CN117572276A - Self-adaptive battery cell health monitoring method, electronic equipment and storage medium - Google Patents
Self-adaptive battery cell health monitoring method, electronic equipment and storage medium Download PDFInfo
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Abstract
A self-adaptive battery cell health monitoring method, electronic equipment and storage medium relate to the field of data monitoring, and the method comprises the following steps: monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter; determining a first environmental temperature of an environment where the battery cell is located; when the first environmental temperature is higher than a first preset monitoring temperature corresponding to the first monitoring frequency, monitoring the operation of the battery cell according to the second monitoring frequency to obtain a second operating parameter; and when the second working parameter is not in the preset normal working threshold range, working early warning information is generated. By implementing the method, the working parameters of the battery cells are monitored by using the corresponding monitoring frequencies, meanwhile, the temperature parameters of the environment are determined, when the corresponding environment temperature is larger than a preset threshold value, the detection standard is changed, the data acquisition frequency is increased, and the self-adaptive and more accurate monitoring of the state of the battery cells under different temperature conditions is realized.
Description
Technical Field
The present disclosure relates to the field of data monitoring, and in particular, to a self-adaptive battery cell health monitoring method, an electronic device, and a storage medium.
Background
The electric core is a basic unit forming a new energy battery, can realize the storage and supply of electric energy, and is widely applied to various devices, including portable electronic devices such as mobile phones, notebook computers and the like, electric tools, electric vehicles, and even electric power storage and power grid systems. The parameters of energy density, voltage, charging speed, service life and the like of the battery core directly determine the service performance of the battery, so that the real-time monitoring of the health condition of the battery core related to the parameters is important in ensuring the safe, effective and durable use of the battery of the equipment.
In the related art, health monitoring of a battery cell generally refers to monitoring some key parameters of the battery cell, such as voltage, current, temperature, etc. The change of these parameters can reflect the operating state and health of the cells. For example, overheating of the cell may mean that an abnormal chemical reaction occurs inside the cell, which may cause a safety problem, and early warning of the safety problem may be achieved by monitoring the temperature of the cell.
However, the battery cell uses the same set of monitoring system in different use environments, such as different temperature environments, so that when the health state of the battery cell is judged by parameters such as voltage, current, temperature and the like, the judgment result is not accurate enough.
Disclosure of Invention
The application provides a self-adaptive battery cell health monitoring method, electronic equipment and a storage medium, which are used for monitoring working parameters of a battery cell by using corresponding monitoring frequencies, determining temperature parameters of the environment and changing detection standards when the corresponding environment temperature is greater than a preset threshold value, increasing data acquisition frequencies, and realizing self-adaptive and more accurate monitoring of the state of the battery cell under different temperature conditions.
In a first aspect, the present application provides an adaptive cell health monitoring method, applied to an electronic device, the method including: monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter; the working parameters comprise working voltage, working current and working temperature; determining a first environmental temperature of an environment where the battery cell is located; when the first environmental temperature is higher than a first preset monitoring temperature corresponding to the first monitoring frequency, monitoring the operation of the battery cell according to the second monitoring frequency to obtain a second operating parameter; and when the second working parameter is not in the preset normal working threshold range, generating working early warning information for prompting the user that the battery cell works abnormally.
In the above embodiment, the electronic device monitors the working parameters of the battery cell by using different monitoring frequencies according to the change of the ambient temperature, so as to realize the self-adaptive monitoring of the state of the battery cell. And when the ambient temperature is higher than a preset threshold value, increasing the acquisition frequency. The real-time state monitoring of the battery cell under different temperature environments can be realized, and compared with the fixed monitoring frequency, the health state of the battery cell can be judged more accurately, and the quick response can be made to the state change of the battery cell. Even under the condition of environmental temperature change, the accurate early warning of the battery cell faults can be carried out, and monitoring errors are avoided.
With reference to some embodiments of the first aspect, in some embodiments, after the step of determining a first ambient temperature of the environment in which the cell is located, the method further includes: determining whether the first ambient temperature is within a safe ambient threshold range for normal operation of the battery cell; if not, generating environment early warning information for prompting the user that the cell operating environment is abnormal.
In the above embodiment, after the electronic device monitors the ambient temperature, it further determines whether the ambient temperature is within a temperature range in which the battery cell normally operates, and if not, the technical scheme of the environmental early warning information is generated. The working environment of the battery cell can be monitored, when the environment temperature is abnormal, early warning is carried out in advance, and the battery cell is prevented from working continuously under the overheat or supercooled environment, so that potential safety hazards are avoided.
With reference to some embodiments of the first aspect, in some embodiments, when the second operating parameter is not within the preset normal operating threshold range, generating the operation early warning information specifically includes: when the second working parameter is not in the preset normal threshold range, determining a second environment temperature of the environment where the battery cell is located; determining whether the second operating parameter is within a preset normal operating threshold range corresponding to the second ambient temperature based on the second ambient temperature; if not, generating working early warning information for prompting the user that the battery cell works abnormally.
In the above embodiment, the electronic device may re-detect the ambient temperature, and determine whether the working parameter is abnormal according to the current ambient temperature, so as to avoid false alarm caused by environmental change. Whether the parameter abnormality is caused by environmental change or caused by battery cell fault can be accurately distinguished, and the judgment accuracy is improved.
With reference to some embodiments of the first aspect, in some embodiments, after the step of monitoring the operation of the battery cell at the second monitoring frequency to obtain the second operating parameter, the method further includes: inputting the second working parameters and the environmental data into a battery cell life model to obtain life prediction residual time of the battery cell; the environmental data are temperature data and humidity data of the environment where the battery cell is located.
In the above embodiment, the electronic device predicts the remaining service time of the battery cell by inputting the environmental temperature and humidity data and the working parameters into the life model. Compared with the method which only utilizes working parameters, the method has the advantages that the factors influencing the aging of the battery cells can be comprehensively considered by adding the environment variables, and the service life prediction result is more accurate. Meanwhile, the scheme can dynamically predict the residual service life of the battery cell according to the specific use environment of the battery cell, and does not simply rely on a fixed statistical model, so that individualized battery cell health assessment can be realized.
With reference to some embodiments of the first aspect, in some embodiments, after the step of inputting the second operating parameter into the battery life model to obtain the life prediction remaining time of the battery, the method further includes: judging whether the life prediction residual time is lower than a preset recovery threshold value or not; if yes, generating recovery information for prompting a user to timely recover the battery cells.
In the above embodiment, when the electronic device determines that the service time of the electronic device reaches the preset threshold according to the lifetime prediction of the specific battery cell, the electronic device prompts the user to recycle the battery cell in time. Compared with fixed statistical service cycle recovery, the technical scheme can exert the service life of the battery cell to the greatest extent, simultaneously avoid the safety problem caused by excessive failure of the battery cell, and perform individualized timing recovery more economically and environmentally friendly than unified recovery.
With reference to some embodiments of the first aspect, in some embodiments, after the step of generating the recovery information, the method further includes: combining the historical environment data and the historical working data of the battery cell into battery cell use data, and uploading the battery cell use data to a cloud database of a background server; the historical environmental data includes a historical environmental temperature, a historical environmental humidity; the historical working data comprises historical charge and discharge data and historical working current and voltage data; and determining the latest battery cell life model based on optimization of the battery cell life model by using the plurality of battery cell use data of the plurality of battery cells in the cloud database by the background server.
In the embodiment, the electronic equipment realizes centralized storage and model training of massive battery cell individual use data through a cloud computing technology, and can continuously optimize the battery cell health assessment and life prediction model so as to be more accurate and intelligent. Compared with local calculation, the cloud calculation can aggregate more data, has stronger calculation capability, and can establish a more accurate cell health evaluation model. The scheme realizes the intellectualization of cell health monitoring and management, and can promote the battery management to develop to the refinement and individuation directions.
With reference to some embodiments of the first aspect, in some embodiments, generating the recovery information specifically includes:
determining the daily free time of the user based on the daily mobile phone use information of the user; determining a cell replacement point nearest to a user based on daily position information of the user; and generating recovery information comprising a battery cell replacement plan based on daily free time and a battery cell replacement point, wherein the recovery information is used for prompting a user to timely recover the battery cell.
In the above embodiment, the electronic device may analyze the usage habit, idle time and frequent places of the mobile phone of the user, determine a cell replacement time according with the habit of the user, and send a recycling reminder to the user. The personalized recovery reminding not only considers the timeliness of cell replacement, but also reduces the inconvenience brought to users. Compare blind recovery and remind, can initiatively discern the time point of being convenient for the user to change the electric core, promote user experience, increase and remind the possibility of being adopted.
In a second aspect, embodiments of the present application provide an electronic device, including: the monitoring module is used for monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter; the working parameters comprise working voltage, working current and working temperature; the temperature module is used for determining a first environment temperature of the environment where the battery cell is located; the updating module is used for monitoring the operation of the battery cell according to the second monitoring frequency when the first environmental temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, so as to obtain a second operating parameter; and the early warning module is used for generating working early warning information when the second working parameter is not in the preset normal working threshold range, and is used for prompting the user that the cell work is abnormal.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors and memory; the memory is coupled to the one or more processors, the memory for storing computer program code comprising computer instructions that the one or more processors call for causing the electronic device to perform the method as described in the first aspect and any possible implementation of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer program product comprising instructions which, when run on an electronic device, cause the electronic device to perform a method as described in the first aspect and any possible implementation of the first aspect.
In a fifth aspect, embodiments of the present application provide a computer-readable storage medium comprising instructions that, when executed on an electronic device, cause the electronic device to perform a method as described in the first aspect and any possible implementation of the first aspect.
It will be appreciated that the electronic device provided in the second aspect, the third aspect, the computer program product provided in the fourth aspect and the computer storage medium provided in the fifth aspect are each configured to perform the method provided in the embodiments of the present application. Therefore, the advantages achieved by the method can be referred to as the advantages of the corresponding method, and will not be described herein.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. due to the adoption of the technical scheme of dynamically adjusting the monitoring frequency according to the ambient temperature, the self-adaptive monitoring of the state of the battery cell is realized, so that the parameter setting of the health monitoring of the battery cell can adapt to the change of the environment where the battery cell is located in real time, and the monitoring accuracy and sensitivity are remarkably improved.
2. The monitoring of the environmental temperature of the battery cell is increased, and the battery cell state is judged by combining the environmental temperature, so that the influence of the environmental temperature change on the monitoring result is avoided, and the accuracy of judging the health state of the battery cell is ensured.
3. Because the dynamic life prediction model is established by adopting the individualized service environment parameters of the battery cells, the accurate evaluation and recovery reminding of the residual life of the single battery cell can be realized, and the utilization efficiency of the battery cells and the safety of a battery system are remarkably improved instead of the conventional unified recovery mode based on the statistical model.
Drawings
FIG. 1 is a schematic flow chart of an adaptive cell health monitoring method according to an embodiment of the present application;
FIG. 2 is another flow chart of an adaptive cell health monitoring method in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a functional module of an electronic device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an entity device of the electronic apparatus according to the embodiment of the present application.
Detailed Description
The terminology used in the following embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms as well, unless the context clearly indicates to the contrary. It should also be understood that the term "and/or" as used in this application is intended to encompass any or all possible combinations of one or more of the listed items.
The terms "first," "second," and the like, are used below for descriptive purposes only and are not to be construed as implying or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature, and in the description of embodiments of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
It should be noted that, the electronic device as the main body of the method is a device with a built-in battery cell and capable of monitoring the battery cell data, including but not limited to a charger, a device, a household or outdoor energy storage device, and a solar energy storage device, where one or more battery cells form a battery energy supply part.
For easy understanding, the application scenario of the embodiments of the present application is described below.
With the popularization of smart phones, portable charging devices such as mobile power supplies are widely used. However, the environment temperature of the charger baby is complex and changeable in the use process, and the temperature difference between different places and seasons is large, so that difficulty is brought to the state monitoring of the battery cell of the charger baby. If the monitoring parameter configuration is fixed, the monitoring parameter configuration cannot be adjusted according to environmental changes, the judgment on the health state of the battery core is inaccurate, the high-temperature and low-temperature fault response of the battery charger is slow, early warning and protection cannot be timely performed, and potential safety hazards exist. Therefore, there is a need for a method for adaptively monitoring the state of a battery cell according to parameters that can be automatically adjusted according to environmental changes.
In the related art, the state monitoring of the battery cell can be realized by adopting preset fixed monitoring parameters and standards. However, the fixed parameter setting cannot adapt to the working change of the battery cell under different environmental temperatures, so that the monitoring result is inaccurate.
Aiming at the battery cell health monitoring requirement of portable charging equipment, a set of fixed parameter monitoring system is adopted by N company. The system measures the voltage, current and temperature of the cell once every 10 minutes and presets the thresholds for these parameters. However, the monitoring parameters of the system are fixed, and when the temperature of the user changes greatly from indoor to outdoor, the monitoring frequency and the parameter threshold value cannot be correspondingly adjusted. Once, a user enters a 40 ℃ high-temperature room from the indoor 20 ℃ for use, the system is still monitored according to the original parameters, so that the state of the battery cell is judged to be wrong, and an alarm event is pushed after the battery cell is overheated.
By adopting the method provided by the embodiment of the application, the self-adaptive monitoring of the state of the battery cell is realized by detecting the ambient temperature and automatically adjusting the monitoring parameters when the ambient temperature changes. The method not only can adapt the monitoring parameters to temperature change, but also avoids errors in judging the health state of the battery cell under the fixed parameter setting.
In order to solve the problem of the fixed monitoring scheme, the H company adopts an self-adaptive battery cell health monitoring system capable of automatically adjusting monitoring parameters according to the ambient temperature. The system monitors the electrical parameters of the battery core and the ambient temperature simultaneously, and establishes monitoring schemes under different temperatures in advance. When the ambient temperature is higher than 25 ℃, the system automatically increases the monitoring frequency and adjusts the threshold values of the voltage and the current.
In the high temperature of 40 ℃ in the previous scene, the system can quickly detect the abnormality of the parameters of the battery cell and push an alarm, so that the overheat damage of the battery cell is avoided. The self-adaptive monitoring of the state of the battery cell is realized, and the safety of the portable power supply equipment is improved.
Therefore, by adopting the self-adaptive battery cell health monitoring method in the embodiment of the application, the problem that the monitoring result is inaccurate and the battery cell working environment cannot be adapted to the change caused by the fixed parameter setting can be effectively solved while the battery cell state is monitored, and further the battery cell state is monitored more accurately and reliably.
For ease of understanding, the method provided in this embodiment is described in the following in conjunction with the above scenario. Fig. 1 is a schematic flow chart of an adaptive cell health monitoring method according to an embodiment of the present application.
S101, monitoring the operation of the battery cell according to a first monitoring frequency to obtain a first operating parameter.
The electronic equipment monitors the battery cell according to a preset first monitoring frequency to acquire working parameter data of the battery cell. The first monitoring frequency defines configuration information such as monitored object parameters, parameter acquisition frequency and the like. The object parameters may include an operating voltage, an operating current, an operating temperature, etc. of the battery cell, and voltage values, current values, and temperature values of these parameters reflect an operating state of the battery cell.
The first monitoring frequency is preset to a lower monitoring frequency, for example, voltage, current and temperature parameters are collected every 10 minutes, so as to save system resources. Through the monitoring of the step, the electronic equipment can periodically acquire the first working parameters such as voltage, current, temperature and the like of the battery cell during normal working.
S102, determining a first environment temperature of the environment where the battery cell is located.
The electronic equipment determines a temperature parameter of the environment where the battery cell is located as a first environment temperature. The detection of the ambient temperature can be acquired by an existing temperature sensor of the device or a special temperature detection module is added. For example, for a mobile power supply product, the indoor or outdoor temperature of the environment in which it is located may be obtained. The ambient temperature of the cell during operation is one of the important parameters affecting its health. The obtained first ambient temperature will be used later to determine whether an adjustment of the monitoring frequency is required.
And S103, when the first environmental temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, monitoring the operation of the battery cell according to the second monitoring frequency to obtain a second operating parameter.
And the electronic equipment judges whether the acquired first environmental temperature exceeds a preset temperature threshold value in the first monitoring frequency, namely a first preset monitoring temperature. And if the ambient temperature is greater than the threshold value, monitoring the operation of the battery cell according to the second monitoring frequency. The second monitoring frequency may be a higher monitoring frequency than the first monitoring frequency, for example, every 5 minutes, and the threshold range of the operating parameter is adjusted. After the second working parameter is obtained, the working state of the battery cell at a higher environmental temperature can be reflected more frequently.
And S104, when the second working parameter is not in the preset normal working threshold range, working early warning information is generated to prompt the user that the cell is abnormal in working.
In this step, the electronic device determines whether the voltage, current, temperature, etc. in the second operating parameter exceeds their respective normal operating threshold ranges preset in the second monitoring frequency.
If the parameters beyond the normal range exist, the battery cell is possibly in an abnormal working state, the electronic equipment can generate early warning information of abnormal working, and the user is informed in the modes of sound, indicator light effect or screen prompt and the like. Therefore, a user can take measures such as checking and replacing the battery as soon as possible, and equipment problems or safety accidents caused by battery cell faults are avoided. When the method is implemented on the charger, the charger can also establish wireless connection with equipment such as a user mobile phone and the like, and carry out information prompt through a specific application program.
The "first" and "second" are merely expressions for ordering in order, and do not limit "one" to a specified object. In practice, the former of the "first" table and the latter of the "second" table become gradually the former with the development of time or progress, that is, the "second data" is taken as the subsequent "first data", which is a normal implementation manner.
In the above embodiment, the electronic device adjusts the monitoring parameters according to the ambient temperature, so as to realize self-adaptive monitoring of the state of the battery cell, and can monitor and alarm the abnormal condition of the battery cell in real time, and compared with the fixed parameter monitoring, the judgment result is more accurate. In practical application, on the basis of monitoring the health of the battery cells, the environment pollution may be caused by random disposal of the battery cells, and through health state monitoring, when abnormality occurs or replacement is needed, the determination of the completely executable recovery step is also very important.
The following supplements the scenario of the present embodiment.
In order to further improve the intellectualization of the monitoring system, the H company adopts a machine learning algorithm to train out a battery cell health evaluation model based on historical use data of the battery cell. The model can be combined with the temperature change condition to predict the residual life of each battery cell.
The treasured charges can in time prompt the user to replace partial battery cells according to life prediction results by utilizing specific application programs instead of replacing the battery cells in a whole, so that accurate maintenance is realized, and the use cost is reduced. Meanwhile, the system adopts a cloud computing platform to analyze big data, so that a battery cell health evaluation model is continuously optimized, and an adaptive battery cell state monitoring service is provided for various mobile power supplies.
In combination with the above scenario, a further more specific flow of the method provided in this embodiment will be described below. Fig. 2 is a schematic flow chart of an adaptive cell health monitoring method according to an embodiment of the present application.
And S201, monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter.
Referring to step S101, the electronic device monitors the battery cell according to a preset first monitoring frequency, and obtains working parameter data of the battery cell.
S202, determining a first environment temperature of an environment where the battery cell is located.
Referring to step S102, the electronic device determines a temperature parameter of an environment where the battery cell is located as a first ambient temperature.
In some embodiments, after obtaining the first ambient temperature, the electronic device further determines whether the first ambient temperature is within a safe ambient threshold range for normal operation of the battery cell; and when the operating environment is not within the safety threshold range, generating environment early warning information for prompting the abnormal operating environment of the battery cell of the user.
Specifically, the electronic device may determine its normal operating temperature range, for example, 0-40 ℃ in advance according to the operating characteristics of the battery cell. After the first ambient temperature is obtained through detection, the electronic equipment compares the temperature value with a preset normal working temperature range. If the first ambient temperature is higher than the upper limit temperature of 40 ℃ or lower than the lower limit temperature of 0 ℃ and is not in the safe ambient temperature range of the battery cell, the electronic equipment can judge that the ambient temperature of the battery cell is abnormal, and the health state of the battery cell is possibly adversely affected. At the moment, the electronic equipment can actively generate early warning information of abnormal ambient temperature, and prompts a user in a display or sound mode and the like, so that the battery cell is prevented from continuously working at the abnormal ambient temperature to generate safety problems or damage.
And S203, when the first environmental temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, monitoring the operation of the battery cell according to the second monitoring frequency to obtain a second operating parameter.
Referring to step S103, the electronic device determines whether the obtained first ambient temperature exceeds a predetermined temperature threshold in the first monitoring frequency, that is, a first preset monitoring temperature. And if the ambient temperature is greater than the threshold value, monitoring the operation of the battery cell according to the second monitoring frequency.
And S204, when the second working parameter is not within the preset normal working threshold range, working early warning information is generated to prompt the user that the cell is abnormal in working.
Referring to step S104, the electronic device determines whether the voltage, current, temperature, etc. in the second operation parameter exceeds their respective normal operation threshold ranges preset in the second monitoring frequency. If the parameters exceeding the normal range exist, the battery cell is possibly in an abnormal working state, and the electronic equipment can generate early warning information of abnormal working.
In some embodiments, the generating the prompt information by the electronic device specifically includes: when the second working parameter is not in the preset normal threshold range, determining a second environment temperature of the environment where the battery cell is located; determining whether the second operating parameter is within a preset normal operating threshold range corresponding to the second ambient temperature based on the second ambient temperature; if not, generating working early warning information for prompting the user that the battery cell works abnormally.
Specifically, if the abnormality of the second working parameter is detected, the electronic device does not directly determine that the battery cell is faulty, but re-collects and confirms the second environmental temperature of the current environment of the battery cell. And then the electronic equipment reads the normal range of the working parameter at the ambient temperature and judges whether the working parameter is in the normal range at the ambient temperature again. The electronic device generates work early warning information to the user only when the second working parameter is not in the normal working range corresponding to the second environment temperature. The design can avoid abnormal judgment errors of the working parameters caused by environmental temperature change, improve the judgment accuracy and prevent false alarms.
S205, inputting the second working parameters and the environmental data into a battery cell life model to obtain life prediction residual time of the battery cell.
The electronic equipment inputs the acquired second working parameters, namely the working voltage, current, temperature and other data of the battery cell at the current ambient temperature, the ambient temperature, humidity and other ambient data, into a pre-established battery cell life prediction model. The model is a data-driven machine learning model, and is obtained through historical use data training of the battery cells.
Such as a deep learning model based on LSTM (Long Short-Term Memory network). After data is input, the model can predict the residual service life of the battery cell according to the data, and the service life prediction residual time of the battery cell is output. Compared with the method which only utilizes the working parameters of the battery cell, the method has the advantages that the service life prediction is more accurate and comprehensive by adding the environmental temperature and humidity variable. The obtained life prediction result can evaluate the health state of the battery cell and provide reference for subsequent maintenance.
S206, judging whether the life prediction residual time is lower than a preset recovery threshold value.
The electronic equipment reads the residual life of the battery cell predicted in the previous step and judges whether the predicted residual time value of the life is lower than a preset recovery threshold value. The reclamation threshold may be determined based on the rated cycle times or age of the cells, and may trigger a reclamation alert when the end of life is approached.
If it is determined that the predicted remaining time of the battery cell lifetime is lower than the recovery threshold, the battery cell is considered to be in a state of being about to be scrapped, and recovery is required, and the process proceeds to step S207 described later.
If the predicted remaining time of the service life of the battery cell is not lower than the recovery threshold value, the battery cell is considered to be in a normal life cycle, and the remaining time can be displayed without prompting and used for providing more information for a user.
S207, determining daily free time of the user based on the daily mobile phone use information of the user.
If the service life of the battery cell is determined to be up to the recovery time, the electronic equipment analyzes a time period with a certain free time in one day of the user by combining the mobile phone use habit of the user, such as the time of video brushing or game playing of the mobile phone, the time of afternoon break and the like. The information may originate from data of applications such as calendars, location services in the handset. These time periods are extracted as time periods that have room in the user's daily life.
In some embodiments, the electronic device may determine a period of time that the user has free time in a day according to the user's mobile phone usage habits.
Specifically, the electronic device may analyze the user's work time and the appointment time, etc. for the planned use time by reading data of a calendar application, a mail application, a telephone application, etc. in the user's mobile phone. Such as retrieving a user's schedule from a calendar, retrieving possible work hours from mail, etc.
In addition, the electronic device can analyze the work and rest time of the user from the social application of the user, for example, acquire the chat time of the user at night from the WeChat, and judge the normal sleeping time of the user. By integrating the application data, the electronic device can roughly judge the time period occupied by work, life and sleep of the user in one day.
The electronic device may then exclude these occupied time periods and determine the remaining time period as the user's daily free time. These free times may occur during commute hours during business hours, during rest hours during the afternoon, during the night after overtime, etc.
After the specific free time is determined, the electronic equipment can arrange the recovery time of the battery cell according to the specific free time, select a time point which has less influence on life of a user and has proper free time to remind the user to replace the battery cell.
S208, determining the cell replacement point closest to the user based on the daily position information of the user.
In this step, the electronic device collects and analyzes the daily position data of the user, and determines the cell replacement point that is closer to the user.
Specifically, the electronic device can collect long-term GPS track data of the user through the positioning module, and analyze daily activity areas of the user, such as tracks of commuting, frequently-occurring places such as shops and restaurants. Meanwhile, the electronic equipment can also acquire address information of each cell replacement point or recovery network point by inquiring a database of the cell replacement service, and the replacement points can be special battery recovery sites or sales network points for providing the cell replacement service.
Then, the electronic equipment can calculate and compare the daily activity area of the user with the address information of each cell replacement point, and judge which replacement points are closer to the activity area of the user and are more convenient to reach according to the linear distance or the road network distance. For example, a cell replacement point closest to a user's business turn track or a cell replacement point closer to a daily stay point such as a mall or a restaurant where the user frequently occurs is determined. Thus, the cell replacement point which is close to the user and is easier to go to in daily life can be determined.
S209, generating recovery information comprising a battery cell replacement plan based on daily free time and a battery cell replacement point, wherein the recovery information is used for prompting a user to timely recover the battery cell.
In the step, the electronic equipment can comprehensively utilize the daily free time of the user and the information of the battery core replacement point which is closer to the daily free time of the user and is determined in the previous step, intelligently generate a battery core replacement plan and prompt the user.
Specifically, the electronic device may schedule the time and place plan of the battery cell replacement according to the daily free time of the user, such as the time of the subway from work on monday to friday, the time of the rest on noon on the weekend, and the like, determined in step S207, and determine the nearby battery cell replacement point in combination with step S208. For example, the user may be recommended to perform a battery replacement to a certain battery replacement point during the off-duty journey from monday to friday, or to go to a battery recovery point closer to home during the weekend.
Finally, the electronic device may actively send the personalized replacement plan reminder including the time and place of the cell replacement to the user by application push or other means. So that a user can find a proper time to go to a nearby battery core replacement point in daily life to recover or replace the battery, and the convenience of battery core recovery and maintenance is improved.
In some embodiments, the electronic device further merges the historical environmental data and the historical working data of the battery cell into battery cell usage data, and uploads the battery cell usage data to a cloud database of the background server; the historical environmental data includes a historical environmental temperature, a historical environmental humidity; the historical working data comprises historical charge and discharge data and historical working current and voltage data; and determining the latest battery cell life model based on optimization of the battery cell life model by using the battery cell use data of the battery cells in the cloud database by the background server.
Specifically, a battery cell life model used by the electronic equipment in life prediction generation can be updated and optimized through the cloud computing platform. Specifically, the electronic device may collect and store long-term usage data of the battery cell, including ambient temperature and humidity, charge and discharge data, operating current and voltage, and the like. The historical data can be uploaded to a cloud database of a background server through connected mobile phones and other devices, so that the centralized storage of massive battery cell individual data is realized. The background server can then use the data to continuously retrain the battery life prediction model for model optimization to improve prediction accuracy. The optimized latest battery cell life model can be fed back and applied to the electronic equipment, and a more accurate evaluation direction is made on the health state of the current battery cell.
In the embodiment of the application, the self-adaptive monitoring of the state of the battery cell is realized by detecting the ambient temperature and adjusting the monitoring parameters according to the temperature change, and the health state of the battery cell can be judged more accurately compared with the fixed parameter monitoring. In addition, on the basis of keeping a basic self-adaptive monitoring function, the electronic equipment also performs function expansion and optimization, the battery core state evaluation can be performed individually by applying a battery core life prediction model, the battery core can be recovered in time according to a model result, and recovery planning is performed by considering the habit of a user, so that the battery core can be utilized to the maximum extent and the operation of the user is facilitated; and the cloud computing continuous optimization health evaluation model is adopted to realize the intellectualization of battery management.
Through the specific embodiment, the battery cell health state can be accurately estimated and the battery can be finely and individually managed, and the use safety, the use efficiency and the convenience of the battery are effectively improved.
The electronic device in the embodiment of the present application is described below from the viewpoint of a module. Fig. 3 is a schematic structural diagram of a functional module of an electronic device according to an embodiment of the present application.
The electronic device includes:
the monitoring module 301 is configured to monitor the operation of the battery cell according to a first monitoring frequency to obtain a first operation parameter; the working parameters comprise working voltage, working current and working temperature;
A temperature module 302, configured to determine a first ambient temperature of an environment in which the battery cell is located;
the updating module 303 is configured to monitor the operation of the battery cell according to the second monitoring frequency when the first ambient temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, so as to obtain a second operation parameter;
and the early warning module 304 is configured to generate working early warning information for prompting the user that the battery cell is abnormal when the second working parameter is not within the preset normal working threshold range.
In some embodiments, the electronic device further comprises:
a processing module 305, configured to determine whether the first environmental temperature is within a safe environmental threshold range for normal operation of the battery cell;
the early warning module 304 is further configured to generate environmental early warning information for prompting a user that the operating environment of the battery cell is abnormal when the first environmental temperature is not within the safe environmental threshold range of the normal operation of the battery cell.
In some embodiments, the pre-warning module 304 specifically includes:
an environment determining unit 3041, configured to determine a second environmental temperature of an environment where the battery cell is located when the second operating parameter is not within a preset normal threshold range;
a threshold value judging unit 3042, configured to determine, based on the second environmental temperature, whether the second operating parameter is within a preset normal operating threshold range corresponding to the second environmental temperature;
The prompt generation unit 3043 is configured to generate working early warning information for prompting the user that the battery cell is abnormal when the second working parameter is not within the preset normal working threshold range corresponding to the second environment temperature.
In some embodiments, the electronic device further comprises:
the prediction module 306 is configured to input the second working parameter and the environmental data into the life model of the battery cell, so as to obtain a life prediction residual time of the battery cell; the environmental data are temperature data and humidity data of the environment where the battery cell is located.
In some embodiments, the electronic device:
the processing module 305 is further configured to determine whether the lifetime prediction remaining time is less than a preset reclamation threshold;
the early warning module 304 is further configured to generate recovery information for prompting a user to timely recover the battery cell when the life prediction remaining time is lower than a preset recovery threshold.
In some embodiments, the electronic device further comprises:
the cloud module 307 is configured to combine the historical environmental data and the historical working data of the battery core into battery core usage data, and upload the battery core usage data to a cloud database of the background server; the historical environmental data includes a historical environmental temperature, a historical environmental humidity; the historical working data comprises historical charge and discharge data and historical working current and voltage data;
The optimization module 308 is configured to determine an up-to-date battery life model based on optimization of the battery life model by the background server using the plurality of battery usage data of the plurality of battery cells in the cloud database.
In some embodiments, the pre-warning module 304 specifically further includes:
a time determining unit 3044, configured to determine a daily free time of the user based on the daily mobile phone usage information of the user;
a location determining unit 3045, configured to determine a cell replacement point nearest to the user based on daily location information of the user;
the planning prompting unit 3046 is configured to generate recovery information including a cell replacement plan based on daily free time and a cell replacement point, so as to prompt a user to timely perform cell recovery.
The electronic device in the embodiment of the present application is described above from the point of view of the modularized functional entity, and the electronic device in the embodiment of the present application is described below from the point of view of hardware processing, please refer to fig. 4, which is a schematic structural diagram of an entity device of the electronic device in the embodiment of the present application.
It should be noted that the structure of the electronic device shown in fig. 4 is only an example, and should not impose any limitation on the functions and the application scope of the embodiments of the present invention.
As shown in fig. 4, the electronic apparatus includes a central processing unit (Central Processing Unit, CPU) 401 which can perform various appropriate actions and processes, such as performing the method described in the above embodiment, according to a program stored in a Read-Only Memory (ROM) 402 or a program loaded from a storage section 408 into a random access Memory (Random Access Memory, RAM) 403. In the RAM 403, various programs and data required for the system operation are also stored. The CPU 401, ROM 402, and RAM 403 are connected to each other by a bus 404. An Input/Output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a temperature detecting means, a humidity detecting means, a positioning means, and the like; an output portion 407 including a liquid crystal display (Liquid Crystal Display, LCD), an indicator light, an audio output device, and the like; a storage section 408 including a hard disk or the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. The drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.
In particular, according to embodiments of the present invention, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 409 and/or installed from the removable medium 411. When executed by a Central Processing Unit (CPU) 401, the computer program performs various functions defined in the present invention.
It should be noted that, the computer readable medium shown in the embodiments of the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Specifically, the electronic device of the present embodiment includes a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the adaptive cell health monitoring method provided in the foregoing embodiment is implemented.
As another aspect, the present invention also provides a computer-readable storage medium that may be contained in the electronic device described in the above-described embodiment; or may exist alone without being incorporated into the electronic device. The storage medium carries one or more computer programs which, when executed by a processor of the electronic device, cause the electronic device to implement the adaptive cell health monitoring method provided in the above embodiments.
The above embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
As used in the above embodiments, the term "when …" may be interpreted to mean "if …" or "after …" or "in response to determination …" or "in response to detection …" depending on the context. Similarly, the phrase "at the time of determination …" or "if detected (a stated condition or event)" may be interpreted to mean "if determined …" or "in response to determination …" or "at the time of detection (a stated condition or event)" or "in response to detection (a stated condition or event)" depending on the context.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, from a website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk), etc.
Those of ordinary skill in the art will appreciate that implementing all or part of the above-described method embodiments may be accomplished by a computer program to instruct related hardware, the program may be stored in a computer readable storage medium, and the program may include the above-described method embodiments when executed. And the aforementioned storage medium includes: ROM or random access memory RAM, magnetic or optical disk, etc.
Claims (10)
1. An adaptive cell health monitoring method applied to electronic equipment, the method comprising:
monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter; the working parameters comprise working voltage, working current and working temperature;
determining a first ambient temperature of an environment in which the battery cell is located;
when the first environmental temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, monitoring the operation of the battery cell according to a second monitoring frequency to obtain a second operating parameter;
and when the second working parameter is not in the preset normal working threshold range, generating working early warning information for prompting the user that the battery cell works abnormally.
2. The method of claim 1, wherein after the step of determining a first ambient temperature of the environment in which the cell is located, the method further comprises:
determining whether the first ambient temperature is within a safe ambient threshold range for normal operation of the battery cell;
if not, generating environment early warning information for prompting the user that the battery cell operation environment is abnormal.
3. The method of claim 1, wherein generating the operation early warning information when the second operation parameter is not within the preset normal operation threshold range specifically includes:
when the second working parameter is not in the preset normal threshold range, determining a second environment temperature of the environment where the battery cell is located;
determining whether the second working parameter is within a preset normal working threshold range corresponding to the second environment temperature based on the second environment temperature;
if not, generating working early warning information for prompting the user that the battery cell works abnormally.
4. The method of claim 1, wherein after the step of monitoring the cell operation at a second monitoring frequency to obtain a second operating parameter, the method further comprises:
Inputting the second working parameters and the environmental data into a battery cell life model to obtain life prediction residual time of the battery cell; the environment data are temperature data and humidity data of the environment where the battery cell is located.
5. The method of claim 4, wherein after the step of inputting the second operating parameter into a battery life model to obtain a life prediction residual time for the battery, the method further comprises:
judging whether the life prediction residual time is lower than a preset recovery threshold value or not;
if yes, generating recovery information for prompting a user to timely recover the battery cells.
6. The method of claim 5, wherein after the step of generating recovery information, the method further comprises:
combining the historical environment data and the historical working data of the battery cell into battery cell use data, and uploading the battery cell use data to a cloud database of a background server; the historical environment data comprises historical environment temperature and historical environment humidity; the historical working data comprise historical charge and discharge data and historical working current and voltage data;
and determining the latest battery cell life model based on optimization of the battery cell life model by using the battery cell use data of the battery cells in the cloud database by the background server.
7. The method according to claim 5, wherein the generating recovery information specifically comprises:
determining daily free time of the user based on the daily mobile phone use information of the user;
determining a cell replacement point nearest to the user based on the daily position information of the user;
and generating recovery information comprising a battery cell replacement plan based on the daily free time and the battery cell replacement point, wherein the recovery information is used for prompting the user to timely recover the battery cell.
8. An electronic device, comprising:
the monitoring module is used for monitoring the operation of the battery cell according to the first monitoring frequency to obtain a first operating parameter; the working parameters comprise working voltage, working current and working temperature;
the temperature module is used for determining a first environment temperature of the environment where the battery cell is located;
the updating module is used for monitoring the operation of the battery cell according to a second monitoring frequency when the first ambient temperature is greater than a first preset monitoring temperature corresponding to the first monitoring frequency, so as to obtain a second operating parameter;
and the early warning module is used for generating working early warning information for prompting the user that the battery cell works abnormally when the second working parameter is not in the preset normal working threshold range.
9. An electronic device, comprising: one or more processors and memory;
the memory is coupled with the one or more processors, the memory for storing computer program code comprising computer instructions that the one or more processors invoke to cause the electronic device to perform the method of any of claims 1-7.
10. A computer readable storage medium comprising instructions which, when run on an electronic device, cause the electronic device to perform the method of any of claims 1-7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118610615A (en) * | 2024-06-11 | 2024-09-06 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Energy storage battery safety protection method, device, equipment, storage medium and program product |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118610615A (en) * | 2024-06-11 | 2024-09-06 | 中国电子产品可靠性与环境试验研究所（（工业和信息化部电子第五研究所）（中国赛宝实验室）） | Energy storage battery safety protection method, device, equipment, storage medium and program product |
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