Dynamic control method of lithium battery module intelligent equalization management system

Abstract

The invention discloses a dynamic control method of a lithium battery module intelligent equalization management system, and relates to the field of lithium battery module equalization, and the method comprises the steps: constructing a hierarchical data fusion platform, and generating a battery state data set containing SOC, SOH and an inconsistency evaluation value; a credibility reasoning algorithm is adopted to calculate a single body imbalance credibility factor value to divide an equalization stage, and equalization current is dynamically adjusted; a charge and discharge curve health factor is extracted through an LAB health factor algorithm, SOH is updated online in combination with extended Kalman filtering, and an SOH attenuation rate is fed back to the battery model; in-module equalization is carried out through a bidirectional energy transfer circuit, inter-module equalization is carried out through a ring bus topology, and layered topology linkage control is formed. The method has the advantages that the consistency and the heat management efficiency of the battery pack are improved through the hybrid equalization strategy and the layered topology linkage control, the service life of the battery pack is prolonged, and the overall performance and the safety of the electric vehicle are improved.

Description

Technical Field

[0001] The present invention relates to the field of lithium battery module balance management, and in particular to a dynamic control method for an intelligent balance management system for lithium battery modules. Background Art

[0002] In electric vehicles, battery packs typically consist of multiple cells connected in series or parallel to provide the required voltage and capacity. Due to differences in production processes, material properties, and operating environments, there are certain inconsistencies between the individual cells. This inconsistency can lead to capacity decay, shortened lifespan, and reduced safety during battery pack operation. In particular, when the performance of a single cell in a battery pack degrades, it can affect the performance of the entire pack and even cause safety issues.

[0003] Furthermore, lithium-ion batteries generate heat during the charging and discharging process. If this heat cannot be dissipated promptly, the battery temperature will rise, affecting its performance and safety. This heat generation is particularly significant during high-power charging and discharging. Traditional air cooling methods are inefficient, and while liquid cooling systems offer good heat dissipation, they are complex and costly. Therefore, effectively managing battery pack heat and ensuring that the batteries operate within an appropriate temperature range is another pressing issue. Summary of the Invention

[0004] In order to solve the above technical problems, a dynamic control method for an intelligent balancing management system of a lithium battery module is provided. This technical solution solves the problems raised in the above background technology, such as low consistency and low thermal management efficiency of the battery pack, which leads to low energy utilization, slow balancing speed, high cost and insufficient safety.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A dynamic control method for a lithium battery module intelligent balancing management system, comprising:

[0007] The voltage, current, and temperature data of each single battery in the module are collected in real time. Based on the historical cycle count, temperature stress, and capacity decay rate of the lithium battery module, the aging coupling factor is calculated in combination with the internal resistance change rate. The battery model parameters are dynamically corrected using the aging coupling factor. A hierarchical data fusion platform is constructed to generate a battery status data set containing SOC, SOH, and inconsistency assessment values. The battery model is a Thevenin equivalent circuit model.

[0008] Based on the battery status data set, a credibility inference algorithm is used to calculate the cell imbalance credibility factor value to divide the balancing stage, and the balancing current is dynamically adjusted according to the product of the credibility factor value and the temperature entropy value;

[0009] Extract the charge and discharge curve health factor through the LAB health factor algorithm, update the SOH online in combination with the extended Kalman filter, feedback the SOH attenuation rate to the battery model, and perform collaborative management of SOC and SOH;

[0010] Based on the single-cell imbalance credibility factor value, perform in-module balancing through the bidirectional energy transfer circuit, calculate the range difference of SOC between modules, and perform inter-module balancing through the ring bus topology to form a hierarchical topology linkage control.

[0011] Preferably, the calculation of the single-cell imbalance credibility factor value to divide the balancing stage and dynamically adjust the balancing current according to the product of the credibility factor value and the temperature entropy value specifically includes:

[0012] Based on the SOC and inconsistency evaluation values in the battery state dataset, calculate the imbalance credibility factor value of each single-cell battery through the credibility reasoning algorithm;

[0013] Based on the historical battery state dataset, obtain the specific quantiles of the historical data distribution as the boundaries of the low-credibility stage and the high-credibility stage, divide the balancing stage according to the imbalance credibility factor value. When the imbalance credibility factor value is lower than the boundary of the low-credibility stage, record it as the low-credibility stage and turn off the balancing circuit;

[0014] When the imbalance credibility factor value is between the boundary of the low-credibility stage and the boundary of the high-credibility stage, record it as the medium-credibility stage and start small-current balancing. The balancing current is less than the charge and discharge current and is the rated capacity of the battery;

[0015] When the imbalance credibility factor value is greater than the boundary of the high-credibility stage, record it as the high-credibility stage and start large-current balancing. The balancing current is greater than the product of the imbalance credibility factor value and the maximum current;

[0016] Real-time monitor the dynamic correction result of the aging coupling factor on its own correction weight, and adaptively adjust the amplitude of the balancing current.

[0017] Preferably, the collaborative management of SOC and SOH specifically includes:

[0018] Based on the SOH value in the battery state dataset, determine the attenuation level of each single-cell battery and assign a differentiated initial window;

[0019] Dynamically adjust the balancing target SOC range according to the attenuation level. For high-attenuation-level batteries, perform protective balancing operations and limit their charge and discharge depth. For low-attenuation-level batteries, maintain full-SOC-range balancing;

[0020] Dynamically adjust the amplitude of the balancing current according to the attenuation level. High-attenuation-level batteries use a balancing current lower than the rated value, and low-attenuation-level batteries use a rated or higher-than-rated balancing current;

[0021] Calculate the equalization priority weight of the battery based on the attenuation level and the current SOC value, and preferentially supplement energy to healthy batteries and perform protective equalization operations on highly attenuated batteries.

[0022] Preferably, determining the attenuation level of each single battery based on the SOH value in the battery state dataset and assigning a differentiated initial window specifically includes:

[0023] Obtain the general health threshold standards of 80% and 90% in the battery industry, divide the attenuation level intervals according to the SOH attenuation rate. If the SOH of a single battery is greater than 90%, it is marked as a low attenuation level; when the SOH of a single battery is between 80% and 90%, it is marked as a medium attenuation level; when the SOH of a single battery is less than 80%, it is marked as a high attenuation level.

[0024] Assign differentiated SOC equalization initial window thresholds based on different attenuation levels, couple the attenuation level, temperature coefficient, and operating condition coefficient to obtain low attenuation window thresholds, medium attenuation window thresholds, and high attenuation window thresholds, which respectively correspond to the initial SOC equalization window thresholds of batteries with different attenuation levels.

[0025] Real-time monitor the change of the SOH attenuation rate. If the change amount of the SOH attenuation rate exceeds the dynamic threshold in three consecutive updates, dynamically adjust the SOC equalization window threshold of the corresponding attenuation level in equal proportion. The dynamic threshold is calculated through the temperature mutation coefficient.

[0026] Preferably, the output power states of batteries with different attenuation levels during charge and discharge are as follows:

[0027] The output current capacity of low attenuation level batteries is less than the rated current, the output current capacity of medium attenuation level batteries is 80%-100% of the rated current, and the output current capacity of high attenuation level batteries is less than 80% of the rated current.

[0028] When the module supplies power, the system dynamically distributes the current load according to the attenuation level, so that the current output ratio of highly attenuated batteries does not exceed 80% of their rated capacity.

[0029] Preferably, for highly attenuated batteries, performing protective equalization operations and restricting their charge and discharge depth specifically includes:

[0030] Real-time obtain the temperature data of the target single battery, dynamically calculate the safety window boundary based on the mapping relationship between temperature and boundary values, update the safety window, and for highly attenuated batteries, narrow the equalization target SOC range to within the safety window.

[0031] For low - attenuation - level batteries, maintain balance across the entire SOC range and set a hysteresis interval at the safety window boundary to avoid frequent switching of the balanced state.

[0032] Preferably, the dynamic proportional adjustment of the SOC balance window threshold corresponding to the attenuation level specifically includes:

[0033] Based on the manufacturer data of the lithium - battery module, obtain the aging characteristics of the battery and obtain the reference threshold δ pre - calibrated by the battery aging characteristics base ;

[0034] Based on the pre - calibrated fixed parameters of the thermal stability of the battery material system, the temperature - change characteristics of the application scenario, and the safety - risk level, obtain the preset temperature - gradient threshold T grad , calculate the current temperature change rate and the ratio with the preset temperature - gradient threshold T grad , determine the temperature - mutation coefficient K, and multiply the temperature - mutation coefficient K by the reference threshold to obtain the dynamic threshold δ;

[0035] Real - time monitor the change amount ΔSOH of the SOH attenuation rate. When ΔSOH exceeds the dynamic threshold δ in three consecutive updates, adjust the SOC balance window threshold, and the adjustment amplitude ΔV window satisfies: , where β is the scaling factor and V window0 is the initial window threshold.

[0036] Preferably, the dynamic calculation of the safety - window boundary based on the mapping relationship between temperature and boundary values specifically includes:

[0037] Define continuous functions of temperature T and the upper safety - boundary voltage V max (T) and the lower limit V min (T) according to the battery electrochemical characteristics of the lithium - battery module, and establish a temperature - safety - boundary mapping function;

[0038] Real - time collect the temperature data of single cells and calculate the dynamic safety boundary at the current temperature through piece - wise linear interpolation: when T ∈ [T1, T2], the safety - window boundary is the fixed interval [V min(base) , V max(base) , where T1 and T2 are the temperature critical points calibrated by material characteristics, [T1, T2] is the normal temperature range, and V min(base) and V max(base) are the charging upper limit and charging lower limit of the lithium batteries in the lithium - battery module respectively;

[0039] When T < T1, it is recorded as the low - temperature zone, and the safety - window lower limit is adjusted to , is the low - temperature boundary compensation coefficient;

[0040] When T > T2, it is denoted as the upper limit of the safety window in the high-temperature region is adjusted to , where β is the high-temperature boundary attenuation coefficient;

[0041] Input the updated safety boundary value into the hysteresis comparator, and combine it with the adjusted SOC equalization window threshold to generate the final safe operating range for high-attenuation-level batteries.

[0042] Preferably, the formation of the hierarchical topology linkage control specifically includes:

[0043] Based on the single-cell imbalance credibility factor value, perform two-way energy transfer through the energy transfer interface of the silicon carbide MOSFET device to achieve energy balance between single cells within the module.

[0044] Calculate the range of SOC between different battery modules. When the range of SOC between modules exceeds the preset threshold, trigger inter-module equalization.

[0045] Directly connect the energy transfer interfaces of each battery module to form a closed-loop path, construct a ring bus topology, and directly transfer energy across modules through the bus to dynamically correct the range of SOC between modules. Among them, the intra-module equalization and the inter-module equalization are linked through the ring bus topology to synchronously reduce the inconsistency between single cells and between modules.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] The present invention proposes a dynamic control method for an intelligent equalization management system of a lithium battery module. By dynamically selecting the equalization method, it realizes efficient energy management of single cells, forms a hybrid equalization strategy that combines the advantages of active equalization and passive equalization. It can not only actively equalize the battery power through energy transfer to avoid energy waste and improve energy utilization efficiency, but also dynamically select the equalization method, which can quickly respond to the state changes of single cells and shorten the equalization time. At the same time, compared with pure active equalization, the hybrid equalization strategy reduces complex circuit design, reduces system costs, and also avoids overcharging and over-discharging through dynamic threshold judgment, improving the safety of the battery pack.

[0048] The present invention proposes a dynamic control method for an intelligent equalization management system of a lithium battery module. By constructing a hierarchical data fusion platform and topology structure, the underlying inductor is used to achieve energy transfer between single cells, and the top-level transformer is used to achieve energy equalization between battery modules, thereby realizing energy equalization between single cells and between battery modules. The hierarchical topology structure reduces the energy transfer path through "intra-module local equalization + inter-module global equalization", improves the equalization speed and accuracy, simplifies the system design, reduces additional equalization circuits and interfaces, and improves the reliability and maintainability of the system. At the same time, through bidirectional energy transfer and ring bus topology, the system can quickly respond to the SOC difference between single cells and battery modules, dynamically adjust energy transfer, and the underlying energy storage inductor is small in size and low in cost, and the top-level multi-winding transformer realizes bidirectional equalization of any single cell, taking into account both efficiency and cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a schematic flow chart of the present invention;

[0050] Figure 2 is a schematic flow chart of calculating the imbalance credibility factor value of a single cell to divide the equalization stage and dynamically adjusting the equalization current according to the product of the credibility factor value and the temperature entropy value in the present invention;

[0051] Figure 3 is a schematic flow chart of performing collaborative management of SOC and SOH in the present invention;

[0052] Figure 4 is a schematic flow chart of determining the attenuation level of each single cell based on the SOH value in the battery state dataset of the present invention and assigning a differentiated initial window;

[0053] Figure 5 is a schematic flow chart of the output state performance of batteries with different attenuation levels during charge and discharge in the present invention;

[0054] Figure 6 is a schematic flow chart of performing a protective equalization operation on high-attenuation-level batteries and restricting their charge and discharge depth in the present invention;

[0055] Figure 7 is a schematic flow chart of dynamically adjusting the SOC equalization window threshold corresponding to the attenuation level in equal proportion in the present invention;

[0056] Figure 8 is a schematic flow chart of dynamically calculating the safety window boundary based on the mapping relationship between temperature and boundary values in the present invention;

[0057] Figure 9 is a schematic flow chart of forming hierarchical topology linkage control in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0058] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and other obvious variations can be conceived by those skilled in the art.

[0059] Referring to Figure 1 as shown, a dynamic control method for an intelligent equalization management system of a lithium battery module includes:

[0060] Real-time collect the voltage, current, and temperature data of each single battery in the module, calculate the aging coupling factor based on the historical cycle times, temperature stress, and capacity attenuation rate of the lithium battery module, combined with the internal resistance change rate, dynamically correct the battery model parameters through the aging coupling factor, construct a hierarchical data fusion platform, generate a battery state data set including SOC, SOH, and inconsistency evaluation values, and the battery model is a Thevenin equivalent circuit model;

[0061] Based on the battery state data set, adopt a credibility inference algorithm, calculate the single-cell imbalance credibility factor value to divide the equalization stage, and dynamically adjust the equalization current according to the product of the credibility factor value and the temperature entropy value;

[0062] Extract the charge and discharge curve health factor through the LAB health factor algorithm, update the SOH online in combination with the extended Kalman filter, feedback the SOH attenuation rate to the battery model, and perform collaborative management of SOC and SOH;

[0063] Based on the single-cell imbalance credibility factor value, perform in-module equalization through a bidirectional energy transfer circuit, calculate the range of SOC between modules, and perform inter-module equalization through a ring bus topology to form a hierarchical topology linkage control.

[0064] Real-time collection of the voltage, current, and temperature data of each single battery in the module is the basis. These data not only reflect the immediate state of the battery but also provide necessary information for subsequent equalization management. The historical cycle times, temperature stress, and capacity attenuation rate of the lithium battery module, combined with the internal resistance change rate to calculate the aging coupling factor, can provide an in-depth understanding and modeling of the battery aging process, and the calculation of the aging coupling factor helps to dynamically correct the battery model parameters to ensure that the model can accurately reflect the actual state of the battery.

[0065] Constructing a hierarchical data fusion platform is a key step in generating a battery state data set. By fusing data at different levels, a battery state data set including SOC (state of charge), SOH (state of health), and inconsistency evaluation values can be generated. The battery model adopts a Thevenin equivalent circuit model, which can effectively describe the electrochemical behavior of the battery.

[0066] In terms of the collaborative management of SOC and SOH, the health factors of the charge and discharge curves are extracted through the LAB health factor algorithm, and the SOH is updated online by combining the extended Kalman filter. This can not only monitor the health status of the battery in real time, but also feedback the SOH decay rate to the battery model to achieve the collaborative management of SOC and SOH. Thus, it can more accurately reflect the actual state of the battery and improve the accuracy and efficiency of battery management.

[0067] In terms of the equalization management, based on the single-cell imbalance credibility factor value, the in-module equalization is carried out through the bidirectional energy transfer circuit. That is, the energy balance between single cells can be achieved through the energy transfer interface to ensure that the single cells in the battery pack can maintain a consistent state. Calculate the range of SOC between modules, and perform inter-module equalization through the ring bus topology to form a hierarchical topology linkage control. This can not only effectively reduce the inconsistency between single cells and between modules, but also improve the response speed and equalization efficiency of the system.

[0068] Thus, the battery equalization management can be carried out more accurately, and the consistency and overall performance of the battery pack can be improved. By dynamically correcting the battery model parameters and monitoring the battery state in real time, the system can better adapt to the aging of the battery and environmental changes, and extend the service life of the battery pack. In addition, the hierarchical topology linkage control structure not only simplifies the system design, but also improves the reliability and maintainability of the system.

[0069] Refer to Figure 2 As shown, the specific steps of dividing the equalization stage according to the calculated single-cell imbalance credibility factor value and dynamically adjusting the equalization current based on the product of the credibility factor value and the temperature entropy value are as follows:

[0070] Based on the SOC and inconsistency evaluation values in the battery state dataset, calculate the imbalance credibility factor values of each single cell through the credibility inference algorithm;

[0071] Based on the historical battery state dataset, obtain the specific quantiles of the historical data distribution as the boundaries of the low-credibility stage and the high-credibility stage. Divide the equalization stage according to the imbalance credibility factor value. When the imbalance credibility factor value is lower than the boundary of the low-credibility stage, record it as the low-credibility stage and turn off the equalization circuit;

[0072] When the imbalance credibility factor value is between the boundary of the low-credibility stage and the boundary of the high-credibility stage, record it as the medium-credibility stage and start the small-current equalization. The equalization current is less than the charge and discharge current and is the rated capacity of the battery;

[0073] When the imbalance credibility factor value is greater than the boundary of the high-credibility stage, record it as the high-credibility stage and start the large-current equalization. The equalization current is greater than the product of the imbalance credibility factor value and the maximum current;

[0074] Monitor the dynamic correction result of the aging coupling factor on its own correction weight in real time, and adaptively adjust the amplitude of the balancing current.

[0075] By collecting the voltage, current, and temperature data of each single battery in the module in real time, and combining the historical cycle times, temperature stress, and capacity attenuation rate of the lithium battery module, calculate the aging coupling factor. Then, the battery model parameters can be dynamically corrected through the aging coupling factor, a hierarchical data fusion platform can be constructed, and a battery state dataset including SOC (state of charge), SOH (state of health), and inconsistency evaluation values can be generated. According to the SOC and inconsistency evaluation values in the battery state dataset, use the credibility inference algorithm to calculate the unbalance credibility factor value of each single battery. In the credibility inference algorithm, it can identify which single batteries are in an unbalanced state and evaluate the degree of their unbalance.

[0076] Based on the historical battery state dataset, the specific quantiles of the historical data distribution can be obtained as the boundaries between the low credibility stage and the high credibility stage. When the unbalance credibility factor value is lower than the boundary of the low credibility stage, the system shuts down the balancing circuit to avoid unnecessary energy consumption and potential safety risks; when the unbalance credibility factor value is between the boundaries of the low credibility stage and the high credibility stage, the system starts small current balancing, and the current of the small current balancing is less than the charge and discharge current, ensuring that the SOC of the single battery is gradually adjusted without affecting the battery performance and reducing the inconsistency; when the unbalance credibility factor value is greater than the boundary of the high credibility stage, the system starts large current balancing, and the current of the large current balancing is greater than the product of the unbalance credibility factor value and the maximum current, which can quickly adjust the SOC of the single battery and rapidly reduce the inconsistency.

[0077] At the same time, monitor the dynamic correction result of the aging coupling factor on its own correction weight in real time, and adaptively adjust the amplitude of the balancing current. Then, according to the aging state and environmental changes of the battery, the balancing current can be dynamically adjusted to ensure the effectiveness and safety of the balancing management, achieve different current sizes in different balancing stages, improve the balancing efficiency, and reduce the balancing time.

[0078] Refer to Figure 3 As shown, the specific implementation of the collaborative management of SOC and SOH includes:

[0079] Based on the SOH value in the battery state dataset, determine the attenuation level of each single battery and assign a differentiated initial window;

[0080] Dynamically adjust the balancing target SOC range according to the attenuation level. For high attenuation level batteries, perform protective balancing operations and limit their charge and discharge depth. For low attenuation level batteries, maintain full SOC range balancing;

[0081] Dynamically adjust the equalization current amplitude according to the attenuation level. Batteries with a high attenuation level use an equalization current lower than the rated value, while batteries with a low attenuation level use the rated or a higher-than-rated equalization current;

[0082] Based on the attenuation level and the current SOC value, calculate the equalization priority weight of the battery, and preferentially replenish energy for healthy batteries and perform protective equalization operations on high-attenuation batteries.

[0083] During control, first, based on the SOH value in the battery state dataset, determine the attenuation level of each single battery. Generally, batteries with an SOH value greater than 90% are marked as having a low attenuation level, those between 80% and 90% are marked as having a medium attenuation level, and those less than 80% are marked as having a high attenuation level. According to these attenuation levels, the system assigns different initial window thresholds, which are coupled with the temperature coefficient and the operating condition coefficient to ensure that batteries with different attenuation levels can be appropriately equalized and managed in the initial stage. After determining the attenuation level, dynamically adjust the equalization target SOC range according to these levels. For batteries with a high attenuation level, the system performs protective equalization operations to limit their charge and discharge depth to avoid further attenuation caused by overuse. For batteries with a low attenuation level, full-SOC-range equalization is maintained to ensure their efficient operation throughout the working range.

[0084] Secondly, the amplitude of the equalization current is also dynamically adjusted according to the attenuation level of the battery. Batteries with a high attenuation level use an equalization current lower than the rated value to reduce the additional stress on them, while batteries with a low attenuation level can use the rated or a higher-than-rated equalization current to accelerate the equalization process. The differential current adjustment strategy helps to improve the equalization efficiency while ensuring the safety of the battery.

[0085] At the same time, based on the attenuation level and the current SOC value, calculate the equalization priority weight of the battery. Healthy batteries (low attenuation level) are preferentially replenished with energy, while protective equalization operations are performed on high-attenuation batteries. This ensures the effective utilization of system resources and preferentially maintains the overall health status of the battery pack.

[0086] Thus, through differential initial windows and dynamic adjustment of the equalization target SOC range, batteries in different health states can be more precisely managed, avoiding the "one-size-fits-all" equalization strategy in traditional methods and improving the accuracy and efficiency of equalization. Secondly, the strategies of dynamically adjusting the equalization current amplitude and calculating the equalization priority weight not only improve the equalization efficiency but also extend the service life of the battery pack. Especially in the protective equalization operations of high-attenuation-level batteries, the risks of overcharging and over-discharging are significantly reduced. Finally, through real-time monitoring and dynamic adjustment, the adaptability and intelligence level of the system are enhanced, providing strong support for the efficient management and safe operation of the battery pack.

[0087] Refer toFigure 4 As shown, determining the attenuation levels of each single battery based on the SOH values in the battery state dataset and assigning differentiated initial windows specifically includes:

[0088] Obtain the general health threshold standards of 80% and 90% in the battery industry, divide the attenuation level intervals according to the SOH attenuation rate. If the SOH of a single battery is greater than 90%, it is marked as a low attenuation level; when the SOH of a single battery is between 80% and 90%, it is marked as a medium attenuation level; when the SOH of a single battery is less than 80%, it is marked as a high attenuation level.

[0089] Assign differentiated SOC equalization initial window thresholds based on different attenuation levels, couple the attenuation level, temperature coefficient, and working condition coefficient to obtain low attenuation window thresholds, medium attenuation window thresholds, and high attenuation window thresholds, which respectively correspond to the initial SOC equalization window thresholds of batteries with different attenuation levels.

[0090] Real-time monitor the change of the SOH attenuation rate. If the change amount of the SOH attenuation rate exceeds the dynamic threshold in three consecutive updates, dynamically adjust the SOC equalization window threshold of the corresponding attenuation level in equal proportion. The dynamic threshold is calculated through the temperature mutation coefficient.

[0091] Through industry data and experience, determine the general health threshold standards for the state of health (SOH) of the battery. Usually, 80% and 90% are set as the benchmarks for dividing the battery attenuation levels. According to the SOH value of a single battery, it is divided into three attenuation levels: when the SOH is greater than 90%, it is marked as a low attenuation level; when the SOH is between 80% and 90%, it is marked as a medium attenuation level; when the SOH is less than 80%, it is marked as a high attenuation level. Based on different attenuation levels, combined with the temperature coefficient and working condition coefficient, assign different SOC equalization initial window thresholds to each level. These thresholds are used to set the initial SOC range in the equalization management to ensure that batteries with different attenuation levels can be properly equalized managed at the initial stage. Through the setting of differentiated initial windows, it is possible to perform precise equalization management for batteries with different attenuation levels, avoiding the "one-size-fits-all" equalization strategy in traditional methods and improving the accuracy and efficiency of equalization.

[0092] Then, the change of the SOH attenuation rate is monitored in real time. If the change amount of the SOH attenuation rate exceeds the preset dynamic threshold in three consecutive updates, the SOC equalization window threshold corresponding to the attenuation level is adjusted dynamically in proportion. By differentiating the initial window and dynamically adjusting the equalization target SOC range, batteries in different health states can be better managed, the risks of overcharging and over-discharging of batteries with a high attenuation level can be reduced, and the service life of the battery pack can be extended. The dynamic threshold is calculated through the temperature mutation coefficient to ensure the effectiveness of equalization management under different working conditions. Thus, by differentiating the initial window and dynamically adjusting the equalization current amplitude, the system can improve the equalization efficiency on the premise of ensuring battery safety. Especially in the protective equalization operation of batteries with a high attenuation level, the risks of overcharging and over-discharging are significantly reduced. At the same time, the real-time monitoring and dynamic adjustment mechanism enable the system to perform adaptive management according to the actual state of the battery, enhancing the adaptability and intelligence level of the system, and providing strong support for the efficient management and safe operation of the battery pack.

[0093] Refer to Figure 5 As shown, the output power states of batteries with different attenuation levels during charge and discharge are as follows:

[0094] The output current capacity of low-attenuation-level batteries is less than the rated current, the output current capacity of medium-attenuation-level batteries is 80%-100% of the rated current, and the output current capacity of high-attenuation-level batteries is less than 80% of the rated current;

[0095] When the module supplies power, the system dynamically distributes the current load according to the attenuation level, so that the current output ratio of high-attenuation batteries does not exceed 80% of their rated capacity.

[0096] Different initial SOC equalization window thresholds are assigned to batteries according to different attenuation levels. These thresholds are obtained by coupling the attenuation level, temperature coefficient, and working condition coefficient, ensuring that batteries with different attenuation levels can be properly equalized managed in the initial stage. When the module supplies power, the current load is dynamically distributed according to the attenuation level of the battery. That is: the output current capacity of low-attenuation-level batteries can be close to the rated current, the output current capacity of medium-attenuation-level batteries is 80%-100% of the rated current, while the output current capacity of high-attenuation-level batteries is limited to less than 80% of the rated current. The differentiated current distribution strategy ensures that high-attenuation-level batteries will not be further accelerated in attenuation due to excessive current output, thus extending the service life of the battery pack.

[0097] Refer to Figure 6 As shown, for high-attenuation-level batteries, the implementation of protective equalization operation and the limitation of their charge and discharge depth specifically include:

[0098] Obtain the temperature data of the target single cell in real time, dynamically calculate the safety window boundary based on the mapping relationship between temperature and boundary values, update the safety window, and for batteries with a high attenuation level, narrow the balanced target SOC range to within the safety window;

[0099] For batteries with a low attenuation level, maintain the balance across the entire SOC range and set a hysteresis interval at the safety window boundary to avoid frequent switching of the balanced state.

[0100] By installing temperature sensors on each single cell, monitor the temperature and SOC status of each single cell in real time to ensure that the latest battery status information can be obtained at any time. Determine through experimental data or theoretical models to ensure that under different temperature conditions, the operating state of the battery is always mapped within the safe range. According to the collected temperature data, use the pre-set mapping relationship between temperature and boundary values to dynamically calculate the safety window boundary, and then, based on the calculated safety window boundary, narrow the balanced target SOC range to within the safety window to avoid the battery operating under extreme temperature conditions, thereby reducing the risk of thermal runaway. For batteries with a low attenuation level, maintain the balance across the entire SOC range, but set a hysteresis interval at the safety window boundary. The setting of the hysteresis interval can avoid frequent switching of the balanced state near the boundary, reduce unnecessary energy consumption and system burden, and ensure the stability and reliability of the balancing operation.

[0101] During its use, the strategy of dynamically adjusting the amplitude of the balancing current and calculating the balancing priority weight not only improves the balancing efficiency but also extends the service life of the battery pack. Especially in the protective balancing operation of batteries with a high attenuation level, the risks of overcharging and over-discharging are significantly reduced. Through real-time monitoring and dynamic adjustment, the adaptability and intelligent level of the system are enhanced, providing strong support for the efficient management and safe operation of the battery pack.

[0102] Refer to Figure 7 As shown, the specific steps for dynamically adjusting the SOC balancing window threshold corresponding to the attenuation level proportionally include:

[0103] Based on the manufacturer data of the lithium battery module, obtain the aging characteristics of the battery and get the reference threshold δ pre-calibrated by the battery aging characteristics base ;

[0104] Based on the fixed parameters pre-calibrated according to the thermal stability of the battery material system, the temperature change characteristics of the application scenario, and the safety risk level, obtain the preset temperature gradient threshold T grad , calculate the current temperature change rate and the ratio of the preset temperature gradient threshold T grad , determine the temperature mutation coefficient K, and multiply the temperature mutation coefficient K by the reference threshold to obtain the dynamic threshold δ;

[0105] Monitor the change ΔSOH of the SOH attenuation rate in real time. When ΔSOH exceeds the dynamic threshold δ in three consecutive updates, the SOC equalization window threshold is adjusted by an adjustment amplitude ΔV window Satisfy: , where β is a scaling factor, and V window0 is the initial window threshold.

[0106] Based on the manufacturer data of the lithium battery module, obtain the aging characteristics of the battery, including the performance changes of the battery under different usage conditions, such as capacity attenuation, internal resistance change, etc. Through these data, a reference threshold δ base can be pre-calibrated to reflect the impact of battery aging on the SOC equalization window threshold. Thus, considering the thermal stability of the battery material system, the temperature change characteristics of the application scenario, and the safety risk level, a set of fixed parameters are pre-calibrated to determine the preset temperature gradient threshold T grad . During actual operation, by calculating the ratio of the current temperature change rate to the preset temperature gradient threshold T grad , a temperature mutation coefficient K can be obtained, which reflects the degree of influence of temperature change on battery performance. Multiply the temperature mutation coefficient K by the reference threshold δ base to obtain a dynamic threshold δ. This dynamic threshold can reflect the influence of temperature change on battery aging characteristics in real time, thereby providing a basis for subsequent adjustment of the SOC equalization window threshold, enabling the dynamic adjustment of the equalization window threshold to appropriately expand the equalization window, accelerate the equalization speed, reduce the equalization time when the battery aging degree is relatively high, avoid overcharging or over-discharging problems caused by improper equalization when the battery is severely aged, and improve the safety of the system.

[0107] That is, during the overall operation period, the change ΔSOH of the SOH (state of health) attenuation rate can be monitored in real time. When ΔSOH exceeds the dynamic threshold δ in three consecutive updates, it indicates that the aging state of the battery has changed significantly. At this time, dynamically adjusting the SOC equalization window threshold according to the aging state of the battery can better adapt to the aging characteristics of the battery under different working conditions, improve the accuracy of equalization management, and ensure the effectiveness and safety of equalization management at the same time.

[0108] Refer to Figure 8 shown, the dynamic calculation of the safety window boundary based on the mapping relationship between temperature and boundary values specifically includes:

[0109] Define a continuous function of temperature T and the upper safety boundary voltage V max (T) and the lower limit V min (T) according to the battery electrochemical characteristics of the lithium battery module, and establish a temperature-safety boundary mapping function;

[0110] Real-time collect the temperature data of single cells, and calculate the dynamic safety boundary at the current temperature through piecewise linear interpolation: when T ∈ [T1, T2], the safety window boundary is a fixed interval [V min(base) , V max(base) , where T1 and T2 are the temperature critical points calibrated by material properties, [T1, T2] is the normal temperature range, V min(base) and V max(base) are respectively the upper charge limit and the lower charge limit of the lithium batteries in the lithium battery module;

[0111] When T < T1, it is recorded as the low-temperature area, and the safety window lower limit is adjusted to , is the low-temperature boundary compensation coefficient;

[0112] When T > T2, it is recorded as the high-temperature area, and the safety window upper limit is adjusted to , where β is the high-temperature boundary attenuation coefficient;

[0113] Input the updated safety boundary value into the hysteresis comparator, and combine with the adjusted SOC equalization window threshold to generate the final safe operating range of the high-decay-level battery.

[0114] According to the electrochemical characteristics of the lithium battery module, based on the electrochemical properties and thermodynamic characteristics of the battery materials calibrated through experimental data and theoretical models, define the continuous functions of temperature T and the upper safety boundary voltage V max (T) and the lower limit V min (T), which reflect the influence of temperature change on the battery voltage safety boundary, ensure that the operating voltage of the battery is always within the safe range at different temperatures, that is, real-time collect the temperature data of single cells, and calculate the dynamic safety boundary at the current temperature through piecewise linear interpolation. That is, by dynamically calculating the safety window boundary, ensure that the operating voltage of the battery is always within the safe range at different temperature conditions, significantly improve the safety of the battery, and reduce the risk of thermal runaway.

[0115] When the temperature T is in the predetermined normal temperature range [T1, T2], the safety window boundary is set as a fixed interval [V min(base) , V max(base) , where V min(base) and V max(base) are respectively the lower charge limit and the upper charge limit of the battery; when the temperature is lower than T1 or higher than T2, it enters the low-temperature area and the high-temperature area respectively. In the low-temperature area, the safety window lower limit is adjusted to , where is the low-temperature boundary compensation coefficient; in the high-temperature area, the safety window upper limit is adjusted to , where β is the high-temperature boundary attenuation coefficient.

[0116] Thus, the updated safety boundary value can be input into the hysteresis comparator to ensure a smooth transition of the safe operating range of the battery during temperature changes and avoid frequent switching of the equalization state. By setting the upper and lower threshold values, the hysteresis comparator ensures that the equalization operation is not immediately triggered when the battery approaches the boundary, thereby reducing unnecessary energy consumption and system burden, avoiding frequent equalization operations when the temperature approaches the boundary, and improving the energy efficiency of the system.

[0117] Referring to Figure 9 as shown, the formation of the hierarchical topology linkage control specifically includes:

[0118] Based on the cell imbalance credibility factor value, bidirectional energy transfer is carried out through the energy transfer interface of the silicon carbide MOSFET device to perform energy equalization between cells inside the module.

[0119] Calculate the range of SOC between different battery modules. When the range of SOC between modules exceeds the preset threshold, trigger inter-module equalization.

[0120] Directly connect the energy transfer interfaces of each battery module to form a closed-loop path, construct a ring bus topology, and directly transfer energy across modules through the bus to dynamically correct the range of SOC between modules. Among them, the intra-module equalization and the inter-module equalization are linked through the ring bus topology to synchronously reduce the inconsistency between cells and between modules.

[0121] Real-time collect the voltage, current, and temperature data of each single battery, calculate its SOC value, and judge which single batteries need energy equalization according to the cell imbalance credibility factor value. Through the bidirectional energy transfer interface of the silicon carbide MOSFET device, transfer the energy of the high-SOC single battery to the low-SOC single battery until the SOC difference between cells is reduced to an acceptable range to achieve equalization between cells.

[0122] Real-time monitor the SOC values of each battery module, calculate the range of SOC between modules. When the range of SOC between modules exceeds the preset threshold, start the inter-module equalization mechanism. Through the ring bus topology, the energy between modules can be directly transferred, and the energy of the high-SOC module can be transferred to the low-SOC module, thereby dynamically correcting the range of SOC between modules.

[0123] The balance between monomers and the balance between modules cooperate with each other to form a hierarchical topology linkage control. The balance within the module and between modules can be carried out synchronously, which can quickly respond to the SOC differences between monomers and modules, dynamically adjust the energy transfer, improve the response speed and balance efficiency of the system. At the same time, through the bidirectional energy transfer and the ring bus topology, the SOC differences between monomers and between modules can be effectively reduced, improving the consistency of the battery pack and extending the service life of the battery pack. The ring bus topology structure simplifies the system design, reduces the additional balancing circuits and interfaces, and reduces the complexity and cost of the system.

[0124] In summary, the advantages of the present invention are as follows: Through the innovative hybrid balancing strategy and hierarchical topology linkage control, the consistency and thermal management efficiency of the battery pack are significantly improved, the service life of the battery pack is extended, and the overall performance and safety of the electric vehicle are enhanced.

[0125] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection required by the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic control method for an intelligent equalization management system of a lithium battery module, characterized in that, Including: Real-time collect the voltage, current, and temperature data of each single battery in the module. Based on the historical cycle times, temperature stress, and capacity attenuation rate of the lithium battery module, combine the internal resistance change rate to calculate the aging coupling factor, dynamically correct the battery model parameters through the aging coupling factor, construct a hierarchical data fusion platform, generate a battery state dataset including SOC, SOH, and inconsistency evaluation values, and the battery model is the Thevenin equivalent circuit model; Based on the battery state dataset, use the credibility inference algorithm to calculate the single-cell imbalance credibility factor value to divide the equalization stage, and dynamically adjust the equalization current according to the product of the credibility factor value and the temperature entropy value; Extract the charge and discharge curve health factors through the LAB health factor algorithm, combine the extended Kalman filter to update the SOH online, feedback the SOH attenuation rate to the battery model, and perform collaborative management of SOC and SOH; Based on the single-cell imbalance credibility factor value, perform in-module equalization through the bidirectional energy transfer circuit, calculate the range difference of SOC between modules, and perform inter-module equalization through the ring bus topology to form a hierarchical topology linkage control.

2. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 1, wherein The specific steps of calculating the single-cell imbalance credibility factor value to divide the equalization stage and dynamically adjusting the equalization current according to the product of the credibility factor value and the temperature entropy value include: Based on the SOC and inconsistency evaluation values in the battery state dataset, calculate the imbalance credibility factor value of each single battery through the credibility inference algorithm; Based on the historical battery state dataset, obtain the specific quantiles of the historical data distribution as the boundaries of the low-credibility stage and the high-credibility stage. Divide the equalization stage according to the imbalance credibility factor value. When the imbalance credibility factor value is lower than the boundary of the low-credibility stage, record it as the low-credibility stage and turn off the equalization circuit; When the imbalance credibility factor value is between the boundary of the low-credibility stage and the boundary of the high-credibility stage, record it as the medium-credibility stage and start small-current equalization. The equalization current is less than the charge and discharge current as the rated capacity of the battery; When the imbalance credibility factor value is greater than the boundary of the high-credibility stage, record it as the high-credibility stage and start large-current equalization. The equalization current is greater than the product of the imbalance credibility factor value and the maximum current; Real-time monitor the dynamic correction result of the aging coupling factor on its own correction weight, and adaptively adjust the amplitude of the equalization current.

3. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 2, wherein The specific steps of performing collaborative management of SOC and SOH include: Based on the SOH value in the battery state dataset, determine the attenuation level of each single battery and assign a differentiated initial window; Dynamically adjust the equalization target SOC range according to the attenuation level. For high-attenuation-level batteries, perform protective equalization operations and limit their charge and discharge depth. For low-attenuation-level batteries, maintain equalization in the full SOC range; Dynamically adjust the amplitude of the equalization current according to the attenuation level. High-attenuation-level batteries use an equalization current lower than the rated value, and low-attenuation-level batteries use a rated or higher-than-rated equalization current; Based on the attenuation level and the current SOC value, calculate the equalization priority weight of the battery, and give priority to energy replenishment of healthy batteries and perform protective equalization operations on high-attenuation batteries.

4. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 3, characterized in that, Determining the attenuation level of each single battery based on the SOH value in the battery state dataset and assigning a differentiated initial window specifically includes: Obtain the general health threshold standards of 80% and 90% in the battery industry, divide the attenuation level intervals according to the SOH attenuation rate. If the SOH of a single battery is greater than 90%, it is marked as a low attenuation level. When the SOH of a single battery is between 80% and 90%, it is marked as a medium attenuation level. When the SOH of a single battery is less than 80%, it is marked as a high attenuation level; Assign differentiated SOC equalization initial window thresholds based on different attenuation levels, couple the attenuation level, temperature coefficient, and operating condition coefficient to obtain low attenuation window thresholds, medium attenuation window thresholds, and high attenuation window thresholds, which respectively correspond to the initial SOC equalization window thresholds of batteries with different attenuation levels; Real-time monitor the change of the SOH attenuation rate. If the change amount of the SOH attenuation rate exceeds the dynamic threshold in three consecutive updates, dynamically adjust the SOC equalization window threshold of the corresponding attenuation level in equal proportion. The dynamic threshold is calculated through the temperature mutation coefficient.

5. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 4, wherein The output power states of batteries with different attenuation levels during charge and discharge are as follows: The output current capacity of low attenuation level batteries is less than the rated current. The output current capacity of medium attenuation level batteries is 80%-100% of the rated current. The output current capacity of high attenuation level batteries is less than 80% of the rated current; When the module supplies power, the system dynamically distributes the current load according to the attenuation level, so that the current output ratio of high attenuation batteries does not exceed 80% of their rated capacity.

6. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 5, characterized in that, For high attenuation level batteries, performing protective equalization operations and restricting their charge and discharge depth specifically includes: Real-time obtain the temperature data of the target single battery, dynamically calculate the safety window boundary based on the mapping relationship between temperature and boundary values, update the safety window. For high attenuation level batteries, narrow the equalization target SOC range within the safety window; For low attenuation level batteries, maintain full SOC range equalization and set a hysteresis interval at the safety window boundary to avoid frequent switching of the equalization state.

7. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 6, characterized in that, The dynamically adjusting the SOC equalization window threshold of the corresponding attenuation level in equal proportion specifically includes: Based on the manufacturer data of the lithium battery module, obtain the aging characteristics of the battery, and obtain the reference threshold δ pre-calibrated by the battery aging characteristics base ; Obtain a preset temperature gradient threshold T based on fixed parameters pre-calibrated according to the thermal stability of the battery material system, the temperature change characteristics of the application scenario, and the safety risk level grad , calculate the current temperature change rate and the ratio of the preset temperature gradient threshold T grad , determine the temperature mutation coefficient K, multiply the temperature mutation coefficient K by the reference threshold to obtain the dynamic threshold δ; Real-time monitor the change amount ΔSOH of the SOH attenuation rate. When ΔSOH exceeds the dynamic threshold δ in three consecutive updates, the SOC equalization window threshold is adjusted, and the adjustment amplitude is ΔV window Satisfy: , where β is the scaling factor, and V window0 is the initial window threshold.

8. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 7, characterized in that, The dynamically calculating the safety window boundary based on the mapping relationship between temperature and boundary values specifically includes: Define the temperature T and the upper safety boundary voltage limit V and the lower safety boundary voltage limit V according to the battery electrochemical characteristics of the lithium battery module max (T) as continuous functions, and establish a temperature-safety boundary mapping function; min (T) Real-time collect the temperature data of single cells, and calculate the dynamic safety boundary at the current temperature through piecewise linear interpolation: when T ∈ [T1, T2], the safety window boundary is a fixed interval [V min(base) , V max(base) , where T1 and T2 are the temperature critical points calibrated by material characteristics, [T1, T2] is the normal temperature range, V min(base) and V max(base) are the upper charge limit and lower charge limit of the lithium batteries in the lithium battery module respectively; When T < T1, it is denoted that the lower limit of the safety window in the low-temperature region is adjusted to , is the low-temperature boundary compensation coefficient; When T > T2, it is denoted that the upper limit of the safety window in the high-temperature region is adjusted to , where β is the attenuation coefficient of the high-temperature boundary; Input the updated safety boundary value into the hysteresis comparator, and combine it with the adjusted SOC equalization window threshold to generate the final safe operation interval of high attenuation level batteries.

9. The dynamic control method of an intelligent equalization management system for a lithium battery module according to claim 8, characterized in that, Forming a hierarchical topology linkage control specifically includes: Based on the single-cell imbalance credibility factor value, perform bidirectional energy transfer through the energy transfer interface of the silicon carbide MOSFET device to perform energy equalization between single cells inside the module; Calculate the range difference of SOC between different battery modules. When the range difference of SOC between modules exceeds the preset threshold, trigger inter-module equalization; Directly connect the energy transfer interfaces of each battery module to form a closed-loop path, construct a ring bus topology, directly transfer energy across modules through the bus to dynamically correct the range difference of SOC between modules. Among them, intra-module equalization and inter-module equalization are linked through the ring bus topology to synchronously reduce the inconsistency between single cells and between modules.

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