1. A digital twin based battery detection and maintenance method, the method comprising:

acquiring real-time operation data of a target battery acquired by an online detection unit;

according to the real-time operation data, determining maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery operation state analysis and prediction model;

and maintaining the target battery according to the maintenance parameters of the target battery.

2. The method of claim 1, wherein the method of obtaining real-time operating data of the target battery obtained by the online detection unit comprises:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

3. The method of claim 1, wherein after the obtaining of the real-time operation data of the target battery obtained by the online detection unit and before the determining of the maintenance parameters of the target battery, the method further comprises:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

4. The method of claim 1, wherein the maintaining the target battery according to the maintenance parameters of the target battery comprises:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

5. The method of claim 1, wherein prior to the method of determining the maintenance parameters of the target battery from the real-time operation data through a pre-trained cell digital twin model and a battery operating state analysis prediction model, the method further comprises:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

6. A digital twin based battery detection and maintenance apparatus, the apparatus comprising:

the first unit is used for acquiring real-time operation data of the target battery acquired by the online detection unit;

the second unit is used for determining the maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery running state analysis and prediction model according to the real-time running data;

and the third unit is used for maintaining the target battery according to the maintenance parameters of the target battery.

7. The apparatus of claim 6, wherein the first unit is configured to:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

8. The apparatus of claim 6, further comprising a fourth unit to:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

9. The apparatus of claim 6, wherein the third unit is further configured to:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

10. The apparatus of claim 6, further comprising a fifth unit configured to:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

Background

At present, many modern precision electric devices are often required to be provided with an uninterruptible power supply system, and a large number of storage batteries are utilized as standby power in the uninterruptible power supply system. These storage batteries are widely used as backup power sources in power supply systems in the industries such as finance, electric power, communication, railway, metallurgy, chemical engineering and medicine.

In actual use, the above-described large number of battery packs need to be appropriately monitored, including voltage monitoring, current monitoring, temperature monitoring, and the like, in order to estimate the state characteristics of the battery packs. The traditional storage battery measurement is carried out on site by engineering personnel, so that the labor cost is high and the measurement is not accurate enough.

Therefore, how to provide a technical solution to the above problems is a technical problem that needs to be solved by those skilled in the art.

Disclosure of Invention

The embodiment of the disclosure provides a battery detection and maintenance method and device based on digital twinning, which can be used for monitoring the working state of a storage battery pack on line in real time, performing on-line charging maintenance on monomer batteries with relatively backward voltages, and performing on-line discharging maintenance on monomer batteries with relatively forward voltages, thereby ensuring that the monomer batteries of the storage battery pack have better consistency.

In a first aspect of the embodiments of the present disclosure, a digital twin-based battery detection and maintenance method is provided, where the method includes:

acquiring real-time operation data of a target battery acquired by an online detection unit;

according to the real-time operation data, determining maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery operation state analysis and prediction model;

and maintaining the target battery according to the maintenance parameters of the target battery.

In an optional embodiment, the method for acquiring real-time operation data of the target battery acquired by the online detection unit includes:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

In an optional implementation manner, after the obtaining of the real-time operation data of the target battery obtained by the online detection unit and before the determining of the maintenance parameter of the target battery, the method further includes:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

In an optional implementation manner, the method for maintaining the target battery according to the maintenance parameter of the target battery includes:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

In an optional embodiment, before the method for determining the maintenance parameter of the target battery according to the real-time operation data through a pre-trained digital twin model of a single battery and a battery operation state analysis and prediction model, the method further includes:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

In a second aspect of the disclosed embodiments, there is provided a digital twin-based battery detection and maintenance apparatus, the apparatus comprising:

the first unit is used for acquiring real-time operation data of the target battery acquired by the online detection unit;

the second unit is used for determining the maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery running state analysis and prediction model according to the real-time running data;

and the third unit is used for maintaining the target battery according to the maintenance parameters of the target battery.

In an alternative embodiment, the first unit is configured to:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

In an alternative embodiment, the apparatus further includes a fourth unit configured to:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

In an alternative embodiment, the third unit is further configured to:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

In an alternative embodiment, the apparatus further includes a fifth unit configured to:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

The battery detection and maintenance method based on the digital twin comprises the steps of obtaining real-time operation data of a target battery obtained by an online detection unit; according to the real-time operation data, determining maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery operation state analysis and prediction model; and maintaining the target battery according to the maintenance parameters of the target battery.

The digital twin-based battery detection and maintenance method can be used for monitoring the working state of the storage battery pack in real time on line, performing on-line charging maintenance on the monomer batteries with relatively backward voltage, and performing on-line discharging maintenance on the monomer batteries with relatively forward voltage, so that the monomer batteries of the storage battery pack have better consistency.

Drawings

FIG. 1 is a schematic flow diagram of a digital twin-based battery detection and maintenance method according to an embodiment of the disclosure;

fig. 2 is a schematic structural diagram of a digital twin-based battery detection and maintenance device according to an embodiment of the disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present disclosure and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein.

It should be understood that, in various embodiments of the present disclosure, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the inherent logic of the processes, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

It should be understood that in the present disclosure, "including" 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.

It should be understood that in the present disclosure, "plurality" means two or more. "and/or" is merely an association describing an associated object, meaning that three relationships may exist, for example, and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "comprises A, B and C" and "comprises A, B, C" means that all three of A, B, C comprise, "comprises A, B or C" means that one of A, B, C comprises, "comprises A, B and/or C" means that any 1 or any 2 or 3 of A, B, C comprises.

It should be understood that in this disclosure, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information. And the matching of A and B means that the similarity of A and B is greater than or equal to a preset threshold value.

As used herein, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context.

The technical solution of the present disclosure is explained in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.

Fig. 1 schematically illustrates a flow chart of a digital twin-based battery detection and maintenance method according to an embodiment of the present disclosure, which includes, as shown in fig. 1:

s101, acquiring real-time operation data of a target battery acquired by an online detection unit;

in an optional embodiment, the method for acquiring real-time operation data of the target battery acquired by the online detection unit includes:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

In an optional implementation manner, after the obtaining of the real-time operation data of the target battery obtained by the online detection unit and before the determining of the maintenance parameter of the target battery, the method further includes:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

Step S102, determining maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery running state analysis and prediction model according to the real-time running data;

in an optional embodiment, before the method for determining the maintenance parameter of the target battery according to the real-time operation data through a pre-trained digital twin model of a single battery and a battery operation state analysis and prediction model, the method further includes:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

And S103, maintaining the target battery according to the maintenance parameters of the target battery.

In an optional implementation manner, the method for maintaining the target battery according to the maintenance parameter of the target battery includes:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

The battery detection and maintenance method based on the digital twin comprises the steps of obtaining real-time operation data of a target battery obtained by an online detection unit; according to the real-time operation data, determining maintenance parameters of the target battery through a pre-trained single battery digital twin model and a battery operation state analysis and prediction model; and maintaining the target battery according to the maintenance parameters of the target battery.

The digital twin-based battery detection and maintenance method can be used for monitoring the working state of the storage battery pack in real time on line, performing on-line charging maintenance on the monomer batteries with relatively backward voltage, and performing on-line discharging maintenance on the monomer batteries with relatively forward voltage, so that the monomer batteries of the storage battery pack have better consistency.

Fig. 2 schematically shows a structural diagram of a digital twin-based battery detection and maintenance device according to an embodiment of the present disclosure, and as shown in fig. 2, the device includes:

the first unit 21 is used for acquiring real-time operation data of the target battery acquired by the online detection unit;

the second unit 22 is used for determining the maintenance parameters of the target battery according to the real-time operation data through a pre-trained single battery digital twin model and a battery operation state analysis and prediction model;

a third unit 23, configured to perform maintenance on the target battery according to the maintenance parameter of the target battery.

In an alternative embodiment, the first unit 21 is configured to:

the on-line detection unit comprises a temperature sensor, a voltage sensor and a current sensor,

the temperature sensor is used for acquiring the operating temperature of the target battery;

the voltage sensor is used for acquiring the operating voltage of the target battery;

the current sensor is used for acquiring the running current of the target battery.

In an alternative embodiment, the apparatus further includes a fourth unit configured to:

judging whether the real-time operation data of the target battery acquired by the online detection unit is abnormal,

when the judgment result is yes, determining the maintenance parameters of the target battery;

and when the judgment result is negative, continuously acquiring the real-time operation data of the target battery.

In an alternative embodiment, the third unit 23 is further configured to:

inputting the maintenance parameters into an online maintenance unit, maintaining the target battery through the online maintenance unit,

the online maintenance unit is connected with the target battery and is used for maintaining the target battery when maintenance parameters are received.

In an alternative embodiment, the apparatus further includes a fifth unit configured to:

training the single battery digital twin model and the battery running state analysis and prediction model, wherein the training method comprises the following steps:

iteratively optimizing model parameters of the single battery digital twin model and the battery running state analysis and prediction model according to historical running data of the target battery so as to enable the single battery digital twin model and the battery running state analysis and prediction model to output maintenance parameters,

and the maintenance parameters are used for ensuring that all the single batteries of the storage battery pack have consistency while the target battery is in normal operation.

It should be noted that, for the beneficial effects of the digital twin-based battery detection and maintenance device according to the embodiment of the present disclosure, reference may be made to the beneficial effects of the foregoing digital twin-based battery detection and maintenance method, and details of the embodiment of the present disclosure are not repeated herein.

The present disclosure also provides a program product comprising execution instructions stored in a readable storage medium. The at least one processor of the device may read the execution instructions from the readable storage medium, and the execution of the execution instructions by the at least one processor causes the device to implement the methods provided by the various embodiments described above.

The readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the readable storage medium may also reside as discrete components in a communication device. The readable storage medium may be a read-only memory (ROM), a random-access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

In the above embodiments of the terminal or the server, it should be understood that the Processor may be a Central Processing Unit (CPU), other general-purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present disclosure may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.