Method for estimating internal temperature of reversible solid oxide battery

Abstract

The invention relates to a reversible solid oxide battery internal temperature estimation method, and belongs to the technical field of new energy, and the method comprises the steps: constructing a solid layer temperature dynamic model of a reversible solid oxide battery; the temperature of fuel entering and exiting the reversible solid oxide battery and the temperature of air entering and exiting the reversible solid oxide battery serve as additional states; constructing a continuous system state-space equation based on the solid layer temperature dynamic model and the additional state, and constructing an extended Kalman filtering observer; and obtaining measurement data of the target reversible solid oxide battery, and inputting the measurement data into the Kalman filtering observer to obtain an internal average temperature estimation value of the target reversible solid oxide battery. According to the method, the solid layer temperature dynamic model is constructed, and the extended Kalman filter observer is constructed based on the solid layer temperature dynamic model, so that the internal average temperature of the reversible solid oxide battery is estimated, and the problem that the internal temperature of the reversible solid oxide battery is difficult to directly measure is solved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a method for estimating the internal temperature of a reversible solid oxide battery. Background Art

[0002] The technical channel formed by the combination of fuel cells, electrolysis and hydrogen energy has opened up the channel for renewable green energy to replace traditional fossil energy, and is a perfect solution for achieving sustainable energy. Hydrogen is an important chemical raw material with the characteristics of convenient long-distance transportation and large-scale storage. Combining fuel cells and electric hydrogen production technology to achieve the exchange of hydrogen energy and electric energy can effectively solve the volatility, randomness and intermittency of renewable energy such as solar energy, wind energy and hydropower.

[0003] Reversible Solid Oxide Cell (rSOC) is an energy conversion device based on the round-trip operation of high-temperature solid oxide cells. It can convert electrical energy into hydrogen energy in fuel cell mode and convert hydrogen energy back into electrical energy in electrolyzer mode. Therefore, the large-scale application of rSOC plays a key role in realizing the energy network supported by hydrogen energy.

[0004] High temperature operation (generally between 600-900°C) poses many challenges to the long life of rSOC. There is a strong coupling relationship between the thermal-electrical-gas dynamics within the rSOC. When the rSOC temperature is too low, it cannot achieve high performance output state, while higher temperatures will cause the durability of the material to be damaged and the operating life to be insufficient.

[0005] Controlling the operating temperature of rSOC within a suitable range is very important for its high performance and long life. To control and manage the temperature of rSOC, its internal temperature must be obtained first. However, rSOC has strict airtightness requirements, and it is very costly to directly measure its internal temperature through sensors. Summary of the invention

[0006] In view of this, it is necessary to provide a method for estimating the internal temperature of a reversible solid oxide battery to solve the problem of high cost caused by directly measuring the internal temperature of the rSOC through a sensor in the prior art.

[0007] In order to solve the above problems, the present invention provides a method for estimating the internal temperature of a reversible solid oxide battery, comprising: Construct a temperature dynamic model of the solid layer of a reversible solid oxide battery; The temperature of the fuel entering and exiting the reversible solid oxide cell and the temperature of the air entering and exiting the reversible solid oxide cell are used as additional states; Constructing a continuous system state space equation based on the solid layer temperature dynamic model and the additional state; Constructing an extended Kalman filter observer based on the continuous system state space equation; The measurement data of the target reversible solid oxide battery is obtained, and the measurement data is input into the Kalman filter observer to obtain an estimated value of the average internal temperature of the target reversible solid oxide battery.

[0008] In a possible implementation, the measurement data includes: The temperature of the air entering the reversible solid oxide cell, the temperature of the fuel entering the reversible solid oxide cell, the voltage of the reversible solid oxide cell, the current of the reversible solid oxide cell, the inlet fuel flow rate, the inlet air flow rate, the fuel pressure and the air pressure.

[0009] In a possible implementation, the solid layer temperature dynamic model is a solid layer average temperature dynamic model, and the expression of the solid layer average temperature dynamic model is:

[0010] In the formula, represents the heat capacity of the reversible solid oxide battery; represents the average temperature of the solid layer of the reversible solid oxide battery; represents the voltage of the reversible solid oxide battery; represents the current of the reversible solid oxide battery; It indicates the enthalpy change of the electrochemical reaction process inside the reversible solid oxide battery; represents the power transferred from the reversible solid oxide cell to the air by convection heat transfer; represents the power transferred from the reversible solid oxide cell to the fuel by convective heat transfer;

[0011] in, represents the formation enthalpy of hydrogen; represents the formation enthalpy of water; represents the formation enthalpy of oxygen; represents the temperature of the fuel entering the reversible solid oxide cell; represents the temperature of the fuel entering the reversible solid oxide cell; represents the temperature of the reversible solid oxide cell fuel; represents the Faraday constant;

[0012]

[0013] in, represents the average convective heat transfer coefficient between the reversible solid oxide cell and the fuel; represents the average convective heat transfer coefficient between the reversible solid oxide cell and air; represents the effective heat transfer area; represents the average temperature of fuel entering and leaving the reversible solid oxide cell; represents the average temperature of the air entering and leaving the reversible solid oxide cell;

[0014]

[0015] in, Represents the temperature of the air in the reversible solid oxide cell.

[0016] In a possible implementation, constructing a continuous system state space equation based on the solid layer temperature dynamic model and the additional state includes: Obtaining parameters of the solid layer temperature dynamic model; A continuous system state space equation is constructed based on the parameters and the additional state.

[0017] In a possible implementation manner, obtaining the parameters of the solid layer temperature dynamic model includes: The parameters are obtained by identifying experimental data or calculating them by theoretical methods.

[0018] In a possible implementation, the parameters of the solid layer temperature dynamic model include the heat capacity of the reversible solid oxide cell, the first average convective heat transfer coefficient between the reversible solid oxide cell and the air, and the second average convective heat transfer coefficient between the reversible solid oxide cell and the fuel. The parameters calculated by the theoretical method include: The calculation formula of the heat capacity of the reversible solid oxide battery is:

[0019] In the formula, represents the specific heat capacity of the reversible solid oxide battery; represents the mass of the reversible solid oxide battery; The calculation formulas of the first average convective heat transfer coefficient and the second average convective heat transfer coefficient are:

[0020] in, represents the first average convection heat transfer coefficient; represents the second average convection heat transfer coefficient; represents the Nusselt number of the flow channel; Represents the characteristic length of the flow channel; represents the average heat transfer coefficient of gas 'i';

[0021] in, Indicates the width of the rectangular flow channel; Indicates the height of the rectangular flow channel;

[0022] in, represents the thermal conductivity of the mixed gas ‘i’; represents the mole fraction of gas 'k'; represents the thermal conductivity of the gas 'k'; represents the mole fraction of gas 'm'; represents a coefficient whose value depends on the thermal conductivity and molecular mass of the gas involved;

[0023] in, represents the thermal conductivity of the gas 'k'; represents the thermal conductivity of the gas 'm'; represents the molecular mass of gas 'k'; represents the molecular mass of the gas 'm'.

[0024] In a possible implementation, the obtaining of parameters through experimental data identification includes: Get the measurement data at the current moment; The measurement data at the current moment is input into the preset equation to correct the parameter until the temporary measurement data output by the preset equation and the measurement data at the current moment are within a preset range, thereby obtaining the parameter.

[0025] In a possible implementation, constructing an extended Kalman filter observer based on the continuous system state space equation includes: Discretizing the continuous system state space equation to obtain a discrete system state space model; An extended Kalman filter observer is obtained based on the discrete system state space model.

[0026] In a possible implementation, the continuous system state space equation is expressed as:

[0027] In the formula, ; ; , T represents matrix transpose; represents a continuous function vector; The expression of the discrete system state space model is:

[0028] in, and Respectively represent Moment and The state vector at the moment; represents the state transfer function vector, ; represents process noise; represents the observation noise; Indicates the sampling time; Indicates measurement data.

[0029] In a possible implementation, obtaining an extended Kalman filter observer based on the discrete system state space model includes: Set the state estimate and covariance at the initial moment; Based on the state estimate and covariance at the initial moment, the predicted state estimate and predicted covariance at the current moment are predicted according to the state estimate at the previous moment, the state covariance at the previous moment, and the control input value at the previous moment; Obtain measurement data; The extended Kalman filter observer is obtained by updating the residual, residual covariance, Kalman gain, state estimate and covariance based on the measurement data, the predicted state estimate at the current moment and the predicted covariance at the current moment.

[0030] The beneficial effects of the present invention are as follows: a method for estimating the internal temperature of a reversible solid oxide cell provided by the present invention first constructs a solid layer temperature dynamic model of the reversible solid oxide cell, then takes the fuel temperature entering and exiting the reversible solid oxide cell and the air temperature entering and exiting the reversible solid oxide cell as additional states, further constructs a continuous system state space equation based on the solid layer temperature dynamic model and the additional states, further constructs an extended Kalman filter observer based on the continuous system state space equation to predict the estimated value of the internal average temperature of the reversible solid oxide cell, and finally obtains the measurement data of the target reversible solid oxide cell, and inputs the measurement data into the Kalman filter observer to obtain the estimated value of the internal average temperature of the target reversible solid oxide cell. The present invention estimates the internal average temperature of the reversible solid oxide cell by constructing a solid layer temperature dynamic model, and further constructs an extended Kalman filter observer based on the solid layer temperature dynamic model, thereby solving the problem that the internal temperature of the reversible solid oxide cell cannot be directly measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A flow chart of an embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Figure 2 A flowchart of a specific embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Figure 3 A structural diagram of a reversible solid oxide battery provided by the present invention; Figure 4 For the present invention Figure 1 A schematic flow chart of an embodiment of S103; Figure 5 For the present invention Figure 1 A schematic flow chart of an embodiment of S104; Figure 6 A calculation flow chart of an extended Kalman filter observer for an embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Figure 7 A diagram showing the effect of estimating the internal temperature of a reversible solid oxide battery in one embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Figure 8 A diagram of voltage and current measurement signals of a reversible solid oxide battery in one embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Fig. 9 A reversible solid oxide battery inlet measured temperature map in one embodiment of a reversible solid oxide battery internal temperature estimation method provided by the present invention; Fig.10 The outlet measurement temperature of the reversible solid oxide battery provided by the present invention is a graph showing the estimated rSOC temperature of this embodiment and the actual rSOC average temperature; Fig.11 A schematic flow chart of an embodiment of a device for estimating the internal temperature of a reversible solid oxide battery provided by the present invention; Fig.12 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0032] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0033] Before presenting the embodiments, the following terms are explained.

[0034] Reversible Solid Oxide Cell (rSOC) is a new type of energy conversion device that integrates solid oxide fuel cell (SOFC) and solid oxide electrolysis cell (SOEC). By switching between FC and EC modes, it can achieve efficient and flexible energy conversion and storage.

[0035] The present invention provides a method for estimating the internal temperature of a reversible solid oxide battery, which is described below.

[0036] Figure 1 A schematic flow chart of an embodiment of a method for estimating the internal temperature of a reversible solid oxide battery provided by the present invention is shown in FIG. Figure 1 As shown, a method for estimating the internal temperature of a reversible solid oxide battery comprises: S101. Construct a solid layer temperature dynamic model of a reversible solid oxide battery; S102, taking the temperature of the fuel entering and exiting the reversible solid oxide cell and the temperature of the air entering and exiting the reversible solid oxide cell as additional states; S103, constructing a continuous system state space equation based on the solid layer temperature dynamic model and the additional state; S104, constructing an extended Kalman filter observer based on the continuous system state space equation; S105, obtaining measurement data of the target reversible solid oxide battery, and inputting the measurement data into the Kalman filter observer to obtain an estimated value of the average internal temperature of the target reversible solid oxide battery.

[0037] Compared with the prior art, the present embodiment provides a method for estimating the internal temperature of a reversible solid oxide cell. First, a dynamic model of the solid layer temperature of the reversible solid oxide cell is constructed. Then, the fuel temperature entering and exiting the reversible solid oxide cell and the air temperature entering and exiting the reversible solid oxide cell are used as additional states. A continuous system state space equation is further constructed based on the solid layer temperature dynamic model and the additional state. An extended Kalman filter observer is further constructed based on the continuous system state space equation to predict the estimated value of the internal average temperature of the reversible solid oxide cell. Finally, the measurement data of the target reversible solid oxide cell is obtained, and the measurement data is input into the Kalman filter observer to obtain the estimated value of the internal average temperature of the target reversible solid oxide cell. The present invention estimates the internal average temperature of the reversible solid oxide cell by constructing a dynamic model of the solid layer temperature and further constructing an extended Kalman filter observer based on the solid layer temperature dynamic model, thereby solving the problem that the internal temperature of the reversible solid oxide cell is difficult to measure directly.

[0038] In some embodiments of the present invention, the measurement data includes: The temperature of the air entering the reversible solid oxide cell, the temperature of the fuel entering the reversible solid oxide cell, the voltage of the reversible solid oxide cell, the current of the reversible solid oxide cell, the inlet fuel flow rate, the inlet air flow rate, the fuel pressure and the air pressure.

[0039] In some embodiments of the present invention, in step S101, a solid layer temperature dynamic model of a reversible solid oxide battery is constructed, such as Figure 2 As shown, specifically including: like Figure 3 The structural diagram of the reversible solid oxide battery shown in the figure is used to establish the rSOC model, and a mechanism modeling method is adopted, including a thermal dynamic model. It is assumed that the heat transfer process in the thermal dynamic model is average temperature difference heat transfer, and other characteristics are quasi-static. Among them, the thermal dynamic model includes: a solid layer temperature dynamic model. In principle, the rSOC stack is formed by stacking multiple single-chip rSOC battery cells. In terms of electrical characteristics, it is equivalent to a series structure, and in terms of airflow distribution, it is equivalent to a parallel structure. The dynamic characteristics of each rSOC single cell in the rSOC stack can be regarded as consistent, and the model for single-chip rSOC can also be applied to the rSOC stack. The following modeling process is for single-chip rSOC.

[0040] The average temperature of air and fuel inside rSOC is recorded as and , the average solid temperature inside rSOC is recorded as ; The average temperature of the air and fuel inside the rSOC is calculated by measuring the fuel and air inlet and outlet temperatures, , ; Air temperature in and out of rSOC and , and the fuel temperature in and out of rSOC and All can be measured by sensors.

[0041] Due to the closed nature of the rSOC stack, the average temperature inside the rSOC It is difficult to measure directly by sensors. According to the law of energy conservation, the expression of the dynamic model of the average temperature of the solid layer is:

[0042] In the formula, represents the heat capacity of the reversible solid oxide battery; represents the voltage of the reversible solid oxide battery; Represents the current of the reversible solid oxide battery. When the current When rSOC is in fuel cell mode, hydrogen and oxygen are consumed and the energy released in the process is converted into electrical energy. When it is negative, it works in electrolyzer mode, consuming electrical energy and producing hydrogen and oxygen; It indicates the enthalpy change of the electrochemical reaction process inside the reversible solid oxide battery; represents the power transferred from the reversible solid oxide cell to the air by convection heat transfer; represents the power transferred from the reversible solid oxide cell to the fuel by convective heat transfer;

[0043] in, represents the formation enthalpy of hydrogen; represents the formation enthalpy of water; represents the formation enthalpy of oxygen; represents the temperature of the fuel entering the reversible solid oxide cell; represents the temperature of the fuel entering the reversible solid oxide cell; represents the temperature of the reversible solid oxide cell fuel; It represents the Faraday constant, with a value of 96485.3 and a unit of C / mol;

[0044]

[0045] in, represents the average convective heat transfer coefficient between the reversible solid oxide cell and the fuel; represents the average convective heat transfer coefficient between the reversible solid oxide cell and air; represents the effective heat transfer area; represents the average temperature of fuel entering and leaving the reversible solid oxide cell; represents the average temperature of the air entering and leaving the reversible solid oxide cell;

[0046]

[0047] in, Represents the temperature of the air in the reversible solid oxide cell.

[0048] In some embodiments of the present invention, after obtaining the solid layer temperature dynamic model, it is necessary to obtain the parameters of the solid layer temperature dynamic model. Specifically, obtaining the parameters of the solid layer temperature dynamic model includes: The parameters are obtained by identifying experimental data or calculating them by theoretical methods.

[0049] Specifically, the parameters of the solid layer temperature dynamic model are identified based on the experimental data. The parameters of the solid layer temperature dynamic model include: the heat capacity of rSOC, , unit J / K; average convective heat transfer coefficient between rSOC and fuel, , unit W / (m 2 K); the average convective heat transfer coefficient between rSOC and air, , unit W / (m 2 K).

[0050] In some embodiments of the present invention, the parameters of the solid layer temperature dynamic model include the heat capacity of the reversible solid oxide cell, the first average convection heat transfer coefficient between the reversible solid oxide cell and the air, and the second average convection heat transfer coefficient between the reversible solid oxide cell and the fuel. The parameters calculated by the theoretical method include: The calculation formula of the heat capacity of the reversible solid oxide battery is:

[0051] In the formula, represents the specific heat capacity of the reversible solid oxide battery; represents the mass of the reversible solid oxide battery; The calculation formulas of the first average convective heat transfer coefficient and the second average convective heat transfer coefficient are:

[0052] in, represents the first average convection heat transfer coefficient; represents the second average convection heat transfer coefficient; represents the Nusselt number of the flow channel; Represents the characteristic length of the flow channel; represents the average heat transfer coefficient of gas 'i';

[0053] in, Indicates the width of the rectangular flow channel; Indicates the height of the rectangular flow channel;

[0054] in, represents the thermal conductivity of the mixed gas 'i' (unit: W / (mK)), , when the mixed gas is the fuel (ie: ), the gases involved are hydrogen, water vapor (ie: ), when the mixed gas is air (ie: ), the gases involved are oxygen and nitrogen (ie: ); represents the mole fraction of gas 'k'; represents the thermal conductivity of the gas 'k'; represents the mole fraction of gas 'm'; represents a coefficient whose value depends on the thermal conductivity and molecular mass of the gas involved;

[0055] in, represents the thermal conductivity of the gas 'k'; represents the thermal conductivity of gas 'm'; represents the molecular mass of gas 'k' (unit: kg / mol); Indicates the molecular mass of the gas 'm' (unit: kg / mol).

[0056] In some embodiments of the present invention, the parameters obtained by identifying experimental data include: Get the measurement data at the current moment; The measurement data at the current moment is input into the preset equation to correct the parameter until the temporary measurement data output by the preset equation and the measurement data at the current moment are within a preset range, thereby obtaining the parameter.

[0057] Specifically, the parameters are obtained through experimental data identification using the actual measured inlet temperature and ,Voltage , Current , inlet fuel flow , Inlet air flow , fuel and air pressure and , input the actual measured signal into the following equation, and repeat the cycle by constantly correcting the rSOC parameters until the output of this equation is the outlet air and fuel temperature and The deviation from the actual measured outlet temperature is within the preset range, and the simplified model parameters are identified. The specific equation is as follows:

[0058] in, and They represent the heat capacity of the air and fuel in the flow channel, respectively, in W / K; and They represent the enthalpy flux of the fuel at the inlet and outlet of rSOC, respectively, in W; and They represent the heat enthalpy flux of air at the inlet and outlet of rSOC, in W; Heat capacity of air and fuel and Calculated as follows:

[0059] in, and Respectively represent the volume of the air flow channel and the fuel flow channel, unit m 3 ; and Respectively represent the pressure of air and fuel, unit is Pa, which can be directly obtained by sensors; The gas constant is 8.3145, in J / (K mol); and They represent the isobaric heat capacity of air and fuel in the flow channel, respectively, in J / (Kmol), and they are calculated by theoretical method.

[0060] Enthalpy flux of gas 'i' at position 'j' and the isobaric heat capacity of gas 'i' Calculate it as follows ( , ):

[0061]

[0062] in and They represent the molar flow rate (in mol / s) of gas 'i' at position 'j' and the molar fraction of gas species 'k', i.e. , for fuel , for air .

[0063] rSOC uses a mixture of hydrogen and water vapor to enter the hydrogen electrode flow channel; air is introduced into the air electrode side; the dynamic process of gas is much faster than the dynamic process of temperature. Assuming that it reaches a steady state, the inlet and outlet gases on the fuel side and the air side have the following relationship: Fuel side:

[0064] Air side:

[0065] In some embodiments of the present invention, Figure 4 As shown, in step S103, the continuous system state space equation is constructed based on the solid layer temperature dynamic model and the additional state, including: S401, obtaining parameters of the solid layer temperature dynamic model; S402: construct a continuous system state space equation based on the parameters and the additional state.

[0066] In some embodiments of the present invention, Figure 5 As shown, in step S104, constructing an extended Kalman filter observer based on the continuous system state space equation includes: S501, discretizing the continuous system state space equation to obtain a discrete system state space model; S502: Obtain an extended Kalman filter observer based on the discrete system state space model.

[0067] In order to use the measurable fuel and air inlet and outlet temperatures to dynamically estimate the unmeasurable rSOC average temperature, the solid layer average temperature model is used as one of the state transfer equations. In addition, the fuel and air inlet and outlet temperatures are added as additional states, and their derivatives are set to zero, that is: , , , In some embodiments of the present invention, the expression of the continuous system state space equation is:

[0068] In the formula, ; ; , T represents matrix transpose; represents a continuous function vector; The forward Euler method is used to discretize the continuous-time state space equation model, namely: The sampling time is , and adding process noise and measurement noise, the expression of the discrete system state space model is:

[0069] in, and Respectively represent Moment and The state vector at the moment; represents the state transfer function vector, ; represents process noise; denotes the observation noise; they are assumed to have zero mean and covariance and The multivariate Gaussian noise is: , ; Indicates the sampling time; Indicates measurement data.

[0070] In some embodiments of the present invention, in step S104, obtaining an extended Kalman filter observer based on the discrete system state space model includes: Set the state estimate and covariance at the initial moment; Based on the state estimate and covariance at the initial moment, the predicted state estimate and predicted covariance at the current moment are predicted according to the state estimate at the previous moment, the state covariance at the previous moment, and the control input value at the previous moment; Obtain measurement data; The extended Kalman filter observer is obtained by updating the residual, residual covariance, Kalman gain, state estimate and covariance based on the measurement data, the predicted state estimate at the current moment and the predicted covariance at the current moment.

[0071] In a specific embodiment of the present invention, Figure 6 As shown, in step S104, the extended Kalman filter observer is obtained based on the discrete system state space model, specifically including: Initialization: Set the state estimate at the initial moment and its covariance .

[0072] Prediction: For each moment , the last moment The estimated value of the state , state estimation covariance , control input value All are known, and the following prediction process is performed: (Forecast state estimate)

[0073] (Forecast Covariance)

[0074] Update: For every moment , when the measurement information When available, the update process is performed as follows, (Calculate residuals)

[0075] (Calculate residual covariance)

[0076] (Calculate Kalman gain)

[0077] (Update state estimate)

[0078] (Update covariance)

[0079] In the above process, the state transfer matrix and observation matrix are as follows:

[0080]

[0081] in, Create a function for a diagonal matrix and enter the diagonal elements to construct a diagonal matrix.

[0082] After obtaining the extended Kalman filter observer, the measurement data such as the external inlet and outlet temperature, operating voltage, and current of the rSOC are collected and input into the extended Kalman filter observer. After the extended Kalman filter observer is operated, the estimated value of the average internal temperature of the rSOC is obtained.

[0083] In addition, in order to more intuitively illustrate the effect of this embodiment, as shown in FIG. Figures 7 to 10 As shown, the effect of the internal temperature estimation of the present invention is demonstrated. The measured current, voltage, and inlet and outlet temperatures of the fuel and air are all changing, wherein rSOC works in the fuel cell mode when the current is positive, and works in the electrolyzer mode when the current is negative. Fig.10 It shows that the method provided by the present invention can effectively estimate the average internal temperature of rSOC.

[0084] In order to better implement a method for estimating the internal temperature of a reversible solid oxide battery in an embodiment of the present invention, based on a method for estimating the internal temperature of a reversible solid oxide battery, correspondingly, as Fig.11 As shown, an embodiment of the present invention further provides a device for estimating the internal temperature of a reversible solid oxide battery. A device for estimating the internal temperature of a reversible solid oxide battery 700 includes: A dynamic model building module 1101 is used to build a solid layer temperature dynamic model of a reversible solid oxide battery; An additional state acquisition module 1102, for taking the temperature of the fuel entering and exiting the reversible solid oxide cell and the temperature of the air entering and exiting the reversible solid oxide cell as additional states; A system state space equation construction module 1103 is used to construct a continuous system state space equation based on the solid layer temperature dynamic model and the additional state; A Kalman filter observer acquisition module 1104 is used to construct a Kalman filter observer based on the continuous system state space equation; The average temperature estimation module 1105 is used to obtain the measurement data of the target reversible solid oxide battery, and input the measurement data into the Kalman filter observer to obtain the estimated value of the internal average temperature of the target reversible solid oxide battery.

[0085] The reversible solid oxide battery internal temperature estimation device 1100 provided in the above embodiment can implement the technical solution described in the above embodiment of a reversible solid oxide battery internal temperature estimation method. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above embodiment of a reversible solid oxide battery internal temperature estimation method, which will not be repeated here.

[0086] like Fig.12 As shown, the present invention also provides an electronic device 1200. The electronic device 1200 includes a processor 1201, a memory 1202 and a display 1203. Fig.12 Only some components of the electronic device 1200 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0087] In some embodiments, the processor 1201 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 1202, such as a reversible solid oxide battery internal temperature estimation method in the present invention.

[0088] In some embodiments, processor 1201 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, processor 1201 may be local or remote. In some embodiments, processor 1201 may be implemented in a cloud platform. In some embodiments, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0089] In some embodiments, the memory 1202 may be an internal storage unit of the electronic device 1200, such as a hard disk or memory of the electronic device 1200. In other embodiments, the memory 1202 may also be an external storage device of the electronic device 1200, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 1200.

[0090] Furthermore, the memory 1202 may include both an internal storage unit of the electronic device 1200 and an external storage device. The memory 1202 is used to store application software installed in the electronic device 1200 and various data.

[0091] In some embodiments, the display 1203 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 1203 is used to display information on the electronic device 1200 and to display a visual user interface. The components 1201-1203 of the electronic device 1200 communicate with each other via a system bus.

[0092] In one embodiment, when the processor 1201 executes a reversible solid oxide battery internal temperature estimation program in the memory 1202, the following steps may be implemented: Construct a temperature dynamic model of the solid layer of a reversible solid oxide battery; The temperature of the fuel entering and exiting the reversible solid oxide cell and the temperature of the air entering and exiting the reversible solid oxide cell are used as additional states; Constructing a continuous system state space equation based on the solid layer temperature dynamic model and the additional state; Constructing an extended Kalman filter observer based on the continuous system state space equation; The measurement data of the target reversible solid oxide battery is obtained, and the measurement data is input into the Kalman filter observer to obtain an estimated value of the average internal temperature of the target reversible solid oxide battery.

[0093] It should be understood that: when the processor 1201 executes a reversible solid oxide battery internal temperature estimation program in the memory 1202, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0094] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 1200 mentioned, and the electronic device 1200 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 1200 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0095] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0096] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for estimating the internal temperature of a reversible solid oxide battery, characterized in that: include: Construct a temperature dynamic model of the solid layer of a reversible solid oxide battery; The temperature of the fuel entering and exiting the reversible solid oxide cell and the temperature of the air entering and exiting the reversible solid oxide cell are used as additional states; Constructing a continuous system state space equation based on the solid layer temperature dynamic model and the additional state; Constructing an extended Kalman filter observer based on the continuous system state space equation; The measurement data of the target reversible solid oxide battery is obtained, and the measurement data is input into the extended Kalman filter observer to obtain an estimated value of the average internal temperature of the target reversible solid oxide battery.

2. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 1, characterized in that: The measurement data include: The temperature of the air entering the reversible solid oxide cell, the temperature of the fuel entering the reversible solid oxide cell, the voltage of the reversible solid oxide cell, the current of the reversible solid oxide cell, the inlet fuel flow rate, the inlet air flow rate, the fuel pressure and the air pressure.

3. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 1, characterized in that: The solid layer temperature dynamic model is a solid layer average temperature dynamic model, and the expression of the solid layer average temperature dynamic model is: In the formula, represents the heat capacity of the reversible solid oxide battery; represents the average temperature of the solid layer of the reversible solid oxide battery; represents the voltage of the reversible solid oxide battery; represents the current of the reversible solid oxide battery; It indicates the enthalpy change of the electrochemical reaction process inside the reversible solid oxide battery; represents the power transferred from the reversible solid oxide cell to the air by convection heat transfer; represents the power transferred from the reversible solid oxide cell to the fuel by convective heat transfer; in, represents the formation enthalpy of hydrogen; represents the enthalpy of formation of water; represents the formation enthalpy of oxygen; represents the temperature of the fuel entering the reversible solid oxide cell; represents the temperature of the air entering the reversible solid oxide cell; represents the temperature of the reversible solid oxide cell fuel; represents the Faraday constant; in, represents the average convective heat transfer coefficient between the reversible solid oxide cell and the fuel; represents the average convective heat transfer coefficient between the reversible solid oxide cell and air; represents the effective heat transfer area; represents the average temperature of fuel entering and leaving the reversible solid oxide cell; represents the average temperature of the air entering and leaving the reversible solid oxide cell; in, Represents the temperature of the air in the reversible solid oxide cell.

4. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 2, characterized in that: The constructing of a continuous system state space equation based on the solid layer temperature dynamic model and the additional state comprises: Obtaining parameters of the solid layer temperature dynamic model; A continuous system state space equation is constructed based on the parameters and the additional state.

5. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 4, characterized in that: The step of obtaining the parameters of the solid layer temperature dynamic model comprises: The parameters are obtained by identifying experimental data or calculating them by theoretical methods.

6. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 5, characterized in that: The parameters of the solid layer temperature dynamic model include the heat capacity of the reversible solid oxide cell, the first average convection heat transfer coefficient between the reversible solid oxide cell and the air, and the second average convection heat transfer coefficient between the reversible solid oxide cell and the fuel. The parameters calculated by the theoretical method include: The calculation formula of the heat capacity of the reversible solid oxide battery is: In the formula, represents the specific heat capacity of the reversible solid oxide battery; represents the mass of the reversible solid oxide battery; The calculation formulas of the first average convective heat transfer coefficient and the second average convective heat transfer coefficient are: in, represents the first average convection heat transfer coefficient; represents the second average convection heat transfer coefficient; represents the Nusselt number of the flow channel; Represents the characteristic length of the flow channel; represents the average heat transfer coefficient of gas 'i'; in, Indicates the width of the rectangular flow channel; Indicates the height of the rectangular flow channel; in, represents the thermal conductivity of the mixed gas ‘i’; represents the mole fraction of gas 'k'; represents the thermal conductivity of the gas 'k'; represents the mole fraction of gas 'm'; represents a coefficient whose value depends on the thermal conductivity and molecular mass of the gas involved; in, represents the thermal conductivity of the gas 'k'; represents the thermal conductivity of gas 'm'; represents the molecular mass of gas 'k'; represents the molecular mass of the gas 'm'.

7. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 5, characterized in that: The parameters obtained by identifying experimental data include: Get the measurement data at the current moment; The measurement data at the current moment is input into the preset equation to correct the parameter until the temporary measurement data output by the preset equation and the measurement data at the current moment are within a preset range, thereby obtaining the parameter.

8. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 3, characterized in that: The method of constructing an extended Kalman filter observer based on the continuous system state space equation comprises: Discretizing the continuous system state space equation to obtain a discrete system state space model; An extended Kalman filter observer is obtained based on the discrete system state space model.

9. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 8, characterized in that: The expression of the state space equation of the continuous system is: In the formula, ; ; , T represents matrix transpose; represents a continuous function vector; The expression of the discrete system state space model is: in, and Respectively represent Moment and The state vector at the moment; , represents the state transfer function vector; represents process noise; represents the observation noise; Indicates sampling time; Indicates measurement data.

10. The method for estimating the internal temperature of a reversible solid oxide battery according to claim 9, characterized in that: The extended Kalman filter observer is obtained based on the discrete system state space model, including: Set the state estimate and covariance at the initial moment; Based on the state estimate and covariance at the initial moment, the predicted state estimate and predicted covariance at the current moment are predicted according to the state estimate at the previous moment, the state covariance at the previous moment, and the control input value at the previous moment; Obtain measurement data; The extended Kalman filter observer is obtained by updating the residual, residual covariance, Kalman gain, state estimate and covariance based on the measurement data, the predicted state estimate at the current moment and the predicted covariance at the current moment.

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