A lithium battery management method and device supporting mixed use of new and old PACKs

Abstract

The present invention discloses a lithium battery management method and device that supports the mixed use of new and old PACKs, and relates to the field of lithium battery management technology. The invention obtains the voltage, SOC, internal resistance and health status of each PACK in the lithium battery pack through the first acquisition module, and combines the SOC and voltage difference analysis of the performance analysis module to effectively identify the differences between battery PACKs and generate targeted balancing plans. The matching module analyzes the health status data set, evaluates the battery aging degree of each PACK, and calculates the performance matching coefficient to ensure that the new and old battery PACKs can be mixed within a reasonable range, thereby avoiding the problem of unbalanced energy transmission caused by differences in battery aging. The second acquisition module collects cable connection parameters and calculates the impedance loss ratio of the PACK, combines the data for loss evaluation, corrects the balancing plan and matching list, reduces the energy loss caused by cable impedance differences, and improves the energy efficiency of the overall battery pack.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery management, and in particular to a lithium battery management method and device that supports mixed use of new and old PACKs. Background Art

[0002] With the growing demand for lithium batteries in electric vehicles, energy storage systems and other fields, the management and optimization of lithium battery packs have become particularly important. Traditional lithium battery management systems (BMS) are mainly based on a single type of battery PACK for management, but in actual applications, due to battery aging, inconsistent performance and differences between batteries in different production batches, the use of new and old battery PACKs has become a common demand. However, traditional BMS cannot effectively cope with the challenges brought by the mixing of new and old PACKs, resulting in unstable performance of lithium battery packs and even shortening the overall life of the battery pack.

[0003] At present, traditional technologies often rely on a single battery voltage or SOC (state of charge) information for balancing management, but this method ignores the performance differences in multiple dimensions such as battery health status, internal resistance, power attenuation, etc., and cannot accurately evaluate the matching between different battery PACKs. As the battery ages, parameters such as the battery's internal resistance, power attenuation, and cycle life will change significantly. Traditional technologies often cannot reflect these changes in real time, thus affecting the overall performance and safety of the battery pack. In addition, the impedance loss problem of cable connections in battery packs is also a key factor affecting battery performance. Traditional technologies lack an effective evaluation mechanism when designing and optimizing cable connections, and cannot effectively reduce the negative impact of cable losses on battery performance. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a lithium battery management method and device that supports mixed use of new and old PACKs, so as to solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A lithium battery management method supporting mixed use of new and old PACKs, comprising the following steps:

[0006] Step 1: Use the network to connect to the battery management platform to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set;

[0007] Step 2: Based on the voltage data set, divide the single PACK area according to the number of PACKs in the lithium battery pack, and then combine with the SOC data set to analyze the SOC difference and voltage difference of each PACK, and generate a corresponding balancing plan list;

[0008] Step 3: Analyze the differences in battery aging in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list;

[0009] Step 4: Collect the cable connection parameters of each PACK in the lithium battery pack and build the PACK impedance loss ratio ; and according to the PACK impedance loss ratio Make corresponding amendments to the balanced plan list and matching list.

[0010] Preferably, the voltage data set includes: the voltage value of each PACK; the SOC data set includes: the SOC value of each PACK; the health status data set includes: the battery internal resistance value , Battery power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate .

[0011] Preferably, the battery internal resistance Calculated by the following formula: ;

[0012] in, Indicates the open circuit voltage of the battery, that is, the voltage value when the battery is not connected to a load. Indicates the voltage of the battery under load, Indicates the current of the battery under load;

[0013] The battery power decay Calculated by the following formula: ;

[0014] in, Indicates the maximum power of the battery in its new state. Indicates the maximum power of the battery in its current state;

[0015] The cycle life Calculated by the following formula: ;

[0016] In the formula, Indicates the current battery capacity. Indicates the initial capacity of the battery, Indicates the number of cycles of the battery design life;

[0017] The thermal runaway coefficient TRI Calculated by the following formula: ;

[0018] In the formula, Indicates the charging current, Indicates the maximum allowable charging current, Indicates the internal resistance of the battery, in ohms. The internal resistance of the battery increases with use, causing the battery to heat up; Indicates the maximum safe internal resistance of the battery; Indicates the current ambient temperature. Indicates the critical temperature of the battery;

[0019] The self-discharge rate Calculated by the following formula: ;

[0020] In the formula, represents the open circuit voltage of the battery at time t=0, Represents the open circuit voltage of the battery at time t.

[0021] Preferably, step 2 comprises:

[0022] S21, obtaining physical topology information of the lithium battery pack, including the number of series connections S and the number of parallel connections P;

[0023] S22. Collect the voltage value of each PACK in the lithium battery pack to form a voltage data set: ;

[0024] Where n=S×P; the series structure is divided into S regions, each of which contains P parallel batteries: ;

[0025] Represents the set of voltage values ​​of all parallel PACKs in the jth series region; the jth series region contains the voltage values ​​of P parallel PACKs , these voltage values ​​together form the set ;

[0026] S23, based on , calculate the average voltage of the jth series region : ;

[0027] in, represents the voltage value of the i-th PACK in the j-th series region; P represents the number of parallel connections; j represents the series region index;

[0028] And record the voltage range value of the jth series area : ;

[0029] in, represents the maximum PACK voltage in the jth series region, represents the minimum PACK voltage in the jth series region;

[0030] S24. Compare the average voltage of each series area , calculate the voltage difference between any two regions : ;

[0031] Where j and k represent the indexes of different series regions; the output region voltage difference set ;

[0032] S25, set the voltage threshold X, if the voltage difference between any two areas Exceeding the voltage threshold X indicates that the voltages of the two series regions are inconsistent; if the voltage difference between any two regions The voltage threshold X is not exceeded, indicating that the voltages of the two series regions are consistent.

[0033] Preferably, step 2 further comprises:

[0034] S26, corresponding to each series area , construct the SOC data set of the jth series area: ;

[0035] Wherein, j=1, 2, ..., S; P represents the number of parallel PACKs in each series region;

[0036] S27, SOC data set based on the jth series area , calculate the average SOC of the jth series area : ;

[0037] in, represents the SOC value of the i-th PACK in the j-th series area; P represents the parallel number; j represents the series area index;

[0038] And record the SOC deviation value of the i-th PACK in the j-th series area : ;

[0039] S28. According to the SOC deviation value of each PACK, a difference threshold is set for classification, including:

[0040] like ≤First difference threshold , classified as low-discrepancy areas;

[0041] If the first difference threshold < ≤ Second difference threshold , classified as medium difference area;

[0042] like >Second difference threshold , classified as high-discrepancy areas;

[0043] S29. Generate a corresponding balancing plan list according to the SOC difference and voltage difference of each PACK.

[0044] Preferably, step three includes:

[0045] S31. Extract the internal resistance value of PACK in the health status data 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate After dimensionless processing, the comprehensive health index is calculated by the following formula : ;

[0046] In the formula, Respectively represented as PACK internal resistance value 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate The weight value of Indicates the normal value of the first repair;

[0047] S32, set the first aging threshold L1 and the second aging threshold L2, and calculate the comprehensive health index The first aging threshold L1 and the second aging threshold L2 are compared respectively to classify each PACK, including:

[0048] When the comprehensive health index ≤ the first aging threshold L1, indicating that the PACK is qualified;

[0049] The first aging threshold L1<comprehensive health index ≤ the second aging threshold L2, indicating that the PACK is at the first aging level;

[0050] When the comprehensive health index >The second aging threshold L2 indicates that the PACK is at the second aging level, which is more serious than the first aging level and needs to be balanced or replaced.

[0051] Preferably, step three also includes:

[0052] S33, all PACK comprehensive health index , calculate the performance matching coefficient of the kth PACK and the fth PACK : ;

[0053] in, The value range of is [0,1], 1 means a perfect match, and vice versa; represents the comprehensive health index of the kth PACK, represents the comprehensive health index of the fth PACK,

[0054] Represents the maximum comprehensive health index of all PACKs, which is used to normalize the difference; forms a matching matrix based on the performance matching coefficient, and performs matching to obtain a matching list;

[0055] S34, according to the performance matching coefficient The values ​​are classified into:

[0056] when , obtain the first matching classification, generate the first priority combination queue, and use it directly;

[0057] when , obtain the second matching classification, generate the second priority combination queue, and use it after balancing;

[0058] when , indicating that the match is unsatisfactory and needs to be balanced or replaced first.

[0059] Preferably, step four includes:

[0060] S41, collecting the cable connection parameters of each PACK in the lithium battery pack, including: cable length cd, cable cross-sectional area A, and resistivity of the cable material W and contact impedance ; S42, calculate the total impedance of the cable according to Ohm's law : ;

[0061] The cable body impedance The calculation formula is: ;

[0062] Among them, A needs to be converted to m in the formula 2 , i.e. 1mm 2 =10 −6 m 2 ; Resistivity of cable material W According to the material settings, including: when the cable material is copper, W=1.68×10−8Ω⋅m; when the cable material is aluminum, W=2.65×10−8Ω⋅m; contact impedance It is the additional impedance generated by the cable connection point, including the plug or terminal block, and is set to 0.005-0.05Ω, which varies according to the actual device and connection method;

[0063] S43, based on the total impedance of the cable , calculate the PACK impedance loss ratio using the following formula : ;

[0064] in, Is the maximum value of the cable impedance in all PACK modules, The value range of is [0,1], which is used to measure the impact of cable impedance on energy transmission loss. , indicating no loss at all; when , indicating the greatest loss and not suitable for use.

[0065] Preferably, step 4 further comprises:

[0066] S44, according to PACK impedance loss ratio The value of is evaluated to obtain the loss evaluation results, including:

[0067] when , indicating that the cable loss is qualified, generating a low impedance loss interval level, and performing equalization directly;

[0068] when , the cable loss is obtained to be unqualified, and the intermediate impedance loss interval level is generated;

[0069] when , indicating that the cable loss is unqualified, generating a high impedance loss interval level;

[0070] S45. According to the loss assessment results, the balancing plan list and the matching list are modified accordingly.

[0071] A lithium battery management device supporting mixed use of new and old PACKs, comprising:

[0072] The first acquisition module is used to connect to the battery management platform through the network to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set;

[0073] The performance analysis module is used to divide the single PACK area according to the number of PACKs in the lithium battery pack based on the voltage data set, and then analyze the SOC difference and voltage difference of each PACK in combination with the SOC data set, and generate a corresponding balancing plan list;

[0074] A matching module is used to analyze the difference in battery aging degree in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list;

[0075] The second acquisition module is used to collect the cable connection parameters of each PACK in the lithium battery pack, including cable length cd, cable cross-sectional area A, and resistivity of cable material W and contact impedance , and calculate the PACK impedance loss ratio ;

[0076] Dynamic balancing module, used to generate a corresponding matching list based on the balancing plan list, combined with the PACK impedance loss ratio And evaluate the loss assessment results, and make corresponding corrections to the balanced plan list and matching list.

[0077] The present invention provides a lithium battery management method and device that supports mixed use of new and old PACKs. It has the following beneficial effects:

[0078] (1) By collecting and acquiring health status data such as battery voltage, SOC, internal resistance, and power attenuation, the present invention can more comprehensively evaluate the performance of each PACK. Unlike the traditional method of balancing based solely on voltage or SOC, the present invention comprehensively considers the aging degree and performance differences of the battery, and can more accurately adjust the balancing plan for each battery PACK, thereby improving the overall performance of the battery pack and extending its service life.

[0079] (2) Traditional BMS often cannot effectively deal with the performance differences caused by the mixed use of new and old battery PACKs. However, the present invention greatly improves the adaptability of the mixed use of new and old battery PACKs by establishing a detailed health status data set and classifying and matching the performance of each PACK. By real-time monitoring and analyzing the health status of the battery, the system can dynamically adjust the operating parameters of the battery pack, so that the new and old battery PACKs can work together efficiently in the same system, avoiding battery loss and shortened life due to battery performance mismatch.

[0080] (3) By calculating the performance matching coefficient between each pair of battery packs and classifying them according to the matching results, the present invention can accurately determine which battery packs need to be balanced or replaced. This process can not only effectively improve the overall performance of the battery pack, but also reduce excessive loss and instability caused by battery performance mismatch, ensuring long-term stable operation of the battery pack.

[0081] (4) By collecting and analyzing the cable connection parameters of each battery PACK, the total impedance of the cable is calculated, and the PACK impedance loss ratio is further established. This mechanism can accurately evaluate the impact of cable loss on battery performance, avoiding the defect of traditional technology that cable loss is not effectively evaluated and optimized, thereby improving the overall energy efficiency and operational safety of the battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 A schematic diagram of the steps of a lithium battery management method supporting mixed use of new and old PACKs according to the present invention;

[0083] Figure 2 The present invention is a schematic flow chart of a lithium battery management device that supports mixed use of new and old PACKs. DETAILED DESCRIPTION

[0084] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0085] Example 1

[0086] See also Figure 1 The present invention provides a lithium battery management method supporting mixed use of new and old PACKs, comprising the following steps:

[0087] Step 1: Use the network to connect to the battery management platform to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set;

[0088] Step 2: Based on the voltage data set, divide the single PACK area according to the number of PACKs in the lithium battery pack, and then combine with the SOC data set to analyze the SOC difference and voltage difference of each PACK, and generate a corresponding balancing plan list;

[0089] Step 3: Analyze the differences in battery aging in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list;

[0090] Step 4: Collect the cable connection parameters of each PACK in the lithium battery pack and build the PACK impedance loss ratio ; and according to the PACK impedance loss ratio Make corresponding amendments to the balanced plan list and matching list.

[0091] In this embodiment, by simultaneously acquiring the battery's voltage, SOC, internal resistance, power attenuation and other health status data, the present invention can more comprehensively evaluate the performance of each PACK. Different from the traditional method of balancing based on voltage or SOC alone, the present invention comprehensively considers the battery's aging degree and performance differences, and can more accurately adjust the balancing plan for each battery PACK, thereby improving the overall performance of the battery pack and extending its service life.

[0092] Traditional BMS often cannot effectively deal with the performance differences caused by the mixed use of new and old battery PACKs. However, the present invention greatly improves the adaptability of the mixed use of new and old battery PACKs by establishing a detailed health status data set and classifying and matching the performance of each PACK. By real-time monitoring and analyzing the health status of the battery, the system can dynamically adjust the operating parameters of the battery pack, so that the new and old battery PACKs can work together efficiently in the same system, avoiding battery loss and shortened life due to battery performance mismatch.

[0093] By calculating the performance matching coefficient between each pair of battery packs and classifying them according to the matching results, the present invention can accurately determine which battery packs need to be balanced or replaced. This process can not only effectively improve the overall performance of the battery pack, but also reduce excessive loss and instability caused by battery performance mismatch, ensuring long-term stable operation of the battery pack.

[0094] The present invention collects and analyzes the cable connection parameters of each battery PACK, calculates the total impedance of the cable, and further establishes the PACK impedance loss ratio. This mechanism can accurately evaluate the impact of cable loss on battery performance, avoiding the defect of cable loss in traditional technology that has not been effectively evaluated and optimized, thereby improving the overall energy efficiency and operational safety of the battery pack.

[0095] Example 2

[0096] This embodiment is an explanation of the embodiment 1. Specifically, the voltage data set includes: the voltage value of each PACK; the SOC data set includes: the SOC value of each PACK; the health status data set includes: the battery internal resistance value , Battery power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate .

[0097] The battery internal resistance Calculated by the following formula: ;

[0098] in, Indicates the open circuit voltage of the battery, that is, the voltage value when the battery is not connected to a load. Indicates the voltage of the battery under load, Represents the current of the battery under load; the internal resistance of the battery is calculated by measuring the open circuit voltage, battery load voltage and load current of the battery. This calculation can accurately reflect the change of the internal resistance of the battery, which is an important indicator of battery performance and life. As the battery ages, the increase in internal resistance may cause power loss and heat, which in turn affects the overall efficiency and safety of the battery. By monitoring the change of internal resistance, the system can predict the degree of battery aging and adjust the balancing management strategy in time to avoid the impact of performance degradation on the battery pack.

[0099] The battery power decay Calculated by the following formula: ;

[0100] in, Indicates the maximum power of the battery in its new state. Indicates the maximum power of the battery in its current state; the power attenuation of the battery is calculated using the ratio of the maximum power of the battery in its new state to the maximum power of its current state. Power attenuation is an important indicator of battery aging. As the battery usage cycle increases, the power output capacity of the battery gradually decreases. By accurately calculating power attenuation, the present invention can reflect the effectiveness and adaptability of the battery in real time, and promptly identify batteries that need to be replaced or reconfigured, thereby optimizing the overall operating efficiency and stability of the battery pack.

[0101] The cycle life Calculated by the following formula: ;

[0102] In the formula, Indicates the current battery capacity. Indicates the initial capacity of the battery, Indicates the number of cycles of the battery's design life; the battery's cycle life is calculated based on the relationship between the battery's current capacity, initial capacity, and the number of cycles of the design life. As the number of cycles increases, the battery's capacity gradually decreases, and its service life also gradually shortens. By calculating and monitoring the battery's cycle life, it is possible to accurately predict when the battery will reach the critical point of replacement, thereby effectively arranging battery maintenance, replacement, or reorganization to avoid battery pack failure due to battery performance degradation.

[0103] The thermal runaway coefficient TRI Calculated by the following formula: ;

[0104] In the formula, Indicates the charging current, Indicates the maximum allowable charging current, Indicates the internal resistance of the battery, in ohms. The internal resistance of the battery increases with use, causing the battery to heat up; Indicates the maximum safe internal resistance of the battery; Indicates the current ambient temperature. Indicates the critical temperature of the battery; the thermal runaway coefficient is calculated through parameters such as charging current, maximum allowable charging current, battery internal resistance, and ambient temperature. Internal resistance and temperature are the main factors for battery heating. Excessive battery internal resistance or charging current may cause the battery to overheat, thereby causing thermal runaway. By real-time monitoring of the TRI coefficient, the present invention can determine the thermal runaway risk of the battery and take timely measures, such as adjusting the charging strategy or enhancing the cooling system, to prevent the battery from overheating and ensure the safe operation of the battery.

[0105] The self-discharge rate Calculated by the following formula: ;

[0106] In the formula, Represents the open circuit voltage of the battery at time t=0. t=0 represents the open circuit voltage of the battery under a known, initial condition, which is usually the voltage value when the battery is not connected to a load and is not discharged. Therefore, t=0 is used as a time reference point to measure and compare the open circuit voltage of the battery over time, thereby calculating the self-discharge rate of the battery.

[0107] It represents the open circuit voltage of the battery at time t; therefore, time t=0 can be regarded as the open circuit voltage value when the battery is in an ideal initial charging state. As time passes and t>0, the open circuit voltage of the battery will gradually decrease, and this decrease can be used to estimate the self-discharge rate.

[0108] The self-discharge rate of the battery is calculated by comparing the open circuit voltage of the battery at different time points. The self-discharge rate is the rate at which the battery loses power when not in use, and usually increases as the battery ages. A higher self-discharge rate means that the battery's energy retention ability is reduced, which may cause the battery to lose power in a short period of time. By monitoring the self-discharge rate, the present invention can promptly detect battery health problems and perform corresponding battery pack management to ensure the continuous and stable performance of the battery pack in actual applications.

[0109] Example 3

[0110] This embodiment is an explanation of the embodiment 1. Specifically, step 2 includes:

[0111] S21, obtaining physical topology information of the lithium battery pack, including the number of series connections S and the number of parallel connections P;

[0112] S22. Collect the voltage value of each PACK in the lithium battery pack to form a voltage data set: ;

[0113] Where n=S×P; the series structure is divided into S regions, each of which contains P parallel batteries: ;

[0114] Represents the set of voltage values ​​of all parallel PACKs in the jth series region; the jth series region contains the voltage values ​​of P parallel PACKs , these voltage values ​​together form the set ;

[0115] S23, based on , calculate the average voltage of the jth series region : ;

[0116] in, represents the voltage value of the i-th PACK in the j-th series region; P represents the number of parallel connections; j represents the series region index;

[0117] And record the voltage range value of the jth series area : ;

[0118] in, represents the maximum PACK voltage in the jth series region, represents the minimum PACK voltage in the jth series region;

[0119] S24. Compare the average voltage of each series area , calculate the voltage difference between any two regions : ;

[0120] Where j and k represent the indexes of different series regions; the output region voltage difference set ;

[0121] S25, set the voltage threshold X, if the voltage difference between any two areas Exceeding the voltage threshold X indicates that the voltages of the two series regions are inconsistent; if the voltage difference between any two regions The voltage threshold X is not exceeded, indicating that the voltages of the two series regions are consistent.

[0122] In this embodiment, by performing detailed voltage monitoring and analysis on the series areas of the lithium battery pack, the present invention can effectively detect and evaluate the voltage consistency between the various series areas. This method not only constructs a voltage data set based on the voltage data of each PACK, but also helps identify areas with inconsistent voltages by calculating and comparing the voltages of each series area. In particular, by setting a voltage difference threshold, it is possible to accurately determine which series areas have voltage differences, thereby achieving effective monitoring of the voltage consistency of each area in the battery pack. The present invention can accurately capture the voltage deviation of each series area in the battery pack by calculating the average voltage and voltage range, and provide support for the balanced management of the battery pack through this deviation to ensure the overall stability of the battery pack performance. This technology can effectively deal with the voltage mismatch problem between batteries when new and old battery PACKs are mixed, thereby optimizing the use efficiency of the battery pack and extending its service life.

[0123] Example 4

[0124] This embodiment is explained in Embodiment 3. Specifically, step 2 also includes:

[0125] S26, corresponding to each series area , construct the SOC data set of the jth series area: ;

[0126] Wherein, j=1, 2, ..., S; P represents the number of parallel PACKs in each series region;

[0127] S27, SOC data set based on the jth series area , calculate the average SOC of the jth series area : ;

[0128] in, represents the SOC value of the i-th PACK in the j-th series area; P represents the parallel number; j represents the series area index;

[0129] And record the SOC deviation value of the i-th PACK in the j-th series area : ;

[0130] S28. According to the SOC deviation value of each PACK, a difference threshold is set for classification, including:

[0131] like ≤First difference threshold , classified as low-discrepancy areas;

[0132] If the first difference threshold , the class is the medium difference area;

[0133] like >Second difference threshold , classified as high-discrepancy areas;

[0134] S29. Generate a corresponding balancing plan list according to the SOC difference and voltage difference of each PACK.

[0135] Balanced Planning Checklist Example Chart:

[0136] PACK No. SOC deviation value Voltage difference Voltage consistency Balance Priority SOC difference classification Balanced approach Balanced operation time Balanced strategy Current / voltage threshold Expected Results 001 5% 0.3V Inconsistency high Medium difference area Passive Balance 30 minutes Current balancing Current limit: 1A SOC difference reduced to 2% 002 2% 0.1V Consistency middle Low variance area Active balancing 20 minutes Voltage balancing Voltage limit: 4.2V Voltage and SOC balance 003 7% 0.5V Inconsistency high High variance areas Active balancing 40 minutes Voltage balancing Current limit: 1.2A The voltage returns to 4.1V 004 3% 0.2V Consistency middle Low variance area Passive Balance 25 minutes Current balancing Current limit: 1A Battery SOC variation reduced 005 10% 0.6V Inconsistency high High variance areas Passive Balance 45 minutes Current balancing Voltage limit: 4.1V The balancing effect is obvious

[0137] In this embodiment, the present invention provides a more accurate basis for the balanced management of the battery pack by analyzing the SOC differences of each series area in the lithium battery pack in detail. First, by constructing the SOC data set of each series area and merging and calculating the average SOC value, the SOC level of each parallel PACK in each series area can be effectively monitored, and the deviation can be further identified. By recording the SOC deviation value of each PACK, the battery health status of different series areas can be clearly understood, and reliable data support can be provided for subsequent classification and optimization.

[0138] Secondly, the difference threshold is used to classify different SOC deviation areas (low, medium, and high difference areas), providing a more detailed hierarchical analysis for the balancing management of the battery pack, ensuring that appropriate management measures are taken for each difference area to reduce the potential risks caused by inconsistent battery performance. Finally, based on the comprehensive analysis of SOC differences and voltage differences, a balancing plan list is generated to provide effective support for the balancing optimization of battery packs when new and old battery PACKs are mixed, ensuring the high efficiency and long life of battery packs in practical applications. The active balancing method is suitable for PACKs with large SOC deviations and large voltage differences. It can significantly reduce the SOC difference through faster voltage balancing operations to achieve the effect of optimizing battery performance. Passive balancing is aimed at battery PACKs with small differences or consistent voltages, reducing energy loss and maintaining the health of the battery. By setting the balancing priority, it can ensure that the battery PACKs that need balancing the most are processed in a timely manner, reduce the negative impact caused by unbalanced batteries, and improve the overall performance of the battery pack.

[0139] Example 5

[0140] This embodiment is an explanation of the embodiment 1. Specifically, step 3 includes:

[0141] S31. Extract the internal resistance value of PACK in the health status data 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate , after dimensionless processing, the comprehensive health index is calculated by the following formula : ;

[0142] In the formula, Respectively represented as PACK internal resistance value 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate The weight value of Indicates the normal value of the first repair;

[0143] S32, set the first aging threshold L1 and the second aging threshold L2, and calculate the comprehensive health index The first aging threshold L1 and the second aging threshold L2 are compared respectively to classify each PACK, including:

[0144] When the comprehensive health index ≤ the first aging threshold L1, indicating that the PACK is qualified;

[0145] The first aging threshold L1<comprehensive health index ≤ the second aging threshold L2, indicating that the PACK is at the first aging level;

[0146] When the comprehensive health index >The second aging threshold L2 indicates that the PACK is at the second aging level, which is more serious than the first aging level and needs to be balanced or replaced.

[0147] Step three also includes:

[0148] S33, all PACK comprehensive health index , calculate the performance matching coefficient of the kth PACK and the fth PACK : ;

[0149] in, The value range of is [0,1], 1 means a perfect match, and vice versa; represents the comprehensive health index of the kth PACK, represents the comprehensive health index of the fth PACK, Represents the maximum comprehensive health index of all PACKs, which is used to normalize the difference; forms a matching matrix M based on the performance matching coefficient, and performs matching to obtain a matching list;

[0150] The matching matrix M is expressed as: ;

[0151] S34, according to the performance matching coefficient The values ​​are classified into:

[0152] when , obtain the first matching classification, generate the first priority combination queue, and use it directly;

[0153] when , obtain the second matching classification, generate the second priority combination queue, and use it after balancing;

[0154] when , indicating that the match is unsatisfactory and needs to be balanced or replaced first.

[0155] Example of a matching list:

[0156]

[0157] In this embodiment, by extracting data such as internal resistance, power attenuation, cycle life, thermal runaway coefficient and self-discharge rate, and performing dimensionless processing, a comprehensive health index is calculated, so that the health status of each battery PACK can be accurately quantified. This comprehensive evaluation method is more comprehensive than the traditional single parameter evaluation and can reflect the overall health level of the battery PACK. The battery PACK is graded according to the comprehensive health index. This method can clearly distinguish battery PACKs of different aging levels, and prioritize balancing or replacement of severely aged batteries, thereby avoiding the negative impact of aging batteries on the performance of the entire battery pack. By calculating the performance matching coefficient and forming a matching matrix, the system can determine the matching between different battery PACKs. In this way, reasonable pairing can be performed according to the difference in health status between battery PACKs, the working efficiency of the battery pack can be optimized, and the battery loss caused by performance mismatch can be reduced. The battery PACKs are classified according to the matching coefficient and divided into different matching priority queues. This classification can ensure that highly matched battery PACKs are used first, while low-matched battery PACKs need to be balanced or replaced. This priority sorting improves the efficiency of battery pack management and reduces the impact of unmatched battery PACKs on the overall performance of the system.

[0158] According to the matching coefficient, the PACKs are divided into different priorities. Combinations with high matching degrees (such as the first priority) can be used directly, while combinations with low matching degrees need to be balanced first to reduce performance losses caused by mismatches. Prioritizing the balancing or replacement of unqualified combinations can avoid the negative impact of inappropriate batteries on the performance of the entire battery pack. Reasonable battery matching and balancing operations can effectively reduce energy waste and improve energy efficiency. Especially when there are significant performance differences between battery PACKs, balancing or replacing unqualified batteries in advance can help reduce energy losses in long-term operation.

[0159] Example 6

[0160] This embodiment is an explanation of the embodiment 1. Specifically, step 4 includes:

[0161] S41, collecting the cable connection parameters of each PACK in the lithium battery pack, including: cable length cd, cable cross-sectional area A, and resistivity of the cable material W and contact impedance ;

[0162] S42. Calculate the total impedance of the cable according to Ohm's law : ;

[0163] The cable body impedance The calculation formula is: ;

[0164] Among them, A needs to be converted to m in the formula 2 , i.e. 1mm 2 =10 −6 m 2 ; Resistivity of cable material W According to the material settings, including: when the cable material is copper, W=1.68×10−8Ω⋅m; when the cable material is aluminum, W=2.65×10−8Ω⋅m; contact impedance It is the additional impedance generated by the cable connection point, including the plug or terminal block, and is set to 0.005-0.05Ω, which varies according to the actual device and connection method;

[0165] S43, based on the total impedance of the cable , calculate the PACK impedance loss ratio using the following formula : ;

[0166] in, Is the maximum value of the cable impedance in all PACK modules, The value range of is [0,1], which is used to measure the impact of cable impedance on energy transmission loss. , indicating no loss at all; when

[0167] , indicating the greatest loss and not suitable for use.

[0168] S44, according to PACK impedance loss ratio The value of is evaluated to obtain the loss evaluation results, including:

[0169] when , indicating that the cable loss is qualified, generating a low impedance loss interval level, and performing equalization directly;

[0170] when , the cable loss is obtained to be unqualified, and the intermediate impedance loss interval level is generated;

[0171] when , indicating that the cable loss is unqualified, generating a high impedance loss interval level;

[0172] S45. According to the loss assessment results, the balancing plan list and the matching list are modified accordingly.

[0173] Balanced plan list corrections:

[0174] PACK No. PACK impedance loss ratio ClbleR Impedance loss range Balanced approach Balanced operation time Balanced strategy Current / voltage threshold Expected Results 001 0.25 Low impedance loss range Passive Balance 30 minutes Current balancing Current limit: 1A SOC difference reduced to 2% 002 0.4 Intermediate impedance loss range Active balancing 25 minutes Voltage balancing Voltage limit: 4.2V Voltage and SOC balance 003 0.7 High impedance loss range Active balancing 50 minutes Voltage balancing Current limit: 1.2A The voltage returns to 4.1V 004 0.2 Low impedance loss range Passive Balance 25 minutes Current balancing Current limit: 1A Battery SOC variation reduced 005 0.75 High impedance loss range Active balancing 50 minutes Current balancing Voltage limit: 4.1V The balancing effect is obvious

[0175] Match list corrections:

[0176] Combination No. PACK No. <![CDATA[Matching coefficient PMC k,f > ClbleR Impedance loss range Priority Balanced approach Correction reason 1 PACK1 and PACK2 0.947 0.25 Low impedance loss range First priority Direct use The cable loss is low and can be directly balanced; the optimization effect reaches 95% 2 PACK1 and PACK3 0.895 0.35 Intermediate impedance loss range First priority Consider the balance and use Intermediate impedance loss range, optimization and balancing are required; the optimization effect reaches 85% 3 PACK2 and PACK4 0.853 0.4 Intermediate impedance loss range Second priority Consider the balance and use Intermediate impedance loss range, optimization and balancing are required; the optimization effect reaches 85% 4 PACK3 and PACK4 0.637 0.63 High impedance loss range Failure Prioritize balancing or replacement In the high impedance loss range, optimization and balancing are required; the optimization effect reaches 65% 5 PACK1 and PACK4 0.689 0.75 High impedance loss range Failure Prioritize balancing or replacement The cable loss is high and needs to be balanced or replaced first; the optimization effect reaches 60%

[0177] In this embodiment, by calculating the total impedance of the cable and obtaining the PACK impedance loss ratio, the energy loss caused by factors such as the cable body and contact impedance in the cable connection can be accurately measured. This provides an important basis for optimizing the energy efficiency of the battery pack. According to the loss assessment results, different cable loss conditions can be identified and classified, and the battery balancing plan can be adjusted according to different loss levels. For cables with large losses, priority is given to balancing or replacement to reduce energy loss, thereby improving the energy efficiency of the overall battery pack. By evaluating the cable impedance, combined with the correction of the balancing plan and the matching list, it is possible to ensure that the energy transmission between different battery PACKs is more balanced, avoid excessive battery consumption caused by cable impedance differences, and optimize the battery life. Reasonable cable loss control and balancing operations help to slow down excessive aging and loss of batteries, thereby extending the overall service life of the battery pack. Especially in the case of cables with large losses, the balancing strategy is adjusted in time to effectively reduce the performance differences between battery PACKs. Excessive cable loss may cause problems such as overheating and overcurrent. By promptly discovering cable impedance problems and correcting the loss interval, the safety and stability of the battery pack can be improved, and failures caused by cable problems can be avoided. By regularly evaluating cable impedance loss, cables with large losses can be discovered and replaced in advance to avoid sudden failures during system operation, thereby reducing system maintenance and replacement costs.

[0178] Example 7

[0179] Please refer to Figure 2 , a lithium battery management device supporting mixed use of new and old PACKs, comprising:

[0180] The first acquisition module is used to connect to the battery management platform through the network to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set;

[0181] The performance analysis module is used to divide the single PACK area according to the number of PACKs in the lithium battery pack based on the voltage data set, and then analyze the SOC difference and voltage difference of each PACK in combination with the SOC data set, and generate a corresponding balancing plan list;

[0182] A matching module is used to analyze the difference in battery aging degree in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list;

[0183] The second acquisition module is used to collect the cable connection parameters of each PACK in the lithium battery pack, including cable length cd, cable cross-sectional area A, and resistivity of cable material W and contact impedance , and calculate the PACK impedance loss ratio ;

[0184] Dynamic balancing module, used to generate a corresponding matching list based on the balancing plan list, combined with the PACK impedance loss ratio And evaluate the loss assessment results, and make corresponding corrections to the balanced plan list and matching list.

[0185] In this embodiment, the voltage, SOC, internal resistance and health status of each PACK in the lithium battery pack are obtained through the first acquisition module. Combined with the SOC and voltage difference analysis of the performance analysis module, it can effectively identify the differences between battery PACKs and generate targeted balancing plans, which helps to optimize the performance distribution of the battery and extend the service life of the entire battery pack. The matching module analyzes the health status data set, evaluates the battery aging degree of each PACK, and calculates the performance matching coefficient to ensure that the new and old battery PACKs can be mixed and used within a reasonable range, thereby avoiding the problem of unbalanced energy transmission caused by differences in battery aging and improving the stability of the battery pack. The second acquisition module collects the cable connection parameters and calculates the impedance loss ratio of the PACK. The dynamic balancing module combines this data to perform loss assessment, correct the balancing plan and matching list, reduce the energy loss caused by cable impedance differences, and improve the energy efficiency of the overall battery pack.

[0186] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0187] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A lithium battery management method supporting mixed use of new and old PACKs, characterized in that: The following steps are involved: Step 1: Use the network to connect to the battery management platform to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set; Step 2: Based on the voltage data set, divide the single PACK area according to the number of PACKs in the lithium battery pack, and then combine with the SOC data set to analyze the SOC difference and voltage difference of each PACK, and generate a corresponding balancing plan list; Step 3: Analyze the differences in battery aging in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list; Step 4: Collect the cable connection parameters of each PACK in the lithium battery pack and build the PACK impedance loss ratio ; And according to the PACK impedance loss ratio Make corresponding amendments to the balanced plan list and matching list.

2. A lithium battery management method supporting mixed use of new and old PACKs according to claim 1, characterized in that: The voltage data set includes: the voltage value of each PACK; the SOC data set includes: the SOC value of each PACK; the health status data set includes: the battery internal resistance value , Battery power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate .

3. A lithium battery management method supporting mixed use of new and old PACKs according to claim 2, characterized in that: The battery internal resistance Calculated by the following formula: ; in, Indicates the open circuit voltage of the battery, that is, the voltage value when the battery is not connected to a load. Indicates the voltage of the battery under load, Indicates the current of the battery under load; The battery power decay Calculated by the following formula: ; in, Indicates the maximum power of the battery in its new state. Indicates the maximum power of the battery in its current state; The cycle life Calculated by the following formula: ; In the formula, Indicates the current battery capacity. Indicates the initial capacity of the battery, Indicates the number of cycles of battery design life; The thermal runaway coefficient TRI Calculated by the following formula: ; In the formula, Indicates the charging current, Indicates the maximum allowable charging current, Indicates the internal resistance of the battery, in ohms. The internal resistance of the battery increases with use, causing the battery to heat up; Indicates the maximum safe internal resistance of the battery; Indicates the current ambient temperature. Indicates the critical temperature of the battery; The self-discharge rate Calculated by the following formula: ; In the formula, represents the open circuit voltage of the battery at time t=0, Represents the open circuit voltage of the battery at time t.

4. A lithium battery management method supporting mixed use of new and old PACKs according to claim 1, characterized in that: Step two includes; S21, obtaining physical topology information of the lithium battery pack, including the number of series connections S and the number of parallel connections P; S22. Collect the voltage value of each PACK in the lithium battery pack to form a voltage data set: Where n=S×P; the series structure is divided into S regions, each of which contains P parallel batteries: ； Represents the set of voltage values ​​of all parallel PACKs in the jth series region; the jth series region contains the voltage values ​​of P parallel PACKs , these voltage values ​​together form the set ; S23, based on , calculate the average voltage of the jth series region : ; in, represents the voltage value of the i-th PACK in the j-th series region; P represents the parallel number; j represents the series region index; And record the voltage range value of the jth series area : ; in, represents the maximum PACK voltage in the jth series region, represents the minimum PACK voltage in the jth series region; S24. Compare the average voltage of each series area , calculate the voltage difference between any two regions : ； Where j and k represent the indexes of different series regions; the output region voltage difference set ; S25, set the voltage threshold X, if the voltage difference between any two areas Exceeding the voltage threshold X indicates that the voltages of the two series regions are inconsistent; if the voltage difference between any two regions The voltage threshold X is not exceeded, indicating that the voltages of the two series regions are consistent.

5. A lithium battery management method supporting mixed use of new and old PACKs according to claim 4, characterized in that: Step two also includes; S26, corresponding to each series area , construct the SOC data set of the jth series area: ； Wherein, j=1, 2, ..., S; P represents the number of parallel PACKs in each series region; S27, SOC data set based on the jth series area , calculate the average SOC of the jth series area : ; in, represents the SOC value of the i-th PACK in the j-th series area; P represents the parallel number; j represents the series area index; And record the SOC deviation value of the i-th PACK in the j-th series area : ; S28. According to the SOC deviation value of each PACK, a difference threshold is set for classification, including: like ≤First difference threshold , classified as low-discrepancy areas; If the first difference threshold < ≤ Second difference threshold , classified as medium difference area; like >Second difference threshold , classified as high-discrepancy areas; S29. Generate a corresponding balancing plan list according to the SOC difference and voltage difference of each PACK.

6. A lithium battery management method supporting mixed use of new and old PACKs according to claim 1, characterized in that: Step three includes: S31. Extract the internal resistance value of PACK in the health status data 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate , after dimensionless processing, the comprehensive health index is calculated by the following formula : ; In the formula, Respectively represented as PACK internal resistance value 、PACK power attenuation , Cycle life , Thermal runaway coefficient TRI and self-discharge rate The weight value of Indicates the normal value of the first repair; S32, set the first aging threshold L1 and the second aging threshold L2, and calculate the comprehensive health index The first aging threshold L1 and the second aging threshold L2 are compared respectively to classify each PACK, including: When the comprehensive health index ≤ the first aging threshold L1, indicating that the PACK is qualified; The first aging threshold L1<comprehensive health index ≤ the second aging threshold L2, indicating that the PACK is at the first aging level; When the comprehensive health index >The second aging threshold L2 indicates that the PACK is at the second aging level, which is more serious than the first aging level and needs to be balanced or replaced.

7. A lithium battery management method supporting mixed use of new and old PACKs according to claim 6, characterized in that: Step three also includes: S33, all PACK comprehensive health index , calculate the performance matching coefficient of the kth PACK and the fth PACK : ; in, The value range of is [0,1], 1 means a complete match; represents the comprehensive health index of the kth PACK, represents the comprehensive health index of the fth PACK, Represents the maximum comprehensive health index of all PACKs, which is used to normalize the difference; forms a matching matrix based on the performance matching coefficient, and performs matching to obtain a matching list; S34, according to the performance matching coefficient The values ​​are classified into: when ≥0.9, the first matching classification is obtained, and the first priority combination queue is generated and used directly; When 0.7≤ <0.9, obtain the second matching classification, generate the second priority combination queue, and use it after balancing; when <0.7, indicating that the match is unqualified and needs to be balanced or replaced first.

8. A lithium battery management method supporting mixed use of new and old PACKs according to claim 1, characterized in that: Step 4 includes: S41, collecting the cable connection parameters of each PACK in the lithium battery pack, including: cable length cd, cable cross-sectional area A, and resistivity of the cable material W and contact impedance ; S42. Calculate the total impedance of the cable according to Ohm's law : ; The cable body impedance The calculation formula is: ; Among them, A needs to be converted to m in the formula 2 , i.e. 1mm 2 =10 −6 m 2 ; Resistivity of cable material W According to the material setting, including: when the cable material is copper, W=1.68×10 −8 Ω⋅m; when the cable material is aluminum, W=2.65×10 −8 Ω⋅m; contact impedance There is an additional impedance at the cable connection point, including the plug or terminal block, which is set to 0.005-0.05Ω, which varies according to the actual device and connection method; S43, based on the total impedance of the cable , calculate the PACK impedance loss ratio using the following formula : ; in, Is the maximum value of the cable impedance in all PACK modules, The value range of is [0,1], which is used to measure the impact of cable impedance on energy transmission loss. , indicating no loss at all; when , indicating the greatest loss and not suitable for use.

9. A lithium battery management method supporting mixed use of new and old PACKs according to claim 8, characterized in that: Step 4 also includes: S44, according to PACK impedance loss ratio The value of is evaluated to obtain the loss evaluation results, including: When 0≤ <0.3, indicating that the cable loss is qualified, generating a low impedance loss interval level, and performing equalization directly; When 0.3≤ <0.6, the cable loss is unqualified, and the intermediate impedance loss interval level is generated; when ≥0.6, indicating that the cable loss is unqualified and generates a high impedance loss interval level; S45. According to the loss assessment results, the balancing plan list and the matching list are modified accordingly.

10. A lithium battery management device supporting mixed use of new and old PACKs, applied to a lithium battery management method supporting mixed use of new and old PACKs as claimed in any one of claims 1 to 9, characterized in that: include: The first acquisition module is used to connect to the battery management platform through the network to obtain the voltage, internal resistance, state of charge SOC and health status of each PACK in the lithium battery pack, and classify them into a voltage data set, an SOC data set and a health status data set; The performance analysis module is used to divide the single PACK area according to the number of PACKs in the lithium battery pack based on the voltage data set, and then analyze the SOC difference and voltage difference of each PACK in combination with the SOC data set, and generate a corresponding balancing plan list; A matching module is used to analyze the difference in battery aging degree in each PACK based on the health status data set, and calculate the performance matching coefficient between each pair of PACKs to generate a corresponding matching list; The second acquisition module is used to collect the cable connection parameters of each PACK in the lithium battery pack, including cable length cd, cable cross-sectional area A, and resistivity of cable material W and contact impedance , and calculate the PACK impedance loss ratio ; Dynamic balancing module, used to generate a corresponding matching list based on the balancing plan list, combined with the PACK impedance loss ratio And evaluate the loss assessment results, and make corresponding corrections to the balanced plan list and matching list.

Images