High-redundancy hot plug type power supply system and control method

Abstract

The invention relates to a high-redundancy hot plug type power supply system and a control method, and belongs to the technical field of power supply systems. Comprising a main power supply module composed of a plurality of groups of rechargeable batteries; the standby power supply module is composed of a plurality of groups of rechargeable batteries or super capacitors supporting hot plugging; the processing unit is in communication connection with the main power supply module and the standby power supply module; wherein the processing unit is configured to dynamically dispatch the standby power supply module to participate in power supply by evaluating the health state of a battery unit in the main power supply module and predicting the future electric heating state of the battery unit, so that the main power supply module works in a preset optimized working interval. According to the invention, the problems of unstable output voltage and reduced power supply reliability caused by the fact that the battery power supply system cannot accurately predict the battery state when the load equipment in the prior art is under the working condition of severe temperature fluctuation are solved.

Description

Technical Field

[0001] This invention relates to a highly redundant, hot-swappable power supply system and control method, belonging to the technical field of power supply systems. Background Technology

[0002] Emergency transport equipment and various mobile medical systems operating outdoors or in complex temperature zones have extremely stringent requirements for power supply reliability. When performing transport missions, these devices often need to integrate functions such as biological sample refrigeration, temperature control, or life support, and their operating environment frequently switches between air-conditioned environments (approximately 20°C–25°C), outdoor high temperatures (above 35°C), and refrigerated environments (below 5°C). Under these conditions, the power supply system not only needs to provide continuous energy but also faces severe electro-thermal management challenges due to drastic temperature changes. Nickel-metal hydride batteries, due to their high intrinsic safety, absence of flammable organic electrolytes, and strong resistance to abuse, have become an ideal choice for such medical scenarios with extremely high safety and ethical requirements.

[0003] However, the electrochemical performance of nickel-metal hydride batteries is more sensitive to temperature, a characteristic that is amplified dramatically during frequent thermal cycling: First, at low temperatures, the internal ionic conductivity of the battery decreases and the charge transfer impedance increases significantly, resulting in a substantial reduction in its actual usable capacity. Furthermore, the output voltage is prone to "collapse" due to a sharp increase in internal resistance at the moment of load startup. Second, at high temperatures, the rate of side reactions inside the battery accelerates, and the decomposition of the electrolyte and the process of alloy corrosion are accelerated, leading to a rapid decline in cycle life. At the same time, the self-discharge rate increases exponentially, creating the illusion of "artificially high capacity."

[0004] Existing power management solutions, such as the redundant power supply architecture proposed in CN103872716A, primarily contribute by achieving compatibility and switching between different power types (such as AC and battery) under multi-bus conditions. However, its control core is based on hysteresis comparison of the current voltage, which is a kind of "passive response" protection. It does not consider the degradation of the battery's health state itself, nor can it predict future temperature changes and the resulting electrical performance degradation. Another document, CN211405552U, provides a more detailed battery state detection and charge / discharge control circuit, but its management logic is still limited to the perception and judgment of the "current state," lacking a predictive model that can integrate electrochemical characteristics and thermodynamic behavior. Therefore, it cannot make forward-looking power allocation decisions in the early stages of rapid temperature changes.

[0005] Even more serious is that under frequent temperature stress shocks, the performance dispersion between individual cells within a nickel-metal hydride battery pack is amplified at an accelerated pace: cells with high internal resistance at low temperatures experience faster voltage drops during discharge, while severely aged cells exhibit more significant self-discharge at high temperatures. This inconsistency creates a typical "weakest link" effect in a fixed series-parallel connected "rigid" battery pack, ultimately causing the usable capacity and power output of the entire battery system to decline earlier than expected. This creates a vicious cycle: drastic temperature changes → fluctuations in battery internal resistance and capacity decay → inaccurate BMS capacity estimation and unstable voltage output → the system is forced to switch to backup power prematurely or shut down unexpectedly → batteries age faster due to frequent deep charge-discharge cycles and deteriorating operating conditions → system reliability continues to decline.

[0006] The essence of this problem is that existing technologies lack the ability to predict the battery health status and electrothermal behavior under dynamic temperature change conditions and lack forward-looking scheduling strategies, which leads to the power supply system falling into a passive response or even protective power outage at critical moments.

[0007] Therefore, developing a highly redundant power supply system and control method capable of accurately predicting the health status and future electrothermal behavior of nickel-metal hydride batteries in environments with rapidly changing temperatures, and dynamically scheduling them accordingly, has become an urgent technical requirement to overcome the current power supply bottleneck of mobile medical devices. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a highly redundant, hot-swappable power supply system and control method, which solves the problem of unstable output voltage and reduced power supply reliability caused by the inability to accurately predict battery status in the existing load equipment under the condition of drastic temperature fluctuation.

[0009] The technical problem to be solved by this invention is achieved by the following technical solution: A highly redundant, hot-swappable power supply system, comprising: The main power supply module consists of multiple sets of rechargeable batteries; The backup power supply module consists of multiple sets of rechargeable batteries or supercapacitors that support hot-swapping. The processing unit is communicatively connected to the main power supply module and the backup power supply module; The processing unit is configured to dynamically schedule the backup power supply module to participate in power supply by evaluating the health status of the battery cells in the main power supply module and predicting their future electrothermal status, so that the main power supply module operates within a predetermined optimized operating range.

[0010] The present invention is further configured such that: the system also includes a load interface for communicating with external electrical equipment; The processing unit receives the expected power demand information sent by the external electrical equipment through the load interface.

[0011] The present invention is further configured such that: the backup power supply module includes a power-type backup unit and an energy-type backup unit; The power-type backup unit is configured to respond to instantaneous peak power demand; The energy-type backup unit is configured to take over the main load or provide temperature-controlled energy to the main power supply module in extreme temperature environments.

[0012] A control method for a highly redundant, hot-swappable power supply system, comprising: S1. Collect the internal and external status parameters of the power supply module. The internal status parameters include voltage, current, core temperature, and real-time internal resistance calculated by the pulse current method. The external parameters include ambient temperature and expected power demand profiles from external electrical equipment. S2. Based on the data collected in step S1, perform electrothermal status prediction and health status assessment, and obtain the corresponding assessment and prediction results. S3. Based on the evaluation and prediction results obtained in step S2, generate scheduling instructions through multiple decision logics; S4. Execute the scheduling instructions generated in step S3, and adjust the load distribution of each power supply module or perform module switching operations to make the main power supply module work within a predetermined optimized working range.

[0013] The present invention is further configured such that step S2 includes: S21. Health status assessment step: Based on the historical cycle count of the power supply module and the real-time internal resistance, calculate the health status value through a predefined aging model. The aging model is used to characterize the relationship between the health status value and the decrease in the number of cycles and the increase in internal resistance. S22. Electrothermal state prediction step: Based on the real-time voltage, current, core temperature and ambient temperature, calculations are performed using a preset electrochemical-thermal coupling model to output the predicted voltage and core temperature values ​​for a specific time period in the future. The electrochemical-thermal coupling model is used to characterize the interaction between the real-time voltage, current, core temperature and ambient temperature.

[0014] The present invention is further configured such that step S3 includes: S31. The health status value, voltage prediction value and core temperature prediction value obtained in step S2 are compared with the preset health status threshold, voltage stability threshold and temperature protection threshold, respectively. S32. Based on the comparison result obtained in step S31, execute at least one of health scheduling logic, thermal management scheduling logic, and power scheduling logic to generate a scheduling instruction, wherein: The health scheduling logic includes: when it is determined that the health status value of any battery cell in the main power supply circuit is lower than the health status threshold or its state of charge is lower than the power switching threshold, the cell is determined to be a weak cell, and a first scheduling instruction is generated to remove the weak cell from the main power supply circuit, and the battery cell with the largest product of health status value and state of charge value is selected from the backup power supply module and switched to the main power supply circuit. The thermal management scheduling logic includes: when the core temperature prediction value exceeds the temperature protection threshold or the ambient temperature change rate exceeds the preset ambient temperature change threshold, it is determined that there is a risk of thermal stress, and a second scheduling instruction is generated to schedule the energy-type backup unit in the backup power supply module to share the main load, so as to reduce the heat generation of the main power supply module, and at the same time start or adjust the working parameters of the active temperature control system. The power scheduling logic includes: when the expected power demand map contains instantaneous high power demand, it is determined that there is a risk of voltage drop, and a third scheduling instruction is generated to pre-connect the power type backup unit in the backup power supply module before the instantaneous high power demand arrives, and instruct it to take on most or all of the instantaneous power during peak load.

[0015] The present invention is further configured such that the health scheduling logic also includes: Before generating the first scheduling instruction, it is determined whether there are battery cells in the backup power supply module whose health status value and state of charge product is greater than a preset product threshold. If it exists, then execute the first scheduling instruction; If it does not exist, a degradation scheduling instruction is generated to reduce the load demand of the main power supply module or trigger an alarm.

[0016] The present invention is further configured such that the thermal management scheduling logic also includes: Before generating the second scheduling instruction, it is determined whether the available capacity of the energy-type backup unit is greater than a preset capacity threshold. If it is greater than that, then execute the second scheduling instruction; If the value is not greater than the specified value, an auxiliary temperature control command is generated to prioritize adjusting the operating parameters of the active temperature control system in order to reduce the heat generated by the main power supply module.

[0017] The present invention is further configured such that the power scheduling logic also includes: Before generating the third scheduling instruction, it is determined whether the duration of the instantaneous high power demand exceeds a preset duration threshold. If the limit is exceeded, then the third scheduling instruction is executed; If the limit is not exceeded, a buffer scheduling instruction is generated, and the instantaneous power is shared by the main power supply module and the power-type backup unit.

[0018] The present invention is further configured such that the method also includes: S5. Adaptive learning step: After step S4 is executed, record the voltage and temperature performance data of the power supply module under actual load and compare it with the predicted value of step S2. Based on the difference between the actual data and the predicted values, the parameters in the electrochemical-thermal coupling model are adjusted to reduce the error in future predictions; The adjustment includes: correcting the internal resistance parameter in the electrochemical-thermal coupling model when the difference between the actual voltage and the predicted voltage exceeds the voltage error threshold; and correcting the heat capacity parameter in the electrochemical-thermal coupling model when the difference between the actual temperature and the predicted temperature exceeds the temperature error threshold.

[0019] The beneficial effects of this invention are: By setting up an electrochemical-thermal coupling model, the system can predict the future voltage and core temperature changes of the main power supply module in advance. When the predicted core temperature exceeds the protection threshold or the ambient temperature changes drastically, the system will schedule the energy-type backup unit in the backup power supply module to share the main load, reduce the heat generated by the main power supply module, and adjust the parameters of the active temperature control system. In the face of instantaneous high power demand, the power-type backup unit will connect in advance and bear most of the peak power, avoiding the output voltage "collapse" caused by the surge in internal resistance of the main power supply module. This fundamentally solves the problem of electrical performance fluctuation of nickel-metal hydride batteries in cold and hot cycles, and ensures that the power supply voltage is always stable within the range required by the equipment. By establishing an aging model based on historical cycle count and real-time internal resistance, the battery health status is assessed. Through health scheduling logic, "weak cells" with low health status or state of charge are actively screened out and removed from the main power supply circuit in a timely manner. At the same time, cells with the largest product of health status and state of charge are selected from the backup modules to supplement the battery. This avoids the "weak cell" causing the "barrel effect" in the rigid series-parallel structure. Furthermore, the system dynamically schedules the backup modules to share the load, reducing excessive losses of the main power supply module under extreme temperature or high power conditions, and reducing the cycle life degradation caused by accelerated side reactions at high temperatures and deep charge-discharge at low temperatures. By constructing a redundancy mode of "main power supply module + classified backup module" and designing a scheduling fault tolerance mechanism, when there are no battery units that meet the requirements of the backup module in the health scheduling, the system will generate a degrade scheduling instruction to reduce the main load demand or alarm; when the capacity of the energy-type backup unit is insufficient in the thermal management scheduling, active temperature control will be strengthened first; when the duration of instantaneous high power demand is short in the power scheduling, the main and backup coordinated power supply will be adopted to avoid the system paralysis caused by the failure of a single module. Attached Figure Description

[0020] Figure 1 This is a block diagram of the system architecture in this invention.

[0021] Figure 2 This is a schematic diagram of the overall process of the method in this invention.

[0022] Figure 3 This is a flowchart illustrating the health scheduling logic in this invention.

[0023] Figure 4 This is a flowchart illustrating the thermal management scheduling logic in this invention.

[0024] Figure 5 This is a flowchart illustrating the power scheduling logic in this invention. Detailed Implementation

[0025] To facilitate a clear understanding of the technical means, creative features, objectives, and effects of this invention, the invention will be further described below in conjunction with specific illustrations.

[0026] like Figure 1 As shown, a highly redundant, hot-swappable power supply system includes: The main power supply module consists of multiple sets of rechargeable batteries, preferably rechargeable nickel-metal hydride (NiMH) batteries. NiMH batteries are inherently safe, contain no flammable organic electrolytes, and exhibit excellent resistance to abuse, maintaining basic stability even under frequent temperature fluctuations. Each NiMH battery set is equipped with an independent state monitoring unit that collects real-time data on battery voltage, current, core temperature, and real-time internal resistance calculated using the pulse current method.

[0027] The backup power supply module includes power-type backup units and energy-type backup units, among which: The power-type backup unit preferably uses supercapacitors. The core advantages of supercapacitors are their fast charging and discharging response speed and high power density, which can quickly match the instantaneous peak power demand of external electrical equipment. The energy-type backup unit also uses nickel-metal hydride batteries, which are the same type of batteries as the main power supply module, and also support hot-swapping.

[0028] The processing unit is communicatively connected to the main power supply module and the backup power supply module; The processing unit is configured to dynamically schedule the backup power supply module to participate in power supply by evaluating the health status of the battery cells in the main power supply module and predicting their future electrothermal status, so that the main power supply module operates within a predetermined optimized operating range.

[0029] The system also includes a load interface for communicating with external electrical equipment. The load interface uses the CAN bus communication protocol, which has strong anti-interference capabilities and stable transmission rates. The processing unit receives the expected power demand map sent by the external electrical equipment through this interface, such as the continuous and stable power demand of the life support module and the fluctuating power demand of the temperature maintenance module.

[0030] like Figures 2-5 As shown, a control method for a highly redundant, hot-swappable power supply system includes: S1. Collect internal and external status parameters of the power supply module. The internal status parameters are collected through dedicated monitoring elements to ensure data accuracy and real-time performance.

[0031] Internal state parameters include voltage, current, core temperature, and real-time internal resistance calculated using the pulse current method, among which: Voltage parameters are acquired using a high-precision voltage sensor with a measurement accuracy of ±0.01V, capable of capturing minute fluctuations in battery cell voltage and providing a basis for subsequent voltage stability assessment. Current parameters are acquired using a Hall current sensor with a measurement range covering 0-50A. Core temperature parameters are acquired using an NTC thermistor built into the battery pack of the power supply module, with a measurement range of -40℃ to 85℃. Real-time internal resistance is calculated using the pulse current method. For example, a constant pulse current with a duration of 100ms and an amplitude of 5A is applied to the battery cell, and the voltage change before and after the pulse is recorded. The resistance is then calculated using Ohm's law R=ΔU / ΔI. This method is fast and has minimal impact on normal battery operation.

[0032] To facilitate power supply system analysis and scheduling strategies, battery external parameters include ambient temperature and expected power demand profiles from external electrical equipment. The ambient temperature is collected by a temperature sensor located on the equipment casing; the expected power demand profiles from external electrical equipment are also included.

[0033] The process of generating power demand maps for load devices is directly related to the characteristics of their own functional modules, workflow presets, and status monitoring capabilities. Taking mobile medical systems as an example, they typically integrate functional modules such as sample refrigeration, life support, and constant temperature maintenance. The power consumption of each module at different working stages follows a clear pattern: for example, the refrigeration module requires high power to drive the refrigeration unit in the initial stage of startup, and then switches to a low-power heat preservation state after reaching the target temperature; the life support module requires continuous and stable medium power output.

[0034] The load device, through its own control unit, combined with the preset operating procedures of each functional module (such as startup sequence and operating mode) and the real-time status of the modules, pre-plans the changes in power demand of each module over a future period. It then integrates these dispersed module power demands into a comprehensive power demand map. This map must include a time dimension and power values ​​at corresponding time points, forming structured power demand data. Finally, it is sent to the power supply system's processing unit through the load interface, providing accurate demand data for the dynamic scheduling of the power supply system.

[0035] S2. Based on the data collected in step S1, perform electrothermal status prediction and health status assessment, and obtain the corresponding assessment and prediction results. S21. Health Status Assessment Step: Based on the historical cycle count and real-time internal resistance of the power supply module. The historical cycle count of the power supply module is accumulated and recorded in real time by the storage module of the processing unit. Each time the battery discharges from a fully charged state to a 20% state of charge and then recharges to a fully charged state, it is counted as one complete cycle. The real-time internal resistance is obtained by the pulse current method in step S1.

[0036] The health status value is calculated using a predefined aging model, which characterizes the relationship between the health status value and the decrease in the number of cycles and the increase in internal resistance. For example, the initial health status value of a new battery is set to 100%. As the number of cycles increases, the health status value gradually decreases. Typically, the health status value decreases by 5% for every 100 cycles. At the same time, an increase in real-time internal resistance will also lead to a decrease in the health status value. When the real-time internal resistance increases by 20% compared to the initial internal resistance of the battery, the health status value decreases by an additional 10%.

[0037] S22. Electrothermal State Prediction Step: Based on real-time voltage, current, core temperature, and ambient temperature, calculations are performed using a preset electrochemical-thermal coupling model to output predicted voltage and core temperature values ​​for a specific time period in the future. The electrochemical-thermal coupling model is used to characterize the interaction between real-time voltage, current, core temperature, and ambient temperature.

[0038] Joule heating is generated when current flows through the internal resistance of the power supply module, causing the core temperature to rise. The increased core temperature accelerates the electrochemical reaction rate inside the battery, thus affecting the stability of the output voltage. Meanwhile, ambient temperature directly affects the heat dissipation efficiency of the power supply module. Excessively high ambient temperature inhibits heat dissipation, further increasing the core temperature, while excessively low ambient temperature slows down the electrochemical reaction rate, leading to a decrease in output voltage. These four parameters form a closed loop of mutual influence.

[0039] S3. Based on the evaluation and prediction results obtained in step S2, scheduling instructions are generated through multiple decision logics. S31. Compare the health status value, voltage prediction value, and core temperature prediction value obtained in step S2 with the preset health status threshold, voltage stability threshold, and temperature protection threshold, respectively. The health status threshold is preferably set at 80%. When the health status value of the nickel-metal hydride battery is below 80%, its capacity and power output capability will be significantly reduced, and continuing to use it as the main power supply unit will easily lead to unstable power supply.

[0040] The voltage stability threshold is set to 90% of the battery's rated voltage. For example, for a 12V rated voltage battery, the threshold is 10.8V. If it is lower than this value, the external load equipment will not work properly. The temperature protection threshold is set to 45℃. When the temperature of a nickel-metal hydride battery exceeds this temperature, the internal side reaction rate will accelerate sharply, shortening the battery life and potentially causing safety hazards.

[0041] S32. Based on the comparison result obtained in step S31, execute at least one of the following: health scheduling logic, thermal management scheduling logic, and power scheduling logic to generate a scheduling instruction, wherein: The health scheduling logic includes: when it is determined that the health status value of any battery cell in the main power supply circuit is lower than the health status threshold or its state of charge is lower than the power switching threshold, the cell is determined to be a weak cell, and a first scheduling instruction is generated. The first scheduling instruction is to remove the weak cell from the main power supply circuit and select the battery cell with the largest product of health status value and state of charge from the backup power supply module to switch to the main power supply circuit. Before generating the first scheduling instruction, it is determined whether there are battery cells in the backup power supply module whose health status value and state of charge product is greater than a preset product threshold. If there are, the first scheduling instruction is executed; if not, a degraded scheduling instruction is generated to reduce the load demand of the main power supply module or trigger an alarm.

[0042] When the health status value of any battery cell in the main power supply circuit is lower than the 80% health status threshold, or the state of charge is lower than the 25% power switching threshold, the cell is identified as a weak cell. Before generating the first dispatch instruction, it is necessary to determine whether there are battery cells in the backup power supply module whose health status value and state of charge product is greater than 60. The cell with the largest product is selected for switching. This product comprehensively reflects the "health" and "available power" of the backup cell. The larger the product, the stronger the power supply reliability and continuity of the backup cell. If there is no backup cell that meets the requirements, a degraded dispatch instruction is generated to reduce the load demand of the main power supply module by 30%-50% or trigger an audible and visual alarm to prevent the main power supply module from being further damaged due to excessive load without the support of a reliable backup cell.

[0043] The thermal management scheduling logic includes: when the core temperature prediction value exceeds the temperature protection threshold or the ambient temperature change rate exceeds the preset ambient temperature change threshold, it is determined that there is a risk of thermal stress and a second scheduling instruction is generated. The second scheduling instruction schedules the energy-type backup unit in the backup power supply module to share the main load, so as to reduce the heat generation of the main power supply module, and at the same time starts or adjusts the working parameters of the active temperature control system. Before generating the second scheduling instruction, it is determined whether the available capacity of the energy-type backup unit is greater than the preset capacity threshold. If it is greater, the second scheduling instruction is executed. If it is not greater, an auxiliary temperature control instruction is generated to prioritize adjusting the operating parameters of the active temperature control system to reduce the heat generation of the main power supply module.

[0044] For example, when the predicted core temperature exceeds the 45°C temperature protection threshold, or the ambient temperature change rate exceeds the 5°C / min ambient temperature change threshold, a thermal stress risk is identified. Before generating the second scheduling instruction, it is necessary to determine whether the available capacity of the energy-type backup unit is greater than the preset capacity threshold. If it is, the energy-type backup unit is scheduled to share 30%-40% of the load of the main power supply module, reducing the heat generation of the main module. At the same time, the active temperature control system is started or adjusted, such as increasing the cooling fan speed to 100% or starting the semiconductor cooling module.

[0045] If the available capacity of the energy-type backup unit is insufficient, an auxiliary temperature control command is generated to prioritize and enhance active temperature control. This reduces the heat generated by the main module by improving heat dissipation efficiency, thus preventing temperature runaway due to insufficient backup unit capacity.

[0046] The power scheduling logic includes: when the expected power demand pattern includes instantaneous high power demand, it is determined that there is a risk of voltage drop and a third scheduling instruction is generated. Before the instantaneous high power demand arrives, the third scheduling instruction pre-connects the power type backup unit in the backup power supply module and instructs it to take on most or all of the instantaneous power during peak load.

[0047] Before generating the third scheduling instruction, it is determined whether the duration of the instantaneous high power demand exceeds a preset duration threshold: if it does, the third scheduling instruction is executed; if it does not exceed the threshold, a buffer scheduling instruction is generated, and the instantaneous power is shared by the main power supply module and the power-type backup unit.

[0048] When the expected power demand pattern includes a momentary high power demand, a risk of voltage drop is identified. Before generating the third scheduling instruction, it is necessary to determine whether the duration of the momentary high power demand exceeds a preset duration threshold of 1 second. If it does, a power-type backup unit is pre-connected 500ms before the demand arrives, instructing it to handle more than 90% of the momentary power, while the main module only handles a small amount of basic power. If the duration does not exceed 1 second, a buffer scheduling instruction is generated, with the main power supply module handling 60%-70% of the momentary power and the power-type backup unit handling 30%-40%. This avoids voltage fluctuations caused by short-term high current output from the main module and excessive wear on the power-type backup unit, balancing power supply stability and backup unit lifespan.

[0049] S4. Execute the scheduling instructions generated in step S3, and adjust the load distribution of each power supply module or perform module switching operations to make the main power supply module work within the predetermined optimized working range.

[0050] Furthermore, to ensure a more stable power supply, when adjusting the load distribution of each power supply module, the processing unit controls the power converters in the main and backup power supply modules via PWM signals to gradually adjust the output current at a rate of 0.2-0.7A / ms. This avoids voltage fluctuations caused by sudden current changes and ensures that the output voltage remains stable within the normal fluctuation range of the rated voltage. It also prevents the main module from operating continuously under high power, extreme temperature, or poor health conditions, thereby guaranteeing the reliability of the power supply system.

[0051] S5. After step S4 is executed, record the voltage and temperature performance data of the power supply module under actual load and compare them with the predicted values ​​in step S2. Based on the difference between actual data and predicted values, the parameters in the electrochemical-thermal coupling model are adjusted to reduce the error in future predictions; The adjustments include: when the difference between the actual voltage and the predicted voltage exceeds the voltage error threshold, it indicates a deviation between the internal resistance parameter in the model and the actual internal resistance of the battery. Furthermore, the processing unit adjusts the internal resistance parameter based on the magnitude of the difference, with the adjustment range being 10%-20% of the ratio of the actual difference to the predicted value. For example, if the actual internal resistance is 10% greater than the model's predicted value, the internal resistance parameter in the model will be increased by 10%-20% to ensure that subsequent voltage predictions better reflect the actual situation.

[0052] When the difference between the actual and predicted temperatures exceeds the 2°C temperature error threshold, it indicates that the heat capacity parameters in the model do not conform to the current thermal characteristics of the battery. The processing unit adjusts the heat capacity parameters according to the same correction logic, with the correction range also being 10%-20% of the ratio of the actual difference to the predicted value. Through targeted correction of these two core parameters, the prediction error of the electrochemical-thermal coupling model is gradually controlled within 5%, making subsequent electrothermal state predictions more accurate. This provides a reliable basis for generating more reasonable scheduling instructions in step S3, further improving the stability and adaptability of the entire power supply system.

[0053] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention, all of which fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A highly redundant, hot-swappable power supply system, characterized in that, include: The main power supply module consists of multiple sets of rechargeable batteries; The backup power supply module consists of multiple sets of rechargeable batteries or supercapacitors that support hot-swapping. The processing unit is communicatively connected to the main power supply module and the backup power supply module; The processing unit is configured to dynamically schedule the backup power supply module to participate in power supply by evaluating the health status of the battery cells in the main power supply module and predicting their future electrothermal status, so that the main power supply module operates within a predetermined optimized operating range.

2. The system according to claim 1, characterized in that, The system also includes a load interface for communicating with external electrical equipment; The processing unit receives the expected power demand information sent by the external electrical equipment through the load interface.

3. The system according to claim 1 or 2, characterized in that, The backup power supply module includes a power-type backup unit and an energy-type backup unit; The power-type backup unit is configured to respond to instantaneous peak power demand; The energy-type backup unit is configured to take over the main load or provide temperature-controlled energy to the main power supply module in extreme temperature environments.

4. A control method for the high redundancy, hot-swappable power supply system according to any one of claims 1-3, characterized in that, include: S1. Collect the internal and external status parameters of the power supply module. The internal status parameters include voltage, current, core temperature, and real-time internal resistance calculated by the pulse current method. The external parameters include ambient temperature and expected power demand profiles from external electrical equipment. S2. Based on the data collected in step S1, perform electrothermal status prediction and health status assessment, and obtain the corresponding assessment and prediction results. S3. Based on the evaluation and prediction results obtained in step S2, generate scheduling instructions through multiple decision logics; S4. Execute the scheduling instructions generated in step S3, and adjust the load distribution of each power supply module or perform module switching operations to make the main power supply module work within a predetermined optimized working range.

5. The method according to claim 4, characterized in that, Step S2 includes: S21. Health status assessment step: Based on the historical cycle count of the power supply module and the real-time internal resistance, calculate the health status value through a predefined aging model. The aging model is used to characterize the relationship between the health status value and the decrease in the number of cycles and the increase in internal resistance. S22. Electrothermal state prediction step: Based on the real-time voltage, current, core temperature and ambient temperature, calculations are performed using a preset electrochemical-thermal coupling model to output the predicted voltage and core temperature values ​​for a specific time period in the future. The electrochemical-thermal coupling model is used to characterize the interaction between the real-time voltage, current, core temperature and ambient temperature.

6. The method according to claim 5, characterized in that, Step S3 includes: S31. The health status value, voltage prediction value and core temperature prediction value obtained in step S2 are compared with the preset health status threshold, voltage stability threshold and temperature protection threshold, respectively. S32. Based on the comparison result obtained in step S31, execute at least one of health scheduling logic, thermal management scheduling logic, and power scheduling logic to generate a scheduling instruction, wherein: The health scheduling logic includes: when it is determined that the health status value of any battery cell in the main power supply circuit is lower than the health status threshold or its state of charge is lower than the power switching threshold, the cell is determined to be a weak cell, and a first scheduling instruction is generated to remove the weak cell from the main power supply circuit, and the battery cell with the largest product of health status value and state of charge value is selected from the backup power supply module and switched to the main power supply circuit. The thermal management scheduling logic includes: when the core temperature prediction value exceeds the temperature protection threshold or the ambient temperature change rate exceeds the preset ambient temperature change threshold, it is determined that there is a risk of thermal stress, and a second scheduling instruction is generated to schedule the energy-type backup unit in the backup power supply module to share the main load, so as to reduce the heat generation of the main power supply module, and at the same time start or adjust the working parameters of the active temperature control system. The power scheduling logic includes: when the expected power demand map contains instantaneous high power demand, it is determined that there is a risk of voltage drop, and a third scheduling instruction is generated to pre-connect the power type backup unit in the backup power supply module before the instantaneous high power demand arrives, and instruct it to take on most or all of the instantaneous power during peak load.

7. The method according to claim 6, characterized in that, The health scheduling logic also includes: Before generating the first scheduling instruction, it is determined whether there are battery cells in the backup power supply module whose health status value and state of charge product is greater than a preset product threshold. If it exists, then execute the first scheduling instruction; If it does not exist, a degradation scheduling instruction is generated to reduce the load demand of the main power supply module or trigger an alarm.

8. The method according to claim 6, characterized in that, The thermal management scheduling logic also includes: Before generating the second scheduling instruction, it is determined whether the available capacity of the energy-type backup unit is greater than a preset capacity threshold. If it is greater than that, then execute the second scheduling instruction; If the value is not greater than the specified value, an auxiliary temperature control command is generated to prioritize adjusting the operating parameters of the active temperature control system in order to reduce the heat generated by the main power supply module.

9. The method according to claim 6, characterized in that, The power scheduling logic also includes: Before generating the third scheduling instruction, it is determined whether the duration of the instantaneous high power demand exceeds a preset duration threshold. If the limit is exceeded, then the third scheduling instruction is executed; If the limit is not exceeded, a buffer scheduling instruction is generated, and the instantaneous power is shared by the main power supply module and the power-type backup unit.

10. The method according to claim 4, characterized in that, The method further includes: S5. Adaptive learning step: After step S4 is executed, record the voltage and temperature performance data of the power supply module under actual load and compare it with the predicted value of step S2. Based on the difference between the actual data and the predicted values, the parameters in the electrochemical-thermal coupling model are adjusted to reduce the error in future predictions; The adjustment includes: correcting the internal resistance parameter in the electrochemical-thermal coupling model when the difference between the actual voltage and the predicted voltage exceeds the voltage error threshold; and correcting the heat capacity parameter in the electrochemical-thermal coupling model when the difference between the actual temperature and the predicted temperature exceeds the temperature error threshold.

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