Coordinated test control method for cascaded energy storage system

Abstract

The application discloses a kind of collaborative test control methods for cascaded energy storage system, it is related to cascaded energy storage system collaborative test control technical field;To energy storage module detection state, verify communication delay, mark timeout module and trigger self-check, record normal module initial parameter;Select test mode, configure collaborative control and data acquisition parameter;Main controller generates total power instruction and dynamically distributes, sends synchronous clock signal and triggers module synchronization execution, gradually reduces power soft cut-off during charge and discharge, fault simulation sends isolation instruction;Receive real-time data, calculate voltage uniformity, SOC deviation and other indicators, analyze efficiency and communication stability;According to the result, dynamically adjust equalization current, etc., abnormal stop command is sent;Satisfy termination condition, stop testing, generate report containing performance indicators, fault record.The application improves test collaboration and precision, optimizes fault early warning and data utilization, enhances safety, reduces operation and maintenance cost.

Description

Technical Field

[0001] This invention relates to the field of collaborative testing and control technology for cascaded energy storage systems, and particularly to a collaborative testing and control method for cascaded energy storage systems. Background Technology

[0002] Cascaded energy storage systems, with their modular architecture and flexible expansion capabilities, have become a core energy storage form for scenarios such as new energy grid connection, microgrid frequency regulation, and backup power. Their testing and control need to achieve integrated operation of multiple modules, performance verification, and fault simulation. However, existing testing and control methods have significant shortcomings in the initialization phase: traditional processes rely on manual testing of voltage, SOC, temperature, and other states of each module, and communication protocol response delays are only verified by a single command, without triggering automatic self-checks for timed-out modules, resulting in initialization taking up to several hours and easily overlooking hidden communication faults caused by loose interfaces or power fluctuations; some methods, while supporting automatic initialization, do not correlate initialization data with subsequent test parameters, such as ignoring the initial SOC differences of modules and directly using a fixed power allocation coefficient, causing low SOC modules to reach discharge cutoff conditions prematurely, and the test cannot cover full-condition performance.

[0003] Static control strategies in the collaborative testing execution phase are difficult to adapt to the dynamic characteristics of modules: power allocation is mostly based on a fixed ratio set by rated capacity, without considering real-time temperature changes of modules. When the temperature of a module rises to near the protection threshold, the original power allocation is still maintained, which can easily lead to converter overload or battery thermal runaway. SOC balancing control uses constant current and does not consider the cumulative effect of deviation. For example, when the SOC deviation of a module gradually increases from 2% to 6%, the balancing current remains unchanged, resulting in slow balancing speed and easy over-adjustment when the deviation decreases, causing energy waste. At the same time, most methods are not optimized for communication delay. Synchronous triggering between modules relies on a unified clock but has no delay compensation. When the communication delay of a module exceeds 200ms, the power command execution time difference reaches hundreds of milliseconds, causing fluctuations in the total system power and affecting test accuracy. Especially in stepped power testing, fluctuations at the time of power switching are easily misjudged as abnormal module performance.

[0004] Existing methods suffer from insufficient fault handling and data utilization capabilities: fault warnings largely rely on hard threshold triggers, such as only issuing alarms when the temperature exceeds 55°C, failing to combine historical fault data and parameter change trends to predict risks and thus unable to proactively avoid potential faults such as slow temperature increases and gradual voltage changes; after data acquisition, only raw values ​​are stored without trend analysis, such as when power tracking accuracy gradually decreases from 98% to 92%, the degradation of converter power modules is not correlated, resulting in test reports that only present results and cannot provide optimization directions; furthermore, there is a lack of collaborative mechanisms for multi-system network testing, with each level of interconnected energy storage systems performing tests independently, failing to simulate power interaction in actual grid-connected scenarios, requiring maintenance personnel to manually summarize data, which is not only inefficient but also prone to analytical bias due to data asynchrony, making it difficult to meet the testing needs of large-scale energy storage power stations and significantly increasing maintenance costs. Summary of the Invention

[0005] The present invention proposes a collaborative testing and control method for cascaded energy storage systems to solve the problems mentioned in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a collaborative testing and control method for cascaded energy storage systems, comprising:

[0007] System initialization steps: Perform status detection on the energy storage modules of the cascaded energy storage system, and collect the initial voltage, state of charge (SOC), temperature, and communication status of each module; send handshake commands to each local controller through the main controller to verify the response delay of the communication protocol; for modules that are detected as normal, record the initial status parameters to the main controller storage unit to complete the initialization.

[0008] Test parameter configuration steps: Select the test mode according to the test target, including constant current charge and discharge test, stepped power test, and fault simulation test; configure the collaborative control parameters, including master-slave control strategy, power distribution coefficient, and equalization control threshold; configure the data acquisition parameters, including acquisition frequency and acquisition index.

[0009] Collaborative test execution steps: The main controller generates a total power command according to the configured test mode, and dynamically adjusts the power commands of each slave module based on the basic power allocation coefficient and the real-time SOC deviation to ensure that the total power command is consistent with the sum of the power commands of each module; the main module sends a synchronization clock signal to each slave module to trigger each module to execute the power command simultaneously, reducing system power fluctuations caused by inter-module response time differences; during charge and discharge tests, the main controller monitors the total system voltage and current in real time, and gradually reduces the power command to achieve soft cutoff when approaching the charge and discharge cutoff condition; during fault simulation tests, the main controller sends a fault trigger command to the designated module and a fault isolation command to other modules to reduce the fault propagation range.

[0010] Data acquisition and analysis steps: The main controller receives real-time data uploaded by each module according to the acquisition frequency; calculates the standard deviation of individual battery voltage for voltage data; calculates the deviation between the SOC of each module and the system average SOC for SOC data; calculates the deviation between the actual output power and the commanded power for power data for each module; calculates the internal temperature difference of the module for temperature data; analyzes the converter conversion efficiency and records operating points with efficiency below 90%; analyzes communication delay data, counts the number of delays exceeding the standard and the corresponding modules, and calculates communication stability.

[0011] Closed-loop control adjustment steps: Dynamic adjustment is performed based on data analysis results. When the SOC deviation of a module exceeds the equalization threshold, the main controller sends an equalization current command to the module and adjusts the power distribution coefficient of other modules to reduce the SOC deviation. When the temperature of a module exceeds the protection threshold, the power command of the module is reduced, and the module's cooling fan is triggered to run at high speed. When an abnormal situation occurs, the main controller sends a shutdown command, cuts off the system's input and output circuits, marks the abnormal module, and records the fault time data.

[0012] Furthermore, it also includes:

[0013] Test termination and report generation steps: When the test termination conditions are met, the main controller sends a test termination command, each module stops power output and returns to standby state; the main controller performs statistics on the data during the test and generates a test report, including basic test information, performance indicators, fault records, and optimization suggestions. The report can be exported as PDF or Excel format.

[0014] SOC adaptive equalization control steps: Based on the real-time and cumulative deviations of the SOC of each module, the equalization current is dynamically adjusted using the formula... Calculate the equalization current, where I bal The target equalization current is given by k1, where k1 is the real-time deviation proportional coefficient, and SOC is the constant current. i Let SOC be the real-time SOC of the i-th module. avg Let k2 be the cumulative deviation integral coefficient, t0 be the start time of the equilibrium control, and t be the current time. The integral term reflects the cumulative effect of the SOC deviation. At this time, k1 and k2 are automatically reduced by 50% to reduce the balancing current and reduce the probability of over-adjustment.

[0015] Dynamic power allocation optimization steps: Considering the module power change rate limit and temperature effect, the power command is smoothly adjusted using the formula. Calculate the real-time power command for the i-th module, where P i (t) represents the real-time power command of the i-th module at time t, P i0 This is the initial power command for the i-th module. The power change rate coefficient, This represents the maximum permissible power change of the module in a single operation. The rate of change of the total system power command. Dynamically assign weights to the i-th module, and the integral term enables a smooth transition of power commands; when the module temperature exceeds 50℃, Reduce power consumption by 30%, decrease the power allocation of the module, and reduce the probability of temperature rise.

[0016] Furthermore, the test parameter configuration steps also include parameter self-optimization based on historical test data. The main controller retrieves historical data from the past three tests under the same test mode, identifies the operating point with the lowest power tracking accuracy, and adjusts the power response coefficient of the corresponding operating point. It also identifies the duration of SOC equalization deviation exceeding the standard, and if it exceeds 5% of the total test duration, it lowers the SOC equalization deviation threshold. It identifies modules with excessive communication latency and optimizes the communication protocol parameters of the modules. The self-optimized parameters need to undergo a 10-minute verification test. If the verification is successful, the parameters are used as the configuration parameters for the current test; if the verification fails, the parameters are restored to the default parameters and marked as requiring manual optimization.

[0017] Furthermore, the collaborative testing execution steps also include redundancy control of each main controller. When the system contains two main controllers, the two synchronize test data and control commands in real time. The primary main controller sends a heartbeat signal to the backup main controller. If the backup main controller does not receive a heartbeat signal for more than three times, it determines that the primary main controller is faulty and immediately switches to the backup main controller to take over control. During the switching process, the backup main controller seamlessly generates power commands based on the synchronized test data and the current module status. After the switching is completed, the backup main controller sends a main controller switching alarm to the monitoring terminal and records the switching time and faulty main controller information.

[0018] Furthermore, the data acquisition and analysis steps also include temperature compensation analysis of converter efficiency, collecting converter input power P at different temperatures. in With output power P out A temperature-efficiency correction model is established: when the temperature is between 25℃ and 40℃, the efficiency correction coefficient β = 1; when the temperature is < 25℃, When the temperature is >40℃, Where T is the real-time temperature of the converter; the corrected efficiency .

[0019] Furthermore, the closed-loop control adjustment steps also include communication delay compensation control, whereby the main controller calculates the average communication delay of each module. When generating power commands, the commands are sent to modules with larger delays in advance, with a lead time of [time value missing]. +10ms; At the same time, a command retransmission mechanism is adopted to automatically retransmit commands that have not received a response. If the number of retransmissions exceeds 3, the communication interface of the module is switched.

[0020] Furthermore, it also includes:

[0021] Fault risk warning steps: Based on the module's real-time status parameters and historical fault data, using formulas... Calculate the fault risk value of the i-th module, where R i Here, 'a' represents the fault risk value, 'a' represents the temperature risk coefficient, and 'T' represents the temperature risk coefficient. i For the module's real-time temperature, T safe Where b is the upper limit of safe temperature, and V is the voltage risk factor. max,i V represents the maximum voltage of a single cell in the module. safe Where c is the upper limit of the safe voltage, and c is the SOC risk integral coefficient. i Let SOC be the real-time SOC of the i-th module. low With SOC high These represent the lower limit (10%) and upper limit (90%) of SOC safety, respectively, with the integral term reflecting the cumulative risk of SOC deviating from the safe range.

[0022] Furthermore, the test termination and report generation steps also include trend analysis of the test data. For power tracking accuracy, SOC equalization, and communication stability indicators, average values ​​are calculated for each test time segment to generate trend curves. The slope of the trend curves is analyzed. If the slope of the power tracking accuracy is negative, it is determined that there may be module performance degradation or parameter drift, and it is recommended to check the converter power module. If the slope of the SOC equalization is positive, the current equalization control parameters are recorded as the optimal parameters for subsequent tests on the same system.

[0023] Furthermore, it also includes:

[0024] Cross-system collaborative testing steps: When cascaded energy storage systems need to be networked for testing, one system is designated as the master system and the rest as slave systems. The master controller of the master system establishes cascaded communication with the master controllers of each slave system. The master system generates a total power command for the entire network and allocates the sub-power command to each slave system proportionally based on the rated capacity and real-time SOC of each slave system. The master system monitors the deviation between the total power of the entire network and the sum of the power of each slave system in real time. When the deviation exceeds 5%, the power allocation coefficient of each slave system is corrected. The data from the cross-system test is summarized and analyzed by the master system to generate a network-wide test report.

[0025] Compared with existing technologies, the beneficial effects of this invention are:

[0026] During the test preparation phase, the systematic initialization and parameter self-optimization design significantly improves the rationality and efficiency of configuration. The initialization phase comprehensively covers the detection of module voltage, SOC, temperature, and communication status. Modules with response timeouts are automatically triggered for self-checks, quickly locating hidden faults and reducing the time-consuming manual intervention. Test parameter configuration is dynamically optimized based on historical test data. For example, the response coefficient is adjusted for operating points with low power tracking accuracy in the past, and the threshold is optimized based on the SOC equalization deviation duration to avoid the blindness of experience-based configuration. At the same time, the power allocation base coefficient is set in conjunction with the initialization data to ensure that each module can participate in full-condition testing, shortening the test preparation cycle and improving configuration accuracy.

[0027] The dynamic control strategy during the collaborative testing execution phase effectively ensures system operational safety and collaborative accuracy. Dynamic power allocation considers module temperature and power change rate limitations, and avoids the impact of sudden power command changes on modules through smooth adjustments. At the same time, it optimizes equalization control based on real-time and cumulative deviation of SOC, which not only speeds up the equalization process but also reduces the equalization current when the deviation decreases, avoiding energy waste and battery damage. Communication delay compensation and synchronous clock control reduce the response time difference between modules and reduce system power fluctuations by sending commands in advance and switching to backup interfaces. In fault simulation testing, isolation commands are quickly issued to reduce the scope of fault impact, ensuring the stability and controllability of the testing process and protecting the energy storage modules from damage such as overload and overheating.

[0028] Enhanced fault early warning and data utilization capabilities provide strong support for system operation and maintenance. Based on the cumulative risk calculation of module real-time temperature, voltage, and SOC deviation from the safe range, different levels of early warning are triggered in advance to avoid system damage caused by sudden failures and reduce operation and maintenance risks. The closed-loop adjustment mechanism responds promptly to issues such as SOC deviation, temperature exceeding limits, and communication delays, such as correcting the power response coefficient and switching communication links to ensure continuous testing. Data trend analysis delves into the patterns of parameter changes, such as linking the decline in power tracking accuracy to converter performance degradation, providing direction for hardware maintenance. Test reports include optimization suggestions, making them more instructive. Cross-system collaborative testing supports the grid connection testing needs of large-scale energy storage power stations, realizing multi-system power collaborative allocation and unified data analysis, reducing redundant debugging, significantly reducing operation and maintenance costs, and fully adapting to the test and control needs of cascaded energy storage systems in different scenarios. Attached Figure Description

[0029] Fig. 1 This is a schematic block diagram of the collaborative testing and control method for cascaded energy storage systems proposed in this invention.

[0030] Fig. 2 This is a schematic diagram comparing the SOC equalization speed of the collaborative test and control method for cascaded energy storage systems proposed in this invention.

[0031] Fig. 3This is a schematic diagram showing the power tracking accuracy of the collaborative test and control method for cascaded energy storage systems proposed in this invention as a function of temperature. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0034] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. Furthermore, the terms "installed," "connected," and "linked" should be interpreted broadly; for example, they may refer to a fixed connection, a detachable connection, or an integral connection; they may refer to a mechanical connection or an electrical connection; they may refer to a direct connection or an indirect connection through an intermediate medium; and they may refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. The invention will now be described in further detail with reference to the accompanying drawings.

[0035] Reference Figs. 1 to 3 A collaborative test and control method for cascaded energy storage systems, comprising:

[0036] System initialization steps: Perform status detection on N energy storage modules (N≥2, each module includes a battery cluster, bidirectional converter, and local controller) of the cascaded energy storage system, and collect the initial voltage (individual battery voltage and total module voltage), state of charge (SOC), temperature (battery terminal temperature and converter heat dissipation temperature), and communication status (link connectivity between local controller and main controller) of each module; send handshake commands to each local controller through the main controller to verify the response delay of the communication protocol (supporting Modbus-RTU or CANopen) (≤100ms). Modules with timeout responses are marked as "to be investigated" and trigger local self-tests (checking power supply, communication interface, and hardware fault codes); for modules that pass the test, record the initial status parameters to the main controller storage unit to complete the initialization.

[0037] Test parameter configuration steps: Select the test mode according to the test objective, including constant current charge / discharge test (set charge / discharge current value, charge / discharge cutoff SOC), stepped power test (set multiple power values ​​and duration of each segment), and fault simulation test (set simulated scenarios such as open circuit fault, short circuit fault, and converter malfunction); Configure collaborative control parameters, including master-slave control strategy (designate one module as the master module and the rest as slave modules, with the master module responsible for command generation and synchronous control), power allocation coefficient (set the basic allocation coefficient based on the ratio of the initial SOC to the rated power of each module), and equalization control threshold (SOC equalization deviation threshold ≤ 5%, voltage equalization deviation threshold ≤ 0.3V, temperature protection threshold ≤ 55℃); Configure data acquisition parameters, including acquisition frequency (voltage and current data ≥ 1kHz, SOC and temperature data ≥ 1Hz), and acquisition indicators (module input and output power, single cell voltage standard deviation, converter conversion efficiency, and communication delay).

[0038] Collaborative test execution steps: The main controller generates a total power command according to the configured test mode, and dynamically adjusts the power commands of each slave module based on the basic power allocation coefficient and the real-time SOC deviation to ensure that the total power command is consistent with the sum of the power commands of each module; the main module sends a synchronization clock signal (accuracy ±1ms) to each slave module to trigger each module to execute the power command simultaneously, reducing system power fluctuations caused by inter-module response time differences; during charge and discharge tests, the main controller monitors the total system voltage and current in real time, and when it approaches the charge and discharge cutoff conditions (such as SOC approaching 90% or 10%), it gradually reduces the power command (reducing the rated power by 10% every 100ms) to achieve soft cutoff; during fault simulation tests, the main controller sends a fault trigger command to the designated module and simultaneously sends a "fault isolation" command to other modules to reduce the fault propagation range;

[0039] Data acquisition and analysis steps: The main controller receives real-time data uploaded by each module according to the acquisition frequency; calculates the standard deviation of individual battery voltage for voltage data (reflecting voltage balance); calculates the deviation between the SOC of each module and the system average SOC for SOC data (reflecting SOC balance); calculates the deviation between the actual output power and the commanded power of each module for power data (reflecting power tracking accuracy); calculates the internal temperature difference of the module for temperature data (reflecting heat dissipation balance); analyzes the converter conversion efficiency (based on the ratio of module input power to output power), and records operating points with efficiency below 90%; analyzes communication delay data, counts the number of delays exceeding the standard and the corresponding modules, and calculates communication stability (the proportion of stable communication time to total test time).

[0040] Closed-loop control adjustment steps: Dynamic adjustments are performed based on data analysis results. When the SOC deviation of a module exceeds the equalization threshold, the main controller sends an equalization current command to the module (active equalization is achieved through a bidirectional DC / DC circuit), while simultaneously adjusting the power distribution coefficients of other modules to reduce the SOC deviation. When the temperature of a module exceeds the protection threshold, the power command of the module is reduced (2% reduction of rated power per °C), and the cooling fan of the module is triggered to run at high speed. When the power tracking accuracy is lower than 95%, the power response coefficient of the module is corrected (the proportional gain is adjusted based on historical deviation data). When the number of communication delay exceedances exceeds the limit, the backup communication link is switched (e.g., from CANopen to EtherCAT). When abnormal conditions (such as module short circuit or voltage drop) occur, the main controller immediately sends a shutdown command, cuts off the system input and output circuits, marks the abnormal module, and records the fault time data.

[0041] Test termination and report generation steps: When the test termination conditions are met (reaching the set test duration, completing all test modes, triggering critical fault protection), the main controller sends a test termination command, and each module stops power output and returns to standby state; the main controller statistically analyzes the data during the test and generates a test report, including basic test information (test time, test mode, number of participating modules), performance indicators (power tracking accuracy, SOC balance, converter efficiency, communication stability), fault records (faulty module, fault type, fault handling result), and optimization suggestions (parameter adjustments and hardware improvement suggestions based on test data). The report can be exported to PDF or Excel format.

[0042] This invention also includes:

[0043] SOC Adaptive Equalization Control Steps: This step dynamically adjusts the equalization current based on the real-time and cumulative deviations of the SOC of each module, using the formula... Calculate the equalization current, where I balThe target equalization current (in A, a positive value indicates charging the module, a negative value indicates discharging), k1 is the real-time deviation proportional coefficient (values ​​range from 0.5 to 2, set based on the module's rated current), and SOC. i The real-time SOC (in %) of the i-th module. avg Let k2 be the average SOC (in %) of all modules in the system, k2 be the cumulative deviation integral coefficient (valued between 0.1 and 0.5, set based on the equalization speed requirement), t0 be the start time of equalization control (in seconds), and t be the current time (in seconds). The integral term reflects the cumulative effect of the SOC deviation; when When the module temperature exceeds 45°C, k1 and k2 are automatically reduced by 50% to decrease the balancing current and reduce the probability of over-adjustment. When the module temperature exceeds 45°C, k1 and k2 are reduced by 70% to slow down the balancing speed and protect the battery. This step improves the dynamic response and stability of SOC balancing and reduces the balancing lag problem caused by static balancing.

[0044] Dynamic power allocation optimization step: This step considers the module power change rate limit and temperature effect, and smoothly adjusts the power command using the formula. Calculate the real-time power command for the i-th module, where P i (t) represents the real-time power command (in kW) of the i-th module at time t. i0 This is the initial power command (in kW) for the i-th module. This is the power change rate coefficient (valued between 0.1 and 0.3, limiting the power change per millisecond). This is the maximum permissible power change of the module in a single operation (unit: kW, set based on the overload capacity of the module converter). The rate of change of the total system power command (in kW / s). The i-th module is dynamically weighted (adjusted based on the ratio of the module's real-time temperature to its rated power; the higher the temperature, the lower the weight), and the integral term enables a smooth transition of power commands; when the module temperature exceeds 50℃, By reducing the power allocation of this module by 30%, the probability of further temperature increases is reduced. This step reduces the impact of sudden power command changes on the module and improves the smoothness and safety of system power control.

[0045] In this invention, the test parameter configuration step also includes parameter self-optimization based on historical test data. The main controller retrieves historical data from the past three tests under the same test mode, identifies the operating point with the lowest power tracking accuracy (e.g., tracking accuracy of only 90% for a certain power segment), and adjusts the power response coefficient of that operating point accordingly (increasing the proportional gain by 10%). It also tracks the duration of SOC equalization deviation exceeding the limit; if it exceeds 5% of the total test duration, the SOC equalization deviation threshold is reduced (from 5% to 4%). Furthermore, it identifies modules with excessive communication latency and optimizes their communication protocol parameters (e.g., baud rate, data frame length) (e.g., increasing the baud rate from 500kbps to 1Mbps). The self-optimized parameters undergo a 10-minute verification test. If the verification passes, the parameters are used as the current test configuration parameters; otherwise, they revert to the default parameters and are marked as "requiring manual optimization." This step improves the rationality of parameter configuration and reduces manual debugging costs.

[0046] In this invention, the collaborative test execution step also includes multi-master controller redundancy control. When the system contains two master controllers (primary and backup), they synchronize test data and control commands in real time. The primary master controller sends a heartbeat signal to the backup master controller (every 50ms interval). If the backup master controller does not receive a heartbeat signal for more than three times, it determines that the primary master controller has failed and immediately switches to the backup master controller to take over control. During the switching process, the backup master controller seamlessly generates power commands based on the synchronized test data and the current module status, ensuring that the test interruption time is ≤500ms. After the switching is completed, the backup master controller sends a "master controller switching" alarm to the monitoring terminal and records the switching time and the faulty master controller information. This step improves the reliability of the system test control and reduces the probability of test interruption caused by the failure of a single master controller.

[0047] In this invention, the data acquisition and analysis steps also include temperature compensation analysis of converter efficiency. This involves collecting the converter input power Pin and output power Pout at different temperatures to establish a temperature-efficiency correction model: when the temperature is between 25℃ and 40℃, the efficiency correction coefficient β=1; when the temperature is <25℃, ... When the temperature is >40℃, Where T is the real-time temperature of the converter (in °C); the corrected efficiency This correction reduces the impact of temperature on efficiency calculation, making efficiency data comparable under different temperature conditions. At the same time, it calculates the efficiency fluctuation coefficient (the difference between the maximum and minimum efficiency values). When the fluctuation coefficient exceeds 5%, the converter is marked as "unstable" and hardware testing is recommended. This step improves the accuracy of efficiency analysis.

[0048] In this invention, the closed-loop control adjustment step also includes communication delay compensation control, whereby the main controller calculates the average communication delay of each module. (Delay of the i-th module), when generating power commands, the commands are sent to the modules with larger delays in advance, with an advance time of . +10ms (10ms redundancy reserved); a command retransmission mechanism is also employed for commands that do not receive a response (timeout period is 2 seconds). Automatic retransmission; if the number of retransmissions exceeds 3, switch the communication interface of the module (e.g., switch from RS485 to CAN); for modules with communication delays exceeding 200ms, temporarily reduce their power allocation weight (by 20%) to reduce the impact of the module on system collaborative control; this step compensates for the synchronization deviation caused by communication delays and improves the collaborative accuracy between modules.

[0049] This invention also includes:

[0050] Fault risk warning steps: This step is based on the module's real-time status parameters and historical fault data, using formulas... Calculate the fault risk value of the i-th module, where R i T represents the fault risk value (ranging from 0 to 100, with higher values ​​indicating higher risk), 'a' represents the temperature risk coefficient (ranging from 2 to 5), and T represents the temperature risk coefficient. i The module's real-time temperature (in °C), T safe The upper limit of the safe temperature (taken as 50℃), b is the voltage risk factor (taken as 3-6), V max,i The maximum voltage of a single cell in the module (in V), V safe is the upper limit of the safe voltage (taken as 3.65V), c is the SOC risk integral coefficient (valued between 0.1 and 0.3), SOC low With SOC high These represent the lower limit (10%) and upper limit (90%) of the State of Charge (SOC), respectively. The integral term reflects the cumulative risk of the SOC deviating from the safe range; when When this occurs, a Level 1 warning is triggered (the power of this module is reduced by 50%). When this occurs, a level-two warning is triggered (an alarm is sent to the monitoring terminal); this step enables early prediction of fault risks and reduces the probability of system damage caused by sudden failures.

[0051] In this invention, the test termination and report generation steps also include trend analysis of test data. For indicators such as power tracking accuracy, SOC balance, and communication stability, average values ​​are calculated for each 30-minute segment of the test time, generating trend curves. The slope of the trend curves is analyzed. If the slope of the power tracking accuracy is negative (accuracy continuously decreasing), it indicates potential module performance degradation or parameter drift, suggesting an inspection of the converter power module. If the slope of the SOC balance is positive (balance continuously improving), the current balance control parameters are recorded as "optimal parameters" for subsequent tests on the same system. Simultaneously, the standard deviation of each indicator is calculated. If the standard deviation exceeds 10%, the indicator is marked as "significantly fluctuating," and the causes of the fluctuations (such as load changes or environmental interference) are analyzed. The trend analysis results are incorporated into the test report, providing data support for system optimization. This step enhances the practicality of the test report.

[0052] This invention also includes:

[0053] Cross-system collaborative testing steps: When multiple cascaded energy storage systems (≥2) need to be networked for testing, one system is designated as the master system, and the rest are slave systems. The master controller of the master system establishes cascaded communication with the master controllers of each slave system (using the EtherCAT protocol, with a communication delay ≤50ms). The master system generates a total power command for the entire network and allocates the sub-power command to each slave system proportionally based on the rated capacity and real-time SOC of each slave system. The master system monitors the deviation between the total power of the entire network and the sum of the power of each slave system in real time. When the deviation exceeds 5%, the power allocation coefficient of each slave system is corrected. The cross-system test data is summarized and analyzed by the master system to generate a network-wide test report. This step realizes the collaborative control of multi-system network testing and meets the testing requirements of large-scale energy storage power stations.

[0054] Specific implementation methods of the collaborative test and control method for cascaded energy storage systems:

[0055] Example 1: Collaborative Testing of a 10MW New Energy Grid-Connected Cascaded Energy Storage System (Application Scenario: A 200MW photovoltaic power station is equipped with a 10MW cascaded energy storage system, which includes five 2MW energy storage modules. Each module contains 150 strings of lithium iron phosphate battery clusters (single cell voltage 3.2-3.6V), a 2MW bidirectional converter, and an STM32H743 local controller. It is used for photovoltaic output smoothing and grid peak shaving. Constant current charging and discharging, stepped power testing, and fault simulation need to be completed. It needs to cope with the SOC difference between modules (initial maximum deviation 8%) and converter temperature fluctuations (25-50℃). The main controller adopts Siemens S7-1500 PLC and is connected to the power station's EMS system).

[0056] I. System Module Deployment and Testing Process Implementation

[0057] System initialization steps: Status monitoring is performed on 5 modules (M1-M5). Individual battery voltages (M1 average 3.42V, M5 average 3.38V) and total module voltages (M1 513V, M5 507V) are collected using an NIcDAQ-9178 data acquisition card. State of Charge (SOC) is calculated using the ampere-hour integration method (M1 85%, M2 82%, M3 79%, M4 77%, M5 77%). Temperatures are collected using a DS18B20 sensor (inverter heatsink temperatures M1 28℃, M5 30℃). The main controller sends data to each module... The ground controller sends Modbus-RTU handshake commands (addresses 0x01-0x05), and the oscilloscope monitors the response delay (M1 75ms, M3 110ms timeout); M3 triggers local self-test, checks the CAN interface voltage (2.4V normal) and hardware fault codes (no abnormalities), and determines that the communication baud rate is mismatched (originally 500kbps, after adjustment to 1Mbps, the delay is 90ms); all module initial parameters are recorded to the PLC storage area (addresses DB1.DBD0-DB1.DBD100), completing the initialization.

[0058] Test parameter configuration steps: Select the "constant current charge / discharge + stepped power" combination mode, constant current charging current 100A (cutoff SOC 90%), discharge current 120A (cutoff SOC 10%), stepped power divided into 3 segments: 1MW (lasting 5min), 1.5MW (5min), 2MW (5min); Configure coordination parameters: designate M1 as the main module, power allocation base coefficient is calculated based on the ratio of SOC to rated power (K1=85% / 80%×0.2=0.2125, K2=82% / 80%×0.2=0.205, K3-K5=0.1925), SOC equalization threshold 3%, temperature protection threshold 55℃; Data acquisition parameters: voltage / current 1kHz (using ADS8344ADC), SOC / temperature 1Hz, acquired indicators include module input and output power (measured using Hall sensor CSM025M), single-unit voltage standard deviation (M1 0.03V), converter efficiency (M1 92.5%).

[0059] Collaborative test execution steps: The main module M1 generates a total power command. During the constant current charging phase, the total power Ptotal = 513V × 100A = 51.3kW ≈ 0.05MW, allocated according to the basic coefficient (M1 0.0106MW, M2 0.0103MW). The synchronization clock uses GPS timing (accuracy ±1ms). M1 sends a synchronization pulse every 10ms, triggering all modules to execute the power command simultaneously. When the stepped power increases to 2MW, the temperature of the M4 converter rises to 48℃. The main controller dynamically adjusts the allocation coefficient (K4 decreases from 0.1925 to 0.18) to ensure that the total power remains at 2MW. During the fault simulation test, a "converter IGBT open circuit" command is sent to M2, and isolation commands are sent to M1 and M3-M5 at the same time to disconnect M2 from the system bus. M2 switches to standby mode.

[0060] Data acquisition and analysis steps: The main controller receives module data every 100ms, calculates the SOC deviation of M1-M5 (M1 88%, M5 85%, deviation 3%), and the standard deviation of individual unit voltage (M2 0.04V, exceeding 0.03V); the converter efficiency is calculated according to Pout / Pin (Pin=2.17MW when M3 outputs 2MW, efficiency 92.2%); communication delay statistics (M4 average 85ms, no exceedance); efficiency-temperature curve is generated, and it is found that the efficiency decreases by 0.5% / ℃ when the temperature exceeds 45℃, and the operating point of M3 with an efficiency of 91.8% at 48℃ is recorded.

[0061] Closed-loop control adjustment steps: When the standard deviation of the voltage of individual cell M2 exceeds the threshold, the main controller sends a current balancing command to M2 (through a bidirectional DC / DC circuit), according to the formula. Calculate: k1=1.2, k2=0.3, SOC2=83%, SOC avg =84%, t0=0, t=10s, integral term=∫(-1)dt=-10, I bal =1.2×(-1)+0.3×(-10)=-4.2A (discharge equalization); M4 temperature rises to 52℃, power command is reduced (52-28)×2%×2MW=0.96MW, triggering cooling fan speed to increase from 2000rpm to 3000rpm; M5 power tracking accuracy is 94% (command 1.925MW, actual 1.81MW), proportional gain is corrected (from 0.8 to 0.85), accuracy is improved to 97%.

[0062] Fault risk warning implementation steps: according to the formula Calculate the M3 risk value: a=3, T i =50℃, T safe =50℃, b=4, V max i = 3.62V, V safe=3.65V, c=0.2, SOC i =86%, integral term =∫(86-10)(90-86)dt=76×4×10=3040, R i =3×0+4×(-0.03)+0.2×3040=-0.12+608=607 (corrected value 60.7), triggering a level 2 warning, and the EMS system pop-up message "M3 temperature is approaching the safe upper limit".

[0063] II. Test Results Verification and Data Comparison

[0064] The test lasted 2 hours, completing 2 charge-discharge cycles, 6 stepped power switching operations, and 3 fault simulations, with no module downtime. Data compared to traditional testing methods is as follows:

[0065] Table 1: Comparison of the effectiveness of test methods for new energy grid-connected energy storage systems in Example 1

[0066]

[0067] Table 1 Data Explanation: Traditional initialization methods are time-consuming due to manual testing of voltage and SOC module by module. This method shortens the time to 35 minutes through automatic data acquisition and self-testing. The improved power point tracking accuracy is due to the dynamic allocation coefficient and synchronous control. M3 actually outputs 1.964MW under 2MW conditions, with a deviation of only 1.8%. SOC balancing is fast because it considers the cumulative deviation (the integral term in the formula accelerates balancing). The SOC deviation between M1 and M5 is reduced from 8% to 3% in just 11 minutes. Fault response delay is low because the main controller directly issues isolation commands without manual confirmation. Data utilization is high because it automatically calculates indicators such as standard deviation and efficiency, generating trend curves (such as the temperature-efficiency curve of the M1 converter). Traditional methods only store raw voltage data, requiring manual post-processing, with a utilization rate of less than 60%.

[0068] Example 2: Collaborative Test of 5MW Microgrid Backup Power Cascaded Energy Storage System (Application Scenario: A 5MW microgrid backup energy storage system in an industrial park, containing four 1.25MW modules (M1-M4), with ternary lithium batteries (3.6-4.2V per cell), and an ABBPCS100 converter, used to supply power to important loads (motors, PLCs) during grid outages. It is necessary to simulate grid open-circuit faults, test backup switching response (≤500ms), address module communication latency (average 150ms for M2), and cross-system collaboration (networked with another 2MW energy storage system S2 in the park). The main controller uses a Schneider M340 PLC and is connected to the microgrid monitoring platform.

[0069] I. System Module Deployment and Testing Process Implementation

[0070] System initialization steps: Collect the status of 4 modules. The total voltages of M1-M4 are 600V, 595V, 598V, and 592V respectively, and the SOC of all modules is 90% (higher SOC is required for standby scenarios). The inverter temperature is 22-25℃. Communication detection uses the CANopen protocol. The main controller sends a heartbeat command (interval of 50ms). The response delay of M2 is 155ms (over 100ms). After switching to the standby CAN interface (from CAN1 to CAN2), the delay is 85ms. Detect the standby switching response time (M1 from standby to power supply is 280ms). Record the initial parameters to the PLCDB2 data block to complete the initialization.

[0071] Test parameter configuration steps: Select the "fault simulation + cross-system collaboration" mode to simulate a power grid open circuit fault (trigger condition: power grid voltage < 0.1 pu for 100 ms), with a standby power supply of 3 MW (load demand); Configure collaboration parameters: M1 is the master module, power allocation coefficient K1-K4=0.25 (SOC consistent), designate this system (S1) as the master system and S2 as the slave system for cross-system collaboration, using EtherCAT communication (delay ≤ 50 ms); Key data acquisition points: standby switching time, power fluctuation, and cross-system power deviation.

[0072] Collaborative test execution steps: The main controller simulates a grid voltage drop (0.05 pu), triggering a fault command after 100 ms. M1 generates a total power command of 3MW, which is allocated to K1-K4 (0.75MW per module). The synchronization clock is provided by the PLC's internal crystal oscillator (accuracy ±2ms). M1 sends synchronization commands to M2-M4 and S2. S2 allocates 0.5MW of power (total power supply 3.5MW, matching load 3.5MW). During fault isolation, the circuit breaker connecting S1 to the grid is disconnected (response time 150ms). The M1-M4 converters switch to V / F control mode, with a power supply voltage of 380V±2%.

[0073] Data acquisition and analysis steps: Acquire standby switching time (S1 320ms, S2 380ms, total delay 400ms); power fluctuation was measured using a YOKOGAWAWT3000 power analyzer (S1 output 0.75MW±0.01MW, fluctuation 1.3%); cross-system power deviation (S1 actual 3MW, S2 0.5MW, total 3.5MW, command deviation 0%); converter efficiency (Pin=0.815MW when M2 outputs 0.75MW, efficiency 92%).

[0074] Closed-loop control and cross-system collaborative implementation: M2 communication latency increased to 180ms, the main controller according to the formula Power adjustment command: P i0 =0.75MW, =0.2, ΔPmax =0.2MW, dP total / dt=0.1MW / s, =0.24 (temperature 28℃), integral term = ∫min(0.04, 0.024)dt = 0.024 × 5 = 0.12, P i (t)=0.87MW, compensating for the delay effect; when the cross-system power deviation exceeds 2%, the S2 allocation factor is corrected (from 0.14 to 0.15), and the deviation is reduced to 0.5%.

[0075] II. Test Results Verification and Data Comparison

[0076] The test simulated five grid faults and conducted one hour of cross-system collaborative operation, demonstrating reliable backup power supply. Data comparing this to traditional backup testing methods is as follows:

[0077] Table 2: Comparison of the test results of the microgrid backup energy storage system in Example 2

[0078]

[0079] Table 2 data explanation: Traditional methods have long switching times because manual fault confirmation and backup activation are required. This method automatically detects voltage drops and triggers switching, reducing the time to 0.4s (meeting the microgrid ≤500ms requirement); power fluctuations are small because of synchronous control and dynamic power adjustment, M2 can still accurately track commands (0.87MW±0.01MW) even with a 180ms delay; the 35ms cross-system delay is due to the real-time nature of the EtherCAT protocol, ensuring synchronized power distribution between S1 and S2; fault isolation is 100% successful because the main controller directly controls the switching of circuit breaker and converter modes, whereas traditional methods are prone to isolation failure due to human error; report generation is fast because the PLC automatically summarizes switching time, power deviation, and other indicators to generate a PDF report (including fault waveform diagrams), whereas traditional methods require manual processing of Excel data, taking more than 50 minutes.

[0080] Fig. 2 The speed advantage of this invention's SOC equalization is clearly demonstrated—traditional fixed current equalization, which does not consider the cumulative effect of deviation, takes 20 minutes to reduce the deviation from 8% to 3.5%, failing to achieve the target; this invention, through real-time deviation ratio adjustment and cumulative deviation integral compensation (in the formula) and (Through synergistic effect), the deviation is ≤3% within 15 minutes and remains stable thereafter. This efficient balancing avoids premature shutdown of low SOC modules, ensuring that the entire system participates in the charge and discharge test. For example, in Example 1, M5 (initial SOC 77%) can follow the system to complete the 90% SOC charging target after balancing. Under the traditional method, M5 will stop charging prematurely due to excessive deviation, resulting in incomplete coverage of test conditions.

[0081] Fig. 3 This invention highlights its adaptability to temperature effects—traditional methods do not consider the impact of temperature on module power capability, and the accuracy drops to 88% when the temperature rises to 50°C, which is below requirements; this invention dynamically adjusts the power allocation weights. (The higher the temperature, the lower the weight) and smooth transition (the integral term limits the rate of power change), the accuracy still reaches 93% even at 55℃, meeting the requirements throughout. This stability ensures the validity of test data under high-temperature conditions. For example, in Example 1, M4 (temperature 52℃) under a 2MW power command actually outputs 1.96MW (accuracy 98%), while under the traditional method, the module outputs only 1.76MW (accuracy 88%), which is easily misjudged as a performance abnormality.

[0082] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A collaborative test and control method for cascaded energy storage systems, characterized in that, include: System initialization steps: Perform status detection on the energy storage modules of the cascaded energy storage system, and collect the initial voltage, state of charge (SOC), temperature, and communication status of each module; The main controller sends handshake commands to each local controller to verify the response delay of the communication protocol; for modules that pass the test, the initial state parameters are recorded to the main controller's storage unit to complete the initialization. Test parameter configuration steps: Select the test mode according to the test target, including constant current charge and discharge test, stepped power test, and fault simulation test; configure the collaborative control parameters, including master-slave control strategy, power distribution coefficient, and equalization control threshold; configure the data acquisition parameters, including acquisition frequency and acquisition index. Collaborative test execution steps: The main controller generates a total power command according to the configured test mode, and dynamically adjusts the power commands of each slave module based on the basic power allocation coefficient and the real-time SOC deviation to ensure that the total power command is consistent with the sum of the power commands of each module; the main module sends a synchronization clock signal to each slave module to trigger each module to execute the power command simultaneously, reducing system power fluctuations caused by inter-module response time differences; during charge and discharge tests, the main controller monitors the total system voltage and current in real time, and gradually reduces the power command to achieve soft cutoff when approaching the charge and discharge cutoff condition; during fault simulation tests, the main controller sends a fault trigger command to the designated module and a fault isolation command to other modules to reduce the fault propagation range. Data acquisition and analysis steps: The main controller receives real-time data uploaded by each module according to the acquisition frequency; calculates the standard deviation of individual battery voltage for voltage data; calculates the deviation between the SOC of each module and the system average SOC for SOC data; calculates the deviation between the actual output power and the commanded power for power data for each module; calculates the internal temperature difference of the module for temperature data; analyzes the converter conversion efficiency and records operating points with efficiency below 90%; analyzes communication delay data, counts the number of delays exceeding the standard and the corresponding modules, and calculates communication stability. Closed-loop control adjustment steps: Dynamic adjustment is performed based on data analysis results. When the SOC deviation of a module exceeds the equalization threshold, the main controller sends an equalization current command to the module and adjusts the power distribution coefficient of other modules to reduce the SOC deviation. When the temperature of a module exceeds the protection threshold, the power command of the module is reduced, and the module's cooling fan is triggered to run at high speed. When an abnormal situation occurs, the main controller sends a shutdown command, cuts off the system's input and output circuits, marks the abnormal module, and records the fault time data.

2. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, Also includes: Test termination and report generation steps: When the test termination conditions are met, the main controller sends a test termination command, and each module stops power output and returns to standby state; The main controller compiles data during the test and generates a test report, including basic test information, performance indicators, fault records, and optimization suggestions. The report can be exported as PDF or Excel format. SOC adaptive equalization control steps: Based on the real-time and cumulative deviations of the SOC of each module, the equalization current is dynamically adjusted using the formula... Calculate the equalization current, where I bal The target equalization current is given by k1, where k1 is the real-time deviation proportional coefficient, and SOC is the constant current. i Let SOC be the real-time SOC of the i-th module. avg The average SOC of all modules in the system is given by , k2 is the cumulative deviation integral coefficient, t0 is the start time of the equalization control, and t is the current time. The integral term reflects the cumulative effect of the SOC deviation. when At this time, k1 and k2 are automatically reduced by 50% to reduce the balancing current and reduce the probability of over-adjustment.

3. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, Also includes: Dynamic power allocation optimization steps: Considering the module power change rate limit and temperature effect, the power command is smoothly adjusted using the formula. Calculate the real-time power command for the i-th module, where P i (t) represents the real-time power command of the i-th module at time t, P i0 This is the initial power command for the i-th module. The power change rate coefficient, This represents the maximum permissible power change of the module in a single operation. The rate of change of the system's total power command. Dynamically assign weights to the i-th module, and the integral term enables a smooth transition of power commands; when the module temperature exceeds 50℃, Reduce power consumption by 30%, decrease the power allocation of the module, and reduce the probability of temperature rise.

4. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, The test parameter configuration steps also include parameter self-optimization based on historical test data. The main controller retrieves historical data from the past three tests with the same test mode, counts the operating point with the lowest power tracking accuracy, and adjusts the power response coefficient of the operating point accordingly. The duration of SOC balance deviation exceeding the standard is recorded. If it exceeds 5% of the total test duration, the SOC balance deviation threshold is lowered. The communication protocol parameters of modules that exceed the standard are analyzed and optimized. The self-optimized parameters need to undergo a 10-minute verification test. If the verification is successful, it is used as the configuration parameters for the current test. If it fails, it is restored to the default parameters and marked as requiring manual optimization.

5. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, The collaborative testing execution steps also include redundancy control of each main controller. When the system contains two main controllers, the two synchronize test data and control commands in real time. The primary main controller sends a heartbeat signal to the backup main controller. If the backup main controller does not receive a heartbeat signal for more than three times, it determines that the primary main controller is faulty and immediately switches to the backup main controller to take over control. During the switching process, the backup main controller seamlessly generates power commands based on the synchronized test data and the current module status. After the switching is completed, the backup main controller sends a main controller switching alarm to the monitoring terminal and records the switching time and faulty main controller information.

6. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, The data acquisition and analysis process also includes temperature compensation analysis of converter efficiency, collecting the converter input power P at different temperatures. in With output power P out A temperature-efficiency correction model is established: when the temperature is between 25℃ and 40℃, the efficiency correction coefficient β = 1; when the temperature is < 25℃, ; When the temperature is >40℃, Where T is the real-time temperature of the converter; the corrected efficiency .

7. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, The closed-loop control adjustment process also includes communication delay compensation control, where the main controller calculates the average communication delay of each module. When generating power commands, the commands are sent to modules with larger delays in advance, with a lead time of [time value missing]. +10ms; At the same time, a command retransmission mechanism is adopted to automatically retransmit commands that have not received a response. If the number of retransmissions exceeds 3, the communication interface of the module is switched.

8. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, Also includes: Fault risk warning steps: Based on the module's real-time status parameters and historical fault data, using formulas... Calculate the fault risk value of the i-th module, where R i Here, 'a' represents the fault risk value, 'a' represents the temperature risk coefficient, and 'T' represents the temperature risk i For the module's real-time temperature, T safe Where b is the upper limit of safe temperature, and V is the voltage risk factor. max,i V represents the maximum voltage of a single cell in the module. safe Where c is the upper limit of the safe voltage, and c is the SOC risk integral coefficient, SOC i Let SOC be the real-time SOC of the i-th module. low With SOC high These represent the lower and upper limits of SOC safety, respectively, with the integral term reflecting the cumulative risk of SOC deviating from the safe range.

9. The collaborative testing and control method for cascaded energy storage systems according to claim 2, characterized in that, The test termination and report generation steps also include trend analysis of test data. For power tracking accuracy, SOC balance, and communication stability indicators, the average value is calculated for each test time segment to generate trend curves. The slope of the trend curve is analyzed. If the slope of the power tracking accuracy is negative, it is determined that there may be module performance degradation or parameter drift, and it is recommended to check the converter power module. If the slope of the SOC balance is positive, then the current balance control parameters are recorded as the optimal parameters for subsequent testing of the same system.

10. The collaborative testing and control method for cascaded energy storage systems according to claim 1, characterized in that, Also includes: Cross-system collaborative testing steps: When cascaded energy storage systems need to be networked for testing, one system is designated as the master system and the rest as slave systems. The master controller of the master system establishes cascaded communication with the master controllers of each slave system. The master system generates a total power command for the entire network and allocates the sub-power command to each slave system proportionally based on the rated capacity and real-time SOC of each slave system. The master system monitors the deviation between the total power of the entire network and the sum of the power of each slave system in real time. When the deviation exceeds 5%, the power allocation coefficient of each slave system is corrected. The data from the cross-system test is summarized and analyzed by the master system to generate a network-wide test report.

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