CN116165555A

CN116165555A - Method, device, equipment, medium and product for identifying abnormal expansion phenomenon of battery cell

Info

Publication number: CN116165555A
Application number: CN202310124866.2A
Authority: CN
Inventors: 何志超; 陈喆; 王垒; 吕喆; 钱昊
Original assignee: Beijing Hyperstrong Technology Co Ltd
Current assignee: Beijing Hyperstrong Technology Co Ltd
Priority date: 2023-02-03
Filing date: 2023-02-03
Publication date: 2023-05-26

Abstract

The application provides a method, a device, equipment, a medium and a product for identifying abnormal expansion phenomenon of a battery cell, wherein the method comprises the following steps: acquiring the temperatures of corresponding target battery cells acquired by temperature sensors corresponding to a plurality of target battery cells in the operation process of the target battery energy storage system at all sampling points; judging whether at least one target cell has temperature-related outlier characteristics in the operation process according to the corresponding target cell temperature of each target cell at each sampling point; and identifying whether the battery core with abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic. According to the method, no additional temperature sensor is required to be deployed, the material cost or the acquisition cost of the system is not additionally increased, and the outlier characteristic of temperature correlation can accurately judge whether the abnormal expansion phenomenon of the target battery cell occurs. Meanwhile, the method is not limited to the battery cell in a specific scene, so that the method has strong portability and universality.

Description

Method, device, equipment, medium and product for identifying abnormal expansion phenomenon of battery cell

Technical Field

The application relates to the technical field of energy storage, in particular to a method, a device, equipment, a medium and a product for identifying abnormal expansion phenomenon of a battery cell.

Background

The energy storage field and the electric vehicle field are rapidly developed under the influence of energy crisis. In particular, various energy storage batteries have been widely developed and used. In order to ensure that the energy storage battery can work normally, whether the battery core in the energy storage battery has abnormal expansion phenomenon needs to be identified, and then the battery core is maintained or replaced after the abnormal expansion phenomenon occurs.

At present, when identifying whether an abnormal expansion phenomenon occurs in a battery cell, a pressure sensor or a pressure deformation detector is generally deployed on the battery cell or a battery module, and whether the abnormal expansion phenomenon occurs is judged by monitoring a pressure value or a deformation amount of a pressure detection point. Or training the supervised learning model by adopting a large number of training samples in a specific scene of the battery cell, and further identifying whether the battery cell in the specific scene has abnormal expansion phenomenon by adopting the trained supervised learning model.

Therefore, in the current method for identifying whether the abnormal expansion phenomenon occurs in the battery cell, a pressure sensor or a pressure deformation detector needs to be additionally arranged, so that the cost is increased. Or the identification method can only be suitable for the battery cells in a specific scene, and the battery cells in other scenes can not be transplanted quickly, so that the universality is low.

Disclosure of Invention

The embodiment of the application provides a method, a device, equipment, a medium and a product for identifying the abnormal expansion phenomenon of a battery cell, which solve the problem of cost increase caused by the need of additionally arranging a pressure sensor or a pressure deformation detector in the method for identifying whether the abnormal expansion phenomenon of the battery cell occurs in the prior art; or the identification method can only be suitable for the battery cells in a specific scene, and the battery cells in other scenes can not be transplanted rapidly, so that the technical problem of low universality is caused.

In a first aspect, an embodiment of the present application provides a method for identifying an abnormal swelling phenomenon of a battery cell, including:

acquiring the temperatures of corresponding target battery cells acquired by temperature sensors corresponding to a plurality of target battery cells in the operation process of the target battery energy storage system at all sampling points;

judging whether at least one target cell has temperature-related outlier characteristics in the operation process according to the corresponding target cell temperature of each target cell at each sampling point;

and identifying whether the battery core with abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic.

Optionally, in the foregoing method, the obtaining, in the operation process of the target battery energy storage system, the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at each sampling point includes:

Judging whether current or power of the corresponding target battery cells collected by the current sensors or power sensors corresponding to the plurality of target battery cells in the operation process of the target battery energy storage system are zero or not;

in response to the fact that the current or the power of the collected corresponding target battery cells is not zero, determining that the process of the collected current or the power of the target battery cells is a charging and discharging process of the target battery energy storage system, and obtaining the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at all sampling points in the charging and discharging process;

and in response to zero current or power of the collected corresponding target battery cells, determining the process of zero current or power of the collected target battery cells as a standing process of the target battery energy storage system, and obtaining the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at each sampling point in the standing process of the target battery energy storage system.

Optionally, the method as described above, the temperature-dependent outlier comprises a highest temperature outlier;

judging whether at least one target cell has temperature-related outlier features in the operation process according to the corresponding target cell temperature of each target cell at each sampling point, comprising:

Determining the highest temperature according to the corresponding target cell temperature of each target cell at each sampling point;

and judging whether the target battery cell corresponding to the highest temperature has the highest temperature outlier characteristic.

Optionally, in the method, the determining whether the target cell corresponding to the highest temperature has the highest temperature outlier feature includes:

judging whether a target cell corresponding to the highest temperature meets a determination condition of a preset highest temperature outlier characteristic or not;

if the determination condition of the preset maximum temperature outlier characteristic is met, determining that the target battery cell corresponding to the maximum temperature has the maximum temperature outlier characteristic;

and if the determination condition of the preset maximum temperature outlier characteristic is not met, determining that the target cell corresponding to the maximum temperature does not have the maximum temperature outlier characteristic.

Optionally, the determining condition of the preset maximum temperature outlier feature includes any one of the following determining conditions, as described above:

the highest temperature is outside a first preset number standard deviation of normal distribution corresponding to all temperatures of the target battery energy storage system;

the first difference value between the highest temperature and the average temperature of the target battery energy storage system is larger than the second preset multiple of the second difference value between the average temperature and the lowest temperature of the target battery energy storage system; the second preset multiple is more than or equal to 1;

The third difference between the highest temperature and the median temperature is larger than the third preset multiple of the fourth difference between the median temperature and the lowest temperature, and the third preset multiple is larger than or equal to 1.

Optionally, the method as described above, wherein the identifying whether the cell has abnormal expansion according to the determination result of whether the cell has the temperature-related outlier includes:

and identifying that the target cell corresponding to the highest temperature is the cell with abnormal expansion phenomenon in response to the target cell corresponding to the highest temperature having the highest temperature outlier characteristic.

Optionally, the method as described above, the temperature-dependent outlier comprises a rate of temperature change outlier over an operating period;

determining a target cell corresponding to the fastest heating rate in the charging and discharging process in the operation period according to the temperature of the target cell corresponding to each sampling point;

judging whether the target battery cell corresponding to the fastest heating rate has the characteristic of outlier heating rate in the charge and discharge process;

Responding to the outlier characteristic of the temperature rise rate in the charge and discharge process, and determining whether a target cell corresponding to the fastest temperature rise rate in the standing process in the operation period is the cell with the slowest falling temperature rate;

and responding to the cell with the slowest falling temperature rate, and judging whether the cell has the characteristic of falling temperature rate outlier in the standing process.

and identifying that the same target battery cell is the battery cell with abnormal expansion phenomenon in response to the fact that the same target battery cell corresponding to the fastest heating rate and the slowest falling temperature rate has the heating rate outlier characteristic of the charging and discharging process and the falling temperature rate outlier characteristic of the standing process.

Optionally, the method as described above, the temperature-dependent outlier comprises a ring-to-temperature rate of change outlier;

determining a target cell with the outlier characteristic of the ring ratio heating rate in the charging and discharging process according to the temperature of the corresponding target cell of each target cell at each sampling point;

And judging whether the target battery cell with the ring ratio temperature rise rate outlier characteristic has the ring ratio falling temperature rate outlier characteristic in the standing process.

and in response to the target cell with the ring-specific temperature rising rate outlier characteristic and the ring-specific falling temperature rate outlier characteristic, identifying the target cell with the ring-specific temperature rising rate outlier characteristic and the ring-specific falling temperature rate outlier characteristic as the cell with the abnormal expansion phenomenon.

In a second aspect, an embodiment of the present application provides an apparatus for identifying abnormal swelling phenomenon of a battery cell, including:

the acquisition module is used for acquiring the temperatures of the corresponding target battery cells acquired by the temperature sensors corresponding to the plurality of target battery cells at each sampling point in the operation process of the target battery energy storage system;

the judging module is used for judging whether at least one target cell has temperature-related outlier characteristics in the operation process according to the corresponding target cell temperature of each target cell at each sampling point;

and the identification module is used for identifying whether the battery core with the abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic.

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored by the memory to implement the method of any one of the first aspects.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored therein computer-executable instructions for performing the method according to any of the first aspects when executed by a processor.

In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program which, when executed by a processor, implements the method according to the first aspect.

The embodiment of the application provides a method, a device, equipment, a medium and a product for identifying abnormal expansion phenomenon of a battery cell, wherein the method comprises the following steps: acquiring the temperatures of corresponding target battery cells acquired by temperature sensors corresponding to a plurality of target battery cells in the operation process of the target battery energy storage system at all sampling points; judging whether at least one target cell has temperature-related outlier characteristics in the operation process according to the corresponding target cell temperature of each target cell at each sampling point; and identifying whether the battery core with abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic. When the temperature sensors corresponding to the multiple target battery cells in the operation process of the target battery energy storage system acquire the temperatures of the corresponding target battery cells acquired by the sampling points, the temperature sensors which are deployed in the target battery energy storage system and set up the corresponding relation with the battery cells are utilized to realize the operation, so that the temperature sensors do not need to be deployed additionally, and the material cost or the acquisition cost of the system cannot be increased additionally. Meanwhile, whether the battery core has temperature-related outlier characteristics in the operation process can accurately reflect whether the battery core generates abnormal expansion phenomenon, so that whether the target battery core generates abnormal expansion phenomenon can be accurately judged by utilizing the temperature-related outlier characteristics. The method is not limited to the battery cell in a specific scene, so that the method has strong portability and universality.

It should be understood that the description of the invention above is not intended to limit key or critical features of embodiments of the invention, nor to limit the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.

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.

Fig. 1 is a schematic diagram of an application scenario of a method for identifying abnormal swelling phenomenon of a battery cell according to an embodiment of the present application;

FIG. 2 is a flowchart of a method for identifying abnormal swelling of a battery cell according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of a method for identifying abnormal swelling of a battery cell according to another embodiment of the present disclosure;

Fig. 4 is a schematic structural diagram of an identification device for abnormal expansion of a battery cell according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present application are shown in the drawings, it is to be understood that the present application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and examples of the present application are for illustrative purposes only and are not intended to limit the scope of the present invention.

The terms first, second, third, fourth and the like in the description and in the claims of embodiments of the application and in the above-described figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the present application described herein may be capable of being practiced otherwise than as specifically illustrated and 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.

The terms referred to in this application are explained as follows:

BMS: english is: battery Management System, chinese is: the battery management system mainly realizes intelligent management and maintenance of each battery unit and has the functions of preventing overcharge and overdischarge of the battery, prolonging the service life of the battery, monitoring the state of the battery and the like.

EMS: english is: energy Management System, chinese is: the electric energy management system is an energy scheduling and management center of the energy storage system, has the functions of real-time monitoring, diagnosis and early warning, panoramic analysis, advanced control and the like, can realize centralized monitoring and management of equipment such as an energy storage power station BMS, a two-way energy storage converter PCS and the like, and ensures safe, reliable and stable operation of the energy storage power station.

For a clear understanding of the technical solutions of the present application, the solutions of the prior art are described in detail.

At present, in order to better identify the abnormal expansion phenomenon of the battery, a pressure deformation detector or a pressure sensor is arranged on a battery cell or a battery module, and whether the abnormal expansion phenomenon occurs is judged by monitoring the deformation quantity or the pressure value of a pressure detection point. The second method realizes the training of the supervised learning model by utilizing a large number of training samples of the battery cell in a specific scene, and further identifies whether the battery cell in the specific scene has abnormal expansion or not through the trained supervised learning model.

Specifically, in the first method, a pressure deformation detector is deployed on a plurality of pressure detection points of a battery module in advance to collect deformation amounts of the pressure detection points of the battery module, the pressure values or the deformation amounts are fitted, and then the pressure values or the deformation amounts are divided by a preset threshold value to obtain a safety coefficient, and the safety coefficient is used for determining an abnormal expansion state of the battery module.

Or disposing pressure sensors on different pressure detection points of the battery core, presetting the pressure value of each pressure detection point of the normal battery core model under preset pressure, comparing with the actually detected pressure value, and judging whether the battery core has abnormal expansion or not by utilizing the comparison result.

In a second approach, the supervised learning model may be an isolated forest algorithm model. Firstly, an isolated forest algorithm model is constructed, and a training set obtained by simulating the faults of the energy storage battery in a specific scene of the battery cell is utilized to train the algorithm model, so that a critical abnormal score value is obtained. And collecting target battery parameters, solving an abnormal value, and judging whether the battery core has abnormal expansion phenomenon or not through comparison of the critical abnormal score value and the abnormal value.

However, the above method either requires additional deployment of a pressure deformation detector or a pressure sensor, which results in increased costs. Or the model trained by using the calibrated training set is only suitable for the battery cells in specific scenes, and the identification method cannot be quickly transplanted in other scenes, so that the universality is low.

Therefore, in order to solve the technical problems in the prior art, it is necessary to consider that no additional sensor or other devices are deployed to determine whether the abnormal expansion phenomenon of the battery cell exists. Because the temperature sensor is deployed in the target battery energy storage system, the corresponding relation with the battery cells is set, and the battery cells need to be radiated in the running process of the system, generally, air flows in gaps among the battery cells by using wind so as to take away heat generated when the battery cells work, if abnormal expansion occurs in the battery cells, the gaps among the battery cells become smaller, the radiating capacity is poor, the temperature of the battery cells rises, and therefore, the temperature of the battery cells can be used for determining whether the battery cells have abnormal expansion phenomenon or not. In order to accurately determine whether the battery cell has abnormal expansion phenomenon or not and be suitable for any battery cell scene, whether the battery cell has temperature-related outlier features in the operation process or not can be judged based on the corresponding target battery cell temperature of each sampling point of the battery cell, and whether the battery cell has abnormal expansion phenomenon or not is identified based on the judgment result of whether the battery cell has the temperature-related outlier features or not.

Fig. 1 is a schematic diagram of an application scenario of the method for identifying abnormal swelling phenomenon of a battery cell provided in the embodiment of the present application, as shown in fig. 1, in the application scenario, a target battery cell may be a battery cell of a battery 12 in an electric automobile 11, where the target battery cell has a plurality of sensors. Specifically, the temperature sensor 14, the current sensor 15 and the power sensor 16 can be included. The temperature sensor 14, the current sensor 15, and the power sensor 16 may be disposed outside the target cell. The temperature sensor 14 is used for collecting the temperature of each sampling point target cell, the current sensor 15 is used for collecting the current of each sampling point target cell, and the power sensor 16 is used for collecting the power of each sampling point target cell. Each sensor is connected to the battery management system BMS (Battery Management System), and the BMS 13 performs battery management. BMS 13 is connected with high in the clouds server 17, and high in the clouds server 17 is used for realizing electric automobile data analysis. As shown in fig. 1, the device for identifying the abnormal cell expansion phenomenon can be deployed on the cloud server 17, and after the data are collected by each sensor, the data are uploaded to the cloud server 17 through the BMS to perform calculation for identifying the abnormal cell expansion phenomenon, so as to determine whether the abnormal cell expansion phenomenon occurs in the target cell. Specifically, according to the temperature of the corresponding target cell of each target cell at each sampling point, whether at least one target cell has an outlier characteristic related to temperature in the operation process is judged, if so, the target cell is identified to be a cell with abnormal expansion phenomenon, and the abnormal expansion prompt of the power cell can be sent to the user side 18 through the cloud server 17.

It should be noted that, in another application scenario of the method for identifying abnormal expansion phenomenon of the battery cell provided by the application, the method can also be applied to an energy storage power station. After the identification method of the abnormal expansion phenomenon of the battery cell provided by the application is executed, if the temperature of the target battery cell at the current moment is determined to have the temperature-related outlier characteristic, the abnormal expansion phenomenon of the target battery cell is determined.

It is understood that in the scenario application of the energy storage power station, the device for identifying the abnormal swelling phenomenon of the battery cell may be deployed on the battery management system BMS/battery energy management system EMS (Energy Management System) or the cloud server. The application does not limit the deployment hardware equipment of the identification device of the abnormal expansion phenomenon of the battery cell.

The following describes the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Embodiment one:

fig. 2 is a flowchart of a method for identifying abnormal cell expansion phenomenon according to an embodiment of the present application, as shown in fig. 2, an execution body of the method for identifying abnormal cell expansion phenomenon according to the embodiment is an apparatus for identifying abnormal cell expansion phenomenon, where the apparatus for identifying abnormal cell expansion phenomenon is located in an electronic device, and the electronic device may be deployed with a BMS or an EMS or a cloud server. The electronic device may take the form of a digital computer representing various forms. Such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The battery remaining energy determination method provided in the present embodiment includes the steps of:

Step 201, acquiring the temperatures of corresponding target cells acquired by temperature sensors corresponding to a plurality of target cells at each sampling point in the operation process of the target battery energy storage system.

In this embodiment, the target battery energy storage system may be an energy storage system in which the target battery cell is located. There may be various types of battery energy storage systems, such as: battery packs, battery boxes, battery clusters, energy storage containers, energy storage whole stations, etc., the type of battery energy storage system is not limited herein.

The target battery cell is a battery cell for identifying abnormal expansion phenomenon. The type of the target battery cell is not limited, and may be a lead-acid battery cell, a nickel-based battery cell, a lithium-based battery cell, or the like.

The operation process can comprise a charging and discharging process and a standing process.

The sampling point may be a position where the temperature sensor is loaded on the target cell.

In this embodiment, the temperature sensor is already deployed when the target battery energy storage system is designed. The number, the spatial distribution and the corresponding relation between the target battery cells are recorded in the design scheme of the target battery energy storage system, the system design scheme can be stored in a preset storage area, and then the preset storage area is accessed to obtain the target battery cells corresponding to the temperature sensors.

Alternatively, the preset storage area may be a storage area in a magnetic disk, a hard disk, or a memory of the electronic device, which is not limited in this embodiment.

Specifically, in this embodiment, first, a temperature sensor corresponding to a target battery cell is determined according to a design scheme of the target battery energy storage system, and then, the temperature of the target battery cell corresponding to each sampling point can be periodically collected through the temperature sensor. And the temperature of the target battery cell corresponding to each collected sampling point is sent to a device for identifying the abnormal expansion phenomenon of the battery cell, so that the device for identifying the abnormal expansion phenomenon of the battery cell can acquire the temperatures of the corresponding target battery cells from the temperature sensors corresponding to the plurality of target battery cells in the operation process of the target battery energy storage system.

Step 202, judging whether at least one target cell has an outlier characteristic related to temperature in the operation process according to the corresponding target cell temperature of each target cell at each sampling point.

The temperature-related outlier features may include any one of a maximum temperature outlier feature, a rate of temperature change outlier feature over an operating period, and a ring ratio temperature change rate outlier feature, among others.

In this embodiment, whether the target battery cell has the maximum temperature outlier feature in the operation process is determined, and the target battery cell with the maximum temperature in the operation process of the target battery energy storage system is first determined, so as to determine whether the temperature corresponding to the target battery cell with the maximum temperature has the maximum temperature outlier feature compared with the temperatures of other target battery cells. The calculation mode of the maximum temperature outlier characteristic of the temperature corresponding to the target battery cell with the maximum temperature compared with the temperatures of other target battery cells is not limited. For example, it may be indicated that the target cell corresponding to the highest temperature has the highest temperature outlier feature by calculating the difference between the highest temperature and the target cell average temperature and the difference between the target cell average temperature and the lowest target cell temperature, and determining that the difference between the highest temperature and the target cell average temperature is greater than K times the difference between the target cell average temperature and the lowest target cell temperature, and setting K > =1.

In this embodiment, whether the target battery cell has an outlier characteristic of a temperature change rate in an operation period in an operation process is determined, and the target battery cell with the fastest temperature rising rate in the operation process of the target battery energy storage system is first determined, so that whether the temperature rising rate corresponding to the target battery cell with the fastest temperature rising rate is compared with the temperature rising rates of other target battery cells, and whether the temperature rising rate outlier characteristic of a charge and discharge process occurs is determined. And determining whether the target battery cell with the temperature rising rate outlier characteristic in the charging and discharging process is the battery cell with the slowest falling temperature rate in the subsequent standing process of the system, and further judging whether the target battery cell has the falling temperature rate outlier characteristic in the standing process compared with the falling temperature rates of other target battery cells. If the temperature rising rate outlier characteristic and the falling temperature rate outlier characteristic of the target battery core occur, determining that the target battery core has the temperature change rate outlier characteristic in the operation period in the operation process.

The calculation mode of whether the temperature rising rate corresponding to the target battery cell with the fastest temperature rising rate is compared with the temperature rising rates of other target battery cells or not is not limited, wherein the temperature rising rate outlier characteristic of the charge and discharge process is calculated. For example, if the difference between the fastest heating rate and the average heating rate of the target battery cell is calculated to be greater than H times the difference between the average heating rate of the target battery cell and the slowest heating rate, and H > =1 is set, it indicates that the target battery cell corresponding to the fastest heating rate has the heating rate outlier characteristic in the charge and discharge process.

The calculation mode of whether the falling temperature rate corresponding to the target cell with the slowest falling temperature rate is compared with the falling temperature rates of other target cells or not is not limited, and the falling temperature rate outlier characteristic of the standing process is calculated. For example, if the difference between the slowest falling temperature rate and the average falling temperature rate of the target cells is calculated to be greater than the multiple L of the difference between the average falling temperature rate of the target cells and the fastest falling temperature rate, and L > =1 is set, it indicates that the target cells corresponding to the slowest falling temperature rate have the outlier characteristic of the falling temperature rate of the standing process.

In this embodiment, whether the target battery core has the ring specific temperature change rate outlier feature in the operation process is determined, first, whether the ring specific temperature rise rate outlier feature occurs in the target battery core temperature rise rate of the target battery energy storage system in the operation process is determined, and further, whether the ring specific temperature fall-back temperature rate outlier feature occurs in the subsequent standing process of the system is determined. If the target battery core has the ring specific temperature rising rate outlier characteristic and the ring specific falling temperature rate outlier characteristic, judging that the target battery core has the ring specific temperature change rate outlier characteristic in the operation process.

Step 203, identifying whether the battery core has abnormal expansion phenomenon according to the judgment result of whether the battery core has the temperature-related outlier characteristic.

The judging result of the temperature-related outlier comprises the judging result of any one of the highest temperature outlier, the temperature change rate outlier in the running period and the ring ratio temperature change rate outlier.

In this embodiment, if it is determined that any one of the above three features appears in the target cell, it is determined that the target cell has an outlier feature related to the temperature, and it is determined that the target cell is a cell in which an abnormal expansion phenomenon occurs.

The embodiment of the application provides a method for identifying abnormal expansion phenomenon of a battery cell, which comprises the following steps: acquiring the temperatures of corresponding target battery cells acquired by temperature sensors corresponding to a plurality of target battery cells in the operation process of the target battery energy storage system at all sampling points; judging whether at least one target cell has temperature-related outlier characteristics in the operation process according to the corresponding target cell temperature of each target cell at each sampling point; and identifying whether the battery core with abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic. When the temperature sensors corresponding to the multiple target battery cells in the operation process of the target battery energy storage system acquire the corresponding target battery cell temperatures acquired by the sampling points, the temperature sensors which are deployed in the target battery energy storage system and set up the corresponding relation with the battery cells are utilized to realize the operation, so that the temperature sensors do not need to be deployed additionally, and the material cost or the acquisition cost of the system cannot be increased additionally. Meanwhile, whether the battery core has temperature-related outlier features in the operation process can accurately reflect whether the battery core generates abnormal expansion phenomenon, so that whether the target battery core generates abnormal expansion phenomenon can be accurately judged by utilizing the temperature-related outlier features. The method is not limited to the battery cell in a specific scene, so that the method has strong portability and universality.

Embodiment two:

fig. 3 is a flowchart of a method for identifying abnormal cell expansion phenomenon according to another embodiment of the present application, and as shown in fig. 3, the method for identifying abnormal cell expansion phenomenon according to the present embodiment further includes a step of acquiring a correspondence between a temperature sensor and a target cell on the basis of the method for identifying abnormal cell expansion phenomenon according to the foregoing embodiment, and further refines steps 201 to 203, where the method for identifying abnormal cell expansion phenomenon further includes the following steps:

step 301, obtaining a corresponding relationship between each data acquisition device and a target battery cell in the design scheme of the target battery energy storage system.

The design scheme of the target battery energy storage system is a basis for constructing the target battery energy storage system, and the content of the design scheme can comprise the number, the spatial distribution and the number of each data acquisition device, the number of the target battery cells, and the corresponding relation between the number of each data acquisition device and the number of the target battery cells, which is set according to the spatial distribution.

The data acquisition equipment is a device for acquiring relevant data in the operation process of the target battery cell, and can comprise a temperature sensor, a current sensor, a timer, a power sensor and the like. In this embodiment, the types of the data acquisition devices are not limited, and different data acquisition devices are set for different target battery energy storage systems.

Specifically, in this embodiment, the design scheme of the target battery energy storage system is stored in a preset storage area, and the corresponding relationship between each data acquisition device and the target battery cell, for example, the corresponding relationship between the acquired number of the temperature sensor and the number of the target battery cell is acquired by accessing the preset storage area.

Step 302, acquiring the temperatures of corresponding target cells acquired by temperature sensors corresponding to a plurality of target cells at each sampling point in the operation process of the target battery energy storage system.

In this embodiment, the corresponding relationship between each sampling point and each target cell may be directly obtained from the design scheme of the target battery energy storage system. In the design scheme of the target battery energy storage system, the corresponding relation of the spatial position distribution design of each target battery cell and each sampling point is preset. For example, the sampling point is designed at a position nearest to the target cell. It is understood that one sampling point may correspond to one target cell.

As an alternative implementation, in this embodiment, step 302 includes the following steps:

in step 3021, it is determined whether the current or power of the corresponding target battery cell is zero acquired by the current sensor or the power sensor corresponding to the plurality of target battery cells at each sampling point in the operation process of the target battery energy storage system.

In this embodiment, the current sensor or power sensor is already installed in the target battery energy storage system, and no additional deployment is required.

Specifically, in this embodiment, the current or power value of the target battery cell corresponding to each sampling point is collected by the current sensor or the power sensor, and the current running process of the target battery energy storage system is determined according to whether the current or power value is zero.

In step 3022, in response to the current or power of the collected target battery cell being not zero, determining that the process of collecting the current or power of the target battery cell being not zero is a charging and discharging process of the target battery energy storage system, and obtaining temperatures of the target battery cells collected at each sampling point by the temperature sensors corresponding to the target battery cells in the charging and discharging process.

The charging and discharging process of the target battery energy storage system is the charging and discharging process of the target battery energy storage system. The charging process is a working process that the target battery system receives electric energy from an external circuit and converts the electric energy into chemical energy. The discharging process is a working process in which the target battery system converts chemical energy into electric energy. The charging and discharging processes of the target battery energy storage system can generate corresponding changes of current and power.

Specifically, in this embodiment, the current or power of the corresponding target battery cell is collected by the current sensor or the power sensor, and if the collected value is not zero, the charging and discharging process of the target battery energy storage system is determined, and then the temperature of the corresponding target battery cell in the process is collected by the temperature sensor.

In step 3023, in response to the current or power of the collected target battery cell being zero, determining that the process of collecting the current or power of the target battery cell being zero is a standing process of the target battery energy storage system, and obtaining temperatures of the target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at each sampling point in the standing process of the target battery energy storage system.

The standing process of the target battery energy storage system is a process after the target battery energy storage system stops charging and discharging, and current or power in the target battery energy storage system in the process is zero.

Specifically, in this embodiment, the current or power of the target battery cell is collected by the current sensor or the power sensor, and if the collected value is zero, the stationary process of the target battery energy storage system is determined, and then the temperature of the target battery cell in the process is collected by the temperature sensor.

According to the method for identifying the abnormal expansion phenomenon of the battery cell, when the temperature of the corresponding target battery cell, which is acquired by the temperature sensors corresponding to the plurality of target battery cells in the operation process of the target battery energy storage system, is acquired, whether the current or the power of the corresponding target battery cell, which is acquired by the current sensor or the power sensor corresponding to the plurality of target battery cells in the operation process of the target battery energy storage system, is zero or not is judged; in response to the fact that the current or the power of the collected corresponding target battery cells is not zero, determining that the process of the collected current or the power of the target battery cells is a charging and discharging process of the target battery energy storage system, and obtaining the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at all sampling points in the charging and discharging process; and in response to zero current or power of the collected corresponding target battery cells, determining the process of zero current or power of the collected target battery cells as a standing process of the target battery energy storage system, and obtaining the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at each sampling point in the standing process of the target battery energy storage system. Because the operation process of the target battery energy storage system comprises a charging and discharging process, a standing process and the like, the current and the power of the corresponding target battery core in each process are different, and the temperature change of the corresponding target battery core in each process is different, the operation process of the target battery energy storage system can be accurately determined to be the charging and discharging process or the standing process by collecting the value of the current or the power. And the temperature sensor corresponding to the target battery cell in the charging and discharging process and the standing process of the target battery energy storage system can be collected in an omnibearing manner, and the temperature of the corresponding target battery cell is collected at each sampling point.

Step 303, judging whether at least one target cell has an outlier characteristic related to temperature in the operation process according to the corresponding target cell temperature of each target cell at each sampling point.

Optionally, the temperature-dependent outlier feature comprises a highest temperature outlier feature. Accordingly, step 303 may specifically include:

step 303a, judging whether at least one target cell has the highest temperature outlier characteristic in the operation process according to the corresponding target cell temperature of each target cell at each sampling point.

As an alternative implementation, in this embodiment, step 303a includes the following steps:

in step 303a1, the highest temperature is determined according to the corresponding target cell temperature of each target cell at each sampling point.

Specifically, in this embodiment, the cell with the highest temperature among all the target cell temperatures at the current moment is determined by a preset comparison algorithm. The present embodiment is not limited to the method of determining the maximum temperature.

The preset comparison algorithm may be an bubbling ordering algorithm, a selection ordering algorithm, an insertion ordering algorithm, or the like, and in this embodiment, the type of the preset comparison algorithm is not limited.

Step 303a2, determining whether the target cell corresponding to the highest temperature has the highest temperature outlier feature.

As an alternative implementation manner, in this embodiment, step 303a2 includes the following steps:

step 303a2a, judging whether the target cell corresponding to the highest temperature meets the determination condition of the preset highest temperature outlier feature;

the characteristic of the outlier of the highest temperature is that the difference between the highest temperature and other temperatures reaches the outlier difference, and specifically the outlier of the highest temperature is higher. The maximum temperature outlier is determined by the following scheme.

In this embodiment, the determination condition of the maximum temperature outlier feature may be performed by determining the outlier condition of the target cell corresponding to the maximum temperature.

Specifically, in this embodiment, the determination condition for determining whether the target cell corresponding to the highest temperature satisfies the preset highest temperature outlier is not limited, and for example, it may be determined that the difference between the highest temperature and the middle of the target cell temperature is greater than the difference K times between the middle of the target cell temperature and the lowest temperature by calculating the difference between the highest temperature and the middle of the target cell temperature and the lowest temperature, and K > =1 is set to indicate that the target cell corresponding to the highest temperature has the highest temperature outlier.

In step 303a2b, if it is determined that the determination condition of the preset maximum temperature outlier is satisfied, it is determined that the target cell corresponding to the maximum temperature has the maximum temperature outlier.

Specifically, in this embodiment, if it is determined that the outlier condition of the target cell corresponding to the highest temperature satisfies the determination condition of the highest temperature outlier feature, it is determined that the target cell corresponding to the highest temperature has the highest temperature outlier feature.

In step 303a2c, if it is determined that the determination condition of the preset maximum temperature outlier is not satisfied, it is determined that the target cell corresponding to the maximum temperature does not have the maximum temperature outlier.

Specifically, in this embodiment, if it is determined that the outlier condition of the target cell corresponding to the highest temperature does not satisfy the determination condition of the highest temperature outlier feature, it is determined that the target cell corresponding to the highest temperature has the highest temperature outlier feature.

As an alternative implementation manner, in this embodiment, the determination conditions of the preset maximum temperature outlier feature include any one of the following determination conditions:

a kind of is: the maximum temperature is outside a first preset number standard deviation of normal distribution corresponding to all temperatures of the target battery energy storage system.

The first preset number standard deviation is jσ, which is a result of normal fitting on all target cell temperatures, and j=3 or 4 is set to represent a determination condition of the maximum temperature outlier feature.

In this embodiment, all the temperature expectations and standard deviations are calculated first, and then normal fitting is performed on all the target cell temperatures to obtain a normally distributed interval, so as to determine whether the highest temperature is outside the first preset number standard deviation.

The other is: the first difference between the highest temperature and the average temperature of the target battery energy storage system is larger than the second preset multiple of the second difference between the average temperature and the lowest temperature of the target battery energy storage system; the second preset multiple is more than or equal to 1.

The average temperature of the target battery energy storage system is the average temperature of all target battery cells in the target battery energy storage system. The minimum temperature of the target battery energy storage system is the minimum temperature of all target cells in the target battery energy storage system.

Specifically, in this embodiment, by calculating the difference between the highest cell temperature and the average target cell temperature and the difference between the average target cell temperature and the lowest temperature, and determining that the first difference between the highest temperature and the average target cell energy storage system temperature is greater than the second preset multiple of the second difference between the average temperature and the lowest target cell energy storage system temperature, it is determined that the determination condition of the highest temperature outlier feature is satisfied.

Wherein, the second preset multiple may be denoted as K, K > =1.

Still another is: the third difference between the highest temperature and the median temperature is larger than the third preset multiple of the fourth difference between the median temperature and the lowest temperature, and the third preset multiple is larger than or equal to 1.

The medium temperature is the temperature of the target cells at the middle position after all the target cells of the system are sequenced according to the temperature.

Specifically, in this embodiment, the determination condition of the maximum temperature outlier is represented by calculating the difference between the highest cell temperature and the temperature median and the difference between the temperature median and the lowest temperature, and determining that the difference between the highest temperature and the target cell temperature median is greater than the third preset multiple of the difference between the target cell temperature median and the lowest temperature.

Wherein, the third preset multiple may be denoted as I, and I > =1.

According to the method for identifying the abnormal expansion phenomenon of the battery cells, which is provided by the embodiment, the temperature-related outlier comprises a highest temperature outlier, and accordingly, when judging whether at least one target battery cell has the temperature-related outlier in the operation process according to the corresponding target battery cell temperature of each target battery cell at each sampling point, the highest temperature is determined according to the corresponding target battery cell temperature of each target battery cell at each sampling point; and judging whether the target battery cell corresponding to the highest temperature has the highest temperature outlier characteristic. Because the target battery energy storage system can change the temperature of the target battery core in the actual operation process, if the target battery core is abnormally expanded, the temperature of the target battery core can exceed the temperature in normal use, and therefore whether the abnormal expansion phenomenon occurs to the temperature of the target battery core can be effectively judged by determining the highest temperature and the outlier characteristic of the highest temperature.

According to the method for identifying the abnormal expansion phenomenon of the battery cell, when judging whether the target battery cell corresponding to the highest temperature has the highest temperature outlier characteristic, judging whether the target battery cell corresponding to the highest temperature meets the determining condition of the preset highest temperature outlier characteristic; if the determination condition of the preset maximum temperature outlier characteristic is met, determining that the target battery cell corresponding to the maximum temperature has the maximum temperature outlier characteristic; and if the determination condition of the preset maximum temperature outlier characteristic is not met, determining that the target cell corresponding to the maximum temperature does not have the maximum temperature outlier characteristic. Because the determination condition of the maximum temperature outlier can accurately reflect the maximum temperature outlier characteristic, whether the target battery cell corresponding to the maximum temperature has the maximum temperature outlier characteristic can be accurately judged by judging whether the target battery cell corresponding to the maximum temperature meets the determination condition of the preset maximum temperature outlier characteristic.

According to the method for identifying the abnormal expansion phenomenon of the battery cell, the determination conditions of the preset maximum temperature outlier feature comprise any one of the following determination conditions: the highest temperature is outside a first preset number standard deviation of normal distribution corresponding to all temperatures of the target battery energy storage system; the first difference between the highest temperature and the average temperature of the target battery energy storage system is larger than the second preset multiple of the second difference between the average temperature and the lowest temperature of the target battery energy storage system; the second preset multiple is more than or equal to 1; the third difference between the highest temperature and the median temperature is larger than the third preset multiple of the fourth difference between the median temperature and the lowest temperature, and the third preset multiple is larger than or equal to 1. The normal distribution is an accurate mode in quality control, so that a small probability event can be well reflected, and the highest temperature abnormality is also a small probability event, so that the highest temperature outlier characteristic can be effectively reflected. The method of utilizing the median and the mean can reflect the outlier condition of the highest temperature, judge through the relation between the outlier degree of the highest temperature and the outlier degree of the lowest temperature, accurately reflect the outlier characteristic of the highest temperature, and enable the determination condition of the preset outlier characteristic of the highest temperature to have more selectivity.

Optionally, the temperature-dependent outlier feature comprises a rate of temperature change outlier feature over the period of operation. Accordingly, step 303 may specifically include:

step 303b, judging whether at least one target cell has an outlier characteristic of temperature change rate in an operation period in the operation process according to the corresponding target cell temperature of each target cell at each sampling point.

Step 303b1, determining a target cell corresponding to the fastest temperature rising rate in the charging and discharging process in the operation period according to the corresponding target cell temperature of each target cell at each sampling point.

The operation period is the duration corresponding to the process from one charge and discharge to complete standing of the target battery energy storage system.

Specifically, in this embodiment, first, the temperature rising rates corresponding to all the target cells in the charging and discharging processes in the operation period are calculated, and the target cell with the fastest temperature rising rate is determined by a preset comparison algorithm. The present embodiment does not limit the sorting algorithm for determining the target cells with the fastest temperature rising rate.

Step 303b2, determining whether the target battery cell corresponding to the fastest temperature rising rate has an outlier characteristic of the temperature rising rate in the charge and discharge process.

Specifically, in this embodiment, it is determined whether the target cell corresponding to the fastest temperature rising rate meets a determination condition of a preset temperature rising rate outlier feature in a charging and discharging process; if the determination condition of the temperature rise rate outlier characteristic of the preset charge and discharge process is met, determining that the target battery cell corresponding to the fastest temperature rise rate has the temperature rise rate outlier characteristic of the charge and discharge process; if the determination condition of the temperature rise rate outlier characteristic of the preset charge and discharge process is not met, the target battery cell corresponding to the fastest temperature rise rate is determined to have no temperature rise rate outlier characteristic of the charge and discharge process.

The determining conditions of the outlier characteristic of the temperature rising rate in the preset charging and discharging process comprise any one of the following determining conditions:

a kind of is: the fastest heating rate is outside a first preset number standard deviation of normal distribution corresponding to the heating rate of the target battery energy storage system.

The temperature rising rate of the target battery energy storage system is the temperature rising rate of all target battery cells in the target battery energy storage system.

The first preset number standard deviation is T sigma, which is a result of normal fitting of all target battery cell temperature rising rates, and t=3 or 4 is set to represent a determination condition of an outlier characteristic of the temperature rising rate in the charging and discharging process.

In this embodiment, the expected and standard deviations of all the temperature rising rates are calculated first, and then the temperature rising rates of all the target cells are fitted normally to obtain a normally distributed interval, so as to determine whether the fastest temperature rising rate is out of the first preset number standard deviation.

The other is: the first difference between the fastest heating rate and the average heating rate of the target battery energy storage system is larger than the second preset multiple of the second difference between the average heating rate of the target battery energy storage system and the slowest heating rate of the target battery energy storage system; the second preset multiple is more than or equal to 1.

The average temperature rising rate of the target battery energy storage system is the average temperature rising rate of all target battery cells in the target battery energy storage system. The slowest temperature rise rate of the target battery energy storage system is the slowest temperature rise rate of all target cells in the target battery energy storage system.

Specifically, in this embodiment, by calculating the difference between the fastest heating rate and the average heating rate of the target battery cell, and the difference between the average heating rate of the target battery cell and the slowest heating rate, and determining that the first difference between the fastest heating rate and the average heating rate of the target battery energy storage system is greater than the second preset multiple of the second difference between the average heating rate and the slowest heating rate of the target battery energy storage system, determining that the determining condition of the discrete feature of the heating rate in the charging and discharging process is satisfied.

Wherein, the second preset multiple may be expressed as H, H > =1.

Still another is: the third difference between the fastest heating rate and the median heating rate is larger than the third preset multiple of the fourth difference between the median heating rate and the slowest heating rate, and the third preset multiple is larger than or equal to 1.

The medium temperature rise rate is the temperature rise rate of the target cells at the middle position after all the target cells of the system are sequenced according to the temperature.

Specifically, in this embodiment, the determining condition of the outlier feature of the temperature rising rate in the charging and discharging process is represented by calculating the difference between the fastest temperature rising rate and the median of the temperature rising rate of the target battery cell and the difference between the median of the temperature rising rate and the slowest temperature rising rate, and determining that the difference between the fastest temperature rising rate and the median of the temperature rising rate of the target battery cell is greater than the third preset multiple of the difference between the median of the temperature rising rate of the target battery cell and the slowest temperature rising rate.

Wherein, the third preset multiple may be denoted as P, and P > =1.

Step 303b3, in response to the outlier feature of the temperature rise rate during charge and discharge, determining whether the target cell corresponding to the fastest temperature rise rate during rest in the run period is the cell with the slowest fallback temperature rate.

The cell with the slowest falling temperature rate is the cell with the slowest temperature falling speed in the current time period.

Specifically, in this embodiment, the target cell with the slowest falling temperature rate is calculated, first, the target battery energy storage system is determined to be a standing process according to the value in the current or power sensor, and the start time and the end time of the process are determined, so that the falling temperature rates of all the cells in the process are calculated, and the slowest falling temperature rate is calculated through a preset sorting algorithm.

In this embodiment, the method for calculating the falling temperature rate of all the cells is not limited, for example: the average change rate of the temperature in any T length interval of the start time and the end time can be calculated by designating a fixed time length T, such as 1 minute, in the standing time period. The present embodiment is not limited to the method of determining the slowest fallback temperature rate.

Step 303b4, in response to the cell being the slowest falling temperature rate, determining whether the cell has a standing process falling temperature rate outlier feature.

In this embodiment, the implementation manner of the step 303b4 is similar to that of the step 303b2, and will not be described in detail herein.

Wherein, the determining conditions of the falling temperature rate outlier characteristic of the preset standing process comprise any one of the following determining conditions:

a kind of is: the slowest fall-back temperature rate is outside a first preset number standard deviation of a normal distribution corresponding to the target battery energy storage system fall-back temperature rate.

The falling temperature rate of the target battery energy storage system is the falling temperature rate of all target cells in the target battery energy storage system.

The first preset standard deviation of the number is Rsigma, namely a result of normal fitting of the falling temperature rates of all the target battery cells, R=3 or 4 is set, and the determining condition of the falling temperature rate outlier characteristic in the standing process is represented.

In this embodiment, the expected and standard deviations of all the falling temperature rates are calculated first, and then the falling temperature rates of all the target cells are fitted normally to obtain a normally distributed interval, so as to determine whether the slowest falling temperature rate is out of the first preset number standard deviation.

The other is: the first difference between the slowest falling temperature rate and the average falling temperature rate of the target battery energy storage system is greater than a second preset multiple of the second difference between the average falling temperature rate of the target battery energy storage system and the fastest falling temperature rate of the target battery energy storage system; the second preset multiple is more than or equal to 1.

The average falling temperature rate of the target battery energy storage system is the average falling temperature rate of all target cells in the target battery energy storage system. The fastest falling temperature rate of the target battery energy storage system is the fastest temperature rising rate of all target cells in the target battery energy storage system.

Specifically, in this embodiment, by calculating the difference between the slowest falling temperature rate and the average falling temperature rate of the target cell, the difference between the average falling temperature rate of the target cell and the difference between the fastest falling temperature rate and determining that the first difference between the slowest falling temperature rate and the average falling temperature rate of the target battery energy storage system is greater than the second preset multiple of the second difference between the average falling temperature rate and the fastest falling temperature rate of the target battery energy storage system, determining that the determining condition of the falling temperature rate outlier feature in the standing process is satisfied.

Wherein, the second preset multiple may be expressed as L, L > =1.

Still another is: the third difference between the slowest falling temperature rate and the median falling temperature rate is greater than a third preset multiple of the fourth difference between the median falling temperature rate and the fastest falling temperature rate, and the third preset multiple is greater than or equal to 1.

The medium-sized fallback temperature rate is the fallback temperature rate of the target cells at the middle position after all the target cells of the system are ordered according to temperature.

Specifically, in this embodiment, the determining condition of the outlier feature of the falling temperature rate in the standing process is represented by calculating the difference between the slowest falling temperature rate and the median of the falling temperature rate of the target cell and the difference between the median of the falling temperature rate and the fastest falling temperature rate, and determining that the difference between the slowest falling temperature rate and the median of the falling temperature rate is greater than the third preset multiple of the difference between the median of the falling temperature rate and the fastest falling temperature rate.

Wherein, the third preset multiple may be denoted as Q, and Q > =1.

According to the identification method for the abnormal expansion phenomenon of the battery cells, which is provided by the embodiment, the temperature-related outlier comprises the highest temperature outlier, and accordingly, when judging whether at least one target battery cell has the temperature change rate outlier in the operation period or not in the operation process according to the corresponding target battery cell temperature of each target battery cell in each sampling point, the target battery cell corresponding to the fastest heating rate in the charge and discharge process in the operation period is determined according to the corresponding target battery cell temperature of each target battery cell in each sampling point; judging whether a target battery cell corresponding to the fastest heating rate has the outlier characteristic of the heating rate in the charging and discharging process; responding to the outlier characteristic of the temperature rise rate in the charge and discharge process, and determining whether a target cell corresponding to the fastest temperature rise rate in the standing process in the operation period is the cell with the slowest falling temperature rate; and responding to the cell with the slowest falling temperature rate, and judging whether the cell has the characteristic of falling temperature rate outlier in the standing process. Because the abnormal expansion rate of the target battery cell can be directly reflected to the temperature change rate of the target battery cell, whether the abnormal expansion phenomenon of the target battery cell occurs can be effectively reflected through the temperature change rate of the battery cell and the outlier characteristic of the temperature change rate of the battery cell. And if the target battery core has abnormal expansion phenomenon, the temperature rising rate outlier characteristic can be reflected in the charging and discharging process, and the falling temperature rate outlier characteristic can also be reflected in the standing process, so that if the same target battery core has the fastest temperature rising rate and the temperature rising rate outlier characteristic in the charging and discharging process, and has the slowest falling temperature rate and the falling temperature rate outlier characteristic in the standing process, the abnormal expansion phenomenon of the target battery core can be more accurately judged.

Optionally, the temperature-dependent outlier feature comprises a ring-to-temperature rate of change outlier feature. Accordingly, step 303 may specifically include:

and step 303c, judging whether at least one target cell has the outlier characteristic of the ring ratio temperature change rate in the operation process according to the corresponding target cell temperature of each target cell at each sampling point.

As an alternative implementation, in this embodiment, step 30c includes the following steps:

step 303c1, determining the target battery cell with the outlier characteristic of the ring ratio temperature rising rate in the charging and discharging process according to the corresponding target battery cell temperature of each target battery cell at each sampling point.

The characteristic of outlier ring ratio temperature rise rate is that the ring ratio temperature rise rate of a certain target battery cell is outlier compared with the ring ratio temperature rise rates of other target battery cells.

When judging whether the temperature rising rate of the target battery cell in the charging and discharging process of the target battery energy storage system has the outlier characteristic of the ring ratio temperature rising rate, determining the state of the target battery energy storage system according to the current or the power of the target battery cell, wherein the state can be a state of charging and discharging for a plurality of times a day and standing, and can also be a state of charging and discharging for one time at intervals of a plurality of days and standing. If the battery is in a state of being charged and discharged for many times a day and still standing, judging whether the increasing rate of the heating rate of the target battery cell at the current moment in the process of charging and discharging is more than N% compared with the increasing rate of the heating rate of the target battery cell at the process of charging and discharging with the same power before M times of charging and discharging; if the temperature rising rate of the target battery core at the current moment is determined to be more than N% compared with the temperature rising rate of the target battery core at the same power charge and discharge time before M times of charge and discharge, determining that the target battery has the ring ratio temperature rising rate outlier characteristic, otherwise, the target battery does not have the ring ratio temperature rising rate outlier characteristic.

If the battery is in a state of being charged and discharged once and kept still for a plurality of days at intervals, judging whether the increasing rate of the target battery cell at the current moment exceeds N% compared with the increasing rate of the target battery cell at the same power charging and discharging before M days. If the increase rate of the temperature rise rate of the target battery core in the current moment exceeds N% compared with the increase rate of the temperature rise rate of the target battery core in the same power charge and discharge before M days, determining that the target battery has the ring ratio temperature rise rate outlier characteristic, otherwise, the target battery does not have the ring ratio temperature rise rate outlier characteristic.

Wherein M is any value greater than 0, and N is any value greater than 0.

Step 303c2, determining whether the target cell with the ring-specific temperature rising rate outlier feature has the ring-specific falling temperature rate outlier feature in the standing process.

The characteristic of outlier of the ring-specific falling temperature rate is that the ring-specific falling temperature rate of a certain target cell is outlier compared with the ring-specific falling temperature rates of other target cells in the current charging and discharging process.

In particular, judging whether the target battery core falling temperature rate of the ring specific temperature rising rate outlier characteristic appears in the subsequent standing process of the system, and similarly judging whether the falling rate of the falling temperature rate of the target battery core in the standing process exceeds N when the falling rate of the falling temperature rate of the same-power charging and discharging in the standing process is compared with the falling rate of the falling temperature rate of the target battery core in the M times before charging and discharging if the falling rate of the target battery core is in a state of being charged and discharged for a plurality of times in one day; if the falling rate of the falling temperature rate of the target battery core at the current moment exceeds N% compared with the falling rate of the falling temperature rate of the target battery core at the same power before M times of charge and discharge, determining that the target battery has the ring ratio falling temperature rate outlier characteristic.

If the charge and discharge are carried out once in a plurality of days at intervals and the state of rest is carried out, judging whether the falling rate of the falling temperature rate of the target battery cell at the current moment exceeds N% compared with the falling rate of the falling temperature rate of the target battery cell at the same power before M days and at rest, and if the falling rate of the falling temperature rate of the target battery cell at the current moment exceeds N% compared with the falling rate of the falling temperature rate of the charge and discharge at the same power before M days and at rest, determining that the target battery cell has the ring ratio falling temperature rate outlier characteristic.

In this embodiment, the calculation method of the target cell temperature rising rate and the falling temperature rate is not limited.

According to the identification method for the abnormal expansion phenomenon of the battery cells, when judging whether at least one target battery cell has the characteristic of the outlier of the ring specific temperature change rate in the operation process according to the corresponding target battery cell temperature of each target battery cell at each sampling point, the target battery cell with the characteristic of the outlier of the ring specific temperature rise rate in the charge and discharge process is determined according to the corresponding target battery cell temperature of each target battery cell at each sampling point; and judging whether the target battery cell with the ring ratio temperature rise rate outlier characteristic has the ring ratio falling temperature rate outlier characteristic in the standing process. Because the charging and discharging time interval of the target battery core is not fixed, the charging and discharging can be performed for a plurality of times a day or can be performed once every few days, and the time interval of abnormal expansion of the target battery core is longer, the ring specific temperature rising rate and the ring specific falling temperature rate of the target battery core are considered, and whether the ring specific temperature rising rate outlier characteristic and the ring specific falling temperature rate outlier characteristic are provided or not, so that the effectiveness of identifying the abnormal expansion phenomenon of the battery core can be effectively improved. Meanwhile, the state of the target battery is considered from the charging and discharging process to the standing process, so that the abnormal expansion identification accuracy of the battery cell is effectively improved.

And step 304, identifying whether the battery core with abnormal expansion phenomenon exists according to the judgment result of whether the battery core has the temperature-related outlier characteristic.

It should be noted that step 304a is performed after step 303a is performed, step 304b is performed after step 303b is performed, and step 304c is performed after step 303c is performed.

Optionally, the determination of the temperature-related outlier comprises a determination of a highest temperature outlier. Accordingly, step 304 may specifically include:

and step 304a, identifying that the target cell corresponding to the highest temperature is a cell with abnormal expansion phenomenon in response to the target cell corresponding to the highest temperature having the highest temperature outlier characteristic.

Specifically, in this embodiment, when the target cell corresponding to the highest temperature is calculated to satisfy the condition of the outlier characteristic of the highest temperature, the target cell corresponding to the highest temperature is considered to be the cell in which the abnormal expansion phenomenon occurs.

Optionally, the determination of the temperature-dependent outlier comprises a determination of a rate of temperature change outlier over the operating period. Accordingly, step 304 may specifically include:

step 304b, in response to the same target cell having the fastest temperature rising rate and the slowest falling temperature rate and having both the charge-discharge process temperature rising rate outlier characteristic and the standing process falling temperature rate outlier characteristic, identifying that the same target cell is a cell having an abnormal expansion phenomenon.

Specifically, in this embodiment, if a certain cell has the fastest heating rate in the charging and discharging process, has the characteristic of outlier of the heating rate in the charging and discharging process, has the slowest falling temperature rate in the subsequent standing process of the target battery energy storage system, and has the characteristic of outlier of the falling temperature rate in the standing process, the target cell is considered to have abnormal expansion phenomenon.

It can be understood that in this embodiment, only if four conditions are satisfied by the target cell, it may be determined that the target cell is abnormally expanded, otherwise erroneous judgment is easily caused.

Optionally, the determination of the temperature-dependent outlier comprises a determination of the ring-specific temperature change rate outlier. Accordingly, step 304 may specifically include:

in step 304c, in response to the target cell having the ring-specific temperature rise rate outlier feature and simultaneously having the ring-specific fall-back temperature rate outlier feature, identifying that the target cell having both the ring-specific temperature rise rate outlier feature and the ring-specific fall-back temperature rate outlier feature is a cell in which an abnormal expansion phenomenon occurs.

Specifically, in this embodiment, if a certain cell has the characteristic of the outlier of the ring-specific temperature rising rate in the charging and discharging process and has the characteristic of the outlier of the ring-specific falling temperature rate in the subsequent standing process of the target battery energy storage system, the abnormal expansion phenomenon of the target cell is considered to occur.

It can be understood that in this embodiment, only if two conditions are satisfied by the target cell, it may be determined that the target cell is abnormally expanded, otherwise erroneous judgment is easily caused.

Embodiment III:

fig. 4 is a schematic structural diagram of an apparatus for identifying abnormal expansion of a battery cell according to an embodiment of the present application, as shown in fig. 4, where the apparatus for identifying abnormal expansion of a battery cell provided in this embodiment is located in an electronic device, and the electronic device may be a BMS, an EMS, or a cloud server. The identifying device 40 for abnormal cell expansion provided in this embodiment includes: the acquisition module 41, the judgment module 42 and the identification module 43.

The acquiring module 41 is configured to acquire temperatures of corresponding target cells acquired by temperature sensors corresponding to a plurality of target cells at each sampling point in an operation process of the target battery energy storage system. The tracking module 42 is configured to determine whether at least one target cell has an outlier feature related to a temperature during operation according to a corresponding target cell temperature of each target cell at each sampling point. The identifying module 43 is configured to identify whether the battery cell has abnormal expansion according to the determination result of whether the battery cell has the temperature-related outlier feature.

The device for identifying abnormal expansion of the battery cell provided in this embodiment may execute the technical scheme of the method embodiment shown in fig. 2, and its implementation principle and technical effect are similar, and will not be described herein again.

Optionally, the obtaining module 41 is specifically configured to:

judging whether current sensors or power sensors corresponding to a plurality of target cells acquire current or power of the corresponding target cells at each sampling point in the operation process of the target battery energy storage system; in response to the current or power of the corresponding target battery cell being acquired, determining that the process of acquiring the current or power of the target battery cell is a charging and discharging process of the target battery energy storage system, and acquiring the temperatures of the corresponding target battery cells acquired by the temperature sensors corresponding to the plurality of target battery cells at all sampling points in the charging and discharging process; and responding to the current or power of the non-collected target battery cells, determining the process of determining the current or power of the non-collected target battery cells as a standing process of the target battery energy storage system, and obtaining the temperatures of the corresponding target battery cells collected by the temperature sensors corresponding to the plurality of target battery cells at each sampling point in the standing process of the target battery energy storage system.

Optionally, the temperature-dependent outlier feature comprises a highest temperature outlier feature. Accordingly, the judging module 42 is specifically configured to:

Determining the highest temperature according to the corresponding target cell temperature of each target cell at each sampling point; and judging whether the target battery cell corresponding to the highest temperature has the highest temperature outlier characteristic.

Optionally, the temperature-dependent outlier feature comprises a rate of temperature change outlier feature over the period of operation. Accordingly, the judging module 42 is specifically configured to:

determining a target cell corresponding to the fastest heating rate in the charging and discharging process in the operation period according to the temperature of the target cell corresponding to each sampling point; judging whether a target battery cell corresponding to the fastest heating rate has the outlier characteristic of the heating rate in the charging and discharging process; responding to the outlier characteristic of the temperature rise rate in the charge and discharge process, and determining whether a target cell corresponding to the fastest temperature rise rate in the standing process in the operation period is the cell with the slowest falling temperature rate; and responding to the cell with the slowest falling temperature rate, and judging whether the cell has the characteristic of falling temperature rate outlier in the standing process.

Optionally, the temperature-dependent outlier feature comprises a ring-to-temperature rate of change outlier feature. Accordingly, the judging module 42 is specifically configured to:

determining a target cell with the outlier characteristic of the ring ratio heating rate in the charging and discharging process according to the temperature of the corresponding target cell of each target cell at each sampling point; and judging whether the target battery cell with the ring ratio temperature rise rate outlier characteristic has the ring ratio falling temperature rate outlier characteristic in the standing process.

Optionally, the temperature-dependent outlier feature comprises a highest temperature outlier feature. Accordingly, the identification module 43 is specifically configured to:

Optionally, the temperature-related outlier comprises a temperature rate of change outlier over the operating period, and accordingly the identification module 43 is specifically configured to:

Optionally, the temperature-dependent outlier feature comprises a ring-to-temperature rate of change outlier feature. Accordingly, the identification module 43 is specifically configured to:

The device for identifying abnormal expansion of the battery cell provided in this embodiment may also execute the technical scheme of the method embodiment shown in fig. 3, and its implementation principle and technical effect are similar, and will not be described herein again.

Example IV

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 5, the electronic device 50 may be a BMS, an EMS, or a cloud server. Comprising the following steps: a processor 52 and a memory 51 communicatively coupled to the processor.

The memory 51 stores computer-executable instructions. The processor 52 executes computer-executable instructions stored in the memory to implement the method for identifying abnormal cell expansion provided in any of the embodiments described above.

The related descriptions and effects corresponding to the steps in the drawings can be understood correspondingly, and are not repeated here.

In the corresponding embodiment of fig. 5, the program may comprise program code comprising computer-executable instructions. The memory may comprise high-speed RAM memory or may further comprise non-volatile memory, such as at least one disk memory.

Wherein the memory, transceiver and processor are connected by a bus. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component Interconnect, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.

The embodiment of the invention also provides a computer readable storage medium, wherein computer executable instructions are stored in the computer readable storage medium, and the computer executable instructions are used for realizing the identification method of the abnormal cell expansion phenomenon provided by any embodiment of the invention when being executed by a processor.

The embodiment of the invention also provides a computer program product, which comprises a computer program, and the computer program realizes the identification method of the abnormal cell expansion phenomenon provided by any one of the embodiments when being executed by a processor.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.

The modules illustrated as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in hardware plus software functional modules.

Program code for carrying out methods of the present invention may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable 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. 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 portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Moreover, although operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.

Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.

Claims

1. The method for identifying the abnormal swelling phenomenon of the battery cell is characterized by comprising the following steps of:

2. The method of claim 1, wherein the obtaining the temperatures of the corresponding target cells collected by the temperature sensors corresponding to the plurality of target cells at each sampling point during the operation of the target battery energy storage system comprises:

3. The method of claim 2, wherein the temperature-dependent outlier comprises a highest temperature outlier;

4. The method of claim 3, wherein determining whether the target cell corresponding to the highest temperature has a highest temperature outlier feature comprises:

5. The method of claim 4, wherein the determination of the preset maximum temperature outlier comprises any one of:

6. The method of claim 3, wherein the identifying whether the cell has abnormal swelling based on the determination of whether the cell has temperature-related outliers comprises:

7. The method of claim 2, wherein the temperature-dependent outlier comprises a rate of temperature change outlier over an operational period;

8. The method of claim 7, wherein the identifying whether the cell has abnormal swelling based on the determination of whether the cell has temperature-related outliers comprises:

9. The method of claim 2, wherein the temperature-dependent outlier comprises a ring-to-temperature rate of change outlier;

10. The method of claim 9, wherein the identifying whether the cell has abnormal swelling based on the determination of whether the cell has temperature-related outliers comprises:

11. An apparatus for identifying abnormal swelling of a battery cell, comprising:

12. An electronic device, comprising: a processor, and a memory communicatively coupled to the processor;

The memory stores computer-executable instructions;

the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-10.

13. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-10.

14. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-10.