Lithium battery health state monitoring method and system

Abstract

The invention discloses a lithium battery health state monitoring method and system, relates to the technical field of lithium battery state monitoring, and particularly discloses a method for collecting power output and temperature change characteristic information of a lithium battery and establishing a corresponding characteristic model; establishing a standard timeline for each characteristic model group, setting an internal resistance detection node on the standard timeline, and performing internal resistance and residual electric quantity detection on the tested lithium battery to form a tested electric quantity and internal resistance parameter group; comparing the parameter groups with a preset standard parameter table to determine the health degree of the battery at the internal resistance detection node; and a parameter group between the accumulation characteristics and the health degree of the battery is also established and is used for monitoring the health state of the lithium battery in real time. And finally, analyzing the real-time accumulation characteristics by using the parameter group so as to accurately determine the real-time health degree of the lithium battery. According to the technical scheme, the lithium battery health state analysis and judgment are realized, and a guarantee is provided 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 the use of lithium batteries, their performance will gradually decline with the increase of the number of charge and discharge cycles, resulting in problems such as decreased capacity and increased internal resistance. This not only affects the endurance of the equipment, but may also cause safety hazards due to the deterioration of the battery health status. Therefore, accurate and real-time monitoring of the health status of lithium batteries is of great significance to ensure the normal operation of equipment, extend battery life and improve system safety. Summary of the invention

[0003] The purpose of the present 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 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 with the lithium battery temperature change characteristic model by corresponding 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 tested 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.

[0009] Compare the test power and internal resistance parameter group 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 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 characteristic 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 in the present invention, the 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 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 temperature change reference system, and the several lithium battery output power mapping points are smoothly connected in sequence to obtain the 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 the lithium battery temperature change curve.

[0016] In some embodiments disclosed in the present invention, 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, 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.

[0019] In some embodiments disclosed in the present invention, a method for determining the temperature change accumulation characteristics of the feature model group at the 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 section, temperature change stable curve section and temperature change falling curve section;

[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 in the present invention, the method for determining the power output accumulation characteristic and the temperature change accumulation characteristic further includes:

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

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

[0026] If a1≤a0<a2, then select the preset first unit time lithium battery loss parameter A2 and multiply it 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 select the preset first unit time lithium battery loss parameter An and multiply it 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 the average curve longitudinal value b0 and the first duration t2 of each stable curve segment in the reference comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group;

[0032] If b0<b1, then select the preset second unit time lithium battery loss parameter B1 and multiply it 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 select the preset second unit time lithium battery loss parameter Bn and multiply it 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 comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group;

[0039] If c0<c1, then select the preset third unit time lithium battery loss parameter C1 and multiply it 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 select the preset third unit time lithium battery loss parameter Cn and multiply it 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 loss parameter of the second lithium battery and the loss parameter of the third lithium battery is calculated, and the cumulative sum is identified as a power output accumulation characteristic or a temperature change accumulation characteristic.

[0046] In some embodiments disclosed in the present invention, the method of analyzing the 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 determine the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter corresponding to the real-time comprehensive temperature change curve parameter group, and calculate the corresponding comprehensive lithium battery total loss parameter;

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

[0050] In some embodiments disclosed in the present invention, 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 in the present invention, the method for limiting and controlling the power output of a lithium battery includes:

[0053] Determine the electrical equipment for lithium battery application, and determine the power consumption characteristic information of several application scenarios of the electrical equipment;

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

[0055] In some embodiments disclosed in the present invention, a lithium battery health status monitoring system is also included, 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, and the lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by 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, and 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 is obtained, and the test remaining power and the test internal resistance are associated to obtain the test power and internal resistance parameter group;

[0058] The third module is used to compare the test power and internal resistance parameter group 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 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 characteristic 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 by using the accumulated characteristics-battery health parameter group when real-time monitoring of the health status of the lithium battery is performed to 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, and specifically 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, and performing internal resistance and remaining power detection on the test lithium battery to form 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, which is used to monitor the health status of the lithium battery in real time. Finally, the real-time accumulated characteristics are analyzed using this parameter group, so as to accurately determine the real-time health status of the lithium battery; the above technical scheme 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 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 described clearly and completely 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 the present 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 also 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, and associate the lithium battery power output characteristic model with the lithium battery temperature change characteristic model by corresponding internal characteristic factors to obtain a characteristic model group.

[0069] Collecting the power output and temperature change characteristic information of lithium batteries is the basis for evaluating the health status of batteries. The power output characteristics reflect the discharge capacity of the battery under different working conditions, while the temperature change characteristics reveal the thermal behavior of the battery during operation. Through in-depth analysis of these characteristic information, we can establish the power output and temperature change characteristic models of lithium batteries. These two models describe the discharge characteristics and thermal characteristics of the battery respectively, providing basic data for subsequent health status assessment. Correlating the internal characteristic factors of these two models can form a more comprehensive characteristic model group, providing strong support for the comprehensive assessment of the battery health status.

[0070] In some embodiments disclosed in the present invention, the 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] Step S103, 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 temperature change 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.

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

[0075] Step S1000: based on the actual application scenario 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 in the present invention, the method for limiting and controlling the power output of a lithium battery includes:

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

[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] Step S200, 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, place the test lithium battery in a preset standard environment for static, wait until the test lithium battery temperature reaches the preset standard temperature, perform internal resistance detection on the test lithium battery to obtain the test internal resistance, and obtain the test remaining power of the test lithium battery, associate the test remaining power with the test internal resistance, and obtain the test power and internal resistance parameter group.

[0080] In order to accurately evaluate the health status of lithium batteries, we need to establish a standard timeline and set internal resistance detection nodes on it. This is because the internal resistance of the battery is one of the important parameters that reflect its health status. By leaving the lithium battery stationary under a standard environment, we can ensure that the battery temperature reaches the preset standard temperature, thereby eliminating the influence of temperature on the internal resistance measurement. By performing internal resistance detection on the test lithium battery, we can obtain the test internal resistance and the remaining power of the test lithium battery at the same time. By associating the test remaining power with the test internal resistance, we can form a test power and internal resistance parameter group, which provides basic data for subsequent health status comparison.

[0081] Step S300, compare the test power, internal resistance parameter group and the preset standard power, 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 group with the preset standard power and internal resistance parameter table is a key step in evaluating the health status of lithium batteries. By limiting the test power and standard power to be equal, 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 evaluate the health of the test battery at the internal resistance detection node. If the internal resistance difference is large, it means 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 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 state 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 change. This is because the health state of a battery is a dynamically changing process, and its power output and temperature change characteristics will change over time. By determining the accumulated characteristics of power output and temperature change of the feature model group at the internal resistance detection node, we can establish a parameter group between the accumulated characteristics and the battery health. This parameter group describes the power output and temperature change behavior of the battery in different health states, providing an important basis for real-time monitoring of the battery health state.

[0085] In some embodiments disclosed in the present invention, 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 section, output power stable curve section and output power falling curve section.

[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 in the present invention, a method for determining the temperature change accumulation characteristics of the feature model group at the 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] Step S404, respectively define parameters for each temperature change rising curve segment, temperature change steady curve segment and temperature change falling curve segment, to obtain a plurality of temperature change rising curve segment parameter groups, temperature change steady curve segment parameter groups and power falling curve segment parameter groups, and integrate 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.

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

[0092] Step S405, for the reference comprehensive output power curve parameter group and the reference comprehensive 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, and a curve stable trend array b[b1, b2, b3, ..., bn] is also established, wherein b1 is the first The preset average curve longitudinal value, 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, 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 comprehensive output power curve parameter group or the reference comprehensive 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.

[0097] ....

[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 comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group.

[0101] 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.

[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.

[0104] ....

[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 comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group.

[0108] 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.

[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.

[0111] ....

[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 the descending curve segments, and record it as the total loss parameter of the third lithium battery.

[0114] Step S409, calculating the cumulative sum of the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter, and identifying 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 the health status of lithium batteries is of great significance to ensure the normal operation of equipment and extend the battery life. By analyzing the real-time accumulated characteristics using the accumulated characteristics ~ battery health parameter group, we can accurately determine the real-time health of lithium batteries. By monitoring the power output and temperature change characteristics of the battery in real time and comparing them with the parameter group, we can promptly detect changes in the battery health status and take corresponding maintenance measures. This helps to avoid equipment failures or safety issues caused by the deterioration of the battery health status.

[0117] In some embodiments disclosed in the present invention, the method of analyzing the 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 comprehensive output power curve parameter group and a real-time comprehensive temperature change curve parameter group;

[0119] Step S502, respectively determining the real-time comprehensive temperature change curve parameter group and the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter corresponding to each of the real-time comprehensive temperature change curve parameter groups, and calculating the corresponding comprehensive lithium battery total loss parameters;

[0120] Step S503, using the comprehensive lithium battery comprehensive loss parameter as the search condition, performing the first screening in the accumulation feature-battery health parameter group, obtaining the accumulation feature-battery health parameter subgroup, using the real-time comprehensive temperature change curve parameter group and the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter corresponding to the real-time comprehensive temperature change curve parameter group respectively as the search condition, and determining the battery health parameter in the accumulation feature-battery health parameter subgroup.

[0121] In some embodiments disclosed in the present invention, a lithium battery health status monitoring system is also included, 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, and the lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by 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, and 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 is obtained, and the test remaining power and the test internal resistance are associated to obtain the test power and internal resistance parameter group;

[0124] The third module is used to compare the test power and internal resistance parameter group 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 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 characteristic 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 by using the accumulated characteristics-battery health parameter group when real-time monitoring of the health status of the lithium battery is performed to 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, and specifically 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, and performing internal resistance and remaining power detection on the test lithium battery to form 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, which is used to monitor the health status of the lithium battery in real time. Finally, the real-time accumulated characteristics are analyzed using this parameter group, so as to accurately determine the real-time health status of the lithium battery; the above technical scheme 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 implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A lithium battery health status monitoring method and system, 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 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 with the lithium battery temperature change characteristic model by corresponding 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 tested 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. Compare the test power and internal resistance parameter group 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 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 characteristic model group at the internal resistance detection node, and establish the accumulation characteristics-battery health parameter group; 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.

2. A lithium battery health status monitoring method according to claim 1, characterized in that: The method of 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 temperature change reference system, and the several lithium battery output power mapping points are smoothly connected in sequence to obtain the 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 the lithium battery temperature change curve.

3. A lithium battery health status monitoring method according to claim 2, characterized in that: 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; 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, 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.

4. A lithium battery health status monitoring method according to claim 3, characterized in that: 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 section, temperature change stable curve section and temperature change falling curve section; 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.

5. A lithium battery health status monitoring method according to claim 4, characterized in that: The method for determining the power output accumulation characteristic and the temperature change accumulation characteristic also includes: A curve rising trend array a[a1, a2, a3, ..., an] is established for the reference comprehensive output power curve parameter group and the reference comprehensive temperature change curve parameter group, 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, and a curve stable trend array b[b1, b2, b3, ..., bn] is also established, wherein b1 is the first preset average rising curvature, b1 is the longitudinal value of the second preset average curve, b2 is the longitudinal value of the second preset average curve, b3 is the longitudinal value of the third preset average curve, bn is the longitudinal value of the nth preset average curve, and b1<b2<b3<...<bn, and a curve descending trend array c[c1, c2, c3, ..., cn] is also established, wherein c1 is the first preset average descending curvature, c2 is the second preset average descending curvature, c3 is the third preset average descending curvature, cn is the nth preset average descending 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 comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group; If a0<a1, then select the preset first unit time lithium battery loss parameter A1 and multiply it by the duration t1 to obtain the lithium battery loss parameter X1 corresponding to the rising curve segment; If a1≤a0<a2, then select the preset first unit time lithium battery loss parameter A2 and multiply it 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 select the preset first unit time lithium battery loss parameter An and multiply it 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 the average curve longitudinal value b0 and the first duration t2 of each stable curve segment in the reference comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group; If b0<b1, then select the preset second unit time lithium battery loss parameter B1 and multiply it 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 select the preset second unit time lithium battery loss parameter Bn and multiply it 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 comprehensive output power curve parameter group or the reference comprehensive temperature change curve parameter group; If c0<c1, then select the preset third unit time lithium battery loss parameter C1 and multiply it 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 select the preset third unit time lithium battery loss parameter Cn and multiply it 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 loss parameter of the second lithium battery and the loss parameter of the third lithium battery is calculated, and the cumulative sum is identified as a power output accumulation characteristic or a temperature change accumulation characteristic.

6. A lithium battery health status monitoring method according to claim 4, characterized in that: The method of analyzing the real-time accumulation characteristics by using the accumulation characteristics-battery health parameter group includes: 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 determine the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter corresponding to the real-time comprehensive temperature change curve parameter group, and calculate the corresponding comprehensive lithium battery total loss parameter; Taking the comprehensive lithium battery comprehensive loss parameter as the search condition, the first screening is performed in the accumulated feature-battery health parameter group to obtain the accumulated feature-battery health parameter subgroup, and the real-time comprehensive temperature change curve parameter group and the first lithium battery total loss parameter, the second lithium battery loss parameter and the third lithium battery loss parameter corresponding to 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.

7. 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.

8. A lithium battery health status monitoring method according to claim 7, characterized in that: Methods for limiting and controlling the power output of lithium batteries include: Determine the electrical equipment for lithium battery application, and determine the power consumption characteristic information of several application scenarios of the electrical equipment; Based on the power consumption characteristic information of several electrical devices, the power output of the lithium battery is limited and controlled.

9. A lithium battery health status monitoring system, characterized in that: include: 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, and the lithium battery power output characteristic model and the lithium battery temperature change characteristic model are associated with each other by 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, and 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 is obtained, and the test remaining power and the test internal resistance are associated to obtain the test power and internal resistance parameter group; The third module is used to compare the test power and internal resistance parameter group 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 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 characteristic 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 by using the accumulated characteristics-battery health parameter group when real-time monitoring of the health status of the lithium battery is performed to determine the real-time health status of the lithium battery.

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