CN119716563A - Battery thermal runaway early warning method, system, vehicle-mounted equipment and storage medium - Google Patents
Battery thermal runaway early warning method, system, vehicle-mounted equipment and storage medium Download PDFInfo
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Abstract
The application provides a battery thermal runaway early warning method, a system, vehicle-mounted equipment and a storage medium, wherein the method comprises the steps of obtaining working condition data of a battery to be detected, wherein the working condition data comprise state data and environmental data of the environment where the working condition data are located, the state data comprise temperature parameters, electrical parameters, health state parameters and charge state parameters, inputting the working condition data into a battery thermal runaway simulation model, performing thermal runaway simulation on the battery to be detected to obtain an early warning parameter extremum of the battery to be detected under the working condition data, the early warning parameter extremum comprises the temperature parameter extremum, the battery thermal runaway simulation model is constructed through thermal performance of the battery under various working condition data in a full life cycle, comparing the temperature parameters with the temperature parameter extremum, and performing battery thermal runaway early warning according to comparison results. Through the battery thermal runaway simulation model in the whole life cycle of the battery, accurate early warning of thermal runaway can be realized according to the working condition data of the battery for batteries in different health states and charge states.
Description
Technical Field
The application relates to the technical field of battery management, in particular to a battery thermal runaway early warning method, a system, vehicle-mounted equipment and a storage medium.
Background
Along with the enhancement of global environmental awareness and the transformation of energy structures, the lithium ion battery has been widely used in the field of new energy automobiles due to the characteristics of green and chargeable property, long service life, high energy density and the like. The lithium ion battery is used as a core power source, so that the cruising ability of the vehicle is determined, and the cost and the safety of the whole vehicle are directly influenced. Based on the requirements of long endurance mileage and quick charge of new energy automobiles, battery manufacturers continuously pursue higher energy density and faster charge rate, and the improvement of high energy density and quick charge performance also brings challenges to battery safety, especially the increase of risk of thermal runaway, and serious threat to personal and property safety.
At present, early warning for thermal runaway of a battery is mostly realized by monitoring signals such as battery voltage, internal resistance, temperature, air pressure, smoke and the like. When the voltage, internal resistance, air pressure and smoke signals are used as early warning monitoring signals, the early warning condition is easy to appear, and early warning effect of early thermal runaway is difficult to realize. The temperature is used as an external appearance before the thermal runaway of the battery, and a characteristic signal for early warning can be provided for the early thermal runaway, however, the following defects exist by taking the temperature as the characteristic signal for early warning. Firstly, a sensor which does not affect normal charge and discharge of the battery and has high temperature resistance, resolution and sensitivity is arranged in the battery, the whole bag development cost is increased, the space utilization rate is reduced, secondly, a large number of experiments under different working conditions are required to be carried out, and because the experiment conditions are limited, and most early warning is only carried out by various test results of fresh battery cells, the performance in the whole life cycle of the battery cells is not considered, and all the working conditions of the whole life cycle of the battery bag cannot be reflected, so that the risk of false alarm and missing report actually exists. Therefore, the battery thermal runaway early warning still has the problems of limited use of the sensor and limited monitoring data, so that the reliability, timeliness and accuracy of the early warning are insufficient.
Disclosure of Invention
In view of the above drawbacks of the prior art, the present application discloses a battery thermal runaway warning method, a system, a vehicle-mounted device and a storage medium, which are used for solving the technical problem of poor battery thermal runaway warning effect in the prior art.
The application provides a battery thermal runaway early warning method, which comprises the steps of obtaining working condition data of a battery to be detected, wherein the working condition data comprise state data and environmental data of the environment, the state data comprise temperature parameters, electrical parameters, health state parameters and charge state parameters, inputting the working condition data into a battery thermal runaway simulation model, carrying out thermal runaway simulation on the battery to be detected according to the state data and the environmental data to obtain early warning parameter extremum of the battery to be detected under the working condition data, the early warning parameter extremum comprises temperature parameter extremum, the battery thermal runaway simulation model is constructed through thermal performance of the battery under various working condition data in a full life cycle, comparing the temperature parameters with the temperature parameter extremum, and carrying out battery thermal runaway early warning according to comparison results.
In an embodiment of the application, the battery thermal runaway simulation model comprises an aging model and a thermal safety mechanism model, wherein the temperature parameter extremum comprises a first temperature parameter extremum, a second temperature parameter extremum, a third temperature parameter extremum and a fourth temperature parameter extremum in sequence from small to large, the working condition data are input into the battery thermal runaway simulation model, the thermal runaway simulation is carried out on the battery to be tested according to the state data and the environment data, and the early warning parameter extremum of the battery to be tested under the working condition data is obtained.
The method for constructing the aging model comprises the steps of preparing a test battery under various health states and various charge states, obtaining a first temperature parameter change curve and a first electrical parameter change curve of the test battery under different environment data, generating a plurality of first test data under different working conditions, obtaining first model parameters at least comprising a solid phase diffusion coefficient, a liquid phase diffusion coefficient, a solid phase conductivity, a liquid phase conductivity, a reaction rate constant and an open circuit voltage, constructing a reference aging model combined with an electric heating coupling model according to the first model parameters, inputting the plurality of first test data into the reference aging model, simulating the conditions of heat generation, temperature rise and voltage of the battery under different working conditions, obtaining a first simulation result, and optimizing the first model parameters according to the first simulation result to obtain the aging model.
In an embodiment of the application, the construction mode of the thermal safety mechanism model comprises the steps of preparing test batteries under various health states and various charge states, acquiring second temperature parameter change curves and second electrical parameter change curves of the batteries from a heat generation stage, a battery voltage dip stage and a voltage dip to a thermal runaway stage when thermal runaway occurs in the test batteries under different environmental data, generating a plurality of second test data under different working condition data, acquiring second model parameters, wherein the second model parameters at least comprise reaction enthalpy, reaction activation energy and a front frequency factor, constructing a standard thermal safety mechanism model according to the second model parameters, inputting the plurality of second test data into the standard thermal safety mechanism model, simulating the heat, the temperature rise and the voltage conditions of the batteries under different working condition data and at different stages when thermal runaway occurs, obtaining second simulation results, and optimizing the second model parameters according to the second simulation results to obtain the thermal safety model.
In an embodiment of the application, the comparing the temperature parameter with the temperature parameter extremum and performing the battery thermal runaway warning according to the comparison result comprises triggering a first-stage battery cooling measure if the temperature parameter is greater than the first temperature parameter extremum and less than or equal to the second temperature parameter extremum, triggering a first-stage thermal runaway warning and a second-stage battery cooling measure if the temperature parameter is greater than the second temperature parameter extremum and less than or equal to the third temperature parameter extremum, triggering a second-stage thermal runaway warning and a third-stage battery cooling measure if the temperature parameter is greater than the third temperature parameter extremum and less than or equal to the fourth temperature parameter extremum, and triggering a thermal runaway protection measure if the temperature parameter is greater than the fourth temperature parameter extremum, and triggering a third-stage thermal runaway warning, a fourth-stage battery cooling measure and a thermal runaway protection and a thermal runaway spreading measure.
In an embodiment of the application, the temperature parameter comprises a temperature value and a temperature rise rate, the temperature parameter extremum comprises a temperature extremum and a temperature rise rate extremum, the comparing the temperature parameter with the temperature parameter extremum and triggering a corresponding thermal runaway early warning measure according to a comparison result comprises comparing the temperature value with the temperature extremum and comparing the temperature rise rate with the temperature rise rate extremum, and triggering the thermal runaway early warning measure when the temperature value is larger than the temperature extremum and the temperature rise rate is larger than the temperature rise rate extremum.
In an embodiment of the application, the electrical parameter includes a voltage parameter, the early warning parameter extremum further includes a voltage parameter extremum, and before the thermal runaway early warning measure is triggered, the method further includes comparing the voltage parameter with the voltage parameter extremum, and when the voltage parameter is greater than the voltage parameter extremum, entering a triggering stage of the thermal runaway early warning measure.
The application provides a battery thermal runaway early warning system, which comprises an acquisition module, a simulation module and an early warning module, wherein the acquisition module is used for acquiring working condition data of a battery to be detected, the working condition data comprise state data and environmental data of the environment, the state data comprise temperature parameters, electric parameters, health state parameters and state of charge parameters, the simulation module is used for inputting the working condition data into a battery thermal runaway simulation model, performing thermal runaway simulation on the battery to be detected according to the state data and the environmental data to obtain early warning parameter extremum of the battery to be detected under the working condition data, the early warning parameter extremum comprises temperature parameter extremum, the battery thermal runaway simulation model is constructed through thermal performance of the battery under various working condition data in a full life cycle, and the early warning module is used for comparing the temperature parameters with the temperature parameter extremum and performing battery thermal runaway early warning according to comparison results.
In a third aspect, the present application provides an in-vehicle apparatus including one or more processors, and a storage device for storing one or more programs that, when executed by the one or more processors, cause the in-vehicle apparatus to implement the battery thermal runaway warning method described in the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the battery thermal runaway warning method described in the first aspect.
As described above, the battery thermal runaway early warning method, system, vehicle-mounted device and storage medium provided by the embodiment of the application have the following beneficial effects:
firstly, working condition data of a battery to be tested are obtained, the working condition data comprise operating state data of the battery to be tested and environmental data of the environment, wherein the state data comprise temperature parameters, electrical parameters, health state parameters and state of charge parameters, then the working condition data are input into a battery thermal runaway simulation model, the thermal runaway simulation of the battery to be tested is carried out, an early warning parameter extreme value of the battery to be tested under the working condition data is obtained, the early warning parameter extreme value comprises the temperature parameter extreme value, the battery thermal runaway simulation model is constructed through thermal performance of the battery under various working condition data in a full life cycle, finally, the temperature parameters are compared with the temperature parameter extreme value, and early warning of the battery is carried out according to comparison results, and the early warning parameter extreme value of the battery under the working condition data can be predicted according to the environmental data, the temperature parameters and the electrical parameters of the battery, and whether the battery reaches the thermal runaway condition is judged based on the early warning parameter extreme value, so that the accurate early warning of the thermal runaway is achieved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. It is evident that the drawings in the following description are only some embodiments of the present application and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art. In the drawings:
FIG. 1 is a schematic view of an implementation environment of a battery thermal runaway warning system according to an exemplary embodiment of the present application;
Fig. 2 is a flowchart illustrating a battery thermal runaway warning method according to an exemplary embodiment of the present application;
FIG. 3 is a flow chart illustrating one manner of thermal safety mechanism model construction in accordance with an exemplary embodiment of the present application;
FIG. 4 is a flow chart illustrating a specific battery thermal runaway warning method according to an exemplary embodiment of the present application;
FIG. 5 is a block diagram of a battery thermal runaway warning system, shown in an exemplary embodiment of the application;
Fig. 6 is a schematic structural diagram of an in-vehicle apparatus according to an embodiment of the present application.
Detailed Description
Further advantages and effects of the present application will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The application may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present application. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present application by way of illustration, and only the components related to the present application are shown in the illustrations, not according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.
In the following description, numerous details are set forth in order to provide a more thorough explanation of embodiments of the present application, it will be apparent, however, to one skilled in the art that embodiments of the present application may be practiced without these specific details, in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the embodiments of the present application.
It should be noted that, the early warning for the thermal runaway of the battery is generally implemented by monitoring signals such as the voltage, the internal resistance, the temperature, the air pressure, and the smoke of the battery. However, the inventor researches and discovers that when voltage, internal resistance, air pressure and smoke signals are used as early warning monitoring signals, early warning is easy to occur in the later situation, early warning effect of early thermal runaway is difficult to achieve, the temperature is used as external appearance before thermal runaway of the battery, and the early warning characteristic signals can be provided for the early thermal runaway, however, the following defects exist when the temperature is used as the early warning characteristic signals. Firstly, a sensor which does not affect normal charge and discharge of the battery and has high temperature resistance, resolution and sensitivity is arranged in the battery, the whole bag development cost is increased, the space utilization rate is reduced, secondly, a large number of experiments under different working conditions are required to be carried out, and because the experiment conditions are limited, and most early warning is only carried out by various test results of fresh battery cells, the performance in the whole life cycle of the battery cells is not considered, and all the working conditions of the whole life cycle of the battery bag cannot be reflected, so that the risk of false alarm and missing report actually exists. Therefore, the battery thermal runaway early warning still has the problems of limited use of the sensor and limited monitoring data, so that the reliability, timeliness and accuracy of the early warning are insufficient.
Thus, referring to fig. 1, fig. 1 is a schematic view of an implementation environment of a battery thermal runaway warning system according to an exemplary embodiment of the present application. As shown in fig. 1, the implementation environment includes a vehicle 110 and a battery thermal runaway warning system 120, where the battery thermal runaway warning system 120 is embedded in the vehicle 110 and is used for implementing thermal runaway warning of a battery in the vehicle 110, the battery thermal runaway warning system 120 includes, but is not limited to, a vehicle system, a vehicle-mounted computer, etc., and for batteries in different health states and states of charge, the warning parameter extremum under the working condition data of the battery can be predicted according to the environmental data, the temperature parameter and the electrical parameter by using the battery thermal runaway simulation model in the battery full life cycle, and whether the battery reaches the thermal runaway warning condition is judged based on the warning parameter extremum, so as to implement accurate warning of thermal runaway and achieve the effect of early thermal runaway warning.
Referring to fig. 2, fig. 2 is a flowchart illustrating a battery thermal runaway warning method according to an exemplary embodiment of the present application. The method may be applied to the implementation environment shown in fig. 1, and it should be understood that the method may also be applied to other exemplary implementation environments, and the implementation environment to which the method is applied is not limited by the embodiment.
As shown in fig. 2, in an exemplary embodiment, the battery thermal runaway warning method at least includes steps S210 to S230, which are described in detail as follows:
Step S210, working condition data of the battery to be tested is obtained, wherein the working condition data comprise state data and environment data of the environment in which the working condition data are located, and the state data comprise temperature parameters, electrical parameters, health state parameters and charge state parameters.
The state data refer to various parameter data inside the battery to be tested in operation and at least comprise temperature parameters, electrical parameters, health state parameters and state of charge parameters of the battery to be tested, and the environment data refer to environment parameters outside the battery in operation and at least comprise environment temperature data.
It should be noted that, the temperature parameter at least includes a temperature value and a temperature rise rate, the electrical parameter at least includes a voltage value, a discharge power value, and a DCR (Direct Current Resistance, direct current internal resistance) value, the State of Health parameter refers to SOH (State of Health), and the State of Charge parameter refers to SOC (State of Charge). In addition, the heat exchange system corresponding to the battery is considered, and the battery exchanges heat with the surrounding environment, so that the influence on the temperature of the battery exists, and the environmental data at least comprises the temperature of the cooling liquid.
Step S220, inputting the working condition data into a thermal runaway simulation model of the battery, performing thermal runaway simulation on the battery to be tested according to the state data and the environment data, and obtaining an early warning parameter extremum of the battery to be tested under the working condition data, wherein the early warning parameter extremum comprises a temperature parameter extremum, and the thermal runaway simulation model of the battery is built through the thermal properties of the battery under various working condition data in a full life cycle.
In the embodiment, the influence of various parameters on the thermal runaway of the battery during the operation of the battery and the influence of performance reduction of the battery on the thermal runaway of the battery during the use are considered, the thermal runaway simulation is performed on the battery to be tested through working condition data such as the temperature parameter, the electrical parameter, the health state parameter, the charge state parameter and the environmental data of the battery to be tested in all aspects, the early warning parameter extremum is obtained, the characteristic that the early warning parameter extremum of the battery to be tested under different working condition data is different is fully represented, namely the early warning parameter extremum can be adjusted in real time according to different working condition data, and the corresponding early warning parameter extremum can be predicted according to the specific working condition data of the battery to be tested, so that the thermal runaway early warning is performed according to the dynamic early warning parameter extremum, and the reliability and the accuracy of the thermal runaway early warning are ensured.
It should be noted that the extreme value of the early warning parameter refers to a threshold condition for triggering the thermal runaway early warning, and the extreme value of the temperature parameter refers to a temperature threshold condition for triggering the thermal runaway early warning. In addition, the battery thermal runaway simulation model is built through the thermal performance of the battery under various working condition data in the whole life cycle, namely through the thermal performance corresponding to various working condition data under various health states and charge states, so that the built battery thermal runaway simulation model can meet the thermal runaway early warning of the battery under different health states, charge states and other specific working condition data, the reliability and the accuracy of the battery thermal runaway early warning are further improved, and the false alarm and missing risk existing in the actual thermal runaway early warning is reduced.
In an embodiment, the battery thermal runaway simulation model comprises an aging model and a thermal safety mechanism model, wherein the temperature parameter extremum comprises a first temperature parameter extremum, a second temperature parameter extremum, a third temperature parameter extremum and a fourth temperature parameter extremum in sequence from small to large, working condition data are input into the battery thermal runaway simulation model, thermal runaway simulation is conducted on a battery to be tested according to the state data and the environment data, and early warning parameter extremum of the battery to be tested under the working condition data is obtained.
Wherein, the aging model of the battery refers to a model for predicting the performance degradation process of the battery in the life cycle of the battery, and the thermal safety mechanism model of the battery refers to a model for describing and predicting the behavior of the battery under the extreme temperature condition and the thermal runaway risk of the battery.
In the embodiment, by introducing an aging model and a thermal safety mechanism model, the temperature parameter extreme value of the battery to be detected under the working condition data can be obtained, and compared with the current temperature parameter, the health condition of the battery can be monitored, and the early thermal runaway early warning effect is realized. Meanwhile, by introducing an aging model and a thermal safety mechanism model to perform battery health monitoring and thermal runaway early warning, the cost increase caused by additional sensor arrangement can be avoided, and the space utilization rate, the battery energy density and the like are reduced. In addition, by introducing an aging model and a thermal safety mechanism model, the two models are utilized to predict the temperature parameter extremum, and a large number of experiments under different working conditions are not required to be carried out to obtain the temperature parameter extremum under different working condition data, so that the thermal runaway early warning of the battery is simple and efficient.
In this embodiment, the working condition data is input into the aging model, and the temperature parameter threshold value of the safe operation of the battery to be tested is predicted according to the working condition data and is used as the first temperature parameter extremum, wherein the first temperature parameter extremum refers to the upper limit boundary value of the temperature parameter of the battery to be tested when the battery to be tested normally operates under the working condition data. By introducing the aging model, the trend of the temperature parameter of the battery to be measured under normal operation can be predicted, the battery can be identified and early-warned in advance before thermal runaway, and the health of the battery can be better monitored and managed.
In this embodiment, the working condition data is input into the thermal safety mechanism model, and the second temperature parameter extremum of the battery to be measured in the self-heating phase, the third temperature parameter extremum of the battery voltage dip phase and the fourth temperature parameter extremum of the battery voltage dip phase are predicted according to the working condition data, wherein the self-heating phase is the phase that the battery starts to generate heat, but the battery is still in a controllable state because the heat is insufficient to cause significant temperature rise, the internal resistance of the battery increases along with the gradual rise of the internal temperature of the battery in the battery voltage dip phase, the battery voltage starts to drop, the battery starts to enter an unstable state is marked, and the temperature is rapidly increased to be in an uncontrollable state when the temperature of the battery continues to rise and reaches a critical point in the thermal runaway phase after the voltage dip. The second temperature parameter extremum refers to the upper limit boundary value of the temperature parameter in the heat generation stage, the third temperature parameter extremum refers to the upper limit boundary value of the temperature parameter in the battery voltage suddenly dropping stage, and the fourth temperature parameter extremum refers to the upper limit boundary value of the temperature parameter from the time of voltage suddenly dropping to the time of thermal runaway stage. The thermal safety mechanism model is introduced, so that the thermal runaway mechanism of the battery in different stages can be reflected, and the thermal runaway early warning precision is higher.
In one possible embodiment, the temperature parameter includes a temperature value and a temperature rise rate, and the temperature parameter extremum includes a temperature extremum and a temperature rise rate extremum. The method comprises the steps of inputting working condition data into an aging model, predicting a first temperature parameter extremum of safe operation of a battery to be tested according to the working condition data, wherein the first temperature parameter extremum comprises a first temperature extremum T 1 and a first temperature rise rate V 1, inputting the working condition data into a thermal safety mechanism model, and predicting a second temperature parameter extremum (comprising a second temperature extremum T 2 and a second temperature rise rate V 2) of the battery to be tested in a self-heating stage, a third temperature parameter extremum (a third temperature extremum T 3 and a third temperature rise rate V 3) of a battery voltage dip stage and a fourth temperature parameter extremum (a fourth temperature extremum T 4 and a fourth temperature rise rate V 4) of the battery to be tested in a thermal runaway stage after voltage dip according to the working condition data.
In an embodiment, an aging model is constructed by preparing a test battery under various health states and various charge states, acquiring a first temperature parameter change curve and a first electrical parameter change curve of the test battery under different environmental data, generating a plurality of first test data under different working conditions, acquiring first model parameters, wherein the first model parameters at least comprise a solid phase diffusion coefficient, a liquid phase diffusion coefficient, a solid phase conductivity, a liquid phase conductivity, a reaction rate constant and an open circuit voltage, constructing a reference aging model combined with an electrothermal coupling model according to the first model parameters, inputting the plurality of first test data into the reference aging model, simulating the heat generation, temperature rise and voltage conditions of the battery under different working conditions, obtaining a first simulation result, and optimizing the first model parameters according to the first simulation result to obtain the aging model.
In this embodiment, the test cells under various states of health and various states of charge may be prepared according to an accelerated aging test method, for example, by increasing the temperature or the discharge rate of the cells to obtain test cells under different states of health and different states of charge. It should be understood that among the test batteries under multiple states of health and multiple states of charge, test batteries under different states of charge under the same state of health and test batteries under the same state of charge under different states of health are included. The method comprises the steps of obtaining a first temperature parameter change curve and a first electrical parameter change curve of a test battery under different environmental data, and generating a plurality of first test data under different working conditions, wherein the plurality of first test data under different working conditions refer to test data under different temperature parameters, electrical parameters, health state parameters, state of charge parameters and environmental data, namely, one first test data refers to test data under a specific temperature parameter, electrical parameters, health state parameters, state of charge parameters and temperature data. In addition, the different states of health include the entire life cycle of the battery, and the different states of charge include the entire range of the battery from fully discharged to fully charged.
In this embodiment, the baseline aging model is built in conjunction with an electrothermal coupling model, wherein the electrothermal coupling model includes a thermal model and an electrochemical model. The electrochemical model and the thermal model are coupled, and the voltage condition of the battery under different working conditions is calculated by the solid-liquid phase diffusion coefficient, the reaction rate constant of the electrochemical reaction and the open circuit voltage. Therefore, the first model parameters of the reference aging model built by combining the electrothermal coupling model at least comprise solid phase diffusion coefficient, liquid phase diffusion coefficient, solid phase conductivity, liquid phase conductivity, reaction rate constant and open circuit voltage.
In the embodiment, the heat generation, temperature rise and voltage conditions of the battery under different working condition data are simulated through the reference aging model to obtain a first simulation result, wherein the first simulation result is a result obtained by comparing the heat generation, temperature rise and voltage conditions of the standard battery corresponding to the first test data with the heat generation, temperature rise and voltage conditions of the battery obtained through simulation, so that the first model parameters are subjected to iterative optimization according to errors between the simulation and the standard, and the aging model is obtained, and therefore, the simulation accuracy of the aging model is ensured.
Therefore, an aging model combined with an electrochemical-thermal coupling model is introduced, so that the heat generation, temperature rise and voltage trend of the battery under normal operation can be predicted, and the battery health can be better monitored and managed by combining with a battery thermal management system.
It should be further noted that, a thermal model is introduced to calculate the heat generation and temperature rise conditions of the working condition data, and firstly, according to the law of conservation of energy, namely, conservation of energy of heat generation, heat dissipation and heat conduction of the battery in operation, the equation is as follows:
wherein, C represents the specific constant-volume heat capacity of the battery, m represents the mass of the battery, T represents the temperature of the battery, T represents the time; Lambda represents the thermal conductivity of the battery; The rate of change of the temperature gradient of the battery is represented, and q represents the rate of heat generation of the battery.
Then the battery can exchange heat with the surrounding environment, such as liquid cooling in a battery pack, a convection heat exchange coefficient h can be set in the model to change the heat exchange condition, and the convection heat exchange coefficient h can be used as the boundary condition of the formula (1), and the boundary condition of the heat exchange between the battery and the surrounding environment is as follows:
wherein λ represents the thermal conductivity of the battery; The temperature gradient of the battery is represented by the change rate, h represents the convective heat transfer coefficient of the battery, A represents the heat transfer surface area of the battery, T represents the temperature of the battery, and T f is the fluid (coolant) temperature.
For battery heat generation, the heat generation formulas include reversible heat (electrochemical heat generation), irreversible heat (electrochemical reaction overpotential heat generation), and ohmic heat (solid phase ohmic heat and liquid phase ohmic heat), and the respective equations are as follows:
Reversible heat:
Wherein q r represents ideal heat generation without energy loss during electrochemical reaction, a is the effective area of the electrode, F is Faraday constant, j n represents net current density; a partial derivative of reversible potential with respect to temperature representing an electrochemical reaction;
Irreversible heat:
q act＝aFjn eta (4)
Wherein q act represents an energy loss due to an overpotential in an electrochemical reaction, a is an effective area of an electrode, F represents a Faraday constant, j n represents a net current density, η represents an overpotential;
ohmic heat:
Wherein q ohm represents the total heat generated when current passes through the solid electrode material and the electrolyte, σ represents the conductivity of the solid electrode, Φ s represents the potential in the solid electrode; represents the gradient of the potential in the solid electrode, kappa represents the conductivity of the electrolyte, phi e represents the potential in the electrolyte; Representing the gradient of the electric potential in the electrolyte, R representing the general gas constant, T representing the temperature of the battery, F representing the Faraday constant, F ± representing the activity factor of the ions, c e representing the electrolyte concentration, T + representing the number of positive ions transported; Representing the partial derivative of the activity factor f ± with respect to the electrolyte concentration c e; a gradient representing the natural logarithm of the electrolyte concentration; represents solid phase ohmic heat; representing ohmic heating in the liquid phase.
And thirdly, coupling the electrochemical model with the thermal model, calculating the temperature inside the battery through the thermal model, feeding back the temperature to the electrochemical model, and calculating the voltage condition of the battery under different working condition data through the solid-liquid phase diffusion coefficient, the reaction rate constant of the electrochemical reaction and the open-circuit voltage. Among them, many of the relationships between physical properties of battery materials and temperature mostly follow the equation of arrhenius Wu Sigong, so the influence of temperature on parameters is calculated using the arrhenius equation.
Equation of solid phase diffusion coefficient versus temperature:
Wherein D s,j,T represents a solid phase diffusion coefficient at a temperature T, D represents a diffusion coefficient, s represents a solid phase, j represents a substance type or an electrode material type of the battery, D s,j,ref represents a solid phase diffusion coefficient at a reference temperature T ref, E ads,j represents adsorption activation energy, R represents a general gas constant, T represents a temperature of the battery, and T ref represents a reference temperature of the battery.
Equation of liquid phase diffusion coefficient versus temperature:
Wherein D e,j,T represents a liquid phase diffusion coefficient at a temperature T, D represents a diffusion coefficient, E represents a liquid phase, j represents a substance type or an electrode material type of the battery, D e,j,ref represents a liquid phase diffusion coefficient at a reference temperature T ref, E ade,j represents absorption and desorption activation energy, R represents a general gas constant, T represents a temperature of the battery, and T ref represents a reference temperature of the battery.
Equation of reaction rate constant versus temperature:
Wherein K j,T represents a reaction rate constant at a temperature T, K represents a reaction rate constant, j represents a substance type or an electrode material type of the battery, K j,ref represents a liquid phase diffusion coefficient at a reference temperature T ref, E ar,j represents activation energy, R represents a general gas constant, T represents a temperature of the battery, and T ref represents a reference temperature of the battery.
Equation for open circuit voltage versus temperature:
Where U j represents an open circuit voltage, T x represents a temperature of the battery, SOC j (x, T) represents a state of charge at a location x and a time T, U j(SOCj(x,t),Tx) represents an open circuit voltage at a given location x and a time T, and at a temperature T x, i.e., at a temperature T x and a state of charge SOC j (x, T), T ref represents a reference temperature of the battery, U j(SOCj(x,t),Tref) represents an open circuit voltage at a reference temperature T ref and a state of charge SOC j (x, T); Representing the partial derivative of the open circuit voltage U j(SOCj (x, t) with respect to temperature.
In an embodiment, the construction method of the thermal safety mechanism model comprises the steps of preparing test batteries under various health states and various charge states, obtaining second temperature parameter change curves and second electrical parameter change curves of the batteries from a heat generation stage, a battery voltage dip stage and a voltage dip to a thermal runaway stage when the batteries are in thermal runaway under different environmental data, generating a plurality of second test data under different working conditions, obtaining second model parameters, wherein the second model parameters at least comprise reaction enthalpy, reaction activation energy and front frequency factors, constructing a reference thermal safety mechanism model according to the second model parameters, inputting the plurality of second test data into the reference thermal safety mechanism model, simulating heat generation, temperature rise and voltage conditions of the batteries under different working conditions and at different stages when the batteries are in thermal runaway, obtaining second simulation results, and optimizing the second model parameters according to the second simulation results to obtain the thermal safety mechanism model.
In this embodiment, the test cells under various states of health and under various states of charge can be prepared according to an accelerated aging test method, for example, the temperature or the discharge rate of the battery is increased to obtain test cells under different states of health and under different states of charge. It should be understood that among the test batteries under multiple states of health and multiple states of charge, test batteries under different states of charge under the same state of health and test batteries under the same state of charge under different states of health are included. And acquiring a second temperature parameter change curve and a second electrical parameter change curve of the battery from a heat generation stage, a battery voltage dip stage and a voltage dip to the thermal runaway stage when the battery is in thermal runaway under different environmental data, and generating a plurality of second test data under different working condition data, wherein the plurality of second test data under different working condition data refer to test data under different temperature parameters, electrical parameters, health state parameters, charge state parameters and environmental data, namely, one second test data refers to test data under one specific temperature parameter, electrical parameter, health state parameter, charge state parameter and temperature data. In addition, the different states of health include the entire life cycle of the battery, and the different states of charge include the entire range of the battery from fully discharged to fully charged.
In the embodiment, a thermal safety mechanism model is introduced, and the heat generation, temperature rise and voltage conditions of the battery under different working condition data are calculated through reaction enthalpy, reaction activation energy and front frequency factors. Thus, the second model parameters of the thermal safety mechanism model include at least the reaction enthalpy, the reaction activation energy and the front frequency factor. The front frequency factor reflects the number and probability of effective collisions of reactant molecules in the battery in unit time, and predicts the rate of chemical reaction and its change with temperature. The reaction enthalpy, the reaction activation energy and the front frequency factor can be obtained by parameter identification based on DSC test or based on thermal runaway experimental data and combining MATLAB (matrix laboratory) and other software.
In the embodiment, the heat generation, temperature rise and voltage conditions of the battery under different working condition data are simulated through the thermal safety mechanism model, and a second simulation result is obtained, wherein the second simulation result is a result obtained by comparing the heat generation, temperature rise and voltage conditions of the standard battery corresponding to the second test data with the heat generation, temperature rise and voltage conditions of the battery obtained through simulation, so that the second model parameters are subjected to iterative optimization according to errors between the simulation and the standard, and the thermal safety mechanism model is obtained, and therefore, the simulation accuracy of the thermal safety mechanism model is ensured.
Therefore, the thermal safety mechanism model is introduced, the thermal runaway mechanism of the battery in different stages can be reflected, the four equations of the thermal runaway mechanism are used as heat sources for control, and the superposition of the chain reaction and a plurality of exothermic reactions in the thermal runaway process is considered, so that the early warning parameter threshold values in different stages in the process of predicting the thermal runaway are more accurate.
It should be further noted that, a thermal safety mechanism model is introduced, and a thermal runaway mechanism of the battery is represented by a four-way process, that is, chemical reactions of the battery in different temperature ranges, for example, SEI film decomposition and regeneration can occur at 70-80 ℃, heat generated by different reactions is continuously accumulated, and finally, the thermal runaway of the battery is caused. Therefore, the conditions of heat generation, temperature rise and voltage of the battery under different working condition data can be judged by researching reactions at different stages, so that the aim of early warning is fulfilled. Specifically, the tetragonal approach includes the following formula:
SEI film decomposition reaction:
Wherein Q sei represents heat generation power of SEI film decomposition reaction, H sei represents enthalpy change of SEI film decomposition reaction, W sei represents quality of SEI film, A sei represents reaction area of SEI film, E sei represents activation energy of SEI film decomposition reaction, R represents general gas constant, T represents temperature of battery, and C sei represents concentration of SEI film;
the corresponding kinetic equation:
Wherein, The change rate of the concentration of the SEI film along with time is represented, and other formula parameters are the same as the above;
the anode reacts with the electrolyte:
Wherein Q ne represents the heat generation power of the reaction between the anode and the electrolyte, H ne represents the enthalpy change of the reaction between the anode and the electrolyte, W ne represents the mass of the anode, A ne represents the reaction area of the anode, E ne represents the activation energy of the reaction between the anode and the electrolyte, R represents the general gas constant, T represents the temperature of the battery, T sei represents the decomposition time of the SEI film, T ref represents the reference time of the decomposition of the SEI film, and C ne represents the concentration of the reaction between the anode and the electrolyte;
the corresponding kinetic equation:
Wherein, The change rate of the concentration of the anode material along with time is represented, and other formula parameters are the same as the above;
Wherein, The change rate of the SEI film decomposition time along with time is represented, and other formula parameters have the same meaning;
the positive electrode reacts with the electrolyte:
Wherein Q pe represents heat generation power of the reaction between the positive electrode and the electrolyte, H pe represents enthalpy change of the reaction between the positive electrode and the electrolyte, W pe represents mass of the positive electrode, A pe represents reaction area of the positive electrode, alpha represents reaction degree (0-1), E pe represents activation energy of the reaction between the positive electrode and the electrolyte, R represents general gas constant, T represents temperature of the battery, and C pe represents concentration of the reaction between the positive electrode and the electrolyte;
the corresponding kinetic equation:
Wherein, The change rate of the concentration of the positive electrode material along with time is represented, and other formula parameters have the same meaning;
Electrolyte solution decomposition reaction:
Wherein Q e represents the heat generation power of the decomposition reaction of the electrolyte solution, H e represents the enthalpy change of the decomposition reaction of the electrolyte solution, W e represents the mass of the electrolyte solution, A e represents the reaction area of the electrolyte solution, E e represents the activation energy of the decomposition reaction of the electrolyte solution, R represents the general gas constant, T represents the temperature of the battery, and C e represents the concentration of the electrolyte solution;
the corresponding kinetic equation:
Wherein, The change rate of the electrolyte solution concentration with time is represented, and other formula parameters are the same as the above.
Thus, the total heat generation power is:
q abuse＝Qsei+Qne+Qpe+Qe (19)
Wherein, Q abuse represents the total heat generation power, Q sei represents the heat generation power of the decomposition reaction of the SEI film (Solid Electrolyte Interface membrane, solid electrolyte interface film), Q ne represents the heat generation power of the reaction of the negative electrode and the electrolyte, Q pe represents the heat generation power of the reaction of the positive electrode and the electrolyte, and Q e represents the heat generation power of the decomposition reaction of the electrolyte solution.
In one possible embodiment, please refer to fig. 3, fig. 3 is a flowchart illustrating a thermal safety mechanism model construction method according to an exemplary embodiment of the present application. As shown in FIG. 3, the specific steps for constructing a thermal safety mechanism model by utilizing COMSOL (multiple physical fields simulation software) comprise selecting a physical field interface, selecting a three-dimensional solid heat transfer module for transient calculation of the thermal safety mechanism model, selecting a proper physical field according to physical characteristics of the model, drawing the model, creating a geometric model by using a modeling tool of COMSOL according to the geometric shape of a thermal safety mechanism of a battery, setting parameters and four-way setting, setting first model parameters and four equations of the model, defining thermal physical parameters of the battery, defining related thermal physical parameters such as heat conductivity, specific heat capacity and the like according to materials and structures of the battery, setting battery boundary conditions such as temperature, heat flow and the like according to the actual application environment of the battery, setting a thermal runaway reaction rate equation according to the chemical reaction characteristics of the battery, dividing grids according to the complexity and calculation resources of the model, dividing the proper grids according to the calculation accuracy and efficiency of the model, performing post-processing analysis according to simulation results, and optimizing the model, and obtaining the thermal runaway mechanism model.
And step S230, comparing the temperature parameter with the temperature parameter extreme value, and carrying out battery thermal runaway early warning according to the comparison result.
In this embodiment, the temperature parameter is compared with the temperature parameter extremum, and if the temperature parameter is greater than the temperature parameter extremum, a battery thermal runaway warning is performed.
In one embodiment, comparing the temperature parameter with the temperature parameter extremum and performing thermal runaway warning of the battery according to the comparison result comprises triggering a first-stage battery cooling measure if the temperature parameter is greater than the first temperature parameter extremum and less than or equal to the second temperature parameter extremum, triggering a first-stage thermal runaway warning and a second-stage battery cooling measure if the temperature parameter is greater than the second temperature parameter extremum and less than or equal to the third temperature parameter extremum, triggering a second-stage thermal runaway warning and a third-stage battery cooling measure and a thermal runaway protection measure if the temperature parameter is greater than the third temperature parameter extremum and less than or equal to the fourth temperature parameter extremum, and triggering a third-stage thermal runaway warning and a fourth-stage battery cooling measure and a thermal runaway protection and a thermal runaway spreading measure if the temperature parameter is greater than the fourth temperature parameter extremum.
In this embodiment, the temperature parameter extremum includes, from small to large, a first temperature parameter extremum of the safe operation of the battery to be measured, a second temperature parameter extremum of the self-heat generation stage, a third temperature parameter extremum of the battery voltage dip stage, and a fourth temperature parameter extremum of the thermal runaway stage after the voltage dip. As the temperature parameter increases, the thermal runaway is more difficult to control, so that the thermal runaway early warning measures triggered are different between different magnitudes of the temperature parameter, and the greater the temperature parameter is, the higher the level of the thermal runaway early warning measures is. Therefore, the early warning measure grade is determined according to the specific temperature parameter, and corresponding protection and cooling measures are given, so that the thermal runaway of the battery can be effectively controlled and treated, and the accurate early warning of the thermal runaway of the battery is realized.
In the embodiment, the cooling measure intensity from the first-level battery cooling measure to the fourth-level battery cooling measure is increased, and the early warning level from the first-level early warning of thermal runaway to the third-level early warning of thermal runaway is increased.
In one possible embodiment, the temperature parameter exceeds the first temperature parameter extremum, or the temperature parameter extremum above the first temperature parameter extremum, and the thermal runaway problem is determined by feeding back the working condition data and the corresponding temperature parameter extremum to the cloud.
In one possible embodiment, if the temperature parameter is greater than the second temperature parameter extremum and less than or equal to the third temperature parameter extremum, and if the temperature parameter is greater than the third temperature parameter extremum and less than or equal to the fourth temperature parameter extremum, the battery is deactivated.
In one possible embodiment, the system informs the primary thermal runaway warning, the secondary thermal runaway warning and the tertiary thermal runaway warning in the form of sound or images, it being understood that the different levels of warning are different in the form of sound or images, for example, the alarm sound frequency is different and the image content is different.
In one possible implementation, when the third temperature parameter extremum corresponding to the battery slump phase is obtained according to the thermal safety mechanism model, the total duration t 1 of the battery slump phase is also obtained, and when the fourth temperature parameter extremum corresponding to the thermal runaway phase is obtained after slump, the total duration t 2 of the thermal runaway phase is also obtained.
As a possible embodiment, the total duration t 1 of the battery voltage dip stage is obtained, the potential thermal runaway risk can be early warned based on t 1, the total duration t 2 of the thermal runaway stage is obtained, a specific early warning strategy can be formulated based on t 2, and timely and effective measures can be ensured to be taken after the thermal runaway occurs.
In one embodiment, the temperature parameter includes a temperature value and a temperature rise rate, the temperature parameter extremum includes a temperature extremum and a temperature rise rate extremum, the comparing the temperature parameter extremum with the temperature parameter extremum and triggering a corresponding thermal runaway warning measure according to the comparing result includes comparing the temperature value with the temperature extremum and comparing the temperature rise rate with the temperature rise rate extremum, and triggering the thermal runaway warning measure when the temperature value is greater than the temperature extremum and the temperature rise rate is greater than the temperature rise rate extremum.
In the embodiment, the thermal runaway early warning measures are determined by combining the temperature value and the temperature rise rate, so that the problem of false alarm of thermal runaway early warning under a single temperature parameter is avoided, and the accuracy of the thermal runaway early warning is improved.
In one embodiment, the electrical parameter includes a voltage parameter, the warning parameter extremum further includes a voltage parameter extremum, and before triggering the thermal runaway warning measure, the method further includes comparing the voltage parameter with the voltage parameter extremum, and entering a triggering stage of the thermal runaway warning measure when the voltage parameter is greater than the voltage parameter extremum.
In this embodiment, the voltage parameter extremum includes, from small to large, the first voltage parameter extremum of the safe operation of the battery to be measured, the second voltage parameter extremum of the self-heating phase, the third voltage parameter extremum of the battery voltage dip phase, and the fourth voltage parameter extremum of the thermal runaway phase.
In the embodiment, the thermal runaway early warning measures are determined by combining the two parameters of the temperature parameter and the voltage parameter, so that the problem of false alarm and false alarm of the thermal runaway early warning under a single parameter is avoided, and the accuracy of the thermal runaway early warning is improved.
Referring to fig. 4, fig. 4 is a flowchart illustrating a specific battery thermal runaway warning method according to an exemplary embodiment of the present application. As shown in fig. 4, the specific steps of the battery thermal runaway warning method are described in detail as follows:
Step S410, building an aging model by combining the thermocouple model and building a thermal safety mechanism model;
Step S420, monitoring working condition data of the battery in real time, and respectively inputting an aging model and a thermal safety mechanism model;
Step S430, obtaining a first temperature parameter extremum and a first voltage parameter extremum of safe operation of the battery through an aging model, and obtaining a second temperature parameter extremum and a second voltage parameter extremum of the battery in a self-heating stage, a third temperature parameter extremum and a third voltage parameter extremum of a battery voltage dip stage, and a fourth temperature parameter threshold and a fourth voltage parameter extremum of a thermal runaway stage through a thermal safety mechanism model;
step S440, comparing the monitored temperature parameter and voltage parameter with the temperature parameter extremum and voltage parameter extremum obtained by simulation respectively;
Step S450, triggering corresponding thermal runaway early warning measures according to the comparison result.
According to the battery thermal runaway early warning method, firstly, working condition data of a battery to be detected are obtained, the working condition data comprise the operating state data of the battery to be detected and the environmental data of the environment, wherein the state data comprise temperature parameters, electrical parameters, health state parameters and charge state parameters, then the working condition data are input into a battery thermal runaway simulation model, the thermal runaway simulation of the battery to be detected is carried out, an early warning parameter extremum of the battery to be detected under the working condition data is obtained, the early warning parameter extremum comprises a temperature parameter extremum, the battery thermal runaway simulation model is constructed through the thermal performance of the battery under various working condition data in a full life cycle, finally, the temperature parameter and the temperature parameter extremum are compared, the battery thermal runaway early warning is carried out according to comparison results, and the early warning parameter extremum of the battery under different health states and charge states can be predicted according to the environmental data, the temperature parameters and the electrical parameters, and whether the battery reaches the thermal runaway early warning condition is judged based on the extreme value of the working condition data, and the early warning effect of early warning thermal runaway is achieved.
Referring to fig. 5, fig. 5 is a block diagram illustrating a battery thermal runaway warning system according to an exemplary embodiment of the present application. The system may be applied to the implementation environment shown in fig. 1, and it should be understood that the system may also be applied to other exemplary implementation environments, and the implementation environment to which the system is applied is not limited by the present embodiment.
As shown in fig. 5, in an exemplary embodiment, the battery thermal runaway warning system 500 at least includes an acquisition module 510, a simulation module 520, and a warning module 530, which are described in detail below:
The acquiring module 510 is configured to acquire working condition data of the battery to be tested, where the working condition data includes state data and environmental data of an environment where the working condition data is located, and the state data includes a temperature parameter, an electrical parameter, a health state parameter and a state of charge parameter;
The simulation module 520 is configured to input working condition data into a thermal runaway simulation model of the battery, perform thermal runaway simulation on the battery to be tested according to the working condition data, and obtain an early warning parameter extremum of the battery to be tested under the working condition data, where the early warning parameter extremum includes a temperature parameter extremum, and the thermal runaway simulation model of the battery is constructed through thermal properties of the battery under various working condition data in a full life cycle;
the early warning module 530 is configured to compare the temperature parameter with the temperature parameter extremum, and perform early warning of thermal runaway of the battery according to the comparison result.
It should be noted that, the battery thermal runaway warning system provided by the foregoing embodiment and the battery thermal runaway warning method provided by the foregoing embodiment belong to the same concept, where the content of performing the operation by each module has been described in detail in the method embodiment, and will not be described herein again.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an in-vehicle apparatus according to an embodiment of the present application. Fig. 6 shows a schematic diagram of a computer system suitable for use in implementing the in-vehicle apparatus of the embodiment of the present application. It should be noted that, the computer system 600 of the in-vehicle apparatus shown in fig. 6 is only an example, and should not impose any limitation on the functions and the application scope of the embodiment of the present application.
As shown in fig. 6, the computer system 600 includes a central processing unit (Central Processing Unit, CPU) 601 that can perform various appropriate actions and processes, such as performing the methods in the above-described embodiments, according to a program stored in a Read-Only Memory (ROM) 602 or a program loaded from a storage portion 608 into a random access Memory (Random Access Memory, RAM) 603. In the RAM603, various programs and data required for system operation are also stored. The CPU601, ROM 602, and RAM603 are connected to each other through a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
Connected to the I/O interface 605 are an input section 606 including a keyboard, a mouse, and the like, an output section 607 including a display such as a Cathode Ray Tube (CRT), a Liquid crystal display (Liquid CRYSTAL DISPLAY, LCD), and a speaker, a storage section 608 including a hard disk, and the like, and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. When executed by a Central Processing Unit (CPU) 601, performs the various functions defined in the system of the present application.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to perform the battery thermal runaway warning method as described above. The computer-readable storage medium may be contained in the in-vehicle apparatus described in the above embodiment or may exist alone without being incorporated in the in-vehicle apparatus.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, etc., or any suitable combination of the foregoing.
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 application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, 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 or flowchart illustration, and combinations of blocks in the block diagrams 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 units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The above embodiments are merely illustrative of the principles of the present application and its effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the application. It is therefore intended that all equivalent modifications and changes made by those skilled in the art without departing from the spirit and technical spirit of the present application shall be covered by the appended claims.
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