A battery group balancing method and system based on clustering

Abstract

The present invention relates to the field of battery balancing, and in particular to a clustering-based battery group balancing method and system. Under the condition that the battery cluster charging is close to being cut off and the single cell overcharge protection is not reached, all battery modules in the same battery cluster are subjected to temperature-equalized voltage-limited charging, and voltage sampling is performed at the battery module level and the battery cell level respectively to obtain a module voltage sampling data set and a single cell voltage sampling data set; the battery modules are clustered and grouped according to the module voltage sampling data set, and active balancing is performed between the battery modules according to the grouping results; the single cells in the battery modules are clustered and grouped according to the single cell voltage sampling data set of each of the battery modules, and passive balancing is performed between the single cells according to the grouping results; active balancing is performed between the battery modules, and passive balancing is performed between the battery cells in the battery module, so as to achieve more effective battery balancing.

Description

Technical Field

[0001] The present invention relates to the field of new energy storage battery balancing, and in particular to a clustering-based battery group balancing method and system. Background Art

[0002] In battery energy storage systems, due to the inevitable series application and environmental factors, as well as the process and materials in battery manufacturing, there will be consistency differences between battery cells. This problem is an inherent problem of energy storage based on electrochemical batteries. There are many studies on improving the consistency between battery cells from the perspective of manufacturing process, controlling environmental factors at the application level, and various battery balancing methods, including active or passive balancing, balancing circuits, balancing strategies, etc. Through in-depth analysis of the causes of lithium-ion battery inconsistency and various balancing variables, parameters that can reflect consistency, such as temperature, SOC, SOH, internal resistance, and voltage, are the focus of research in the current field.

[0003] The judgment of lithium battery consistency relies on accurate SOC calculation, and this parameter is related to temperature. In general SOC estimation, the influence of temperature is calibrated and corrected, which increases the workload of calibration test and calculation. SOH is a parameter with a long time scale, which does not match the control cycle of balance. The consistency correction based on SOH cannot achieve ideal results in a short time. The AC internal resistance of the battery can reflect the change of characteristics when the battery material ages, and the DC internal resistance is also related to the state of charge. However, factors such as temperature change, discharge plateau period and production process make it impossible to distinguish SOC differences with high resolution through internal resistance. In the usual balancing strategy, the most commonly used method is to judge the consistency through the single cell voltage. The open circuit voltage OCV reflects the charge condition of the material from the electrochemical principle. However, for lithium-ion batteries with lithium iron phosphate as the positive electrode, the OCV difference in the middle area of ​​SOC is not obvious. In order to capture slight voltage changes, the battery often needs to be left still for a long time, which is difficult to achieve when pursuing the utilization rate of lithium battery energy storage. The judgment based on the voltage OV at the working time avoids the waiting time of voltage sampling, but is easily affected by the fluctuation of working current.

[0004] As the number of lithium batteries in series increases, the problem of balancing efficiency gradually emerges. Active balancing has also become a hot topic of research due to its high balancing efficiency, forming many topics related to active balancing circuits. Active balancing circuits applied to single cells will increase the risk of circuit device failure and affect the battery. Single-level low-voltage converters have a negative impact on efficiency and cost, and also increase the complexity of the circuit, thereby reducing reliability; passive balancing is still widely used because of its low current and high reliability, but the SOC difference is large, especially when there is an imbalance between modules, the balancing time will be very long, and the control method often uses the extreme difference method, switch method, etc., which cannot give full play to the efficiency of cluster balancing. Summary of the invention

[0005] The technical problem to be solved by the present invention is: a clustering-based battery group balancing method and system of the present invention realizes more effective battery balancing.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A battery group balancing method based on clustering includes the following steps:

[0008] S1. When the battery cluster charging is close to the end and the single cell overcharge protection is not reached, all battery modules in the same battery cluster are charged with equal temperature and voltage limit, and voltage sampling is performed at the battery module level and the battery cell level to obtain a module voltage sampling data set and a single cell voltage sampling data set;

[0009] S2. Clustering the battery modules according to the module voltage sampling data set, and performing active balancing among the battery modules according to the clustering results;

[0010] The single cells in the battery module are clustered and grouped according to the single cell voltage sampling data set of each battery module, and passive balancing is performed between the single cells according to the grouping result.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] A cluster-based battery group balancing system, each battery cluster in the system includes multiple battery modules;

[0013] Each of the battery modules includes a plurality of battery cells, and is provided with a bidirectional active balancing converter and a battery cell management unit, wherein the bidirectional active balancing converter is used to realize a bidirectional flow of balanced energy between the low-voltage auxiliary power supply and the battery module, thereby realizing active balancing;

[0014] The battery cell management unit includes a microprocessor and an analog front end, and the battery cell management unit is communicatively connected with the battery module management unit for receiving control instructions, and the analog front end is used to realize passive balancing between single cells;

[0015] The battery cluster implements the steps in the above-mentioned clustering-based battery group balancing method based on the above structure.

[0016] The beneficial effects of the present invention are as follows: a clustering-based battery group balancing method and system of the present invention eliminates the influence of temperature, realizes clustering of battery modules and battery cells according to voltage, and according to the clustering results, performs active balancing between battery modules and passive balancing between battery cells in the battery modules, thereby achieving more effective battery balancing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a battery group balancing method based on clustering according to an embodiment of the present invention;

[0018] Figure 2 The structure diagram of a battery group balancing system based on clustering according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0020] Please refer to Figure 1 , a battery group balancing method based on clustering, comprising the steps of:

[0021] S1. When the battery cluster charging is close to the end and the single cell overcharge protection is not reached, all battery modules in the same battery cluster are charged with equal temperature and voltage limit, and voltage sampling is performed at the battery module level and the battery cell level to obtain a module voltage sampling data set and a single cell voltage sampling data set;

[0022] S2. Clustering the battery modules according to the module voltage sampling data set, and performing active balancing among the battery modules according to the clustering results;

[0023] The single cells in the battery module are clustered and grouped according to the single cell voltage sampling data set of each battery module, and passive balancing is performed between the single cells according to the grouping result.

[0024] From the above description, it can be seen that the beneficial effects of the present invention are: a clustering-based battery group balancing method of the present invention eliminates the influence of temperature, realizes clustering of battery modules and battery cells according to voltage, and according to the clustering results, performs active balancing between battery modules and passive balancing between battery cells in the battery module, thereby achieving more effective battery balancing.

[0025] Further, step S1 includes the steps of:

[0026] S11, collecting the voltage and charging current of N battery modules in the same battery cluster, and when the voltage of a module reaches a first preset charging voltage, reducing the charging current I C The preset ratio is the same as the previous moment, and the single-cell uniform temperature thermal management is started at the same time;

[0027] S12, each time a module voltage reaches the first charging preset voltage When the charging current is reduced I Cis the preset ratio of the previous moment until the following conditions are met:

[0028] ;

[0029] Performing a first synchronous sampling on the voltages of the N battery modules;

[0030] in, V m_max It is the highest voltage of each battery module in the battery cluster. is the temperature difference of M battery cells, is the temperature extreme limit value, C 1 is the preset rate for average temperature and voltage limit charging. I CN is the rated charging current;

[0031] S13, from the first synchronous sampling moment, maintain the charging current I C Keep unchanged, and perform k consecutive synchronous sampling until the voltage of any module reaches the second charging preset voltage :

[0032] ;

[0033] Obtaining the module voltage sampling data set;

[0034] S14, record the energy charged into the highest voltage module in k samplings:

[0035] ;

[0036] S15. In the kth sampling, the voltages of all battery cells in each battery module are collected to obtain the cell voltage sampling data set.

[0037] From the above description, it can be seen that through single-cell uniform temperature thermal management, uniform temperature and voltage-limited charging of the battery module is achieved, the temperature influence is eliminated, and voltage sampling is performed under uniform temperature and voltage-limited charging.

[0038] Furthermore, in step S2, the battery modules are clustered and grouped according to the module voltage sampling data set, and active balancing is performed between the battery modules according to the grouping result, including the steps of:

[0039] S21a, calculating a balanced voltage judgment threshold according to the module voltage sampling data set;

[0040] S22a, sorting the voltage sampled for the kth time in the module voltage sampling data set, and calculating the range and the mean, judging whether active balancing between modules is required according to the range and the balanced voltage judgment threshold, and if active balancing is required, proceeding to step S23a;

[0041] S23a, clustering and grouping are performed according to the mean value, and active balancing is performed between the battery modules according to the grouping result.

[0042] From the above description, it can be seen that the threshold value of the range and the balancing voltage is used to determine whether active balancing is required between battery modules. If active balancing is required, clustering and grouping are performed according to the mean value of the voltage to determine the battery modules with voltages lower than the mean and greater than the mean, and then active balancing is performed.

[0043] Furthermore, step S21a is specifically as follows:

[0044] Take the first and kth sampling data sets of the module voltage sampling data set respectively and The maximum value of the two is used as the equalization voltage judgment threshold. :

[0045] .

[0046] It can be seen from the above description that according to the above steps, the equalization voltage judgment threshold is determined.

[0047] Further, step S22a is specifically as follows:

[0048] Sort the voltage sampled for the kth time in the module voltage sampling data set and calculate the range. If the range is greater than the balanced voltage judgment threshold , it is considered that active balancing between modules is required, and the process goes to step S23a.

[0049] From the above description, it can be known that whether the voltage range of the k-th sampling is greater than the equalization voltage judgment threshold is used to confirm whether active equalization between battery modules is required.

[0050] Further, step S23a is specifically as follows:

[0051] Calculate the mean value of the voltage sampled for the kth time in the module voltage sampling data set , and divide the dataset into two subsets ;

[0052] Among them, all values ​​less than or equal to the mean The voltage value is classified into , otherwise ;

[0053] Control Dataset Maximum value The corresponding bidirectional active balancing converter of the battery module is started, and the battery module performs energy conversion to the auxiliary power supply direction, and the duration is for:

[0054] ;

[0055] in, For the dataset The minimum value in For the dataset The maximum value in is the adjustment coefficient, is the constant power of the bidirectional active balanced converter;

[0056] Computational Dataset The opening time of the bidirectional active balancing converter of the battery module corresponding to each value in forms a data set ;

[0057] Among them, The jth value among the h values V ml_k_j The start-up time of the bidirectional active balancing converter of the corresponding battery module:

[0058] ;

[0059] Get the dataset , the data set The data in the data set are sorted, and the bidirectional active balancing converters of the corresponding battery modules are turned on in sequence, and energy is converted from the auxiliary power supply to the module direction, and the work time is corresponding until the data set is The bidirectional active balancing converters of the battery modules corresponding to all the data have completed operation.

[0060] From the above description, it can be seen that the battery module with the largest voltage is discharged through the bidirectional active balancing converter, and each battery module with a voltage lower than the average receives the electric energy released by the battery module with the largest voltage at once, so that the incoming and outgoing energy are balanced.

[0061] Furthermore, according to the single cell voltage sampling data set of each of the battery modules, the single cells in the battery module are clustered and grouped, and passive balancing between the single cells is performed according to the grouping result, including the steps of:

[0062] S21b, for each of the battery modules, calculating the range and mean according to the single cell voltage sampling data set, and sorting them;

[0063] S22b: When the range difference is greater than the preset balancing threshold, all battery cells whose voltages are greater than the mean value are acquired to perform discharge passive balancing.

[0064] From the above description, it can be seen that whether balancing between battery cells is required is determined based on the range, and clustering is achieved based on the mean to obtain all battery cells with voltage greater than the mean for discharge passive balancing.

[0065] Furthermore, the passive discharge equalization is specifically:

[0066] Different PWM control is applied to each battery cell, and the duty cycle d of PWM is proportional to the degree to which the voltage of the battery cell deviates from the average value. For the jth battery cell that needs to be balanced in the battery module, there is :

[0067] ;

[0068] in, represents the voltage of the jth battery cell that needs to be balanced in the battery module, represents the mean value of the single cell voltage sampling data set, Indicates the maximum value in the single cell voltage sampling data set.

[0069] It can be seen from the above description that passive balancing is achieved by applying different PWM controls to the battery cells and adjusting the duty cycle.

[0070] Furthermore, the method further comprises the steps of:

[0071] S3. Repeat steps S1 and S2 until the balancing is completed.

[0072] From the above description, it can be seen that the execution is repeated until the balancing is completed to ensure the effectiveness of the balancing.

[0073] Please refer to Figure 2 , a cluster-based battery group balancing system, each battery cluster in the system includes multiple battery modules;

[0074] Each of the battery modules includes a plurality of battery cells, and is provided with a bidirectional active balancing converter and a battery cell management unit, wherein the bidirectional active balancing converter is used to realize a bidirectional flow of balanced energy between the low-voltage auxiliary power supply and the battery module, thereby realizing active balancing;

[0075] The battery cell management unit includes a microprocessor and an analog front end, and the battery cell management unit is communicatively connected with the battery module management unit for receiving control instructions, and the analog front end is used to realize passive balancing between single cells;

[0076] The battery cluster implements the steps in the above-mentioned clustering-based battery group balancing method based on the above structure.

[0077] The present invention discloses a clustering-based battery group balancing method and system, which are suitable for battery balancing of a battery energy storage system.

[0078] Please refer to Figure 1 , Embodiment 1 of the present invention is:

[0079] A battery group balancing method based on clustering includes the following steps:

[0080] S1. When the battery cluster charging is close to the end and the single cell overcharge protection is not reached, all battery modules in the same battery cluster are charged with equal temperature and voltage limit, and voltage sampling is performed at the battery module level and the battery cell level to obtain a module voltage sampling data set and a single cell voltage sampling data set;

[0081] Step S1 includes the steps of:

[0082] S11, collecting the voltage and charging current of N battery modules in the same battery cluster, and when the voltage of a module reaches a first preset charging voltage, reducing the charging current I C It is the preset ratio of the previous moment, and the single cell uniform temperature thermal management is started at the same time.

[0083] In this embodiment, the preset ratio is 0.5 times, and in other equivalent embodiments, it can be adjusted according to actual conditions.

[0084] In this embodiment, the voltages and charging currents of N modules in the same battery cluster are collected. When the voltage of a module reaches the first preset charging voltage, When the charging current is reduced I C It is 0.5 times of the previous moment, and the single cell temperature uniformity thermal management is started at the same time, so that the temperatures of all M battery cells in all N modules in the same battery cluster tend to be consistent.

[0085] S12, each time a module voltage reaches the first charging preset voltage When the charging current is reduced I C is the preset ratio of the previous moment until the following conditions are met:

[0086] ;

[0087] Performing a first synchronous sampling on the voltages of the N battery modules;

[0088] in, V m_maxIt is the highest voltage of each battery module in the battery cluster. is the temperature difference of M battery cells, is the temperature extreme limit value, C 1 is the preset rate for average temperature and voltage limit charging. I CN is the rated charging current.

[0089] In this embodiment, when the module voltage reaches the first preset charging voltage each time, the IC is reduced to 0.5 times of the previous moment again until the above conditions are met, and the N module voltages are sampled synchronously for the first time. During the process, the average temperature thermal management is kept turned on.

[0090] Specifically, for the charged battery cluster, the voltages of N battery modules are collected synchronously to form a data set. ;

[0091] When the first two conditions are met, , then I C Drop to zero and keep the average temperature thermal management on until the temperature conditions are met After that, restore the rate Continue to charge the battery and Collecting data sets at all times .

[0092] S13, from the first synchronous sampling moment, maintain the charging current I C Keep unchanged, and perform k consecutive synchronous sampling until the voltage of any module reaches the second charging preset voltage :

[0093] ;

[0094] Obtaining the module voltage sampling data set;

[0095] S14, record the energy charged into the highest voltage module in k samplings:

[0096] ;

[0097] S15. In the kth sampling, the voltages of all battery cells in each battery module are collected to obtain the cell voltage sampling data set.

[0098] In this embodiment, from the first synchronous sampling moment, maintain I C Continue charging until the voltage of any module reaches the second charging preset voltage ,Right now During this period, k consecutive synchronous samplings are performed, and the energy charged into the highest voltage module in the k samplings is recorded.

[0099] S2, clustering the battery modules according to the module voltage sampling data set, and performing active balancing between the battery modules according to the grouping results; comprising the steps of:

[0100] S21a, calculating a balanced voltage judgment threshold according to the module voltage sampling data set;

[0101] Step S21a is specifically as follows:

[0102] Take the first and kth sampling data sets of the module voltage sampling data set respectively and The maximum value of the two is used as the equalization voltage judgment threshold. :

[0103] .

[0104] In this embodiment, the first and kth sampling data sets are taken respectively and The maximum value of the two is used as the module balance voltage judgment threshold.

[0105] S22a, sorting the voltage sampled for the kth time in the module voltage sampling data set, and calculating the range and the mean, judging whether active balancing between modules is required based on the range and the balanced voltage judgment threshold, and if active balancing is required, proceeding to step S23a.

[0106] Specifically, the voltage sampled for the kth time in the module voltage sampling data set is sorted, and the range is calculated. If the range is greater than the balanced voltage judgment threshold , it is considered that active balancing between modules is required, and the process goes to step S23a.

[0107] In this embodiment, The voltages in the module are sorted, the range and mean are calculated, the modules that need to be balanced are clustered and grouped according to the set threshold, and active balancing at the module level is implemented.

[0108] The reasons for imbalance between battery modules include long-term operation under conditions with large temperature differences, abnormal power consumption of the module's internal circuit, and different initial SOC or SOH due to maintenance or replacement of the module. In these cases, the consistency of cells within the same module may be better than that between cells in different modules. Passive balancing of cells will make the balancing time of all cells very long. Used to indicate the voltage imbalance threshold between modules.

[0109] In this embodiment, the module management unit (BMU) of the battery management system processes the data set. Sort the N voltage data in and get ,when , indicating that the module voltage extreme difference exceeds the consistency threshold and module-level balancing is required, that is, a module balancing condition is started.

[0110] S23a, performing clustering and grouping according to the mean value, and performing active balancing among the battery modules according to the grouping result;

[0111] Step S23a is specifically as follows:

[0112] Calculate the mean value of the voltage sampled for the kth time in the module voltage sampling data set , and divide the dataset into two subsets ;

[0113] Among them, all values ​​less than or equal to the mean The voltage value is classified into , otherwise ;

[0114] In this embodiment, the required balancing time is calculated based on the module consistency requirement threshold, the required balancing energy, the deviation degree between the highest voltage module and the average value, and the balancing power:

[0115] Control data set controlled by BMU Maximum value The corresponding bidirectional active balancing converter of the battery module is started, and the battery module performs energy conversion to the auxiliary power supply direction, and the duration is for:

[0116] ;

[0117] in, For the dataset The minimum value in For the dataset The maximum value in is the adjustment coefficient, is the constant power of the bidirectional active balancing converter.

[0118] In this embodiment, the energy loss caused by the converter efficiency is compensated by adjusting the coefficient s1.

[0119] Computational Dataset The opening time of the bidirectional active balancing converter of the battery module corresponding to each value in forms a data set ;

[0120] Among them, The jth value among the h values V ml_k_j The start-up time of the bidirectional active balancing converter of the corresponding battery module:

[0121] ;

[0122] Get the dataset , the data set The data in the data set are sorted, and the bidirectional active balancing converters of the corresponding battery modules are turned on in sequence, and energy is converted from the auxiliary power supply to the module direction, and the work time is corresponding until the data set is The bidirectional active balancing converters of the battery modules corresponding to all the data have completed operation.

[0123] In this embodiment, the BMU calculates the data set Each value in the corresponding module's converter start time dataset , and control these converters in the previous The corresponding bidirectional active balancing converters of the battery modules are started up simultaneously and sequentially, and energy is converted from the auxiliary power supply to the module. The data in the module are sorted, and the converters in the corresponding modules are turned on in sequence and work for the corresponding time, until all k converters finish their work and are turned off.

[0124] The energy transmitted by the converter in the maximum voltage module is received by k modules with voltages lower than the average value. The converters are turned on one by one from the longest to the shortest duration, so that the energy entering and flowing out of the auxiliary power supply line is balanced.

[0125] In this embodiment, when one round of balancing calculation cannot be completed within one balancing working condition cycle, new voltage collection and balancing time calculation are not performed in the next cycle until the current round of balancing is completed.

[0126] S3. Repeat steps S1 and S2 until the balancing is completed.

[0127] In this embodiment, when the battery cluster is working, each time the condition described in S1 is met, the above sampling-clustering-control process is repeated until The active balancing condition of this module ends at this time.

[0128] s 2 is the active balancing judgment hysteresis coefficient, which is generally set to 0.5~0.8.

[0129] According to the single cell voltage sampling data set of each of the battery modules, the single cells in the battery module are clustered and grouped, and passive balancing between the single cells is performed according to the grouping result, including the steps of:

[0130] S21b. For each of the battery modules, calculate the range and mean value according to the single cell voltage sampling data set, and sort them.

[0131] In this embodiment, the cell management unit (CSC) of the battery management system processes the cell voltage data set in this module. Sort all the data in and calculate the mean, and get and ,when At this time, the passive discharge balancing of all monomers with values ​​greater than the average value is started.

[0132] Among them, depending on the monomer type, The selection is generally from 0 to several hundred mV.

[0133] S22b: When the range difference is greater than the preset balancing threshold, all battery cells whose voltages are greater than the mean value are acquired to perform discharge passive balancing.

[0134] The passive discharge balancing is specifically:

[0135] Different PWM control is applied to each battery cell, and the duty cycle d of PWM is proportional to the degree to which the voltage of the battery cell deviates from the average value. For the jth battery cell that needs to be balanced in the battery module, there is :

[0136] ;

[0137] in, represents the voltage of the jth battery cell that needs to be balanced in the battery module, represents the mean value of the single cell voltage sampling data set, Indicates the maximum value in the single cell voltage sampling data set.

[0138] In this embodiment, passive balancing is achieved by applying different PWM controls to the balancing circuit corresponding to each cell by the analog front end (AFE) chip on the CSC, and the duty cycle d of the PWM is proportional to the degree to which the cell voltage deviates from the average value.

[0139] S3. Repeat steps S1 and S2 until the balancing is completed.

[0140] In this embodiment, steps S21b and S22b are repeatedly executed at each voltage collection moment. The equilibrium ends.

[0141] s3 is the passive equalization judgment hysteresis coefficient, which is generally set to 0.5~0.8.

[0142] Please refer to Figure 2 , Embodiment 2 of the present invention is:

[0143] A cluster-based battery group balancing system, each battery cluster in the system includes multiple battery modules;

[0144] Each of the battery modules includes a plurality of battery cells, and is provided with a bidirectional active balancing converter and a battery cell management unit, wherein the bidirectional active balancing converter is used to realize a bidirectional flow of balanced energy between the low-voltage auxiliary power supply and the battery module, thereby realizing active balancing;

[0145] In this embodiment, each of the N battery modules in the battery cluster contains an isolated bidirectional active balancing converter, which can realize the balanced bidirectional flow of energy between the low-voltage auxiliary power supply and the battery module, and realize the energy of one battery module to be transferred to another battery module through the auxiliary power supply line.

[0146] The battery cell management unit includes a microprocessor and an analog front end, and the battery cell management unit is communicatively connected with the battery module management unit for receiving control instructions, and the analog front end is used to achieve passive balancing between single cells.

[0147] In this embodiment, the start and stop and power regulation of the bidirectional active balancing converter in each battery module are controlled by the battery cell management unit (CSC) in the battery module. There is communication between the CSC and the battery module management unit (BMU) for receiving control instructions. The CSC includes an MCU and an AFE (analog front end), wherein the MCU implements the start and stop and power control of the balancing converter.

[0148] Description: The converter of a battery module steps down the module voltage to a low-voltage auxiliary power supply of 12V or 24V, while the converter of another module steps up the 12V or 24V to the module voltage, thus realizing the energy transfer between the two modules.

[0149] The battery cluster implements the steps in the above-mentioned clustering-based battery group balancing method based on the above structure.

[0150] In summary, the clustering-based battery group balancing method and system of the present invention eliminates the influence of temperature, realizes the clustering of battery modules and battery cells according to voltage, and according to the clustering results, performs active balancing between battery modules and passive balancing between battery cells in the battery modules to achieve more effective battery balancing.

[0151] The present invention adopts active balancing between modules and passive balancing within the modules; the control is based on the OV method, and the influence of temperature is eliminated at the same time, forming a hierarchical balancing strategy based on clustering ideas and an active balancing circuit.

[0152] For energy storage systems with a large number of battery cells, the general passive balancing method discharges and balances high-voltage battery cells within the entire battery cluster. When high and low voltage battery cells are relatively concentrated in a certain battery module, the balancing efficiency is low, resulting in energy waste. Module-level active balancing is achieved without adding too many circuits and converters, which is conducive to the automatic maintenance and operation of energy storage batteries and the correction of consistency deviations caused by differences in working conditions or environments. The balance of energy flowing out of the battery module and into the battery module ensures that the auxiliary power line does not cause excessive fluctuations.

[0153] While balancing at the module level, passive balancing at the monomer level adopts a clustering grouping method, which is also beneficial to improving balancing efficiency.

[0154] The balanced sampling point is selected at the low current stage before the end of charging, which reduces the impact of current on the operating voltage sampling and avoids static waiting. At the same time, temperature consistency and average temperature collection strategy are also considered to achieve dimensionality reduction of SOC data, reduce calculation load and increase accuracy.

[0155] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A battery group balancing method based on clustering, characterized in that: Includes steps: S1. When the battery cluster charging is close to the end and the single cell overcharge protection is not reached, all battery modules in the same battery cluster are charged with equal temperature and voltage limit, and voltage sampling is performed at the battery module level and the battery cell level to obtain a module voltage sampling data set and a single cell voltage sampling data set; Step S1 includes the steps of: S11, collecting the voltage and charging current of N battery modules in the same battery cluster, and when the voltage of a module reaches the first preset charging voltage, reducing the charging current I C The preset ratio is the same as the previous moment, and the single-cell uniform temperature thermal management is started at the same time; S12, each time a module voltage reaches the first charging preset voltage When the charging current I C is the preset ratio of the previous moment until the following conditions are met: ； Performing a first synchronous sampling on the voltages of the N battery modules; Among them, V m_max It is the highest voltage of each battery module in the battery cluster. is the temperature difference of M battery cells, is the temperature extreme difference limit value, C1 is the preset rate of average temperature and voltage limit charging, I CN is the rated charging current; S13, from the first synchronous sampling moment, maintain the charging current I C Keep unchanged, and perform k consecutive synchronous sampling until the voltage of any module reaches the second charging preset voltage : ； Obtaining the module voltage sampling data set; S14, record the energy charged into the highest voltage module in k samplings: ； S15, in the kth sampling, collecting the voltages of all battery cells in each battery module to obtain the cell voltage sampling data set; S2. Clustering the battery modules according to the module voltage sampling data set, and performing active balancing among the battery modules according to the clustering results; The single cells in the battery module are clustered and grouped according to the single cell voltage sampling data set of each battery module, and passive balancing is performed between the single cells according to the grouping result.

2. A clustering-based battery group balancing method according to claim 1, characterized in that: In step S2, the battery modules are clustered and grouped according to the module voltage sampling data set, and active balancing is performed between the battery modules according to the grouping result, including the steps of: S21a, calculating a balanced voltage judgment threshold according to the module voltage sampling data set; S22a, sorting the voltage sampled for the kth time in the module voltage sampling data set, and calculating the range and the mean, judging whether active balancing between modules is required according to the range and the balanced voltage judgment threshold, and if active balancing is required, proceeding to step S23a; S23a, clustering and grouping are performed according to the mean value, and active balancing is performed between the battery modules according to the grouping result.

3. A clustering-based battery group balancing method according to claim 2, characterized in that: Step S21a is specifically as follows: Take the first and kth sampling data sets of the module voltage sampling data set respectively and The maximum value of the two is used as the equalization voltage judgment threshold. : 。 4. The clustering-based battery group balancing method according to claim 2, characterized in that: Step S22a is specifically as follows: Sort the voltage sampled for the kth time in the module voltage sampling data set and calculate the range. If the range is greater than the balanced voltage judgment threshold , it is considered that active balancing between modules is required, and the process goes to step S23a.

5. The clustering-based battery group balancing method according to claim 2, characterized in that: Step S23a is specifically as follows: Calculate the mean value of the voltage sampled for the kth time in the module voltage sampling data set , and divide the dataset into two subsets ; Among them, all values ​​less than or equal to the mean The voltage value is classified into , otherwise ; Control Dataset Maximum value The corresponding bidirectional active balancing converter of the battery module is started, and the battery module performs energy conversion to the auxiliary power supply direction, and the duration is for: ； in, For the dataset The minimum value in For the dataset The maximum value in is the adjustment coefficient, is the constant power of the bidirectional active balanced converter; Computational Dataset The opening time of the bidirectional active balancing converter of the battery module corresponding to each value in forms a data set ; Among them, The jth value among the h values V ml_k_j The start-up time of the bidirectional active balancing converter of the corresponding battery module: ； Get the dataset , the dataset The data in the data set are sorted, and the bidirectional active balancing converters of the corresponding battery modules are turned on in sequence, and energy is converted from the auxiliary power supply to the module direction, and the work time is corresponding until the data set is The bidirectional active balancing converters of the battery modules corresponding to all the data have completed operation.

6. The clustering-based battery group balancing method according to claim 1, characterized in that: According to the single cell voltage sampling data set of each of the battery modules, the single cells in the battery module are clustered and grouped, and passive balancing between the single cells is performed according to the grouping result, including the steps of: S21b, for each of the battery modules, calculating the range and mean according to the single cell voltage sampling data set, and sorting them; S22b: When the range difference is greater than the preset balancing threshold, all battery cells whose voltages are greater than the mean value are acquired to perform discharge passive balancing.

7. A clustering-based battery group balancing method according to claim 6, characterized in that: The passive discharge balancing is specifically: Different PWM control is applied to each battery cell, and the duty cycle d of PWM is proportional to the degree to which the voltage of the battery cell deviates from the average value. For the jth battery cell that needs to be balanced in the battery module, there is : ； in, represents the voltage of the jth battery cell that needs to be balanced in the battery module, represents the mean value of the single cell voltage sampling data set, Indicates the maximum value in the single cell voltage sampling data set.

8. The clustering-based battery group balancing method according to claim 1, characterized in that: Also includes the steps: S3. Repeat steps S1 and S2 until the balancing is completed.

9. A cluster-based battery group balancing system, characterized in that: Each battery cluster in the system includes multiple battery modules; Each of the battery modules includes a plurality of battery cells, and is provided with a bidirectional active balancing converter and a battery cell management unit, wherein the bidirectional active balancing converter is used to realize a bidirectional flow of balanced energy between the low-voltage auxiliary power supply and the battery module, thereby realizing active balancing; The battery cell management unit includes a microprocessor and an analog front end, and the battery cell management unit is communicatively connected with the battery module management unit for receiving control instructions, and the analog front end is used to realize passive balancing between single cells; The battery cluster implements the steps in a clustering-based battery group balancing method according to any one of claims 1 to 8 based on the above structure.

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