Battery overcharge and overdischarge safety guarantee system with cold plate liquid cooling and ai regulation

Abstract

This invention relates to the field of battery safety technology and discloses a battery overcharge and over-discharge safety protection system based on cold plate liquid cooling and AI regulation. The system's battery pack module consists of retired power battery cells connected in series and parallel, each cell equipped with temperature and voltage sensors. A two-phase cold plate liquid cooling heat dissipation module is attached to the battery pack surface to absorb heat using a cooling medium. A charge / discharge monitoring module connects to various sensors, preprocesses temperature, voltage, and current data to generate a real-time battery status dataset. A charge / discharge control module controls the on / off state of the circuit via a switch and regulates the charge / discharge current using a regulator. A central processing module has a built-in database of retired power battery characteristics, receives the real-time status dataset and heat dissipation module parameters, generates charge / discharge control commands and liquid cooling regulation commands, and outputs them to the charge / discharge control module and heat dissipation module, respectively. This achieves safety protection against overcharge and over-discharge of retired power batteries, adapts to the characteristics of retired batteries, and improves usage safety and lifespan.

Description

Technical Field

[0001] This invention relates to the field of battery safety technology, specifically to a battery overcharge and over-discharge safety protection system using cold plate liquid cooling and AI regulation. Background Technology

[0002] With the rapid development of the new energy industry, the demand for power batteries continues to grow, leading to a significant increase in the number of retired power batteries. While retired power batteries no longer meet the needs of high-end applications such as new energy vehicles, they still possess a certain amount of remaining capacity and value. Recycling and reusing them can reduce resource waste and environmental burden, making it a key focus of the industry. However, retired power batteries experience problems such as electrode material aging, electrolyte performance degradation, and increased internal impedance during long-term use, resulting in unstable electrochemical performance and a greater susceptibility to overcharging and over-discharging during charging and discharging.

[0003] Overcharging can easily lead to chemical reactions such as lithium plating and electrolyte decomposition inside the battery, potentially causing thermal runaway. Over-discharging, on the other hand, can damage the battery structure, shorten its lifespan, and even create safety hazards. To address these issues, current technologies typically employ battery status monitoring and charge / discharge control. However, traditional monitoring methods often only collect data on the overall temperature or voltage of the battery pack, making it difficult to accurately capture the real-time status of each individual battery cell. Furthermore, the performance differences between retired power battery cells are significant, and this overall monitoring approach is prone to missing abnormalities in individual cells, failing to provide timely warnings of overcharging and over-discharging risks.

[0004] In terms of heat dissipation, existing battery cooling solutions mainly include air cooling and traditional liquid cooling. Air cooling is greatly affected by ambient temperature and has low heat dissipation efficiency. When the battery pack generates a lot of heat, it is difficult to dissipate the heat quickly, which can easily lead to local overheating, exacerbating battery performance degradation and safety risks. Traditional liquid cooling mostly uses a single-phase cooling medium, and the heat dissipation structure does not fit well with the battery pack, resulting in limited heat exchange efficiency. It cannot dynamically adjust the heat dissipation capacity according to the real-time battery temperature, and its adaptability is poor for the large heat fluctuations of retired power batteries during charging and discharging.

[0005] Existing charge and discharge control systems lack specific design for the characteristics of retired power batteries. Their control strategies are mostly based on the performance parameters of new batteries, failing to consider the aging characteristics and remaining capacity differences of retired batteries. This results in inaccurate adjustment of charge and discharge current, either failing to fully utilize the remaining battery capacity or further exacerbating battery damage due to excessive current, increasing the probability of overcharging and over-discharging. Furthermore, in existing technologies, monitoring, heat dissipation, and control are often independent, lacking a coordinated mechanism. Monitoring data cannot guide timely and accurate adjustments to heat dissipation and control strategies. The heat dissipation effect and control precision are insufficient to meet the safety requirements of retired power batteries, hindering the large-scale promotion of retired power battery recycling and reuse. Summary of the Invention

[0006] The purpose of this invention is to provide a battery overcharge and over-discharge safety protection system with cold plate liquid cooling and AI regulation, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides a battery overcharge and over-discharge safety protection system with cold plate liquid cooling and AI regulation, the system comprising:

[0008] The battery pack module is composed of retired power battery cells connected in series and parallel. Each battery cell is equipped with a temperature sensor and a voltage sensor.

[0009] The two-phase cold plate liquid cooling heat dissipation module is closely attached to the surface of the battery pack module, and the cooling medium flowing inside it absorbs the heat generated by the battery pack module.

[0010] The charge / discharge monitoring module is connected to the temperature sensor, voltage sensor, and current sensor in the charge / discharge circuit of the battery pack module. It preprocesses the collected temperature data, voltage data, and charge / discharge current data to generate a real-time battery status dataset.

[0011] The charge / discharge control module includes a charging switch, a discharging switch, and a charge / discharge regulator. The charging switch controls the on / off state of the charging circuit, the discharging switch controls the on / off state of the discharging circuit, and the charge / discharge regulator dynamically adjusts the charge / discharge current value.

[0012] The central processing module has a built-in database of retired power battery characteristics. It receives the real-time battery status dataset output by the charge / discharge monitoring module and simultaneously acquires the cooling medium flow rate and temperature parameters of the two-phase cold plate liquid cooling heat dissipation module. Based on the real-time battery status dataset, cooling medium parameters, and retired power battery characteristic database, the central processing module generates charge / discharge control commands and liquid cooling regulation commands. The charge / discharge control commands are output to the charge / discharge control module, and the liquid cooling regulation commands are output to the two-phase cold plate liquid cooling heat dissipation module.

[0013] Preferably, the charge / discharge monitoring module performs charge / discharge voltage difference analysis on the collected voltage data, extracts the voltage fluctuation characteristics during the charge / discharge process, and generates a real-time voltage difference coefficient; at the same time, it calculates the cumulative charge based on the time integral of the charge / discharge current data, and generates a capacity decay factor by combining the rated capacity value in the retired power battery characteristic database.

[0014] Preferably, the charge / discharge monitoring module performs spatial distribution analysis on the temperature data, identifies the temperature gradient distribution of each cell in the battery pack module, and generates a temperature rise spatial distribution map; combined with the real-time differential pressure coefficient and capacity decay factor, it constructs a battery aging characteristic compensation value.

[0015] Preferably, the central processing module dynamically corrects the nominal internal resistance value in the retired power battery characteristic database based on the battery aging characteristic compensation value, and generates an estimated value of the actual internal resistance; at the same time, it calculates the heat dissipation efficiency coefficient based on the cooling medium flow rate and temperature parameters, and generates a thermal runaway risk level by combining the highest temperature value in the real-time battery status data set.

[0016] Preferably, the central processing module inputs the actual internal resistance estimate, heat dissipation efficiency coefficient, and thermal runaway risk level into the multi-source fusion decision unit, and generates a battery safety operation index through weighted superposition; when the battery safety operation index exceeds a preset threshold, a charge / discharge current limiting command is generated and output to the charge / discharge control module.

[0017] Preferably, the multi-source fusion decision unit performs regional segmentation on the temperature rise spatial distribution map and identifies the coordinates of high-temperature accumulation areas; combined with the cooling channel distribution topology of the two-phase cold plate liquid cooling heat dissipation module, it generates liquid cooling zone control parameters, which include the medium flow rate adjustment amount for each channel region.

[0018] Preferably, the central processing module generates a dynamic liquid cooling strategy based on the liquid cooling zone control parameters and the thermal runaway risk level; the dynamic liquid cooling strategy includes a total cooling medium flow rate setpoint and a zone flow rate ratio coefficient, and is output to the actuator of the two-phase cold plate liquid cooling heat dissipation module.

[0019] Preferably, after receiving the charge / discharge current limiting command, the charge / discharge control module reduces the charge / discharge current value through the charge / discharge regulator; at the same time, it calculates the charge / discharge cutoff voltage correction amount based on the capacity decay factor and the real-time voltage difference coefficient, and dynamically adjusts the voltage protection threshold of the charge / discharge circuit.

[0020] Preferably, the central processing module continuously acquires the adjusted charge and discharge current values ​​and voltage protection thresholds, and combines them with the actual medium flow execution data fed back by the two-phase cold plate liquid cooling heat dissipation module to generate a system status verification vector; the system status verification vector is used to update the historical operating parameters in the retired power battery characteristic database.

[0021] Preferably, the multi-source fusion decision unit performs iterative optimization of charge and discharge control commands based on the system state verification vector and the latest battery safety operation index, and generates adaptive control parameters; the adaptive control parameters are synchronously output to the control logic units of the charge and discharge control module and the two-phase cold plate liquid cooling heat dissipation module.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] This cold-plate liquid cooling and AI-controlled battery overcharge and over-discharge safety protection system provides a comprehensive and efficient solution for the safe use of retired power batteries through the synergistic effect of its various modules. Within the battery pack module, each retired power battery cell is equipped with a temperature sensor and a voltage sensor, enabling precise monitoring of the individual cell's status. Compared to traditional monitoring methods that only target the entire battery pack, this system can more promptly detect temperature anomalies or voltage fluctuations at the cell level, preventing the risk of localized overcharge and over-discharge due to differences in cell performance from being overlooked. This improves the detail and accuracy of battery status perception from the source of monitoring.

[0024] The two-phase liquid-cooled heat dissipation module is tightly attached to the surface of the battery pack module. This structural design maximizes the contact area between the heat dissipation module and the battery pack, ensuring efficient heat exchange between the cooling medium and the battery. Simultaneously, the two-phase cooling medium possesses superior heat capacity and heat exchange efficiency, enabling it to quickly absorb the heat generated by the battery pack during charging and discharging. Especially in scenarios where retired power batteries experience increased heat generation due to increased internal resistance, it effectively controls the battery temperature to remain stable within a safe range. Furthermore, this heat dissipation module can adjust the flow rate and temperature of the cooling medium according to liquid cooling control commands output from the subsequent central processing module. This breaks through the limitations of traditional heat dissipation methods with fixed heat dissipation capacity, achieving dynamic matching between heat dissipation capacity and battery heat generation, avoiding energy waste caused by excessive heat dissipation or safety hazards caused by insufficient heat dissipation.

[0025] The charge / discharge monitoring module connects to various sensors in the battery pack and current sensors in the charge / discharge circuit. It preprocesses the collected temperature, voltage, and current data to generate a real-time battery status dataset. This data preprocessing filters out interference from the raw data, improving data accuracy and providing a reliable data foundation for subsequent analysis and decision-making by the central processing module, avoiding control deviations caused by data errors. The charge / discharge control module includes a charging switch, a discharging switch, and a charge / discharge regulator, which can respectively control the on / off state of the charge / discharge circuit and dynamically adjust the charge / discharge current value. Compared to traditional simple on / off control, its control dimensions are richer, enabling refined management of the charge / discharge process based on the real-time battery status. For example, when the battery voltage approaches the overcharge threshold, the charge / discharge regulator gradually reduces the charging current instead of directly cutting off the charging circuit, ensuring safety while fully utilizing the remaining battery capacity.

[0026] The central processing module incorporates a database of retired power battery characteristics. This database contains performance parameters and safety thresholds of retired power batteries under different aging levels and temperature environments, providing targeted reference for system regulation and solving the problem of insufficient adaptability caused by traditional control strategies that do not consider the characteristics of retired batteries. The central processing module receives real-time status datasets from the charge / discharge monitoring module and simultaneously acquires the cooling medium parameters of the heat dissipation module. By comprehensively analyzing this information and combining it with the characteristic data in the database, it generates precise charge / discharge control commands and liquid cooling regulation commands, achieving coordinated linkage between monitoring, heat dissipation, and control.

[0027] When the system detects an increase in battery temperature, the central processing module can simultaneously send instructions to the charge / discharge control module to reduce the charge / discharge current, thereby reducing battery heat generation, and to the heat dissipation module to increase the flow rate of the cooling medium, enhancing heat dissipation capacity. This bidirectional regulation quickly suppresses the temperature rise. When an abnormal battery voltage is detected, the system can promptly control the on / off state of the charge / discharge circuit and adjust the heat dissipation strategy to prevent further deterioration of the battery temperature under abnormal conditions. This multi-module collaborative control mode enables the system to address the risks of overcharging and over-discharging from both the perspectives of heat generation control and enhanced heat dissipation, forming a complete safety assurance closed loop. This not only effectively reduces the probability of safety accidents during the use of retired power batteries, but also slows down the performance degradation rate of retired batteries and extends their secondary service life through refined charge / discharge control and temperature management. This enhances the economic value and environmental benefits of recycling and reusing retired power batteries, promoting the healthy development of the retired power battery resource utilization industry. Attached Figure Description

[0028] Figure 1 This is a timing diagram of the battery overcharge and over-discharge safety protection system with cold plate liquid cooling and AI control described in this invention.

[0029] Figure 2 A flowchart for analyzing temperature data from the charge / discharge monitoring module and constructing battery aging characteristic compensation values;

[0030] Figure 3 A flowchart for generating the internal resistance correction and thermal runaway risk level of the central processing module;

[0031] Figure 4 A flowchart for generating liquid-cooled partition control parameters for a multi-source fusion decision unit. Detailed Implementation

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

[0033] Please see Figure 1 This invention provides a battery overcharge and over-discharge safety protection system with cold plate liquid cooling and AI regulation. The system is composed of a battery pack module, a two-phase cold plate liquid cooling heat dissipation module, a charge and discharge monitoring module, a charge and discharge control module, and a central processing module.

[0034] The battery pack module is composed of retired power battery cells recombined in series and parallel. Each battery cell has a temperature sensor and a voltage sensor tightly installed on its surface to directly collect the physical state parameters of the battery cell.

[0035] The two-phase cold plate liquid cooling heat dissipation module maintains close contact with the surface of the battery pack module through thermally conductive materials, and the cooling medium circulating in its internal flow channel continuously absorbs the heat generated by the battery pack during operation through the principle of phase change heat absorption.

[0036] The charge / discharge monitoring module is electrically connected to the temperature sensor, voltage sensor, and current sensor embedded in the charge / discharge circuit of the battery cell. The module filters, calibrates, and normalizes the collected raw temperature data, voltage data, and charge / discharge current data, and then generates a real-time battery status dataset containing timestamps.

[0037] The charge and discharge control module consists of a charging switch, a discharging switch, and a charge and discharge regulator. The charging switch is connected in series in the charging circuit to control its on and off state, the discharging switch is connected in series in the discharging circuit to control its on and off state, and the charge and discharge regulator dynamically adjusts the current value in the circuit through power semiconductor devices.

[0038] The central processing module has a built-in database of retired power battery characteristics, which stores the historical performance parameters and nominal characteristic values ​​of individual battery cells. The central processing module receives real-time battery status datasets from the charge / discharge monitoring module and simultaneously obtains real-time flow and temperature parameters of the cooling medium from the flow meter and temperature sensor of the two-phase cold plate liquid cooling heat dissipation module. The central processing module calls the built-in algorithm model to analyze and make decisions based on the input real-time battery status dataset, cooling medium parameters, and reference data in the retired power battery characteristic database, generating two types of instructions: charge / discharge control instructions are sent to the charge / discharge control module, and liquid cooling regulation instructions are sent to the flow control valve and pump mechanism of the two-phase cold plate liquid cooling heat dissipation module.

[0039] Example 1: This example involves the construction of a battery pack module, sensor configuration, data acquisition and processing, and the calculation and transmission of key derived parameters. The battery pack module is composed of multiple retired power battery cells connected in series and parallel to form a complete battery unit with the required voltage and capacity output. When each battery cell is integrated into the module, a temperature sensor and a voltage sensor are mounted on its physical surface. The temperature sensor is typically a surface-mount thermistor or thermocouple, and its installation must ensure good thermal contact with the battery casing surface to accurately sense changes in battery temperature. The voltage sensor is connected directly to the positive and negative electrodes of the battery cell via high-impedance wires to monitor its terminal voltage. All these sensor wires are bundled into a unified wiring harness and connected to the data acquisition unit of the charge / discharge monitoring module.

[0040] The core of the charge / discharge monitoring module is a multi-channel data acquisition system, which internally includes signal conditioning circuitry, an analog-to-digital converter (ADC), and a microprocessor. This module continuously reads analog signals from temperature and voltage sensors. These analog signals are first processed by the signal conditioning circuitry, including filtering to eliminate high-frequency noise, scaling to adjust the signal amplitude to the ADC's optimal operating range, and, in some cases, cold junction compensation for thermocouple signals. The conditioned signals are then converted into digital values ​​by the ADC. Simultaneously, the module also acquires an analog signal of the charge / discharge current from a precision current sensor (such as a Hall effect sensor) connected in series in the main charge / discharge circuit; this signal is also conditioned and digitized.

[0041] These digitized voltage, current, and temperature readings are received by a microprocessor. The microprocessor executes preprocessing algorithms, including applying digital filters to the raw data to further smooth it, checking for data outside reasonable ranges and marking them accordingly, and standardizing all data to a uniform timestamp and numerical range. After these preprocessing steps, the microprocessor packages the data to generate a real-time battery status dataset. This dataset is a structured collection containing the serial number of each battery cell, its corresponding temperature and voltage values, the total current value of the entire battery pack, and a precise timestamp.

[0042] Building upon this, the microprocessor in the charge / discharge monitoring module performs further analysis and calculations to generate two key derived parameters: the real-time differential voltage coefficient and the capacity decay factor. The real-time differential voltage coefficient is calculated based on the acquired voltage data. The microprocessor analyzes the voltage changes throughout a complete charge / discharge cycle, identifying key points such as the charging start voltage, charging cut-off voltage, discharging start voltage, and discharging cut-off voltage. By calculating the voltage differences between these characteristic points and analyzing the slope changes of the voltage curves during constant-current charging or discharging, the microprocessor extracts voltage fluctuation characteristics that reflect the degree of polarization and changes in the state of active materials within the battery. These characteristics are then combined into a dimensionless coefficient, the real-time differential voltage coefficient. An increase in this coefficient typically indicates an increase in resistance to chemical reactions within the battery.

[0043] The calculation of the capacity decay factor relies on the processing of current data. The microprocessor performs time integration on the current value, continuously multiplying the current value (amperes) by the sampling time interval (hours) and accumulating these products. This calculation yields the total ampere-hours accumulated since the last reset point, i.e., the accumulated charge. The microprocessor accesses the initial rated capacity (ampere-hours) of the battery cell, either issued by the central processing module or stored locally. The capacity decay factor is calculated by comparing the accumulated charge with the rated capacity. In actual operation, the current actual capacity is typically determined by the total ampere-hours released in a complete discharge cycle; the ratio of this actual capacity to the rated capacity is the capacity decay factor. A factor of 1 indicates no capacity decay, while a value less than 1 indicates that capacity decay has occurred.

[0044] The battery real-time status dataset has been expanded to include the calculated real-time differential pressure coefficient and capacity degradation factor. The charge / discharge monitoring module periodically sends this complete real-time battery status dataset to the central processing module via its communication interface (such as CAN bus or Ethernet). The central processing module receives this dataset and compares and analyzes it with historical data and behavioral models in the built-in database of retired power battery characteristics, providing crucial real-time input for subsequent comprehensive decision-making and control of the system. The entire process begins with physical signal sensing, undergoes multiple stages of signal conversion and data processing, and ultimately generates high-value information parameters, demonstrating the transformation of data from the bottom layer to the top layer, and from the raw to the abstract.

[0045] Example 2: See Figure 2 and Figure 3This embodiment involves in-depth analysis of the battery temperature field distribution, multi-parameter fusion calculation, and the calculation of key safety parameters by the central processing module based on this data. The process begins with the charge / discharge monitoring module processing the collected temperature data. The module's microprocessor has a built-in spatial distribution analysis algorithm, which first acquires the physical layout information of the battery pack module, including the three-dimensional coordinates of each battery cell. This coordinate information is defined and stored during system initialization. The microprocessor binds the values ​​read by each temperature sensor to their corresponding battery cell coordinates, forming a discrete set of data points containing both spatial location and temperature value.

[0046] Since sensors can only acquire temperature data at a limited number of points, the microprocessor performs spatial interpolation calculations to obtain the continuous temperature field distribution throughout the entire battery module. This calculation process estimates the temperature of areas without sensors using mathematical methods based on known discrete temperature values. Common interpolation methods include nearest neighbor interpolation, linear interpolation, or Kriging interpolation. Using these algorithms, the microprocessor generates a virtual three-dimensional temperature model covering the entire battery module volume, composed of numerous small grid cells. Each grid cell is assigned a calculated temperature value.

[0047] Based on this three-dimensional temperature model, the microprocessor further analyzes its temperature distribution characteristics. It calculates the temperature difference between adjacent grid cells, thereby identifying the severity and direction of temperature changes. By tracing the trajectory of temperature changes, the isothermal surfaces and heat flow paths within the battery module can be depicted. The temperature gradient distribution is quantified, typically described by parameters such as the maximum temperature gradient value, the average temperature gradient, and the rate of temperature change in a specific direction. All this spatial temperature information is comprehensively encoded to generate a digital spatial temperature distribution map. This map is essentially a multi-dimensional array, where the index corresponds to spatial grid coordinates, and the array values ​​correspond to the temperature and its derived properties at that location.

[0048] While generating the temperature rise spatial distribution map, the microprocessor of the charge / discharge monitoring module accesses the previously calculated real-time differential pressure coefficient and capacity degradation factor. It performs a data fusion process, combining these three different dimensions of parameters: spatial temperature distribution, voltage polarization characteristics, and capacity degradation degree. The fusion algorithm may employ a weighted summation method, assigning a weight to each input parameter, which may be determined based on battery chemical characteristics or historical operating experience. It may also employ a more complex nonlinear function mapping. Through this calculation process, a comprehensive index is generated: the battery aging characteristic compensation value. This value is a composite parameter designed to comprehensively reflect the various performance change trends caused by battery aging, including the degradation of thermal and electrochemical characteristics, in a single numerical value.

[0049] The central processing module receives data transmitted from the charge / discharge monitoring module, including a temperature rise spatial distribution map and battery aging characteristic compensation values. The central processing module accesses its built-in database of retired power battery characteristics, which stores the nominal parameters of various battery models in their new condition, including nominal internal resistance values. The application algorithm of the central processing module uses the received battery aging characteristic compensation values ​​as a correction factor to adjust the nominal internal resistance value. This correction is not a simple addition or subtraction, but rather a function calculation related to the compensation value, aiming to make the internal resistance value more accurately reflect the actual internal resistance changes caused by aging cycles and operating conditions. The calculated result is named the actual internal resistance estimate, which is a dynamically updated parameter that more closely reflects the battery's actual state.

[0050] The central processing module synchronously processes real-time cooling medium parameters obtained from the two-phase cold plate liquid cooling module, namely the temperature and flow rate of the medium flowing into the cold plate. Based on these parameters and the known characteristics of the cold plate system (such as channel geometry, material thermal conductivity, and specific heat capacity of the medium), the central processing module calculates a heat dissipation efficiency coefficient. This coefficient characterizes the ability of the current cooling system to remove heat from the battery module, and its value is affected by factors such as medium flow rate, inlet temperature, and thermal resistance between the cold plate and the battery.

[0051] The central processing module incorporates the instantaneous highest temperature value from the battery's real-time status dataset, the calculated estimated actual internal resistance, and the heat dissipation efficiency coefficient into the risk assessment logic. This logic may be a rule-based system or a simple lookup table. It compares the highest temperature value with a series of temperature thresholds, while considering the balance between actual internal resistance (reflecting the heat generation rate) and heat dissipation efficiency (reflecting heat dissipation capacity). Through comprehensive judgment, the assessment logic outputs a discrete level index, namely the thermal runaway risk level. This level indicates the current likelihood of thermal runaway in the system; a higher level indicates a greater risk.

[0052] Example 3: See Figure 4 This embodiment focuses on how the multi-source fusion decision unit within the central processing module collaboratively processes multiple heterogeneous data sources and generates a comprehensive safety index and precise spatial control instructions. The process begins with the central processing module inputting its calculated estimated internal resistance, heat dissipation efficiency coefficient, and thermal runaway risk level into its dedicated multi-source fusion decision unit. The core function of this unit is to integrate different dimensional parameters characterizing the battery's electrical state, thermal management effectiveness, and risk level into a unified, quantifiable safety index.

[0053] To achieve this fusion, the multi-source fusion decision unit assigns a dynamic weight coefficient to each input parameter. This weight is not fixed; its assignment logic depends on the parameter's numerical range and its relative impact on the overall safety status. For example, when the thermal runaway risk level is high, its weight may be increased accordingly. The fusion calculation is performed through a weighting function, and its output is a scalar value called the Battery Safety Operation Index (BSOI). The formula for calculating this index can be expressed as:

[0054]

[0055] In this formula: This represents the final calculated battery safety operation index. This represents the estimated actual internal resistance. An increase in this value usually means increased resistance to chemical reactions inside the battery, increased heat generation, and a negative impact on safety. This represents the heat dissipation efficiency coefficient. An increase in its value indicates that the cooling system is performing well and makes a positive contribution to safety. It represents the risk level of thermal runaway and is a discrete value obtained by mapping according to rules. The higher the level, the greater the risk. , , These are the dynamic weighting coefficients assigned to the three parameters mentioned above, which together determine the contribution ratio of each parameter to the final safety index.

[0056] This battery safety operation index is designed to comprehensively reflect the current safety status of the system. A safety threshold is preset within the system. The decision-making unit will calculate in real time... Value and Perform continuous comparisons. When detected... When this occurs, it indicates that the overall safety status of the system has exceeded the acceptable range, posing a potential risk. At this point, the multi-source fusion decision unit will immediately generate a charge / discharge current limiting command. This command contains a proposed new current limit and is output to the charge / discharge control module via the internal communication bus, requiring it to perform current regulation.

[0057] On the parallel path, the multi-source fusion decision unit also performs in-depth analysis of the temperature rise spatial distribution map transmitted from the charge / discharge monitoring module. This analysis involves image processing and pattern recognition technologies. The algorithm within the unit performs region segmentation on the temperature distribution data, aiming to identify local hotspots in the map where the temperature is significantly higher than the surrounding areas, i.e., high-temperature clustering regions. The segmentation algorithm may be based on a set temperature threshold or may employ more complex clustering analysis methods to identify abnormally high-temperature regions. Once these regions are identified, the algorithm further calculates and records their geometric center coordinates or coverage area coordinates.

[0058] Next, the decision unit accesses the cooling channel distribution topology map of the two-phase cold plate liquid cooling heat dissipation module stored therein. This topology map is a digital model that defines in detail the physical layout of the cooling medium channels, the division of each independent controllable channel region, and the cooling correspondence between each region and different parts of the battery pack module. The decision unit performs a matching analysis process: overlaying and associating the coordinates of the identified high-temperature accumulation areas with the cooling channel distribution topology map to determine which specific channel regions are responsible for cooling these hot spots.

[0059] Based on this correlation analysis, the decision-making unit generates a set of liquid cooling zone control parameters. These parameters are specific control commands, the core of which is to specify the adjustment amount of the cooling medium flow rate for the identified specific flow channel areas that require enhanced cooling. The adjustment amount is usually expressed as a percentage or absolute change in flow rate. For example, the command may require the flow rate in a certain area to increase by a certain percentage, while the flow rate in other areas with normal temperatures remains unchanged or slightly decreases, in order to achieve precise on-demand allocation of cooling capacity.

[0060] Example 4: This example details the collaborative control and dynamic adjustment process between the central processing module, the two-phase cold plate liquid cooling module, and the charge / discharge control module. This process is illustrated with a specific example: Assume a battery pack module composed of multiple retired battery cells is under high-current discharge conditions. The charge / discharge monitoring module continuously collects data. The multi-source fusion decision unit within the central processing module calculates based on real-time data that the battery safety operation index has exceeded a preset threshold. Simultaneously, it identifies a high-temperature accumulation zone in the northeast quadrant of the battery pack module, and its coordinates are precisely recorded.

[0061] The central processing module (CPU) first handles the generation of thermal management instructions. It receives liquid cooling zone control parameters from the multi-source fusion decision unit, which explicitly indicate the need to increase the medium flow rate in specific cooling channels serving the northeast quadrant of the battery pack. Simultaneously, the CPU independently assesses the current thermal runaway risk level as "medium." Based on these two inputs, the CPU's algorithm generates a dynamic liquid cooling strategy. This strategy includes instructions at two levels: First, a system-level total cooling medium flow rate setpoint. Due to the "medium" risk level, the algorithm determines to increase the total flow rate by a percentage above the base flow rate. Second, detailed zone flow rate allocation coefficients. This coefficient matrix specifies the distribution ratio of the total flow rate among the various independently controllable channels. For channels corresponding to identified high-temperature accumulation areas, the allocation ratio is significantly increased; while for other channels with normal temperatures, the allocation ratio is maintained or slightly reduced accordingly, ensuring that, with the increased total flow rate, cooling capacity is prioritized and precisely directed to the most needed areas. This complete dynamic liquid cooling strategy is output to the actuator of the two-phase cold plate liquid cooling module via a digital communication interface. The actuator includes a variable frequency pump and multiple zone flow control valves. The variable frequency pump receives a total flow setpoint command and adjusts its speed to change the total amount of media circulating in the entire system. Simultaneously, each zone flow control valve receives its corresponding flow distribution coefficient and adjusts its opening to distribute the total flow proportionally to each cooling channel. In this example, the flow control valve serving the northeast quadrant of the battery pack has an increased opening, allowing more cooling medium to flow through the cold plates in that area, thus specifically enhancing heat dissipation in this hot spot region.

[0062] Simultaneously with generating the liquid cooling regulation command, the central processing module also generates a charge / discharge control command. This command is also output to the charge / discharge control module. Upon receiving the charge / discharge current limiting command from the central processing module, the charge / discharge control module's internal microcontroller immediately takes action. It uses a charge / discharge regulator (typically a circuit composed of power semiconductor devices) to reduce the current value in the discharge loop. The current regulation process is not instantaneous but employs a gradual closed-loop control method to smoothly reduce the current value to the new limit required by the command, avoiding shocks to the battery and load caused by sudden current changes.

[0063] The execution logic of the charge / discharge control module also initiates another calculation. It calls upon the capacity decay factor and real-time differential voltage coefficient provided by the charge / discharge monitoring module. The capacity decay factor reflects the degree to which the battery's current actual capacity decreases relative to its initial nominal capacity. The real-time differential voltage coefficient reflects the magnitude of the battery's polarization voltage during charge / discharge; an increase in its value leads to a change in the effective operating voltage window. Using these two parameters, the charge / discharge control module dynamically calculates a safer charge / discharge cutoff voltage correction for the current cycle through an internally preset algorithm model. For example, for a battery with decayed capacity, its full-charge voltage threshold may need to be appropriately lowered; for a battery with increased polarization voltage difference, its discharge cutoff voltage may need to be appropriately increased to prevent over-discharge. After calculating the new voltage threshold, the charge / discharge control module dynamically adjusts the trigger settings of its internal voltage protection relays or voltage monitoring ICs, thereby updating the voltage protection threshold of the entire charge / discharge circuit.

[0064] The system, through the aforementioned implementation, demonstrates a multi-dimensional collaborative control: on one hand, the liquid cooling system receives precise spatial zoning flow allocation commands, focusing on cooling localized overheated areas; on the other hand, the electrical system receives current and voltage protection threshold adjustment commands, reducing the overall electrical load and heat generation rate of the system, and adapting to the aging state of the battery. These two control actions are not performed in isolation, but are simultaneously issued by the central processing module based on a unified assessment of the system state, working together to address any abnormal operating conditions that may arise in the battery system.

[0065] Example 5: This example illustrates the complete closed-loop process by which the system continuously verifies, learns, and iteratively optimizes its own state after executing control commands. This process begins with the central processing module actively collecting feedback data from various execution endpoints of the system. It sends a data request to the charge / discharge control module via the communication bus to obtain the adjusted actual charge / discharge current value. This current value is the actual current present in the loop after the charge / discharge regulator executes the current-limiting command, measured by a high-precision current sensor. Simultaneously, the central processing module obtains the currently effective voltage protection threshold of the charge / discharge control module. This threshold is a dynamically corrected new value used to determine the termination condition of the charge / discharge process. Furthermore, the central processing module sends a query command to the actuator of the two-phase cold plate liquid cooling module to obtain the actual opening feedback of the flow control valves in each zone and the actual speed feedback of the variable frequency pump. These data are converted to obtain the total flow rate of the cooling medium circulating in the system and the flow execution data of each zone.

[0066] Feedback data from different subsystems, marked with time synchronization, are transmitted to the central processing module. The module's internal data processing unit aligns and packages these heterogeneous data sources, combining them into a system state verification vector. This vector is a structured dataset whose elements include: actual current value, actual voltage protection threshold, actual total cooling flow rate, actual cooling flow rate of each zone, and key battery pack state parameters (such as maximum temperature) at the corresponding time point. This vector is not simply a list of data, but rather represents a real, instantaneous operating state point reached by the entire system under the action of a specific set of control commands.

[0067] One of the core functions of the central processing module is to learn and update using this system state verification vector. It compares and analyzes the actual execution results (such as actual cooling flow) contained in the vector with previously issued control commands (such as commanded flow rate setpoints), calculates the execution deviation, and evaluates the degree of achievement of the control commands. More importantly, it correlates the system's response results (such as the rate of battery temperature change after current reduction and the capacity utilization rate after voltage threshold adjustment) with the expected safety goals. All these analysis results, including execution deviations, system response characteristics, and a complete snapshot of the operating state point, are used to update the historical operating parameter records in the retired power battery characteristic database. This transforms the database from a static initial data set into a continuously evolving and enriched knowledge base that records the real behavioral characteristics of a specific battery pack under different operating conditions and control strategies, providing a more realistic reference for future decision-making.

[0068] The multi-source fusion decision unit acts as an optimization engine in this process. It receives the latest system state verification vector and combines it with the recalculated latest battery safety operating index. This recalculation is based on the latest system state data, reflecting new changes in the system safety level after executing the previous round of control commands. The decision unit performs an iterative optimization process: it analyzes the actual effects of previous control commands and evaluates their effectiveness in improving the safety index. For example, it determines whether the current current limiting magnitude and cooling intensity combination is sufficient to suppress the safety index below the threshold, or whether it overreacts and unnecessarily limits system performance. Based on this evaluation, the optimization algorithm generates a new set of modified control parameters, i.e., adaptive control parameters. This set of parameters may include fine-tuned current limits, further optimized voltage protection thresholds, and finely adjusted cooling flow rate setpoints and zoning ratios.

[0069] Ultimately, these adaptive control parameters are synchronously output to the control logic units of the charge / discharge control module and the two-phase cold plate liquid cooling module. The charge / discharge control module readjusts its operating setpoint based on the new current and voltage parameters, while the two-phase cold plate liquid cooling module adjusts its pump speed and valve opening according to the new flow command. This completes a full "monitoring-decision-control-verification-learning-optimization" closed loop. By continuously operating this closed loop, the system can constantly adapt to changes in the battery's own state (such as accelerated aging) and changes in external operating conditions (such as fluctuations in ambient temperature), allowing the control strategy to dynamically evolve and gradually approach the optimal balance between safety and economy under current conditions, exhibiting a self-learning and self-adjusting intelligent characteristic.

[0070] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0071] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A battery overcharge and over-discharge safety protection system based on cold plate liquid cooling and multi-element integrated decision control, characterized in that, include: The battery pack module is composed of retired power battery cells connected in series and parallel. Each battery cell is equipped with a temperature sensor and a voltage sensor. The two-phase cold plate liquid cooling heat dissipation module is closely attached to the surface of the battery pack module, and the cooling medium flowing inside it absorbs the heat generated by the battery pack module. The charge / discharge monitoring module is connected to the temperature sensor, voltage sensor, and current sensor in the charge / discharge circuit of the battery pack module. It preprocesses the collected temperature data, voltage data, and charge / discharge current data to generate a real-time battery status dataset. The charge and discharge monitoring module performs charge and discharge voltage difference analysis on the collected voltage data, extracts the voltage fluctuation characteristics during the charge and discharge process, and generates a real-time voltage difference coefficient; at the same time, it calculates the cumulative charge based on the time integral of the charge and discharge current data, and generates a capacity decay factor by combining the rated capacity value in the retired power battery characteristic database. The charge / discharge monitoring module performs spatial distribution analysis on the temperature data, identifies the temperature gradient distribution of each cell in the battery pack module, and generates a temperature rise spatial distribution map; it also combines the real-time differential pressure coefficient and capacity decay factor to construct a battery aging characteristic compensation value. The charge / discharge control module includes a charging switch, a discharging switch, and a charge / discharge regulator. The charging switch controls the on / off state of the charging circuit, the discharging switch controls the on / off state of the discharging circuit, and the charge / discharge regulator dynamically adjusts the charge / discharge current value. The central processing module, with a built-in database of retired power battery characteristics, receives the real-time battery status dataset output by the charge / discharge monitoring module and simultaneously acquires the cooling medium flow rate and temperature parameters of the two-phase cold plate liquid cooling heat dissipation module. Based on the real-time battery status dataset, cooling medium parameters, and the retired power battery characteristic database, the central processing module generates charge / discharge control commands and liquid cooling regulation commands. The charge / discharge control commands are output to the charge / discharge control module, and the liquid cooling regulation commands are output to the two-phase cold plate liquid cooling heat dissipation module. Based on the battery aging characteristic compensation value, the central processing module dynamically corrects the nominal internal resistance value in the retired power battery characteristic database to generate an estimated actual internal resistance value. Simultaneously, it calculates the heat dissipation efficiency coefficient based on the cooling medium flow rate and temperature parameters, and, combined with the highest temperature value in the real-time battery status dataset, generates a thermal runaway risk level. The central processing module inputs the actual internal resistance estimate, heat dissipation efficiency coefficient and thermal runaway risk level into the multi-source fusion decision unit, and generates a battery safety operation index by weighted superposition. When the battery safety operation index exceeds the preset threshold, the multi-source fusion decision unit generates a charge and discharge current limiting command and outputs it to the charge and discharge control module.

2. The battery overcharge and over-discharge safety assurance system based on cold plate liquid cooling and multi-element integrated decision control according to claim 1, characterized in that, The multi-source fusion decision unit divides the temperature rise spatial distribution map into regions and identifies the coordinates of high-temperature accumulation areas; combined with the cooling channel distribution topology of the two-phase cold plate liquid cooling heat dissipation module, it generates liquid cooling zone control parameters, which include the medium flow rate adjustment amount of each channel region.

3. The battery overcharge and over-discharge safety assurance system based on cold plate liquid cooling and multi-element integrated decision control according to claim 2, characterized in that, The central processing module generates a dynamic liquid cooling strategy based on the liquid cooling zone control parameters and the thermal runaway risk level. The dynamic liquid cooling strategy includes the total flow rate setting value of the cooling medium and the zone flow rate ratio coefficient, and is output to the actuator of the two-phase cold plate liquid cooling heat dissipation module.

4. The battery overcharge and over-discharge safety assurance system based on cold plate liquid cooling and multi-element integrated decision control according to claim 3, characterized in that, After receiving the charge / discharge current limiting command, the charge / discharge control module reduces the charge / discharge current value through the charge / discharge regulator; at the same time, it calculates the charge / discharge cutoff voltage correction amount based on the capacity decay factor and the real-time voltage difference coefficient, and dynamically adjusts the voltage protection threshold of the charge / discharge circuit.

5. The battery overcharge and over-discharge safety protection system based on cold plate liquid cooling and multi-element integrated decision control according to claim 4, characterized in that, The central processing module continuously acquires the adjusted charge and discharge current values ​​and voltage protection thresholds, and combines them with the actual medium flow execution data fed back by the two-phase cold plate liquid cooling heat dissipation module to generate a system status verification vector; the system status verification vector is used to update the historical operating parameters in the retired power battery characteristic database.

6. The battery overcharge and over-discharge safety assurance system based on cold plate liquid cooling and multi-element integrated decision control according to claim 5, characterized in that, The multi-source fusion decision unit performs iterative optimization of charge and discharge control commands based on the system state verification vector and the latest battery safety operation index, and generates adaptive control parameters; the adaptive control parameters are synchronously output to the control logic units of the charge and discharge control module and the two-phase cold plate liquid cooling heat dissipation module.

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