Battery intelligent charging scheduling and dynamic power management method and system for battery swap station

Abstract

The present application relates to the technical field of charging control, and particularly relates to a battery intelligent charging scheduling and dynamic power management method and system for a battery swap station, comprising a data acquisition module, a charging scheduling decision module, a charging control execution module and a temperature control cooperation module, the data acquisition module acquires the SOC, charging state, voltage, temperature and BMS charging permission flag of the battery; the charging scheduling decision module performs multi-dimensional safety inspection on the battery, calculates three-level dynamic weight values and sorts them, and selects a target charging battery according to a limit mode; the temperature control cooperation module calculates temperature control power consumption and feeds it back to the decision module, and obtains available charging power by deducting the temperature control power consumption and safety redundant power from the total power of the cabinet machine; the charging control execution module turns on the charger for the target battery and sets four-stage curve charging parameters, and adjusts the charging stage in real time to protect the battery. The present application can realize the cooperative management of charging and temperature control, and improve the battery turnover efficiency and charging safety.

Description

Technical Field

[0001] This invention relates to the field of charging control technology, and in particular to a method and system for intelligent charging scheduling and dynamic power management of batteries in battery swapping stations. Background Technology

[0002] With the rapid popularization of new energy vehicles, battery swapping stations, as important infrastructure, play a crucial role in the rapid replenishment of batteries. Battery swapping stations achieve rapid battery replacement through battery exchange cabinets, significantly shortening the refueling time of electric vehicles. Battery exchange cabinets typically contain multiple battery compartments, each capable of holding one battery to be charged or replaceable. Due to limitations in the total power of the cabinet and the hardware of the charger, it is usually not possible to charge all batteries at full power simultaneously.

[0003] Existing technologies have made some progress in battery charging management at battery swapping stations, but they mainly focus on power allocation for charging pile clusters, identification of concurrent charging of multiple battery types, and macro-level charging demand prediction based on machine learning. Regarding power allocation for charging pile clusters, existing solutions introduce mechanisms such as remaining power screening, access time sorting, and power level matching to achieve power scheduling in multi-terminal parallel charging scenarios. However, these solutions only address direct charging scenarios for electric vehicles and do not address the parallel charging scheduling of multiple battery compartments within the battery swapping station cabinet. Furthermore, the scheduling is primarily based on access time and power level, without considering the coupled effects of multiple dimensions such as battery state of charge, current charging status, and compartment location.

[0004] Regarding concurrent charging of multiple battery types, existing solutions identify battery types and match corresponding charging strategies to achieve concurrent charging control of multiple battery types by charging equipment. However, the focus is on battery type identification and strategy matching, without addressing charging priority scheduling between multiple battery compartments, and without considering dynamic power budget allocation under the total power limit of the battery swapping station. As for intelligent charging scheduling algorithms, existing solutions use deep learning for macro-level charging demand prediction and solve for the optimal allocation scheme through mixed integer programming. However, the algorithm has high complexity, relies on a large amount of historical data, and does not address real-time charging scheduling within the battery swapping station's battery compartments. Summary of the Invention

[0005] The inventors discovered through research that existing technologies have significant gaps in the intelligent charging scheduling of multi-compartment batteries within battery swapping station cabinets, primarily due to the lack of a coordinated management mechanism for charging and temperature control. Specifically, battery swapping station cabinets need to simultaneously perform battery charging and temperature control during operation; these two functional systems are interdependent and tightly coupled. On one hand, the charging process generates heat, causing the cabinet temperature to rise, requiring temperature control equipment for heat dissipation; on the other hand, in low-temperature environments, heating equipment is needed to raise the cabinet temperature to ensure that the batteries are charged within a suitable temperature range.

[0006] The purpose of this invention is to provide a method and system for intelligent charging scheduling and dynamic power management of batteries in battery swapping stations. It achieves intelligent sorting of charging priorities through a multi-dimensional dynamic weight scheduling algorithm, incorporates temperature control power consumption into the power budget to achieve adaptive power allocation, adopts a four-stage curve charging strategy to dynamically adjust charging parameters, and achieves coordinated control of charging scheduling and temperature control management within the same scheduling cycle, thereby improving the battery turnover efficiency and charging safety of battery swapping stations.

[0007] One aspect of the present invention provides a method for intelligent charging scheduling and dynamic power management of batteries in battery swapping stations, comprising: Collect real-time status data of batteries in each battery compartment within the battery swapping station. The real-time status data includes at least the battery's state of charge (SOC), charging status, voltage, temperature, and the charging permission flag of the battery management system (BMS). Perform multi-dimensional safety checks on the battery to select a set of rechargeable batteries that meet the charging conditions; Based on the battery model and the corresponding charging configuration, calculate the charging parameters of each rechargeable battery. For each battery in the rechargeable battery set, a multi-dimensional dynamic weight value is calculated based on its SOC, current charging state and compartment number, and the batteries are sorted from high to low according to the weight value. The charger is turned on for the target rechargeable battery selected from the sorted set of rechargeable batteries according to the preset charging limit mode, and the charging parameters are set. The charger is turned off for the unselected batteries whose chargers are turned on. Within the same scheduling cycle, the cabinet temperature data is collected and the temperature control power consumption is calculated. After deducting the temperature control power consumption and the preset safety redundancy power from the total power of the cabinet, the available charging power is obtained. The available charging power is used to determine the charging limitation mode.

[0008] In some embodiments, the multi-dimensional security check includes at least: Returns "Not Allowed" when the compartment is disabled; returns "Not Allowed" when the compartment door is open; returns "Not Allowed" when there are no batteries in the compartment; returns "Not Allowed" when the battery BMS does not allow charging; returns "Not Allowed" when the charger is in an abnormal state. Returns "Not Allowed" when a charger fault alarm is present; returns "Not Allowed" when the battery is fully charged; returns "Not Allowed" when the SOC exceeds the maximum value threshold; returns "Not Allowed" when the voltage exceeds the maximum value threshold. Returns to no operation when the battery is in the recharge range and not being charged; returns to no operation when the battery is in the voltage recharge range and not being charged; returns to no operation when the battery is within the protection period.

[0009] In some embodiments, permission is returned when all hard conditions are not met and no soft conditions are triggered. The hard conditions include the compartment being disabled, the compartment door being open, the presence of batteries in the compartment, the battery BMS charging being allowed, the charger being in an abnormal state, the charger being faulty and alarming, the battery being fully charged, the maximum SOC value, and the maximum voltage value. The soft conditions include the recharge interval without charging, the voltage recharge interval without charging, and the protection period.

[0010] In some embodiments, the calculation of the multi-dimensional dynamic weight value adopts a three-level coding structure. The total weight is equal to the stage weight multiplied by the first base, plus the SOC weight multiplied by the second base, plus the warehouse number weight. The stage weight determines the priority level based on the current charging state and SOC range of the battery. The SOC weight further distinguishes the SOC differences of the battery within the same stage weight. The warehouse number weight is sorted by warehouse number within the same stage weight and SOC weight. The first base is greater than the sum of the product of the maximum SOC weight and the second base plus the maximum warehouse number weight. The second base is greater than the maximum warehouse number weight.

[0011] In some embodiments, the priority level of the stage weights is determined according to the following rules: When the battery is charging and the SOC is less than or equal to the first threshold, the stage weight is the highest level. When the battery is charging and the first threshold is less than the SOC and the SOC is less than or equal to the second threshold, the stage weight is the second highest level. When SOC is greater than the second threshold, the stage weight is the third level; When the battery is not charging and the first threshold is less than the state of charge (SOC) and the SOC is less than or equal to the second threshold, the stage weight is the lowest level.

[0012] In some embodiments, the charging limitation mode includes a quantity limitation mode and a power limitation mode; wherein, the quantity limitation mode configures the maximum number of batteries that can be charged simultaneously, selects target charging batteries from high to low according to the sorting results, and stops charging the remaining batteries after the maximum number is reached. The power-limited mode dynamically calculates the available charging power as equal to the total power of the cabinet minus the temperature control power consumption minus the safety redundancy power. The charging power of the sorted batteries is calculated sequentially. If the available charging power is greater than or equal to the sum of the battery power and the safety margin of a single battery, charging is allowed. The available charging power is then reduced by the battery power. Otherwise, charging is not allowed.

[0013] It should be noted that when the available charging power becomes negative or insufficient to support the next battery after deducting the power of a certain battery, the addition of a new battery will be stopped immediately, and the already charged batteries will continue to be charged.

[0014] In some embodiments, the battery power calculation formula is as follows: Battery power = min(charging voltage × charging current, charger maximum power).

[0015] In some embodiments, the calculation of the charging parameters adopts a four-stage curve charging strategy, which divides the charging process into a pre-charging stage, a fast charging stage, a current reduction stage, and a trickle charging stage based on the SOC and charging time. The pre-charge phase is triggered when the charging time is less than or equal to the preset protection time or the SOC is less than the third threshold. At this time, the charging current is the smaller value between the preset pre-charge current and the configured current. The fast charging phase is triggered when the SOC is less than the fourth threshold and the pre-charging phase conditions are not met. At this time, the charging current is the configuration current. The trigger condition for the current reduction phase is that the fourth threshold is less than or equal to the SOC and the SOC is less than or equal to the fifth threshold. At this time, the charging current is the smaller value between the preset current reduction current and the configured current. The trigger condition for the trickle phase is that the SOC is greater than the fifth threshold. At this time, the charging current is the smaller value between the preset trickle current and the configured current. Wherein, the fourth threshold is greater than the third threshold, and the fifth threshold is greater than the fourth threshold.

[0016] In some embodiments, for batteries that are already in a charging state and using a curve charging mode, the charging parameters are recalculated periodically, and the voltage and current settings of the charger are updated in real time when a change in SOC is detected that causes a stage switch.

[0017] Another aspect of the present invention provides a smart charging scheduling and dynamic power management system for batteries in battery swapping stations, including a data acquisition module, a charging scheduling decision module, a charging control execution module, and a temperature control coordination module. The data acquisition module is used to collect site-level status data, cabinet-level status data, battery compartment-level status data, and battery status data within the battery swapping station. The charging scheduling decision module is used to perform safety checks, calculate charging parameters, calculate and sort multi-dimensional dynamic weights based on the status data, and select target charging batteries according to the charging restriction mode. The charging control execution module is used to turn on the charger for the target rechargeable battery and set the charging parameters, and to turn off the charger for unselected batteries that have already been turned on. The temperature control coordination module is used to collect cabinet temperature data and calculate temperature control power consumption within the same scheduling cycle, and feed the temperature control power consumption back to the charging scheduling decision module to participate in the charging power budget calculation. The charging scheduling decision module includes a site safety inspection unit, a single-compartment charging inspection unit, a charging parameter calculation unit, a weight ranking calculation unit, and a power or quantity restriction unit. The site safety inspection unit is used to determine whether the entire station is allowed to charge based on the site status acquisition results. The single-compartment charging inspection unit is used to perform multi-dimensional safety inspections on a single battery compartment. The charging parameter calculation unit is used to match the corresponding charging configuration according to the battery model, and to try three modes in order of priority: BMS guided charging, curve charging and direct charging to calculate the charging voltage and current. The weighted sorting calculation unit is used to calculate multi-dimensional weight values ​​for rechargeable batteries that have passed the safety inspection and sort them from high to low weight. The power or quantity limiting unit is used to select the final set of batteries that are allowed to be charged from the sorted battery list according to the configuration mode. The temperature control coordination module includes a temperature monitoring unit and a heat dissipation or heating control unit. The temperature monitoring unit is used to monitor the temperature of the cabinet core board and the temperature inside each compartment. The heat dissipation or heating control unit is used to control the opening and closing of the whole cabinet cooling fan, the single compartment cooling fan and the whole cabinet PTC heating according to the comparison result of temperature and threshold. Heating and heat dissipation adopt a mutual exclusion strategy.

[0018] It should be noted that the core board temperature sensor is located in the center of the battery swapping cabinet control board, and one compartment temperature sensor is located on the right side of the battery compartment of the battery swapping cabinet. Each temperature sensor is of the type of NTC thermistor and the model is MF52A103F3950 (A1).

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. By comprehensively considering the three-level weighted coding of battery SOC, current charging status and battery compartment location, a multi-dimensional dynamic priority sorting is achieved. In particular, batteries that are charging and have low power are set as the highest priority, which avoids charging interruptions caused by improper scheduling strategies, shortens the overall charging cycle, and improves the battery turnover efficiency of the battery swapping station. 2. The power consumption of temperature control and the safety redundancy power are deducted from the total power of the cabinet before the charging power is allocated, so as to avoid the actual overload risk caused by the power occupied by temperature control equipment, actuator start-up fluctuations or sampling errors. At the same time, it supports flexible switching between two modes of quantity limit and power limit to adapt to different scenario needs. 3. The four-stage curve charging strategy dynamically adjusts the current based on the SOC and charging time. When the battery is low, a small current is used for pre-charging to protect the battery. When the battery is medium to high, a full current is used for fast charging. When the battery is high, the current is gradually reduced to avoid overcharging and overheating. Compared with the direct charging mode with fixed parameters, it significantly extends battery life and reduces safety hazards. 4. Charging scheduling and temperature control management are executed within the same scheduling cycle. Temperature control power consumption is fed back to the charging power budget in real time. High temperature alarm directly triggers the entire station to stop charging, realizing closed-loop collaborative management of charging and temperature control, avoiding information silos and response delays caused by the independent operation of two systems in traditional solutions. 5. The charging protection buffer mechanism effectively prevents frequent retries after the charger fails to start, as well as frequent switching operations caused by status fluctuations, thus extending the service life of the charger hardware. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a diagram illustrating the architecture of the intelligent charging scheduling and dynamic power management system for battery swapping stations according to the present invention. Figure 2 This is a logical diagram of the main process of cabinet charging scheduling in this invention. Detailed Implementation

[0022] The following will be based on embodiments of the present invention. Figures 1-2 The technical solutions in the embodiments of the present invention will be clearly and completely described together. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0023] To better understand this invention, some of the content is explained below: 1. Current charging status: refers to the core status of the charger, including idle, starting up, charging, fully charged, abnormal, etc. 2. SOC: This is the percentage of battery charge reported by the battery management system (BMS). 3. Recharge interval: This is a hysteresis interval to prevent frequent start-stop after charging has just stopped. When using the SOC strategy, the default is 97%-100% as the waiting interval for recharge. The battery will not restart when it is not charging and the SOC is in this interval. Charging will only be allowed to resume when the SOC is below the lower limit.

[0024] Example 1 This invention provides a method and system for intelligent charging scheduling and dynamic power management of batteries in battery swapping stations. The system is applied to the charging management scenario of battery swapping cabinets in battery swapping stations.

[0025] like Figure 1 The system in this embodiment adopts a four-layer architecture design, including a data acquisition layer, a temperature control coordination layer, a charging scheduling decision layer, and a charging control execution layer. The data acquisition layer includes cabinet status acquisition, warehouse-level status acquisition, site status acquisition, and battery status acquisition. The temperature control coordination layer includes temperature monitoring and heat dissipation / heating control. The charging scheduling decision layer includes site safety checks, single-warehouse charging checks, charging parameter calculation, weighted ranking calculation, and power or quantity limits. The charging control execution layer includes three modules: charger on / off control, charger off / off control, and dynamic parameter adjustment.

[0026] The data acquisition layer includes several key components: Cabinet status acquisition (collecting data on the core board status, total power configuration, and heating power configuration of individual cabinets); Warehouse status acquisition (collecting data on the door status, disabled status, charger operating status, and fault alarm status of each battery compartment); Site status acquisition (collecting data on the overall operating status of the battery swapping station, including site-level parameters such as temperature alarms, voltage anomalies, and reverse power supply status); and Battery status acquisition (collecting data on the SOC, voltage, temperature, and BMS charging permission flags of each battery in each compartment). All data collected by the data acquisition layer provides real-time data input to the charging scheduling decision layer.

[0027] The site safety check in the charging scheduling decision layer determines whether charging is allowed at the entire site based on the site status data. When a high-temperature alarm or reverse power supply is detected, a command to prohibit charging at the entire site is directly output to the charging control execution layer. Single-compartment charging checks perform multi-dimensional safety checks on each battery compartment, including whether the compartment is disabled, whether the compartment door is open, whether there are batteries inside, whether the battery BMS allows charging, whether the charger status is abnormal, whether there are fault alarms, whether the battery is fully charged, whether the SOC and voltage exceed thresholds, whether it is in the recharge range, and whether it is within the protection period. Charging parameter calculation matches the corresponding charging configuration according to the battery model, and attempts three modes—BMS-guided charging, curve charging, and direct charging—in order of priority, calculating the final charging voltage and current. Weighted ranking calculation calculates multi-dimensional weight values ​​for rechargeable batteries that pass the safety check, and sorts them from high to low using a TreeMap. Power or quantity limits select the final set of batteries allowed to charge from the sorted battery list according to the configuration mode. When using the power-limited mode, the available charging power equals the total power of the cabinet minus the temperature control power consumption minus the safety redundancy power.

[0028] The charger activation control in the charging control execution layer invokes hardware services to activate the charger and set charging voltage and current parameters for batteries that are ultimately allowed to charge. The charger deactivation control performs a deactivation operation on batteries that are not allowed to charge; if the charger for that battery is in the activated state, it invokes hardware services to deactivate the charger. Dynamic parameter adjustment periodically recalculates charging parameters for batteries already in a charging state using a curve charging mode. When a change in SOC is detected causing a switching of charging stages, the voltage and current settings of the corresponding charger are updated in real time.

[0029] Temperature monitoring in the temperature control coordination layer is used to monitor the core board temperature of the cabinet and the temperature inside each compartment in real time. Heat dissipation or heating control, based on the comparison between the temperature data collected by the temperature monitoring and preset thresholds, controls the on / off state of the cabinet's cooling fans, individual compartment cooling fans, and the cabinet's PTC heater. Heating and heat dissipation employ a mutual exclusion strategy to avoid conflicts. The temperature control power consumption output by the temperature control coordination layer serves as the input parameter for the power budget calculation of the charging scheduling decision layer. The four layers execute sequentially within the same scheduling cycle, forming a closed-loop control.

[0030] like Figure 2 The main process for cabinet charging scheduling in this embodiment includes the following steps: After the system starts, the core loop check service performs cabinet status scans according to a preset cycle. Each scan first performs site status checks and reverse power supply checks to determine whether all chargers need to be shut down. When a site-level high temperature alarm or reverse power supply status is detected, charging of the entire site is prohibited and all powered chargers are shut down. Then, each battery compartment is traversed to perform a single compartment safety check. Based on the check results, the batteries are divided into three categories: allowed, not allowed, and no operation, and are added to the rechargeable list, non-rechargeable list, or skipped, respectively. After the traversal is completed, the charging parameters, charging weights, and power / quantity limit filters are calculated in sequence. Finally, the non-rechargeable list is shut down and the rechargeable list is opened.

[0031] During the process of performing a single-compartment safety check while traversing each battery compartment, the single-compartment safety check sequentially checks various conditions through a serial multi-condition judgment chain. The detailed judgment logic of the single-compartment safety check includes two categories: hard conditions and soft conditions. Hard conditions include compartment disabled state, compartment door open state, presence of batteries in the compartment, battery BMS charging allowed state, charger abnormal state, charger fault alarm, full charge state, maximum SOC value, and maximum voltage value. Soft conditions include recharge range and not charging, voltage recharge range and not charging, and within the protection period. Returns "Allow" when all hard conditions are not met and no soft conditions are triggered; returns "Disallow" when the compartment is disabled; returns "Disallow" when the compartment door is open; returns "Disallow" when there are no batteries in the compartment; returns "Disallow" when the battery BMS does not allow charging; returns "Disallow" when the charger is in an abnormal state; returns "Disallow" when there is a charger fault alarm; returns "Disallow" when the battery is fully charged; returns "Disallow" when the SOC exceeds the maximum value threshold; returns "Disallow" when the voltage exceeds the maximum value threshold; returns "No Operation" when in the recharge range and the battery is not charging; returns "No Operation" when in the voltage recharge range and the battery is not charging; returns "No Operation" when within the protection period.

[0032] The charging parameter calculation sub-process matches the charging configuration for each rechargeable battery. The calculation first parses the battery model and matches the configuration, then prioritizes and determines the BMS fast charging request, BMS slow charging request, and curve charging mode. When using curve charging mode, it performs tiered judgments based on charging time and State of Charge (SOC). When the charging time is less than or equal to 60 seconds or the SOC is less than 5%, it enters the pre-charging stage, returning a voltage equal to the configured voltage and a current equal to the smaller of 5A and the configured current. When the SOC is less than 95%, it enters the fast charging stage, returning a voltage equal to the configured voltage and a current equal to the configured current. When the SOC is less than or equal to 98%, it enters the current reduction stage, returning a voltage equal to the configured voltage and a current equal to the smaller of 10A and the configured current. When the SOC is greater than 98%, it enters the trickle charging stage, returning a voltage equal to the configured voltage and a current equal to the smaller of 5A and the configured current.

[0033] It is understandable that one of the innovations of this embodiment is the multi-dimensional dynamic weight scheduling algorithm. Furthermore, for each rechargeable battery that passes the safety check, its comprehensive weight value is calculated to determine the charging priority. The weight calculation adopts a three-level coding structure, where the total weight equals the stage weight multiplied by the first base, plus the SOC weight multiplied by the second base, plus the warehouse number weight. In a specific embodiment of this invention, the first base is 10000, and the second base is 100. The stage weight determines the priority level based on the battery's current charging state and SOC range, with a value range of 6 to 9, corresponding to four different priority levels. When the battery is charging and the SOC is less than or equal to the first threshold of 10%, the stage weight is set to 9, i.e., the highest priority; when the battery is charging and the first threshold of 10% is less than the SOC and the SOC is less than or equal to the second threshold of 15%, the stage weight is set to 8, i.e., the second highest priority; when the SOC is greater than the second threshold of 15%, the stage weight is set to 7, i.e., the third level; when the battery is not charging and the first threshold of 10% is less than the SOC and the SOC is less than or equal to the second threshold of 15%, the stage weight is set to 6, i.e., the lowest priority.

[0034] The State of Charge (SOC) weight further differentiates battery SOC differences within the same weighting stage, with a value range normalized to 0 to 99 (the second base number minus one). Within the same weighting stage, when a battery is charging and its SOC is less than or equal to the first threshold, the SOC weight equals 99 minus the SOC value, ensuring that batteries with lower SOCs receive higher weights to prevent interruptions in charging low-charge batteries. When the battery is in other states, the SOC weight equals the smaller value between the SOC value and 99, ensuring that batteries with higher SOCs receive higher weights to be prioritized for replacement. The Warehouse Number weight is sorted by warehouse number within the same weighting stage and SOC weighting stage, with a value range of 0 to 99 (the second base number minus one). Smaller warehouse numbers receive higher warehouse number weights, calculated as 99 minus the warehouse number.

[0035] Since the first base number 10000 is greater than the product of the maximum SOC weight of 99 and the second base number 100 plus the maximum warehouse number weight of 99 (i.e., 10000 is greater than 99 × 100 + 99), and the second base number 100 is greater than the maximum warehouse number weight of 99, the SOC weight and warehouse number weight only take effect within the same stage weight and will not override the stage priority, ensuring the hierarchical priority characteristic of multi-dimensional weight encoding. Through the above three-level encoding, an ordered set of rechargeable batteries is obtained by sorting the weights from high to low using a TreeMap.

[0036] It is understandable that the second innovation of this embodiment is the power and quantity adaptive charging limitation mechanism. This invention supports two charging limitation modes: a quantity-based limitation mode and a power-based limitation mode. In the quantity-based limitation mode, the maximum number of batteries that can be charged simultaneously is manually configured. The system selects target batteries for charging from high to low weight based on the weighted sorting results, and stops charging the remaining batteries once the maximum number is reached. In the power-based limitation mode, the available charging power is automatically calculated. The system dynamically calculates the temperature control power consumption, which equals the heating equipment power consumption plus the total cabinet fan power consumption plus the single-compartment fan power consumption plus the power consumption of other temperature control actuators. The available charging power equals the total cabinet power minus the temperature control power consumption minus the safety redundancy power.

[0037] The charging power of each battery is calculated sequentially after sorting. The power of a single battery is equal to the smaller of the product of the charging voltage and the charging current and the charger's maximum power. If the available charging power is greater than or equal to the sum of the battery's power and the single-cell safety margin, charging is allowed, and the available charging power is subtracted from the battery's power. Otherwise, the battery is not allowed to be added to or remain charged during the current scheduling cycle. This mechanism ensures that even with power consumption by temperature control equipment, fluctuations in fan start-up power, and sampling errors, the charging power will not exceed the cabinet's total power limit.

[0038] It is understandable that the third innovation of this embodiment is the four-stage curve charging strategy. The curve charging mode divides the charging process into four stages based on SOC and charging time: The pre-charge stage, also known as stage one, is triggered when the charging time is less than or equal to the preset protection time of 60 seconds or the SOC is less than 5% of the third threshold. The charging voltage is the configured voltage, and the charging current is the smaller value between the preset pre-charge current of 5A and the configured current. This stage is used to protect low-charge batteries from large current surges.

[0039] The fast charging phase, also known as phase two, is triggered when the SOC is less than 95% of the fourth threshold and the pre-charging phase conditions are not met. The charging voltage and the charging current are the configured voltage and the normal fast charging phase.

[0040] The current reduction stage, also known as stage three, is triggered when the fourth threshold of 95% is less than or equal to the SOC and the SOC is less than or equal to the fifth threshold of 98%. The charging voltage is the configured voltage, and the charging current is the smaller value between the preset current reduction current of 10A and the configured current. This stage is used to reduce the current and reduce heat generation to protect the battery.

[0041] The trickle charge phase, also known as phase four, is triggered when the SOC is greater than the fifth threshold of 98%. The charging voltage is the configured voltage, and the charging current is the smaller value between the preset trickle charge current of 5A and the configured current. This phase is used for trickle charging to avoid overcharging.

[0042] In curve charging mode, even when the charger is on, the system periodically recalculates charging parameters. When a change in SOC causes a stage switch, the system dynamically adjusts the charger's voltage and current settings in real time to achieve dynamic parameter adjustment during the charging process. In a specific embodiment of the invention, the current is configured to be 15A. When the SOC changes from stage two to stage three, the charging current is updated from 15A to min(10A, 15A), which equals 10A. See Table 1 below for details: Table 1. Four-stage curve charging strategy

[0043] Furthermore, it can be understood that the fourth innovation of this embodiment is the charging and temperature control collaborative safety protection mechanism. Within the same scheduling cycle, charging scheduling and temperature control management are executed sequentially and influence each other. The temperature control collaboration layer first calculates the current temperature control power consumption, which includes the power consumption of heating equipment, the power consumption of the entire cabinet fan, the power consumption of a single compartment fan, and the power consumption of other temperature control actuators. This value serves as the power budget input for the charging scheduling decision layer. In the power limit calculation, the charging scheduling decision layer subtracts the temperature control power consumption and safety redundancy power from the total power of the cabinet to obtain the actual available charging power for charging limit judgment. If a high temperature alarm or reverse power supply status is detected during the site safety check, a command to prohibit charging throughout the entire site is directly output to the charging control execution layer, and all chargers are shut down. If an abnormal charger status or fault alarm is detected during a single compartment charging check, charging in that compartment is prohibited.

[0044] Heating and cooling employ a mutual exclusion strategy to avoid conflicts. PTC heating is activated when the temperature is below the heating threshold, and the cooling fan for the entire cabinet or a single compartment is activated when the temperature is above the cooling threshold. The system uses a cache mechanism with an expiration time for charging protection. Each attempt to turn on the charger, whether successful or not, adds the compartment to the protection cache. The preset protection interval is 30 seconds. During the protection interval, the charger operation will not be repeated on the battery compartment to prevent damage to the charger hardware due to frequent on / off operations.

[0045] Example 2 This embodiment describes the complete operation process of the present invention using a specific application scenario.

[0046] The application scenario is a battery swapping station containing a cabinet with 10 battery compartments. The total power configuration of the cabinet is 10000W, and the temperature control power consumption example is 2200W (e.g., 2000W for PTC heating in winter, 200W for fans and other temperature control actuators). The safety redundancy power configuration is 500W, and the maximum power of the charger is 3000W. The configuration allows for simultaneous charging of 3 batteries, i.e., using either a quantity-limited mode or an automatic power-limited mode.

[0047] After the system starts up, the core loop check service performs a cabinet status scan every 10 to 30 seconds. In each scan, first, a site-level check is performed, including temperature alarm and reverse power supply check. If a site-level high temperature alarm or reverse power supply status is detected, charging of the entire site is prohibited and all powered chargers are turned off. If the site status is normal, the subsequent process continues.

[0048] Then, a multi-dimensional safety check is performed on each battery compartment, including the compartment's disabled status, door status, battery presence, BMS permission, charger status, fault alarm, full charge determination, SOC threshold, voltage threshold, recharge range, protection period, and other judgments. Based on the check results, the batteries are divided into three categories: allowed, not allowed, and no operation, and are added to the rechargeable list, non-rechargeable list, or skipped.

[0049] After completing the traversal, for each battery in the rechargeable list, the charging parameters are calculated, its model is parsed, and the charging configuration is matched. The BMS fast charging request, BMS slow charging request, and curve charging mode are tried sequentially to calculate the charging voltage and current. For example, when the battery SOC is 3% and the charging time is 30 seconds, according to the four-stage curve charging strategy, it should enter the pre-charging stage, using the configured voltage and the minimum charging current (5A, configured current).

[0050] The weighted sorting calculation calculates multi-dimensional weight values ​​for all rechargeable batteries. For example, if a battery is currently charging and its SOC is 8%, its stage weight is 9, its SOC weight is 99 minus 8 equals 91, its warehouse number weight is 99 minus its warehouse number, and its total weight is 9 multiplied by 10000 plus 91 multiplied by 100 plus its warehouse number weight. A TreeMap is then used to sort the batteries by weight from highest to lowest to obtain an ordered list.

[0051] Power / quantity limits are used to filter the batteries that are ultimately allowed to be charged based on the configuration mode. When using the quantity limit mode, the first three batteries after sorting are selected as the target charging batteries. When using the power limit mode, for example, with a temperature control power consumption of 2200W and a safety redundancy power of 500W, the available charging power is 10000W - 2200W - 500W = 7300W. Starting from the first battery after sorting, the charging power minus voltage multiplied by current is calculated sequentially, 3000W. When the remaining available charging power is not less than the sum of the battery's power and the single battery's safety margin, the battery is allowed to enter the charging set, and the remaining available charging power is subtracted from the battery's power.

[0052] Finally, the charger shutdown control shuts off the charger for batteries that are not allowed to be charged, while the charger startup control turns on the charger for batteries that are allowed to be charged and sets the charging parameters. For batteries that are already powered on and using curve charging, the parameters are dynamically adjusted to detect changes in their SOC. When the SOC changes from stage two to stage three, the current is updated from the configured value of 15A to min(10A, 15A), which equals 10A.

[0053] Within the same scheduling cycle, the temperature monitoring cabinet temperature is monitored by the temperature control coordination layer. The heat dissipation or heating control controls the opening and closing of the whole cabinet cooling fan, single compartment cooling fan, and whole cabinet PTC heating based on the comparison result of temperature and threshold. The heating power consumption, heat dissipation power consumption, and power consumption of other temperature control actuators are summarized into temperature control power consumption and fed back to the charging scheduling decision layer in real time. This power consumption, along with the safety redundancy power, is deducted from the total power of the cabinet to obtain the available charging power for power limitation judgment.

[0054] Through the above implementation, the present invention achieves significant technical effects: the average battery charging cycle is shortened by about 15% to 20% because the battery is not interrupted during low-power charging but receives the highest priority to continue charging; the cabinet power utilization rate is increased to over 90% because the power budget takes into account temperature control power consumption, avoiding overestimation of available charging power; battery life is extended because automatic current reduction during high SOC stages avoids overcharging damage and overheating risks; and the charger failure rate is reduced because the 30-second protection buffer reduces damage to the charger hardware caused by frequent switching operations.

[0055] Example 3 In other embodiments, the battery swapping station includes multiple cabinets, each of which independently executes the charging scheduling process described above. The cabinets share site-level status data, such as temperature alarms and reverse power supply status. When a cabinet detects a site-level high-temperature alarm, all cabinets simultaneously disable charging and shut down all chargers. Once the site status returns to normal, each cabinet continues to independently execute the charging scheduling process.

[0056] Example 4 In some embodiments, the charging limitation mode supports dynamic switching, allowing administrators to switch between quantity-based and power-based limitation modes according to actual operational needs. When switched to power-based limitation mode, the system automatically obtains real-time temperature and power consumption data from the temperature control coordination layer and recalculates the available charging power without manual intervention. When switched to quantity-based limitation mode, the system filters according to the preset maximum number of batteries that can be charged simultaneously.

[0057] Example 5 In some embodiments, the safety margin of a single battery can be dynamically adjusted according to the battery type and charger status. For newly connected batteries or chargers in abnormal states, the safety margin is appropriately increased to reserve more power margin. For chargers operating stably, the safety margin can be appropriately reduced to improve power utilization.

[0058] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0059] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for intelligent charging scheduling and dynamic power management of batteries in battery swapping stations, characterized in that, include: Collect real-time status data of batteries in each battery compartment within the battery swapping station. The real-time status data includes at least the battery's state of charge (SOC), charging status, voltage, temperature, and the charging permission flag of the battery management system (BMS). Perform multi-dimensional safety checks on the battery to select a set of rechargeable batteries that meet the charging conditions; Based on the battery model and the corresponding charging configuration, calculate the charging parameters of each rechargeable battery. For each battery in the rechargeable battery set, a multi-dimensional dynamic weight value is calculated based on its SOC, current charging state and compartment number, and the batteries are sorted from high to low according to the weight value. The charger is turned on for the target rechargeable battery selected from the sorted set of rechargeable batteries according to the preset charging limit mode, and the charging parameters are set. The charger is turned off for the unselected batteries whose chargers are turned on. Within the same scheduling cycle, the cabinet temperature data is collected and the temperature control power consumption is calculated. After deducting the temperature control power consumption and the preset safety redundancy power from the total power of the cabinet, the available charging power is obtained. The available charging power is used to determine the charging limitation mode.

2. The method according to claim 1, characterized in that, The multi-dimensional security check includes at least: Returns "Not Allowed" when the compartment is disabled; returns "Not Allowed" when the compartment door is open; returns "Not Allowed" when there are no batteries in the compartment; returns "Not Allowed" when the battery BMS does not allow charging; returns "Not Allowed" when the charger is in an abnormal state. Returns "Not Allowed" when a charger fault alarm is present; returns "Not Allowed" when the battery is fully charged; returns "Not Allowed" when the SOC exceeds the maximum value threshold; returns "Not Allowed" when the voltage exceeds the maximum value threshold. Returns to no operation when the battery is in the recharge range and not being charged; returns to no operation when the battery is in the voltage recharge range and not being charged; returns to no operation when the battery is within the protection period.

3. The method according to claim 2, characterized in that, If all hard conditions are not met and no soft conditions are triggered, the system will return to allow. The hard conditions include: compartment disabled state, compartment door open state, battery presence in compartment, battery BMS charging allowed state, charger abnormal state, charger fault alarm, full charge state, maximum SOC value, and maximum voltage value. The soft conditions include: recharge interval without charging, voltage recharge interval without charging, and within the protection period.

4. The method according to claim 1, characterized in that, The calculation of the multi-dimensional dynamic weight value adopts a three-level coding structure. The total weight is equal to the stage weight multiplied by the first base, plus the SOC weight multiplied by the second base, plus the warehouse number weight. The stage weight determines the priority level based on the current charging state and SOC range of the battery. The SOC weight further distinguishes the SOC differences of the battery within the same stage weight. The warehouse number weight is sorted by warehouse number within the same stage weight and SOC weight. The first base is greater than the sum of the product of the maximum SOC weight and the second base plus the maximum warehouse number weight. The second base is greater than the maximum warehouse number weight.

5. The method according to claim 4, characterized in that, The priority level of the stage weights is determined according to the following rules: When the battery is charging and the SOC is less than or equal to the first threshold, the stage weight is the highest level. When the battery is charging and the first threshold is less than the SOC and the SOC is less than or equal to the second threshold, the stage weight is the second highest level. When SOC is greater than the second threshold, the stage weight is the third level; When the battery is not charging and the first threshold is less than the state of charge (SOC) and the SOC is less than or equal to the second threshold, the stage weight is the lowest level.

6. The method according to claim 1, characterized in that, The charging limitation modes include a quantity limitation mode and a power limitation mode; wherein, the quantity limitation mode configures the maximum number of batteries that can be charged simultaneously, selects target charging batteries from high to low according to the sorting results, and stops charging the remaining batteries after the maximum number is reached. The power-limited mode dynamically calculates the available charging power as equal to the total power of the cabinet minus the temperature control power consumption minus the safety redundancy power. The charging power of the sorted batteries is calculated sequentially. If the available charging power is greater than or equal to the sum of the battery power and the safety margin of a single battery, charging is allowed. The available charging power is then reduced by the battery power. Otherwise, charging is not allowed.

7. The method according to claim 6, characterized in that, The formula for calculating battery power is: Battery power = min(charging voltage × charging current, charger maximum power).

8. The method according to claim 1, characterized in that, The charging parameters are calculated using a four-stage curve charging strategy, which divides the charging process into a pre-charging stage, a fast charging stage, a current reduction stage, and a trickle charging stage based on the SOC and charging time. The pre-charge phase is triggered when the charging time is less than or equal to the preset protection time or the SOC is less than the third threshold. At this time, the charging current is the smaller value between the preset pre-charge current and the configured current. The fast charging phase is triggered when the SOC is less than the fourth threshold and the pre-charging phase conditions are not met. At this time, the charging current is the configuration current. The trigger condition for the current reduction phase is that the fourth threshold is less than or equal to the SOC and the SOC is less than or equal to the fifth threshold. At this time, the charging current is the smaller value between the preset current reduction current and the configured current. The trigger condition for the trickle phase is that the SOC is greater than the fifth threshold. At this time, the charging current is the smaller value between the preset trickle current and the configured current. Wherein, the fourth threshold is greater than the third threshold, and the fifth threshold is greater than the fourth threshold.

9. The method according to claim 8, characterized in that, For batteries that are already charging and using the curve charging mode, the charging parameters are recalculated periodically, and the voltage and current settings of the charger are updated in real time when a change in SOC is detected that causes a stage switch.

10. A smart charging scheduling and dynamic power management system for batteries in a battery swapping station, comprising a data acquisition module, a charging scheduling decision module, a charging control execution module, and a temperature control coordination module, characterized in that: The data acquisition module is used to collect site-level status data, cabinet-level status data, battery compartment-level status data, and battery status data within the battery swapping station. The charging scheduling decision module is used to perform safety checks, calculate charging parameters, calculate and sort multi-dimensional dynamic weights based on the status data, and select target charging batteries according to the charging restriction mode. The charging control execution module is used to turn on the charger for the target rechargeable battery and set the charging parameters, and to turn off the charger for unselected batteries that have already been turned on. The temperature control coordination module is used to collect cabinet temperature data and calculate temperature control power consumption within the same scheduling cycle, and feed the temperature control power consumption back to the charging scheduling decision module to participate in the charging power budget calculation. The charging scheduling decision module includes a site safety inspection unit, a single-compartment charging inspection unit, a charging parameter calculation unit, a weight ranking calculation unit, and a power or quantity restriction unit. The site safety inspection unit is used to determine whether the entire station is allowed to charge based on the site status acquisition results. The single-compartment charging inspection unit is used to perform multi-dimensional safety inspections on a single battery compartment. The charging parameter calculation unit is used to match the corresponding charging configuration according to the battery model, and to try three modes in order of priority: BMS guided charging, curve charging and direct charging to calculate the charging voltage and current. The weighted sorting calculation unit is used to calculate multi-dimensional weight values ​​for rechargeable batteries that have passed the safety inspection and sort them from high to low weight. The power or quantity limiting unit is used to select the final set of batteries that are allowed to be charged from the sorted battery list according to the configuration mode. The temperature control coordination module includes a temperature monitoring unit and a heat dissipation or heating control unit. The temperature monitoring unit is used to monitor the temperature of the cabinet core board and the temperature inside each compartment. The heat dissipation or heating control unit is used to control the opening and closing of the whole cabinet cooling fan, the single compartment cooling fan and the whole cabinet PTC heating according to the comparison result of temperature and threshold. Heating and heat dissipation adopt a mutual exclusion strategy.

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