CN117790843A

CN117790843A - Solid oxide battery cold start method and device, electronic equipment and storage medium

Info

Publication number: CN117790843A
Application number: CN202311595279.8A
Authority: CN
Inventors: 林今; 李沛洋; 池映天
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2023-11-27
Filing date: 2023-11-27
Publication date: 2024-03-29

Abstract

The disclosure relates to a solid oxide battery cold start method, a device, electronic equipment and a storage medium, wherein a state space proxy model for representing a temperature change trend of a solid oxide battery is obtained based on physical structure modeling of the solid oxide battery. And determining an initial temperature parameter of the solid oxide battery, taking the initial temperature parameter as initial input data, taking a heating parameter included in the initial temperature parameter as a variable, and iteratively predicting an optimal solution of the state space agent model through the self-adaptive controller according to a preset simulation step length. After each iteration process is finished, determining the actual heating parameters of the solid oxide cell according to the optimal solution, and inputting data of the next iteration process. According to the method, the space distribution of the temperature in the electric pile is simulated by establishing the state space agent model with reduced dimension, and the actual heating parameters corresponding to each period are determined based on the periodic calculation state space agent model of the self-adaptive controller, so that the safe and rapid cold start of the solid oxide battery is realized.

Description

Solid oxide battery cold start method and device, electronic equipment and storage medium

Technical Field

The disclosure relates to the technical field of clean energy, in particular to a solid oxide battery cold start method, a device, electronic equipment and a storage medium.

Background

The power of a single solid oxide stack is typically on the order of several kilowatts. In order to further amplify the power, a plurality of electric stacks are required to be packaged in a heat preservation box and are provided with auxiliary machine components to form independent controllable modules with the level of tens of kilowatts, and then a megawatt high-power high-temperature electric hydrogen production system is formed by a plurality of independent modules. The method is oriented to the application scene of the power grid hour-level peak regulation auxiliary service, and the shutdown of part of modules at low load is beneficial to reducing the heat preservation power required by maintaining the working temperature of the modules, so that the hydrogen production efficiency of the system is improved. However, during a cold start process in which the temperature of the module is raised again from room temperature to 600-900 ℃ after shutdown, the galvanic pile structure is prone to failure due to uneven heating.

Disclosure of Invention

In view of this, the disclosure provides a method, a device, an electronic device and a storage medium for cold starting a solid oxide battery, which aim to realize rapid cold starting of the solid oxide battery on the premise of ensuring temperature uniformity.

According to a first aspect of the present disclosure, there is provided a solid oxide cell cold start method comprising:

Modeling based on the physical structure of the solid oxide battery to obtain a state space proxy model for representing the temperature change trend of the solid oxide battery;

determining initial temperature parameters of the solid oxide cell, wherein the initial temperature parameters comprise a gas temperature, a hot box temperature and a heating parameter;

taking the initial temperature parameter as initial input data, taking the heating parameter as a variable, and iteratively predicting an optimal solution of the state space agent model through a self-adaptive controller according to a preset simulation step length, wherein the optimal solution comprises a gas temperature, a hot box temperature and the heating parameter;

and after each iteration process is finished, determining the actual heating parameters of the solid oxide battery according to the optimal solution, and inputting data of the next iteration process.

In one possible implementation, the solid oxide cell includes a cell stack and a thermal box wrapped outside the cell stack; modeling based on the physical structure of the solid oxide battery to obtain a state space proxy model for representing the temperature change trend of the solid oxide battery, wherein the modeling comprises the following steps:

determining a thermal box temperature function representative of the thermal box temperature dynamics;

Establishing a three-dimensional structure model of the solid oxide cell according to the electric pile and a thermal box outside the electric pile;

dividing the three-dimensional structure model along an x-axis, a y-axis and a z-axis according to preset size parameters to obtain a plurality of control volumes;

modeling based on an energy conservation law to obtain a solid temperature function and a gas temperature function of each control volume;

and determining a system equation according to the thermal box temperature function, the solid temperature function and the gas temperature function corresponding to each control volume, and obtaining a state space proxy model for representing the temperature change trend of the solid oxide battery.

In one possible implementation, the thermal box temperature function isWherein C is _hb Representing the heat capacity, P, of the thermal box _hb Representing the electric heating power of the thermal box, T _hb Indicating the temperature of the thermal box, h _dis Representing the heat dissipation coefficient between the thermal box and the environment, T _env Represents the ambient temperature, P _ex Representing the heat exchange power between the stack and the heat box.

In one possible implementation, the solid temperature function includes a solid temperature equation and a heat exchange term equation:

the solid temperature equation isThe heat exchange term equation is +.>Wherein (1) >And->Characterizing the gas temperature and the solid temperature, P, of the corresponding control volumes, respectively _ex Representing the heat exchange power of the corresponding control volume and the adjacent control volume, h _conv，s2g Is the convective heat transfer coefficient between solid and gas, A _s2g For the convective heat transfer area between solid and gas, C _s 、ρ _s And V _s And respectively representing the solid heat capacity, the solid density and the solid volume of the corresponding control volume, wherein i, j and k are used for representing the position of the corresponding control volume in the three-dimensional structure model, x, y and z respectively represent three coordinate axes corresponding to the three-dimensional structure model, b and f respectively represent the backward direction and the forward direction of the corresponding coordinate axes, and N represents the solid quantity obtained by dividing the three-dimensional structure model in the direction of the corresponding coordinate axes.

In one possible implementation, the gas temperature function includes a gas temperature formula and a gas enthalpy difference formula;

the gas temperature formula isThe difference formula of the enthalpy value of the gas is +.>Wherein p is _atm Characterization of atmospheric pressure, ++>Is thermodynamic constant, C _g And V _g Characterizing the gas heat capacity and the gas volume in the corresponding control volumes, respectively, < >>Characterizing the enthalpy of a gas flowing into and out of a corresponding control volume, Q _air Characterizing air flow into the stack, T _in The intake air temperature of the air side is characterized.

In one possible implementation, the state space proxy model isWherein T is _s Characterizing a vector, T, constituted by the solid temperature corresponding to each of said control volumes _g And characterizing a vector consisting of the gas temperature corresponding to each control volume.

In one possible implementation, the heating parameters include electrical heating power and intake air temperature;

the cold start process of the solid oxide cell comprises an electric heating mode and an aero-thermal mode;

setting the air flow rate entering the electric pile to be 0 under the condition of cold start through the electric heating mode;

in the case of cold start by the aero-thermal mode, the electric heating power is set to 0.

In one possible implementation manner, the iteratively predicting, by the adaptive controller, the optimal solution of the state space agent model according to a preset simulation step length, using the initial temperature parameter as initial input data and the heating parameter as a variable includes:

simplifying the state space proxy model derivationWherein T is _s Characterizing a vector comprising a solid temperature of each control volume in a corresponding three-dimensional structural model of the solid oxide cell, T _hb Representing the heat box temperature, P of the heat box _hb Representing the electric heating power of the thermal box, T _in Characterizing an intake air temperature of the air side;

determining a simplified local linearization model corresponding to the state space agent model through the self-adaptive controller;

discretizing the local linearization model to obtain a corresponding discrete time state space model;

and taking the initial temperature parameter as initial input data, and iteratively predicting the optimal solution of the discrete time state space model according to the simulation step length and the preset constraint condition.

In one possible implementation, the local linearization model isWherein (1)>For a state variable and a control variable without disturbance, Δx and Δu are disturbances corresponding to the control variable and the state variable respectively, and x= [ T ] _s ，T _hb ] ^T To add the perturbed state variable, u= [ P ] _hb ，T _in ] ^T For adding the perturbed control variable, +.>Is a system matrix.

In one possible implementation, the discrete-time state space model isWhere k is the current iteration period,y _k vector d, the output of which corresponds to the control variable _k For outputting disturbance terms, C, I are all preset matrices, +. >For residual vector, ++>Is an augmented state variable.

In one possible implementation manner, the determining the actual heating parameter of the solid oxide battery according to the optimal solution, and the input data of the next iteration process include:

taking the heating parameters in the optimal solution as actual heating parameters of the solid oxide cell before the next iteration is finished;

performing Kalman filtering on the gas temperature and the hot box temperature in the optimal solution;

and taking the heating parameters in the optimal solution, the gas temperature after Kalman filtering and the hot box temperature as input data of the next iteration process.

According to a second aspect of the present disclosure, there is provided a solid oxide cell cold start device, the device comprising:

the physical modeling module is used for modeling based on the physical structure of the solid oxide battery to obtain a state space proxy model for representing the temperature change trend of the solid oxide battery;

a parameter determination module for determining initial temperature parameters of the solid oxide cell, the temperature parameters including a gas temperature, a hot box temperature, and a heating parameter;

The iteration prediction module is used for iteratively predicting an optimal solution of the state space agent model by taking the initial temperature parameter as initial input data and taking the heating parameter as a variable through the self-adaptive controller according to a preset simulation step length, wherein the optimal solution comprises a gas temperature, a hot box temperature and a heating parameter;

and the cold start module is used for determining the actual heating parameters of the solid oxide battery and the input data of the next iteration process according to the optimal solution after the iteration process is finished.

In one possible implementation, the solid oxide cell includes a cell stack and a thermal box wrapped outside the cell stack; the physical modeling module is further configured to:

the solid temperature equation isThe heat exchange term equation is +.>Wherein (1)>And->Characterizing the gas temperature and the solid temperature, P, of the corresponding control volumes, respectively _ex Representing the heat exchange power of the corresponding control volume and the adjacent control volume, h _conv，s2g Is the convective heat transfer coefficient between solid and gas, A _s2g For the convective heat transfer area between solid and gas, C _s 、ρ _s And V _s And respectively representing the solid heat capacity, the solid density and the solid volume of the corresponding control volume, wherein i, j and k are used for representing the position of the corresponding control volume in the three-dimensional structure model, x, y and z respectively represent three coordinate axes corresponding to the three-dimensional structure model, b and f respectively represent the backward direction and the forward direction of the corresponding coordinate axes, and N represents the solid quantity obtained by dividing the three-dimensional structure model in the direction of the corresponding coordinate axes.

In one possible implementation, the iterative prediction module is further configured to:

In one possible implementation, the local linearization model isWherein (1)>For a state variable and a control variable without disturbance, Δx and Δu are disturbances corresponding to the control variable and the state variable respectively, and x= [ T ] _s ，T _hb ] ^T To add the perturbed state variable, u= [ P ] _hb ，T _in ] ^T For adding the perturbed control variable, +. >Is a system matrix.

In one possible implementation, the discrete-time state space model isWhere k is the current iteration period,y _k vector d, the output of which corresponds to the control variable _k For outputting disturbance terms, C, I are all preset matrices, +.>For residual vector, ++>Is an augmented state variable.

In one possible implementation, the cold start module is further configured to:

According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described method when executing the instructions stored by the memory.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer program instructions, wherein the computer program instructions, when executed by a processor, implement the above-described method.

According to a fifth aspect of the present disclosure, there is provided a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, performs the above method.

In the embodiment of the disclosure, a state space proxy model for representing the temperature change trend of the solid oxide battery is obtained based on physical structure modeling of the solid oxide battery. And determining an initial temperature parameter of the solid oxide battery, taking the initial temperature parameter as initial input data, taking a heating parameter included in the initial temperature parameter as a variable, and iteratively predicting an optimal solution of the state space agent model through the self-adaptive controller according to a preset simulation step length. After each iteration process is finished, determining the actual heating parameters of the solid oxide cell according to the optimal solution, and inputting data of the next iteration process. According to the method, the space distribution of the temperature in the electric pile is simulated by establishing the state space agent model with reduced dimension, and the actual heating parameters corresponding to each period are determined based on the periodic calculation state space agent model of the self-adaptive controller, so that the safe and rapid cold start of the solid oxide battery is realized.

Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features and aspects of the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 illustrates a flow chart of a solid oxide cell cold start method according to an embodiment of the present disclosure;

fig. 2 illustrates a schematic structural view of a thermal case in a solid oxide cell according to an embodiment of the present disclosure;

FIG. 3 illustrates a schematic diagram of a three-dimensional structural model according to an embodiment of the present disclosure;

FIG. 4 illustrates a schematic diagram of a solid oxide cell cold start process according to an embodiment of the present disclosure;

fig. 5 shows a schematic diagram of a solid oxide cell cold start device according to an embodiment of the present disclosure;

FIG. 6 shows a schematic diagram of an electronic device according to an embodiment of the disclosure;

fig. 7 shows a schematic diagram of another electronic device according to an embodiment of the disclosure.

Detailed Description

Various exemplary embodiments, features and aspects of the disclosure will be described in detail below with reference to the drawings. In the drawings, like reference numbers indicate identical or functionally similar elements. Although various aspects of the embodiments are illustrated in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

In addition, numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art have not been described in detail in order not to obscure the present disclosure.

The solid oxide battery cold start method of the embodiment of the disclosure can be executed by electronic equipment such as terminal equipment or a server. The terminal device may be any fixed or mobile terminal such as a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle mounted device, a wearable device, etc. The server may be a single server or a server cluster composed of a plurality of servers. Any electronic device may implement the solid oxide cell cold start method of embodiments of the present disclosure by way of a processor invoking computer readable instructions stored in a memory.

Fig. 1 shows a flow chart of a solid oxide cell cold start method according to an embodiment of the present disclosure. As shown in fig. 1, the solid oxide cell cold start method of the embodiment of the present disclosure may include the following steps S10 to S40.

And step S10, modeling based on the physical structure of the solid oxide battery to obtain a state space proxy model for representing the temperature change trend of the solid oxide battery.

In a possible implementation manner, the solid oxide battery cold start method of the embodiment of the present disclosure is used for cold starting a solid oxide battery, and the electronic device may perform modeling on a physical structure of the solid oxide battery that is cold started in advance according to needs, so as to obtain a state space proxy model that can simulate a temperature variation trend of the solid oxide battery. Further, the electronic device can regulate and control the actual heating parameters of the solid oxide cell by solving the optimal solution of the state space agent model so as to realize efficient and stable cold start.

Alternatively, the solid oxide cell may include a stack and a thermal box that is wrapped around the outside of the stack. The heat box is used for providing a high-temperature environment required by the operation of the electric pile and comprises a preheating coil for accommodating the electric pile and air inlet. Fig. 2 illustrates a schematic structural view of a thermal box in a solid oxide cell according to an embodiment of the present disclosure, as shown in fig. 2, the thermal box comprising three layers of material, an innermost layer which may be a ceramic fiber sheet with a higher mechanical density and an electrical heating wire mounted on the inner wall, for carrying a galvanic pile. Intermediate part The layer can be a heat-insulating material with a main body of aerogel felt, and the heat conductivity at normal temperature is lower than 0.04Wm ^-1 K ^-1 . The outermost layer is a stainless steel sheet for fixation. Based on the structure, the heat box can ensure good heat preservation and uniform temperature distribution inside. The electric pile contained in the thermal box can be of a co-current plate type electric pile structure, wherein the electric pile structure comprises a plurality of single cells connected in series, and each single cell is provided with a preset number of repeated flow channel units with preset sizes. According to different heating modes, the cold start process of the solid oxide cell according to the embodiment of the disclosure comprises an electric heating mode and an aero-thermal mode, wherein the electric heating mode is used for heating through an electric heating wire on the inner wall of the hot box, and the aero-thermal mode is used for heating through a mode of inputting high-temperature gas into a galvanic pile inside the hot box.

Further, based on the above-mentioned physical structure of the solid oxide battery, the electronic device may first determine a thermal box temperature function characterizing a thermal box temperature characteristic, and an overall temperature function characterizing an overall structure temperature characteristic of the solid oxide battery, and determine a state space proxy model by the thermal box temperature function and the overall temperature function together. The electronic device may divide the solid oxide battery according to a physical structure of the solid oxide battery when determining a temperature of the solid oxide battery overall structure, to obtain a plurality of substructures, and characterize temperature characteristics of the substructures through a corresponding temperature function. And based on the structural features of the solid oxide cell, the electronic device may determine that the temperature function corresponding to each substructure includes a solid temperature function characterizing the solid temperature feature, and a gas temperature function characterizing the gas temperature feature.

For example, the electronic device may first determine a thermal box temperature function that represents thermal box temperature dynamics, and then build a three-dimensional structural model of the solid oxide cell based on the stack and the thermal box external to the stack. And then dividing the three-dimensional structure model along the x-axis, the y-axis and the z-axis according to preset size parameters to obtain a plurality of control volumes, modeling based on the law of conservation of energy to obtain a solid temperature function and a gas temperature function of each control volume, and determining a system equation according to the temperature function of the thermal box, the solid temperature function and the gas temperature function corresponding to each control volume to obtain a state space proxy model representing the temperature change trend of the solid oxide battery.

Fig. 3 shows a schematic diagram of a three-dimensional structural model according to an embodiment of the present disclosure. As shown in fig. 3, after determining the three-dimensional structure model of the solid oxide cell, the electronic device may discretize the three-dimensional structure model into N in the x-axis, y-axis, and z-axis directions, respectively _x 、N _y And N _z The volumes are controlled so as to simulate the temperature distribution in the electrothermal mode and the aero-thermal mode. Wherein each control volume is characterized by a corresponding number (i, j, k), and the solid temperature and the gas temperature corresponding to each control volume are respectively determined by And->Characterization.

In one possible implementation, the thermal box temperature function established by the electronic device based on the dynamic characteristics of the thermal box temperature may beWherein C is _hb Representing the heat capacity, P, of the thermal box _hb Indicating the electric heating power of the heat box, T _hb Indicating the temperature of the hot box, h _dis Representing the heat dissipation coefficient between the thermal box and the environment, T _env Represents the ambient temperature, P _ex Representing the heat exchange power between the stack and the heat box. C (C) _hb And P _hb Can be obtained by fitting experimental data. P (P) _ex Can be arranged on the outer surface A of the pile by heat flux to the outer surface A of the pile _stack Integrating to obtain +.>σ _rad Is the constant of Sithepan-Boltzmann, ε _rad Is the surface emissivity of the solid oxide cell.

Alternatively, the solids temperature function for each control volume may include a solids temperature equation and a heat exchange term equation. Equation of solid temperatureIs thatThe heat exchange term equation is->Wherein (1)>And->Characterizing the gas temperature and the solid temperature, P, of the corresponding control volumes, respectively _ex Representing the heat exchange power of the corresponding control volume and the adjacent control volume, h _conv，s2g Is the convective heat transfer coefficient between solid and gas, A _s2g For the convective heat transfer area between solid and gas, C _s 、ρ _s And V _s The method comprises the steps of respectively representing solid heat capacity, solid density and solid volume of a corresponding control volume, wherein i, j and k are used for representing the position of the corresponding control volume in a three-dimensional structure model, x, y and z represent three coordinate axes corresponding to the three-dimensional structure model, b and f represent backward and forward directions of the corresponding coordinate axes, and N represents the quantity of solids obtained by dividing the three-dimensional structure model in the direction of the corresponding coordinate axes.

Further, the gas temperature function corresponding to each control volume may include a gas temperature equation and a gas enthalpy difference equation. The gas temperature formula isThe difference formula of the gas enthalpy value is +.>Wherein p is _atm Characterization of atmospheric pressure, ++>Is thermodynamic constant, C _g And V _g Characterizing the gas heat capacity and the gas volume in the corresponding control volumes, respectively, < >>Characterizing the enthalpy of a gas flowing into and out of a corresponding control volume, Q _air Characterizing air flow into the stack, T _in The intake air temperature on the air side is characterized.

After the electronic equipment determines the thermal box temperature function, the solid temperature function corresponding to each control volume and the gas temperature function, a system equation can be determined according to the thermal box temperature function, the solid temperature function corresponding to each control volume and the gas temperature function, and a state space proxy model representing the temperature change trend of the solid oxide battery can be obtained. Wherein the state space agent model is as followsWherein T is _s Characterizing a vector consisting of the solid temperature corresponding to each control volume, T _g The vector constituted by the gas temperature corresponding to each control volume is characterized. In the state space proxy model, the heat exchange power in the heat box temperature function is determined according to the heat exchange equation of each control volume corresponding to the solid temperature function.

And step S20, determining initial temperature parameters of the solid oxide battery.

In one possible implementation, the electronic device determines initial temperature parameters of the solid oxide cell, including gas temperature, hot box temperature, and heating parameters, prior to cold starting the solid oxide cell. The gas temperature is used for representing the temperature of gas introduced into the solid oxide battery, the hot box temperature is used for representing the temperature of the hot box in the solid oxide battery, and the heating parameter is used for representing the variable parameter for heating the solid oxide battery, and can comprise electric heating power and air inlet temperature. The variable parameters in the heating parameters are different for different cold start modes. For example, when cold start is performed in the electric heating mode, the air flow rate into the stack is set to 0, and when cold start is performed in the aero-thermal mode, the electric heating power is set to 0.

And step S30, taking the initial temperature parameter as initial input data, taking the heating parameter as a variable, and iteratively predicting the optimal solution of the state space agent model through the self-adaptive controller according to a preset simulation step length.

In one possible implementation, after determining the initial temperature parameter of the solid oxide, the electronic device iteratively predicts an optimal solution of the spatial state proxy model by using the initial temperature parameter as initial input data through the adaptive controller according to a preset simulation step. Alternatively, based on the actual application scenario of the cold start process and the heat transfer characteristics, the gas temperature and the hot box temperature may be used as dependent variables in the input data, and the heating parameters including the electric heating power and the intake air temperature may be used as controllable sub-variables. The optimal solution output by the self-adaptive controller after each iteration also comprises gas temperature, heat box temperature and heating parameters, and the optimal solution is used for representing the temperature state of the solid oxide battery at the beginning of the next iteration under the optimal state, and corresponding electric heating power or air inlet temperature.

Alternatively, since the heat capacity of the gas is small, the time constant of the gas temperature is significantly lower than the solid temperature, i.e. the state space agent model has a strong rigidity, the simulation step size needs to be set to the millisecond level. The process of cold starting the solid oxide battery takes several hours, the simulation step length of millisecond level can ignore the dynamic process of gas temperature, and the state space agent model can be simplified and then the optimal solution can be calculated. In particular, the electronic device can simplify the state space proxy model to obtainWherein T is _s Characterizing a vector comprising a solid temperature for each control volume in a corresponding three-dimensional structural model of a solid oxide cell, T _hb Representing the temperature of the thermal box, P _hb Indicating the electric heating power of the heat box, T _in The intake air temperature on the air side is characterized. And determining a local linearization model corresponding to the simplified state space agent model through the self-adaptive controller. Performing dissociation on local linearization modelAnd carrying out the dispersion treatment to obtain a corresponding discrete time state space model. And then taking the initial temperature parameter as initial input data, and iteratively predicting the optimal solution of the discrete time state space model according to the simulation step length and the preset constraint condition.

Further, the electronic device may obtain a corresponding local linearization model by performing taylor expansion on the simplified state space proxy model. The local linearization model may beWherein,for the state variable and the control variable without disturbance, Δx and Δu are the disturbance corresponding to the control variable and the state variable, respectively, and x= [ T ] _s ，T _hb ] ^T To add the perturbed state variable, u= [ P ] _hb ，T _in ] ^T In order to add the control variable after the disturbance,is a system matrix.

Further, since the local linearization model is a continuous time linearization model, but the adaptive controller makes decisions in discrete time periods, it is necessary to discretize the local linearization model to a system matrix thereinAnd->Proceed as->The transformation shown, where τ _s Representing the sampling period of the adaptive controller, i.e. a time period corresponding to the simulation length. After the discretization process, due toThe obtained discrete time state space model isWhere k is the current iteration period,y _k vector d for controlling the corresponding output of the variable _k For outputting disturbance terms, C, I are all preset matrices, +.>For residual vector, ++>Is an augmented state variable.

In one possible implementation, the constraint condition for the adaptive controller to find the optimal solution in each iteration cycle may be preset, for example, may include u _min ≤u _k+i-1|k ≤u _max ，i＝1，…，N _c 、Δu _min ≤u _k+i|k -u _k+i-1|k ≤Δu _max ，i＝1，…，N _c -1 and y _min -w _min s≤y _k+i|k ≤y _max +w _max s，i＝1，…，N _p . Wherein each parameter may be set based on the following table contents in different cold start modes.

And step S40, after each iteration process is finished, determining the actual heating parameters of the solid oxide battery and the input data of the next iteration process according to the optimal solution.

In one possible implementation, after each iteration process is completed, the electronic device obtains an optimal solution for the current iteration process, including the gas temperature, the hot box temperature, and the heating parameters. Wherein, because the state variables including the gas temperature and the hot box temperature output by the adaptive controller each time include non-measurable output disturbance items and temperature distribution in the electric pile, the accuracy of the gas temperature and the hot box temperature needs to be further improved through Kalman filtering. That is, after the optimal solution is obtained, the heating parameter in the optimal solution is taken as the actual heating parameter of the solid oxide battery before the end of the next iteration, that is, the solid oxide battery is heated by using the electric heating power or the air inlet temperature before the end of the next iteration. And meanwhile, carrying out Kalman filtering on the gas temperature and the hot box temperature in the optimal solution, and taking the heating parameters in the optimal solution, the gas temperature and the hot box temperature after Kalman filtering as input data of the next iteration process.

Alternatively, the kalman filtering process estimates the unknown state quantity in an iterative manner, with each iterative process divided into two steps. First pass throughOptimal solution using the previous cycle +.>To predict the optimal solution of the current period, and mark the prediction result as +.>At the same time utilizeThe prediction covariance matrix P is updated. Then re-using y in the optimal solution of the current period _k Calculate its and +.>Between (a) and (b)Residual error, again according to-> And->Performing state update to obtain filtered +.>Wherein K is a Kalman gain matrix, and Q and R are covariance matrices of process noise and measurement noise respectively.

Fig. 4 shows a schematic diagram of a solid oxide cell cold start process according to an embodiment of the present disclosure. As shown in fig. 4, the embodiment of the disclosure further establishes a three-dimensional structure model as a verification platform of a control strategy by constructing the three-dimensional structure model including the thermal box and the cell stack structure due to higher cost and difficulty of the solid oxide cell stack dynamic experiment. The temperature dynamics of the solid oxide battery and the high-resolution temperature spatial distribution inside the electric pile are simulated through the three-dimensional structure model, so that a real scene is simulated. In the simulation process, a state space proxy model corresponding to the three-dimensional structure model is established, and then the model is subjected to optimization problem solving through the self-adaptive controller, so that an optimal result is obtained. Meanwhile, the accuracy of the solving result is improved in a Kalman filtering mode.

Based on the technical characteristics, the embodiment of the disclosure establishes a state space agent model for reducing dimension to simulate the space distribution of the temperature in the galvanic pile, and periodically calculates the state space agent model based on the self-adaptive controller to determine the actual heating parameters corresponding to each period, so as to realize safe and rapid cold start of the solid oxide battery.

Fig. 5 shows a schematic diagram of a solid oxide cell cold start device according to an embodiment of the present disclosure. As shown in fig. 5, a solid oxide cell cold start device of an embodiment of the present disclosure may include:

the physical modeling module 50 is configured to perform modeling based on a physical structure of the solid oxide cell, so as to obtain a state space proxy model that characterizes a temperature variation trend of the solid oxide cell;

a parameter determination module 51 for determining initial temperature parameters of the solid oxide cell, the temperature parameters including a gas temperature, a hot box temperature, and a heating parameter;

the iteration prediction module 52 is configured to iteratively predict, by using the initial temperature parameter as initial input data and the heating parameter as a variable, an optimal solution of the state space agent model according to a preset simulation step size by using the adaptive controller, where the optimal solution includes a gas temperature, a hot box temperature, and a heating parameter;

The cold start module 53 is configured to determine, after each iteration process is finished, an actual heating parameter of the solid oxide battery according to the optimal solution, and input data of a next iteration process.

In one possible implementation, the solid oxide cell includes a cell stack and a thermal box wrapped outside the cell stack; the physical modeling module 50 is further configured to:

In one possible implementation, the iterative prediction module 52 is further configured to:

In one possible implementation, the cold start module 53 is further configured to:

In some embodiments, functions or modules included in an apparatus provided by the embodiments of the present disclosure may be used to perform a method described in the foregoing method embodiments, and specific implementations thereof may refer to descriptions of the foregoing method embodiments, which are not repeated herein for brevity.

The disclosed embodiments also provide a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method. The computer readable storage medium may be a volatile or nonvolatile computer readable storage medium.

The embodiment of the disclosure also provides an electronic device, which comprises: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described method when executing the instructions stored by the memory.

Embodiments of the present disclosure also provide a computer program product comprising computer readable code, or a non-transitory computer readable storage medium carrying computer readable code, which when run in a processor of an electronic device, performs the above method.

Fig. 6 shows a schematic diagram of an electronic device 800 according to an embodiment of the disclosure. For example, electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.

Referring to fig. 6, an electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output interface 812 (I/O interface), a sensor component 814, and a communication component 816.

The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interactions between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 800.

The multimedia component 808 includes a screen between the electronic device 800 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operational mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 further includes a speaker for outputting audio signals.

Input/output interface 812 provides an interface between processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.

The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the electronic device 800. For example, the sensor assembly 814 may detect an on/off state of the electronic device 800, a relative positioning of the components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of a user's contact with the electronic device 800, an orientation or acceleration/deceleration of the electronic device 800, and a change in temperature of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices, either wired or wireless. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for executing the methods described above.

In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 804 including computer program instructions executable by processor 820 of electronic device 800 to perform the above-described methods.

Fig. 7 shows a schematic diagram of another electronic device 1900 according to an embodiment of the disclosure. For example, electronic device 1900 may be provided as a server or terminal device. Referring to FIG. 7, electronic device 1900 includes a processing component 1922 that further includes one or more processors and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by processing component 1922. The application programs stored in memory 1932 may include one or more modules each corresponding to a set of instructions. Further, processing component 1922 is configured to execute instructions to perform the methods described above.

The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output interface 1958 (I/O interface). The electronic device 1900 may operate an operating system based on a memory 1932, such as Windows Server ^TM ，Mac OS X ^TM ，Unix ^TM ,Linux ^TM ，FreeBSD ^TM Or the like.

In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 1932, including computer program instructions executable by processing component 1922 of electronic device 1900 to perform the methods described above.

The present disclosure may be a system, method, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present disclosure.

The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.

The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.

Computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvements in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method of cold starting a solid oxide cell, the method comprising:

2. The method of claim 1, wherein the solid oxide cell comprises a stack and a thermal box wrapped around the outside of the stack; modeling based on the physical structure of the solid oxide battery to obtain a state space proxy model for representing the temperature change trend of the solid oxide battery, wherein the modeling comprises the following steps:

3. The method according to claim 2, characterized in that theThe temperature function of the thermal box isWherein C is _hb Representing the heat capacity, P, of the thermal box _hb Representing the electric heating power of the thermal box, T _hb Indicating the temperature of the thermal box, h _dis Representing the heat dissipation coefficient between the thermal box and the environment, T _env Represents the ambient temperature, P _ex Representing the heat exchange power between the stack and the heat box.

4. A method according to claim 3, wherein the solid temperature function comprises a solid temperature equation and a heat exchange term equation:

the solid temperature equation isThe heat exchange term equation is +.>Wherein (1)>And->Characterizing the gas temperature and the solid temperature, P, of the corresponding control volumes, respectively _ex Representing the heat exchange power of the corresponding control volume and the adjacent control volume, h _conv，s2g Is the convective heat transfer coefficient between solid and gas, A _s2g For the convective heat transfer area between solid and gas, C _s 、ρ _S And V _s Respectively representing the solid heat capacity, the solid density and the solid volume of the corresponding control volume, wherein i, j and k are used for representing the position of the corresponding control volume in the three-dimensional structure model, x, y and z respectively represent three coordinate axes corresponding to the three-dimensional structure model, b and f respectively represent the backward direction and the forward direction of the corresponding coordinate axes, and N represents the modeling corresponding sitting position And dividing the three-dimensional structure model in the punctuation direction to obtain the solid quantity.

5. The method of claim 4, wherein the gas temperature function comprises a gas temperature equation and a gas enthalpy difference equation;

6. The method of claim 5, wherein the state space proxy model isWherein T is _s Characterizing a vector, T, constituted by the solid temperature corresponding to each of said control volumes _g And characterizing a vector consisting of the gas temperature corresponding to each control volume.

7. The method according to any one of claims 1-5, wherein the heating parameters include electric heating power and intake air temperature;

8. The method of claim 7, wherein iteratively predicting, by the adaptive controller, the optimal solution of the state space agent model in accordance with a preset simulation step using the initial temperature parameter as initial input data and the heating parameter as a variable, comprises:

9. The method of claim 8, wherein the local linearization model isWherein (1)>For a state variable and a control variable without disturbance, Δx and Δu are disturbances corresponding to the control variable and the state variable respectively, and x= [ T ] _s ，T _hb ] ^T To add the perturbed state variable, u= [ P ] _hb ，T _in ] ^T For adding the perturbed control variable, +.>Is a system matrix.

10. The method of claim 9, wherein the discrete-time state space model isWhere k is the current iteration period,y _k vector d, the output of which corresponds to the control variable _k For outputting disturbance terms, C, I are all preset matrices, +.>For residual vector, ++>Is an augmented state variable.

11. The method according to any one of claims 1-10, wherein said determining actual heating parameters of the solid oxide cell from the optimal solution, and input data for a next iteration process, comprises:

12. A solid oxide cell cold start device, the device comprising:

13. An electronic device, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to implement the method of any one of claims 1 to 11 when executing the instructions stored by the memory.

14. A non-transitory computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 11.