CN115663311A - Battery core temperature determination method and device, electronic equipment and storage medium - Google Patents
Battery core temperature determination method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN115663311A CN115663311A CN202211598058.1A CN202211598058A CN115663311A CN 115663311 A CN115663311 A CN 115663311A CN 202211598058 A CN202211598058 A CN 202211598058A CN 115663311 A CN115663311 A CN 115663311A
- Authority
- CN
- China
- Prior art keywords
- temperature
- cell
- battery cell
- battery
- tested
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Landscapes
- Secondary Cells (AREA)
Abstract
The invention discloses a method and a device for determining the temperature of a battery core, electronic equipment and a storage medium. The method comprises the following steps: acquiring measurement data of a to-be-measured battery cell, wherein the measurement data of the to-be-measured battery cell comprises battery cell position information, charge state information, module current and battery cell nickel strip temperature; inputting the cell position information, the charge state information, the module current and the cell nickel strap temperature into a cell-nickel strap temperature difference model which is trained in advance to obtain cell-nickel strap temperature difference data; and determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model. According to the scheme, the accurate cell-nickel strip temperature difference data is obtained by inputting the cell position information, the charge state information, the module current and the cell surface temperature into the pre-trained cell-nickel strip temperature difference model, the temperature distribution result of the cell to be measured is determined according to the accurate cell-nickel strip temperature difference data and the cell temperature model, and the measurement accuracy of the cell temperature distribution is improved.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a method and a device for determining a cell temperature, electronic equipment and a storage medium.
Background
At present, the new energy industry develops rapidly, and more energy storage products such as outdoor power supplies and uninterruptible power supplies need to be charged and discharged at a high rate in a high-temperature application scene. When the battery is charged and discharged at high multiplying power under higher ambient temperature, the heat power consumption of the battery core is large, the heat dissipation is difficult, and the problem of over-temperature of the battery core is easy to occur. The battery core temperature is monitored to be out of limit in time, and charging and discharging current reduction and shutdown of the battery are carried out, so that the safety of users is protected, and the service life of products is maintained.
At present, the temperature monitoring of the battery is mainly realized by arranging thermistor measuring points on a positive electrode nickel strip and a negative electrode nickel strip of a battery core so as to monitor the highest temperature of the whole battery.
In the process of implementing the invention, the inventor finds that at least the following technical problems exist in the prior art: the prior art scheme has the problem of inaccurate temperature measurement.
Disclosure of Invention
The invention provides a method and a device for determining the temperature of a battery core, electronic equipment and a storage medium, which aim to solve the problem of inaccurate temperature measurement.
According to an aspect of the present invention, there is provided a cell temperature determination method, including:
acquiring measurement data of a to-be-measured battery cell, wherein the measurement data of the to-be-measured battery cell comprises battery cell position information, charge state information, module current and battery cell nickel strap temperature;
inputting the cell position information, the charge state information, the module current and the cell nickel strap temperature into a cell-nickel strap temperature difference model which is trained in advance to obtain cell-nickel strap temperature difference data;
and determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
According to another aspect of the present invention, there is provided a cell temperature determination apparatus including:
the measurement data acquisition module is used for acquiring the measurement data of the battery cell to be measured, wherein the measurement data of the battery cell to be measured comprises battery cell position information, charge state information, module current and battery cell nickel strap temperature;
the temperature difference data prediction module is used for inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data;
and the temperature distribution determining module is used for determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the cell temperature determination method according to any embodiment of the present invention.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the cell temperature determination method according to any one of the embodiments of the present invention when the computer instructions are executed.
According to the technical scheme of the embodiment of the invention, the accurate cell-nickel strap temperature difference data of the cell to be measured is obtained by inputting the cell position information, the charge state information, the module current and the cell nickel strap temperature of the cell to be measured into the pre-trained cell-nickel strap temperature difference model, and the temperature distribution result of the cell to be measured is determined according to the accurate cell-nickel strap temperature difference data and the cell temperature model, so that the measurement accuracy of the temperature distribution result is improved, and the problem of inaccurate temperature measurement is solved.
It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a flowchart of a cell temperature determination method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of distribution of cylindrical cell nodes according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a neural network architecture according to an embodiment of the present invention;
fig. 4 is a flowchart of a cell temperature determining method according to a second embodiment of the present invention;
fig. 5 is a flowchart of a cell temperature determination method according to a third embodiment of the present invention;
fig. 6 is a schematic structural diagram of a cell temperature determination apparatus according to a fourth embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device implementing the cell temperature determination method according to the embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a flowchart of a cell temperature determination method according to an embodiment of the present invention, where the embodiment is applicable to a situation where an internal temperature of a battery cell is automatically predicted, and the method may be executed by a cell temperature determination device, where the cell temperature determination device may be implemented in a form of hardware and/or software, and the cell temperature determination device may be configured in a computer terminal. As shown in fig. 1, the method includes:
s110, obtaining measurement data of the battery cell to be measured, wherein the measurement data of the battery cell to be measured comprise battery cell position information, charge state information, module current and battery cell nickel strip temperature.
In this embodiment, the battery core to be tested refers to a battery core to be subjected to temperature prediction, and the number of the battery cores to be tested may be one or more. When the number of the cells to be tested is multiple, the battery is indicated to be an assembled battery, in other words, the battery may include multiple cells. The measurement data of the battery cell to be measured refers to battery cell associated data which can be acquired through information acquisition equipment, and may include, but is not limited to, battery cell position information, charge state information, module current and battery cell nickel strap temperature. The cell position information refers to a deployment position of the cell in the battery. Illustratively, the cell position information includes a horizontal column sequence and a vertical column sequence, the horizontal column sequence is the horizontal position information of the cell in the battery, and the vertical column sequence is the vertical position information of the cell in the battery. The State Of Charge (SOC) refers to the State Of Charge information Of the battery cell. The module current refers to the overall current of the battery module. The cell nickel strap temperature refers to the measured temperature at the cell nickel strap.
For example, the measurement data of the electrical core to be measured may be obtained by calling from a preset storage path, or may also be obtained by acquiring in real time through an information acquisition device, which is not limited herein. For example, the cell position information, the state of charge information, and the module current may be obtained from the recorded data of the battery management system; the temperature of the nickel strap of the battery core can be measured by a thermocouple arranged on the battery core.
S120, inputting the cell position information, the charge state information, the module current and the cell nickel strap temperature into a pre-trained cell-nickel strap temperature difference model to obtain cell-nickel strap temperature difference data.
In this embodiment, the battery cell-nickel strap temperature difference model refers to a neural network model trained in advance, and may be used to predict the temperature difference between the battery cell body and the positive and negative nickel straps. In other words, the battery cell-nickel strip temperature difference data refers to the temperature difference value between the battery cell body and the positive and negative electrode nickel strips. Optionally, the cell-nickel strip temperature difference data includes cell body-upper nickel strip temperature difference data and/or cell body-lower nickel strip temperature difference data. The battery cell body-upper nickel strap temperature difference data may be a temperature difference value between the battery cell body and the positive electrode nickel strap, and correspondingly, the battery cell body-lower nickel strap temperature difference data may be a temperature difference value between the battery cell body and the negative electrode nickel strap.
Specifically, the cell temperature difference model comprises an input layer, a hidden layer and an output layer; correspondingly, with electric core position information, state of charge information, module electric current and electric core nickel strap temperature input to the electric core difference in temperature model of training completion in advance, obtain electric core difference in temperature data, include: inputting the position information of the battery cell, the charge state information, the module current and the nickel strap temperature of the battery cell through an input layer; converting the position information, the charge state information, the module current and the nickel strap temperature of the battery core through a hidden layer to obtain hidden characteristic data; and outputting the hidden characteristic data through an output layer to obtain the temperature difference data of the cell body-upper nickel strip and the temperature difference data of the cell body-lower nickel strip.
S130, determining a temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
In this embodiment, the temperature distribution result refers to temperature distribution data of each node inside the battery cell. Optionally, the temperature distribution result may be temperature distribution data of the battery cell to be tested at any time. The cell temperature model can be used for predicting the temperature distribution result of the cell to be tested.
Exemplarily, fig. 2 is a schematic diagram of distribution of cylindrical cell nodes provided in this embodiment. Taking a cylindrical battery cell as an example, the cylindrical battery cell includes [0,1,2,3,4,5, R ], specifically, the temperature distribution result includes a temperature corresponding to node 0, a temperature corresponding to node 1, a temperature corresponding to node 2, a temperature corresponding to node 3, a temperature corresponding to node 4, a temperature corresponding to node 5, and a temperature corresponding to node R, where node 0 is a center node, and node R is a battery cell surface node. Correspondingly, the cell temperature model may be a temperature model of the cylindrical cell on the diameter. It should be noted that, in the heating process of the battery cell, the temperature difference is mainly reflected in the radial direction from inside to outside of the battery cell, and in this embodiment, a one-dimensional battery cell temperature field is simplified for the battery cell, and it is considered that the temperatures of the points on the same radius are the same.
In some optional embodiments, the training process of the cell-nickel strip temperature difference model includes: acquiring a plurality of groups of training sample data, wherein the training sample data comprises cell position sample information, charge state sample information, module sample current and cell surface sample temperature, and cell temperature difference label data corresponding to the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature; training an initial model based on the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature, and cell temperature difference label data corresponding to the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature to obtain a cell temperature difference model; wherein the cell skin sample temperature comprises: the temperature of the outer surface of the battery cell body, the temperature of the upper nickel strap of the battery cell and the temperature of the lower nickel strap of the battery cell.
For example, fig. 3 is a schematic diagram of a neural network architecture provided in this embodiment. The sample input dimension of the neural network of the battery cell-nickel strip temperature difference model is 5, namely a transverse sequence, a longitudinal sequence, charge state information, module current and battery cell nickel strip temperature; the output dimension is 2, and the data are the temperature difference data between the cell body and the upper nickel strip and the temperature difference data between the cell body and the lower nickel strip respectively; the number of hidden nodes is s. In the following formula, (1) - (3) obtain a network calculation error through forward calculation; (4) - (7) through inverse calculation, through the connection weight matrix and the threshold vector of the error correction network.
Wherein the content of the first and second substances,
a connection weight matrix representing the ith input layer neuron and the jth hidden layer neuron,
represents the ith input sample, and f represents the activation function;
representing hidden feature data;
the threshold vector representing the jth hidden layer neuron.
Wherein the content of the first and second substances,
representing a connection weight matrix for the jth hidden layer neuron and the kth output layer neuron,
a threshold vector representing the kth output layer neuron, s representing the number of hidden layer nodes;
and (4) representing predicted battery core-nickel strip temperature difference data.
Wherein the content of the first and second substances,
cell temperature difference label data representing the kth output layer neuron,
indicating a network computation error.
Wherein the content of the first and second substances,
representing a modified connection weight matrix for the jth hidden layer neuron and the kth output layer neuron,
indicating the learning rate.
Wherein, the first and the second end of the pipe are connected with each other,
representing the modified k-th threshold vector.
Wherein the content of the first and second substances,
and representing the modified connection weight matrix of the ith input layer neuron and the jth hidden layer neuron.
Wherein the content of the first and second substances,
the threshold vector representing the modified jth hidden layer neuron.
According to the technical scheme of the embodiment of the invention, the accurate cell-nickel strip temperature difference data of the to-be-measured cell is obtained by inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature of the to-be-measured cell into the pre-trained cell-nickel strip temperature difference model, and the temperature distribution result of the to-be-measured cell is determined according to the accurate cell-nickel strip temperature difference data and the cell temperature model, so that the measurement accuracy of the temperature distribution result is improved, and the problem of inaccurate temperature measurement is solved.
Example two
Fig. 4 is a flowchart of a method for determining a cell temperature according to a second embodiment of the present invention, where the method according to this embodiment may be combined with various alternatives of the method for determining a cell temperature according to the foregoing embodiments. The cell temperature determination method provided by the embodiment is further optimized. Optionally, before determining a temperature distribution result of the to-be-measured electric core based on the electric core-nickel strip temperature difference data and the electric core temperature model, the method further includes: acquiring the temperature of each node of a battery core to be tested at a historical moment, wherein the historical moment comprises a battery working initial moment and any moment after the battery working initial moment; correspondingly, the determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model includes: and determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
As shown in fig. 4, the method includes:
s210, acquiring measurement data of the battery cell to be measured, wherein the measurement data of the battery cell to be measured comprise battery cell position information, charge state information, module current and battery cell nickel strap temperature.
S220, inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data.
And S230, acquiring the temperature of each node of the battery cell to be tested at historical time, wherein the historical time comprises the initial working time of the battery and any time after the initial working time of the battery.
S240, determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
In this embodiment, the historical time may include a battery operation initial time and any time after the battery operation initial time. In other words, the temperature of the battery to be tested at any moment can be monitored, so that the real-time monitoring of the battery is realized.
In some optional embodiments, the obtaining the temperature of each node of the battery cell to be tested at the historical time includes: acquiring the environment temperature of the battery to be tested, and determining the environment temperature of the battery to be tested as the temperature of each node of the battery cell to be tested at the initial working moment of the battery; correspondingly, determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical time, the battery cell-nickel strip temperature difference data and the battery cell temperature model, includes: and determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the initial working moment of the battery, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
And the temperature of each node of the battery cell at the initial moment is consistent and is consistent with the ambient temperature. It can be understood that, in the case where the battery is not in operation, the battery does not generate heat, and the battery temperature is in a normal temperature state, and is a measurable value in accordance with the ambient temperature. Any time after the initial time may be any time the battery is in operation. It can be understood that, when the battery is in an operating state, the battery may generate heat, and the temperatures of the nodes of the radii of the battery cells in the battery are also inconsistent and cannot be directly measured, and the temperatures of the nodes of the battery cells at the initial time may be predicted.
In some optional embodiments, the cell temperature model comprises a thermal conductivity differential equation and a heat transfer boundary condition; the determining, based on the temperature of each node of the battery cell to be tested at the initial moment of the battery operation, the battery cell-nickel strap temperature difference data, and the battery cell temperature model, a temperature distribution result of the battery cell to be tested includes: discretizing the heat conduction differential equation and the heat transfer boundary condition to obtain a discrete heat conduction differential equation and a discrete heat transfer boundary condition; solving to obtain the temperature of each radius node of the battery cell to be tested at the next moment based on the temperature of each node of the battery cell to be tested at the initial working moment of the battery and the discrete heat conduction differential equation; determining the temperature of the central node of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment and the discrete heat transfer boundary condition; determining the temperature of the surface node of the battery cell to be tested at the next moment based on the battery cell nickel strip temperature and the battery cell-nickel strip temperature difference data; determining a temperature distribution result of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment, the temperature of the center node of the battery cell to be tested at the next moment and the temperature of the surface node of the battery cell to be tested at the next moment; if the next moment is a target moment, determining the temperature distribution result of the battery cell to be tested at the next moment as the temperature distribution result of the battery cell to be tested; and if not, continuously and circularly solving the temperature distribution result of the battery cell to be tested at the next moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model until the target moment to obtain the temperature distribution result of the battery cell to be tested.
Wherein, the heat conduction differential equation may be a heat conduction differential equation in a radial direction of the polar coordinate system. The heat transfer boundary condition refers to a regular representation of the change of the solved variable or its derivative with time and position over the boundary of the solution area. The target time can be a real-time change value so as to realize real-time monitoring of the temperature of the battery cell to be detected.
For example, the thermal conductivity differential equation may be:
the heat transfer boundary conditions may be:
wherein, the first and the second end of the pipe are connected with each other,
represents the cell density, C represents the specific heat capacity of the cell,
represents the heat conductivity coefficient of the cell in the radial direction, q represents the heat generation rate of the cell, T represents time, r represents radius, T represents the temperature of the cell in different radial directions,
represents the surface temperature of the cell body, NET _ output represents the cell temperature difference data,
representing a temperature measurement at the cell nickel strap location. It should be noted that the heat transfer boundary condition is considered as thermal insulation of the center inside the cell.
Further, the heat conduction differential equation and the heat transfer boundary condition can be discretized by a finite difference method, wherein the discretized heat conduction differential equation is as follows:
the corresponding and discrete heat transfer boundary conditions are:
wherein n represents time, k represents a cell radius, kmax represents a maximum cell radius, and the cell heat generation rate q can be obtained by solving the following formula:
wherein the content of the first and second substances,
the cell volume is represented;
the cell open-circuit voltage is represented and can be measured through a cell SOC-open-circuit voltage curve;
represents a cell terminal voltage, and I represents a cell current;
the cell entropy thermal coefficient can be obtained by measuring a cell SOC-entropy thermal coefficient curve. The cell current, the cell terminal voltage and the SOC can be obtained in real time through a battery management system.
Further, the cell temperature distribution result inside the cell at each moment is calculated iteratively, and the iteration process is as follows:
acquiring the environment temperature of the battery to be tested at the initial moment, and determining the environment temperature of the battery to be tested as the temperature of each node of the battery core to be tested at the initial working moment of the battery;
solving the temperature of each node of the battery cell to be tested at the initial working moment of the battery and a discrete heat conduction differential equation to obtain the temperature of each radius node of the battery cell to be tested at the next moment;
determining the temperature of the central node of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment and the discrete heat transfer boundary condition;
determining the temperature of the surface node of the battery cell to be detected at the next moment based on the battery cell nickel strip temperature and the battery cell-nickel strip temperature difference data;
determining a temperature distribution result of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment, the temperature of a center node of the battery cell to be tested at the next moment and the temperature of a surface node of the battery cell to be tested at the next moment;
if the next moment is the target moment, determining the temperature distribution result of the battery cell to be tested at the next moment as the temperature distribution result of the battery cell to be tested; and if not, continuously and circularly solving the temperature distribution result of the battery cell to be tested, the battery cell-nickel strip temperature difference data and the battery cell temperature model at the next moment until the target moment to obtain the temperature distribution result of the battery cell to be tested.
The specific operation process is as follows:
expressed in matrix form as:
order to
，
，
，
；
Then:
according to the iteration process, the temperature distribution result of the battery core at each moment can be sequentially calculated in an iteration mode, the temperature value of the whole battery core at each moment can be obtained in real time, the battery management system can monitor the value in real time, and over-temperature protection measures can be implemented in real time.
According to the technical scheme of the embodiment of the invention, the temperature of each node of the battery cell to be tested at the historical moment is obtained, wherein the historical moment comprises the battery working initial moment and any moment after the battery working initial moment, and the temperature distribution result of the battery cell to be tested is further determined based on the temperature of each node of the battery cell to be tested at the historical moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
EXAMPLE III
Fig. 5 is a flowchart of a cell temperature determining method provided in a third embodiment of the present invention, and the method of this embodiment may be combined with various alternatives of the cell temperature determining method provided in the foregoing embodiments. The cell temperature determination method provided by the embodiment is further optimized. Optionally, after determining the temperature distribution result of the to-be-measured electric core based on the electric core-nickel strip temperature difference data and the electric core temperature model, the scheme further includes: and transmitting the highest temperature in the temperature distribution result of the battery core to be tested to a battery management system, and monitoring the temperature by the battery management system based on the highest temperature in the temperature distribution result of the battery core to be tested.
As shown in fig. 5, the method includes:
s310, obtaining measurement data of the battery cell to be measured, wherein the measurement data of the battery cell to be measured comprise battery cell position information, charge state information, module current and battery cell nickel strip temperature.
S320, inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data.
S330, determining a temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
S340, transmitting the highest temperature in the temperature distribution result of the battery cell to be tested to a battery management system, and monitoring the temperature by the battery management system based on the highest temperature in the temperature distribution result of the battery cell to be tested.
The maximum temperature in the temperature distribution result of the battery core to be tested can be used as a temperature monitoring value of the battery management system, and the battery management system can implement measures such as charging, discharging and current reduction, over-temperature protection and the like according to the temperature.
According to the technical scheme of the embodiment of the invention, the highest temperature in the temperature distribution result of the battery cell to be tested is transmitted to the battery management system, so that the battery management system can monitor the temperature according to the highest temperature in the temperature distribution result based on the battery cell to be tested, the problems of delay and hysteresis of shutdown of the battery when the temperature exceeds the limit due to the temperature difference between the nickel strap of the battery cell and the internal part of the battery cell are avoided, and the cycle service life of the battery cell is prolonged, and the long-term stable operation of the battery cell is facilitated to be improved.
Example four
Fig. 6 is a schematic structural diagram of a battery cell temperature determination apparatus according to a fourth embodiment of the present invention. As shown in fig. 6, the apparatus includes:
the measurement data acquisition module 410 is configured to acquire measurement data of a to-be-measured battery cell, where the measurement data of the to-be-measured battery cell includes battery cell position information, state of charge information, module current, and battery cell nickel strap temperature;
a temperature difference data prediction module 420, configured to input the electric core position information, the state of charge information, the module current, and the electric core nickel strap temperature into a pre-trained electric core-nickel strap temperature difference model, so as to obtain electric core-nickel strap temperature difference data;
and a temperature distribution determining module 430, configured to determine a temperature distribution result of the to-be-measured electrical core based on the electrical core-nickel strap temperature difference data and the electrical core temperature model.
According to the technical scheme of the embodiment of the invention, the accurate cell-nickel strip temperature difference data of the to-be-measured cell is obtained by inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature of the to-be-measured cell into the pre-trained cell-nickel strip temperature difference model, and the temperature distribution result of the to-be-measured cell is determined according to the accurate cell-nickel strip temperature difference data and the cell temperature model, so that the measurement accuracy of the temperature distribution result is improved, and the problem of inaccurate temperature measurement is solved.
In some optional embodiments, the cell-nickel strap temperature difference data comprises cell body-upper nickel strap temperature difference data and/or cell body-lower nickel strap temperature difference data.
In some optional embodiments, the apparatus further comprises:
the historical temperature acquisition module is used for acquiring the temperature of each node of the battery cell to be tested at a historical moment, wherein the historical moment comprises a battery working initial moment and any moment after the battery working initial moment;
accordingly, the temperature distribution determination module 430 includes:
and the battery cell temperature distribution determining unit is used for determining the temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
In some optional embodiments, the historical temperature obtaining module is specifically configured to:
acquiring the environment temperature of the battery to be tested, and determining the environment temperature of the battery to be tested as the temperature of each node of the battery cell to be tested at the initial working moment of the battery;
correspondingly, the cell temperature distribution determining unit comprises:
and the to-be-detected battery core temperature distribution determining subunit is used for determining a temperature distribution result of the to-be-detected battery core based on the temperature of each node of the to-be-detected battery core at the initial working moment of the battery, the battery core-nickel strip temperature difference data and the battery core temperature model.
In some alternative embodiments, the cell temperature model includes a thermal conductivity differential equation and a heat transfer boundary condition; the to-be-tested battery core temperature distribution determining subunit is specifically configured to:
discretizing the heat conduction differential equation and the heat transfer boundary condition to obtain a discrete heat conduction differential equation and a discrete heat transfer boundary condition;
solving to obtain the temperature of each radius node of the battery cell to be tested at the next moment based on the temperature of each node of the battery cell to be tested at the initial working moment of the battery and the discrete heat conduction differential equation;
determining the temperature of the central node of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment and the discrete heat transfer boundary condition;
determining the temperature of the surface node of the battery cell to be detected at the next moment based on the battery cell nickel strap temperature and the battery cell-nickel strap temperature difference data;
determining a temperature distribution result of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment, the temperature of the center node of the battery cell to be tested at the next moment and the temperature of the surface node of the battery cell to be tested at the next moment;
if the next moment is a target moment, determining the temperature distribution result of the battery cell to be tested at the next moment as the temperature distribution result of the battery cell to be tested; and if not, continuously and circularly solving the temperature distribution result of the battery cell to be tested at the next moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model until the target moment to obtain the temperature distribution result of the battery cell to be tested.
In some optional embodiments, the apparatus further comprises:
and the temperature monitoring module is used for transmitting the highest temperature in the temperature distribution result of the battery core to be tested to the battery management system, and the battery management system carries out temperature monitoring on the basis of the highest temperature in the temperature distribution result of the battery core to be tested.
In some optional embodiments, the training process of the cell-nickel strip temperature difference model includes:
acquiring a plurality of groups of training sample data, wherein the training sample data comprises cell position sample information, charge state sample information, module sample current and cell surface sample temperature, and cell temperature difference label data corresponding to the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature;
training an initial model based on the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature, and cell temperature difference label data corresponding to the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature to obtain a cell temperature difference model;
wherein the cell skin sample temperature comprises: the temperature of the outer surface of the battery cell body, the temperature of the upper nickel strap of the battery cell and the temperature of the lower nickel strap of the battery cell.
The cell temperature determination device provided by the embodiment of the invention can execute the cell temperature determination method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
FIG. 7 illustrates a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 7, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The processor 11 performs the various methods and processes described above, such as the cell temperature determination method, including:
acquiring measurement data of a to-be-measured battery cell, wherein the measurement data of the to-be-measured battery cell comprises battery cell position information, charge state information, module current and battery cell nickel strip temperature;
inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data;
and determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
In some embodiments, the cell temperature determination method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the memory unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the cell temperature determination method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the cell temperature determination method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on 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 (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for determining a cell temperature, comprising:
acquiring measurement data of a to-be-measured battery cell, wherein the measurement data of the to-be-measured battery cell comprises battery cell position information, charge state information, module current and battery cell nickel strap temperature;
inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data;
and determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
2. The method of claim 1, wherein the cell-nickel strap temperature differential data comprises cell body-upper nickel strap temperature differential data and/or cell body-lower nickel strap temperature differential data.
3. The method of claim 1, wherein before the determining the temperature distribution result of the cell under test based on the cell-nickel strip temperature difference data and a cell temperature model, the method further comprises:
acquiring the temperature of each node of a battery core to be tested at a historical moment, wherein the historical moment comprises a battery working initial moment and any moment after the battery working initial moment;
correspondingly, the determining a temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model includes:
and determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
4. The method of claim 3, wherein the obtaining the temperature of each node of the battery cell to be tested at the historical time includes:
acquiring the environmental temperature of the battery to be tested, and determining the environmental temperature of the battery to be tested as the temperature of each node of the battery cell to be tested at the initial working moment of the battery;
correspondingly, the determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the historical time, the battery cell-nickel strip temperature difference data and the battery cell temperature model includes:
and determining a temperature distribution result of the battery cell to be tested based on the temperature of each node of the battery cell to be tested at the initial working moment of the battery, the battery cell-nickel strip temperature difference data and the battery cell temperature model.
5. The method of claim 3, wherein the cell temperature model comprises a thermal conductivity differential equation and a heat transfer boundary condition;
the determining, based on the temperature of each node of the battery cell to be tested at the initial moment of the battery operation, the battery cell-nickel strap temperature difference data, and the battery cell temperature model, a temperature distribution result of the battery cell to be tested includes:
discretizing the heat conduction differential equation and the heat transfer boundary condition to obtain a discrete heat conduction differential equation and a discrete heat transfer boundary condition;
solving to obtain the temperature of each radius node of the battery cell to be tested at the next moment based on the temperature of each node of the battery cell to be tested at the initial working moment of the battery and the discrete heat conduction differential equation;
determining the temperature of the central node of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment and the discrete heat transfer boundary condition;
determining the temperature of the surface node of the battery cell to be detected at the next moment based on the battery cell nickel strap temperature and the battery cell-nickel strap temperature difference data;
determining a temperature distribution result of the battery cell to be tested at the next moment based on the temperature of each radius node of the battery cell to be tested at the next moment, the temperature of the center node of the battery cell to be tested at the next moment and the temperature of the surface node of the battery cell to be tested at the next moment;
if the next moment is a target moment, determining the temperature distribution result of the battery cell to be tested at the next moment as the temperature distribution result of the battery cell to be tested; and if not, continuously and circularly solving the temperature distribution result of the battery cell to be tested at the next moment, the battery cell-nickel strip temperature difference data and the battery cell temperature model until the target moment to obtain the temperature distribution result of the battery cell to be tested.
6. The method of claim 1, wherein after determining the temperature distribution result of the cell under test based on the cell-nickel strip temperature difference data and a cell temperature model, the method further comprises:
and transmitting the highest temperature in the temperature distribution result of the battery core to be tested to a battery management system, and monitoring the temperature by the battery management system based on the highest temperature in the temperature distribution result of the battery core to be tested.
7. The method of claim 1, wherein the training process of the cell-nickel strip temperature difference model comprises:
acquiring a plurality of groups of training sample data, wherein the training sample data comprise electric core position sample information, charge state sample information, module sample current and electric core surface sample temperature, and electric core temperature difference label data corresponding to the electric core position sample information, the charge state sample information, the module sample current and the electric core surface sample temperature;
training an initial model based on the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature, and cell temperature difference label data corresponding to the cell position sample information, the charge state sample information, the module sample current and the cell surface sample temperature to obtain a cell temperature difference model;
wherein the cell skin sample temperature comprises: the temperature of the outer surface of the battery cell body, the temperature of the upper nickel strap of the battery cell and the temperature of the lower nickel strap of the battery cell.
8. A cell temperature determination apparatus, comprising:
the measurement data acquisition module is used for acquiring the measurement data of the battery cell to be measured, wherein the measurement data of the battery cell to be measured comprises battery cell position information, charge state information, module current and battery cell nickel strap temperature;
the temperature difference data prediction module is used for inputting the cell position information, the charge state information, the module current and the cell nickel strip temperature into a pre-trained cell-nickel strip temperature difference model to obtain cell-nickel strip temperature difference data;
and the temperature distribution determining module is used for determining the temperature distribution result of the battery cell to be tested based on the battery cell-nickel strip temperature difference data and the battery cell temperature model.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform the cell temperature determination method of any of claims 1-7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a processor to execute the method for determining a cell temperature according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211598058.1A CN115663311B (en) | 2022-12-14 | 2022-12-14 | Battery cell temperature determining method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211598058.1A CN115663311B (en) | 2022-12-14 | 2022-12-14 | Battery cell temperature determining method and device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115663311A true CN115663311A (en) | 2023-01-31 |
| CN115663311B CN115663311B (en) | 2023-05-05 |
Family
ID=85023187
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211598058.1A Active CN115663311B (en) | 2022-12-14 | 2022-12-14 | Battery cell temperature determining method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115663311B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013765A (en) * | 2007-01-26 | 2007-08-08 | 清华大学 | Method for real-time evaluating internal-external temperature difference of nickel-hydrogen electrokinetic cell |
| JP2018147680A (en) * | 2017-03-03 | 2018-09-20 | 住友電気工業株式会社 | Temperature abnormality determination device, temperature abnormality determination method, and computer program |
| US20190058336A1 (en) * | 2017-08-15 | 2019-02-21 | Dell Products L.P. | Battery management using battery temperature distribution |
| CN110118617A (en) * | 2019-05-30 | 2019-08-13 | 上海元城汽车技术有限公司 | The internal temperature of battery modules determines method, apparatus and intelligent terminal |
| CN111725573A (en) * | 2019-03-22 | 2020-09-29 | 东莞新能安科技有限公司 | Temperature compensation method, device with rechargeable battery and storage medium |
| CN112016190A (en) * | 2020-08-04 | 2020-12-01 | 华人运通(上海)新能源驱动技术有限公司 | Power battery temperature correction method and device and computer readable storage medium |
| CN113420471A (en) * | 2021-06-01 | 2021-09-21 | 上海交通大学 | Power lithium battery thermal model construction and establishment method and system based on electrochemical mechanism |
| CN113895309A (en) * | 2021-10-09 | 2022-01-07 | 北京理工大学 | Battery thermal management method applying digital twinning technology |
| CN114638156A (en) * | 2022-02-25 | 2022-06-17 | 香港科技大学 | Lithium battery temperature prediction method, device, equipment and storage medium |
| WO2022164127A1 (en) * | 2021-02-01 | 2022-08-04 | 한국전기연구원 | Digital twin device and digital twin-based battery temperature monitoring method |
| CN114966428A (en) * | 2022-05-12 | 2022-08-30 | 湖北亿纬动力有限公司 | Method for testing battery performance parameters |
| CN115436821A (en) * | 2022-09-02 | 2022-12-06 | 四川新能源汽车创新中心有限公司 | Method and device for identifying heat generation abnormity of battery system |
-
2022
- 2022-12-14 CN CN202211598058.1A patent/CN115663311B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101013765A (en) * | 2007-01-26 | 2007-08-08 | 清华大学 | Method for real-time evaluating internal-external temperature difference of nickel-hydrogen electrokinetic cell |
| JP2018147680A (en) * | 2017-03-03 | 2018-09-20 | 住友電気工業株式会社 | Temperature abnormality determination device, temperature abnormality determination method, and computer program |
| US20190058336A1 (en) * | 2017-08-15 | 2019-02-21 | Dell Products L.P. | Battery management using battery temperature distribution |
| CN111725573A (en) * | 2019-03-22 | 2020-09-29 | 东莞新能安科技有限公司 | Temperature compensation method, device with rechargeable battery and storage medium |
| CN110118617A (en) * | 2019-05-30 | 2019-08-13 | 上海元城汽车技术有限公司 | The internal temperature of battery modules determines method, apparatus and intelligent terminal |
| CN112016190A (en) * | 2020-08-04 | 2020-12-01 | 华人运通(上海)新能源驱动技术有限公司 | Power battery temperature correction method and device and computer readable storage medium |
| WO2022164127A1 (en) * | 2021-02-01 | 2022-08-04 | 한국전기연구원 | Digital twin device and digital twin-based battery temperature monitoring method |
| CN113420471A (en) * | 2021-06-01 | 2021-09-21 | 上海交通大学 | Power lithium battery thermal model construction and establishment method and system based on electrochemical mechanism |
| CN113895309A (en) * | 2021-10-09 | 2022-01-07 | 北京理工大学 | Battery thermal management method applying digital twinning technology |
| CN114638156A (en) * | 2022-02-25 | 2022-06-17 | 香港科技大学 | Lithium battery temperature prediction method, device, equipment and storage medium |
| CN114966428A (en) * | 2022-05-12 | 2022-08-30 | 湖北亿纬动力有限公司 | Method for testing battery performance parameters |
| CN115436821A (en) * | 2022-09-02 | 2022-12-06 | 四川新能源汽车创新中心有限公司 | Method and device for identifying heat generation abnormity of battery system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115663311B (en) | 2023-05-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yang et al. | Extreme learning machine-based thermal model for lithium-ion batteries of electric vehicles under external short circuit | |
| US11243262B2 (en) | Degradation estimation apparatus, computer program, and degradation estimation method | |
| EP3904894B1 (en) | Training device, estimation device, training method, estimation method, training program, and estimation program | |
| KR102362532B1 (en) | Method and apparatus for predicting state of battery health based on neural network | |
| CN108627766B (en) | Real-time measurement method for internal temperature of battery core in battery module and battery pack | |
| WO2019114240A1 (en) | Method and system for predicting state of charge of battery | |
| WO2014119328A1 (en) | Battery state estimating device | |
| US11619674B2 (en) | State estimation method and state estimation apparatus | |
| Sun et al. | Adaptive evolution enhanced physics-informed neural networks for time-variant health prognosis of lithium-ion batteries | |
| Chang et al. | Lithium-ion battery state of health estimation based on electrochemical impedance spectroscopy and cuckoo search algorithm optimized elman neural network | |
| CN109814037A (en) | Acquisition methods, terminal device and the medium of the hot coefficient of lithium ion battery entropy | |
| CN115214424A (en) | Temperature determination method and device of battery thermal management system and electronic equipment | |
| Li et al. | Lithium-ion battery state of health estimation based on multi-source health indicators extraction and sparse Bayesian learning | |
| CN110850315A (en) | Method and device for estimating state of charge of battery | |
| Ma et al. | A novel health index for battery RUL degradation modeling and prognostics | |
| EP4293373A1 (en) | Method and apparatus with battery short detection | |
| CN116859255A (en) | Method, device, equipment and medium for predicting state of health of energy storage battery | |
| CN115663311B (en) | Battery cell temperature determining method and device, electronic equipment and storage medium | |
| CN115946569A (en) | Battery charging time prediction method and device, electronic equipment and storage medium | |
| Nguyen-Thoi et al. | An effective deep neural network method for prediction of battery state at cell and module level | |
| CN115630502A (en) | Battery expansion force determination method, electronic device, and storage medium | |
| CN115128465A (en) | Battery thermal simulation system and method and electronic equipment | |
| Foo et al. | Virtual Sensor of Li-Ion Batteries in Electric Vehicles Using Data-Driven Analytic Thermal Solutions | |
| Xiong et al. | Neural network and physical enable one sensor to estimate the temperature for all cells in the battery pack | |
| Yang et al. | State of charge and state of health estimation of lithium-ion battery packs with inconsistent internal parameters using dual extended Kalman filter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |