A lithium battery health status monitoring method and system

Abstract

The present invention discloses a lithium battery health status monitoring method and system, which relates to the technical field of lithium battery status monitoring. Specifically, the invention discloses collecting the power output and temperature change characteristic information of the lithium battery and establishing a corresponding characteristic model; establishing a standard timeline for each characteristic model group, and setting an internal resistance detection node on it, performing internal resistance and remaining power detection on the test lithium battery, and forming a test power and internal resistance parameter group; by comparing these parameter groups with a preset standard parameter table, the health of the battery at the internal resistance detection node is determined; a parameter group between the accumulated characteristics and the battery health is also established for real-time monitoring of the health status of the lithium battery. Finally, the real-time accumulated characteristics are analyzed using this parameter group, thereby accurately determining the real-time health status of the lithium battery; the above technical solution of the present invention realizes the analysis and judgment of the health status of the lithium battery, and provides a guarantee for ensuring the normal operation of the lithium battery.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery status monitoring, and in particular to a lithium battery health status monitoring method and system. Background Art

[0002] With the rapid development of new energy technologies, lithium batteries, as efficient and environmentally friendly energy storage devices, have been widely used in electric vehicles, portable electronic devices, energy storage systems, and other fields. However, during use, the performance of lithium batteries gradually declines with the number of charge and discharge cycles, resulting in problems such as reduced capacity and increased internal resistance. This not only affects the endurance of the device but can also lead to safety hazards due to the deterioration of battery health. Therefore, accurate and real-time monitoring of the health of lithium batteries is crucial for ensuring the normal operation of equipment, extending battery life, and improving system safety. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for monitoring and analyzing the health status of lithium batteries.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] A lithium battery health status monitoring method and system, comprising:

[0006] Establishing a lithium battery health test experiment:

[0007] Collecting lithium battery power output characteristic information, and performing characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model; when collecting the lithium battery power output characteristic information, simultaneously collecting lithium battery temperature change characteristic information, and performing characteristic analysis on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model; and correlating the lithium battery power output characteristic model and the lithium battery temperature change characteristic model with internal characteristic factors to obtain a characteristic model group;

[0008] A standard timeline is established for each feature model group, and a number of internal resistance detection nodes are randomly set on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static use. When the temperature of the test lithium battery reaches the preset standard temperature, the test lithium battery is internally resisted to obtain the test internal resistance, and the test remaining power of the test lithium battery is obtained. The test remaining power and the test internal resistance are correlated to obtain a test power and internal resistance parameter group;

[0009] Comparing the test power and internal resistance parameter group with a preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and determining the battery health of the test battery at the internal resistance detection node based on the internal resistance difference;

[0010] Determine the power output accumulation characteristics and temperature change accumulation characteristics of the feature model group at the internal resistance detection node, and establish the accumulation characteristics ~ battery health parameter group;

[0011] When the health status of the lithium battery is monitored in real time, the real-time accumulated characteristics are analyzed using the accumulated characteristics~battery health parameter group to determine the real-time health status of the lithium battery.

[0012] In some embodiments disclosed herein, a method for constructing a lithium battery power output characteristic model and a lithium battery temperature change characteristic model includes:

[0013] Establish a time horizontal axis, and establish a power output vertical axis or a temperature change vertical axis in a direction perpendicular to the time horizontal axis, to obtain a lithium battery power output reference system and a lithium battery temperature change reference system respectively;

[0014] Analyze the lithium battery power output characteristic information and the lithium battery temperature change characteristic information to determine the lithium battery output power and lithium battery temperature at different time nodes;

[0015] Based on the lithium battery output power at different time nodes, a number of lithium battery output power mapping points are configured for the lithium battery power output reference system, and the number of lithium battery output power mapping points are smoothly connected in sequence to obtain a lithium battery output power curve. Based on the lithium battery temperature at different time nodes, a number of lithium battery temperature mapping points are configured for the lithium battery temperature change reference system, and the lithium battery temperature mapping points are smoothly connected in sequence to obtain a lithium battery temperature change curve.

[0016] In some embodiments disclosed herein, a method for determining a power output accumulation characteristic of a characteristic model group at an internal resistance detection node includes:

[0017] Scan and analyze the section before each internal resistance time node of the lithium battery output power curve to locate each output power rising curve section, output power stable curve section, and output power falling curve section;

[0018] Parameters are defined for each output power rising curve segment, output power steady curve segment, and output power falling curve segment respectively to obtain several power rising curve segment parameter groups, power steady curve segment parameter groups, and power falling curve segment parameter groups. The power rising curve segment parameter groups, power steady curve segment parameter groups, and power falling curve segment parameter groups corresponding to the same lithium battery output power curve are integrated to obtain a reference comprehensive output power curve parameter group.

[0019] In some embodiments disclosed herein, a method for determining a temperature change accumulation characteristic of a feature model group at an internal resistance detection node includes:

[0020] Scan and analyze the section before each internal resistance time node of the lithium battery temperature change curve to locate each temperature change rising curve segment, temperature change stable curve segment, and temperature change falling curve segment;

[0021] Parameters are defined for each temperature change rising curve segment, temperature change steady curve segment, and temperature change falling curve segment respectively, to obtain several temperature change rising curve segment parameter groups, temperature change steady curve segment parameter groups, and power falling curve segment parameter groups. The power rising curve segment parameter group, steady curve segment parameter group, and temperature change falling curve segment parameter group corresponding to the same lithium battery output power curve are integrated to obtain a reference comprehensive temperature change curve parameter group.

[0022] In some embodiments disclosed herein, the method for determining the power output accumulation characteristic and the temperature change accumulation characteristic further includes:

[0023] For the reference integrated output power curve parameter group and the reference integrated temperature change curve parameter group, a curve rising trend array a[a1, a2, a3, ..., an] is established, wherein a1 is the first preset average rising curvature, a2 is the second preset average rising curvature, a3 is the third preset average rising curvature, an is the nth preset average rising curvature, and a1<a2<a3<...<an is established. A curve steady trend array b[b1, b2, b3, ..., bn] is also established, wherein b1 is the first preset average rising curvature. b2 is the second preset average curve longitudinal value, b3 is the third preset average curve longitudinal value, bn is the nth preset average curve longitudinal value, and b1<b2<b3<...<bn. A curve downward trend array c[c1, c2, c3, ..., cn] is also established, where c1 is the first preset average downward curvature, c2 is the second preset average downward curvature, c3 is the third preset average downward curvature, cn is the nth preset average downward curvature, and c1<c2<c3<...<cn;

[0024] Determine an average rising curvature a0 and a first duration t1 of each rising curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group;

[0025] If a0<a1, the preset first unit time lithium battery loss parameter A1 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment;

[0026] If a1≤a0<a2, then the preset first unit time lithium battery loss parameter A2 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment;

[0027] If a2≤a0<a3, then select the preset first unit time lithium battery loss parameter A3 and multiply it by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; ...;

[0029] If an-1≤a0<an, then the preset first unit time lithium battery loss parameter An is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment;

[0030] Calculate the sum of the lithium battery loss parameters X1 corresponding to all rising curve segments, and record it as the total loss parameter of the first lithium battery;

[0031] Determine an average curve longitudinal value b0 and a first duration t2 of each stable curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group;

[0032] If b0<b1, then the preset second unit time lithium battery loss parameter B1 is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment;

[0033] If b1≤b0<b2, then select the preset second unit time lithium battery loss parameter B2 and multiply it by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment;

[0034] If b2≤b0<b3, then select the preset second unit time lithium battery loss parameter B3 and multiply it by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment; ...;

[0036] If bn-1≤b0<bn, then the preset second unit time lithium battery loss parameter Bn is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment;

[0037] Calculate the sum of the lithium battery loss parameters X2 corresponding to all stable curve segments, and record it as the total loss parameter of the second lithium battery;

[0038] Determine an average descending curvature c0 and a third duration t3 of each descending curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group;

[0039] If c0<c1, then the preset third unit time lithium battery loss parameter C1 is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment;

[0040] If c1≤c0<c2, then select the preset third unit time lithium battery loss parameter C2 and multiply it by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment;

[0041] If c2≤c0<c3, then select the preset third unit time lithium battery loss parameter C3 and multiply it by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment; ...;

[0043] If cn-1≤c0<cn, then the preset third unit time lithium battery loss parameter Cn is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment;

[0044] Calculate the sum of the lithium battery loss parameters X3 corresponding to all the descending curve segments, and record it as the total loss parameter of the third lithium battery;

[0045] The cumulative sum of the total loss parameter of the first lithium battery, the total loss parameter of the second lithium battery, and the total loss parameter of the third lithium battery is calculated, and the cumulative sum is identified as the power output accumulation characteristic or the temperature change accumulation characteristic.

[0046] In some embodiments disclosed herein, a method for analyzing real-time accumulated features using the accumulated features-battery health parameter group includes:

[0047] Analyze the real-time accumulation characteristics of the lithium battery to determine the real-time comprehensive output power curve parameter group and the real-time comprehensive temperature change curve parameter group;

[0048] Respectively determining the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time comprehensive output power curve parameter group and the real-time comprehensive temperature change curve parameter group, and calculating the corresponding comprehensive lithium battery total loss parameter;

[0049] Using the comprehensive lithium battery total loss parameter as the search condition, a first screening is performed in the accumulated feature~battery health parameter group to obtain the accumulated feature~battery health parameter subgroup. Using the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time comprehensive temperature change curve parameter group and the real-time comprehensive temperature change curve parameter group respectively as the search conditions, the battery health parameter is determined in the accumulated feature~battery health parameter subgroup.

[0050] In some embodiments disclosed herein, the lithium battery health status monitoring method further includes:

[0051] Based on the actual application scenario needs of lithium batteries, the power output of lithium batteries is limited and controlled, and the power output characteristic information of the lithium batteries after limited control is collected.

[0052] In some embodiments disclosed herein, a method for limiting and controlling the power output of a lithium battery includes:

[0053] Identify the electrical equipment used by the lithium battery and determine the power consumption characteristics of the electrical equipment for several application scenarios;

[0054] Based on the power consumption characteristics of several electrical devices, the power output of the lithium battery is limited and controlled.

[0055] Some embodiments disclosed in the present invention further include a lithium battery health status monitoring system, including:

[0056] The first module is used to collect lithium battery power output characteristic information, and perform characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model. When collecting the lithium battery power output characteristic information, the lithium battery temperature change characteristic information is simultaneously collected, and characteristic analysis is performed on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model. The lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by corresponding internal characteristic factors to obtain a characteristic model group.

[0057] The second module is used to establish a standard timeline for each feature model group and randomly set a number of internal resistance detection nodes on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static. When the temperature of the test lithium battery reaches the preset standard temperature, the test lithium battery is tested for internal resistance to obtain the test internal resistance and the test remaining power of the test lithium battery. The test remaining power and the test internal resistance are correlated to obtain a test power and internal resistance parameter group;

[0058] The third module is used to compare the test power and internal resistance parameter group with a preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and determining the battery health of the test battery at the internal resistance detection node based on the internal resistance difference;

[0059] The fourth module is used to determine the power output accumulation characteristics and temperature change accumulation characteristics of the feature model group at the internal resistance detection node, and establish the accumulation characteristics ~ battery health parameter group;

[0060] The fifth module is used to analyze the real-time accumulated characteristics using the accumulated characteristics~battery health parameter group when monitoring the health status of the lithium battery in real time, and determine the real-time health status of the lithium battery.

[0061] The present invention discloses a lithium battery health status monitoring method and system, which relates to the technical field of lithium battery status monitoring. Specifically, the invention discloses collecting the power output and temperature change characteristic information of the lithium battery and establishing a corresponding characteristic model; establishing a standard timeline for each characteristic model group, and setting an internal resistance detection node on it, performing internal resistance and remaining power detection on the test lithium battery, and forming a test power and internal resistance parameter group; by comparing these parameter groups with a preset standard parameter table, the health of the battery at the internal resistance detection node is determined; a parameter group between the accumulated characteristics and the battery health is also established for real-time monitoring of the health status of the lithium battery. Finally, the real-time accumulated characteristics are analyzed using this parameter group, thereby accurately determining the real-time health status of the lithium battery; the above technical solution of the present invention realizes the analysis and judgment of the health status of the lithium battery, and provides a guarantee for ensuring the normal operation of the lithium battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a method step diagram of a lithium battery health status monitoring method disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0064] The purpose of this invention is to provide a method and system for monitoring and analyzing the health status of lithium batteries.

[0065] In order to achieve the above object, the present invention adopts the following technical solutions:

[0066] See Figure 1 , a lithium battery health status monitoring method and system, comprising:

[0067] Establishing a lithium battery health test experiment:

[0068] Step S100, collecting lithium battery power output characteristic information, and performing characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model. When collecting the lithium battery power output characteristic information, simultaneously collect the lithium battery temperature change characteristic information, and perform characteristic analysis on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model. The lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by corresponding internal characteristic factors to obtain a characteristic model group.

[0069] Collecting lithium-ion battery power output and temperature variation characteristics is fundamental to assessing battery health. Power output characteristics reflect the battery's discharge capacity under different operating conditions, while temperature variation characteristics reveal the battery's thermal behavior during operation. By deeply analyzing these characteristics, we can build models for lithium-ion battery power output and temperature variation. These models describe the battery's discharge and thermal characteristics, respectively, providing foundational data for subsequent health assessment. Correlating the internal characteristic factors of these two models creates a more comprehensive set of characteristic models, providing strong support for comprehensive battery health assessment.

[0070] In some embodiments disclosed herein, a method for constructing a lithium battery power output characteristic model and a lithium battery temperature change characteristic model includes:

[0071] Step S101 , establishing a time horizontal axis, and establishing a power output vertical axis or a temperature change vertical axis in a direction perpendicular to the time horizontal axis, to obtain a lithium battery power output reference system and a lithium battery temperature change reference system respectively.

[0072] Step S102 : Analyze the lithium battery power output characteristic information and the lithium battery temperature change characteristic information to determine the lithium battery output power and lithium battery temperature at different time points.

[0073] In step S103, based on the output power of the lithium battery at different time nodes, a plurality of lithium battery output power mapping points are configured for the lithium battery power output reference system, and the plurality of lithium battery output power mapping points are sequentially and smoothly connected to obtain a lithium battery output power curve. Based on the lithium battery temperature at different time nodes, a plurality of lithium battery temperature mapping points are configured for the lithium battery temperature change reference system, and the lithium battery temperature mapping points are sequentially and smoothly connected to obtain a lithium battery temperature change curve.

[0074] In some embodiments disclosed herein, the lithium battery health status monitoring method further includes:

[0075] Step S1000 : Based on the actual application scenario requirements of the lithium battery, the power output of the lithium battery is limited and controlled, and characteristic information of the power output of the lithium battery after the limited control is collected.

[0076] In some embodiments disclosed herein, a method for limiting and controlling the power output of a lithium battery includes:

[0077] Step S1010 , determining an electrical device to which the lithium battery is applied, and determining power consumption characteristic information of several application scenarios of the electrical device.

[0078] Step S1020: Based on the power consumption characteristic information of the plurality of electrical devices, the power output of the lithium battery is limited and controlled.

[0079] In step S200, a standard timeline is established for each feature model group, and several internal resistance detection nodes are randomly set on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static use. When the temperature of the test lithium battery reaches the preset standard temperature, the internal resistance of the test lithium battery is detected to obtain the test internal resistance, and the test remaining power of the test lithium battery is obtained. The test remaining power and the test internal resistance are associated to obtain a test power and internal resistance parameter group.

[0080] To accurately assess the health of lithium-ion batteries, we need to establish a standard timeline and set internal resistance test nodes on it. This is because the internal resistance of a battery is a key parameter reflecting its health. By stabilizing the lithium-ion battery under a standard environment, we ensure that the battery temperature reaches the preset standard temperature, thereby eliminating the impact of temperature on the internal resistance measurement. By performing an internal resistance test on the test lithium-ion battery, we can obtain the test internal resistance and the remaining charge of the test lithium-ion battery at the same time. By correlating the test remaining charge and the test internal resistance, we can form a test charge and internal resistance parameter group, providing basic data for subsequent health status comparisons.

[0081] In step S300, the test power and internal resistance parameter group are compared with the preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and based on the internal resistance difference, determining the battery health of the test battery at the internal resistance detection node.

[0082] Comparing the test power and internal resistance parameter set with a preset standard power and internal resistance parameter table is a key step in assessing the health of a lithium battery. By limiting the test power to the standard power, we can eliminate the impact of power on the internal resistance difference, thereby more accurately determining the difference between the test internal resistance and the standard internal resistance. Based on the internal resistance difference, we can assess the health of the test battery at the internal resistance detection point. If the internal resistance difference is large, it indicates that the battery is in poor health and may need to be replaced or repaired.

[0083] Step S400 : determining the power output accumulation characteristics and the temperature change accumulation characteristics of the characteristic model group at the internal resistance detection node, and establishing an accumulation characteristic-battery health parameter group.

[0084] When determining the health status of a lithium battery, in addition to direct parameters such as internal resistance, it is also necessary to consider the accumulated characteristics of power output and temperature variation. This is because the battery's health status is a dynamic process, and its power output and temperature variation characteristics will change over time. By determining the accumulated characteristics of power output and temperature variation of the feature model group at the internal resistance detection node, we can establish a parameter set that links the accumulated characteristics with the battery's health status. This parameter set describes the power output and temperature variation behavior of the battery at different health states, providing an important basis for real-time monitoring of the battery's health status.

[0085] In some embodiments disclosed herein, a method for determining a power output accumulation characteristic of a characteristic model group at an internal resistance detection node includes:

[0086] Step S401 , scanning and analyzing the section before each internal resistance time node of the lithium battery output power curve, and locating each output power rising curve segment, output power stable curve segment, and output power falling curve segment.

[0087] In step S402, each output power rising curve segment, output power steady curve segment and output power falling curve segment are parameterized and defined respectively to obtain a plurality of power rising curve segment parameter groups, power steady curve segment parameter groups and power falling curve segment parameter groups, and the power rising curve segment parameter groups, power steady curve segment parameter groups and power falling curve segment parameter groups corresponding to the same lithium battery output power curve are integrated to obtain a reference comprehensive output power curve parameter group.

[0088] In some embodiments disclosed herein, a method for determining a temperature change accumulation characteristic of a feature model group at an internal resistance detection node includes:

[0089] Step S403 , scanning and analyzing the section before each internal resistance time node of the lithium battery temperature change curve, and locating each temperature change rising curve segment, temperature change stable curve segment, and temperature change falling curve segment.

[0090] In step S404, each temperature change rising curve segment, temperature change steady curve segment and temperature change falling curve segment are parameterized and defined respectively to obtain several temperature change rising curve segment parameter groups, temperature change steady curve segment parameter groups and power falling curve segment parameter groups, and the power rising curve segment parameter group, steady curve segment parameter group and temperature change falling curve segment parameter group corresponding to the same lithium battery output power curve are integrated to obtain a reference comprehensive temperature change curve parameter group.

[0091] In some embodiments disclosed herein, the method for determining the power output accumulation characteristic and the temperature change accumulation characteristic further includes:

[0092] Step S405: For the reference integrated output power curve parameter group and the reference integrated temperature change curve parameter group, a curve rising trend array a[a1, a2, a3, ..., an] is established, wherein a1 is the first preset average rising curvature, a2 is the second preset average rising curvature, a3 is the third preset average rising curvature, an is the nth preset average rising curvature, and a1<a2<a3<...<an is established. A curve steady trend array b[b1, b2, b3, ..., bn] is also established, wherein b1 is the first The longitudinal value of the preset average curve, b2 is the second longitudinal value of the preset average curve, b3 is the third longitudinal value of the preset average curve, bn is the nth preset average curve longitudinal value, and b1<b2<b3<...<bn, and a curve downward trend array c[c1, c2, c3, ..., cn] is also established, wherein c1 is the first preset average downward curvature, c2 is the second preset average downward curvature, c3 is the third preset average downward curvature, cn is the nth preset average downward curvature, and c1<c2<c3<...<cn.

[0093] Step S406 , determining the average rising curvature a0 and the first duration t1 of each rising curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group.

[0094] If a0<a1, then the preset first unit time lithium battery loss parameter A1 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment.

[0095] If a1≤a0<a2, then the preset first unit time lithium battery loss parameter A2 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment.

[0096] If a2≤a0<a3, then the preset first unit time lithium battery loss parameter A3 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment. ...

[0098] If an-1≤a0<an, then the preset first unit time lithium battery loss parameter An is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment.

[0099] Calculate the sum of the lithium battery loss parameters X1 corresponding to all rising curve segments, and record it as the first lithium battery total loss parameter.

[0100] Step S407 : determining the average curve longitudinal value b0 and the first duration t2 of each stable curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group.

[0101] If b0<b1, the preset second unit time lithium battery loss parameter B1 is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment.

[0102] If b1≤b0<b2, then the preset second unit time lithium battery loss parameter B2 is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment.

[0103] If b2≤b0<b3, then the preset second unit time lithium battery loss parameter B3 is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment. ...

[0105] If bn-1≤b0<bn, then the preset second unit time lithium battery loss parameter Bn is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment.

[0106] Calculate the sum of the lithium battery loss parameters X2 corresponding to all stable curve segments, and record it as the total loss parameter of the second lithium battery.

[0107] Step S408 : determining the average descending curvature c0 and the third duration t3 of each descending curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group.

[0108] If c0<c1, the preset third unit time lithium battery loss parameter C1 is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment.

[0109] If c1≤c0<c2, then the preset third unit time lithium battery loss parameter C2 is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment.

[0110] If c2≤c0<c3, then the preset third unit time lithium battery loss parameter C3 is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment. ...

[0112] If cn-1≤c0<cn, then the preset third unit time lithium battery loss parameter Cn is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment.

[0113] Calculate the sum of the lithium battery loss parameters X3 corresponding to all descending curve segments, and record it as the total loss parameter of the third lithium battery.

[0114] Step S409: Calculate the cumulative sum of the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter, and identify the cumulative sum as a power output accumulation characteristic or a temperature change accumulation characteristic.

[0115] Step S500 , when real-time monitoring of the health status of the lithium battery is performed, the real-time accumulated characteristics are analyzed using the accumulated characteristics-battery health parameter group to determine the real-time health status of the lithium battery.

[0116] Real-time monitoring of lithium-ion battery health is crucial for ensuring proper equipment operation and extending battery life. By analyzing real-time accumulated features using the battery health parameter set, we can accurately determine the real-time health of lithium-ion batteries. By monitoring the battery's power output and temperature variation in real time and comparing them with the parameter set, we can promptly identify changes in battery health and take appropriate maintenance measures. This helps prevent equipment failures or safety issues caused by deteriorating battery health.

[0117] In some embodiments disclosed herein, a method for analyzing real-time accumulated features using the accumulated features-battery health parameter group includes:

[0118] Step S501, analyzing the real-time accumulated characteristics of the lithium battery to determine a real-time integrated output power curve parameter group and a real-time integrated temperature change curve parameter group;

[0119] Step S502, respectively determining the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time integrated output power curve parameter group and the real-time integrated temperature change curve parameter group, and calculating the corresponding integrated lithium battery total loss parameter;

[0120] In step S503, the comprehensive lithium battery total loss parameter is used as a search condition, and a first screening is performed in the accumulated feature~battery health parameter group to obtain the accumulated feature~battery health parameter subgroup. The first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time comprehensive temperature change curve parameter group and the real-time comprehensive temperature change curve parameter group are used as search conditions to determine the battery health parameter in the accumulated feature~battery health parameter subgroup.

[0121] Some embodiments disclosed in the present invention further include a lithium battery health status monitoring system, including:

[0122] The first module is used to collect lithium battery power output characteristic information, and perform characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model. When collecting the lithium battery power output characteristic information, the lithium battery temperature change characteristic information is simultaneously collected, and characteristic analysis is performed on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model. The lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by corresponding internal characteristic factors to obtain a characteristic model group.

[0123] The second module is used to establish a standard timeline for each feature model group and randomly set a number of internal resistance detection nodes on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static. When the temperature of the test lithium battery reaches the preset standard temperature, the test lithium battery is tested for internal resistance to obtain the test internal resistance and the test remaining power of the test lithium battery. The test remaining power and the test internal resistance are correlated to obtain a test power and internal resistance parameter group;

[0124] The third module is used to compare the test power and internal resistance parameter group with a preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and determining the battery health of the test battery at the internal resistance detection node based on the internal resistance difference;

[0125] The fourth module is used to determine the power output accumulation characteristics and temperature change accumulation characteristics of the feature model group at the internal resistance detection node, and establish the accumulation characteristics ~ battery health parameter group;

[0126] The fifth module is used to analyze the real-time accumulated characteristics using the accumulated characteristics~battery health parameter group when monitoring the health status of the lithium battery in real time, and determine the real-time health status of the lithium battery.

[0127] The present invention discloses a lithium battery health status monitoring method and system, which relates to the technical field of lithium battery status monitoring. Specifically, the invention discloses collecting the power output and temperature change characteristic information of the lithium battery and establishing a corresponding characteristic model; establishing a standard timeline for each characteristic model group, and setting an internal resistance detection node on it, performing internal resistance and remaining power detection on the test lithium battery, and forming a test power and internal resistance parameter group; by comparing these parameter groups with a preset standard parameter table, the health of the battery at the internal resistance detection node is determined; a parameter group between the accumulated characteristics and the battery health is also established for real-time monitoring of the health status of the lithium battery. Finally, the real-time accumulated characteristics are analyzed using this parameter group, thereby accurately determining the real-time health status of the lithium battery; the above technical solution of the present invention realizes the analysis and judgment of the health status of the lithium battery, and provides a guarantee for ensuring the normal operation of the lithium battery.

[0128] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for monitoring the health status of a lithium battery, characterized in that: include: Establishing a lithium battery health test experiment: Collecting lithium battery power output characteristic information, and performing characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model; when collecting the lithium battery power output characteristic information, simultaneously collecting lithium battery temperature change characteristic information, and performing characteristic analysis on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model; and correlating the lithium battery power output characteristic model and the lithium battery temperature change characteristic model with internal characteristic factors to obtain a characteristic model group; A standard timeline is established for each feature model group, and a number of internal resistance detection nodes are randomly set on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static use. When the temperature of the test lithium battery reaches the preset standard temperature, the test lithium battery is internally resisted to obtain the test internal resistance, and the test remaining power of the test lithium battery is obtained. The test remaining power and the test internal resistance are correlated to obtain a test power and internal resistance parameter group; Comparing the test power and internal resistance parameter group with a preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and determining the battery health of the test battery at the internal resistance detection node based on the internal resistance difference; Determine the power output accumulation characteristics and temperature change accumulation characteristics of the feature model group at the internal resistance detection node, and establish the accumulation characteristics ~ battery health parameter group; When monitoring the health status of lithium batteries in real time, the accumulated characteristics and battery health parameter group are used to analyze the real-time accumulated characteristics to determine the real-time health status of the lithium battery. The method for constructing a lithium battery power output characteristic model and a lithium battery temperature change characteristic model includes: Establish a time horizontal axis, and establish a power output vertical axis or a temperature change vertical axis in a direction perpendicular to the time horizontal axis, to obtain a lithium battery power output reference system and a lithium battery temperature change reference system respectively; Analyze the lithium battery power output characteristic information and the lithium battery temperature change characteristic information to determine the lithium battery output power and lithium battery temperature at different time nodes; Based on the output power of the lithium battery at different time nodes, a number of lithium battery output power mapping points are configured for the lithium battery power output reference system, and the number of lithium battery output power mapping points are sequentially and smoothly connected to obtain a lithium battery output power curve. Based on the lithium battery temperature at different time nodes, a number of lithium battery temperature mapping points are configured for the lithium battery temperature change reference system, and the lithium battery temperature mapping points are sequentially and smoothly connected to obtain a lithium battery temperature change curve. The method for determining the power output accumulation characteristic of the characteristic model group at the internal resistance detection node includes: Scan and analyze the section before each internal resistance time node of the lithium battery output power curve to locate each output power rising curve section, output power stable curve section, and output power falling curve section; Parameterizing each output power rising curve segment, output power steady curve segment, and output power falling curve segment to obtain a plurality of power rising curve segment parameter groups, power steady curve segment parameter groups, and power falling curve segment parameter groups, and integrating the power rising curve segment parameter groups, power steady curve segment parameter groups, and power falling curve segment parameter groups corresponding to the same lithium battery output power curve to obtain a reference comprehensive output power curve parameter group; The method for determining the temperature change accumulation characteristics of the characteristic model group at the internal resistance detection node includes: Scan and analyze the section before each internal resistance time node of the lithium battery temperature change curve to locate each temperature change rising curve segment, temperature change stable curve segment, and temperature change falling curve segment; Parameterizing each temperature change rising curve segment, temperature change steady curve segment, and temperature change falling curve segment to obtain several temperature change rising curve segment parameter groups, temperature change steady curve segment parameter groups, and power falling curve segment parameter groups, and integrating the power rising curve segment parameter group, steady curve segment parameter group, and temperature change falling curve segment parameter group corresponding to the same lithium battery output power curve to obtain a reference comprehensive temperature change curve parameter group; The method for determining the power output accumulation characteristic and the temperature change accumulation characteristic further includes: For the reference integrated output power curve parameter group and the reference integrated temperature change curve parameter group, a curve rising trend array a[a1, a2, a3, ..., an] is established, wherein a1 is the first preset average rising curvature, a2 is the second preset average rising curvature, a3 is the third preset average rising curvature, an is the nth preset average rising curvature, and a1<a2<a3<...<an is established. A curve steady trend array b[b1, b2, b3, ..., bn] is also established, wherein b1 is the first preset average rising curvature. b2 is the second preset average curve longitudinal value, b3 is the third preset average curve longitudinal value, bn is the nth preset average curve longitudinal value, and b1<b2<b3<...<bn. A curve downward trend array c[c1, c2, c3, ..., cn] is also established, where c1 is the first preset average downward curvature, c2 is the second preset average downward curvature, c3 is the third preset average downward curvature, cn is the nth preset average downward curvature, and c1<c2<c3<...<cn; Determine an average rising curvature a0 and a first duration t1 of each rising curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group; If a0<a1, the preset first unit time lithium battery loss parameter A1 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; If a1≤a0<a2, then the preset first unit time lithium battery loss parameter A2 is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; If a2≤a0<a3, then select the preset first unit time lithium battery loss parameter A3 and multiply it by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; ...； If an-1≤a0<an, then the preset first unit time lithium battery loss parameter An is selected and multiplied by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; Calculate the sum of the lithium battery loss parameters X1 corresponding to all rising curve segments, and record it as the total loss parameter of the first lithium battery; Determine an average curve longitudinal value b0 and a first duration t2 of each stable curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group; If b0<b1, then the preset second unit time lithium battery loss parameter B1 is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment; If b1≤b0<b2, then select the preset second unit time lithium battery loss parameter B2 and multiply it by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment; If b2≤b0<b3, then select the preset second unit time lithium battery loss parameter B3 and multiply it by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment; ...； If bn-1≤b0<bn, then the preset second unit time lithium battery loss parameter Bn is selected and multiplied by the duration t2 to obtain the lithium battery loss parameter X2 corresponding to the stable curve segment; Calculate the sum of the lithium battery loss parameters X2 corresponding to all stable curve segments, and record it as the total loss parameter of the second lithium battery; Determine an average descending curvature c0 and a third duration t3 of each descending curve segment in the reference integrated output power curve parameter group or the reference integrated temperature change curve parameter group; If c0<c1, then the preset third unit time lithium battery loss parameter C1 is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment; If c1≤c0<c2, then select the preset third unit time lithium battery loss parameter C2 and multiply it by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment; If c2≤c0<c3, then select the preset third unit time lithium battery loss parameter C3 and multiply it by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment; ...； If cn-1≤c0<cn, then the preset third unit time lithium battery loss parameter Cn is selected and multiplied by the duration t3 to obtain the lithium battery loss parameter X3 corresponding to the descending curve segment; Calculate the sum of the lithium battery loss parameters X3 corresponding to all the descending curve segments, and record it as the total loss parameter of the third lithium battery; The cumulative sum of the total loss parameter of the first lithium battery, the total loss parameter of the second lithium battery, and the total loss parameter of the third lithium battery is calculated, and the cumulative sum is identified as the power output accumulation characteristic or the temperature change accumulation characteristic.

2. A lithium battery health status monitoring method according to claim 1, characterized in that: Methods for analyzing real-time accumulated features using the accumulated features-battery health parameter group include: Analyze the real-time accumulation characteristics of the lithium battery to determine the real-time comprehensive output power curve parameter group and the real-time comprehensive temperature change curve parameter group; Respectively determining the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time comprehensive output power curve parameter group and the real-time comprehensive temperature change curve parameter group, and calculating the corresponding comprehensive lithium battery total loss parameter; Using the comprehensive lithium battery total loss parameter as the search condition, a first screening is performed in the accumulated feature~battery health parameter group to obtain the accumulated feature~battery health parameter subgroup. Using the first lithium battery total loss parameter, the second lithium battery total loss parameter, and the third lithium battery total loss parameter corresponding to the real-time integrated output power curve parameter group and the real-time integrated temperature change curve parameter group respectively as the search conditions, the battery health parameter is determined in the accumulated feature~battery health parameter subgroup.

3. A lithium battery health status monitoring method according to claim 1, characterized in that: Also includes: Based on the actual application scenario needs of lithium batteries, the power output of lithium batteries is limited and controlled, and the power output characteristic information of the lithium batteries after limited control is collected.

4. A lithium battery health status monitoring method according to claim 3, characterized in that: Methods for limiting and controlling the power output of lithium batteries include: Identify the electrical equipment used by the lithium battery and determine the power consumption characteristics of the electrical equipment for several application scenarios; Based on the power consumption characteristics of several electrical devices, the power output of the lithium battery is limited and controlled.

5. A lithium battery health status monitoring system, characterized in that: A method for monitoring the health of a lithium battery according to any one of claims 1 to 4, comprising: The first module is used to collect lithium battery power output characteristic information, and perform characteristic analysis on each lithium battery power output characteristic information to obtain a lithium battery power output characteristic model. When collecting the lithium battery power output characteristic information, the lithium battery temperature change characteristic information is simultaneously collected, and characteristic analysis is performed on each lithium battery temperature change characteristic information to obtain a lithium battery temperature change characteristic model. The lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by corresponding internal characteristic factors to obtain a characteristic model group. The second module is used to establish a standard timeline for each feature model group and randomly set a number of internal resistance detection nodes on the standard timeline. At the internal resistance detection node, the test lithium battery is placed in a preset standard environment for static. When the temperature of the test lithium battery reaches the preset standard temperature, the test lithium battery is tested for internal resistance to obtain the test internal resistance and the test remaining power of the test lithium battery. The test remaining power and the test internal resistance are correlated to obtain a test power and internal resistance parameter group; The third module is used to compare the test power and internal resistance parameter group with a preset standard power and internal resistance parameter table. The comparison method includes limiting the test power and the standard power to be equal, determining the internal resistance difference between the test internal resistance and the standard internal resistance, and determining the battery health of the test battery at the internal resistance detection node based on the internal resistance difference; The fourth module is used to determine the power output accumulation characteristics and temperature change accumulation characteristics of the feature model group at the internal resistance detection node, and establish the accumulation characteristics ~ battery health parameter group; The fifth module is used to analyze the real-time accumulated characteristics using the accumulated characteristics~battery health parameter group when monitoring the health status of the lithium battery in real time, and determine the real-time health status of the lithium battery.

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