A method, device and system for online monitoring of remaining power of lithium battery

Abstract

The present application relates to the technical field of power monitoring, and specifically to a method, device and system for online monitoring of the remaining power of a lithium battery. The method includes: collecting data such as current, voltage and temperature through sensors; constructing a target time interval, and obtaining load current fluctuations according to the fluctuations of the current in the target time interval; obtaining a load state coefficient according to different current differences and temperatures; obtaining the load intensity at each moment based on the two; obtaining the charging influence coefficient at each moment according to the difference in voltages of adjacent batteries and the load intensity in the target time interval; obtaining the charging efficiency at each moment according to the charging influence coefficient; monitoring the remaining power of the lithium battery at each moment through the ampere-hour integration method according to the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment. The present application improves the monitoring accuracy of the remaining power when the lithium battery is charged.

Description

Technical Field

[0001] The present application relates to the technical field of power monitoring, and in particular to a method, device and system for online monitoring of the remaining power of a lithium battery. Background Art

[0002] As the core energy supply technology for today's electronic devices, electric vehicles and energy storage systems, lithium batteries have developed rapidly in recent years. With the rise of the new energy industry, the application areas of lithium batteries have been further expanded, promoting the continuous upgrading of battery performance and manufacturing technology.

[0003] With the widespread application of lithium batteries in high-demand scenarios, issues such as their safety, life prediction and online monitoring have also received increasing attention, especially the accurate monitoring of the remaining power. Accurate monitoring of the remaining power of lithium batteries is of great significance for improving battery efficiency, ensuring safe and stable operation of equipment, and optimizing user experience. Although the traditional ampere-hour integration method is simple and easy to use for monitoring the remaining power of lithium batteries, the ampere-hour integration method usually requires the battery to be in a single discharge state during the process of monitoring the remaining power of the battery. However, for the battery charging process, when the equipment is working normally, the remaining power of the battery monitored by the traditional ampere-hour integration method is less accurate due to the complex charging and discharging state, and it is difficult to meet the high-precision and real-time monitoring requirements of online monitoring of the remaining power of lithium batteries. Summary of the invention

[0004] In order to solve the technical problem of inaccurate power monitoring during charging, the present application provides a method, device and system for online monitoring of the remaining power of a lithium battery. The technical solution adopted is as follows:

[0005] In a first aspect, the present application proposes a method for online monitoring of the remaining power of a lithium battery, the method comprising the following steps:

[0006] The temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging are collected through sensors;

[0007] For each moment, the preset moments before each moment constitute the target time interval corresponding to each moment; the load current fluctuation at each moment is obtained according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line; the load state coefficient at each moment is obtained according to the temperature at each moment and the difference between the load current and the battery current; the load current fluctuation and the load state coefficient at each moment are forwardly fused to obtain the load intensity at each moment;

[0008] The sum of the differences in the voltages of all adjacent batteries within the target time interval corresponding to each moment is taken as the voltage cumulative amplitude at each moment, and the charging influence coefficient at each moment is obtained according to the voltage cumulative amplitude, the load intensity, and the difference in the battery voltage at each moment; the charging influence coefficient is normalized and then inversely mapped to obtain the charging efficiency at each moment;

[0009] The remaining capacity of the lithium battery at each moment is monitored by the ampere-hour integration method based on the initial capacity, the rated capacity of the battery, the charging efficiency and the charging current at each moment.

[0010] In the above scheme, the present application collects temperature, current and voltage data during the charging process of the lithium battery, and constructs the load intensity by analyzing the correlation between current and temperature during the charging process. The load intensity takes into account the impact of the high-load operation of the equipment during the charging process of the lithium battery on the charging efficiency of the lithium battery. According to the load intensity, the difference between the load current and the lithium battery current when the charging current provided by the external power supply under high-load operation of the lithium battery is used for normal operation of the equipment can be reflected; secondly, the charging efficiency of the battery is constructed based on the voltage change of the lithium battery when the equipment is under high-load charging state and combined with the load change index of the equipment. The beneficial effect is that the charging efficiency takes into account the drop phenomenon of the lithium battery voltage when the equipment is under high-load charging state. According to the charging efficiency, the charging efficiency used for charging the lithium battery can be more accurately reflected, thereby improving the monitoring accuracy of the remaining power when the lithium battery is charging.

[0011] In one embodiment, the method for obtaining the load current fluctuation at each moment according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line is:

[0012] The load current at all times within the target time interval is fitted by the least square method, and the slope of the straight line is calculated;

[0013] The load current fluctuation is positively correlated with the variance of the load current and positively correlated with the slope of the straight line.

[0014] In one embodiment, the method for obtaining the load state coefficient at each moment according to the temperature at each moment and the difference between the load current and the battery current is: , represents the temperature at the tth moment, represents the load current at the tth moment, represents the battery current at the tth moment, represents an exponential function with a natural constant as base, represents the load state coefficient at the t-th moment, where the t-th moment is the current moment.

[0015] In one embodiment, the method of forward fusing the load current fluctuation and the load state coefficient at each moment to obtain the load intensity at each moment is: , represents the load state coefficient at the tth moment, represents the load current fluctuation at the tth moment, represents the load intensity at the t-th moment, where the t-th moment is the current moment.

[0016] In one embodiment, the method of using the sum of the differences of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment is:

[0017] For the target time interval, the battery voltage at each moment in the target time interval is subtracted from the battery voltage at the next moment, and all the differences are accumulated as the voltage cumulative amplitude at each moment.

[0018] In one embodiment, the method for obtaining the charging influence coefficient at each moment according to the difference between the voltage cumulative amplitude and the load intensity and the battery voltage at each moment is: , represents the load intensity at the tth moment, represents the battery voltage at the tth moment, represents the battery voltage at the t-1th moment, represents the voltage cumulative amplitude at the tth moment, Represents the charging influence coefficient at the tth moment.

[0019] In one embodiment, the method of normalizing the charging influence coefficient and then inversely mapping to obtain the charging efficiency at each moment is:

[0020] The charging influence coefficient at each moment is linearly normalized, and the charging efficiency at each moment is obtained by subtracting the number 1 from the normalized charging influence coefficient.

[0021] In one embodiment, the method for monitoring the remaining power of the lithium battery at each moment by the ampere-hour integration method according to the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment is: , Indicates the initial capacity of the lithium battery during charging, C indicates the available capacity under standard conditions, represents the charging efficiency at the tth moment, represents the charging current at the tth moment, It shows the remaining power of the lithium battery at the tth moment.

[0022] On the other hand, an embodiment of the present application further provides an online monitoring system for the remaining power of a lithium battery, the system comprising:

[0023] The acquisition module is used to collect the temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging through sensors;

[0024] The load intensity acquisition module is used to, for each moment, form a target time interval corresponding to each moment with the preset moments before each moment; obtain the load current fluctuation at each moment according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line; obtain the load state coefficient at each moment according to the temperature at each moment and the difference between the load current and the battery current; forwardly fuse the load current fluctuation and the load state coefficient at each moment to obtain the load intensity at each moment;

[0025] The charging efficiency acquisition module is used to take the difference of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment, and obtain the charging influence coefficient at each moment according to the voltage cumulative amplitude, load intensity and the difference of battery voltage at each moment; the charging influence coefficient is normalized and then inversely mapped to obtain the charging efficiency at each moment;

[0026] The remaining power monitoring module is used to monitor the remaining power of the lithium battery at each moment through the ampere-hour integration method based on the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment.

[0027] In a third aspect, an embodiment of the present application also provides an online monitoring device for the remaining power of a lithium battery, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for online monitoring the remaining power of a lithium battery are implemented.

[0028] The beneficial effects of this application are:

[0029] This application collects temperature, current and voltage data during the charging process of a lithium battery, and constructs a load intensity by analyzing the correlation between current and temperature during the charging process. The load intensity takes into account the impact of the high-load operation of the device during the charging process of the lithium battery on the charging efficiency of the lithium battery. The load intensity can reflect the difference between the load current and the lithium battery current when the charging current provided by an external power supply under high-load operation of the lithium battery is used for normal operation of the device. Secondly, the charging efficiency of the battery is constructed based on the voltage change of the lithium battery when the device is under high-load charging and combined with the load change index of the device. The beneficial effect is that the charging efficiency takes into account the drop of the lithium battery voltage when the device is under high-load charging. The charging efficiency can more accurately reflect the charging efficiency used for charging the lithium battery, thereby improving the monitoring accuracy of the remaining power when the lithium battery is charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A flow chart of a method for online monitoring of the remaining power of a lithium battery provided in one embodiment of the present application;

[0032] Figure 2 This is the curve of voltage changing with charging time. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the method, device and system for online monitoring of the remaining power of a lithium battery proposed in the present application, its specific implementation method, structure, characteristics and effects in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0035] An embodiment of a method for online monitoring of the remaining power of a lithium battery:

[0036] The following is a detailed description of a method for online monitoring of the remaining power of a lithium battery provided by the present application in conjunction with the accompanying drawings.

[0037] See also Figure 1 , which shows a flow chart of a method for online monitoring of the remaining power of a lithium battery provided by an embodiment of the present application, the method comprising the following steps:

[0038] Step S001, collecting the temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging through sensors.

[0039] The remaining power of a lithium battery during charging is not only related to the charging current and the initial remaining power during charging, but also to the operating status of the device during charging of the lithium battery. High-load operation of the device will seriously affect the charging efficiency of the lithium battery.

[0040] Therefore, the present application uses a temperature sensor, a current sensor, and a voltage sensor to obtain the temperature data of the device when the lithium battery is charging, the load current for normal operation of the device, the battery current, the charging current provided by the external power supply, and the lithium battery voltage data; each of which is recorded as a parameter as temperature, load current, battery current, charging current, and battery voltage. In this embodiment, the collection interval is 1s.

[0041] So far, the temperature, load current, battery current, charging current and battery voltage during charging have been obtained.

[0042] Step S002, for each moment, the preset moments before each moment constitute the target time interval corresponding to each moment; the load current fluctuation at each moment is obtained according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting line; the load state coefficient at each moment is obtained according to the temperature at each moment and the difference between the load current and the battery current; the load current fluctuation at each moment and the load state coefficient are forwardly fused to obtain the load intensity at each moment.

[0043] In battery management systems, the ampere-hour integration method is a common method to estimate the state of charge, which refers to the ratio of the remaining power in the battery to the total power, so it can be used to obtain the percentage of remaining power. Under normal circumstances, when a lithium battery is in a single charging or discharging state, the voltage, current and temperature parameters of the lithium battery change relatively stably, and the remaining power estimation is usually more accurate;

[0044] However, in actual applications, when the lithium battery is in the process of charging, the equipment is also working normally, and is in both charging and discharging states. In this state, the lithium battery provides power for the equipment while receiving the charging current, resulting in large fluctuations in current and voltage. In addition, when the lithium battery is charging and discharging at the same time, the charging efficiency will decrease due to the heating of the equipment and the increase in power consumption, and may even cause the lithium battery to be in a discharging state at some times. This complex working state makes it impossible for the traditional ampere-hour integration method to accurately estimate the remaining power of the lithium battery.

[0045] The stability of the device load is particularly important when the lithium battery is working while charging. For example, when the user turns on multiple high-energy-consuming devices at the same time and works at high load, the battery current will fluctuate violently, which will affect the power supply capacity and charging process of the lithium battery, resulting in a lower charging efficiency of the lithium battery. At the same time, the high-load operation and charging process of the equipment will generate a lot of heat, and the temperature change will directly affect the internal resistance and chemical reaction efficiency of the lithium battery, which will lead to a decrease in the discharge efficiency of the lithium battery and the energy conversion rate of the charging process. Therefore, this application comprehensively considers the fluctuations in battery current and temperature and evaluates the changes in the remaining power of the device when charging under high load operation. Specifically, the greater the working intensity of the equipment, the greater the load current required to support the normal operation of the equipment, and the smaller the charging current used to supply the lithium battery. At the same time, due to the high-load operation of the equipment and the charging of the lithium battery, the temperature of the equipment will also rise sharply at this time.

[0046] In addition, the charging current of lithium batteries needs to respond quickly to changes, and the inertia of the chemical reaction inside lithium batteries makes it difficult to cope with high-frequency fluctuations in current, thereby reducing charging efficiency. For example, when the energy storage system powers multiple devices at the same time, high-frequency current fluctuations will increase energy loss during the charging process. Specifically, when the load current rises or falls rapidly, the system needs to quickly adjust the power distribution. If the load current changes too quickly, the lithium battery and the charging system may not be able to respond in time, which will cause the charging efficiency of the lithium battery to decrease. Therefore, the fluctuations in the load current of the lithium battery at the current moment are calculated for the past period of time.

[0047] In this embodiment, all moments 1 minute before the current moment are selected to form a time interval, and the load fluctuation is calculated through the time interval to reflect the charging efficiency of the lithium battery, and this time interval is recorded as the target time interval.

[0048] Perform linear fitting on the load current at all times within the target time interval to obtain the slope of the fitted straight line. The linear fitting method used in this embodiment is the least squares method, and the implementer may also use other linear fitting methods.

[0049] The load current fluctuation at the current moment is obtained by the variance of the load current at all moments in the target time interval and the slope of the corresponding straight line.

[0050] The load current fluctuation is positively correlated with the variance of the load current and positively correlated with the slope of the straight line.

[0051] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the two variables change in the same direction. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large. The specific relationship is determined by actual application and this application does not impose any special restrictions.

[0052] Preferably, in this embodiment, the expression of load current fluctuation is: , It represents the slope of the straight line fitting the load current in the time interval corresponding to the tth moment, represents the load current set in the time interval corresponding to the tth moment, It represents the variance of all load currents in the time interval corresponding to the tth moment, represents the load current fluctuation at the t-th moment, where the t-th moment is the current moment.

[0053] Preferably, in another embodiment of the present application, the expression of load current fluctuation is: , It represents the slope of the straight line fitting the load current in the time interval corresponding to the tth moment, represents the load current set in the time interval corresponding to the tth moment, It represents the variance of all load currents in the time interval corresponding to the tth moment, represents the load current fluctuation at the t-th moment, where the t-th moment is the current moment.

[0054] The load state coefficient of the device at the current moment is obtained through the temperature at the current moment and the difference between the load current and the battery current corresponding to the current moment.

[0055] The load state factor is positively correlated with temperature and with the difference between load current and battery current.

[0056] Preferably, in this embodiment, the expression of the load state coefficient is: , represents the temperature at the tth moment, represents the load current at the tth moment, represents the battery current at the tth moment, represents an exponential function with a natural constant as base, represents the load state coefficient at the t-th moment, where the t-th moment is the current moment.

[0057] The load intensity at the current moment is obtained according to the load state coefficient at the current moment and the load current fluctuation at the current moment.

[0058] The load intensity is positively correlated with the load state coefficient and the load current fluctuation respectively.

[0059] Preferably, in this embodiment, the expression of load intensity is: , represents the load state coefficient at the tth moment, represents the load current fluctuation at the tth moment, represents the load intensity at the t-th moment, where the t-th moment is the current moment.

[0060] When the device is charged under high load, most of the power supplied by the external power supply to the device is used to support the normal operation of the device, and a small part is used to support the charging of the lithium battery. At this time, the load current is greater than the battery current, which makes the calculated current difference larger. At the same time, since the device temperature will rise sharply when the device is running under high load, the device temperature at this time is relatively large, which makes the calculated load state coefficient at the current moment larger. The larger the load state coefficient, the more likely the battery is in the load state; and when the load current of the device fluctuates greatly, the variance of the calculated load current is larger. At the same time, when the device changes from low load to high load, the load current of the device will rise sharply in a short time, which makes the calculated linear fitting slope of the load current larger, making the calculated load current fluctuation of the device at the current moment larger, and making the calculated load intensity of the device larger. It means that the device is in a high load state at the current moment, and the charging efficiency of the lithium battery is low.

[0061] At this point, the load strength of the lithium battery at the current moment is obtained.

[0062] Step S003, taking the difference of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment, and obtaining the charging influence coefficient at each moment according to the voltage cumulative amplitude, load intensity and the difference of battery voltage at each moment; normalizing the charging influence coefficient and then inversely mapping it to obtain the charging efficiency at each moment.

[0063] During normal charging, the voltage of a lithium battery will go through multiple stages of change. The voltage of a lithium battery will gradually rise as charging progresses. When the voltage of a lithium battery approaches its charging limit voltage, the voltage of the lithium battery enters the constant voltage charging stage, and the voltage of the lithium battery remains basically unchanged. However, under high-load charging conditions, the voltage of a lithium battery will drop instantly due to the instantaneous increase in load current, thereby affecting the accuracy of the estimation of the remaining power of the lithium battery. Figure 2 shown.

[0064] Since the lithium battery voltage continues to drop, in this embodiment, the time interval 1 minute before the current moment is also used as the target time interval. The battery charging influence coefficient is obtained by the difference between two adjacent voltages in the target time interval, the voltage difference between the current moment and the previous moment, and the load intensity of the lithium battery at the current moment.

[0065] The battery charging influence coefficient is positively correlated with the difference between two adjacent voltages in the time interval, is positively correlated with the load intensity of the lithium battery at the current moment, and is positively correlated with the voltage difference between the current moment and the previous moment.

[0066] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly, and the two variables change in opposite directions. When one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small. The specific relationship is determined by actual application and this application does not impose any special restrictions.

[0067] Preferably, in this embodiment, the expression of the charging influence coefficient is: , , represents the battery voltage at the i-th moment in the target time interval, represents the battery voltage at the i-1th moment in the target time interval, Indicates the number of moments in the target time interval, represents the load intensity at the tth moment, represents the battery voltage at the tth moment, represents the battery voltage at the t-1th moment, represents the voltage cumulative amplitude at the tth moment, Represents the charging influence coefficient at the tth moment.

[0068] When the device is in a high-load charging state, the load current fluctuates, causing the lithium battery voltage to fluctuate and drop for a short time, making the battery voltage at the previous moment in the target time interval greater than the battery voltage at the next moment. The larger the value is, and the larger the difference is, the more it indicates that the time interval is affected by the load current, and the charging efficiency is reduced at this time. Similarly, the smaller the difference between the current moment and the previous moment is, the current moment is also affected by the load current, and the charging efficiency is reduced. At the same time, when the device is in a high load state, the greater the load intensity of the lithium battery, and the greater the charging influence coefficient of the lithium battery when the device is charged. This indicates that the charging efficiency of the lithium battery is low at the current moment.

[0069] The charging influence coefficient at each moment is obtained through the above steps, and the charging efficiency of the battery at each moment is calculated through the charging influence coefficient at each moment.

[0070] Preferably, in this embodiment, the expression of charging efficiency is: , represents the charging influence coefficient at the tth moment, represents the linear normalization function, Represents the charging efficiency of the battery at the tth moment.

[0071] Since the load of the battery will not be affected when it just starts to run, in this embodiment, since the time 1 minute before each moment is selected, the charging efficiency of the moment collected in the first minute is represented by 1.

[0072] So far, the charging efficiency of the battery at each moment has been obtained through the above steps.

[0073] Step S004, monitoring the remaining power of the lithium battery at each moment by the ampere-hour integration method according to the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment.

[0074] The charging efficiency of the battery at each moment is obtained through the above steps. The remaining power of the lithium battery at each moment is obtained by using the ampere-hour integration method through the charging efficiency, initial power, charging current and rated power of the battery at each moment.

[0075] , Indicates the initial capacity of the lithium battery during charging, C indicates the available capacity under standard conditions, represents the charging efficiency at the tth moment, represents the charging current at the tth moment, It shows the remaining power of the lithium battery at the tth moment.

[0076] At this point, the monitoring of the remaining power of the lithium battery is completed.

[0077] Based on the same inventive concept as the above method, an embodiment of the present invention further provides an online monitoring system for the remaining power of a lithium battery, comprising the following modules:

[0078] The acquisition module is used to collect the temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging through sensors;

[0079] The load intensity acquisition module is used to, for each moment, form a target time interval corresponding to each moment with the preset moments before each moment; obtain the load current fluctuation at each moment according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line; obtain the load state coefficient at each moment according to the temperature at each moment and the difference between the load current and the battery current; forwardly fuse the load current fluctuation and the load state coefficient at each moment to obtain the load intensity at each moment;

[0080] The charging efficiency acquisition module is used to take the difference of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment, and obtain the charging influence coefficient at each moment according to the voltage cumulative amplitude, load intensity and the difference of battery voltage at each moment; the charging influence coefficient is normalized and then inversely mapped to obtain the charging efficiency at each moment;

[0081] The remaining power monitoring module is used to monitor the remaining power of the lithium battery at each moment through the ampere-hour integration method based on the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment.

[0082] Based on the same inventive concept as the above method, an embodiment of the present invention also provides an online monitoring device for the remaining power of a lithium battery, wherein the computer device includes a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned methods for online monitoring the remaining power of a lithium battery are implemented.

[0083] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

[0084] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for online monitoring of the remaining power of a lithium battery, characterized in that: The method comprises the following steps: The temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging are collected through sensors; For each moment, the preset time period before each moment constitutes the target time interval corresponding to each moment; the load current fluctuation at each moment is obtained according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line; the load state coefficient at each moment is obtained according to the temperature at each moment and the difference between the load current and the battery current; the load current fluctuation at each moment and the load state coefficient are forwardly fused to obtain the load intensity at each moment; The sum of the differences in the voltages of all adjacent batteries within the target time interval corresponding to each moment is taken as the voltage cumulative amplitude at each moment, and the charging influence coefficient at each moment is obtained according to the voltage cumulative amplitude, the load intensity, and the difference in the battery voltage at each moment; the charging influence coefficient is normalized and then inversely mapped to obtain the charging efficiency at each moment; The remaining capacity of the lithium battery at each moment is monitored by the ampere-hour integration method based on the initial capacity, the rated capacity of the battery, the charging efficiency and the charging current at each moment; The method for obtaining the load current fluctuation at each moment according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line is: The load current at all times within the target time interval is fitted by the least square method, and the slope of the straight line is calculated; The load current fluctuation is positively correlated with the variance of the load current and positively correlated with the slope of the straight line; The method for obtaining the load state coefficient at each moment according to the temperature at each moment and the difference between the load current and the battery current is: , represents the temperature at the tth moment, represents the load current at the tth moment, represents the battery current at the tth moment, exp() represents an exponential function with a natural constant as the base, represents the load state coefficient at the tth moment; The method of forward fusing the load current fluctuation and the load state coefficient at each moment to obtain the load intensity at each moment is: , represents the load state coefficient at the tth moment, represents the load current fluctuation at the tth moment, represents the load intensity at the tth moment; The method for obtaining the charging influence coefficient at each moment according to the difference between the voltage cumulative amplitude and the load intensity and the battery voltage at each moment is: , represents the load intensity at the tth moment, represents the battery voltage at the tth moment, represents the battery voltage at the t-1th moment, represents the voltage cumulative amplitude at the tth moment, It represents the charging influence coefficient at the t-th moment, and exp() represents an exponential function with a natural constant as the base.

2. A method for online monitoring of the remaining power of a lithium battery as claimed in claim 1, characterized in that: The method of taking the sum of the differences of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment is: For the target time interval, the battery voltage at each moment in the target time interval is subtracted from the battery voltage at the next moment, and all the differences are accumulated as the voltage cumulative amplitude at each moment.

3. The method for online monitoring of the remaining power of a lithium battery according to claim 1, characterized in that: The method of normalizing the charging influence coefficient and then inversely mapping to obtain the charging efficiency at each moment is: The charging influence coefficient at each moment is linearly normalized, and the charging efficiency at each moment is obtained by subtracting the number 1 from the normalized charging influence coefficient.

4. The method for online monitoring of the remaining power of a lithium battery according to claim 1, characterized in that: The method for monitoring the remaining power of the lithium battery at each moment by the ampere-hour integration method according to the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment is: , Indicates the initial capacity of the lithium battery during charging, C indicates the available capacity under standard conditions, represents the charging efficiency at the tth moment, represents the charging current at the tth moment, It shows the remaining power of the lithium battery at the tth moment.

5. A system for online monitoring of the remaining power of a lithium battery, which implements the method for online monitoring of the remaining power of a lithium battery as claimed in claim 1, characterized in that: The system comprises: The acquisition module is used to collect the temperature, load current, battery current, charging current and battery voltage of the lithium battery during charging through sensors; The load intensity acquisition module is used to, for each moment, form a target time interval corresponding to each moment from a preset time period before each moment; obtain the load current fluctuation at each moment according to the variance of the load current at all moments in the target time interval and the slope of the load current fitting straight line; obtain the load state coefficient at each moment according to the temperature at each moment and the difference between the load current and the battery current; forwardly fuse the load current fluctuation and the load state coefficient at each moment to obtain the load intensity at each moment; The charging efficiency acquisition module is used to take the difference of all adjacent battery voltages within the target time interval corresponding to each moment as the voltage cumulative amplitude at each moment, and obtain the charging influence coefficient at each moment according to the voltage cumulative amplitude, load intensity and the difference of battery voltage at each moment; the charging influence coefficient is normalized and then inversely mapped to obtain the charging efficiency at each moment; The remaining power monitoring module is used to monitor the remaining power of the lithium battery at each moment through the ampere-hour integration method based on the initial power, the rated power of the battery, and the charging efficiency and charging current at each moment.

6. An online monitoring device for the remaining power of a lithium battery, the device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for online monitoring the remaining power of a lithium battery as described in any one of claims 1 to 4 is implemented.

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