A bidirectional mppt interconnected energy storage product mutual charging efficiency optimization method

Abstract

The application discloses a kind of two-way MPPT interconnection's energy storage product mutual charging efficiency optimization method, it is related to portable energy storage equipment interconnection power supply and efficiency optimization technical field, including the following steps: after starting energy storage equipment, equipment EMS system self-checking and acquisition battery SOC, cell temperature, two-way MPPT module operating state, by communication module transmission to associated control APP;Control APP runs equipment interconnection adaptability evaluation model, carries out nonlinear normalization to the data acquisition, judges equipment interconnection adaptability;In the application, using two-way MPPT direct interconnection link, equipment interconnection adaptability evaluation model, coupled charging and discharging parameter optimization algorithm, load standby power collaborative algorithm and abnormal adaptive processing mechanism, combined with machine learning and MPPT switching optimization technology, solve the problems of traditional AC inverter mutual charging low efficiency, equipment collaborative ability is insufficient, load power supply is disturbed, operation is complicated and potential safety hazard.

Description

Technical Field

[0001] This invention relates to the field of portable energy storage device interconnection and power replenishment and efficiency optimization technology, specifically a method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products. Background Technology

[0002] In special scenarios without a stable mains power supply, such as outdoor operations, emergency rescue, long-distance driving, and field exploration, mutual charging of multiple portable energy storage devices has become a key mode for ensuring continuous power supply. In particular, the 3kWh and 2kWh models, which are the mainstream capacity models, are often used in combination by users due to their complementary capacity advantages to meet the power supply needs of different loads and durations. For example, in emergency rescue, they provide continuous power to communication equipment and medical instruments; in long-distance driving, they provide power support for vehicle electrical appliances and camping equipment; and in field exploration, they ensure the 24 / 7 operation of testing equipment. This multi-device collaborative charging mode not only improves the reliability and continuity of power supply but also flexibly adapts to diverse power usage scenarios. Therefore, it has become the core usage method for users in environments without mains power, and its importance is becoming increasingly prominent as the application scenarios of energy storage devices expand.

[0003] However, existing energy storage device interconnection technology remains at the level of traditional AC inverter interconnection, which has inherent defects. Currently, the conversion efficiency of mainstream AC inverters on the market can only reach about 92%. During the mutual charging process between two devices, the energy needs to undergo two conversions, further reducing the overall interconnection efficiency to 84%, resulting in extremely serious energy loss. This inefficient interconnection mode is also accompanied by a series of derivative problems: the reusability of functional modules is extremely poor. When one device is in inverter mode supplying power to an external load, the other device cannot efficiently act as a backup power pack to continuously replenish energy, resulting in insufficient collaborative working ability of the devices; at the same time, energy fluctuations during the interconnection process can easily interfere with the normal output of the AC load, affecting power stability and even potentially damaging precision equipment and other equipment with high voltage stability requirements; in addition, traditional interconnection methods rely entirely on local manual operation and lack remote intelligent control methods. Users cannot flexibly switch charging and discharging modes according to the remaining power of the device and the power consumption of the load, making the operation cumbersome and the response slow.

[0004] Low cross-charging efficiency and related issues have severely hampered the comprehensive value of energy storage products and the industry's development. In critical scenarios such as emergency rescue, significant energy waste directly leads to a substantial reduction in the actual operating time of equipment, potentially failing to provide sufficient power support for critical loads and impacting rescue effectiveness or operational progress. In scenarios such as long-distance driving and camping, users need to carry additional backup equipment or rely on limited renewable energy charging resources to compensate for energy loss, increasing travel burden and costs while reducing travel flexibility. From a user experience perspective, the cumbersome operation and unstable power supply further lower product satisfaction, preventing the full realization of the advantages of multi-device cross-charging. From an industry perspective, this inefficient and rigid cross-charging technology can no longer meet users' core needs for efficient, intelligent, and reliable cross-charging experiences, becoming a major bottleneck restricting the expansion of energy storage equipment in multi-scenario collaborative power supply, and seriously hindering the industry's pace towards high-quality and high-value-added upgrades. Therefore, this paper proposes a method for optimizing the cross-charging efficiency of bidirectional MPPT interconnected energy storage products to overcome the aforementioned problems. Summary of the Invention

[0005] The purpose of this invention is to provide a method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products, so as to solve the problems mentioned in the background art.

[0006] To address the aforementioned technical problems, this invention provides a method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products, used for mutual charging of multiple portable energy storage devices in scenarios without a stable mains power supply, comprising the following steps: Step 1) After starting the energy storage device, the device's EMS system performs a self-test and collects data on battery SOC, cell temperature, and bidirectional MPPT module operating status, which is then transmitted to the associated control APP via the communication module. Step 2) Control the APP to run the device interconnection compatibility assessment model, perform non-linear normalization processing on the collected data, and determine the device interconnection compatibility; Step 3) After the compatibility is met, the user selects the mutual charging scenario through the APP and triggers the mutual charging efficiency optimization algorithm to calculate the coupled charging and discharging current parameters; Step 4) The energy storage device establishes a direct interconnection link through the bidirectional MPPT module. The MPPT modules of the power supply side and the power receiving side switch to the corresponding modes respectively to complete the direct energy transmission. Step 5) During the mutual charging process, data is collected in real time through the EMS system, parameters are dynamically adjusted by the algorithm, and energy is distributed through the load backup power coordination algorithm. Step 6) Monitor the device status in real time and perform adaptive processing for abnormal scenarios to ensure the safety and stability of mutual charging.

[0007] Furthermore, the core formula of the device interconnectivity compatibility assessment model is: ; in For the first Interoperability rating of the devices For the first Real-time working efficiency of the bidirectional MPPT module on the device. The nonlinear weighting exponent for MPPT efficiency. For the first The actual remaining power of the device For the first Real-time temperature of the battery cells in the device. The normal distribution coefficient for temperature is used. When both of the coefficients are ≥0.7, the system is considered interconnect ready.

[0008] Furthermore, the constraints of the coupled charging and discharging current calculation model include: charging and discharging current ≤ 21.4A, charging and discharging voltage ≤ 58Vdc, total mutual charging efficiency ≥ 90%, the APP displays the calculated current, voltage and expected mutual charging time, and sends them to the device EMS system after user confirmation.

[0009] Furthermore, the energy allocation formula of the load backup power coordination algorithm is as follows: ; in To allocate MPPT output power to mutual charging, The total output power of the MPPT module supplied by the power provider. Power consumed by AC loads This is the load priority coefficient, which ensures that the load power supply priority is higher than mutual charging by amplifying the load power weight.

[0010] Furthermore, the sampling period for the closed-loop control of the mutual charging process is 100ms; when the MPPT efficiency of the power supply is less than 95%, the algorithm fine-tunes the output voltage amplitude to ≤±1Vdc; when the SOC of the receiving battery is close to 90%, the charging current is reduced according to the exponential decay law.

[0011] Furthermore, the anomaly adaptive handling includes: switching to the backup communication channel and reducing current by 10% when the MPPT interconnection link packet loss rate exceeds 2%; starting heat dissipation and reducing power by 20% when the cell temperature rises to 43°C; and triggering short-circuit protection and synchronous alarm when the AC load is short-circuited.

[0012] Furthermore, algorithm optimizations include: introducing machine learning models to build efficiency prediction models; optimizing the MPPT bidirectional switching control algorithm to reduce switching latency to ≤5ms; and expanding multi-device interconnection logic.

[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. Significantly improved mutual charging efficiency: By directly interconnecting bidirectional MPPT modules, the two energy conversion stages of the traditional AC inverter are eliminated. Combined with efficiency optimization algorithms and machine learning prediction models, the total mutual charging efficiency reaches 92.16%, which is 9.7 percentage points lower than the traditional 84%. The efficiency of a single-stage MPPT is stable at over 96.5%, significantly reducing energy loss.

[0014] 2. Enhanced device collaboration and adaptability: Based on the device interconnection adaptability assessment model, the device interconnection readiness status is accurately determined. It supports collaborative charging of 3 or more devices. In backup power mode, the load power supply time is extended by more than 60% compared to a single device, solving the problem of insufficient traditional device collaboration capabilities.

[0015] 3. Load power supply stability guarantee: The load backup power coordination algorithm prioritizes the AC load power supply: the load has higher priority than mutual charging. During mutual charging, the load output voltage fluctuation is ≤2%, the frequency fluctuation is ≤0.5Hz, and the waveform distortion THD is ≤3%, avoiding the interference of traditional mutual charging to the load.

[0016] 4. Dynamic parameter optimization and convenient operation: Closed-loop control with a 100ms sampling period can dynamically adjust charging and discharging parameters, and the MPPT bidirectional switching delay is ≤5ms; it supports remote start / stop, equalization / directional mutual charging, and status monitoring via mobile APP, with an operation response time of ≤30ms, solving the problems of cumbersome traditional manual operation and slow response.

[0017] 5. Enhanced safety and reliability: The anomaly adaptive handling response time is ≤50ms, which can specifically solve problems such as link packet loss, cell overheating, and load short circuit. At the same time, through charging and discharging parameter constraints and SOC threshold control, risks such as overcharging and overheating are avoided. The maximum battery temperature is controlled at 42℃, and the interface temperature is ≤35℃. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of a method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products according to the present invention. Figure 2 A schematic diagram of the mutual charging state of a traditional AC inverter; Figure 3 This is a schematic diagram of the bidirectional MPPT interconnection and mutual charging state of the energy storage product mutual charging efficiency optimization method of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figures 1-3 The present invention provides a technical solution: See Figures 1-3 As shown, an embodiment of a method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products is presented: I. Implementation Environment and Equipment Composition: 1. Energy Storage Equipment: One 3kWh portable energy storage unit and one 2kWh portable energy storage unit. Both units are equipped with an EMS system, a BMS system, a DC / DC converter, a DC / AC inverter, and a bidirectional MPPT module. For example... Figure 2 As shown, in the traditional AC charging mode, both devices achieve energy transfer through DC / AC inverters, resulting in two energy conversion losses; for example... Figure 3 As shown, the bidirectional MPPT module supports bidirectional input / output switching, with an output voltage range of 42Vdc to 58Vdc, a full-load average efficiency of ≥94%, and a single-stage efficiency of 96%. Direct interconnection between MPPTs eliminates the need for an inverter conversion stage. The device has a built-in communication module, supporting bidirectional data interaction with a mobile app and another device, with a communication latency of ≤30ms.

[0021] 2. Control Equipment: A smartphone with a dedicated control APP for energy storage equipment installed. The APP supports mutual charging mode selection, charging and discharging parameter setting, equipment status monitoring and abnormal alarm functions, and facilitates remote issuance of bidirectional charging and discharging commands. It is compatible with the communication protocol of energy storage equipment to ensure the accuracy and real-time performance of command transmission.

[0022] 3. Load Equipment: Resistive, inductive, and capacitive loads that meet AC output characteristics, with a load power ≤1800W and a power factor ≥0.8. They are compatible with the output specifications of DC / AC inverters for energy storage devices, with an output voltage of 114Vac to 125Vac and convenient frequency switching of 50Hz / 60Hz. They are used to verify the stability of the load output during mutual charging.

[0023] 4. Algorithm support: Deploy mutual charging efficiency optimization algorithm, MPPT bidirectional switching control algorithm and load backup power coordination algorithm, run on the equipment EMS system, and realize intelligent switching of charging and discharging modes and dynamic optimization of parameters based on data such as battery SOC, voltage, current, temperature and MPPT working status.

[0024] II. Specific Implementation Steps: (a) Equipment status self-check and interconnection preparation: 1. Upon starting both energy storage devices, the EMS system automatically executes a self-test program, collecting data such as battery SOC, individual cell voltage, cell temperature, bidirectional MPPT module operating status, DC / AC inverter operating parameters, and AC load connection status. The data collection frequency is 50Hz. After filtering, the data is transmitted to the local storage module and communication module. This step addresses the issue of poor device coordination in the background technology by proactively checking the status of core components, laying the foundation for MPPT interconnection.

[0025] 2. A connection is established by scanning the device's QR code via a mobile app. The app receives self-test data from both devices. To accurately quantify device interoperability, considering the non-linear impact of various parameters on interoperability, a device interoperability assessment model is used to perform non-linear normalization on the data. The constructed assessment formula is as follows: ; In the formula: : No. The inter-charging compatibility score of the devices is as follows: the higher the score, the more suitable the device is for participating in bidirectional MPPT inter-charging.

[0026] : No. The real-time operating efficiency of the bidirectional MPPT module of the two-way device is the core influencing factor for optimizing the mutual charging efficiency.

[0027] The MPPT efficiency nonlinear weighting index is determined based on experimental data fitting, which makes the weight of the high-efficiency range higher and highlights the core position of efficiency.

[0028] : No. The actual remaining power of the device. =10% is the minimum mutual charging capacity threshold; below this value, stable mutual charging energy cannot be provided. =90% is the maximum mutual charging capacity threshold. Exceeding this value can easily lead to overcharging risk.

[0029] : No. Real-time temperature of the battery cells in the device. =25℃ is the optimal mutual charging temperature. =0℃、 =45℃ is the suitable temperature range for cross-charging; exceeding this range will affect battery life and cross-charging safety.

[0030] Temperature normal distribution coefficient, used to quantify the degree of influence of temperature deviating from the optimal value.

[0031] =0.55: MPPT efficiency weighting coefficient. Since efficiency is the core optimization objective in this embodiment, it has the highest weighting.

[0032] =0.25: SOC weighting coefficient, which uses an exponential function to reflect the non-linear growth of adaptability as the power consumption increases from low to high.

[0033] =0.2: Temperature weighting coefficient, using a Gaussian function to highlight the adaptation advantage of the optimal temperature range; the sum of the three weighting coefficients is 1, determined based on fitting of multi-scenario test data to ensure the accuracy of the evaluation results.

[0034] 3. When two devices When both are ≥0.7, the app displays "Connection Ready" and allows entry into mutual charging mode; if If the value is less than 0.7, the APP will display specific abnormalities, such as restarting the module when MPPT efficiency is insufficient, prompting for power replenishment when the battery is too low, and initiating heat dissipation when the temperature is abnormal, until the device status meets the standard.

[0035] (II) APP mode settings and cross-charging parameter configuration: 1. Users can select the bidirectional MPPT mutual charging mode through the mobile APP. The APP provides two mutual charging scenario options: balanced mutual charging, which means that the power of the two devices tends to be the same, and targeted mutual charging, which means that one device is designated as the power supply and the other as the power receiving device. After the user selects according to the actual needs, the APP automatically reads the capacity specifications and status data of the two devices.

[0036] 2. To maximize mutual charging efficiency and achieve dynamic parameter adaptation, considering the coupled influence of device capacity, compatibility score, and MPPT efficiency, the mutual charging efficiency optimization algorithm constructs a coupled charging and discharging current calculation model. The core formula is as follows: ; in, Here is the SOC correction function for the power supply, used to compensate for the decrease in discharge capability under low SOC conditions, where: The charging current of the receiving device directly affects the charging speed and efficiency.

[0037] Rated capacity of the receiving equipment, 3 kWh or 2 kWh.

[0038] The rated capacity of the power supply equipment is matched with the capacity of the power receiving equipment.

[0039] The inter-charging compatibility score of the power receiving equipment is calculated by the equipment interconnection compatibility assessment model.

[0040] The interoperability rating of the power supply equipment is consistent with the rating logic of the power receiving equipment.

[0041] The maximum output current of the bidirectional MPPT module is determined based on the module's constant power output characteristics.

[0042] The total efficiency of mutual charging between two devices is calculated by introducing a compatibility score correction item. The higher the compatibility, the smaller the efficiency loss.

[0043] : Working efficiency of the MPPT module of the power supply equipment.

[0044] : Working efficiency of the MPPT module of the power receiving device.

[0045] The actual remaining power of the power supply equipment is dynamically adjusted by a correction function to adjust the current distribution ratio.

[0046] 3. The algorithm sets three constraints simultaneously: charging and discharging current ≤21.4A, charging and discharging voltage ≤58Vdc, and total mutual charging efficiency ≥90%, ensuring that the parameters meet the device hardware specifications; the APP displays the calculated charging and discharging parameters, including current, voltage, and estimated mutual charging time, and sends them to the EMS system of both devices after user confirmation.

[0047] (III) MPPT Interconnection Establishment and Inter-charge Startup: 1. After receiving the APP command, the EMS systems of the two devices establish an MPPT interconnection link through their built-in communication modules, such as... Figure 3 As shown, the bidirectional MPPT module of the power supply equipment switches to discharge mode, and the bidirectional MPPT module of the power receiving equipment switches to charging mode, forming an energy transmission channel with direct MPPT-MPPT interconnection, replacing... Figure 2 The traditional AC inverter interconnection method reduces energy conversion losses.

[0048] 2. The power supply device converts the battery power into a suitable DC voltage (42Vdc to 51.2Vdc) through the MPPT module, and transmits it to the MPPT module of the power receiving device via the interconnection link. The power receiving device's MPPT module further optimizes the voltage and current to adapt to its own battery charging needs, and then delivers it to the battery circuit through a DC / DC converter to start the mutual charging process.

[0049] 3. If there are AC load connections, such as camping appliances or emergency communication equipment, the DC / AC inverter remains in normal working condition. The EMS system dynamically allocates energy through a load backup power coordination algorithm to ensure that mutual charging energy and load power supply energy do not interfere with each other. The energy allocation formula is as follows: ; in, To allocate MPPT output power to mutual charging, The total output power of the MPPT module supplied by the power provider. Power consumed by AC loads This is the load priority coefficient. By amplifying the load power weight, it ensures that the load power supply has a higher priority than mutual charging, thus avoiding load voltage fluctuations.

[0050] (iv) Closed-loop control and mode switching during mutual charging: 1. During the mutual charging process, the EMS system collects real-time data on battery voltage, current, temperature, SOC, and MPPT efficiency of both devices at a sampling period of 100ms, and transmits this data to the mutual charging efficiency optimization algorithm for dynamic adjustment. When the MPPT efficiency of the power supply is detected to be lower than 95%, the algorithm automatically fine-tunes the output voltage based on the efficiency-voltage coupling model, with an adjustment range of ≤±1Vdc, so that the efficiency rises back to above 96% and the mutual charging efficiency is stable.

[0051] When the state of charge (SOC) of the receiving battery approaches 90%, the algorithm gradually reduces the charging current according to the exponential decay law to avoid overcharging. At the same time, the APP updates the battery level in real time for easy monitoring by the user.

[0052] 2. If the user needs to switch to backup power mode, they can issue a command through the APP to designate one device to keep the inverter working to supply power to the load, while the other device switches to backup power mode. Its MPPT module continuously supplies power to the inverter device at a 96% efficiency to achieve continuous power replenishment. At this time, the energy source of the inverter device is the coordinated supply of its own battery and the backup power device, which extends the power supply time of the load.

[0053] 3. Throughout the process, the DC / AC inverter output voltage fluctuation is ≤2% and the frequency fluctuation is ≤0.5Hz, ensuring that the AC load works normally without any interruption or shutdown, thus solving the problem of traditional mutual charging interference load output.

[0054] (v) Anomaly detection and adaptive processing: 1. During mutual charging, the algorithm monitors device status data in real time, performs threshold judgment and trend analysis on the collected data such as voltage, current, temperature, MPPT efficiency, and communication link status, and promptly identifies various abnormal scenarios: When the packet loss rate of the MPPT interconnection link exceeds 2%, it immediately switches to the backup communication channel and reduces the charging and discharging current by 10% to ensure the stability of energy transmission before the link is restored.

[0055] When the cell temperature rises to 43℃, the cooling fan is activated, and the algorithm reduces the charging and discharging power by 20% until the temperature drops below 40℃ to prevent overheating from affecting equipment safety.

[0056] When the AC load is short-circuited, the DC / AC inverter triggers instantaneous short-circuit protection. If the short circuit persists after automatic restart, it will lock, and the APP will simultaneously issue an alarm. The mutual charging process will be suspended to prioritize equipment safety.

[0057] 2. The response time for all exception handling commands is ≤50ms. After the exception is handled, if the device status returns to normal, the mutual charging process will be automatically restarted and the original parameters will be restored. If the status cannot be restored, the APP will prompt manual intervention to ensure the timeliness and effectiveness of exception handling.

[0058] III. Algorithm Optimization: (a) Optimization of mutual charging efficiency algorithm: By introducing a machine learning model and using historical cross-charging data, including device status, ambient temperature, and load power, as training samples, an efficiency prediction model is constructed. This model dynamically optimizes the operating parameters of the MPPT module, including voltage and current, so that the efficiency of a single-stage MPPT is stabilized at over 96.5%, further improving the overall cross-charging efficiency.

[0059] (II) Robustness optimization of MPPT bidirectional switching control algorithm: A power grid harmonics and electromagnetic interference detection module is added. The algorithm eliminates the impact of interference signals on MPPT switching through filtering algorithm, optimizes the switching timing logic, and shortens the switching delay from ≤10ms to ≤5ms, avoiding energy loss and voltage fluctuations during the switching process.

[0060] (III) Optimization of multi-device interconnection compatibility: The algorithm extends the multi-device interconnection logic, supporting collaborative charging of three or more energy storage devices with different capacities. It automatically identifies the capacity and status of each device, allocates charging and discharging priorities and power ratios, and improves the versatility and adaptability of the solution to different scenarios.

[0061] IV. Verification of Implementation Results: 1. Comparison of mutual charging efficiency: such as Figure 2 As shown, in the traditional AC inverter mutual charging mode, with an inverter efficiency of 92%, the total mutual charging efficiency of the two devices is 84%. After adopting the bidirectional MPPT interconnection scheme of this embodiment, as... Figure 3As shown, the overall mutual charging efficiency reaches 92.16%, and the energy loss is reduced by about 9.7 percentage points, significantly improving energy utilization and solving the core pain point of inefficient mutual charging in the background technology.

[0062] 2. Load output stability verification: During the mutual charging process, the AC load operates normally, with output voltage fluctuation ≤2%, frequency fluctuation ≤0.5Hz, and waveform distortion THD ≤3%, which is consistent with the load operating state when there is no mutual charging, verifying the effect of mutual charging and load power supply not interfering with each other.

[0063] 3. Module reuse and backup power effect verification: After switching to backup power mode, the backup power equipment continuously replenishes power to the inverter equipment through the MPPT module. The load power supply time of the inverter equipment is extended by more than 60% compared with the independent power supply of a single equipment. The reusability of functional modules is significantly improved, the backup power attribute is strengthened, and the problem of insufficient collaborative work capability of traditional equipment is solved.

[0064] 4. Ease of Operation Verification: The mobile APP allows for convenient remote start / stop, parameter setting, status monitoring, and abnormal alarms. The operation response time is ≤30ms, eliminating the need for local manual wiring or adjustment, thus solving the problems of cumbersome operation and delayed response in traditional cross-charging.

[0065] 5. Safety verification: During the entire charging process, the battery temperature was controlled at a maximum of 42℃, and the interface temperature was ≤35℃. No abnormalities such as overcharging, overheating, or short circuit occurred. The BMS system and EMS system worked together to effectively protect the equipment and personnel.

Claims

1. A method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products, used for mutual charging of multiple portable energy storage devices in scenarios without a stable mains power supply, characterized in that... Includes the following steps: Step 1) After starting the energy storage device, the device's EMS system performs a self-test and collects data on battery SOC, cell temperature, and bidirectional MPPT module operating status, which is then transmitted to the associated control APP via the communication module. Step 2) Control the APP to run the device interconnection compatibility assessment model, perform non-linear normalization processing on the collected data, and determine the device interconnection compatibility; Step 3) After the compatibility is met, the user selects the mutual charging scenario through the APP and triggers the mutual charging efficiency optimization algorithm to calculate the coupled charging and discharging current parameters; Step 4) The energy storage device establishes a direct interconnection link through the bidirectional MPPT module. The MPPT modules of the power supply side and the power receiving side switch to the corresponding modes respectively to complete the direct energy transmission. Step 5) During the mutual charging process, data is collected in real time through the EMS system, parameters are dynamically adjusted by the algorithm, and energy is distributed through the load backup power coordination algorithm. Step 6) Monitor the device status in real time and perform adaptive processing for abnormal scenarios to ensure the safety and stability of mutual charging.

2. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: The core formula of the device interconnectivity compatibility assessment model is: ； in For the first Interoperability rating of the devices For the first Real-time working efficiency of the bidirectional MPPT module on the device. The nonlinear weighting exponent for MPPT efficiency. For the first The actual remaining power of the device For the first Real-time temperature of the battery cells in the device. The normal distribution coefficient for temperature is used. When both of the coefficients are ≥0.7, the system is considered interconnect ready.

3. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: The constraints of the coupled charging and discharging current calculation model include: charging and discharging current ≤ 21.4A, charging and discharging voltage ≤ 58Vdc, and total mutual charging efficiency ≥ 90%. The APP displays the calculated current, voltage, and estimated mutual charging time, which are then sent to the device EMS system after user confirmation.

4. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: The energy allocation formula for the load backup power coordination algorithm is: ； in To allocate MPPT output power to mutual charging, The total output power of the MPPT module supplied by the power provider. Power consumed by AC loads This is the load priority coefficient, which ensures that the load power supply priority is higher than mutual charging by amplifying the load power weight.

5. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: The sampling period for the closed-loop control of the mutual charging process is 100ms; when the MPPT efficiency of the power supply is less than 95%, the algorithm fine-tunes the output voltage amplitude to ≤±1Vdc; when the SOC of the receiving battery is close to 90%, the charging current is reduced according to the exponential decay law.

6. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: Anomaly adaptive handling includes: switching to backup communication channel and reducing current by 10% when MPPT interconnection link packet loss rate exceeds 2%; starting heat dissipation and reducing power by 20% when cell temperature rises to 43℃; and triggering short-circuit protection and synchronous alarm when AC load is short-circuited.

7. The method for optimizing the mutual charging efficiency of bidirectional MPPT interconnected energy storage products as described in claim 1, characterized in that: Algorithm optimizations include: introducing machine learning models to build efficiency prediction models; optimizing the MPPT bidirectional switching control algorithm to reduce switching latency to ≤5ms; and expanding multi-device interconnection logic.

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