Double-layer optimization method for plug-in box optimizer

Abstract

The invention provides a double-layer optimization method for a plug-in box optimizer, and belongs to the technical field of electric energy storage. The method aims at a plurality of battery clusters connected in parallel under the control of a PCS, each battery cluster comprises a plurality of plug-in box optimization groups connected in series, and each plug-in box optimization group comprises a battery plug-in box and a plug-in box optimizer connected with the battery plug-in box in series. The method specifically comprises the following steps of: selecting the battery cluster with the maximum current quantity for optimization processing when the charging and discharging current quantities of a plurality of battery clusters are not equal; after the optimization processing of the battery cluster with the maximum magnitude of current is completed, searching the next battery cluster with the maximum magnitude of current, and performing optimization processing; the current magnitudes among the plurality of battery clusters are equal. Through the double-layer optimization method of the plug-in box optimizer, the service life and the safety of the battery are effectively ensured, and the cost of the electrochemical energy storage system is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of electric energy storage, and in particular relates to a double-layer optimization method for a plug-in box optimizer. Background Art

[0002] Large-scale electrochemical energy storage systems are composed of multiple batteries connected in series to form a battery cluster, and multiple battery clusters are connected in parallel to form a battery stack. During the operation of large-scale electrochemical energy storage, the inconsistency of each battery cluster will cause electrical circulation between clusters; the electrical circulation between battery clusters will aggravate the inconsistency of battery clusters, thereby further increasing the electrical circulation and forming a vicious cycle. Such a vicious cycle will aggravate the attenuation of the battery stack capacity. In addition, the inconsistency of batteries within a battery cluster will also cause the battery cluster to have excess capacity that cannot be charged or discharged. Summary of the invention

[0003] The purpose of the present invention is to solve the above-mentioned problems existing in the prior art and provide a new plug-in box optimization method, namely a double-layer optimization method of a plug-in box optimizer, which balances the current within and between battery clusters through the plug-in box optimizer.

[0004] The present invention is achieved through the following technical solutions:

[0005] A double-layer optimization method for a plug-in box optimizer, the method is for a plurality of parallel battery clusters under the control of an energy storage converter PCS, the battery clusters comprising a plurality of plug-in box optimization groups connected in series, the plug-in box optimization group comprising a battery plug-in box and a plug-in box optimizer connected in series therewith;

[0006] The method is specifically as follows:

[0007] If the charging and discharging currents of multiple battery clusters are not equal, the battery cluster with the largest current is optimized;

[0008] After the optimization process for the battery cluster with the largest current is completed, searching for the next battery cluster with the largest current and optimizing it;

[0009] The process continues in this way until the currents of multiple battery clusters are equal.

[0010] Furthermore, the operation of optimizing the battery cluster with the largest current includes:

[0011] Perform the following optimization operations on all the plug-in optimization groups in the battery cluster in sequence;

[0012] The DC / DC conversion circuit inside the plug-in box optimizer in the plug-in box optimization group is turned off, so that the current is charged and discharged through the bypass circuit.

[0013] Furthermore, the specific steps of the method are:

[0014] Step (1), determining whether the battery stack is being charged, if yes, proceeding to step (2), if no, proceeding to step (6);

[0015] Step (2), calculating the current difference ΔI between battery clusters;

[0016] Step (3), determining whether the current difference ΔI between the battery clusters is greater than a threshold value, if yes, proceeding to step (4), if no, proceeding to step (11);

[0017] Step (4), putting into operation the battery box optimizer corresponding to the battery box with the highest average voltage in the battery cluster with the maximum charging current;

[0018] Step (5), after sending the optimizer target voltage value, return to step (3);

[0019] Step (6), determining whether the battery stack is discharging, if yes, proceeding to step (7), if no, proceeding to step (11);

[0020] Step (7), calculating the current difference ΔI between battery clusters;

[0021] Step (8), determining whether the current difference ΔI between the battery clusters is greater than a threshold value, if yes, proceeding to step (9), if no, proceeding to step (11);

[0022] Step (9), putting into operation the battery box optimizer corresponding to the battery box with the lowest average voltage in the battery cluster with the maximum discharge current;

[0023] Step (10), after sending the optimizer target voltage value, return to step (8);

[0024] Step (11) ends.

[0025] Furthermore, in step (2), the current difference ΔI between the battery clusters is obtained by the following formula:

[0026] ΔI = maximum cluster charging current - minimum cluster charging current;

[0027] The maximum cluster charging current refers to the charging current of the battery cluster with the largest charging current, and the minimum cluster charging current refers to the charging current of the battery cluster with the smallest charging current.

[0028] Further, the specific operation of step (4) is as follows:

[0029] Find the charging currents I1, I2, ... I of the battery cluster n The battery cluster corresponding to the maximum charging current in is taken as the maximum charging battery cluster;

[0030] The average voltage of each battery plug-in box in the largest rechargeable battery cluster is calculated respectively, the battery plug-in box with the highest average voltage is found, and the plug-in box optimizer corresponding to the battery plug-in box with the highest average voltage is put into operation.

[0031] Furthermore, in step (7), the current difference ΔI between the battery clusters is obtained by the following formula:

[0032] ΔI = maximum cluster discharge current - minimum cluster discharge current;

[0033] The maximum cluster discharge current refers to the discharge current of the battery cluster with the largest discharge current, and the minimum cluster discharge current refers to the discharge current of the battery cluster with the smallest discharge current.

[0034] Further, the specific operation of step (9) is as follows:

[0035] Find the discharge current I1, I2, ... I of the battery cluster n The battery cluster corresponding to the maximum discharge current in is taken as the maximum discharge battery cluster;

[0036] The average voltage of each battery plug-in box in the maximum discharge battery cluster is calculated respectively, the battery plug-in box with the lowest average voltage is found, and the plug-in box optimizer corresponding to the battery plug-in box with the lowest average voltage is put into operation.

[0037] Furthermore, the threshold value is a fixed value set according to the state of the battery, specifically 10% of the rated charge and discharge current of the battery.

[0038] Furthermore, the optimizer target voltage value is adjusted according to the change of the current difference ΔI between the battery clusters. When the current difference ΔI between the battery clusters decreases, an optimizer target voltage value adjusted according to the minimum step size is continuously issued.

[0039] Further, the optimizer target voltage value is obtained by the following formula:

[0040] Optimizer target voltage value = initial target voltage value - n*minimum step size;

[0041] Here, n is 1%.

[0042] Compared with the prior art, the beneficial effects of the present invention are: effectively ensuring the life and safety of the battery and reducing the cost of the electrochemical energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a diagram of the overall architecture of the battery stack implemented by the optimization method of the present invention;

[0044] Figure 2 is a flow chart of the optimization method of the present invention;

[0045] Figure 3It is a schematic diagram of the composition structure of the battery plug box optimizer of the present invention. DETAILED DESCRIPTION

[0046] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0047] The present invention is based on Figure 1 A battery cluster and intra-cluster optimization method for a large-scale electrochemical energy storage system based on a battery stack architecture.

[0048] like Figure 1 As shown, the architecture includes an energy storage inverter PCS, and multiple battery clusters respectively connected to the energy storage inverter PCS, each battery cluster includes multiple plug-in box optimization groups connected in series, each plug-in box optimization group includes battery plug-ins and plug-in box optimizers connected in series, that is, a plug-in box optimizer is connected to each battery plug-in box; multiple groups of batteries are arranged in each battery plug-in box; multiple plug-in box optimization groups are connected in series, and the plug-in box optimizer located at the top of each battery cluster is connected to the DC side of the energy storage inverter PCS.

[0049] The energy storage converter PCS is responsible for controlling the charging and discharging process of the battery and performing AC / DC conversion. It controls multiple battery clusters. In this embodiment, two battery clusters are taken as an example, which can actually be expanded to multiple battery clusters. Specifically, the energy storage converter PCS outputs current to each parallel battery cluster. The double-layer optimization method of the present invention is to control the electric circulation (i.e., the current difference between the maximum current and the minimum current among all battery clusters in the battery stack) through the plug-in box optimizer to solve the shortcomings of the energy storage battery and achieve current balance among battery clusters.

[0050] like Figure 3 As shown, each plug-in box optimizer includes a main control unit and a DC / DC conversion circuit and a high-speed communication interface respectively connected thereto. Among them, the positive and negative electrodes at one end of the DC / DC conversion circuit are respectively connected to the positive and negative output electrodes of the battery plug-in box, and the positive and negative electrodes at the other end of the DC / DC conversion circuit are respectively connected to the positive and negative electrodes of the cascade circuit. The plug-in box optimization group where the plug-in box optimizer is located can be connected in series with other plug-in box optimization groups through the cascade circuit, that is, the cascade side end (cascade circuit) of the plug-in box optimizer is connected to the cascade side end (cascade circuit) of the plug-in box optimizer in the adjacent plug-in box optimization group. The high-speed communication interface can be connected to the cluster management system and the battery management system.

[0051] The cascade circuit of the topmost plug-in box optimizer in each battery cluster is connected to the DC side of the energy storage converter PCS, and the high-speed communication interface of the topmost plug-in box optimizer in each battery cluster is connected to the cluster management system.

[0052] Furthermore, a bypass circuit is provided inside the plug-in box optimizer, one end of the bypass circuit is connected to the output positive and negative poles of the battery plug-in box, and the other end is connected to the positive and negative poles of the cascade circuit, so that during the plateau period of battery charging and discharging, the bypass circuit is controlled to be connected through the cluster management system, and the DC / DC conversion circuit is controlled to be closed at the same time, so that the current is charged and discharged through the bypass circuit, and the DC / DC conversion circuit does not work. Only at the end of battery charging or discharging, the cluster management system controls the bypass circuit to be disconnected, and controls the DC / DC conversion circuit to be turned on, so that the DC / DC conversion circuit is put into operation (specifically, the existing circuit control method is used to control the on and off of the bypass circuit and the DC / DC conversion circuit through PLC programming to achieve this function, which will not be repeated here). In this way, the present invention eliminates the shortcomings between the battery plug-ins in the battery cluster through the bypass circuit. Under normal circumstances, during the entire charging and discharging process, the bypass circuit will not be affected by the loss of charging and discharging efficiency. Only at the end of charging and discharging, the DC / DC conversion circuit is put into operation, which greatly improves the charging and discharging efficiency.

[0053] Furthermore, the battery data uploaded by each battery management system in the battery cluster (the data include the voltage and temperature of each battery in the battery cluster) and the data uploaded by the plug-in box optimizer (the data include the PACK voltage and the working status of the plug-in box optimizer, etc.) are obtained, and according to the analysis results of the above data and the instructions issued by the centralized control device, the operation mode of the plug-in box optimizer is controlled (the specific control of the operation mode of the plug-in box optimizer belongs to the prior art and will not be repeated here.).

[0054] Specifically, the SOC and SOH values ​​of each battery are calculated, the SOC and SOH values ​​of each battery plug box are calculated, and the SOC and SOH values ​​of the entire battery cluster are calculated. Based on these data analysis results and the instructions received from the centralized control device, the operation mode of the plug box optimizer is controlled. (The specific SOC and SOH value algorithms and control instructions are all existing technologies and will not be repeated here.)

[0055] Furthermore, the centralized control device is responsible for receiving external instructions and informing the superior control system of the charge and discharge capacity of the entire battery stack, and charging and discharging the entire battery cluster. In addition, the cluster management system and the energy storage converter PCS also have interconnected control logic (for example, power reduction operation, etc.) to protect the battery charge and discharge current within a reasonable range. (The specific battery management system, cluster management system and centralized control device are all existing technologies and will not be repeated here.)

[0056] Furthermore, in the initial state, all the plug-in optimizers are working in the direct state, that is, the plug-in optimizers can be regarded as not working, but the batteries are in the state of operation. Due to the differences in the battery clusters themselves, a circulation will be generated between the two clusters. Assuming that the total charging power of the two battery clusters is constant, the two battery clusters are connected in parallel, so their voltages are also the same, but the different charging currents lead to different charging powers of the two clusters. At this time, the specific plug-in optimizer is selected according to the optimization algorithm calculation. The plug-in optimizer can adjust the charging and discharging power of one of the battery plug-ins in the cluster, thereby adjusting the power of the entire battery cluster. In this way, the cycle gradually adjusts the power of the two clusters to balance, and the circulation will disappear. Further, the operation of multiple battery clusters is to perform the above optimization operation on the battery cluster with the largest current; after completing the optimization of the battery cluster, find the next battery cluster with the largest current, and perform the above optimization operation in turn; until the charging power between the battery clusters is equal.

[0057] Specifically, Figure 1 In the present invention, the currents of the two battery clusters for charging and discharging are I1 and I2, respectively, wherein the currents of I1 and I2 are not equal. The first level of optimization of the double-layer optimization method of the plug-in box optimizer of the present invention is to select the battery cluster with the highest current for optimization according to the current circulation of the battery cluster for charging and discharging.

[0058] like Figure 2 As shown, the second-level optimization process of the double-layer optimization method of the plug-in box optimizer of the present invention is: first, the current difference ΔI between battery clusters is calculated; then, according to whether the current difference ΔI between battery clusters is greater than the threshold value, the plug-in box optimizer is gradually put into use, and the plug-in box optimizer is controlled to perform optimization. The present invention takes the battery cluster where the current I1 is located as an example. The current I1 is optimized on the battery plug-in box 1 by the plug-in box optimizer 1 in the put-in mode, that is, the DC / DC conversion circuit inside the plug-in box optimizer 1 is controlled to be turned off, so that the current I1 is charged and discharged through the bypass circuit. The current I1 continues to flow to the subsequent plug-in box optimization group, and is successively put into the plug-in box optimizer for optimization processing until all the plug-in box optimization groups in this battery cluster have been processed.

[0059] The specific optimization order of the slot optimizer is: when charging, the slot optimizer corresponding to the battery slot with the highest average voltage is put into operation to solve the problem that the remaining capacity cannot be released due to the inconsistency of the batteries in the cluster during charging; when discharging, the slot optimizer corresponding to the battery slot with the lowest average voltage is put into operation to solve the problem that the remaining capacity cannot be released due to the inconsistency of the batteries in the cluster during discharging. The optimization process is as follows Figure 2In the figure, the left and right branches represent the optimization process under charging and discharging conditions, respectively. That is, the charging and discharging state of the battery stack is judged, and the current difference ΔI between battery clusters is calculated; it is judged whether the current difference ΔI between battery clusters is greater than the threshold value and the current difference ΔI between battery clusters is limited to a reasonable range through optimization to achieve battery balance in the same cluster.

[0060] The specific steps of the method of the present invention are as follows:

[0061] Step (1) determines whether the battery stack is being charged. If so, proceed to step (2); if not, proceed to step (6).

[0062] Specifically, the cluster management system determines whether the battery stack is in a charging or discharging state based on the data uploaded by the main control unit. The cluster management system and the main control unit are both existing technologies, and the determination method can adopt the existing method, which will not be repeated here.

[0063] Step (2) calculates the current difference between battery clusters.

[0064] ΔI is the current difference between battery clusters, which is obtained by the following formula:

[0065] ΔI=Maximum cluster charging current - minimum cluster charging current

[0066] The maximum cluster charging current and the minimum cluster charging current are both acquired through the battery management system, and refer to the charging current of the battery cluster with the largest charging current and the charging current of the battery cluster with the smallest charging current, respectively.

[0067] Step (3) determines whether the current difference ΔI between the battery clusters is greater than a threshold value. If yes, proceed to step (4); if not, proceed to step (11).

[0068] The threshold value is a fixed value, and the specific value is set according to the state of the battery. In the present invention, it is 10% of the rated charge and discharge current of the battery.

[0069] Step (4) puts into operation the battery box optimizer corresponding to the battery box with the highest average voltage in the maximum charging current cluster.

[0070] Specifically, find the charging currents I1, I2, ...I of the battery cluster. n The battery cluster corresponding to the maximum charging current in is taken as the maximum charging battery cluster, and then the average voltage of each battery box in the maximum charging battery cluster is calculated respectively, and the battery box with the highest average voltage is found, and the box optimizer corresponding to the battery box with the highest average voltage is put into operation.

[0071] After step (5) sends the optimizer target voltage value, return to step (3).

[0072] The optimizer target voltage value is sent to the slot optimizer corresponding to the battery slot with the highest average voltage with the minimum step size (the specific minimum step size value is determined according to different adjustment requirements). The battery slot with the highest average voltage is selected here because it shows the imbalance within the cluster. During the charging process, the cluster can balance the battery cluster by limiting the charging of the battery slot with the highest average voltage to achieve balance within the cluster. The slot optimizer corresponding to the selected battery slot with the highest average voltage is used to optimize the battery slot.

[0073] The specific optimization process is as follows:

[0074] The main control unit of the plug-in box optimizer receives the output voltage command value sent by the centralized control device, and drives the DC / DC conversion circuit according to the output voltage command value, so that the plug-in box optimizer naturally inputs or outputs current to the port on the battery plug-in box side according to the output current (this is the control logic inside the DC / DC conversion circuit, which will not be repeated here). At this time, the battery plug-in box side is clamped by the battery voltage, the cascade side voltage is controlled by this plug-in box optimizer, and the output current is controlled by the energy storage inverter as a whole (that is, the output and input power of the charging and discharging are controlled by the inverter). According to the power balance principle, the current on the battery plug-in box side naturally changes with the other three variables (that is, the battery voltage, the cascade side voltage and the output current). The specific optimization method of the plug-in box optimizer belongs to the prior art and will not be repeated here.

[0075] Through optimization, the current difference ΔI between battery clusters is reduced.

[0076] Wherein, optimizer target voltage value = initial target voltage value - n*minimum step size;

[0077] In the present invention, n is 1%.

[0078] Furthermore, the initial value of the optimizer target voltage value is determined according to different adjustment requirements, and the optimizer target voltage value optimized each time is a negative feedback variable, that is, the initial value of the target voltage value is sent to the plug-in box optimizer. When the current difference ΔI between the battery clusters decreases, an optimizer target voltage value adjusted according to the minimum step size continues to be sent.

[0079] Specifically, the optimizer target voltage value sent down each time is adjusted according to the change of the current difference ΔI between battery clusters. That is, the current difference ΔI between battery clusters is compared with the threshold value to decide whether to send down the target voltage value, and the change of the target value sent down each time is determined by whether the current difference ΔI between battery clusters becomes smaller. For example, the initial value of the optimizer target voltage value is 50V, the minimum step is 0.5V, and the optimizer target voltage value sent down is 49.5V; observe whether the current difference ΔI between battery clusters becomes smaller: if it becomes smaller, send down a minimum step of 0.5, and the optimizer target voltage value sent down becomes 49; if it becomes larger, the optimizer target voltage value sent down is set to 49.5V. The optimization is terminated until the current difference ΔI between battery clusters is less than or equal to the threshold value.

[0080] Step (6) determines whether the battery stack is discharging. If yes, proceed to step (7); if not, proceed to step (11).

[0081] Step (7) calculates the current difference between battery clusters.

[0082] ΔI is the current difference between battery clusters, which is obtained by the following formula:

[0083] ΔI=maximum cluster discharge current-minimum cluster discharge current

[0084] The maximum cluster discharge current and the minimum cluster discharge current are both acquired through the battery management system, and refer to the discharge current of the battery cluster with the largest discharge current and the discharge current of the battery cluster with the smallest discharge current, respectively.

[0085] Step (8) determines whether the current difference is greater than a threshold value. If yes, proceed to step (9); if no, proceed to step (11).

[0086] The threshold value is a fixed value, and the specific value is set according to the state of the battery. In the present invention, it is 10% of the rated charge and discharge current of the battery.

[0087] Step (9) puts into operation the battery box optimizer corresponding to the battery box with the lowest average voltage in the maximum discharge current cluster.

[0088] Specifically, find the discharge currents I1, I2, ...I of the battery cluster. n The battery cluster corresponding to the maximum discharge current in is taken as the maximum discharge battery cluster, and then the average voltage of each battery plug-in box in the maximum discharge battery cluster is calculated respectively, and the battery plug-in box with the lowest average voltage is found, and the plug-in box optimizer corresponding to the battery plug-in box with the lowest average voltage is put into operation.

[0089] After step (10) sends the optimizer target voltage value, return to step (8)

[0090] With the minimum step size (the specific minimum step size is determined according to different adjustment requirements), send the optimizer target voltage value to the battery box optimizer corresponding to the battery box with the lowest average voltage, and optimize the battery box through the box optimizer (the optimization method of the box optimizer belongs to the prior art and will not be repeated here). As with the principle of the charging process, the battery box with the lowest average voltage is selected here because during the discharge process, the lowest average voltage indicates that this battery box is the short board point in the cluster, and the overall balance of the batteries in the cluster can be achieved by limiting its discharge. Use the box optimizer corresponding to the selected battery box with the lowest average voltage to optimize the battery box.

[0091] The specific optimization process is as follows:

[0092] The main control unit of the plug-in box optimizer receives the output voltage command value sent by the centralized control device, and drives the DC / DC conversion circuit according to the output voltage command value, so that the plug-in box optimizer naturally inputs or outputs current to the port on the battery plug-in box side according to the output current (this is the control logic inside the DC / DC change circuit, which controls the duty cycle and will not be repeated here). At this time, the battery plug-in box side is clamped by the battery voltage, the cascade side voltage is controlled by this plug-in box optimizer, and the output current is controlled by the energy storage inverter as a whole (that is, the output and input power of the charging and discharging are controlled by the inverter). According to the power balance principle, the current on the battery plug-in box side naturally changes with the other three variables (that is, the battery voltage, the cascade side voltage and the output current). The specific optimization method of the plug-in box optimizer belongs to the prior art and will not be repeated here.

[0093] Through optimization, the current difference ΔI between battery clusters is reduced.

[0094] Wherein, optimizer target voltage value = initial target voltage value - n*minimum step size;

[0095] In the present invention, n is 1%.

[0096] Furthermore, the initial value of the optimizer target voltage is determined according to different adjustment requirements, and the optimizer target voltage value optimized each time is a negative feedback variable, that is, the initial value of the target voltage is sent to the plug-in box optimizer. When the current difference ΔI between battery clusters decreases, an optimizer target voltage value adjusted according to the minimum step size continues to be sent.

[0097] Specifically, each time the optimization process is repeated, the optimizer target voltage value sent down each time is adjusted according to the change of the current difference ΔI between the battery clusters. For example, the initial value of the optimizer target voltage value is 50V, the minimum step is 0.5V, and the optimizer target voltage value sent down is 49.5V; observe whether the current difference ΔI between the battery clusters decreases: if it decreases, send another minimum step of 0.5, and the optimizer target voltage value sent down becomes 49; if it increases, the optimizer target voltage value sent down is set to 49.5V. The optimization ends when the current difference ΔI between the battery clusters is less than or equal to the threshold value.

[0098] (11)End.

[0099] At this point, when the circulating current (i.e., the current difference between the maximum current and the minimum current among all battery clusters in the battery stack) is less than or equal to the threshold value, the batteries within the cluster are balanced; at the same time, the batteries between clusters are also balanced.

[0100] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0101] The above technical solution is only one implementation mode of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the principles disclosed in the present invention, and it is not limited to the technical solution described in the above specific embodiments of the present invention. Therefore, the above description is only preferred and does not have a restrictive meaning.

Claims

1. A two-layer optimization method for a plug-in box optimizer, characterized in that: The method is directed to a plurality of parallel battery clusters under the control of an energy storage converter PCS, wherein the battery cluster comprises a plurality of plug-in box optimization groups connected in series, and the plug-in box optimization group comprises a battery plug-in box and a plug-in box optimizer connected in series therewith; The method is specifically as follows: If the charging and discharging currents of multiple battery clusters are not equal, the battery cluster with the largest current is optimized; After the optimization process for the battery cluster with the largest current is completed, searching for the next battery cluster with the largest current and optimizing it; The process continues in this way until the currents of multiple battery clusters are equal.

2. The double-layer optimization method of the plug-in optimizer according to claim 1, characterized in that: The operation of optimizing the battery cluster with the largest current includes: Perform the following optimization operations on all the plug-in optimization groups in the battery cluster in sequence; The DC / DC conversion circuit inside the plug-in box optimizer in the plug-in box optimization group is turned off, so that the current is charged and discharged through the bypass circuit.

3. The double-layer optimization method of the plug-in box optimizer according to claim 1 or 2, characterized in that: The specific steps of the method are: Step (1), determining whether the battery stack is being charged, if yes, proceeding to step (2), if no, proceeding to step (6); Step (2), calculating the current difference ΔI between battery clusters; Step (3), determining whether the current difference ΔI between the battery clusters is greater than a threshold value, if yes, proceeding to step (4), if no, proceeding to step (11); Step (4), putting into operation the battery box optimizer corresponding to the battery box with the highest average voltage in the battery cluster with the maximum charging current; Step (5), after sending the optimizer target voltage value, return to step (3); Step (6), determining whether the battery stack is discharging, if yes, proceeding to step (7), if no, proceeding to step (11); Step (7), calculating the current difference ΔI between battery clusters; Step (8), determining whether the current difference ΔI between the battery clusters is greater than a threshold value, if yes, proceeding to step (9), if no, proceeding to step (11); Step (9), putting into operation the battery box optimizer corresponding to the battery box with the lowest average voltage in the battery cluster with the maximum discharge current; Step (10), after sending the optimizer target voltage value, return to step (8); Step (11) ends.

4. The double-layer optimization method of the plug-in optimizer according to claim 3 is characterized in that: In the step (2), the current difference ΔI between the battery clusters is obtained by the following formula: ΔI = maximum cluster charging current - minimum cluster charging current; The maximum cluster charging current refers to the charging current of the battery cluster with the largest charging current, and the minimum cluster charging current refers to the charging current of the battery cluster with the smallest charging current.

5. The double-layer optimization method of the plug-in optimizer according to claim 3 is characterized in that: The specific operations of step (4) are: Find the charging currents I1, I2, ... I of the battery cluster n The battery cluster corresponding to the maximum charging current in is taken as the maximum charging battery cluster; The average voltage of each battery plug-in box in the largest rechargeable battery cluster is calculated respectively, the battery plug-in box with the highest average voltage is found, and the plug-in box optimizer corresponding to the battery plug-in box with the highest average voltage is put into operation.

6. The double-layer optimization method of the plug-in optimizer according to claim 3, characterized in that: In step (7), the current difference ΔI between the battery clusters is obtained by the following formula: ΔI = maximum cluster discharge current - minimum cluster discharge current; The maximum cluster discharge current refers to the discharge current of the battery cluster with the largest discharge current, and the minimum cluster discharge current refers to the discharge current of the battery cluster with the smallest discharge current.

7. The double-layer optimization method of the plug-in optimizer according to claim 3, characterized in that: The specific operation of step (9) is as follows: Find the discharge current I1, I2, ... I of the battery cluster n The battery cluster corresponding to the maximum discharge current in is taken as the maximum discharge battery cluster; The average voltage of each battery plug-in box in the maximum discharge battery cluster is calculated respectively, the battery plug-in box with the lowest average voltage is found, and the plug-in box optimizer corresponding to the battery plug-in box with the lowest average voltage is put into operation.

8. The double-layer optimization method of the plug-in optimizer according to claim 3, characterized in that: The threshold value is a fixed value set according to the state of the battery, specifically 10% of the rated charge and discharge current of the battery.

9. The double-layer optimization method of the plug-in optimizer according to claim 3, characterized in that: The optimizer target voltage value is adjusted according to the change of the current difference ΔI between the battery clusters. When the current difference ΔI between the battery clusters decreases, an optimizer target voltage value adjusted according to the minimum step size is continuously issued.

10. The double-layer optimization method of the plug-in optimizer according to claim 3, characterized in that: The optimizer target voltage value is obtained by the following formula: Optimizer target voltage value = initial target voltage value - n*minimum step size; Here, n is 1%.

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