Battery management system supporting active balancing

Abstract

The present invention discloses a battery management system supporting active balancing, and relates to the field of battery detection technology. When the system is running, the battery status monitoring module monitors and integrates the working status data of the battery cells in real time, generates a battery status vector BSV, identifies the current charging mode CM of the battery pack, and effectively limits the charging fluctuation range between the battery cells by adjusting the balancing strategy ASOC between the battery cells in real time, thereby avoiding the loss and overheating of the battery cells caused by uneven current or charging speed differences during the charging process. By monitoring the working status of the battery cells and comparing it with the safety work warning threshold Athe, the risk of overheating or overload of the battery cells can be identified in time, avoiding possible safety accidents. By summarizing and calculating the overall charging efficiency OE of the battery pack, a targeted charging optimization plan can be proposed to further improve the charging efficiency and reduce energy loss.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and in particular to a battery management system supporting active balancing. Background Art

[0002] In the context of the rapid development of modern technology, battery management systems (BMS), as one of the indispensable core technologies in electronic devices and electric vehicles, are widely used in the field of energy storage and management. With the increasing requirements for battery efficiency and service life in consumer electronics, smart devices and electric vehicles, the functions and technologies of battery management systems are also constantly evolving. Especially in the fields of mobile devices, wearable devices and electric vehicles, battery management systems need to not only ensure the safety and stability of the battery, but also optimize its charging and discharging process to extend the battery life. At the same time, the battery management system needs to cope with different charging modes, such as fast charging, standard charging and slow charging. The battery charging requirements in each mode are different, so a smarter management method is needed.

[0003] Although modern battery management systems have optimized the charging and discharging process of batteries to a great extent, existing technologies still have certain limitations when dealing with different charging modes. Existing battery management systems usually adopt a fixed balancing strategy during the charging process, and may not be able to dynamically adjust the power distribution between battery cells according to different charging speeds and charging methods. For example, during fast charging, the voltage difference between battery cells may be exacerbated, causing some battery cells to overheat or be damaged due to charging too quickly, while other battery cells cannot reach the ideal charging state due to insufficient charging. In addition, traditional passive balancing technology may balance the battery by wasting energy in this case, but this is not only inefficient, but also easily burdens the battery and shortens the battery life. Therefore, existing battery management systems still face significant challenges in charging efficiency and battery protection under different charging modes. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a battery management system supporting active balancing, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a battery management system supporting active balancing, including a battery status monitoring module, a charging mode identification and selection module, a battery balancing strategy adjustment module, an energy transfer module, a temperature and overload protection module, and a charging efficiency evaluation and optimization module;

[0006] The battery status monitoring module monitors the working status data of each battery cell in the battery pack in real time, and digitally processes and integrates the working status data to obtain a battery status vector BSV;

[0007] The charging mode identification and selection module identifies the charging mode of the current battery pack according to the battery state vector BSV, adjusts the charging strategy according to the charging mode, and synchronously marks the charging mode CM of the current battery pack;

[0008] The battery balancing strategy adjustment module adjusts the balancing strategy ASOC between battery cells in real time according to the charging mode CM and the battery state vector BSV, and determines whether to perform energy transfer according to the overall state of the battery pack;

[0009] The energy transfer module is used to control the energy transfer between battery cells and start the DC-DC converter according to the balancing strategy ASOC to adjust the flow of energy and obtain the energy transfer amount ET;

[0010] The temperature and overload protection module is used to monitor the working state of the battery unit and compare it with the safety working warning threshold Athe, and determine the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result;

[0011] The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution.

[0012] Preferably, the battery status monitoring module includes a battery status acquisition unit and a data processing and integration unit;

[0013] The battery status acquisition unit collects the working status data of the battery pack through an integrated battery management chip, and collects real-time working status data from each battery cell in the battery pack, including voltage V, current I and temperature T, to form an initial battery cell vector BSV1={(V1, I1, T1), V2, I2, T2), ..., Vn, In, Tn)} of the battery cell;

[0014] Wherein, V1, I1 and T1 represent the voltage V, current I and temperature T of the first battery cell respectively, and n represents the total number of battery cells.

[0015] Preferably, the data processing and integration unit performs digitization, unit conversion, filtering and correction preprocessing on the initial battery cell vector BSV1, and then performs SOC estimation processing and SOH estimation processing to obtain the state of charge SOCi(t) and the battery state of health SOHi(t), and obtains the preprocessed battery state vector BSV by integrating the preprocessed initial battery cell vector BSV1, the state of charge SOCi(t) and the battery state of health SOHi(t), specifically BSV=(V1, I1, T1, SOC1, SOH1), (V2, I2, T2, SOC2, SOH2), ..., (Vn, In, Tn, SOCn, SOHn);

[0016] The SOC estimation process includes estimating the state of charge SOCi(t) of the i-th battery cell using the coulomb counting method and the open circuit voltage method to reflect the state of charge of the i-th battery cell at time t;

[0017] The charging state SOCi(t) is obtained by the following calculation formula:

[0018] ;

[0019] In the formula, SOCi(t-1) represents the state of charge of the ith battery cell at time t-1, Ii(t) represents the current of the ith battery cell at time t, △t represents the time interval between each calculation sample, and Cnominal represents the rated capacity of the battery cell;

[0020] The SOH estimation process calculates the battery health state SOHi(t) of the i-th battery cell by measuring the internal resistance of the battery, reflecting the health state of the i-th battery cell at time t;

[0021] The battery health state SOHi(t) is obtained by the following calculation formula:

[0022] ;

[0023] Where Ri(t) represents the battery internal resistance of the ith battery cell at time t, and Rnominal represents the initial internal resistance of the battery cell.

[0024] Preferably, the charging mode identification and selection module includes a charging mode identification unit and a charging strategy adjustment unit;

[0025] The charging mode identification unit identifies the current charging mode of the battery pack according to the battery information in the battery state vector BSV, including fast charging, standard charging and slow charging;

[0026] The current charging mode of the battery pack is identified by comparing with the preset fast threshold Kthe, standard threshold Bthe and slow threshold Mthe of fast charging, standard charging and slow charging:

[0027] When the state of charge SOCi(t) is less than the fast threshold Kthe, and the voltage Vi(t) is less than the voltage threshold Vlow, it is determined that the current charging mode of the battery pack is changed to the fast charging mode, and the charging mode is marked as CM=9;

[0028] Wherein, Vi(t) represents the voltage of the i-th battery cell at time t, and Vlow represents the voltage threshold for fast charging execution;

[0029] When the fast threshold Kthe≤SOCi(t)≤standard threshold Bthe, and the temperature Ti(t)<temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack is changed to the standard charging mode, and the charging mode is marked as CM=3;

[0030] Wherein, temperature Ti(t) represents the temperature of the ith battery cell at time t, and TMax represents the upper temperature threshold for charging the battery pack;

[0031] When the state of charge SOCi(t)>slow threshold Mthe or the temperature Ti(t)>temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack is changed to slow charging mode, and the charging mode CM=1 is marked.

[0032] Preferably, the charging strategy adjustment unit adjusts the charging strategy in real time according to the charging mode CM, triggers a limiting strategy for the charging current Ic during the current charging process of the battery cell according to different charging modes CM, and synchronously adjusts the charging current Ic for charging the battery cells in the battery pack;

[0033] The restriction strategy includes the following identification restriction strategies:

[0034] When charging mode CM=9, adjust the charging current Ic=2*C;

[0035] When charging mode CM=3, adjust the charging current Ic=C;

[0036] When charging mode CM=1, adjust the charging current Ic=0.5*C;

[0037] Wherein, C represents the capacity of the battery cell.

[0038] Preferably, the battery balancing strategy adjustment module includes a balancing strategy calculation unit and an energy transfer decision unit;

[0039] The balancing strategy calculation unit adjusts the balancing strategy ASOC between the battery cells in real time according to the charging mode CM and the battery state vector BSV;

[0040] The balancing strategy ASOC specifically obtains the SOC difference △SOCi of the i-th battery cell by calculating the charge state SOCi(t) of the i-th battery cell in the battery state vector BSV and the average SOCavg of all battery cells in the battery pack;

[0041] Then, the SOC difference △SOCi of the i-th battery cell is fitted with the charging mode CM to obtain the balancing strategy ASOC;

[0042] The balance strategy ASOC is obtained by the following calculation formula:

[0043] ;

[0044] Wherein, k represents the amplification constant, specifically represents the amplification ratio coefficient between the SOC difference △SOCi of the i-th battery cell and the charging mode CM, and min represents the minimum value function.

[0045] Preferably, the energy transfer decision unit compares the SOC difference △SOCi of the i-th battery cell with the balancing strategy ASOC to determine whether the SOC fluctuation of the battery cell exceeds the allowable range of the balancing strategy ASOC, and performs energy transfer according to the determination result;

[0046] The judgment result is obtained by the following judgment method:

[0047] When the SOC difference △SOCi of the i-th battery cell is greater than the balancing strategy ASOC, it is determined that the SOC difference of the i-th battery cell exceeds the allowable range of the balancing strategy ASOC, and energy transfer is performed, including transferring energy from the i-th battery cell to the i+1-th battery cell that does not exceed the allowable range of the balancing strategy ASOC.

[0048] Preferably, the energy transfer module is used to control the energy transfer between battery cells, and start the DC-DC converter according to the charging mode CM and the balancing strategy ASOC to adjust the flow of energy, obtain the energy transfer amount ET, and reflect the energy exchange amount between the battery cells;

[0049] The energy transfer amount ET is obtained by the following calculation formula:

[0050] ;

[0051] Where Pmax represents the upper limit power of the battery pack, SOCmax represents the upper limit SOC between battery cells, and Pdc represents the upper limit power of the DC-DC converter.

[0052] Preferably, the temperature and overload protection module is used to monitor the working state of the battery unit, including the temperature state and the load state, specifically by monitoring the temperature Ti(t) and current Ii(t) of the i-th battery unit at time t, and comparing them with the safety operation warning threshold Athe, and determining the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result;

[0053] Among them, the safety work warning threshold Athe includes the safety work warning temperature upper threshold AtheTMax, the safety work warning temperature lower threshold AtheTMin and the safety work warning current threshold AtheI;

[0054] The evaluation results are obtained by the following comparison method:

[0055] When the lower limit threshold of the safe working warning temperature AtheTMin≤temperature Ti(t)≤upper limit threshold of the safe working warning temperature AtheTMax, and the current Ii(t)≤the safe working warning current threshold AtheI, it is determined that the working state of the battery unit during operation is a qualified evaluation result;

[0056] When the temperature Ti (t) is less than the lower limit threshold of the safe working warning temperature AtheTMin, the working state of the battery unit during operation is judged to be an unqualified evaluation result, and the battery unit temperature is low, so please stop charging and provide heating protection;

[0057] When the temperature Ti (t) is greater than the upper threshold of the safe working warning temperature AtheTMax, the working state of the battery unit is judged to be an unqualified evaluation result, and a prompt is given to stop charging and provide cooling protection when the temperature of the battery unit is high;

[0058] When the current Ii(t)>safe operation warning current threshold AtheI, the operating state of the battery unit during operation is determined to be an unqualified evaluation result, and a prompt is given to stop charging.

[0059] Preferably, the charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution;

[0060] The overall charging efficiency OE is obtained by the following calculation formula:

[0061] ;

[0062] In the formula, represents the charging efficiency of the ith battery cell, which is obtained by comparing the ratio of the actual stored energy of the battery to the input energy during charging, Ci represents the capacity of the ith battery cell, and n represents the total number of battery cells in the battery pack;

[0063] The charging efficiency evaluation strategy is obtained by the following comparison method:

[0064] When the overall charging efficiency OE is less than the overall charging efficiency evaluation threshold Cthe, an iteratively optimized charging efficiency evaluation strategy is obtained;

[0065] When the overall charging efficiency OE ≥ the overall charging efficiency evaluation threshold Cthe, a charging efficiency evaluation strategy scheme with a qualified battery balancing state is obtained.

[0066] The present invention provides a battery management system supporting active balancing, which has the following beneficial effects:

[0067] (1) When the system is running, the battery status monitoring module monitors and integrates the working status data of the battery cells in real time to generate the battery status vector BSV, identify the current charging mode CM of the battery pack, and adjust the charging strategy in real time on this basis. Secondly, by adjusting the balancing strategy ASOC between battery cells in real time, the charging fluctuation range between battery cells is effectively limited, avoiding the loss and overheating of battery cells caused by uneven current or charging speed differences during the charging process. By monitoring the working status of the battery cells and comparing it with the safety working warning threshold Athe, the overheating or overload risk of the battery cells can be identified in time, thereby providing a safety line for the battery pack and avoiding possible safety accidents. By calculating the charging efficiency of each battery cell and summarizing the calculation of the overall charging efficiency OE of the battery pack, after evaluating the gap between it and the preset threshold Cthe, a targeted charging optimization plan can be proposed to further improve the charging efficiency and reduce energy loss.

[0068] (2) According to the battery information in the battery state vector BSV, the current charging mode of the battery pack is accurately identified, and the charging strategy is automatically adjusted according to different charging modes. This module not only supports real-time identification of the charging mode based on the battery charging state SOCi(t) and the voltage Vi(t) and temperature Ti(t) of the battery cell, but also can automatically execute different charging current Ic limiting strategies according to the mode set by the user, thereby achieving optimization adjustment during the charging process. It can also automatically select the most suitable charging mode according to different charging requirements and battery status, ensuring that the battery pack is always in the best working state and extending the battery life. This real-time adjustment and intelligent selection capability makes the charging process both efficient and safer.

[0069] (3) It can adjust the balancing strategy ASOC between battery cells in real time according to the battery state vector BS and the charging mode CM, thereby achieving precise control of the charging fluctuation of the battery cells. This module first calculates the difference △SOCi between the charging state SOCi(t) of each battery cell and the average charging state SOCavg of all battery cells in the battery pack, and further fits the balancing strategy ASOC, and appropriately adjusts the fluctuation range according to different charging modes. At the same time, the excess energy is transferred to other battery cells to ensure the energy balance between all battery cells, thereby further improving the charging efficiency and the service life of the battery pack. This real-time and dynamic balancing adjustment strategy not only ensures the efficient and stable operation of the battery pack, but also effectively improves the safety and economy of the system.

[0070] (4) Start the DC-DC converter according to the charging mode CM and the balancing strategy ASOC, accurately control the energy flow between the battery cells, dynamically adjust the energy transfer amount ET, ensure that the energy difference between the battery cells is always kept within a reasonable range, and prevent some cells from being overcharged or over-discharged. Through the maximum power limit Pmax and the converter power limit Pdc, as well as the constraints of the battery cell's charging capacity SOCmax, the system avoids excessive energy transfer, thereby effectively protecting the overall health of the battery pack. Secondly, the temperature and overload protection module monitors the battery cell's temperature Ti(t) and current Ii(t) in real time to ensure that the battery cell operates in a suitable working environment and that the battery pack's charging process is efficient and has minimal losses. This optimization process ensures that the battery can store energy in the best way during the charging process, improving the long-term efficiency of the battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 The figure is a schematic diagram of a battery management system supporting active balancing according to the present invention. DETAILED DESCRIPTION

[0072] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0073] Example 1

[0074] The present invention provides a battery management system that supports active balancing, see Figure 1 , including battery status monitoring module, charging mode identification and selection module, battery balancing strategy adjustment module, energy transfer module, temperature and overload protection module and charging efficiency evaluation and optimization module;

[0075] The battery status monitoring module monitors the working status data of each battery cell in the battery pack in real time, and digitally processes and integrates the working status data to obtain a battery status vector BSV;

[0076] The charging mode identification and selection module identifies the charging mode of the current battery pack according to the battery state vector BSV, adjusts the charging strategy according to the charging mode, and synchronously marks the charging mode CM of the current battery pack;

[0077] The battery balancing strategy adjustment module adjusts the balancing strategy ASOC between battery cells in real time according to the charging mode CM and the battery state vector BSV, and determines whether to perform energy transfer according to the overall state of the battery pack;

[0078] The energy transfer module is used to control the energy transfer between battery cells and start the DC-DC converter according to the balancing strategy ASOC to adjust the flow of energy and obtain the energy transfer amount ET;

[0079] The temperature and overload protection module is used to monitor the working state of the battery unit and compare it with the safety working warning threshold Athe, and determine the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result;

[0080] The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution.

[0081] In this embodiment, the battery state monitoring module generates a battery state vector BSV by real-time monitoring and integrating the working state data of the battery cell, which provides accurate basic data for the subsequent charging mode identification and selection. This process ensures that the battery pack can be dynamically optimized according to the actual working state during the charging process, thereby improving the adaptability and accuracy of charging. The charging mode identification and selection module identifies the current charging mode CM of the battery pack according to the battery state vector BSV, and adjusts the charging strategy in real time on this basis, so that the charging current and voltage of the battery cells under different charging modes can be optimized, thereby improving the charging efficiency. Secondly, the battery balancing strategy adjustment module adjusts the balancing strategy ASOC between the battery cells in real time according to the charging mode CM and the battery state vector BSV, thereby effectively limiting the charging fluctuation range between the battery cells and avoiding the loss and overheating of the battery cells caused by uneven current or charging speed differences during the charging process. At the same time, the system can determine whether to perform energy transfer, and by starting the energy transfer module, use the DC-DC converter to optimize the energy distribution between the battery cells to ensure the overall charging efficiency of the battery pack. This process effectively reduces energy waste and avoids damage to battery cells caused by overcharging, improving the safety and life of the system. The temperature and overload protection module monitors the working status of the battery cells and compares it with the safety warning threshold Athe, which can timely identify the risk of overheating or overload of the battery cells, thereby providing a safety line of defense for the battery pack and avoiding possible safety accidents. Finally, the charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell and summarizes the overall charging efficiency OE of the battery pack. After evaluating the gap between it and the preset threshold Cthe, it can propose targeted charging optimization solutions to further improve charging efficiency and reduce energy loss.

[0082] Example 2

[0083] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the battery status monitoring module includes a battery status acquisition unit and a data processing and integration unit;

[0084] The battery status acquisition unit collects the working status data of the battery pack through an integrated battery management chip, and collects real-time working status data from each battery cell in the battery pack, including voltage V, current I and temperature T, to form an initial battery cell vector BSV1={(V1, I1, T1), V2, I2, T2), ..., Vn, In, Tn)} of the battery cell;

[0085] Wherein, V1, I1 and T1 represent the voltage V, current I and temperature T of the first battery cell respectively, and n represents the total number of battery cells.

[0086] The data processing and integration unit performs digitization, unit conversion, filtering and correction preprocessing on the initial battery cell vector BSV1, and then performs SOC estimation processing and SOH estimation processing to obtain the state of charge SOCi (t) and the battery state of health SOHi (t). The preprocessed initial battery cell vector BSV1, the state of charge SOCi (t) and the battery state of health SOHi (t) are integrated to obtain the preprocessed battery state vector BSV, specifically BSV=(V1, I1, T1, SOC1, SOH1), (V2, I2, T2, SOC2, SOH2), ..., (Vn, In, Tn, SOCn, SOHn);

[0087] The SOC estimation process includes estimating the state of charge SOCi(t) of the i-th battery cell using the coulomb counting method and the open circuit voltage method to reflect the state of charge of the i-th battery cell at time t;

[0088] The charging state SOCi(t) is obtained by the following calculation formula:

[0089] ;

[0090] In the formula, SOCi(t-1) represents the state of charge of the ith battery cell at time t-1, Ii(t) represents the current of the ith battery cell at time t, △t represents the time interval between each calculation sample, and Cnominal represents the rated capacity of the battery cell;

[0091] The SOH estimation process calculates the battery health state SOHi(t) of the i-th battery cell by measuring the internal resistance of the battery, reflecting the health state of the i-th battery cell at time t;

[0092] The battery health state SOHi(t) is obtained by the following calculation formula:

[0093] ;

[0094] Where Ri(t) represents the battery internal resistance of the ith battery cell at time t, and Rnominal represents the initial internal resistance of the battery cell.

[0095] In this embodiment, the real-time working state data of each battery cell, including voltage Vi, current Ii and temperature Ti, are obtained, and the state of charge SOCi(t) and health state SOHi(t) of each battery cell are calculated through these data. This precise monitoring can provide comprehensive and real-time data support for the battery management system, and then provide a scientific basis for the dynamic adjustment and optimization of the battery pack. The battery state acquisition unit uses the battery management chip to collect the operating state of each battery cell in real time, thereby generating an initial battery cell vector BSVraw. Then, the data processing and integration unit further estimates the state of charge SOCi(t) and battery health state SOHi(t) of the battery cell by digitizing, converting units, filtering and correcting these data, and finally integrates them into a complete battery state vector BSV, providing a more comprehensive and accurate view of the working state of the battery pack. This process estimates the charging state through the coulomb counting method and the open circuit voltage method, and infers the health state in combination with the internal resistance measurement of the battery, so that the battery pack can maintain the best working state during the charging and discharging process.

[0096] Example 3

[0097] This embodiment is explained in Example 2. Please refer to Figure 1 , specifically: the charging mode identification and selection module includes a charging mode identification unit and a charging strategy adjustment unit;

[0098] The charging mode identification unit identifies the current charging mode of the battery pack according to the battery information in the battery state vector BSV, including fast charging, standard charging and slow charging, and the charging mode can be actively set by the user;

[0099] The current charging mode of the battery pack is identified by comparing with the preset fast threshold Kthe, standard threshold Bthe and slow threshold Mthe of fast charging, standard charging and slow charging:

[0100] When the state of charge SOCi(t) is less than the fast threshold Kthe, and the voltage Vi(t) is less than the voltage threshold Vlow, it is determined that the current charging mode of the battery pack has changed to the fast charging mode, and the charging mode is marked as CM=9. When the state of charge SOCi(t) is low and the voltage Vi(t) is also low, the battery pack will be marked as the fast charging mode;

[0101] Wherein, Vi(t) represents the voltage of the i-th battery cell at time t, and Vlow represents the voltage threshold for fast charging execution;

[0102] When the fast threshold Kthe≤SOCi(t)≤standard threshold Bthe, and the temperature Ti(t)<temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack has changed to the standard charging mode, and the charging mode is marked as CM=3. The battery pack will enter the standard charging mode only when the battery's charging state SOCi(t) is within this range and the temperature is lower than the temperature upper limit threshold TMax;

[0103] Wherein, temperature Ti(t) represents the temperature of the ith battery cell at time t, and TMax represents the upper temperature threshold for charging the battery pack;

[0104] When the charging state SOCi(t)>slow threshold Mthe or temperature Ti(t)>temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack is changed to slow charging mode, and the charging mode is marked as CM=1, which means that when the battery's charging state SOCi(t) is high or the temperature Ti(t) is too high, the battery pack will be marked as slow charging mode.

[0105] The charging strategy adjustment unit adjusts the charging strategy in real time according to the charging mode CM, triggers a limiting strategy for the charging current Ic during the current battery cell charging process according to different charging modes CM, and synchronously adjusts the charging current Ic for charging the battery cells in the battery pack;

[0106] The restriction strategy includes the following identification restriction strategies:

[0107] When charging mode CM=9, adjust the charging current Ic=2*C;

[0108] When charging mode CM=3, adjust the charging current Ic=C;

[0109] When charging mode CM=1, adjust the charging current Ic=0.5*C;

[0110] Wherein, C represents the capacity of the battery cell.

[0111] In this embodiment, the current charging mode of the battery pack is accurately identified according to the battery information in the battery state vector BSV, and the charging strategy is automatically adjusted according to different charging modes. This module not only supports real-time identification of the charging mode according to the battery charging state SOCi(t) and the voltage Vi(t) and temperature Ti(t) of the battery cell, but also can automatically execute different charging current Ic limiting strategies according to the mode set by the user, thereby achieving optimization adjustment during the charging process. When the battery pack is in fast charging mode, the charging current is adjusted to twice the battery capacity; in standard charging mode, the charging current is equivalent to the battery capacity; and in slow charging mode, the charging current is reduced to half of the battery capacity. This accurate charging mode identification and real-time charging strategy adjustment can significantly improve the safety and efficiency of the charging process. By adjusting the charging current and voltage limits in real time according to the actual state of the battery pack, the system can effectively avoid overcharging or insufficient charging while ensuring the charging speed, reducing damage to the battery cell. In addition, the automatic identification and adjustment of the charging mode also improves the intelligence level of the system, and can automatically select the most suitable charging mode according to different charging requirements and battery status, ensuring that the battery pack is always in the best working state and extending the battery life. This ability to adjust in real time and select intelligently makes the charging process both more efficient and safer.

[0112] Example 4

[0113] This embodiment is explained in Example 3, please refer to Figure 1 , specifically: the battery balancing strategy adjustment module includes a balancing strategy calculation unit and an energy transfer decision unit;

[0114] The balancing strategy calculation unit adjusts the balancing strategy ASOC between the battery cells in real time according to the charging mode CM and the battery state vector BSV, so as to control the limiting range of the charging fluctuation of the battery cells in real time;

[0115] The balancing strategy ASOC specifically obtains the SOC difference △SOCi of the i-th battery cell by calculating the charge state SOCi(t) of the i-th battery cell in the battery state vector BSV and the average SOCavg of all battery cells in the battery pack;

[0116] Then, the SOC difference △SOCi of the i-th battery cell is fitted with the charging mode CM to obtain the balancing strategy ASOC;

[0117] The balance strategy ASOC is obtained by the following calculation formula:

[0118] ;

[0119] Wherein, k represents the amplification constant, specifically represents the amplification ratio coefficient between the SOC difference △SOCi of the i-th battery cell and the charging mode CM, and min represents the minimum value function.

[0120] The energy transfer decision unit compares the SOC difference △SOCi of the i-th battery cell with the balancing strategy ASOC to determine whether the SOC fluctuation of the battery cell exceeds the allowable range of the balancing strategy ASOC, and performs energy transfer according to the determination result;

[0121] The judgment result is obtained by the following judgment method:

[0122] When the SOC difference △SOCi of the ith battery cell is greater than the balancing strategy ASOC, it is determined that the SOC difference of the ith battery cell exceeds the allowable range of the balancing strategy ASOC, and energy transfer is performed, including transferring energy from the ith battery cell to the i+1th battery cell that does not exceed the allowable range of the balancing strategy ASOC, until the SOC difference between all battery cells does not exceed the allowable range of the balancing strategy ASOC.

[0123] In this embodiment, the balancing strategy ASOC between the battery cells can be adjusted in real time according to the battery state vector BS and the charging mode CM, so as to achieve accurate control of the charging fluctuation of the battery cells. The module first calculates the difference △SOCi between the state of charge SOCi(t) of each battery cell and the average state of charge SOCavg of all battery cells in the battery pack, and further fits the balancing strategy ASOC, and appropriately adjusts the fluctuation range according to different charging modes. By dynamically controlling the balancing strategy, the charging fluctuation of each battery cell can be limited in real time according to the actual working state of the battery pack, avoiding battery loss or performance degradation due to excessive differences between battery cells, which makes the charging process of the entire battery pack more stable and balanced. By real-time monitoring and adjustment of the difference in the state of charge of the battery cells, it can effectively prevent some battery cells from affecting the performance of the entire battery pack due to over-discharge or over-charging. By setting a suitable balancing strategy ASOC, the system ensures that the charging fluctuation of each battery cell does not exceed the preset range, thereby avoiding excessive loss of the battery cell and optimizing energy utilization efficiency. When the △SOCi of a battery cell exceeds the ASOC limit of the balancing strategy, the system can intelligently transfer the excess energy to other battery cells through the energy transfer decision unit to ensure the energy balance between all battery cells, thereby further improving the charging efficiency and the service life of the battery pack. This real-time, dynamic balancing adjustment strategy not only ensures the efficient and stable operation of the battery pack, but also effectively improves the safety and economy of the system.

[0124] Example 5

[0125] This embodiment is explained in Example 4. Please refer to Figure 1 Specifically: the energy transfer module is used to control the energy transfer between battery cells, and start the DC-DC converter according to the charging mode CM and the balancing strategy ASOC, adjust the flow of energy, obtain the energy transfer amount ET, reflect the energy exchange amount between the battery cells, and determine how much energy needs to be transferred from one battery cell to another;

[0126] The energy transfer amount ET is obtained by the following calculation formula:

[0127] ;

[0128] Wherein, Pmax represents the upper limit power of the battery pack, specifically the maximum power output and input that the battery pack can withstand within a fixed period, SOCmax represents the upper limit SOC between battery cells, specifically the maximum charge capacity of the battery cells, and Pdc represents the upper limit power of the DC-DC converter, specifically the maximum power that the DC-DC converter can transmit.

[0129] The temperature and overload protection module is used to monitor the working state of the battery unit, including the temperature state and the load state, specifically by monitoring the temperature Ti(t) and current Ii(t) of the i-th battery unit at time t, and comparing them with the safety working warning threshold Athe, and determining the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result;

[0130] Among them, the safety work warning threshold Athe includes the safety work warning temperature upper threshold AtheTMax, the safety work warning temperature lower threshold AtheTMin and the safety work warning current threshold AtheI;

[0131] The evaluation results are obtained by the following comparison method:

[0132] When the lower limit threshold of the safe working warning temperature AtheTMin≤temperature Ti(t)≤upper limit threshold of the safe working warning temperature AtheTMax, and the current Ii(t)≤the safe working warning current threshold AtheI, it is determined that the working state of the battery unit during operation is a qualified evaluation result;

[0133] When the temperature Ti (t) is less than the lower limit threshold of the safe working warning temperature AtheTMin, the working state of the battery unit during operation is judged to be an unqualified evaluation result, and the battery unit temperature is low, so please stop charging and provide heating protection;

[0134] When the temperature Ti (t) is greater than the upper threshold of the safe working warning temperature AtheTMax, the working state of the battery unit is judged to be an unqualified evaluation result, and a prompt is given to stop charging and provide cooling protection when the temperature of the battery unit is high;

[0135] When the current Ii(t)>safe operation warning current threshold AtheI, the operating state of the battery unit during operation is determined to be an unqualified evaluation result, and a prompt is given to stop charging.

[0136] The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution;

[0137] The overall charging efficiency OE is obtained by the following calculation formula:

[0138] ;

[0139] In the formula, represents the charging efficiency of the ith battery cell, which is obtained by comparing the ratio of the actual stored energy of the battery to the input energy during charging, Ci represents the capacity of the ith battery cell, and n represents the total number of battery cells in the battery pack;

[0140] The charging efficiency evaluation strategy is obtained by the following comparison method:

[0141] When the overall charging efficiency OE is less than the overall charging efficiency evaluation threshold Cthe, an iteratively optimized charging efficiency evaluation strategy is obtained, including dynamically adjusting the charging mode CM and improving the settings of voltage and current, so as to minimize the energy loss during the charging process of the battery pack;

[0142] When the overall charging efficiency OE ≥ the overall charging efficiency evaluation threshold Cthe, a charging efficiency evaluation strategy scheme with a qualified battery balancing state is obtained.

[0143] In this implementation, the DC-DC converter is started according to the charging mode CM and the balancing strategy ASOC, the energy flow between the battery cells is accurately controlled, and the energy transfer amount ET is dynamically adjusted to ensure that the energy difference between the battery cells is always kept within a reasonable range to prevent some cells from being overcharged or over-discharged. Through the constraints of the maximum power limit Pmax and the converter power limit Pdc, as well as the charging capacity SOCmax of the battery cell, the system avoids excessive energy transfer, thereby effectively protecting the overall health of the battery pack. Secondly, the temperature and overload protection module monitors the temperature Ti(t) and current Ii(t) of the battery cell in real time to ensure that the battery cell operates in a suitable working environment. If the temperature or current exceeds the set threshold, the system will automatically start protection measures, such as stopping charging or performing temperature control, to minimize the risk of battery damage. The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell and compares it with the preset evaluation threshold Cthe based on the overall charging efficiency OE of the battery pack to further optimize the charging strategy. When the overall charging efficiency is lower than the set threshold, the system will iteratively adjust the charging mode CM, optimize the voltage and current settings, and ensure that the charging process of the battery pack is efficient and the loss is minimized. This optimization process ensures that the battery can store energy in the best way during charging, improving the long-term efficiency of the battery pack.

[0144] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Support active balancing battery management system, characterized by: It includes battery status monitoring module, charging mode identification and selection module, battery balancing strategy adjustment module, energy transfer module, temperature and overload protection module and charging efficiency evaluation and optimization module; The battery status monitoring module monitors the working status data of each battery cell in the battery pack in real time, and digitally processes and integrates the working status data to obtain a battery status vector BSV; The charging mode identification and selection module identifies the charging mode of the current battery pack according to the battery state vector BSV, adjusts the charging strategy according to the charging mode, and synchronously marks the charging mode CM of the current battery pack; The charging mode identification and selection module includes a charging mode identification unit and a charging strategy adjustment unit; The charging mode identification unit identifies the current charging mode of the battery pack according to the battery information in the battery state vector BSV, including fast charging, standard charging and slow charging; The current charging mode of the battery pack is identified by comparing with the preset fast threshold Kthe, standard threshold Bthe and slow threshold Mthe of fast charging, standard charging and slow charging: When the state of charge SOCi(t) is less than the fast threshold Kthe, and the voltage Vi(t) is less than the voltage threshold Vlow, it is determined that the current charging mode of the battery pack is changed to the fast charging mode, and the charging mode is marked as CM=9; Wherein, Vi(t) represents the voltage of the i-th battery cell at time t, and Vlow represents the voltage threshold for fast charging execution; When the fast threshold Kthe≤SOCi(t)≤standard threshold Bthe, and the temperature Ti(t)<temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack is changed to the standard charging mode, and the charging mode is marked as CM=3; Wherein, temperature Ti(t) represents the temperature of the ith battery cell at time t, and TMax represents the upper temperature threshold for charging the battery pack; When the state of charge SOCi(t)>slow threshold Mthe or the temperature Ti(t)>temperature upper limit threshold TMax, it is determined that the current charging mode of the battery pack is changed to slow charging mode, and the charging mode is marked as CM=1; The charging strategy adjustment unit adjusts the charging strategy in real time according to the charging mode CM, triggers a limiting strategy for the charging current Ic during the current battery cell charging process according to different charging modes CM, and synchronously adjusts the charging current Ic for charging the battery cells in the battery pack; The restriction strategy includes the following identification restriction strategies: When charging mode CM=9, adjust the charging current Ic=0.5*C; When charging mode CM=3, adjust the charging current Ic=C; When charging mode CM=1, adjust the charging current Ic=0.5*C; Wherein, C represents the capacity of the battery cell; The battery balancing strategy adjustment module adjusts the balancing strategy ASOC between battery cells in real time according to the charging mode CM and the battery state vector BSV, and determines whether to perform energy transfer according to the overall state of the battery pack; The battery balancing strategy adjustment module includes a balancing strategy calculation unit and an energy transfer decision unit; The balancing strategy calculation unit adjusts the balancing strategy ASOC between the battery cells in real time according to the charging mode CM and the battery state vector BSV; The balancing strategy ASOC specifically obtains the SOC difference △SOCi of the i-th battery cell by calculating the charge state SOCi(t) of the i-th battery cell in the battery state vector BSV and the average SOCavg of all battery cells in the battery pack; Then, the SOC difference △SOCi of the i-th battery cell is fitted with the charging mode CM to obtain the balancing strategy ASOC; The balance strategy ASOC is obtained by the following calculation formula: ； Wherein, k represents the amplification constant, specifically represents the amplification ratio coefficient between the SOC difference △SOCi of the i-th battery cell and the charging mode CM, and min represents the minimum value function; The energy transfer decision unit compares the SOC difference △SOCi of the i-th battery cell with the balancing strategy ASOC to determine whether the SOC fluctuation of the battery cell exceeds the allowable range of the balancing strategy ASOC, and performs energy transfer according to the determination result; The judgment result is obtained by the following judgment method: When the SOC difference △SOCi of the i-th battery cell> the balancing strategy ASOC, it is determined that the SOC difference of the i-th battery cell exceeds the allowable range of the balancing strategy ASOC, and energy transfer is performed, including transferring energy from the i-th battery cell to the i+1-th battery cell that does not exceed the allowable range of the balancing strategy ASOC; The energy transfer module is used to control the energy transfer between battery cells and start the DC-DC converter according to the balancing strategy ASOC to adjust the flow of energy and obtain the energy transfer amount ET; The temperature and overload protection module is used to monitor the working state of the battery unit and compare it with the safety working warning threshold Athe, and determine the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result; The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution.

2. The battery management system supporting active balancing according to claim 1, characterized in that: The battery status monitoring module includes a battery status acquisition unit and a data processing and integration unit; The battery status acquisition unit collects the working status data of the battery pack through an integrated battery management chip, and collects real-time working status data from each battery cell in the battery pack, including voltage V, current I and temperature T, to form an initial battery cell vector BSV1={(V1, I1, T1), V2, I2, T2), ..., Vn, In, Tn)} of the battery cell; Wherein, V1, I1 and T1 represent the voltage V, current I and temperature T of the first battery cell respectively, and n represents the total number of battery cells.

3. The battery management system supporting active balancing according to claim 2, characterized in that: The data processing and integration unit performs digitization, unit conversion, filtering and correction preprocessing on the initial battery cell vector BSV1, and then performs SOC estimation processing and SOH estimation processing to obtain the state of charge SOCi (t) and the battery state of health SOHi (t). The preprocessed initial battery cell vector BSV1, the state of charge SOCi (t) and the battery state of health SOHi (t) are integrated to obtain the preprocessed battery state vector BSV, specifically BSV=(V1, I1, T1, SOC1, SOH1), (V2, I2, T2, SOC2, SOH2), ..., (Vn, In, Tn, SOCn, SOHn); The SOC estimation process includes estimating the state of charge SOCi(t) of the i-th battery cell using the coulomb counting method and the open circuit voltage method to reflect the state of charge of the i-th battery cell at time t; The charging state SOCi(t) is obtained by the following calculation formula: ； In the formula, SOCi(t-1) represents the state of charge of the ith battery cell at time t-1, Ii(t) represents the current of the ith battery cell at time t, △t represents the time interval between each calculation sample, and Cnominal represents the rated capacity of the battery cell; The SOH estimation process calculates the battery health state SOHi(t) of the i-th battery cell by measuring the internal resistance of the battery, reflecting the health state of the i-th battery cell at time t; The battery health state SOHi(t) is obtained by the following calculation formula: ； Where Ri(t) represents the battery internal resistance of the ith battery cell at time t, and Rnominal represents the initial internal resistance of the battery cell.

4. The battery management system supporting active balancing according to claim 1, characterized in that: The energy transfer module is used to control the energy transfer between battery cells, and start the DC-DC converter according to the charging mode CM and the balancing strategy ASOC to adjust the flow of energy, obtain the energy transfer amount ET, and reflect the energy exchange amount between battery cells; The energy transfer amount ET is obtained by the following calculation formula: ； Where Pmax represents the upper limit power of the battery pack, SOCmax represents the upper limit SOC between battery cells, and Pdc represents the upper limit power of the DC-DC converter.

5. The battery management system supporting active balancing according to claim 2, characterized in that: The temperature and overload protection module is used to monitor the working state of the battery unit, including the temperature state and the load state, specifically by monitoring the temperature Ti(t) and current Ii(t) of the i-th battery unit at time t, and comparing them with the safety working warning threshold Athe, and determining the evaluation result corresponding to the working state of the battery unit during operation according to the comparison result; Among them, the safety work warning threshold Athe includes the safety work warning temperature upper threshold AtheTMax, the safety work warning temperature lower threshold AtheTMin and the safety work warning current threshold AtheI; The evaluation results are obtained by the following comparison method: When the lower limit threshold of the safe working warning temperature AtheTMin≤temperature Ti(t)≤upper limit threshold of the safe working warning temperature AtheTMax, and the current Ii(t)≤the safe working warning current threshold AtheI, it is determined that the working state of the battery unit during operation is a qualified evaluation result; When the temperature Ti (t) is less than the lower limit threshold of the safe working warning temperature AtheTMin, the working state of the battery unit during operation is judged to be an unqualified evaluation result, and the battery unit temperature is low, so please stop charging and provide heating protection; When the temperature Ti (t) is greater than the upper threshold of the safe working warning temperature AtheTMax, the working state of the battery unit is judged to be an unqualified evaluation result, and a prompt is given to stop charging and provide cooling protection when the temperature of the battery unit is high; When the current Ii(t)>safe operation warning current threshold AtheI, the operating state of the battery unit during operation is determined to be an unqualified evaluation result, and a prompt is given to stop charging.

6. The battery management system supporting active balancing according to claim 1, characterized in that: The charging efficiency evaluation and optimization module calculates the charging efficiency of each battery cell, summarizes and obtains the overall charging efficiency OE of the battery pack, and evaluates it with a preset overall charging efficiency evaluation threshold Cthe to obtain a charging efficiency evaluation strategy solution; The overall charging efficiency OE is obtained by the following calculation formula: ； In the formula, represents the charging efficiency of the ith battery cell, which is obtained by comparing the ratio of the actual stored energy of the battery to the input energy during charging, Ci represents the capacity of the ith battery cell, and n represents the total number of battery cells in the battery pack; The charging efficiency evaluation strategy is obtained by the following comparison method: When the overall charging efficiency OE is less than the overall charging efficiency evaluation threshold Cthe, an iteratively optimized charging efficiency evaluation strategy is obtained; When the overall charging efficiency OE ≥ the overall charging efficiency evaluation threshold Cthe, a charging efficiency evaluation strategy scheme with a qualified battery balancing state is obtained.

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