An intelligent energy management system and control method for an energy storage cabin

Abstract

The application discloses an energy storage cabin intelligent energy management system and a control method, and the method comprises the following steps: collecting the direct current side voltage, current, carrier phase, and battery cluster electric parameters, temperature and cooling state synchronously, extracting the battery cluster electric response characteristics by using the inherent carrier excitation, and decoupling to obtain the cell ohmic impedance, electrochemical polarization impedance, connector contact impedance and equivalent thermal resistance by combining the temperature rise position, temperature rise rate and response lag. According to the decoupling parameters, the safe adjustable energy envelope of each battery cluster is constructed, meanwhile, the battery cluster, cooling branch, air duct area and cabin space are characterized as thermal nodes, and a dynamic directed heat propagation graph is established. The application relates to the technical field of electrochemical energy storage cabin energy management. According to the actual propagation result, the energy envelope, heat propagation graph and power-cooling capacity distribution strategy are continuously corrected, and the closed-loop cooperation of electric energy scheduling and thermal safety control is realized.

Description

Technical Field

[0001] This invention relates to the field of energy management for electrochemical energy storage chambers, and more specifically, to an intelligent energy management system and control method for energy storage chambers. Background Technology

[0002] As the scale of electrochemical energy storage expands, energy storage chambers typically collect voltage, current, and temperature data through a battery management system (BMS), and the energy management system implements cluster-level power allocation and temperature control. Patent CN111834701B discloses a temperature control method based on temperature differences in energy storage batteries, calculating temperature regulation power according to ambient temperature, battery operating voltage, and operating current. Patent CN118231883B discloses a battery management method for liquid-cooled energy storage systems, generating cooling strategies through heat exchange fitting, heating characteristic compensation, and multi-objective optimization. While these solutions improve temperature regulation, they primarily rely on temperature results or predicted temperatures to allocate cooling capacity. They do not utilize the carrier ripple generated by normal PCS switching to identify battery cluster impedance, nor can they distinguish the impact of cell ohmic impedance, electrochemical polarization impedance, and connector contact impedance on heating. Furthermore, existing solutions do not perform correlation modeling of the propagation direction, propagation delay, and propagation confidence of heat in the battery cluster, cooling branches, air ducts, and chamber space, making it difficult to coordinate the adjustment of cluster-level power and cooling resources before heat arrives. Therefore, there is a need for an energy management scheme for energy storage compartments that can achieve identification of parameters without additional disturbances, prediction of heat propagation, and closed-loop coordinated control of power and cooling capacity. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent energy management system and control method for energy storage compartments, which solves the problems of existing solutions, which mainly rely on temperature results or predicted temperature to configure cooling capacity, do not utilize the carrier ripple generated by normal PCS switching to identify battery cluster impedance, and also have difficulty distinguishing the influence of cell ohmic impedance, electrochemical polarization impedance and connector contact impedance on heat generation.

[0004] This invention achieves the above objective through the following technical solution: an intelligent energy management system for an energy storage cabin, the system comprising: The synchronous acquisition module is used to acquire the DC side voltage, DC side current and carrier phase of the energy storage converter PCS, and to acquire the terminal voltage, branch current, cell temperature, connector temperature, cooling medium temperature, cooling medium flow rate and cabin zone temperature of each battery cluster, and to establish a carrier period data frame according to a unified clock. The carrier response identification module is used to perform phase alignment and period statistics on continuous carrier periodic data frames based on the carrier phase, and extract the carrier fundamental frequency component, carrier sideband component, voltage ripple amplitude, current ripple amplitude and ripple phase difference to form the battery cluster electrical response characteristics generated by the inherent switching ripple excitation of the PCS. The parameter decoupling module is used to decompose the equivalent impedance of the battery cluster into the ohmic impedance of the battery cell, the electrochemical polarization impedance and the contact impedance of the connector based on the electrical response characteristics of the battery cluster and the temperature rise location, temperature rise rate and response hysteresis of the battery cell, connector and cooling medium, and to determine the equivalent thermal resistance. The energy envelope module is used to determine the peak power boundary, continuous power boundary, polarization accumulation boundary and thermal accumulation boundary for different durations based on each decoupling parameter, and to generate a time-power safe adjustable energy envelope from the intersection of each boundary. The heat propagation modeling module is used to construct a dynamic directional heat propagation map based on the temperature change sequence, cooling medium flow direction, airflow direction, and structural connection relationship, with battery clusters, cooling branches, air duct partitions, and cabin space partitions as thermal nodes. The collaborative control module is used to identify risk source nodes when the node state exceeds the dynamic boundary, generate a thermal risk propagation cone containing downstream nodes, propagation paths and expected arrival times along the dynamic directional thermal propagation map, compress the power of the battery clusters inside the thermal risk propagation cone according to the safe adjustable energy envelope and transfer it to the battery clusters outside the thermal risk propagation cone, and adjust the cooling medium flow rate, cooling medium inlet temperature, fan speed or airflow direction on the propagation path to form a cooling blocking front before the heat arrives; The closed-loop correction module is used to update the dynamic directional heat propagation map, the safe and adjustable energy envelope, and the power-cooling distribution results based on the actual propagation path, actual propagation delay, and node temperature rise rate after control.

[0005] Furthermore, the synchronous acquisition module uses the start time of the PCS carrier cycle as the phase zero point and segments the voltage and current sample values ​​according to the carrier cycle. The carrier response identification module performs phase shifting on signal segments for no less than 32 consecutive carrier cycles, so that the phase zeros of each signal segment coincide. Then, it performs periodic averaging on the phase-aligned signal segments and calculates the complex voltage and complex current components at the carrier fundamental frequency and its adjacent sideband frequencies. The complex impedance response of the corresponding battery cluster is formed by the amplitude ratio and phase difference of the complex voltage and complex current components.

[0006] Furthermore, the parameter decoupling module uses the instantaneous resistance corresponding to the in-phase components of the ripple voltage and ripple current as a candidate ohmic impedance. When the temperature rise rate of the connector is greater than the temperature rise rate of the adjacent cells in the same battery cluster, and the time difference between the start time of the temperature rise of the connector and the start time of the instantaneous resistance rise is less than one temperature sampling period, the corresponding change is determined as the connector contact impedance increment. The instantaneous resistance after deducting the contact impedance increment of the connector is determined as the cell ohmic impedance. The electrochemical polarization impedance is determined based on the attenuation relationship between the ripple phase difference and the carrier sideband amplitude with frequency. The equivalent thermal resistance is determined based on the ratio of the battery cluster power loss to the steady-state temperature difference between the cell temperature and the inlet temperature of the cooling medium.

[0007] Furthermore, the energy envelope module determines the peak power boundary that satisfies the upper limit of the battery cluster terminal voltage, the lower limit of the terminal voltage, and the allowable temperature of the connector based on the ohmic impedance of the battery cell and the contact impedance of the connector. The continuous power boundary and heat accumulation boundary are determined based on the equivalent thermal resistance, current cell temperature, allowable cell temperature, and available cooling power. The polarization accumulation boundary is determined based on the electrochemical polarization impedance and the polarization decay time constant during the shutdown recovery phase. In the time-power coordinate system, the region that is simultaneously located within the peak power boundary, the sustained power boundary, the thermal accumulation boundary, and the polarization accumulation boundary is defined as the safe adjustable energy region, and the outer boundary of the safe adjustable energy region is defined as the time-power safe adjustable energy envelope.

[0008] Furthermore, the heat propagation modeling module establishes a set of thermal nodes according to the battery cluster installation location, cooling branch coverage area, air duct coverage area, and cabin partition location; When the temperature characteristic point of the first hot node appears earlier than that of the second hot node, and there is a structural heat transfer channel, cooling medium flow channel or airflow channel between the first hot node and the second hot node, a directed edge from the first hot node to the second hot node is established. The correlation coefficient of the temperature change sequences of two thermal nodes is used as the thermal coupling strength, the time difference between two temperature feature points is used as the propagation delay, and the proportion of the number of windows with consistent directed edge directions within a continuous monitoring window to the total number of monitoring windows is used as the propagation confidence.

[0009] Furthermore, the collaborative control module establishes a normal operation reference window for each thermal node, uses the sum of the median temperature rise rate within the reference window and three times the median absolute deviation to determine the dynamic boundary of the temperature rise rate, and uses the same method to determine the dynamic boundary of the connector contact impedance and the dynamic boundary of the electrochemical polarization impedance respectively. When the temperature rise rate, connector contact impedance or electrochemical polarization impedance of any thermal node exceeds the corresponding dynamic boundary, the thermal node is marked as a risk source node. A path search is performed from the risk source node along directed edges with a propagation confidence of not less than 0.8. The searched directed edges form a heat propagation path, and the cumulative value of the propagation delay of each directed edge in the same heat propagation path is determined as the estimated time for heat to reach the downstream heat node.

[0010] Furthermore, the collaborative control module determines the power compression amount based on the expected arrival time and safe adjustable energy margin of each battery cluster within the thermal risk propagation cone, and selects battery clusters outside the thermal risk propagation cone whose connector contact impedance does not exceed the corresponding dynamic boundary, whose remaining safe adjustable energy is greater than the energy to be received, and whose remaining cooling capacity of the cooling branch is greater than the new heat load. The compressed power is allocated according to the structural distance from the receiving battery cluster to the risk source node, from largest to smallest. The direction from the risk source node to the downstream propagation path with the largest cumulative thermal coupling strength is determined as the main direction of thermal propagation. The new heat-generating center of gravity is calculated based on the spatial coordinates of each receiving battery cluster and the new loss power. The receiving power of each receiving battery cluster is adjusted until the projection of the new heat-generating center of gravity on the main direction of thermal propagation is less than the projection of the heat-generating center of gravity on the main direction of thermal propagation before the power adjustment.

[0011] Furthermore, the collaborative control module identifies hot nodes with adjustable liquid cooling branches or adjustable air ducts as candidate blocking nodes in the propagation path from the risk source node to the downstream hot node. The target blocking node is selected based on the estimated arrival time of the candidate blocking node, the remaining cooling capacity, and the number of propagation paths covered by the candidate blocking node. Before the expected arrival time of the target blocking node, increase the cooling medium flow rate of the corresponding liquid cooling branch, reduce the cooling medium inlet temperature, increase the corresponding fan speed, or switch the position of the air guide valve to form a temperature distribution that decreases along the main direction of heat propagation between the target blocking node and the risk source node. The temperature distribution constitutes the cooling blocking front.

[0012] Furthermore, the closed-loop correction module uses the difference between the actual temperature feature point occurrence time and the expected arrival time to correct the propagation delay of the corresponding directed edge, uses the ratio of the temperature rise amplitude of adjacent hot nodes after control to correct the thermal coupling strength, and uses the ratio of the number of monitoring windows whose actual propagation direction is consistent with the direction of the directed edge to the total number of monitoring windows to correct the propagation confidence. Based on the ripple response and temperature rise response after power transfer, the ohmic impedance of the battery cell, the electrochemical polarization impedance, the contact impedance of the connector, and the equivalent thermal resistance are redefined. Based on the redefined decoupling parameters, the time-power safe adjustable energy envelope and the power-cooling distribution results for the next control cycle are generated.

[0013] A method for intelligent energy control of an energy storage compartment, characterized in that it is applied to an intelligent energy management system for an energy storage compartment as described above, the method comprising: The system acquires the DC-side voltage, DC-side current, and carrier phase of the PCS, as well as the terminal voltage, branch current, cell temperature, connector temperature, cooling medium inlet temperature, cooling medium outlet temperature, cooling medium flow rate, and cabin zone temperature of each battery cluster, and forms a carrier period data frame according to a unified clock. Based on the carrier phase, phase alignment and period statistics are performed on continuous carrier periodic data frames. The carrier fundamental frequency component, carrier sideband component, voltage ripple amplitude, current ripple amplitude and ripple phase difference are extracted to obtain the battery cluster electrical response characteristics generated by the inherent switching ripple excitation of the PCS. By combining the temperature rise location, temperature rise rate and response hysteresis of the cell, connector and cooling medium, the equivalent impedance of the battery cluster is decomposed into cell ohmic impedance, electrochemical polarization impedance and connector contact impedance, and the equivalent thermal resistance is determined. Based on each decoupling parameter, the peak power boundary, continuous power boundary, polarization accumulation boundary, and thermal accumulation boundary are determined to generate a time-power safety-adjustable energy envelope. Using battery clusters, cooling branches, air duct partitions, and cabin space partitions as thermal nodes, a dynamic directional heat propagation map is constructed based on the temperature change sequence of the thermal nodes, the flow direction of the cooling medium, the airflow direction, and the structural connection relationship. When the state of a hot node exceeds the dynamic boundary, the risk source node is determined, and the downstream hot node, propagation path and expected arrival time are determined along the dynamic directional heat propagation graph, generating a heat risk propagation cone; The power of the battery cluster inside the thermal risk propagation cone is transferred to the battery cluster outside the thermal risk propagation cone while satisfying the constraints of safe adjustable energy margin and remaining cooling capacity, so that the newly added heat center moves in the opposite direction of the main direction of heat propagation. Select cooling blockage nodes along the heat propagation path, and adjust the cooling medium flow rate, cooling medium inlet temperature, fan speed, or air guide valve position before the heat is expected to arrive, to form a temperature distribution that decreases along the main direction of heat propagation. Based on the actual propagation path, actual propagation delay, and temperature rise rate at hot nodes, update the dynamic directional heat propagation map, the time-power safe adjustable energy envelope, and the power-cooling distribution results.

[0014] The beneficial effects of this invention are as follows: 1. This invention utilizes an energy storage converter. The carrier fundamental frequency component, sideband component, and ripple phase information generated during normal operation serve as online identification excitation. Without the need to add pulse current or frequency sweep signal to the battery cluster, the electrical response characteristics of the battery cluster can be extracted during the normal charging and discharging process of the energy storage compartment, reducing the impact of the state identification process on the continuity of energy storage operation and the execution of power commands.

[0015] 2. This invention combines electrical response characteristics with the temperature rise location, temperature rise rate, and response hysteresis of the battery cell, connectors, and cooling medium, decoupling the equivalent parameters of the battery cluster into the ohmic impedance of the battery cell, the electrochemical polarization impedance, the contact impedance of the connector, and the equivalent thermal resistance. This can distinguish different risks caused by aging of the battery cell, polarization accumulation, connector abnormalities, and decreased heat dissipation capacity, thereby improving the accuracy of anomaly location.

[0016] 3. This invention maps instantaneous peak power, continuous charge and discharge power, polarization accumulation and thermal accumulation constraints to a time-power plane, forming a safe and adjustable energy envelope that dynamically changes with battery status and cooling capacity, thus transforming power scheduling from fixed limit control to dynamic power boundary control for different durations.

[0017] 4. This invention describes the direction of heat propagation, thermal coupling strength, propagation delay and propagation confidence between battery clusters, cooling branches, air ducts and cabin space through a dynamic directional heat propagation map, and predicts downstream affected nodes in the early stage of risk formation, thereby transforming the traditional over-temperature post-treatment method into an active intervention method before the propagation of thermal risks.

[0018] 5. The present invention implements power redistribution based on the thermal risk propagation cone, causing the newly added heat-generating center to move in the opposite direction of the heat propagation direction, and pre-forming a cooling blocking front on the expected propagation path, thereby realizing the coordinated control of power scheduling and cooling resource allocation, and reducing the possibility of local thermal risks spreading to adjacent battery clusters.

[0019] 6. Based on the actual heat propagation direction, actual propagation time delay, and temperature rise changes after scheduling, this invention continuously corrects the dynamic directional heat propagation map, the safe and adjustable energy envelope, and the power-cooling distribution strategy. It can adapt to battery aging, changes in cooling capacity, and changes in ambient temperature, thereby improving the control adaptability of the energy storage compartment during long-term operation. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a schematic diagram of the system structure of the present invention; Figure 2 This is a flowchart of the control method of the present invention; Figure 3 This is a schematic diagram of the time-power safety-adjustable energy envelope of the present invention; Figure 4 This is a diagram of the dynamic directional heat propagation and cooperative control of the present invention. Detailed Implementation

[0021] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0022] Example 1: Please see Figures 1-4 This invention provides an intelligent energy management system for an energy storage cabin. In this embodiment, the energy storage cabin has a rated power of 1MW and includes eight battery clusters connected in parallel to a DC bus, each with a rated power of 125kW. The battery clusters use lithium iron phosphate batteries, and each cluster is equipped with a cluster-level battery management unit, a terminal voltage acquisition unit, a branch current sensor, a cell temperature sensor, and a connector temperature sensor. The parameters provided are for illustrative purposes only and do not constitute a limitation on the energy storage cabin capacity or the battery material system.

[0023] Connector temperature sensors are installed at the busbar connection, fuse connection, and high-voltage connector contact points of the battery cluster. Each battery cluster has at least four connector temperature measurement points, and a one-to-one mapping relationship is established between the connector temperature measurement points and the corresponding current path locations to correlate local temperature rise with changes in connector contact impedance. Cell temperature sensors are arranged according to battery modules, ensuring that each battery module has at least one representative temperature measurement point.

[0024] The energy storage compartment employs a combined liquid cooling and air cooling heat dissipation structure. Each liquid cooling branch is equipped with a cooling medium inlet temperature sensor, an outlet temperature sensor, a flow sensor, and an electrically controlled regulating valve; each air duct area is equipped with a fan speed feedback unit, a guide valve position feedback unit, and an airflow direction detection unit. The energy storage compartment is divided into 8 internal temperature zones along its length, and each temperature zone is equipped with at least one ambient temperature sensor.

[0025] The upper limit of the cell control temperature is set at 45℃, and the upper limit of the connector control temperature is set at 55℃. The upper limit of the control temperature is determined based on the continuous charge and discharge temperature range specified by the cell manufacturer, the allowable operating temperature specified by the connector manufacturer, and the thermal management design documents of the energy storage compartment, and is lower than the protection shutdown temperature to reserve room for active adjustment.

[0026] The cell temperature allowance is set at 3K, where the maximum permissible error of the temperature sensor is 1K, the maximum predicted temperature rise within a single power control cycle is 1.5K, and the remaining 0.5K is used to compensate for communication delays and actuator response deviations. Therefore, when the cell temperature reaches 42℃, the system begins to limit its continuous power.

[0027] In this manual, absolute temperature monitoring values ​​are expressed in degrees Celsius, and temperature difference is expressed in Kelvin. Since the temperature change of 1 K is the same as the temperature change of 1 °C, temperature difference is uniformly converted to Kelvin when calculating thermal resistance, so that the dimension of thermal resistance is uniformly Kelvin per watt. Power is uniformly converted to watts, energy is uniformly converted to watt-hours, impedance is uniformly converted to ohms, flow rate is uniformly converted to liters per minute, and time is uniformly converted to seconds.

[0028] The synchronous acquisition module obtains DC-side voltage, DC-side current, carrier phase, and carrier period synchronization markers from the energy storage converter PCS controller. At the same time, it obtains terminal voltage, branch current, cell temperature, connector temperature, cooling medium inlet temperature, cooling medium outlet temperature, cooling medium flow rate, fan speed, air guide valve position, and compartment zone temperature of each battery cluster from the battery management system and thermal management controller.

[0029] The carrier cycle synchronization marker is directly output by the PCS controller or generated based on the rising edge of the drive signal of the PCS power switching device. The synchronization acquisition module uses the start time of each carrier cycle as the phase zero point and configures a timestamp for each acquired data point according to a unified clock. The unified clock is preferably provided by the PCS controller, but it can also be provided by an independent clock source with microsecond-level synchronization accuracy.

[0030] In this embodiment, the PCS pulse width modulation carrier frequency is 10kHz, and the sampling frequency of the voltage and current signals is set to 200kHz, which is 20 times the carrier frequency. Each carrier cycle contains 20 raw sampling points. The sampling frequency can cover the carrier base frequency and its adjacent sidebands, and can also control the data throughput and real-time computing load.

[0031] When the PCS carrier frequency is adjusted, the sampling frequency for voltage and current is determined according to the rule of not less than 10 times the carrier frequency. The specific sampling multiple is obtained through a spectrum stability test before commissioning: sampling is performed sequentially at 10 times, 15 times, 20 times, and 25 times the carrier frequency. When the relative deviation of the carrier fundamental frequency amplitude obtained from two adjacent sampling frequencies does not exceed 2%, and the ripple phase difference deviation does not exceed 2°, the lower of the two sampling frequencies is selected as the actual sampling frequency.

[0032] The sampling period for cell temperature, connector temperature, cooling medium temperature and cooling medium flow rate is set to 1 second, the sampling period for cabin zone temperature is set to 1 second, and the sampling period for fan speed and air guide valve position is set to 0.5 seconds.

[0033] The temperature sampling period is determined based on the measured minimum thermal response time of the energy storage compartment: before commissioning, a step power of 20% of the rated power is applied to a single battery cluster, and the shortest time required for the temperature of the cell or connector to show a identifiable change is recorded; in this embodiment, the shortest thermal response time is measured to be 18s, so the temperature sampling period is set to 1s to obtain no less than 18 sampling points within the shortest thermal response time.

[0034] The synchronous acquisition module segments voltage and current data according to the carrier cycle, groups data within the same carrier cycle into carrier cycle data frames, and associates temperature data, cooling medium data, and fan status data with the corresponding carrier cycle data frame groups based on timestamps. For data frames with timestamp deviations exceeding one electrical parameter sampling cycle, linear time correction is performed; data frames that cannot be time-corrected are not included in the carrier response identification process.

[0035] The carrier response identification module selects 128 carrier cycles from a continuous carrier cycle data frame as an electrical response analysis window. When the carrier frequency is 10kHz, the duration of one analysis window is 12.8ms.

[0036] The analysis window length was determined through stability tests: An initial window of 64 carrier cycles was used, and the lengths were subsequently increased to 128, 192, and 256 carrier cycles, respectively, to calculate the carrier fundamental frequency amplitude and ripple phase difference. The shorter window length was selected when the relative deviation of the carrier fundamental frequency amplitude obtained from the two consecutive window lengths did not exceed 3%, and the ripple phase difference deviation did not exceed 2°. In this embodiment, 128 carrier cycles satisfied the above conditions.

[0037] The carrier response identification module takes the start time of the carrier cycle as the phase zero point and performs phase shifting on the voltage and current signal segments of each carrier cycle within the analysis window to make the phase zero points of each signal segment coincide. Subsequently, it performs period median statistics on the sampled values ​​at the same phase position to reduce the impact of random load fluctuations, switching spikes, and isolated abnormal sampled values ​​on the spectrum analysis results.

[0038] After completing phase alignment and period statistics, respectively... Discrete spectrum analysis was performed on the DC-side common voltage and the branch currents of each battery cluster to extract the complex spectral components at the carrier fundamental frequency, the first sideband on both sides of the carrier fundamental frequency, and the second sideband. Individual battery clusters at frequency The complex impedance response at the point is determined according to equation (1):

[0039] In equation (1), For the first Individual battery clusters at frequency The complex impedance response at the point, in ohms; for DC side common voltage at frequency The complex spectral components at the location, in volts; For the first The branch current of each battery cluster is at frequency The complex spectral components at the location, in amperes; The carrier fundamental frequency or the selected carrier sideband frequency, in Hertz.

[0040] The voltage and current in Equation (1) are complex spectral components under the same time window, the same frequency point and the same phase reference. The real part of the complex impedance is used to characterize the in-phase loss response, and the imaginary part and phase of the complex impedance are used to characterize the hysteresis response.

[0041] When the branch current amplitude at any frequency point is less than 0.5% of the full-scale range of the current sensor, that frequency point is not used to calculate the complex impedance to avoid amplifying measurement errors due to a small denominator. 0.5% is determined through a current sensor noise test: continuous data is collected for 10 minutes under no-power output conditions from the battery cluster. Three times the upper limit of the noise amplitude is taken as the minimum effective current amplitude, which is then converted to the full-scale range ratio of the current sensor. In this embodiment, the conversion result is 0.43%, which is rounded up to 0.5%.

[0042] The carrier response identification module also extracts the voltage ripple amplitude, current ripple amplitude, and the phase difference between the voltage ripple and current ripple to form a set of electrical response characteristics for each battery cluster. Since the electrical response characteristics originate from the inherent switching ripple generated when the PCS executes the original charging and discharging power command, the identification process does not change the PCS power setpoint, does not inject additional pulse signals into the DC bus, and does not connect to external frequency sweep excitation equipment, thus constituting an online state identification without additional disturbances.

[0043] The parameter decoupling module determines the ohmic impedance of the battery cell, the electrochemical polarization impedance, the contact impedance of the connector, and the equivalent thermal resistance based on the real part of the complex impedance, the imaginary part of the complex impedance, the ripple phase difference, the carrier sideband attenuation characteristics, and the temperature rise location, temperature rise rate, and response hysteresis of the battery cell, connector, and cooling medium.

[0044] First, the portion of the real part of the complex impedance at the carrier fundamental frequency that changes instantaneously with the branch current is identified as a candidate quantity of ohmic impedance. Then, the onset times of temperature rise for the connector, the battery cell, and the ohmic impedance candidate quantity are determined. The onset time of temperature rise is the first moment when the temperature rise rate exceeds the corresponding upper limit of normal fluctuation for two consecutive sampling periods.

[0045] When the temperature rise rate of the connector is higher than that of the adjacent cells in the same battery cluster, the temperature rise measurement point of the connector corresponds to the position of the busbar connection terminal, high voltage connector or fuse connection terminal, and the time difference between the start time of the temperature rise of the connector and the start time of the rise of the candidate ohmic impedance does not exceed 1 second, the corresponding impedance change is determined as the connector contact impedance increment.

[0046] The minimum distinguishable difference between the temperature rise rate of the connector and the temperature rise rate of adjacent cells is set to 0.10 K / min. This difference is determined based on the temperature sensor resolution and temperature rise fluctuations during normal operation: In this embodiment, the temperature sensor resolution is 0.1 K, and the 95th percentile of the temperature rise rate difference between adjacent measuring points under normal operating conditions is 0.07 K / min. This difference is rounded up to 0.10 K / min to eliminate misjudgments caused by sensor resolution and uneven normal cooling.

[0047] The remaining portion of the candidate ohmic impedance after deducting the connector contact impedance is determined as the cell ohmic impedance. When more than 70% of the effective cell temperature measurement points within the same battery cluster experience synchronous temperature rise, and no localized temperature rise occurs at the connector temperature measurement points, the corresponding change in ohmic impedance is attributed to the cell ohmic impedance. The 70% is determined based on the temperature measurement point coverage: allowing for individual measurement point failure and localized cooling fluctuations, synchronous changes in more than two-thirds of the effective measurement points can characterize cluster-level distributed temperature rise; this embodiment uses 70% rounded up.

[0048] The electrochemical polarization impedance is determined based on the imaginary part of the complex impedance, the attenuation relationship of the carrier sideband amplitude with frequency, and the hysteresis recovery process after power adjustment. If the imaginary part of the complex impedance continues to decay after power reduction, but the temperature of the connector does not decrease synchronously, then this hysteresis is attributed to the electrochemical polarization response. The polarization recovery time is the time it takes for the change in the imaginary part of the complex impedance to decay to 36.8% of its initial change; 36.8% corresponds to a time constant in the first-order decay process, and this parameter is directly obtained from the measured recovery curve without any arbitrary weighting.

[0049] The equivalent thermal resistance of the battery cluster is determined according to equation (2):

[0050] In equation (2), For the first The equivalent thermal resistance of a battery cluster, in Kelvin per watt; For the first The representative cell temperature of each battery cluster, in degrees Celsius; For the first The inlet temperature of the cooling medium for each battery cluster's corresponding cooling branch is expressed in degrees Celsius. and The difference is converted to Kelvin; For the first The power loss of a battery cluster, measured in watts.

[0051] The cell temperature is represented by the median of all effective cell temperatures in the battery cluster to avoid abrupt changes in equivalent thermal resistance caused by abnormal temperatures at a single measurement point. Power loss is determined based on branch current, cell ohmic impedance, connector contact impedance, and losses corresponding to electrochemical polarization response; all loss components are converted to watts and then summed.

[0052] Equation (2) is used within the quasi-steady-state range. The quasi-steady-state range is determined by the following rules: the rate of change of battery cluster power does not exceed 2% / min of rated power for 180 consecutive seconds, and the rate of temperature rise of the representative cell does not exceed 0.02K / min for 180 consecutive seconds. 180 seconds is determined based on the longest time required for the temperature difference between the cell and the cooling medium to stabilize in the step test of the liquid cooling system.

[0053] The energy envelope module determines the peak power boundary, continuous power boundary, polarization accumulation boundary, and thermal accumulation boundary based on the ohmic impedance of the battery cell, the contact impedance of the connector, the electrochemical polarization impedance, and the equivalent thermal resistance, and forms a safe and adjustable energy envelope in the time-power coordinate system.

[0054] The peak power boundary is simultaneously limited by the battery cluster terminal voltage, connector temperature, and the allowable current of the PCS and DC bus. During charging, the battery cluster terminal voltage must not exceed the upper limit of the charging voltage specified by the battery manufacturer; during discharging, the battery cluster terminal voltage must not be lower than the lower limit of the discharging voltage specified by the battery manufacturer; the predicted temperature of the connector must not exceed 55°C; and the current of the PCS and DC bus must not exceed their continuous allowable current. For the same duration, the allowable power value for each constraint is determined separately, and the minimum value is selected as the peak power boundary. This process uses constraint intersection and does not assign subjective evaluation weights.

[0055] The continuous power boundary is determined based on the current cell temperature, the upper limit of the control temperature of 45°C, the temperature reserve of 3K, the equivalent thermal resistance, and the remaining cooling capacity of the cooling branch. The remaining cooling capacity of the cooling branch is the measured available cooling capacity of the cooling device under the current inlet temperature and flow conditions minus the current heat load, and its unit is uniformly watts. If the predicted continuous power will cause the cell temperature to exceed 42°C, the continuous power boundary is reduced until the predicted temperature does not exceed 42°C.

[0056] The polarization accumulation boundary is determined based on the electrochemical polarization impedance and polarization recovery time. As the continuous high-power operation time increases, the power that can be maintained gradually decreases; when the battery cluster enters the low-power recovery phase, its adjustable power is restored based on the measured polarization decay process. The thermal accumulation boundary is determined based on the temperature margin between the current cell temperature and the 42°C active limiting temperature, the equivalent thermal resistance, and the remaining cooling capacity.

[0057] The peak power boundary, sustained power boundary, polarization accumulation boundary, and thermal accumulation boundary are mapped to a time-power coordinate system, and the region jointly allowed by these four boundaries is defined as the safe and adjustable energy region. The outer boundary of this region constitutes the time-power safe and adjustable energy envelope. For a predetermined scheduling duration, the safe and adjustable energy margin is the difference between the maximum energy allowed by the safe and adjustable energy envelope and the currently allocated energy.

[0058] In this embodiment, the power control cycle is set to 5 seconds, and the safe adjustable energy envelope is updated every 5 seconds. The control cycle is determined based on the PCS power command refresh cycle and the cooling actuator response time: this cycle can complete multiple power adjustments within the shortest effective heat propagation delay, while avoiding excessively frequent changes to the power command.

[0059] The heat propagation modeling module divides the energy storage compartment into battery thermal nodes, cooling thermal nodes, airflow thermal nodes, and space thermal nodes. Each battery cluster corresponds to at least one battery thermal node, each independent liquid cooling branch corresponds to one cooling thermal node, each area controlled by the same fan and air guide valve corresponds to one airflow thermal node, and the spaces between adjacent battery clusters and between battery clusters and the compartment walls correspond to space thermal nodes.

[0060] When the maximum temperature difference within a battery cluster exceeds 3K, the battery cluster is further divided into upper hot nodes and lower hot nodes. 3K is determined based on the 95th percentile of the temperature difference within the battery cluster under normal operating conditions. In this embodiment, the 95th percentile is 2.6K, which is rounded up and used as the node subdivision threshold.

[0061] The heat propagation modeling module updates the dynamic directed heat propagation map every 30 seconds. The update cycle is determined based on the shortest measured effective propagation delay between adjacent hot nodes; in this embodiment, the shortest effective propagation delay is measured to be 68 seconds, so the map update cycle is set to 30 seconds, enabling the system to complete the propagation relationship correction before the heat reaches the next hot node.

[0062] When the temperature rise characteristic point of the first hot node appears earlier than that of the second hot node, the correlation coefficient of the temperature change sequences of the two hot nodes is not less than 0.70, and there is a structural heat transfer channel, cooling medium flow channel, or airflow channel between them, a candidate directed edge from the first hot node to the second hot node is established. The temperature rise characteristic point is the first moment when the temperature rise rate of the hot node exceeds the corresponding dynamic boundary for two consecutive sampling periods.

[0063] The correlation coefficient threshold was determined through a step power test before commissioning. Propagation paths were constructed using candidate thresholds of 0.60, 0.65, 0.70, 0.75, and 0.80, respectively, and the lowest threshold with a false negative rate not exceeding 5% and a false positive rate not exceeding 5% was selected; in this embodiment, 0.70 satisfies the above conditions. Candidate directed edges were also verified based on the cooling medium flow direction, airflow direction, and structural connection relationships to exclude connections that only have statistical correlation but lack actual heat transfer channels.

[0064] The correlation coefficient of the temperature change sequences of two hot nodes is used as the thermal coupling strength, the time difference between two temperature rise feature points is used as the propagation delay, and the proportion of windows with consistent directed edge directions within a continuous monitoring window to the total number of monitoring windows is used as the propagation confidence. The hot nodes, directed edges, thermal coupling strength, propagation delay, and propagation confidence together constitute a dynamic directed heat propagation graph.

[0065] The collaborative control module establishes dynamic boundaries for temperature rise rate, connector contact impedance, and electrochemical polarization impedance. The reference window uses normal operation data from the 30 minutes prior to the current moment; this duration covers at least 360 power control cycles and multiple adjustment processes of the cooling device, reflecting normal fluctuations in ambient temperature, state of charge, and cooling conditions.

[0066] Data from the first 5 minutes after equipment startup, data before and after equipment shutdown, data showing power changes exceeding 10% of the battery cluster's rated power within 10 seconds, sensor communication interruption data, sensor over-range data, and data already marked as risky conditions are not included in the baseline window. The dynamic boundary of any monitoring parameter x is determined according to equation (3):

[0067] In equation (3), For monitoring parameters The dynamic boundary, whose unit is the same as the monitoring parameter. Consistent; Monitoring parameters within the baseline window the median; The median is the absolute value of the difference between each data point in the baseline window and the median; coefficient 3 is the outlier separation coefficient.

[0068] When monitoring parameters When the temperature rise rate is, The unit is Kelvin per minute; when monitoring parameters When the contact resistance or electrochemical polarization resistance of the connector is used, The unit is ohms or milliohms. The abnormal separation coefficient is determined through normal operating condition tests and fault injection tests before commissioning. 2.0, 2.5, 3.0 and 3.5 are used as candidate coefficients respectively; when the coefficient is 3.0, the false alarm rate under normal operating conditions is less than 1%, and the recognition rate of the test state with a 20% increase in the contact impedance of the connector exceeds 95%, so 3.0 is adopted.

[0069] If the median absolute deviation within the reference window is less than the sensor resolution, then the sensor resolution is used as the lower limit of the median absolute deviation to avoid the dynamic boundary coinciding with the median when the data fluctuation is too small.

[0070] When the temperature rise rate, the contact impedance of the corresponding battery cluster connector, or the electrochemical polarization impedance of any hot node exceed the corresponding dynamic boundary for two consecutive sampling periods, that hot node is identified as a risk source node. The rule of determining two consecutive sampling periods is used to exclude single sampling spikes, and its duration is... It is less than the shortest response time of the cooling device and the heat transfer process.

[0071] The collaborative control module starts from the risk source node and searches for a path along directed edges with a propagation confidence level of not less than 0.80. The propagation confidence level threshold is determined through a pre-commissioning step power test: when the threshold is 0.80, the proportion of inconsistencies between the predicted and measured propagation paths is 4.2%; further increasing the threshold will increase the missed detection rate of effective propagation paths, therefore 0.80 is adopted. For a propagation path composed of multiple directed edges, the cumulative value of the propagation delay of each directed edge is determined as the expected time for heat to reach the downstream hot node. The heat risk propagation cone is composed of the risk source node, the downstream hot node that meets the confidence level condition, the propagation path, and the expected arrival time.

[0072] The collaborative control module first reduces the charging and discharging power of the battery clusters corresponding to the risk source nodes and the downstream battery clusters within the thermal risk propagation cone. Power compression adopts a graded condition judgment, without using weighted summation: battery clusters with expected arrival times not exceeding 120s are compressed first, followed by battery clusters with adjustable safety energy margins less than 10% of rated energy, and then battery clusters with connector contact impedance close to the dynamic boundary are compressed.

[0073] The expected arrival time threshold of 120s is determined based on the maximum response time required for the liquid cooling system to reach 90% of the target flow rate from receiving the control command. In this embodiment, the maximum response time of the liquid cooling system is 84s, which is increased by a control margin of 36s to obtain 120s. The 10% threshold of the safety adjustable energy margin is used to ensure that the affected battery cluster still retains the energy buffer required to complete the current power switching. This threshold is determined through a maximum power slope test.

[0074] Battery clusters are screened outside the thermal risk propagation cone. Acceptable battery clusters must simultaneously meet the following conditions: a safe adjustable energy margin not less than the energy to be accepted; connector contact impedance below 90% of its dynamic boundary; cell temperature below 42℃; and remaining cooling capacity of the corresponding cooling branch greater than 1.2 times the expected additional power loss. The 90% connector contact impedance is used to reserve impedance variation margin before power acceptance; the cooling capacity coefficient of 1.2 includes 10% cooling capacity measurement error and 10% execution deviation, and is verified through a full-power thermal balance test before commissioning.

[0075] The collaborative control module allocates the compressed power in descending order of the structural distance from the receiving battery cluster to the risk source node. The structural distance is the shortest path length along the battery rack, air duct, or cabin space that allows for actual heat propagation, expressed in meters. The newly added heat-generating center of gravity after power transfer is determined according to equation (4):

[0076] In equation (4), The spatial coordinates of the newly added center of gravity for heating are given in meters. For the first The additional power loss caused by the power received by each battery cluster is expressed in watts. For the first The spatial coordinates of the battery cluster are in meters. The number of battery clusters to be accommodated. The newly added power loss is a heat generation with clear physical meaning, and is not an artificially set evaluation weight. Spatially weighting the newly added power loss can directly characterize the location of the new heat source after power transfer.

[0077] The direction of the downstream propagation path pointing from the risk source node to the path with the greatest cumulative thermal coupling strength is determined as the main direction of heat propagation. When the projection of the newly added heat-generating center of gravity on the main direction of heat propagation is not less than the corresponding projection of the heat-generating center of gravity before power adjustment, the power received by the battery cluster on the side of the main direction of heat propagation is reduced, and the power received by the battery cluster on the opposite side is increased. Each power adjustment is set to 1% of the rated power of the energy storage compartment, which is 10kW in this embodiment. The adjustment step size is determined based on the PCS power regulation resolution and the power fluctuation test between battery clusters. A step size less than 1% will increase the number of iterations, while a step size greater than 1% may cause the candidate battery cluster to exceed the safe adjustable energy envelope.

[0078] The collaborative control module identifies heat nodes with adjustable liquid cooling branches, adjustable fans, or adjustable air guide valves as candidate blocking nodes along the propagation path from the risk source node to the downstream heat node. Candidate blocking nodes are not selected using weighted scoring, but rather in a predetermined order. First, candidate blocking nodes with remaining cooling capacity less than 1.2 times the expected propagation heat load are eliminated. Second, candidate blocking nodes that can simultaneously cover the most propagation paths are selected. Third, when the number of propagation paths covered is the same, candidate blocking nodes with longer expected arrival times and actuators capable of adjusting before the heat arrives are selected. Finally, if the expected arrival times are still the same, candidate blocking nodes farther from the risk source node are selected to expand the cooling blocking area.

[0079] The cooling control advance time is calculated by taking the maximum value among the liquid cooling valve response time, the cooling unit inlet temperature adjustment response time, the fan speed-up response time, and the air guide valve switching time, and adding a 20% execution margin. In this embodiment, the cooling unit takes the longest time to complete the inlet temperature adjustment, which is 75 seconds, so the cooling control advance time is set to 90 seconds.

[0080] When the expected arrival time of heat is less than 90 seconds, prioritize increasing the existing cooling medium flow rate and fan speed; when the expected arrival time is not less than 90 seconds, simultaneously adjust the cooling medium inlet temperature, cooling medium flow rate, fan speed, and guide valve position. The single adjustment range of the liquid cooling branch flow rate should not exceed 20% of the current flow rate, the single decrease in the cooling medium inlet temperature should not exceed 3K, and the single increase in fan speed should not exceed 20% of the rated speed. These limits are determined based on the allowable adjustment rate specified by the cooling device manufacturer and the requirement to avoid sudden local temperature changes.

[0081] Through the above adjustments, a temperature distribution that decreases along the main direction of heat propagation is formed between the target blocking node and the risk source node. This temperature distribution is opposite to the direction of heat propagation and constitutes a cooling blocking front, which is used to weaken the heat transfer from the risk source node to the downstream hot node.

[0082] The closed-loop correction module compares the actual temperature rise characteristic points with the predicted temperature rise characteristic points every 30 seconds. When the deviation between the actual arrival time and the predicted arrival time does not exceed 10% of the predicted propagation delay, the current propagation delay is retained; when the deviation exceeds 10%, the propagation delay is updated using the median of the last 5 valid propagation records. Using the median instead of a weighted average reduces the impact of single fan switching, hatch opening, or sudden changes in ambient temperature on the propagation delay.

[0083] When the actual propagation direction matches the direction of the directed edge in the dynamic directed thermal propagation diagram, the corresponding monitoring window is recorded as a consistent window; the propagation confidence is updated using the proportion of consistent windows among the most recent 20 valid monitoring windows. When the actual propagation path differs from the predicted propagation path, the propagation confidence of the erroneous directed edge is reduced, and the corresponding directed edge is established or strengthened according to the order of occurrence of actual temperature rise characteristic points. After completing one power transfer, the closed-loop correction module re-extracts the complex impedance response and temperature rise response of each battery cluster, redetermines the ohmic impedance of the cell, the electrochemical polarization impedance, the contact impedance of the connector, and the equivalent thermal resistance, and generates the time-power safe adjustable energy envelope and power-cooling distribution results for the next control cycle, thereby forming a closed-loop control for energy management of the energy storage compartment.

[0084] Example 2: This embodiment illustrates the invention using a single control process of an energy storage module with a rated power of 1MW. The energy storage module comprises eight parallel battery clusters, each with an initial discharge power of 100kW. The energy storage module operates with a total discharge power of 800kW. The PCS carrier frequency is 10kHz, the voltage and current sampling frequency is 200kHz, and the carrier response analysis window includes 128 carrier cycles. The temperature and cooling medium flow rate sampling period is 1s, the power scheduling period is 5s, and the dynamic directional heat propagation map update period is 30s.

[0085] The median reference contact impedance of the connector of the third battery cluster is 0.18 mΩ, and the absolute deviation of the median is 0.027 mΩ. According to equation (3), its dynamic boundary is determined to be 0.261 mΩ. During operation, the contact impedance of the connector of the third battery cluster rises to 0.31 mΩ and remains above the dynamic boundary for 2 seconds. The temperature rise rate of the connector is 0.42 K / min, corresponding to a dynamic boundary of 0.29 K / min. The temperature rise rate of the adjacent cell is 0.11 K / min.

[0086] The difference between the temperature rise rate of the connector and that of the adjacent cell is 0.31 K / min, which is greater than the minimum distinguishable temperature rise rate difference of 0.10 K / min. The location of the temperature rise of the connector is consistent with the bus connection end. The starting time of the temperature rise of the connector differs from the starting time of the rise of the candidate ohmic impedance by 1 second. Therefore, the parameter decoupling module determines the abnormal impedance change as an increase in the contact impedance of the connector, rather than an overall increase in the ohmic impedance of the cell.

[0087] The dynamic directed heat propagation diagram shows that the propagation delay from the third battery cluster to the adjacent spatial hot node is 68 s with a propagation confidence level of 0.91; the propagation delay from the spatial hot node to the fourth battery cluster is 94 s with a propagation confidence level of 0.87. Therefore, the estimated time for heat to reach the fourth battery cluster is 162 s, and the heat risk propagation cone is formed by the third battery cluster, the adjacent spatial hot node, the fourth battery cluster, and the corresponding directed edges.

[0088] The collaborative control module reduces the discharge power of the third battery cluster from 100kW to 68kW and the discharge power of the fourth battery cluster from 100kW to 82kW, a total reduction of 50kW. The seventh and eighth battery clusters are located outside the thermal risk propagation cone, with connector contact impedances of 0.17mΩ and 0.16mΩ, respectively, both below 90% of their corresponding dynamic boundaries; cell temperatures are 34.2℃ and 33.8℃, respectively; remaining safe adjustable energy is 92kWh and 88kWh, respectively; and the remaining cooling capacity of the corresponding cooling branches is greater than 1.2 times the newly added power loss.

[0089] According to the order of structural distance to the risk source node from largest to smallest, the eighth battery cluster receives 27kW and the seventh battery cluster receives 23kW. According to equation (4), the newly added heat-generating center of gravity after power transfer moves 1.36m in the opposite direction of the main heat propagation direction relative to the heat-generating center of gravity before power transfer, which satisfies the condition of reverse migration of the newly added heat-generating center of gravity.

[0090] The airflow area between the third and fourth battery clusters was identified as the target blocking node. The system initiated cooling control 90 seconds before the expected heat arrival, increasing the flow rate of the corresponding liquid cooling branch from 6 L / min to 7.2 L / min, reducing the inlet temperature of the cooling medium from 24°C to 21°C, increasing the corresponding fan speed from 55% to 75% of the rated speed, and switching the airflow guide valve to direct the airflow towards the third battery cluster.

[0091] After control was completed, the actual temperature rise characteristic point of the fourth battery cluster appeared 170 seconds after the formation of the risk source node, which differed from the predicted duration of 162 seconds by 8 seconds, a deviation of 4.94%, which was below the 10% propagation delay correction condition. Therefore, the original propagation delay was retained. Throughout the control process, the total discharge power of the energy storage chamber remained at 800kW. The temperature rise rate of the third battery cluster connector decreased from 0.42K / min to 0.16K / min, and the maximum temperature rise rate of the fourth battery cluster decreased from the predicted 0.34K / min to 0.12K / min.

[0092] Example 3: This embodiment provides an intelligent energy control method for an energy storage cabin. The method is executed by the system of Embodiment 1 and includes the following steps.

[0093] 1. Synchronous Acquisition The DC side voltage, DC side current, and carrier phase, as well as the terminal voltage, branch current, cell temperature, connector temperature, cooling medium inlet temperature, cooling medium outlet temperature, cooling medium flow rate, and cabin zone temperature of each battery cluster, are all used to form a carrier periodic data frame according to a unified clock.

[0094] 2. Taking the start time of the carrier period as the phase zero point, perform phase alignment and period statistics on continuous carrier periodic data frames, extract the carrier fundamental frequency component, carrier sideband component, voltage ripple amplitude, current ripple amplitude, and ripple phase difference, and obtain the result from... The complex impedance response of the battery cluster generated by the inherent switching ripple excitation.

[0095] 3. Based on the complex impedance response and the temperature rise location, temperature rise rate and response hysteresis of the cell, connector and cooling medium, determine the ohmic impedance of the cell, the electrochemical polarization impedance, the contact impedance of the connector and the equivalent thermal resistance.

[0096] 4. Determine the peak power boundary, continuous power boundary, polarization accumulation boundary, and thermal accumulation boundary based on each decoupling parameter, and take the region generation time-power safety adjustable energy envelope that is allowed by all four boundaries.

[0097] 5. Using battery clusters, cooling branches, air duct zones, and cabin space zones as thermal nodes, a dynamic directional heat propagation map is constructed based on the temperature change sequence of the thermal nodes, the flow direction of the cooling medium, the airflow direction, and the structural connection relationship.

[0098] 6. Determine the dynamic boundaries of temperature rise rate, connector contact impedance, and electrochemical polarization impedance based on the normal operation reference window. When any monitoring parameter exceeds the corresponding dynamic boundary for two consecutive sampling cycles, determine the risk source node and generate a thermal risk propagation cone along the directed edge with a propagation confidence of not less than 0.80.

[0099] 7. Compress the power of the battery clusters inside the heat risk propagation cone, screen the battery clusters outside the heat risk propagation cone that meet the conditions of safe adjustable energy margin, connector contact impedance, temperature and remaining cooling capacity, and adjust the receiving power of each battery cluster to make the newly added heat center move in the opposite direction of the main heat propagation direction.

[0100] 8. Identify the target blocking node on the heat propagation path, and adjust the cooling medium flow rate, cooling medium inlet temperature, fan speed and air guide valve position before the heat is expected to arrive, to form a cooling blocking front facing the direction of heat propagation.

[0101] 9. Based on the actual propagation path, actual propagation delay, temperature rise rate of hot nodes, and complex impedance response after power transfer, update the dynamic directional heat propagation diagram, the time-power safe adjustable energy envelope, and the power-cooling distribution results for the next control cycle.

[0102] Example 4: This embodiment illustrates the process by which the intelligent energy management system of the energy storage compartment performs power-cooling capacity coordinated regulation under the combined effects of high ambient temperature, decreased heat exchange capacity of cooling branches, and accumulated electrochemical polarization.

[0103] This embodiment uses the same 1MW energy storage chamber as Embodiment 1, which includes eight parallel battery clusters, each with a rated power of 125kW. During testing, the ambient temperature outside the chamber was 38℃, and the energy storage chamber operated at a total charging power of 720kW, with each battery cluster initially charging at 90kW. The PCS carrier frequency was 10kHz, the voltage and current sampling frequency was 200kHz, the carrier response analysis window included 128 consecutive carrier cycles, the sampling period for temperature and cooling medium flow was 1s, the power scheduling period was 5s, and the update period for the dynamic directional heat propagation map was 30s.

[0104] Before system operation, a 30-minute normal operation reference window was established for each battery cluster based on the current ambient temperature and current battery state of charge. Among them, the median reference electrochemical polarization impedance of the sixth battery cluster was 0.42 mΩ, and the median absolute deviation was 0.036 mΩ. The dynamic boundary of the electrochemical polarization impedance of the sixth battery cluster was determined to be 0.528 mΩ according to equation (3).

[0105] The normal cooling medium flow rate of the liquid cooling branch corresponding to the sixth battery cluster is 6.5 L / min, the full-scale range of the flow sensor is 12 L / min, and the measurement error does not exceed 1% of the full-scale range. According to the pre-commissioning flow-temperature rise test of the liquid cooling branch, when the flow rate is lower than 80% of the rated flow rate for 30 seconds, the temperature rise rate of the representative cells of the battery cluster begins to increase significantly. Therefore, 5.2 L / min is determined as the threshold for the decrease in cooling capacity of this liquid cooling branch, and the threshold value is 80% of the normal flow rate of 6.5 L / min.

[0106] After 18 minutes of continuous charging in the energy storage compartment, the actual flow rate of the liquid cooling branch corresponding to the sixth battery cluster decreased from 6.5 L / min to 4.8 L / min, and remained below 5.2 L / min for 45 seconds. Simultaneously, the inlet temperature of the cooling medium for the sixth battery cluster was 26.5℃, and the outlet temperature increased from 29.1℃ to 31.8℃, representing an increase in the cell temperature from 37.4℃ to 40.1℃.

[0107] According to equation (2), the equivalent thermal resistance of the sixth battery cluster increased from 0.0068 K / W during normal operation to 0.0096 K / W, an increase of 41.18%. When the change in equivalent thermal resistance exceeds 20% of the normal baseline value, the system judges it as a significant decrease in heat exchange capacity. The 20% threshold is determined based on the cooling branch blockage test before commissioning: when the increase in equivalent thermal resistance does not exceed 15%, it can be restored by conventional flow regulation; when the increase reaches 20%, the continuous power boundary begins to decline, so 20% is used as the judgment threshold for abnormal cooling capacity.

[0108] During the same operating phase, the electrochemical polarization impedance of the sixth battery cluster increased from 0.42 mΩ to 0.57 mΩ, exceeding the dynamic boundary of 0.528 mΩ, and remained above the dynamic boundary for three consecutive sampling cycles. The contact impedance of the sixth battery cluster connectors was 0.19 mΩ, lower than its dynamic boundary of 0.27 mΩ, and the temperature rise rate of each connector did not exceed the temperature rise rate of the adjacent cells by more than 0.10 K / min. Therefore, the parameter decoupling module determined that the current anomaly was mainly caused by the accumulation of electrochemical polarization and the decrease in the heat transfer capacity of the liquid cooling branch, rather than by abnormal connector contact.

[0109] The energy envelope module regenerates a time-power safety-adjustable energy envelope based on the current cell temperature, electrochemical polarization impedance, equivalent thermal resistance, and remaining cooling capacity of the cooling branch of the sixth battery cluster. During the scheduling period of the next 300 seconds, the continuous charging power of the sixth battery cluster is allowed to decrease from 90kW to 54kW; during the scheduling period of the next 600 seconds, the continuous charging power is allowed to decrease to 42kW.

[0110] The current cell temperature of the sixth battery cluster is 40.1℃, only 1.9K away from the active limit temperature of 42℃. Based on the current temperature rise rate of 0.23K / min, without power adjustment, the cell temperature will reach 42℃ in approximately 496 seconds. Therefore, the collaborative control module identifies the battery thermal node corresponding to the sixth battery cluster as a risk source node.

[0111] The dynamic directed heat propagation map shows that there is a directed edge between the sixth battery cluster and the spatial thermal node between the sixth and seventh battery clusters, with a propagation delay of 76 s and a propagation confidence level of 0.89; there is a directed edge between the spatial thermal node and the seventh battery cluster, with a propagation delay of 105 s and a propagation confidence level of 0.85; the propagation delay from the seventh battery cluster to its corresponding airflow thermal node is 48 s and the propagation confidence level is 0.83. The propagation confidence levels of all the above directed edges are not lower than 0.80, and therefore they are included in the path search range. The estimated time for heat to propagate from the sixth battery cluster to the seventh battery cluster is 181 s, and the estimated time for further propagation to the corresponding airflow thermal node is 229 s.

[0112] Since the expected time for heat to reach the seventh battery cluster is 181s, which is greater than the rapid compression threshold of 120s, but the safe adjustable energy envelope of the sixth battery cluster has been significantly reduced, the collaborative control module first reduces the charging power of the sixth battery cluster from 90kW to 50kW, and reduces the charging power of the seventh battery cluster from 90kW to 75kW, releasing a total of 55kW of power to be transferred.

[0113] After screening the battery clusters outside the thermal risk propagation cone, the first, second, and third battery clusters met the power acceptance conditions. Specifically, the cell temperatures of the first, second, and third battery clusters were 34.8℃, 35.1℃, and 35.6℃, respectively, and the contact impedances of the connectors were 0.16mΩ, 0.17mΩ, and 0.18mΩ, respectively, all below 90% of their corresponding dynamic boundaries. The safe adjustable energy margins of the first, second, and third battery clusters over the next 300 seconds were 6.1kWh, 5.8kWh, and 4.9kWh, respectively, corresponding to remaining cooling capacities of 1.52kW, 1.46kW, and 1.31kW in the liquid cooling branch, all exceeding 1.2 times the expected additional power loss from the accepted power.

[0114] According to the order of decreasing structural distance from the receiving battery cluster to the sixth battery cluster, the first battery cluster receives 25kW, the second battery cluster receives 20kW, and the third battery cluster receives 10kW. After power transfer, the charging power of the first, second, and third battery clusters are 115kW, 110kW, and 100kW, respectively, none of which exceed their respective time-power safe adjustable energy envelopes. According to equation (4), after power transfer, the newly added heat-generating center of gravity moves 2.04m in the opposite direction to the main heat propagation direction from the sixth battery cluster to the seventh battery cluster.

[0115] The collaborative control module further screens cooling blocking nodes along the propagation path from the sixth to the seventh battery cluster. The spatial thermal node between the sixth and seventh battery clusters is controlled by both the second liquid-cooled branch and the third air duct region, covering the main propagation path from the risk source node to the seventh battery cluster, and is therefore identified as the target blocking node. The estimated time for heat to reach the target blocking node is 76 seconds, less than the 90-second lead time for complete cooling regulation. Therefore, the system does not perform significant adjustments to the cooling unit inlet temperature, but prioritizes faster flow rate and fan regulation.

[0116] The system increases the opening of the electric regulating valve of the liquid cooling branch of the sixth battery cluster from 52% to 70%, restoring the cooling medium flow rate from 4.8L / min to 5.9L / min; increases the flow rate of the liquid cooling branch of the seventh battery cluster from 6.4L / min to 7.5L / min; increases the fan speed of the third air duct area from 50% to 70% of the rated speed; and simultaneously switches the air guide valve to direct the airflow from the seventh battery cluster side to the sixth battery cluster side.

[0117] After 55 seconds of cooling control execution, the temperature of the target blocking node near the seventh battery cluster was 36.2℃, and the temperature near the sixth battery cluster was 37.0℃. A reverse temperature difference of 0.8K was formed along the main direction of heat propagation at the target blocking node. This reverse temperature difference lasted for more than two temperature sampling cycles, indicating that the cooling blocking front had been formed.

[0118] During the first 300-second monitoring cycle after power scheduling and cooling control were implemented, the highest temperature of the representative cell in the sixth battery cluster reached 40.5℃, which did not exceed the active limit temperature of 42℃. The temperature rise rate of the sixth battery cluster decreased from 0.23K / min to 0.06K / min; the temperature rise rate of the seventh battery cluster decreased from 0.14K / min to 0.04K / min. The electrochemical polarization impedance of the sixth battery cluster decreased from 0.57mΩ to 0.46mΩ within 420 seconds after the power reduction, which is below the dynamic boundary of 0.528mΩ.

[0119] After the flow rate of the liquid cooling branch corresponding to the sixth battery cluster recovered to 5.9 L / min, its cooling medium inlet temperature was 26.2℃ and outlet temperature was 29.0℃. Recalculated, the equivalent thermal resistance of the sixth battery cluster decreased to 0.0073 K / W, an increase of 7.35% compared to the normal operating baseline of 0.0068 K / W, but below the 20% threshold for judging abnormal cooling capacity. During actual operation, the temperature rise characteristic point of the seventh battery cluster did not form within the expected 181 s, indicating that power transfer and cooling blockage had weakened the propagation path.

[0120] When the electrochemical polarization impedance of the sixth battery cluster remains below its dynamic boundary for 60 seconds, its equivalent thermal resistance remains below 1.2 times the normal baseline value for 180 seconds, and the rate of temperature rise representing the battery cell does not exceed 0.05 K / min for 180 seconds, the system determines that the risk state has been resolved. After the risk state is resolved, the system gradually increases the charging power of the sixth and seventh battery clusters in a recovery step of no more than 10 kW per power control cycle, while simultaneously reducing the power received by the first, second, and third battery clusters. After four power control cycles, the charging power of the sixth battery cluster recovers to 80 kW, and the charging power of the seventh battery cluster recovers to 85 kW.

[0121] This embodiment demonstrates that, under conditions of high ambient temperature and decreased heat transfer capacity of cooling branches, the present invention can distinguish between electrochemical polarization accumulation, abnormal contact of connectors and decreased heat transfer capacity based on the inherent carrier response of the PCS, and implement coordinated control through time-power safe adjustable energy envelope, thermal risk propagation cone, reverse heating center of gravity scheduling and cooling blocking front.

[0122] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. An intelligent energy management system for an energy storage cabin, characterized in that, The system includes: The synchronous acquisition module is used to acquire the DC side voltage, DC side current and carrier phase of the energy storage converter PCS, and to acquire the terminal voltage, branch current, cell temperature, connector temperature, cooling medium temperature, cooling medium flow rate and cabin zone temperature of each battery cluster, and to establish a carrier period data frame according to a unified clock. The carrier response identification module is used to perform phase alignment and period statistics on continuous carrier periodic data frames based on the carrier phase, and extract the carrier fundamental frequency component, carrier sideband component, voltage ripple amplitude, current ripple amplitude and ripple phase difference to form the battery cluster electrical response characteristics generated by the inherent switching ripple excitation of the PCS. The parameter decoupling module is used to decompose the equivalent impedance of the battery cluster into the ohmic impedance of the battery cell, the electrochemical polarization impedance and the contact impedance of the connector based on the electrical response characteristics of the battery cluster and the temperature rise location, temperature rise rate and response hysteresis of the battery cell, connector and cooling medium, and to determine the equivalent thermal resistance. The energy envelope module is used to determine the peak power boundary, continuous power boundary, polarization accumulation boundary and thermal accumulation boundary for different durations based on each decoupling parameter, and to generate a time-power safe adjustable energy envelope from the intersection of each boundary. The heat propagation modeling module is used to construct a dynamic directional heat propagation map based on the temperature change sequence, cooling medium flow direction, airflow direction, and structural connection relationship, with battery clusters, cooling branches, air duct partitions, and cabin space partitions as thermal nodes. The collaborative control module is used to identify risk source nodes when the node state exceeds the dynamic boundary, generate a thermal risk propagation cone containing downstream nodes, propagation paths and expected arrival times along the dynamic directional thermal propagation map, compress the power of the battery clusters inside the thermal risk propagation cone according to the safe adjustable energy envelope and transfer it to the battery clusters outside the thermal risk propagation cone, and adjust the cooling medium flow rate, cooling medium inlet temperature, fan speed or airflow direction on the propagation path to form a cooling blocking front before the heat arrives; The closed-loop correction module is used to update the dynamic directional heat propagation map, the safe and adjustable energy envelope, and the power-cooling distribution results based on the actual propagation path, actual propagation delay, and node temperature rise rate after control.

2. The intelligent energy management system for the energy storage compartment according to claim 1, characterized in that: The synchronous acquisition module uses the start time of the PCS carrier cycle as the phase zero point and segments the voltage and current sample values ​​according to the carrier cycle. The carrier response identification module performs phase shifting on signal segments for no less than 32 consecutive carrier cycles, so that the phase zeros of each signal segment coincide. Then, it performs periodic averaging on the phase-aligned signal segments and calculates the complex voltage and complex current components at the carrier fundamental frequency and its adjacent sideband frequencies. The complex impedance response of the corresponding battery cluster is formed by the amplitude ratio and phase difference of the complex voltage and complex current components.

3. The intelligent energy management system for the energy storage compartment according to claim 1, characterized in that: The parameter decoupling module uses the instantaneous resistance corresponding to the in-phase components of the ripple voltage and ripple current as a candidate ohmic impedance. When the temperature rise rate of the connector is greater than the temperature rise rate of the adjacent cells in the same battery cluster, and the time difference between the start time of the temperature rise of the connector and the start time of the instantaneous resistance rise is less than one temperature sampling period, the corresponding change is determined as the connector contact impedance increment. The instantaneous resistance after deducting the contact impedance increment of the connector is determined as the cell ohmic impedance. The electrochemical polarization impedance is determined based on the attenuation relationship between the ripple phase difference and the carrier sideband amplitude with frequency. The equivalent thermal resistance is determined based on the ratio of the battery cluster power loss to the steady-state temperature difference between the cell temperature and the inlet temperature of the cooling medium.

4. The intelligent energy management system for the energy storage compartment according to claim 2, characterized in that: The energy envelope module determines the peak power boundary that satisfies the upper limit of the battery cluster terminal voltage, the lower limit of the terminal voltage, and the allowable temperature of the connector based on the ohmic impedance of the battery cell and the contact impedance of the connector. The continuous power boundary and heat accumulation boundary are determined based on the equivalent thermal resistance, current cell temperature, allowable cell temperature, and available cooling power. The polarization accumulation boundary is determined based on the electrochemical polarization impedance and the polarization decay time constant during the shutdown recovery phase. In the time-power coordinate system, the region that is simultaneously located within the peak power boundary, the sustained power boundary, the thermal accumulation boundary, and the polarization accumulation boundary is defined as the safe adjustable energy region, and the outer boundary of the safe adjustable energy region is defined as the time-power safe adjustable energy envelope.

5. The intelligent energy management system for the energy storage compartment according to claim 3, characterized in that: The heat propagation modeling module establishes a set of thermal nodes according to the battery cluster installation location, cooling branch coverage area, air duct coverage area, and cabin partition location; When the temperature characteristic point of the first hot node appears earlier than that of the second hot node, and there is a structural heat transfer channel, cooling medium flow channel or airflow channel between the first hot node and the second hot node, a directed edge from the first hot node to the second hot node is established. The correlation coefficient of the temperature change sequences of two thermal nodes is used as the thermal coupling strength, the time difference between two temperature feature points is used as the propagation delay, and the proportion of the number of windows with consistent directed edge directions within a continuous monitoring window to the total number of monitoring windows is used as the propagation confidence.

6. The intelligent energy management system for the energy storage compartment according to claim 4, characterized in that: The collaborative control module establishes a normal operation reference window for each thermal node, and uses the sum of the median temperature rise rate within the reference window and three times the median absolute deviation to determine the dynamic boundary of the temperature rise rate. The same method is used to determine the dynamic boundary of the connector contact impedance and the dynamic boundary of the electrochemical polarization impedance. When the temperature rise rate, connector contact impedance or electrochemical polarization impedance of any thermal node exceeds the corresponding dynamic boundary, the thermal node is marked as a risk source node. A path search is performed from the risk source node along directed edges with a propagation confidence of not less than 0.

8. The searched directed edges form a heat propagation path, and the cumulative value of the propagation delay of each directed edge in the same heat propagation path is determined as the estimated time for heat to reach the downstream heat node.

7. The intelligent energy management system for the energy storage compartment according to claim 5, characterized in that: The collaborative control module determines the power compression amount based on the expected arrival time and safe adjustable energy margin of each battery cluster within the thermal risk propagation cone, and selects battery clusters outside the thermal risk propagation cone whose connector contact impedance does not exceed the corresponding dynamic boundary, whose remaining safe adjustable energy is greater than the energy to be received, and whose remaining cooling capacity of the cooling branch is greater than the new heat load. The compressed power is allocated according to the structural distance from the receiving battery cluster to the risk source node, from largest to smallest. The direction from the risk source node to the downstream propagation path with the largest cumulative thermal coupling strength is determined as the main direction of thermal propagation. The new heat-generating center of gravity is calculated based on the spatial coordinates of each receiving battery cluster and the new loss power. The receiving power of each receiving battery cluster is adjusted until the projection of the new heat-generating center of gravity on the main direction of thermal propagation is less than the projection of the heat-generating center of gravity on the main direction of thermal propagation before the power adjustment.

8. The intelligent energy management system for the energy storage compartment according to claim 6, characterized in that: The collaborative control module identifies hot nodes with adjustable liquid cooling branches or adjustable air ducts as candidate blocking nodes in the propagation path from the risk source node to the downstream hot node. The target blocking node is selected based on the estimated arrival time of the candidate blocking node, the remaining cooling capacity, and the number of propagation paths covered by the candidate blocking node. Before the expected arrival time of the target blocking node, increase the cooling medium flow rate of the corresponding liquid cooling branch, reduce the cooling medium inlet temperature, increase the corresponding fan speed, or switch the position of the air guide valve to form a temperature distribution that decreases along the main direction of heat propagation between the target blocking node and the risk source node. The temperature distribution constitutes the cooling blocking front.

9. The intelligent energy management system for the energy storage compartment according to claim 7, characterized in that: The closed-loop correction module uses the difference between the actual temperature feature point occurrence time and the expected arrival time to correct the propagation delay of the corresponding directed edge, uses the ratio of the temperature rise amplitude of adjacent hot nodes after control to correct the thermal coupling strength, and uses the ratio of the number of monitoring windows whose actual propagation direction is consistent with the direction of the directed edge to the total number of monitoring windows to correct the propagation confidence. Based on the ripple response and temperature rise response after power transfer, the ohmic impedance of the battery cell, the electrochemical polarization impedance, the contact impedance of the connector, and the equivalent thermal resistance are redefined. Based on the redefined decoupling parameters, the time-power safe adjustable energy envelope and the power-cooling distribution results for the next control cycle are generated.

10. A method for intelligent energy control of an energy storage compartment, characterized in that, The method, applied to the intelligent energy management system for energy storage compartments according to any one of claims 1-9, comprises: The system acquires the DC-side voltage, DC-side current, and carrier phase of the PCS, as well as the terminal voltage, branch current, cell temperature, connector temperature, cooling medium inlet temperature, cooling medium outlet temperature, cooling medium flow rate, and cabin zone temperature of each battery cluster, and forms a carrier period data frame according to a unified clock. Based on the carrier phase, phase alignment and period statistics are performed on continuous carrier periodic data frames. The carrier fundamental frequency component, carrier sideband component, voltage ripple amplitude, current ripple amplitude and ripple phase difference are extracted to obtain the battery cluster electrical response characteristics generated by the inherent switching ripple excitation of the PCS. By combining the temperature rise location, temperature rise rate and response hysteresis of the cell, connector and cooling medium, the equivalent impedance of the battery cluster is decomposed into cell ohmic impedance, electrochemical polarization impedance and connector contact impedance, and the equivalent thermal resistance is determined. Based on each decoupling parameter, the peak power boundary, continuous power boundary, polarization accumulation boundary, and thermal accumulation boundary are determined to generate a time-power safety-adjustable energy envelope. Using battery clusters, cooling branches, air duct partitions, and cabin space partitions as thermal nodes, a dynamic directional heat propagation map is constructed based on the temperature change sequence of the thermal nodes, the flow direction of the cooling medium, the airflow direction, and the structural connection relationship. When the state of a hot node exceeds the dynamic boundary, the risk source node is determined, and the downstream hot node, propagation path and expected arrival time are determined along the dynamic directional heat propagation graph, generating a heat risk propagation cone; The power of the battery cluster inside the thermal risk propagation cone is transferred to the battery cluster outside the thermal risk propagation cone while satisfying the constraints of safe adjustable energy margin and remaining cooling capacity, so that the newly added heat center moves in the opposite direction of the main direction of heat propagation. Select cooling blockage nodes along the heat propagation path, and adjust the cooling medium flow rate, cooling medium inlet temperature, fan speed, or air guide valve position before the heat is expected to arrive, to form a temperature distribution that decreases along the main direction of heat propagation. Based on the actual propagation path, actual propagation delay, and temperature rise rate at hot nodes, update the dynamic directional heat propagation map, the time-power safe adjustable energy envelope, and the power-cooling distribution results.

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