition, the lifespan prediction step (S150) may further include a feature that predicts the lifespan of the fuel cell stack (10) based on the integrated deterioration prediction model (M3) and outputs the time required until the failure determination condition is reached based on the predicted lifespan.

[0089] The disclosed embodiments have been described with reference to the attached drawings as described above. Those skilled in the art will understand that the present invention can be implemented in forms other than the disclosed embodiments without altering the technical spirit or essential features of the present invention. The disclosed embodiments are illustrative and should not be construed as limiting.

Claims

1. An information collection unit that measures the voltage of each of a plurality of unit cells provided in a fuel cell stack; A cell prediction model unit that generates a cell degradation prediction model to define a degradation pattern of each unit cell based on the voltage measured from the unit cell; A cell prediction correction unit that generates a cell degradation correction model that corrects the degradation pattern to reflect the dependency of the degradation pattern of one unit cell among the degradation patterns of the plurality of unit cells on the degradation patterns of other unit cells; and A fuel cell life prediction device including a life prediction unit that predicts the life of each unit cell based on the cell deterioration compensation model and outputs the time required for the predicted life to reach a failure judgment condition.

2. In paragraph 1, A fuel cell life prediction device further comprising a stack prediction model unit that generates an integrated deterioration prediction model to define a deterioration pattern of the fuel cell stack based on the deterioration patterns of the plurality of unit cells corrected by the cell prediction correction unit.

3. In paragraph 2, The above life prediction section A fuel cell life prediction device that predicts the life of the fuel cell stack based on the integrated deterioration prediction model and outputs the time required for the predicted life to reach a deterioration judgment condition.

4. In paragraph 1, The above cell prediction model part A fuel cell life prediction device characterized by defining a cell deterioration prediction model as in the following [Mathematical Formula 1]. [Mathematical Formula 1] (Here, i is an index for a unit cell, an integer greater than or equal to 1 and less than or equal to n; j is an arbitrary point in time, an integer greater than or equal to 1 and less than or equal to n; Y ij is time t ij Voltage at ; is the parameter γ i Transformation function for time; σ is the diffusion parameter; B(t ij ) stands for Brownian motion) 5. In paragraph 4, The above cell prediction correction unit A fuel cell life prediction device characterized by correcting a deterioration pattern as in [Mathematical Formula 2] below. [Mathematical formula 2] (here represents the joint cumulative distribution between the first differences of the actual cell degradation values ​​modeled by the copula function C, is a transformation function of the first difference value of the actual cell degradation value at time j of the i-th unit cell, and θ is a parameter that controls the correlation between the first difference values ​​of the actual cell degradation values.

6. In paragraph 1, A fuel cell life prediction device further comprising a storage unit that stores information about the voltage measured by the information collection unit, the cell deterioration prediction model generated by the cell prediction model unit, and the cell deterioration correction model generated by the cell prediction correction unit.

7. An information collection unit that measures the voltage of each of a plurality of unit cells provided in a fuel cell stack; A cell prediction model unit that predicts the deterioration pattern of each unit cell based on the voltage measured in the unit cell; A cell prediction correction unit that corrects the degradation pattern to reflect the mutual dependency of the above multiple unit cell degradation patterns; A stack prediction model unit that predicts the deterioration pattern of the fuel cell stack based on the above-mentioned corrected deterioration pattern; and A fuel cell life prediction device including a life prediction unit that predicts the life of each of the unit cell and the fuel cell stack based on the corrected deterioration pattern of the unit cell and the deterioration pattern of the fuel cell stack.

8. Information collection step of measuring the voltage of each of the multiple unit cells provided in the fuel cell stack; A cell prediction step for generating a cell degradation prediction model to define a degradation pattern of each unit cell based on the voltage measured in the unit cell; A cell prediction correction step for generating a cell degradation correction model that corrects the dependency of the degradation pattern of one unit cell among the degradation patterns of the plurality of unit cells on the degradation patterns of other unit cells; and A fuel cell life prediction method, comprising: a life prediction step for predicting the life of each unit cell based on the cell deterioration compensation model and outputting the time required for the predicted life to reach a failure judgment condition.

9. In paragraph 8, A fuel cell life prediction method further comprising a stack prediction step of generating an integrated deterioration prediction model to define a deterioration pattern of the fuel cell stack based on the cell deterioration correction model.

10. In paragraph 9, The above life prediction steps are A fuel cell life prediction method further comprising a feature of predicting the life of the fuel cell stack based on the integrated deterioration prediction model and outputting the time required for the predicted life to reach a failure determination condition.

11. In paragraph 8, The above cell prediction step is, A fuel cell life prediction method characterized by defining a cell deterioration prediction model as in the following [Mathematical Formula 1]. [Mathematical Formula 1] (Here, i is an index for a unit cell, an integer greater than or equal to 1 and less than or equal to n; j is an arbitrary point in time, an integer greater than or equal to 1 and less than or equal to n; Y ij is time t ij Voltage at ; is the parameter γ i Transformation function for time; σ is the diffusion parameter; B(t ij ) stands for Brownian motion) 12. In the above paragraph 11, The above cell prediction correction step is A fuel cell life prediction method characterized by correcting a deterioration pattern as in [Mathematical Formula 2] below. [Mathematical formula 2] (here represents the joint cumulative distribution between the first differences of the actual cell degradation values ​​modeled by the copula function C, is a transformation function of the first difference value of the actual cell degradation value at time j of the i-th unit cell, and θ is a parameter that controls the correlation between the first difference values ​​of the actual cell degradation values.

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