Defect detection method of energy storage system and energy storage system

Abstract

The invention relates to the technical field of energy storage, and discloses a defect detection method of an energy storage system and the energy storage system.The defect detection method of the energy storage system comprises the steps that an operation mode of the energy storage system is obtained, and corresponding pulse current is determined according to the operation mode; estimating whether the battery core superposition pulse current of the energy storage system affects the safe operation of the battery core, if the battery core superposition pulse current does not affect the safe operation of the battery core, superposing the pulse current on the battery core, and calculating the equivalent alternating current impedance of the battery core in real time; and calculating a difference ratio between the equivalent alternating current impedance and the predicted equivalent current impedance, judging whether the difference ratio exceeds a first preset threshold value or not, if the difference ratio exceeds the first preset threshold value, judging that the battery cell has defects, and if the difference ratio does not exceed the first preset threshold value, judging that the battery cell has no defects. Therefore, whether the electrical core has defects or not is pre-judged before the energy storage system deteriorates to safety failure, and the safety of the energy storage system is improved.

Description

Technical Field

[0001] This application relates to the field of circuit technologies, and particularly to a method for detecting defects in an energy storage system and an energy storage system. Background Art

[0002] With the rapid development of the energy storage industry, the technology for detecting the safety of battery cells in an energy storage system has become increasingly important. Existing battery cell safety detection technologies include: thermal runaway, overvoltage detection of single battery cells, undervoltage, overcurrent, over-temperature, under-temperature, etc.

[0003] However, the existing detection of battery cell defects in an energy storage system still cannot effectively improve the safety of the energy storage system. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method for detecting defects in an energy storage system and an energy storage system, so as to improve the safety of the energy storage system.

[0005] To solve the above technical problems, the embodiments of this application provide a method for detecting defects in an energy storage system, including: obtaining the operating mode of the energy storage system, where the operating mode includes a planned curve mode, a reverse power flow control protection mode, a demand control protection mode, and a target operating mode, and the target operating mode is an operating mode other than the planned curve mode, the reverse power flow control protection mode, and the demand control protection mode; determining a corresponding pulse current according to the operating mode; estimating whether superimposing the pulse current on the battery cells of the energy storage system affects the safe operation of the battery cells, where the battery cells are in a charging mode or a discharging mode; if it does not affect the safe operation of the battery cells, then superimpose the pulse current on the battery cells, and if it affects the safe operation of the battery cells, then prompt that there is a safety risk; after superimposing the pulse current on the battery cells, calculate the equivalent AC impedance of the battery cells in real time; calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, where the predicted equivalent current impedance is the equivalent current impedance when there is no abnormality in the defects of the battery cells; determine whether the difference ratio exceeds a first preset threshold, if the difference ratio exceeds the first preset threshold, determine that the battery cells have defects, and if the difference ratio does not exceed the first preset threshold, determine that the battery cells have no defects.

[0006] The embodiments of this application also provide an energy storage system, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method for detecting defects in an energy storage system as described above.

[0007] In some embodiments, after determining that the battery cell is defective, it further includes: determining whether the difference ratio is greater than a second preset threshold, where the second preset threshold is greater than the first preset threshold; if the difference ratio is less than or equal to the second preset threshold, a defect warning is issued; if the difference ratio is greater than the second preset threshold, the charge-discharge power of the battery cell is reduced; after reducing the charge-discharge power of the battery cell, the steps between obtaining the operating mode of the energy storage system and determining whether the difference ratio is greater than the second preset threshold are re-executed, and if it is determined again that the difference ratio is greater than the second preset threshold, the energy storage system is controlled to stop operating.

[0008] In some embodiments, if the energy storage system is in the demand control protection mode, the pulse current is determined to be a first pulse current according to the demand control protection mode, and the first pulse current is a discharge current; if the energy storage system is in the anti-backflow control protection mode, the pulse current is determined to be a second pulse current according to the anti-backflow control protection mode, and the second pulse current is a charging current; if the energy storage system is in the planned curve mode, the pulse current is determined to be a third pulse current according to the planned curve mode, and the third pulse current is a charge-discharge current; if the energy storage system is in the target operating mode, the pulse current is determined to be a fourth pulse current according to the target operating mode, and the fourth pulse current is a charge-discharge current; the amplitudes of the first pulse current, the second pulse current, the third pulse current, and the fourth pulse current are the same.

[0009] In some embodiments, the method for obtaining the predicted equivalent current impedance is as follows: using the Kalman filter algorithm to obtain an updated impedance change trend model; wherein, the Kalman filter algorithm calculates the update parameters of the impedance change trend model according to the equivalent AC impedance and the charge value of the battery cell, and updates the impedance change trend model according to the update parameters; inputting the charge value of the battery cell into the updated impedance change trend model so that the impedance change trend model outputs the predicted equivalent current impedance.

[0010] In some embodiments, the impedance change trend model is an exponential function model; before using the Kalman filter algorithm to obtain an updated impedance change trend model, it includes: recording in real time the impedance change data of the battery cell during continuous charging or discharging; constructing an initial exponential function model according to the impedance change data; using the Kalman filter algorithm to obtain an updated impedance change trend model includes: using the Kalman filter algorithm to calculate the update parameters of the initial exponential function model according to the equivalent AC impedance and the charge value of the battery cell; obtaining an updated exponential function model by adjusting the parameters of the initial exponential function model according to the update parameters.

[0011] In some embodiments, the updated exponential function model is as follows: ; where A and m are the updated parameters, Z0 is the DC impedance of the battery cell at the initial charging moment, Z is the DC impedance of the battery cell at the target moment, SOC0 is the state of charge value of the battery cell at the initial charging moment, SOC is the state of charge value of the battery cell at the target moment, A is the rate, and m is a constant; the target moment is the moment corresponding to the predicted equivalent current impedance.

[0012] In some embodiments, the calculation method of the difference ratio is as follows: ; where the is the difference ratio, Z1 is the equivalent AC impedance, and Z2 is the predicted equivalent current impedance.

[0013] In some embodiments, the value range of the first preset threshold is 1% to 3%, and the value range of the second preset threshold is 4% to 6%.

[0014] In some embodiments, the pulsed current is a square-wave pulsed current.

[0015] The technical solutions provided by the embodiments of the present application have at least the following advantages: In the defect detection of the embodiments of the present application, a corresponding pulsed current is superimposed on the battery cells of the energy storage system to calculate the equivalent AC impedance of the battery cells. By calculating the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, it is possible to predict in advance whether there are defects in the battery cells before the energy storage system deteriorates to a safety failure, improving the safety of the energy storage system. Moreover, the pulsed current superimposed in the embodiments of the present application is determined according to the operation mode of the energy storage system, and the pulsed current superimposed on the subsequent battery cells corresponds to the operation mode, ensuring that the battery cells can operate normally in each operation mode; before superimposing the pulsed current on the battery cells in the embodiments of the present application, it is predicted whether the superimposed pulsed current affects the safe operation of the battery cells, and the pulsed current is superimposed when the battery cells are safe to superimpose the pulsed current, improving the safety of the battery cells. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] One or more embodiments are illustrated by way of example in the accompanying drawings, which do not constitute a limitation to the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements, unless otherwise stated, and the drawings in the figures do not constitute a proportional limitation.

[0017] Figure 1 is a schematic flowchart of a method for defect detection of an energy storage system according to an embodiment of the present application; Figure 2 is a schematic waveform diagram of a first pulsed current according to an embodiment of the present application; Figure 3 It is a schematic waveform diagram of a second pulse current according to an embodiment of the present application; Figure 4 It is a schematic waveform diagram of a third pulse current and a fourth pulse current according to an embodiment of the present application; Figure 5 It is a schematic flowchart of each sub-step of step 102 in the method for detecting defects in an energy storage system according to an embodiment of the present application; Figure 6 It is a schematic diagram of the real-time change trend of the cell impedance of an energy storage system in the related art; Figure 7 It is another schematic flowchart of the method for detecting defects in an energy storage system according to an embodiment of the present application; Figure 8 It is a schematic structural diagram of an energy storage system according to an embodiment of the present application. Detailed implementation manners

[0018] As can be seen from the background art, the detection of cell defects in existing energy storage systems still cannot effectively improve the safety of energy storage systems.

[0019] An energy storage system generally includes energy storage batteries (such as lithium-ion batteries, lead-acid batteries, flow batteries, sodium-ion batteries), a power conversion system (PCS), a battery management system (BMS), an energy management system (EMS), an electrical connection and protection system, a communication and monitoring system, and auxiliary systems (such as a cooling system, a fire protection system, a housing and protection, etc.).

[0020] Among them, the battery management system is an important part of the energy storage system, which can realize functions such as battery state monitoring (real-time monitoring of parameters such as battery voltage, current, and temperature), battery equalization management (extending the battery life through equalized charging or discharging), and safety protection (preventing abnormal conditions such as overcharging, over-discharging, and overheating of the battery). The energy management system is the "brain" of the energy storage system, responsible for the operation and scheduling of the entire system, and can realize functions such as data acquisition and analysis (acquiring data of the energy storage system, the power grid, the load, etc. and performing real-time analysis), operation strategy formulation (formulating charge and discharge plans, demand control strategies, etc. according to user requirements and power grid requirements), scheduling and control (performing real-time scheduling and control on the power conversion system, the battery management system, etc. according to the operation strategy), and user interface and interaction (providing a user interface to facilitate users to monitor and operate the energy storage system).

[0021] Through analysis and research, it is found that existing battery cell defect detection technologies are all "passive safety" detections carried out when the energy storage system has already experienced a safety failure. Existing battery cell safety detections lack "active safety" identification that can predict in advance before the energy storage system deteriorates to a safety failure, resulting in a relatively low safety level of the energy storage system.

[0022] To solve the above technical problem that the existing battery cell defect detection of the energy storage system still cannot effectively improve the safety of the energy storage system, this application provides a defect detection method for an energy storage system, including: obtaining the operating mode of the energy storage system, where the operating mode includes a planned curve mode, a reverse power flow control protection mode, a demand control protection mode, and a target operating mode, and the target operating mode is an operating mode other than the planned curve mode, the reverse power flow control protection mode, and the demand control protection mode; determining the corresponding pulse current according to the operating mode; estimating whether the superposition of the pulse current on the battery cell of the energy storage system affects the safe operation of the battery cell, where the battery cell is in a charging mode or a discharging mode; if it does not affect the safe operation of the battery cell, then superpose the pulse current on the battery cell, and if it affects the safe operation of the battery cell, then prompt that there is a safety risk; after superposing the pulse current on the battery cell, calculate the equivalent AC impedance of the battery cell in real time; calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, where the predicted equivalent current impedance is the equivalent current impedance when there is no abnormality in the defect of the battery cell; determine whether the difference ratio exceeds a first preset threshold. If the difference ratio exceeds the first preset threshold, it is determined that the battery cell has a defect. If the difference ratio does not exceed the first preset threshold, it is determined that the battery cell has no defect.

[0023] The defect detection in the embodiment of this application superimposes the corresponding pulse current on the battery cell of the energy storage system to calculate the equivalent AC impedance of the battery cell. By calculating the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, it is possible to predict in advance whether the battery cell has a defect before the energy storage system deteriorates to a safety failure, improving the safety of the energy storage system. Moreover, the pulse current superimposed in the embodiment of this application is determined according to the operating mode of the energy storage system, and the subsequent pulse current superimposed on the battery cell corresponds to the operating mode, ensuring that the battery cell can operate normally in each operating mode; in the embodiment of this application, before superimposing the pulse current on the battery cell, it is predicted whether the superposition of the pulse current on the battery cell affects the safe operation of the battery cell, and the pulse current is superimposed only when it is safe to superimpose the pulse current on the battery cell, improving the safety of the battery cell.

[0024] The defect detection method of the energy storage system in the embodiment of this application can be applied in the battery management system or the energy management system of the energy storage system. A computer program is stored inside the battery management system or the energy management system, and when the computer program is executed by a processor, the defect detection method of the energy storage system in the embodiment of this application is implemented.

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will elaborate on each embodiment of this application with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in each embodiment of this application, many technical details are provided to help readers better understand this application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed in this application can still be implemented. The division of the following embodiments is for convenience of description and should not impose any limitation on the specific implementation of this application. The various embodiments can be combined and cross-referenced with each other on the premise of not being contradictory.

[0026] An embodiment of this application relates to a method for detecting defects in an energy storage system. The schematic flowchart is as Figure 1 shown. The method for detecting defects in the energy storage system includes the following steps: Step 101: Obtain the operating mode of the energy storage system.

[0027] The execution entity of the method for detecting defects in the energy storage system in this embodiment is the battery management system or the energy management system of the energy storage system. When the method for detecting defects in the energy storage system in this embodiment is executed through the battery management system of the energy storage system, the energy storage system adopts a three-level battery management system. The three-level battery management system usually adopts a hierarchical architecture, including three levels: a slave control unit (Battery Management Unit, BMU), a master control unit (Battery Cluster Unit, BCU), and a total control unit (Battery Aggregation Unit, BAU). This architecture can achieve hierarchical management and control of the battery cells from the battery module to the battery stack, ensuring the safe, efficient, and reliable operation of the energy storage system. When the method for detecting defects in the energy storage system in this embodiment is executed through the energy management system of the energy storage system, since the energy management system itself has the ability to be responsible for the operation and scheduling of the entire system, by executing the method for detecting defects in the energy storage system in this embodiment through the energy management system, an integrated defect detection solution integrating detection, monitoring, and execution can be implemented on the same hardware, namely the energy management system, to ensure the safe and reliable defect detection of the energy storage system.

[0028] The operating modes in this embodiment include a planned curve mode, a reverse power flow control protection mode, a demand control protection mode, and a target operating mode. Among them, the reverse power flow control protection mode means that the battery cell is in a charging state and the battery cell triggers reverse power flow control protection; the demand control protection mode means that the battery cell is in a charging state or a discharging mode and the battery cell triggers demand control protection; the planned curve mode means that the battery cell is in a charging mode or a discharging mode and the battery cell operates according to a planned curve, and the target operating mode is an operating mode other than the planned curve mode, the reverse power flow control protection mode, and the demand control protection mode.

[0029] The planned curve mode is mainly used in industrial and commercial energy storage scenarios for the purpose of optimizing economic benefits. In this mode, it can be controlled either in the charging state or in the discharging state. In the planned curve mode of the energy storage system, users can configure the charging and discharging power of the battery cells at different times according to local time-of-use electricity prices and other conditions to form a planned curve, thereby controlling the energy storage device to charge and discharge according to the planned curve. For example, users can set the charging state during low electricity price periods and the discharging state during high electricity price periods.

[0030] The anti-backflow control protection mode is mainly applicable to scenarios where strict control of power flow is required, such as when distributed generation equipment is connected to the power grid. In this mode, it is mainly controlled in the discharging state. In the anti-backflow control protection mode of the energy storage system, when the energy storage system is in the discharging state, the energy management system monitors the current direction and power magnitude in real time. If backflow occurs (i.e., the current direction reverses and the energy storage system sends power to the power grid), corresponding measures will be taken. For example, the discharging power of the battery cells will be reduced or the battery cells will be switched to the charging mode to prevent backflow.

[0031] The demand control protection mode is mainly used for demand management to help users reduce demand electricity charges. In this mode, it can be controlled either in the discharging state or in the charging state. In the demand control protection mode of the energy storage system, the energy management system monitors the power on the low-voltage side of the real-time energy storage inverter. When the power on the low-voltage side reaches the limit value, the energy management system will control the battery cells according to the configured parameters. For example, during charging, if the power on the low-voltage side of the energy storage inverter approaches the limit value, the charging power of the battery cells will be reduced; during discharging, if the power on the low-voltage side of the energy storage inverter is greater than the limit value, the discharging power of the battery cells will be reduced.

[0032] In addition to the above-mentioned planned curve mode, anti-backflow control protection mode, and demand control protection mode, the operating modes of the energy storage system also include grid-connected mode, off-grid mode, hybrid mode (flexible switching between grid-connected mode and off-grid mode), self-use mode, peak shaving and valley filling mode, standby power supply mode, load priority mode, AC coupling power supply mode, virtual synchronous generator mode, autonomous mode, dispatching mode, black start mode, multi-user linkage mode, etc. The target operating mode can be one or more of the above operating modes.

[0033] Step 102: Determine the corresponding pulse current according to the operating mode.

[0034] The pulse current in this embodiment is a square wave pulse current. The pulse current corresponding to the energy storage system in different operating modes in this embodiment is different, so that the pulse current superimposed on the subsequent battery cells corresponds to the operating mode, ensuring that the battery cells can operate normally in each operating mode.

[0035] Since the energy management system monitors the power on the low-voltage side of the energy storage converter in real time when the energy storage system is in the demand control protection mode, and when the power reaches the limit value, the energy management system controls the energy storage according to the configured parameters. Especially in the charging mode, the overload on the low-voltage side of the energy storage converter may cause the charging voltage of the battery cells to be too high, posing a safety risk and increasing the probability of defects in the battery cells such as lithium plating phenomenon, resulting in lower safety of the battery cells. Therefore, if the energy storage system is in the demand control protection mode, the pulse current is determined as the first pulse current according to the demand control protection mode, and the first pulse current is a discharge current. As Figure 2 shown, it is a waveform schematic diagram of the first pulse current. The abscissa is time and the ordinate is current. The waveform of the first pulse current presents a periodic pulse shape, and each pulse is negative. By setting the first pulse current as the discharge current, in the charging mode, the power on the low-voltage side of the energy storage converter is reduced, preventing the power on the low-voltage side of the energy storage converter from overloading and improving the safety of the battery cells. At the same time, in the discharge mode, even if the first pulse current is superimposed on the battery cells, which is equivalent to increasing the discharge power of the battery cells, the battery cells can still operate safely and reliably. And because the energy storage system is in the demand control protection mode, even if the power on the low-voltage side of the energy storage converter exceeds the limit value, it can be controlled through the demand control protection mode, ensuring the safety of the energy storage converter.

[0036] Since the energy storage system in the anti-backflow control protection mode is mainly controlled in the discharge state, and its main function is to monitor the current direction and power magnitude in real time to prevent backflow. Therefore, if the energy storage system is in the anti-backflow control protection mode, the pulse current is determined as the second pulse current according to the anti-backflow control protection mode, and the second pulse current is a charging current. As Figure 3 shown, it is a waveform schematic diagram of the second pulse current. The abscissa is time and the ordinate is current. The waveform of the second pulse current presents a periodic pulse shape, and each pulse is positive. By setting the second pulse current as the charging current, when the pulse current is superimposed on the battery cells, the discharge power of the battery cells is appropriately reduced, preventing the backflow phenomenon caused by the large discharge power of the battery cells and improving the safety of the energy storage system.

[0037] Since the energy storage system can be controlled in the charging state or the discharging state in the planned curve mode and the target operation mode, if the pulse current is only set as the charging current or the discharging current, it may increase the actual charging power or discharging power of the battery cell. Therefore, in order to minimize the impact of the pulse current on the charging power or discharging power of the battery cell, if the energy storage system is in the planned curve mode, the pulse current is determined as the third pulse current according to the planned curve mode, and the third pulse current is the charge-discharge current. If the energy storage system is in the target operation mode, the pulse current is determined as the fourth pulse current according to the target operation mode, and the fourth pulse current is the charge-discharge current. The waveform structures of the third pulse current and the fourth pulse current are substantially the same; as Figure 4 shown, it is a waveform schematic diagram of the third pulse current and the fourth pulse current. The abscissa is time and the ordinate is current. The waveforms of the third pulse current and the fourth pulse current present a periodic pulse shape. Each pulse includes a rising edge, a high level (positive), a falling edge, and a low level (negative), forming the charge-discharge current. By setting the third pulse current and the fourth pulse current as the charge-discharge current, when the energy storage system is in the planned curve mode or the target operation mode, the fluctuation of the actual charging power or discharging power of the battery cell is small, improving the safety of the battery cell.

[0038] In some embodiments, the amplitudes of the first pulse current, the second pulse current, the third pulse current, and the fourth pulse current are the same. Referring to Figure 2 , Figure 3 , Figure 4 , for the same energy storage system, the amplitudes of the corresponding first pulse current, second pulse current, third pulse current, and fourth pulse current are the same, that is, in different operation modes of the energy storage system, the amplitudes of the superimposed pulse currents are the same, thus ensuring the consistency of the amplitudes of the pulse currents superimposed on the battery cell and improving the accuracy of defect detection.

[0039] In some embodiments, since the energy storage system may be in two operation modes simultaneously. For example, in some application scenarios, the demand control protection mode and the anti-counterflow protection mode can work together. In this case, when the energy storage system discharges, the demand control protection mode is used to prevent the energy storage converter from being overloaded, and the anti-counterflow control protection mode is used to prevent the current from flowing in the reverse direction. However, the pulse currents corresponding to the two operation modes are different. In order to avoid the problem that the pulse currents corresponding to two or more operation modes are different and cause safety risks to the battery cell, in this embodiment, priorities are set for the above-mentioned planned curve mode, anti-counterflow control protection mode, demand control protection mode, and target operation mode.

[0040] As Figure 5As shown, it is a schematic flowchart of each sub-step of step 102 of this embodiment. Step 102 of this embodiment is to determine the corresponding pulse current according to the operation mode, and specifically includes the following sub-steps: Step 1021, determine whether the energy storage system triggers the demand control protection mode.

[0041] If not, proceed to step 1022; if so, proceed to step 1023.

[0042] Step 1022, determine whether the energy storage system triggers the anti-backflow control protection mode.

[0043] If not, proceed to step 1024; if so, proceed to step 1025.

[0044] Step 1023, determine that the pulse current is the first pulse current according to the demand control protection mode, and the first pulse current is the discharge current.

[0045] Step 1024, determine whether the energy storage system triggers the planned curve mode.

[0046] If not, proceed to step 1026; if so, proceed to step 1027.

[0047] Step 1025, determine that the pulse current is the second pulse current according to the anti-backflow control protection mode, and the second pulse current is the charging current.

[0048] Step 1026, determine that the pulse current is the third pulse current according to the planned curve mode, and the third pulse current is the charge and discharge current.

[0049] Step 1027, determine that the energy storage system is in the target operation mode, and determine that the pulse current is the fourth pulse current according to the target operation mode, and the fourth pulse current is the charge and discharge current.

[0050] In this embodiment, priorities are set for the planned curve mode, anti-backflow control protection mode, demand control protection mode, and target operation mode. When a higher-priority operation mode is triggered, the pulse current corresponding to this operation mode is obtained, thereby avoiding the problem that two or more operation modes operate simultaneously, resulting in different corresponding pulse currents, and improving the safety of the battery cells. At the same time, even when the energy storage system is in the charging state and simultaneously in the demand control protection mode and the anti-backflow control protection mode, by the above steps, the pulse current corresponding to the demand control protection mode, that is, the discharge current, is selected. Since the anti-backflow control protection mode also exists simultaneously, even if the pulse current, that is, the discharge current, it can well prevent the current from flowing back to the power grid, ensuring the safety of the energy storage system. And even if the energy storage system may also be in the planned curve mode at this time, since the superimposed discharge current is relatively small compared to the current of the planned curve, the influence on the discharge power of the battery cells is small, ensuring that the energy storage system can operate in the planned curve mode, so that the defect detection of this embodiment can be carried out without affecting the user's benefits.

[0051] If the demand control protection mode of the energy storage system is not triggered and the anti-backflow control protection mode is triggered, then the pulse current is determined as the second pulse current, that is, the charging current, according to the anti-backflow control protection mode. Even if the energy storage system may also be in the planned curve mode at this time, since the superimposed charging current is relatively small compared to the charging current of the planned curve, the influence on the charging power of the battery cells is small, ensuring that the energy storage system can operate in the planned curve mode, so that the defect detection of this embodiment can be carried out without affecting the user's benefits.

[0052] Step 103: Estimate whether the superimposed pulse current of the battery cells of the energy storage system affects the safe operation of the battery cells.

[0053] If it does not affect the safe operation of the battery cells, then enter Step 104, that is, superimpose a pulse current on the battery cells for subsequent detection. If it affects the safe operation of the battery cells, then enter Step 105, that is, prompt that there is a safety risk and prompt the user of the possible safety risks of superimposing the pulse current.

[0054] The battery cell of this embodiment is in the charging mode or the discharging mode. The energy storage system of this embodiment is applied to the industrial and commercial energy storage system. Compared with other fields such as the power battery system, in the discharging process and the charging process of the industrial and commercial energy storage system of this embodiment, the charge and discharge rate of the battery cell is relatively low, and there is no need for rapid charge and discharge. The energy density requirement is relatively low, and the power density requirement is low. The industrial and commercial energy storage system pays more attention to the long-cycle cycle life and energy storage efficiency, and the change of the battery cell is relatively regular; while the power battery system needs to support high-rate charge and discharge to meet the needs of rapid acceleration and charging of the vehicle. At the same time, it also needs high energy density to increase the vehicle's cruising range and high power density to support the rapid acceleration and climbing of the vehicle, resulting in complex and changeable working conditions in the discharging process of the vehicle's power battery system. And the discharge situation of the battery cell during vehicle driving is mainly randomly determined by the driver according to the road conditions, making it difficult to detect the defects in the discharging process of the power battery system. The defect detection method of the energy storage system of this embodiment can be applied not only to the charging state of the battery cell, but also to the discharging state of the battery cell, so that the defect detection of the energy storage system can be realized in both the charging stage and the discharging stage of the battery cell, improving the comprehensiveness of the battery cell detection and thus improving the safety of the energy storage system.

[0055] Step 104: Superimpose a pulsed current on the battery cell.

[0056] Step 105: Prompt that there is a safety risk.

[0057] In this embodiment, the corresponding pulsed current is determined according to the operating mode of the energy storage system, and when it is estimated that superimposing the pulsed current on the battery cell of the energy storage system does not affect the safe operation of the battery cell, the pulsed current is superimposed on the battery cell for subsequent detection. For example, whether there is lithium plating on the battery cell is detected by superimposing the pulsed current. When it is estimated that superimposing the pulsed current on the battery cell of the energy storage system affects the safe operation of the battery cell, a safety risk is prompted, that is, the user is prompted through the user interface that it is not appropriate to superimpose the pulsed current.

[0058] After superimposing the pulsed current on the battery cell in this embodiment, the energy storage system enters a process of judging whether the impedance of the battery cell meets the requirements. After step 104 of this embodiment, the following steps are further included: Step 106: Calculate the equivalent AC impedance of the battery cell in real time.

[0059] Through analysis and research, it is found that when there are defects in the battery cell, such as lithium plating phenomenon, the corresponding impedance of the battery cell has a decreasing trend. As Figure 6As shown in the figure, it is a schematic diagram of the real-time change trend of the cell impedance of an energy storage system in the related art. The abscissa is the state of charge, and the ordinate is the impedance. When the cell is charged to a state of charge of about 55%, an inflection point M appears in the corresponding impedance change of the cell. After the inflection point M, there is an obvious decrease. This phenomenon is caused by the reversible lithium plating phenomenon inside the cell. After the lithium plating phenomenon lasts for a period of time, there is more reversible lithium plating on the graphite surface of the cell, which is equivalent to an increase in the channels for the deposition of this part of lithium in the intercalation process between lithium ions and graphite. In the equivalent circuit model, it is equivalent to adding a parallel resistor. Therefore, the external characteristics of the cell show an obvious decrease in the impedance of the charge transfer process.

[0060] Therefore, in order to avoid a large amount of reversible lithium plating on the graphite surface of the cell, in this embodiment, when the inflection point M in Figure 6 is reached, it can timely detect that the cell will have a lithium plating phenomenon in the next period of time, so as to make corresponding treatments, such as cloud warning, limiting the charge and discharge power, shutting down and other intervention means, before the energy storage system deteriorates to a safety failure, to ensure the safety of the energy storage unit; while in the related art, the lithium plating phenomenon of the cell is detected only after the lithium plating phenomenon has lasted for a period of time, resulting in an increase in the resistance of the cell and an obvious decrease in the impedance at this time.

[0061] On the basis of the original charge and discharge current of the cell, this embodiment superimposes a pulsed current such as Figure 2 or Figure 3 or Figure 4 . After that, the cell will generate a voltage response. By calculating the relationship between the pulsed current and the response voltage in real time, the real-time equivalent AC impedance of the cell can be approximately obtained; that is, in this embodiment, after superimposing the pulsed current, the equivalent AC impedance of the cell is calculated in real time.

[0062] Step 107, calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance.

[0063] Specifically, after obtaining the equivalent AC impedance of the cell, in order to determine whether the cell has defects such as the lithium plating phenomenon, it is necessary to calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, where the predicted equivalent current impedance is the equivalent current impedance when there is no abnormality in the defects of the cell.

[0064] In some embodiments, the calculation method of the difference ratio is: ; where is the difference ratio, Z1 is the equivalent AC impedance, and Z2 is the predicted equivalent current impedance.

[0065] In this embodiment, by comparing the equivalently alternating current impedance obtained in real time with the predicted approximate equivalently alternating current impedance, calculating the difference ratio between the two, and setting a reasonable deviation threshold, i.e., the first preset threshold, in the subsequent process, it is determined that the battery cell will have defects such as lithium plating phenomenon when the threshold is exceeded.

[0066] In some embodiments, the method for obtaining the predicted equivalently alternating current impedance is as follows: using the Kalman filter algorithm to obtain an updated impedance change trend model; wherein, the Kalman filter algorithm calculates the update parameters of the impedance change trend model according to the equivalently alternating current impedance and the charge value of the battery cell, and updates the impedance change trend model according to the update parameters; inputting the charge value of the battery cell into the updated impedance change trend model so that the impedance change trend model outputs the predicted equivalently alternating current impedance.

[0067] This embodiment not only sets an impedance change trend model, but also calculates the update parameters of the impedance change trend model in real time through the equivalently alternating current impedance and the charge value of the battery cell, and updates the impedance change trend model according to the update parameters, so that the updated impedance change trend model eliminates the influence of detection errors and noise on the impedance, improves the accuracy of the predicted equivalently alternating current impedance, and improves the accuracy of defect detection.

[0068] In some embodiments, the impedance change trend model is an exponential function model; before using the Kalman filter algorithm to obtain the updated impedance change trend model, it includes: recording in real time the impedance change data of the battery cell during continuous charging or discharging; constructing an initial exponential function model according to the impedance change data; using the Kalman filter algorithm to obtain the updated impedance change trend model, including: using the Kalman filter algorithm to calculate the update parameters of the initial exponential function model according to the equivalently alternating current impedance and the charge value of the battery cell; obtaining the updated exponential function model according to the update parameters for the parameters of the initial exponential function model.

[0069] Specifically, this embodiment considers that if only a fixed impedance change trend model is set, it may lead to the predicted equivalently alternating current impedance not considering the influence of the current normal working state (voltage, current, temperature) of each battery cell on the impedance, resulting in inaccurate predicted equivalently alternating current impedance. The equivalently alternating current impedance calculated in real time will consider the influence of the normal working state (voltage, current, temperature) on the impedance, resulting in a large error in the calculated difference ratio when calculating the difference ratio between the equivalently alternating current impedance and the predicted equivalently alternating current impedance, and resulting in poor accuracy of defect detection of the energy storage system.

[0070] Therefore, in order to further improve the accuracy of the predicted equivalent current impedance, in this embodiment, when constructing the initial exponential function model, by recording the impedance change data of the battery cell during continuous charging or discharging, this part of the data retains the influence of the normal working state of the battery cell on the impedance. The initial exponential function model is constructed based on these impedance change data, which also reflects the influence of the normal working state of the battery cell on the impedance. However, the initial exponential function model also reflects some detection errors and noise parts. In order to eliminate the influence of these detection errors and noise parts on the impedance, in this embodiment, the Kalman filter algorithm is used to calculate the update parameters of the initial exponential function model according to the equivalent AC impedance and the charge value of the battery cell, so as to eliminate the influence of these detection errors and noise parts, and only retain the influence of the normal working state of the battery cell on the impedance. Therefore, when calculating the difference ratio, the difference ratio only reflects the influence of battery cell defects such as lithium plating on the impedance, improving the accuracy of defect detection.

[0071] The Kalman filter algorithm mainly reduces noise interference and improves prediction accuracy through a data fusion and iterative update mechanism. The Kalman filter algorithm combines the prior prediction value (the parameters of the initial exponential function model) and the actual observation value (the equivalent AC impedance and the charge value of the battery cell obtained in real time), and performs weighted fusion with the goal of minimizing the error variance to obtain the update parameters of the exponential function model. In this embodiment, by recording the impedance change trend during the past continuous charging or discharging process in real time, an initial exponential function model is established for this dynamic system, the parameters of the initial exponential function model are extracted, and the parameters of the exponential function in the model are updated according to the actually detected AC impedance and the charge value of the battery cell, so as to exclude the detection errors and noise parts as much as possible and reflect the actual change trend.

[0072] In some embodiments, the updated exponential function model is: ; where A and m are update parameters, Z0 is the DC impedance of the battery cell at the initial charging moment, Z is the DC impedance of the battery cell at the target moment, SOC0 is the state of charge value of the battery cell at the initial charging moment, SOC is the state of charge value of the battery cell at the target moment, A is the rate, m is a constant; the target moment is the moment corresponding to the predicted equivalent current impedance.

[0073] Step 108, determine whether the difference ratio exceeds the first preset threshold.

[0074] If the difference ratio exceeds the first preset threshold, go to step 109, that is, determine that the battery cell has a defect. If the difference ratio does not exceed the first preset threshold, go to step 110, that is, determine that the battery cell has no defect.

[0075] After calculating the difference ratio between the equivalent AC impedance and the predicted approximate equivalent current impedance in this embodiment, the difference ratio is compared with a preset first preset threshold. If it exceeds the first preset threshold, it is determined that the battery cell has a defect, such as lithium plating phenomenon.

[0076] Step 109, determine that the battery cell has a defect.

[0077] In this embodiment, when it is determined that the battery cell has a defect, necessary interventions can be carried out by means such as cloud warning, restricting the charge and discharge power, and shutting down the machine.

[0078] Step 110, determine that the battery cell has no defect.

[0079] In this embodiment, when it is determined that the battery cell has no defect, after a period of time, step 101 of this embodiment can be restarted to perform defect detection in the next cycle. By performing defect detection periodically, defects generated during the operation of the battery cell, such as lithium plating phenomenon, can be detected in time, improving the safety of the energy storage system.

[0080] In some embodiments, when it is determined that the battery cell has a defect, in order to determine the corresponding intervention strategy, this embodiment also compares the difference ratio with a second preset threshold. As Figure 7 shown, it is another flow schematic diagram of the defect detection method of the energy storage system in this embodiment. The defect detection method of the energy storage system in this embodiment specifically includes the following steps: Step 201, obtain the operation mode of the energy storage system.

[0081] Step 202, determine the corresponding pulse current according to the operation mode.

[0082] Step 203, estimate whether the superposition of the pulse current on the battery cell of the energy storage system affects the safe operation of the battery cell. If it does not affect the safe operation of the battery cell, go to step 204, that is, superimpose the pulse current on the battery cell. If it affects the safe operation of the battery cell, go to step 205, that is, prompt that there is a safety risk, and prompt the user of the possible safety risks when superimposing the pulse current.

[0083] Step 204, superimpose the pulse current on the battery cell.

[0084] Step 205, prompt that there is a safety risk.

[0085] Step 206, calculate the equivalent AC impedance of the battery cell in real time.

[0086] Step 207, calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance.

[0087] Step 208: Determine whether the difference ratio exceeds the first preset threshold. If the difference ratio exceeds the first preset threshold, proceed to step 209, that is, determine that the battery cell has a defect. If the difference ratio does not exceed the first preset threshold, proceed to step 210, that is, determine that the battery cell has no defect.

[0088] Step 209: Determine that the battery cell has a defect.

[0089] Step 210: Determine that the battery cell has no defect.

[0090] Steps 201 to 210 of this embodiment are substantially the same as Figure 1 steps 101 to 110 therein. To avoid repetition, they will not be elaborated here. Next, steps 211 to 215 of this embodiment will be described in detail.

[0091] Step 211: Determine whether the difference ratio is greater than the second preset threshold.

[0092] Step 211 is executed after step 209. That is, when it is determined that the battery cell has a defect, continue to determine whether the difference ratio is greater than the second preset threshold, where the second preset threshold is greater than the first preset threshold. In some embodiments, the value range of the first preset threshold is 1% to 3%, such as 1%, 2%, 3%, and the value range of the second preset threshold is 4% to 6%, such as 4%, 5%, 6%.

[0093] Specifically, if the difference ratio is less than or equal to the second preset threshold, proceed to step 212, that is, issue a defect warning. If the difference ratio is greater than the second preset threshold, proceed to step 213, that is, determine whether it is the first time to determine that the difference ratio of the battery cell is greater than the second preset threshold.

[0094] Specifically, when the difference ratio is greater than the first preset threshold and less than or equal to the second preset threshold for the first time, at this time, the impedance fluctuation is small, which may be caused by the change of the external environment, and at this time, the influence caused by defects such as lithium deposition is small, and the defects of the battery cell may disappear during subsequent charge and discharge processes. Therefore, in this embodiment, only a defect warning is issued at this time to prompt the user that there may be a defect in the future for a period of time.

[0095] Step 212: Issue a defect warning.

[0096] Step 213: Determine whether it is the first time to determine that the difference ratio of the battery cell is greater than the second preset threshold.

[0097] If so, proceed to step 214 to reduce the charge and discharge power of the battery cell. After reducing the charge and discharge power of the battery cell, enter the next cycle and continue to execute each step between step 201 and step 211; if not, proceed to step 215 to control the energy storage system to stop operating. After the energy storage system stops operating, the number of times the determined battery cell difference ratio is greater than the second preset threshold is cleared, and the calculation is restarted after the next startup.

[0098] Step 214: Reduce the charge and discharge power of the battery cell.

[0099] Step 215: Control the energy storage system to stop operating.

[0100] In this embodiment, when it is first determined that the battery cell difference ratio is greater than the second preset threshold, it indicates that the impedance of the battery cell reaches the inflection point M as shown in Figure 6 The predicted battery cell may have defects inside in the next period of time. By reducing the charge and discharge power of the battery cell, the probability of the battery cell having defects in the next period of time can be reduced without affecting the operation of the energy storage system. Therefore, in this embodiment, after reducing the charge and discharge power of the battery cell, enter the next cycle. If it is determined again that the battery cell difference ratio is greater than the second preset threshold, it means that it is predicted that the battery cell will have defects such as lithium plating in the next period of time and the probability of this defect occurring cannot be reduced by reducing the charge and discharge power of the battery cell, thus affecting the safe operation of the battery cell. Therefore, in this embodiment, when it is determined again that the battery cell difference ratio is greater than the second preset threshold, the energy storage system is controlled to stop operating, that is, before the energy storage system deteriorates to a safety failure due to a large defect, the energy storage system is controlled to stop operating to improve the safety of the energy storage system.

[0101] An embodiment of the present application relates to an energy storage system, as shown in Figure 8 It includes: at least one processor 301; and a memory 302 communicatively connected to the at least one processor 301; wherein, the memory stores instructions executable by the at least one processor 301, and the instructions are executed by the at least one processor 301 so that the at least one processor 301 can execute the above-mentioned defect detection method of the energy storage system.

[0102] Among them, the memory 302 and the processor 301 are connected in a bus manner. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors 301 and the memory 302 together. The bus can also connect various other circuits together, such as peripheral devices, voltage regulators, and power management circuits, etc., which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a component or multiple components, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on the transmission medium. The data processed by the processor 301 is transmitted on the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor 301.

[0103] The processor 301 is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. The memory 302 can be used to store the data used by the processor when executing operations.

[0104] An embodiment of the present application relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the above method embodiment is implemented.

[0105] That is, those skilled in the art can understand that all or part of the steps in implementing the above method embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions for causing a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the method embodiments of the present application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0106] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present application, and in practical applications, various changes can be made in form and details without departing from the spirit and scope of the present application.

Claims

1. A method for detecting defects in an energy storage system, characterized in that, Including: Obtain the operating mode of the energy storage system, where the operating mode includes a planned curve mode, a reverse power flow control protection mode, a demand control protection mode, and a target operating mode, and the target operating mode is an operating mode other than the planned curve mode, the reverse power flow control protection mode, and the demand control protection mode; Determine the corresponding pulse current according to the operating mode; Estimate whether superimposing the pulse current on the battery cells of the energy storage system affects the safe operation of the battery cells, where the battery cells are in a charging mode or a discharging mode; if it does not affect the safe operation of the battery cells, then superimpose the pulse current on the battery cells, and if it affects the safe operation of the battery cells, then prompt that there is a safety risk; After superimposing the pulse current on the battery cells, calculate the equivalent AC impedance of the battery cells in real time; Calculate the difference ratio between the equivalent AC impedance and the predicted equivalent current impedance, where the predicted equivalent current impedance is the equivalent current impedance when there is no abnormality in the defects of the battery cells; Judge whether the difference ratio exceeds a first preset threshold. If the difference ratio exceeds the first preset threshold, it is determined that the battery cells have defects. If the difference ratio does not exceed the first preset threshold, it is determined that the battery cells have no defects.

2. The defect detection method for the energy storage system according to claim 1, wherein After determining that the battery cells have defects, it further includes: Judge whether the difference ratio is greater than a second preset threshold, where the second preset threshold is greater than the first preset threshold; If the difference ratio is less than or equal to the second preset threshold, then issue a defect warning; If the difference ratio is greater than the second preset threshold, then reduce the charge and discharge power of the battery cells; after reducing the charge and discharge power of the battery cells, re-execute the steps between obtaining the operating mode of the energy storage system and judging whether the difference ratio is greater than the second preset threshold. If it is again determined that the difference ratio is greater than the second preset threshold, then control the energy storage system to stop operating.

3. The defect detection method of the energy storage system according to claim 1, characterized in that, If the energy storage system is in the demand control protection mode, determine that the pulse current is a first pulse current according to the demand control protection mode, and the first pulse current is a discharge current; If the energy storage system is in the reverse power flow control protection mode, determine that the pulse current is a second pulse current according to the reverse power flow control protection mode, and the second pulse current is a charging current; If the energy storage system is in the planned curve mode, determine that the pulse current is a third pulse current according to the planned curve mode, and the third pulse current is a charge and discharge current; If the energy storage system is in the target operating mode, determine that the pulse current is a fourth pulse current according to the target operating mode, and the fourth pulse current is a charge and discharge current; the amplitudes of the first pulse current, the second pulse current, the third pulse current, and the fourth pulse current are the same.

4. The defect detection method of the energy storage system according to claim 1, wherein, The obtaining method of the predicted equivalent current impedance is: The updated impedance change trend model is obtained by using the Kalman filtering algorithm; wherein, the Kalman filtering algorithm calculates the update parameters of the impedance change trend model according to the equivalent AC impedance and the charge value of the battery cell, and updates the impedance change trend model according to the update parameters; The charge value of the battery cell is input into the updated impedance change trend model so that the impedance change trend model outputs the predicted equivalent current impedance.

5. The defect detection method for the energy storage system according to claim 4, wherein, The impedance change trend model is an exponential function model; before obtaining the updated impedance change trend model by using the Kalman filtering algorithm, it includes: Real-time record the impedance change data of the battery cell during continuous charging or discharging; Construct an initial exponential function model according to the impedance change data; The obtaining of the updated impedance change trend model by using the Kalman filtering algorithm includes: Using the Kalman filtering algorithm to calculate the update parameters of the initial exponential function model according to the equivalent AC impedance and the charge value of the battery cell; Obtain the updated exponential function model according to the update parameters for the parameters of the initial exponential function model.

6. The method for detecting defects of the energy storage system according to claim 5, characterized in that, The updated exponential function model is as follows: ; Wherein, A and m are the update parameters, Z0 is the DC impedance of the battery cell at the initial charging moment, Z is the DC impedance of the battery cell at the target moment, SOC0 is the state of charge value of the battery cell at the initial charging moment, SOC is the state of charge value of the battery cell at the target moment, A is the rate, m is a constant; the target moment is the moment corresponding to the predicted equivalent current impedance.

7. The defect detection method for the energy storage system according to claim 1, characterized in that The calculation method of the difference ratio is as follows: ; Among them, the is the difference ratio, Z1 is the equivalent AC impedance, and Z2 is the predicted equivalent current impedance.

8. The defect detection method of the energy storage system according to claim 2, wherein The value range of the first preset threshold is 1% to 3%, and the value range of the second preset threshold is 4% to 6%.

9. The defect detection method of the energy storage system according to claim 1, wherein the pulsed current is a square wave pulsed current.

10. A energy storage system, characterized in that, It includes: At least one processor; And, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the defect detection method of the energy storage system according to any one of claims 1 to 9.

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