Intelligent voltage-regulated battery output current control method and system

Abstract

The present invention relates to the field of battery management and discloses a method and system for intelligent voltage-regulated battery output current control. The method comprises: first obtaining the load demand corresponding to the test battery and determining its application conditions; setting an initial regulation voltage to create a simulated control environment; monitoring real-time current; calculating current deviation values under different operating conditions; formulating a voltage regulation strategy based on this; conducting multiple rounds of load testing; and calculating the current load index to build an efficiency control system. This system is then used to analyze discharge response effects, query voltage change trends, and identify core change factors. Subsequently, an intelligent feedback regulation unit is connected to the test battery to form a group, dynamic operating current data is collected, controllable current nodes are screened, and finally a current control scheme adapted to the test battery is generated. The present invention can improve the control efficiency of battery output current.

Description

Technical Field

[0001] The present invention relates to an intelligent voltage-regulated battery output current control method and system, belonging to the field of battery management. Background Art

[0002] In today's electronic devices and new energy applications, batteries, as core energy supply components, play a vital role in the stability and precise control of their output current. Whether it is portable consumer electronics such as smartphones and tablets, or large-scale application scenarios such as electric vehicles and distributed energy storage systems, the effective control of battery output current is directly related to the performance, service life and operational safety of the equipment.

[0003] At present, traditional battery output current control methods mostly adopt relatively simple and direct fixed resistor current limiting or rough voltage feedback regulation. On the one hand, fixed current limiting resistors or primary voltage regulation strategies lack adaptability and dynamic adjustment capabilities when facing different load requirements, battery aging status, and complex and changeable working environment temperatures. For example, in the multi-tasking and high-power discharge scenarios of smartphones, the fixed current control method cannot flexibly adjust the output current in time according to power consumption and dynamic changes in chip load, which can easily cause device lag, heat, and even rapid battery life degradation; on the other hand, rough voltage feedback regulation makes it difficult to accurately track the real-time internal resistance changes and charge and discharge characteristic curve fluctuations of the battery. Especially when electric vehicles frequently accelerate and brake, the battery output current cannot be accurately controlled, which not only affects the smoothness of power output, but also may endanger the safety of the battery system due to the risk of overcharging and over-discharging. Therefore, an intelligent voltage-regulated battery output current control method is needed to improve the control efficiency of battery output current. Summary of the Invention

[0004] The present invention provides an intelligent voltage-regulated battery output current control method and system, the main purpose of which is to improve the control efficiency of the battery output current.

[0005] To achieve the above objectives, the present invention provides an intelligent voltage-regulated battery output current control method, comprising:

[0006] Obtaining load demand information corresponding to a test battery, analyzing an application scenario corresponding to the test battery based on the load demand information, setting an initial regulation voltage adapted for the test battery based on the application scenario, and constructing a simulated control environment corresponding to the test battery based on the initial regulation voltage;

[0007] monitoring real-time current data under the simulated control environment, extracting detailed current fluctuation values from the real-time current data, and calculating current deviation values of the test battery under different operating conditions based on the detailed current fluctuation values;

[0008] formulating a voltage regulation strategy corresponding to the test battery based on the current deviation value, performing multiple rounds of load testing on the test battery based on the voltage regulation strategy to obtain multiple rounds of test records, calculating a current load index corresponding to each record in the multiple rounds of test records, and constructing a performance control system corresponding to the test battery based on the current load index;

[0009] Based on the performance control system, analyzing the discharge response effect of the test battery under different load mutation conditions, querying the voltage change trend of the test battery during the discharge process based on the discharge response effect, and identifying the core change factors in the voltage change trend;

[0010] Based on the core change elements, the preset intelligent feedback adjustment unit is tested and connected to the test battery to form a test battery group. The dynamic current data of the test battery group during operation is collected, and the controllable current nodes in the dynamic current data are screened. Based on the controllable current nodes, the current control scheme corresponding to the test battery is generated.

[0011] Optionally, analyzing an application operating scenario corresponding to the test battery based on the load demand information includes:

[0012] Collecting current peak and valley data in the load demand information;

[0013] Dividing the load time interval corresponding to the load demand information based on the current peak and valley data;

[0014] Extracting the load duration and load frequency corresponding to the load time period;

[0015] Determining a load operating mode corresponding to the test battery based on the load duration and the load frequency;

[0016] Based on the load operating mode, the application operating scenario corresponding to the test battery is analyzed.

[0017] Optionally, constructing a simulated control environment corresponding to the test battery based on the initial adjustment voltage includes:

[0018] querying a key regulation point in the initial regulation voltage;

[0019] Calculating the regulated power consumption value corresponding to the key regulation point;

[0020] Determining a power consumption adjustment direction corresponding to the test battery based on the adjusted power consumption value;

[0021] Analyze the power consumption control scenario corresponding to the battery under the power consumption adjustment direction;

[0022] Based on the power consumption control scenario, a simulated control environment corresponding to the test battery is constructed.

[0023] Optionally, the calculating the regulated power consumption value corresponding to the key regulation point includes:

[0024] The regulated power consumption value corresponding to the key regulation point is calculated using the following formula:

[0025]

[0026] in, Indicates the regulated power consumption value corresponding to the key regulation point, represents the voltage value corresponding to the key regulation point, Indicates at time The current value corresponding to the battery is and Respectively represent the start time and end time of the power consumption measurement period, Indicates the internal resistance of the battery. Indicates the load equivalent resistance.

[0027] Optionally, monitoring the real-time current data under the simulated control environment includes:

[0028] Deploy intelligent sensing nodes in the simulated control environment;

[0029] collecting a current sensing signal from the intelligent sensing node;

[0030] Converting the current sensing signal into a digital signal code;

[0031] generating a current data sequence corresponding to the digital signal code;

[0032] Dividing the data subsequences corresponding to the current data sequence;

[0033] Based on the data subsequence, real-time current data in the simulated control environment is monitored.

[0034] Optionally, calculating the current deviation value of the test battery under different operating conditions based on the current fluctuation detailed value includes:

[0035] The current deviation value of the test battery under different working conditions is calculated using the following formula:

[0036]

[0037] in, Indicates the current deviation value of the test battery under different working conditions, Indicates the total number of detailed values corresponding to the current fluctuation detailed value, Indicates the quantity index corresponding to the current fluctuation detailed value, Indicates the The weight coefficient corresponding to the current fluctuation value is: Indicates the The normalized value corresponding to the current fluctuation value, Indicates the total number of working conditions corresponding to different working conditions, Indicates the quantity index corresponding to different working conditions, Indicates the The current adjustment value under each working condition is: Represents the normalization constant.

[0038] Optionally, performing multiple rounds of load testing on the test battery based on the voltage regulation strategy to obtain multiple rounds of test records includes:

[0039] Based on the voltage regulation strategy, setting the initial load parameters corresponding to the test battery;

[0040] Based on the initial load parameters, performing a first round of testing on the test battery to obtain the first round of load parameters;

[0041] Based on the first round of load parameters, optimizing and adjusting the load test environment of the test battery to obtain a load optimized environment;

[0042] Based on the load optimization environment, multiple rounds of load testing are performed on the test battery to obtain multiple rounds of test records.

[0043] Optionally, constructing a performance control system corresponding to the test battery based on the current load index includes:

[0044] Analyzing the index fluctuation range corresponding to the current load index;

[0045] Based on the index fluctuation range, the current load index is classified into intervals to obtain index classification intervals;

[0046] Identifying energy efficiency variation patterns corresponding to indices in the index classification interval;

[0047] Integrating the energy efficiency change rules to obtain an energy efficiency integration set;

[0048] Based on the energy efficiency integration set, an efficiency control system corresponding to the test battery is constructed.

[0049] Optionally, querying a voltage change trend of the test battery during a discharge process based on the discharge response effect includes:

[0050] querying a response highlight node in the discharge response effect;

[0051] sorting out the discharge highlight phase corresponding to the response highlight node;

[0052] Analyzing the voltage change wave value corresponding to the discharge highlight stage;

[0053] Extracting the influence factors of the change in the voltage change wave value;

[0054] Based on the change influencing factors, the voltage change trend of the test battery during the discharge process is queried.

[0055] In order to solve the above problems, the present invention further provides an intelligent voltage-regulated battery output current control system, the system comprising:

[0056] An environment construction module is used to obtain load demand information corresponding to a test battery, analyze an application operating scenario corresponding to the test battery based on the load demand information, set an initial regulation voltage adapted for the test battery based on the application operating scenario, and construct a simulated control environment corresponding to the test battery based on the initial regulation voltage;

[0057] a deviation value calculation module, configured to monitor real-time current data under the simulated control environment, extract detailed current fluctuation values from the real-time current data, and calculate current deviation values of the test battery under different operating conditions based on the detailed current fluctuation values;

[0058] a system construction module, configured to formulate a voltage regulation strategy corresponding to the test battery based on the current deviation value, perform multiple rounds of load testing on the test battery based on the voltage regulation strategy, obtain multiple rounds of test records, calculate a current load index corresponding to each record in the multiple rounds of test records, and construct a performance control system corresponding to the test battery based on the current load index;

[0059] an element identification module, configured to analyze, based on the performance control system, the discharge response effect of the test battery under different load mutation conditions, query the voltage change trend of the test battery during the discharge process based on the discharge response effect, and identify the core change element in the voltage change trend;

[0060] A scheme generation module is used to test connect the preset intelligent feedback adjustment unit with the test battery based on the core change elements to form a test battery group, collect dynamic current data of the test battery group during operation, and screen the controllable current nodes in the dynamic current data, and generate a current control scheme corresponding to the test battery based on the controllable current nodes.

[0061] Compared with the problems described in the background technology, the present invention obtains the load demand information corresponding to the test battery, and can accurately adapt to the application scenarios. For example, according to the multi-tasking operation of smart phones and different working conditions of electric vehicles, the current output can be planned in advance to avoid the shortcomings of fixed current limiting, which is helpful to build a simulation control environment that fits the reality to simulate complex and changeable real-life usage conditions and lay the foundation for subsequent precise control. By monitoring the real-time current data under the simulation control environment, the present invention can grasp the battery working status in real time, detect abnormal current fluctuations in time, prevent battery failures, ensure safe and stable operation of the system, help optimize the battery management strategy, adjust the charging and discharging parameters according to the current data, and extend the battery life. Furthermore, the present invention formulates the voltage regulation strategy corresponding to the test battery based on the current deviation value, which can accurately adapt to the battery working status and realize the real-time current deviation according to the current deviation. Adjust the voltage in time to ensure efficient and stable power supply of the battery, such as improving the endurance and power performance in electric vehicles, which can effectively extend the battery life and avoid problems such as overcharging and over-discharging caused by abnormal current fluctuations. The battery health is maintained through voltage regulation. Furthermore, based on the performance control system, the present invention analyzes the discharge response effect of the test battery under different load mutation conditions, which can accurately understand the emergency power supply capacity of the battery and understand whether the battery can quickly adjust the output when the load suddenly changes, to ensure the stable operation of the electrical equipment and reduce the risk of power outages. Finally, based on the core change elements, the present invention connects the preset intelligent feedback adjustment unit with the test battery for testing to form a test battery group, which can accurately perceive the battery working condition according to the core change elements. The intelligent unit monitors the voltage sudden change, slope turning point and other conditions in real time, and responds quickly to ensure stable power supply of the battery. Therefore, the intelligent voltage-regulated battery output current control method and system provided in the embodiment of the present invention can improve the control efficiency of the battery output current. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flow chart of a method for controlling output current of an intelligent voltage-regulated battery provided by one embodiment of the present invention;

[0063] Figure 2 A schematic diagram of a module for implementing the intelligent voltage-regulated battery output current control system provided by an embodiment of the present invention.

[0064] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0065] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0066] Embodiments of the present application provide an intelligent voltage-regulated battery output current control method. The method can be executed by at least one of electronic devices, such as a server or a terminal, that can be configured to execute the method provided by the embodiments of the present application. In other words, the method can be executed by software or hardware installed on a terminal or server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0067] Example 1:

[0068] Reference Figure 1 FIG. 1 is a flow chart of an intelligent voltage-regulated battery output current control method according to an embodiment of the present invention. In this embodiment, the intelligent voltage-regulated battery output current control method includes:

[0069] S1. Obtain the load demand information corresponding to the test battery, analyze the application operating scenario corresponding to the test battery based on the load demand information, set the initial adjustment voltage adapted to the test battery based on the application operating scenario, and construct a simulated control environment corresponding to the test battery based on the initial adjustment voltage.

[0070] The present invention obtains load demand information corresponding to the test battery and can accurately adapt to application scenarios. For example, it can plan current output in advance based on the multi-tasking operation of smartphones and different operating conditions of electric vehicles, avoiding the shortcomings of fixed current limiting. It helps to build a simulation and control environment that fits reality to simulate complex and changeable real-world usage conditions, laying the foundation for subsequent precise control.

[0071] The test battery refers to a battery sample used as a research object during the development and optimization of an intelligent voltage-regulated battery output current control system. It can cover various common battery types, including but not limited to lithium-ion batteries and lead-acid batteries, and is intended to represent the energy supply batteries used in actual application scenarios, such as smartphones, tablets, electric vehicles, and distributed energy storage systems. The load demand information refers to the detailed requirements of the external power load connected to the test battery for the battery output current, voltage, and other electrical parameters under different operating conditions. For example, when a smartphone is running large games or multitasking, the chip performs high-speed computing and the screen displays at high brightness, which requires the battery to provide instantaneous high-power supply, specifically manifested as a high current output requirement. When an electric vehicle accelerates, the drive motor requires the battery to quickly provide a large current to propel the vehicle forward, and when braking, there is a special current load mode corresponding to energy recovery. The collection of information such as the power, current, and voltage changes of these different loads at different times is the load demand information. Optionally, obtaining the load demand information corresponding to the test battery can be achieved using circuit simulation tools such as LTspice and PSpice.

[0072] Furthermore, the present invention analyzes the application operating scenarios corresponding to the test battery based on the load demand information, allowing the battery control system to accurately adapt to various types of equipment, such as understanding the different current requirements of electric vehicles during acceleration, constant speed, and braking, ensuring stable power output and improving the driving experience. In addition, it helps to predict the working pressure of the battery under complex working conditions in advance, optimize the current control strategy in a targeted manner, avoid overheating and over-discharge of the battery in high-load scenarios, and extend battery life.

[0073] Among them, the application operating scenario refers to the complete environment in which the test battery is actually put into use, covering all load operating modes that may appear, the switching sequence and logical relationship between them, and the sum of information such as the external environmental conditions (such as temperature, humidity, etc.). Taking the backup power battery of an outdoor mobile base station as an example, it is necessary to consider the high-load voice and data transmission conditions during the daytime communication peak, as well as the low-load standby conditions at night, and also combine the impact of temperature changes in the outdoor environment on battery performance to construct a comprehensive application operating scenario.

[0074] As an embodiment of the present invention, the analysis of the application operating scenario corresponding to the test battery based on the load demand information includes: collecting current peak and valley data in the load demand information; dividing the load time period corresponding to the load demand information based on the current peak and valley data; extracting the load duration and load frequency corresponding to the load time period; determining the load operating mode corresponding to the test battery based on the load duration and the load frequency; and analyzing the application operating scenario corresponding to the test battery based on the load operating mode.

[0075] Among them, the current peak and valley data refers to the collection of the maximum current (peak value) and minimum current (valley value) obtained during the power consumption process of the load connected to the monitoring test battery, as well as related information such as the time of occurrence and duration. For example, when an electric vehicle accelerates suddenly, the battery output current instantly soars to a maximum value, which is the current peak value. When the vehicle idles or coasts for a long time, the current demand is extremely small, close to the valley value. These extreme values and related dynamic change data constitute the current peak and valley data; the load time period refers to the sub-time periods after the complete time period of load operation is divided according to the characteristics of the current peak and valley data. When the current peak-valley data shows obvious periodic or stage-by-stage changes, the current rise from the trough to the next trough is considered an interval. For example, when a smartphone switches from standby mode at night to high-intensity use during the day, the current remains stable at a low level during the standby period, which can be divided into a low-load period. During the daytime, when multiple tasks are running and the screen is always on, the current fluctuates greatly and is generally high, which is divided into a high-load period. This clearly defines periods with different load demands. The load duration refers to the duration of each load period. For example, when an industrial robot performs a high-intensity welding task, the length of the high current demand period from starting the welding equipment and the robot starting to operate to the end of the task is the high-load duration. For example, in the cooling mode of a household air conditioner, the time during which the compressor continues to operate is the duration of the cooling load. The load frequency refers to the number of times each load time interval recurs within a certain observation period. For example, for a smart bracelet, operations such as raising your wrist to check the time and receiving notifications every hour will trigger a short period of high current demand. This high-load time interval may occur dozens of times a day. This is a high load frequency; in electric vehicles, the acceleration condition occurs less frequently than the braking and constant-speed driving conditions. This frequency data helps to understand the frequency of different load conditions; the load condition mode refers to a representative load working state category summarized by comprehensive information such as load duration, load frequency, and current peak and valley data. For example, new energy vehicles have multiple typical conditions such as constant-speed cruising, sudden acceleration, sudden braking, and slow climbing. The current demand, load duration, and frequency are different under each condition. These with similar characteristics are classified into one category to form a load condition mode.

[0076] Furthermore, the collection of current peak and valley data in the load demand information can be achieved through a data acquisition card, such as: the data acquisition card transmits the collected current data to computer software for storage and analysis, and sorts and filters the data to find the maximum value (peak value) and the minimum value (valley value), thereby obtaining the current peak and valley data; the division of the load time period corresponding to the load demand information can be achieved through a threshold determination method, such as: setting a certain proportion of the current peak value (such as 80%) as a high load current threshold, and a certain proportion below the valley value (such as 30%) as a low load current threshold, thereby distinguishing the load time period interval); the extraction of the load duration and load frequency corresponding to the load time period interval can be achieved through timestamp marking, such as: after the load time period interval is divided, by calculating each The difference between the start timestamp and the end timestamp of the interval is used to obtain the load duration, and within a set longer time period (such as a day or a week), the number of times each load time interval appears is counted, which is the load frequency; the determination of the load operating mode corresponding to the test battery can be achieved through a feature matching method, such as: through a pre-established load operating mode feature library, the analyzed load duration, load frequency and other features are matched with the patterns in the library to determine the most suitable load operating mode; the analysis of the application operating scenario corresponding to the test battery can be achieved through a Monte Carlo simulation method, such as: simulating the driving conditions of electric vehicles under different weather conditions (temperature, humidity), and after multiple simulations, obtaining a complete application operating scenario including the switching sequence and probability of various operating modes and the influence of the external environment.

[0077] Based on the application operating scenario, the present invention sets the initial adjustment voltage adapted to the test battery, which can meet the actual needs of different devices. For example, electric vehicles require high voltage to ensure power when accelerating and climbing. The initial adjustment voltage can be accurately adapted accordingly to improve operating efficiency, avoid excessive battery loss under complex working conditions, and flexibly adjust the voltage according to scenarios such as multi-tasking switching and standby of smartphones to extend battery life.

[0078] Among them, the initial regulation voltage refers to the voltage value initially set to guide the battery output current control process after comprehensively considering the application operating scenarios faced by the test battery, including the type of load, power requirements, operating time, frequency of occurrence, and environmental conditions. It is not fixed, but serves as the starting benchmark for subsequent dynamic adjustments. It aims to enable the battery output to quickly approach the ideal state and adapt to the immediate current demand of the load under different working conditions. For example, in the starting and acceleration scenario of new energy vehicles, a starting voltage is determined based on the initial torque requirement of the motor, the current battery power and temperature conditions. Optionally, the setting of the initial regulation voltage adapted to the test battery can be achieved through a neural network algorithm. For example, in the battery management of smart home systems, for the complex working conditions of various smart devices, a suitable initial regulation voltage is predicted by a trained neural network model.

[0079] Based on the initial regulation voltage, the present invention constructs a simulated control environment corresponding to the test battery, which can accurately reproduce various operating conditions of the battery in actual use, such as simulating the voltage and current changes when an electric vehicle climbs a slope or suddenly brakes, preparing the battery in advance to cope with complex scenarios, helping to optimize the voltage regulation strategy, and fine-tune the initial regulation voltage based on the feedback from the simulated environment to ensure stable battery output and improve power supply efficiency.

[0080] Among them, the simulated control environment refers to a battery working environment that is as close to the actual application scenario as possible simulated in a laboratory or virtual simulation space using various electronic equipment and simulation software based on the power consumption control scenario. By using programmable electronic loads, software modules that simulate battery characteristics, etc., the voltage, current, and load change parameters that are consistent with the actual scenario are set, making the test battery feel as if it is in actual working conditions, so as to accurately study the performance of the battery under different working conditions.

[0081] As an embodiment of the present invention, constructing a simulated control environment corresponding to the test battery based on the initial adjustment voltage includes: querying the key adjustment points in the initial adjustment voltage; calculating the adjustment power consumption value corresponding to the key adjustment point; determining the power consumption adjustment direction corresponding to the test battery based on the adjustment power consumption value; analyzing the power consumption control scenario corresponding to the battery under the power consumption adjustment direction; and constructing a simulated control environment corresponding to the test battery based on the power consumption control scenario.

[0082] Among them, the key regulation point refers to the voltage value nodes that play a key role in the battery output characteristics and subsequent current regulation and have a symbolic significance within the numerical range set by the initial regulation voltage. For example, in a lithium-ion battery power supply system, when the voltage reaches a certain specific value, the internal resistance of the battery will change significantly, or the output power of the battery will have a turning point. These special voltage values become key regulation points; the regulated power consumption value refers to the energy value consumed per unit time when the battery outputs at the voltage value corresponding to the key regulation point, which reflects the energy utilization efficiency and loss of the battery at this specific voltage. Taking the electric vehicle battery as an example, when the battery voltage is at a certain key regulation point and the motor is driven to run, the regulated power consumption value is obtained by measuring the power input to the motor and the power loss such as the battery's own heat; the power consumption adjustment direction refers to the value of the regulated power consumption value according to the size, change trend and battery The application working conditions faced will determine the direction of subsequent adjustments to the battery power consumption. If the adjusted power consumption value is too high and the current application working conditions require reduced energy consumption, such as when a smartphone is in standby mode, then the power consumption adjustment direction may be to lower the voltage and reduce the output current to achieve energy saving. On the contrary, if the electric vehicle is accelerating and climbing, the adjusted power consumption value is high but the power demand takes priority. The power consumption control scenario refers to a specific picture of the interaction between the battery and the load that is constructed by comprehensively considering the power consumption adjustment direction and the characteristics and change laws of the actual load. For example, in the industrial robot operation scenario, when the power consumption adjustment direction is energy saving and it is known that the robot is performing a light load handling task, the power consumption control scenario is that the battery outputs at a lower voltage and current, and the robot completes the handling operation smoothly and slowly. If the power consumption adjustment direction is to increase power, and the corresponding robot performs heavy forging tasks, the battery needs to increase the voltage and provide a large current as set to meet the high-intensity load operation requirements.

[0083] Furthermore, the query of the key adjustment points in the initial adjustment voltage can be achieved by querying a preset machine learning library, such as Scikit-learn, TensorFlow, etc.; the calculation of the adjustment power consumption value corresponding to the key adjustment point can be achieved through the following calculation formula; the determination of the power consumption adjustment direction corresponding to the test battery can be achieved through an optimization algorithm, such as a genetic algorithm, a particle swarm optimization algorithm; the analysis of the power consumption control scenario corresponding to the battery under the power consumption adjustment direction can be achieved through a scenario modeling tool, such as Simulink, MATLAB and other tools; the construction of the simulation control environment corresponding to the test battery can be achieved through an environmental simulation tool, such as PSpice, LTspice and other tools.

[0084] As an embodiment of the present invention, the calculating the regulated power consumption value corresponding to the key regulation point includes:

[0085] The regulated power consumption value corresponding to the key regulation point is calculated using the following formula:

[0086]

[0087] in, Indicates the regulated power consumption value corresponding to the key regulation point, represents the voltage value corresponding to the key regulation point, Indicates at time The current value corresponding to the battery is and Respectively represent the start time and end time of the power consumption measurement period, Indicates the internal resistance of the battery. Indicates the load equivalent resistance.

[0088] In detail, the regulated power consumption value refers to the comprehensive measurement value of the energy consumption and utilization of the battery in a specific time period at the voltage corresponding to the key regulation point, which reflects the power characteristics of the battery in this critical state; the power consumption measurement time period refers to a specific time interval selected for measuring the regulated power consumption value of the battery, which is determined by the starting time. and end time Definition: During this time period, the battery current and other parameters are monitored and calculated to determine the adjusted power consumption value; the battery internal resistance refers to a parameter inherent to the battery itself, which represents the degree of obstruction to the passage of current inside the battery, and the unit is ohm, which will affect the internal energy loss of the battery during operation; the load equivalent resistance refers to simplifying the complex load actually connected to the battery into an equivalent resistance value, which is used to describe the load's consumption characteristics of battery power from a macro perspective, and the unit is ohm, which is used to reflect the impact of the load on the battery's power output.

[0089] S2. Monitor the real-time current data under the simulated control environment, extract the current fluctuation detailed value in the real-time current data, and calculate the current deviation value of the test battery under different working conditions based on the current fluctuation detailed value.

[0090] By monitoring the real-time current data under the simulated control environment, the present invention can grasp the battery working status in real time, promptly detect abnormal current fluctuations, prevent battery failures, ensure safe and stable operation of the system, help optimize the battery management strategy, adjust the charging and discharging parameters according to the current data, and extend the battery life.

[0091] Among them, the real-time current data refers to the current-related information occurring at the current moment in the simulated control environment, including the instantaneous value of the current, the rate of change, the fluctuation, etc., which is obtained and monitored in real time through the above series of steps (from intelligent sensing node collection to data subsequence analysis, etc.) to timely understand the battery working status and the impact of load changes on the current.

[0092] As an embodiment of the present invention, the monitoring of real-time current data in the simulated control environment includes: deploying intelligent sensing nodes in the simulated control environment; collecting current sensing signals in the intelligent sensing nodes; converting the current sensing signals into digital signal codes; generating a current data sequence corresponding to the digital signal codes; dividing the current data sequence into data subsequences corresponding to the current data sequence; and monitoring the real-time current data in the simulated control environment based on the data subsequences.

[0093] Among them, the intelligent sensing node refers to a small electronic device specially designed to sense current information in an analog control environment. It has high-precision current sensing capability, can obtain current-related physical quantities in real time, and can transmit the sensed information to the subsequent processing system. It usually has the characteristics of being small, low power consumption, and high sensitivity, and can be flexibly deployed in key positions between the battery and the load; the current sensing signal refers to an analog signal generated by the intelligent sensing node after sensing the current, which reflects the magnitude, direction, change trend and other information of the current. It is an electrical signal representation of the current physical quantity inside the sensing node, and its intensity, waveform and other characteristics are closely related to the characteristics of the actual current; the digital signal code refers to the binary coding form obtained by converting the current sensing signal through a device such as an analog-to-digital converter (ADC). These codes are in digital form. It accurately represents the characteristics of the current sensing signal, facilitates storage, transmission and processing by digital circuits and computer systems, and is a key intermediate product for the conversion of analog signals to digital information; the current data sequence refers to a collection of a series of continuous digital signal codes arranged in chronological order, which completely records the information of the digitized current sensing signal over a period of time, can reflect the change of current over time, and is an orderly organization and presentation method of current data; the data subsequence refers to smaller data fragments obtained by dividing the current data sequence according to certain rules (such as equal time intervals, specific event triggering, etc.). Each data subsequence contains current data information within a specific time period, which facilitates local analysis and feature extraction of current data, and can more accurately capture the changing characteristics and laws of current in different time periods.

[0094] Furthermore, the deployment of smart sensing nodes in the simulated control environment can be achieved through an Internet of Things platform, such as Arduino, Raspberry Pi, etc.; the collection of current sensing signals in the smart sensing nodes can be achieved through a script programming language, such as Python, C++, etc.; the conversion of the current sensing signals into digital signal codes can be achieved through a data conversion algorithm, such as normalization, standardization, etc.; the generation of the current data sequence corresponding to the digital signal code can be achieved through a queue storage method, such as sequential queue storage, circular queue storage, etc.; the division of data subsequences corresponding to the current data sequence can be achieved through a window partitioning method, such as a sliding window, a timestamp window, etc.; the monitoring of real-time current data in the simulated control environment can be achieved through supervised learning methods, such as support vector machines, decision trees, etc.

[0095] The present invention helps to monitor the operating stability of electrical equipment in real time by extracting detailed current fluctuation values from the real-time current data. For example, on an industrial production line, the detailed fluctuation values can quickly detect whether the motor is abnormal, avoid shutdowns caused by failures, ensure smooth production processes, and accurately assess the health of batteries. Taking smartphones as an example, abnormal current fluctuations can reveal battery aging or charging module failures in advance, reminding users to replace or repair them in time.

[0096] Among them, the current fluctuation detailed value refers to a series of quantitative indicators that accurately reflect the degree of change of current magnitude and direction over time in real-time current data. It covers the peak-to-valley difference of current amplitude, that is, the difference between the maximum and minimum current values, which intuitively shows the amplitude of current fluctuation; it also includes the current change rate, which reflects the speed of current increase and decrease per unit time, and reflects the severity of the dynamic change of current; and the frequency of irregular fluctuations, which is used to measure the frequency of current deviation from a stable state. Optionally, the extraction of the current fluctuation detailed value from the real-time current data can be achieved through a differential algorithm, such as: performing differential operations on the real-time current data sequence in chronological order, that is, calculating the difference between two adjacent data points to obtain the current fluctuation detailed value.

[0097] Furthermore, the present invention calculates the current deviation value of the test battery under different operating conditions based on the detailed value of the current fluctuation, can accurately evaluate the battery performance, compare the current deviation under different operating conditions such as acceleration, constant speed, and braking of the electric vehicle, and clearly judge the battery power supply stability.

[0098] The current deviation value refers to a quantitative indicator of the degree of difference between the actual current value and the ideal value or standard value of the test battery under different operating conditions. It comprehensively considers the detailed value of current fluctuation and the impact of different operating conditions, and is used to evaluate the stability and consistency of the battery current under various operating conditions.

[0099] As an embodiment of the present invention, the calculating, based on the current fluctuation detailed value, the current deviation value of the test battery under different operating conditions includes:

[0100] The current deviation value of the test battery under different working conditions is calculated using the following formula:

[0101]

[0102] in, Indicates the current deviation value of the test battery under different working conditions, Indicates the total number of detailed values corresponding to the current fluctuation detailed value, Indicates the quantity index corresponding to the current fluctuation detailed value, Indicates the The weight coefficient corresponding to the current fluctuation value is: Indicates the The normalized value corresponding to the current fluctuation value, Indicates the total number of working conditions corresponding to different working conditions, Indicates the quantity index corresponding to different working conditions, Indicates the The current adjustment value under each working condition is: Represents the normalization constant.

[0103] Specifically, the weight coefficient refers to a numerical value indicating the importance of each current fluctuation value, reflecting the impact of that current fluctuation value on the overall current deviation value. A larger weight coefficient indicates a higher weight for the corresponding current fluctuation value in calculating the current deviation value, and a more significant impact on the result. The normalized value refers to the value obtained by normalizing the current fluctuation value. A specific normalization method (such as extreme value normalization) is used to unify current fluctuation values of different dimensions and ranges into a specific interval (such as [0, 1]). The current adjustment value refers to a numerical value determined based on the characteristics of different operating conditions and the degree of their impact on the current, used to reflect the additional deviation or change in battery current under different operating conditions, such as the current change caused by changes in battery internal resistance under high-temperature conditions. The normalization constant refers to a numerical value used to adjust the second term in the formula (the sum of the current adjustment values under different operating conditions) to ensure that the calculation result of the entire formula is within a reasonable range and the accuracy and comparability of the current deviation value. Its value is generally determined based on specific calculation requirements and data range.

[0104] S3. Based on the current deviation value, formulate a voltage regulation strategy corresponding to the test battery; based on the voltage regulation strategy, perform multiple rounds of load testing on the test battery to obtain multiple rounds of test records; calculate the current load index corresponding to each record in the multiple rounds of test records; and based on the current load index, construct a performance control system corresponding to the test battery.

[0105] Based on the current deviation value, the present invention formulates a voltage regulation strategy corresponding to the test battery, which can accurately adapt to the battery working state and adjust the voltage in real time according to the current deviation to ensure efficient and stable power supply of the battery. For example, in electric vehicles, the endurance and power performance can be improved, the battery life can be effectively extended, and problems such as overcharging and over-discharging caused by abnormal current fluctuations can be avoided. The battery health is maintained through voltage regulation.

[0106] Among them, the voltage regulation strategy refers to a series of targeted voltage adjustment methods and rules formulated according to the current deviation value of the test battery to optimize battery performance and ensure system stability. It covers factors such as determining the direction of voltage regulation (increase or decrease), the amplitude of adjustment, and the timing of adjustment under different current deviation conditions. For example, when the current deviation value exceeds the normal range and is positive (the current is too large), the strategy may include moderately reducing the voltage to reduce the current to prevent battery overload; when the current deviation is negative (the current is too small), measures such as increasing the voltage may be taken to increase the current to ensure that the battery can normally supply power to the load. At the same time, multiple factors such as the battery's own characteristics, load requirements, and the overall operating status of the system must also be considered. Optionally, the formulation of the voltage regulation strategy corresponding to the test battery can be implemented through a strategy generation tool, such as PSIM, MATLAB Simulink, and other tools.

[0107] Furthermore, based on the voltage regulation strategy, the present invention performs multiple rounds of load tests on the test battery to obtain multiple rounds of test records, which can accurately verify the effectiveness of the voltage regulation strategy. Each round of load testing simulates different real working conditions. By comparing the actual battery performance with expectations, strategy loopholes can be discovered and optimized in a timely manner.

[0108] Among them, the multi-round test records refer to the sum of comprehensive data and information collected and organized during a series of multiple rounds of repeated load tests on the test battery under a load optimization environment. It includes the key parameter values of the battery such as voltage, current, temperature at different times in each round of testing, as well as the corresponding load status, such as load power changes and load type switching timing; it also covers the specific implementation of the voltage regulation strategy in each round of testing, such as the number of adjustments and the adjustment amplitude.

[0109] As an embodiment of the present invention, the test battery is subjected to multiple rounds of load tests based on the voltage regulation strategy to obtain multiple rounds of test records, including: setting the initial load parameters corresponding to the test battery based on the voltage regulation strategy; performing a first round of testing on the test battery based on the initial load parameters to obtain the first round of load parameters; optimizing and adjusting the load test environment in which the test battery is located based on the first round of load parameters to obtain a load optimization environment; performing multiple rounds of load testing on the test battery based on the load optimization environment to obtain multiple rounds of test records.

[0110] Among them, the initial load parameters refer to a series of basic condition values pre-set for starting the first round of load testing of the test battery according to the voltage regulation strategy, which covers the initial power size of the load, which determines the initial discharge intensity of the battery; the type of load, such as constant resistance load, constant current load or dynamically changing load, different types will cause different output characteristics of the battery; the first round of load parameters refers to the set of parameters related to the load and battery operating status that are actually monitored and recorded after the first round of testing of the test battery according to the initial load parameters, including the dynamic changes in the actual power consumption of the load end during the test, which reflects whether the actual power supply of the battery is stable; the real-time fluctuation value of the battery output current can show the battery under the load. Current response characteristics; the load test environment refers to a comprehensive space and condition setting constructed to test the performance of the battery under load conditions. The space includes the layout of the site for placing batteries, loads and various monitoring equipment to ensure that signal transmission is not interfered with and the heat dissipation conditions are reasonable; the condition setting involves the control range of ambient temperature and humidity; the load optimization environment refers to an environment that is more suitable for testing batteries after targeted improvements to the load test environment based on the first round of load parameter feedback. For example, if the first round finds that the battery performance fluctuates greatly at high temperatures, the heat dissipation system will be strengthened in the optimized environment to accurately control the temperature to the optimal working range of the battery; if the load power fluctuation causes the electromagnetic interference to become stronger, more efficient electromagnetic shielding materials will be added.

[0111] Furthermore, the setting of the initial load parameters corresponding to the test battery can be achieved through theoretical analysis methods, such as: preliminary analysis and setting based on the technical specifications and application scenarios of the test battery, so as to obtain the initial load parameters; the first round of testing of the test battery can be achieved through programming languages, such as: Python, LabVIEW, etc.; the optimization and adjustment of the load test environment of the test battery can be achieved through thermal simulation tools, such as: ANSYSFluent, CST Studio Suite and other tools; the multiple rounds of load testing of the test battery can be achieved through automated test scripts, such as: LabVIEW, Selenium and other scripts.

[0112] By counting the current load index corresponding to each record in the multiple rounds of test records, the present invention can accurately understand the carrying capacity of the battery under different working conditions, clarify the adaptation status of the battery output current and load demand based on the current load index, and optimize the battery usage strategy.

[0113] Among them, the current load index refers to a quantitative indicator used to measure the closeness of the relationship between the output current and the load demand of the battery during the load test. It comprehensively considers factors such as the size and nature of the load and the size and stability of the actual output current of the battery under the load. For example, the current load index can be the ratio of the battery output current to the rated current of the load. This ratio can intuitively reflect whether the battery is working under a suitable load intensity; or it can also be a comprehensive value that includes current fluctuations. By calculating the variance or standard deviation of the current within a certain period of time and combining parameters such as the power factor of the load, the dynamic response characteristics of the battery during load changes can be reflected. Optionally, the statistics of the current load index corresponding to each record in the multiple rounds of test records can be achieved through index statistical methods, such as descriptive statistics, inferential statistics, etc.

[0114] Furthermore, the present invention constructs a performance control system corresponding to the test battery based on the current load index, which can achieve precise control of battery performance and adjust the battery operating state in real time according to the current load index, so that it can maintain high-efficiency output under different working conditions, extend battery life, help improve battery safety, and promptly detect potential risks caused by abnormal loads, provide early warning and intervention, and prevent battery failures such as overheating and short circuits.

[0115] Among them, the efficiency control system refers to a comprehensive system built based on the energy efficiency integration set, which includes monitoring, judgment, regulation and other functions. It can monitor the current load index in real time, quickly determine the index classification interval to which it belongs, and automatically trigger control measures such as adjusting the charging current, optimizing the heat dissipation means, switching the power supply mode, etc. according to the corresponding energy efficiency change rules.

[0116] As an embodiment of the present invention, the performance control system corresponding to the test battery is constructed based on the current load index, including: analyzing the index fluctuation range corresponding to the current load index; based on the index fluctuation range, classifying the current load index into intervals to obtain index classification intervals; identifying the energy efficiency change rules corresponding to the indexes in the index classification intervals; integrating the energy efficiency change rules to obtain an energy efficiency integration set; and constructing the performance control system corresponding to the test battery based on the energy efficiency integration set.

[0117] Among them, the index fluctuation range refers to the span between the maximum and minimum values of the current load index under multiple rounds of test records, which reflects the fluctuation range of the battery load conditions under different working conditions and different time periods. For example, after a series of tests, the current load index reaches a minimum of 0.3 and a maximum of 0.9, then the interval of 0.3-0.9 is the index fluctuation range; the index classification interval refers to the sub-intervals into which the current load index is divided according to certain rules (such as equal interval division, division based on key thresholds, etc.) based on the index fluctuation range. For example, the fluctuation range of 0.3-0.9 is divided into 0.3-0.5, 0.5-0.7, and 0.7-0.9. Each of these three intervals represents a relatively concentrated type of load condition; the energy efficiency variation law refers to the inherent trend of energy efficiency-related indicators such as the battery's energy conversion efficiency, output power stability, and heat generation as the current load index changes within each index classification interval. Taking the index classification interval of 0.5-0.7 as an example, it can be found that as the current load index increases, the battery's energy conversion efficiency first increases and then tends to stabilize, while the heat generation rate accelerates. This is the energy efficiency variation law corresponding to this interval; the energy efficiency integration set refers to a collection that summarizes, sorts out, and optimizes the energy efficiency variation laws corresponding to different index classification intervals, which comprehensively covers the energy efficiency characteristics of batteries under various conditions from low load to high load.

[0118] Furthermore, the analysis of the index fluctuation range corresponding to the current load index can be achieved through statistical analysis tools, such as Excel, R, Python and other tools; the interval classification of the current load index can be achieved through what methods, tools or algorithms, such as: (and examples of the methods, tools or algorithms that can be implemented, remember to finally obtain the index classification interval); the identification of the energy efficiency change law corresponding to the index in the index classification interval can be achieved through regression analysis methods, such as linear regression, polynomial regression and other methods; the integration processing of the energy efficiency change law can be achieved through aggregation functions, such as groupby(), agg() and other functions; the construction of the performance control system corresponding to the test battery can be achieved through system construction tools, such as AMESim, LabVIEW and other tools.

[0119] S4. Based on the performance control system, analyze the discharge response effect of the test battery under different load mutation conditions; based on the discharge response effect, query the voltage change trend of the test battery during the discharge process, and identify the core change factors in the voltage change trend.

[0120] Based on the performance control system, the present invention analyzes the discharge response effect of the test battery under different load mutation conditions, which can accurately understand the emergency power supply capability of the battery and understand whether the battery can quickly adjust its output when the load suddenly changes, thereby ensuring the stable operation of electrical equipment and reducing the risk of power outages.

[0121] Among them, the discharge response effect refers to a comprehensive reflection of the immediate and subsequent short-term performance of the test battery in the face of sudden changes in load, specifically covering the stability of the battery output voltage, whether it can quickly suppress the voltage fluctuations caused by the mutation, maintain it in a reasonable range, and ensure the normal operation of electrical equipment; the adaptability of the current output, whether it can quickly adjust the size to accurately match the new load requirements, and prevent damage to the battery and load due to excessive or insufficient current; and the response time to a new stable state, that is, the time from the occurrence of the load mutation to the stabilization of the various battery parameters. The shorter the time, the stronger the battery's adaptability to load changes, and the overall intuitive display of the battery's performance in responding to sudden load changes. Optionally, the analysis of the discharge response effect of the test battery under different load mutation conditions can be achieved through machine learning models, such as LSTM, CNN and other models.

[0122] Furthermore, based on the discharge response effect, the present invention queries the voltage change trend of the test battery during the discharge process, which can intuitively present the power supply stability of the battery. By observing whether the voltage drops steadily or fluctuates violently, it is determined whether the battery can continue to stably supply energy to the device to avoid abnormal operation of the device.

[0123] The voltage change trend refers to connecting the voltage change wave values of each discharge highlight stage in chronological order to form a curve that can clearly reflect how the battery voltage evolves over time during the entire discharge process. It comprehensively shows the battery from the beginning to the end of discharge.

[0124] As an embodiment of the present invention, the voltage change trend of the test battery during the discharge process is queried based on the discharge response effect, including: querying the response highlight node in the discharge response effect; sorting out the discharge highlight stage corresponding to the response highlight node; analyzing the voltage change wave value corresponding to the discharge highlight stage; extracting the change influencing factors in the voltage change wave value; and based on the change influencing factors, querying the voltage change trend of the test battery during the discharge process.

[0125] Among them, the response highlight node refers to the key moments in the battery discharge response process that can clearly reflect the significant change in the battery state, such as the moment when the load suddenly increases or decreases significantly, at which time the battery needs to quickly adjust the output, and this moment is a response highlight node; or the moment when the battery output voltage and current experience a sharp jump, such as the time point when the voltage drops suddenly or the current suddenly surges; the discharge highlight stage refers to the specific time period divided according to the above-mentioned response highlight nodes, and each two adjacent response highlight nodes constitute a discharge highlight stage; the voltage change wave value refers to the fluctuation range of the battery voltage from the starting value to the ending value in each discharge highlight stage. As well as the key change values such as peak values and valley values that appear during the period, which intuitively show the voltage fluctuation dynamics during this stage, including specific characteristics such as whether the voltage changes steadily, oscillates violently, or rises and falls in stages; the change influencing factors refer to various reasons that cause the voltage change wave value to present a specific form, which include both the inherent properties inside the battery, such as the internal resistance of the battery. The larger the internal resistance, the more obvious the voltage drop when current passes through, which affects the voltage change; it also involves external conditions, such as the ambient temperature. At low temperatures, the chemical reaction rate of the battery slows down, the voltage output characteristics change, and the characteristics of the load. Different power and type of loads require different currents from the battery, which in turn affects the voltage fluctuation.

[0126] Furthermore, the query of the response highlight node in the discharge response effect can be achieved by a threshold judgment method, such as: when the normal discharge voltage of the test battery is 3.7V, when it is monitored that the voltage drops to 3.5V within 0.05 seconds, and the change rate reaches -5.4%, the time point at this time is used as the response highlight node; the sorting of the discharge highlight stages corresponding to the response highlight nodes can be achieved by a time series division method, such as: recording three response highlight nodes respectively at t1=10s, t2=25s, and t3= 40s, then two discharge highlight stages are divided: stage one is from 10s to 25s, and stage two is from 25s to 40s; the analysis of the voltage change wave value corresponding to the discharge highlight stage can be achieved by a range calculation method, such as: in a discharge highlight stage from 15s to 30s, after processing the voltage data, it is found that the maximum value is 3.6V at 20s, at this time the current is 0.5A, and the minimum value is 3.4V at 25s, and the current is 0.6A, then the voltage change wave value range is 0.2V; the extraction of the change influencing factors in the voltage change wave value can be achieved by statistical analysis tools, such as SPSS, SAS and other tools; the query of the voltage change trend of the test battery during the discharge process can be achieved by a fitting function, such as: fitting the voltage data, drawing a curve of voltage change over time, and the trend of the curve is the voltage change trend.

[0127] Furthermore, by identifying the core changing factors in the voltage change trend, the present invention can accurately control battery performance, and based on core factors such as slope mutation points and staged plateaus, gain insight into the battery health status and detect aging and short-circuit risks in advance.

[0128] Among them, the core change factors refer to the characteristic points and key intervals in the voltage change trend during the battery discharge process that play a key and decisive role in the battery performance, stability and power supply capacity. On the one hand, they cover sudden changes such as voltage rise and fall, which are often related to sudden reactions inside the battery, such as the instantaneous voltage drop caused by plate short circuit; on the other hand, they include turning points in the stage of stable voltage change, such as the turning point from slow decline to rapid decline, which implies a major change in the battery chemical reaction rate, and a voltage platform area maintained for a long time. Optionally, the identification of the core change factors in the voltage change trend can be achieved through natural language processing tools, such as NLTK, spaCy and other tools.

[0129] S5. Based on the core change elements, the preset intelligent feedback adjustment unit is tested and connected with the test battery to form a test battery group, the dynamic current data of the test battery group during operation is collected, and the controllable current nodes in the dynamic current data are screened. Based on the controllable current nodes, a current control scheme corresponding to the test battery is generated.

[0130] Based on the core change factors, the present invention connects a preset intelligent feedback adjustment unit with the test battery for testing to form a test battery group. The test battery group can accurately sense the battery operating condition based on the core change factors. The intelligent unit monitors voltage sudden changes, slope turning points and other situations in real time, and responds quickly to ensure stable power supply of the battery.

[0131] Among them, the preset intelligent feedback regulation unit refers to an intelligent device with advanced monitoring, analysis and regulation capabilities. It has a built-in high-precision sensor that can capture key parameters such as battery voltage, current, temperature, etc. in real time, and uses a built-in intelligent algorithm to quickly analyze these parameters, especially focusing on the battery state changes reflected by the core change factors. Once the battery state is detected to deviate from the preset normal range, such as the voltage is approaching the dangerous threshold, it can quickly issue a regulation instruction according to the preset strategy to automatically adjust the battery's charge and discharge rate, switch the circuit connection mode, or start auxiliary heat dissipation measures; the test battery pack refers to a whole composed of a test battery and a preset intelligent feedback regulation unit through a special electrical connection. The battery pack not only has the energy storage and release functions of an ordinary battery, but also has an "intelligent brain" due to the presence of the intelligent feedback regulation unit. In actual operating scenarios, it can flexibly adjust the working mode under the command of the intelligent feedback regulation unit according to different power demand, environmental conditions and the real-time status of the battery itself, providing reliable, stable and adaptable power support for various complex electrical equipment. Optionally, the test connection between the preset intelligent feedback regulation unit and the test battery can be achieved through a connection tool, such as: CAN Bus analyzer, twisted pair and other tools.

[0132] Furthermore, the present invention collects dynamic current data of the test battery pack during operation and screens the controllable current nodes in the dynamic current data, which helps to accurately control the working status of the battery pack. It can optimize the battery management strategy based on the controllable current nodes, accurately regulate current input and output, extend battery life, and improve overall energy efficiency.

[0133] Among them, the dynamic current data refers to a series of data records generated by the continuous change of current over time during the operation of the test battery pack. These data reflect the real-time changes of the current of the battery pack under different working conditions, such as charging, discharging, different load connection or environmental conditions change, including the current size, change rate, fluctuation frequency and other information, which can fully demonstrate the dynamic characteristics of the current in the electrochemical reaction inside the battery pack and the interaction with the external circuit; the controllable current node refers to those specific current state points in the dynamic current data that can be effectively intervened and adjusted by external control means (such as intelligent feedback regulation unit). These nodes usually appear at the critical point of current change. Key turning points, such as the starting point where the current starts to rise or fall from a stable state, the moment when the set current threshold is reached, or the boundary point where the current fluctuation exceeds the normal range, etc. Optionally, the acquisition of dynamic current data of the test battery pack during operation can be achieved through a current sensor, such as: converting the sensitivity value of the current sensor, converting the voltage signal into a corresponding current value, thereby obtaining dynamic current data; the screening of controllable current nodes in the dynamic current data can be achieved by setting a threshold method, such as: when the current data is greater than 8.2A or less than 1.8A, these time points and corresponding current values are recorded as candidate points for controllable current nodes.

[0134] Furthermore, based on the controllable current node, a current control scheme corresponding to the test battery is generated, which can ensure the safe and stable operation of the battery, and timely adjust the nodes where the current fluctuation is abnormal, avoid problems such as overcharging, over-discharging or overheating, and reduce the risk of battery failure.

[0135] Among them, the current control scheme refers to a set of systematic control strategies specially designed to ensure the efficient, stable and safe operation of the test battery pack. It takes the controllable current node as the key basis and covers many specific measures: on the one hand, it includes the precise limitation of the current size. For example, in the charging stage, when the current approaches the controllable current node that can cause battery overheating, the charging current is limited to a safe and efficient range by adjusting the charger output voltage or switching the circuit topology; on the other hand, it involves the control of current flow direction. When the battery pack is discharging and supplying energy, according to the load demand and battery status, with the help of intelligent switches, relays and other components, the current is reasonably distributed to different branches to ensure the power supply of key equipment and avoid unnecessary shunt losses. Optionally, the generation of the current control scheme corresponding to the test battery can be achieved through a scheme generation tool, such as: MTPA-MPTV, iBLDC and other tools.

[0136] Compared with the problems described in the background technology, the present invention obtains the load demand information corresponding to the test battery, and can accurately adapt to the application scenarios. For example, according to the multi-tasking operation of smart phones and different working conditions of electric vehicles, the current output can be planned in advance to avoid the shortcomings of fixed current limiting, which is helpful to build a simulation control environment that fits the reality to simulate complex and changeable real-life usage conditions and lay the foundation for subsequent precise control. By monitoring the real-time current data under the simulation control environment, the present invention can grasp the battery working status in real time, detect abnormal current fluctuations in time, prevent battery failures, ensure safe and stable operation of the system, help optimize the battery management strategy, adjust the charging and discharging parameters according to the current data, and extend the battery life. Furthermore, the present invention formulates the voltage regulation strategy corresponding to the test battery based on the current deviation value, which can accurately adapt to the battery working status and realize the real-time current deviation according to the current deviation. Adjust the voltage in time to ensure efficient and stable power supply of the battery, such as improving the endurance and power performance in electric vehicles, which can effectively extend the battery life and avoid problems such as overcharging and over-discharging caused by abnormal current fluctuations. The battery health is maintained through voltage regulation. Furthermore, based on the performance control system, the present invention analyzes the discharge response effect of the test battery under different load mutation conditions, which can accurately understand the emergency power supply capacity of the battery and understand whether the battery can quickly adjust the output when the load suddenly changes, to ensure the stable operation of the electrical equipment and reduce the risk of power outages. Finally, based on the core change elements, the present invention connects the preset intelligent feedback adjustment unit with the test battery for testing to form a test battery group, which can accurately perceive the battery working condition according to the core change elements. The intelligent unit monitors the voltage sudden change, slope turning point and other conditions in real time, and responds quickly to ensure stable power supply of the battery. Therefore, the intelligent voltage-regulated battery output current control method and system provided in the embodiment of the present invention can improve the control efficiency of the battery output current.

[0137] Example 2:

[0138] like Figure 2 FIG. 1 is a functional module diagram of an intelligent voltage-regulated battery output current control system according to the present invention.

[0139] The intelligent voltage-regulated battery output current control system 200 described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the intelligent voltage-regulated battery output current control system may include an environment construction module 201, a deviation value calculation module 202, a system construction module 203, a factor identification module 204, and a solution generation module 205. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These modules are stored in the electronic device's memory.

[0140] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0141] The environment construction module 201 is used to obtain load demand information corresponding to the test battery, analyze the application scenario corresponding to the test battery based on the load demand information, set the initial regulation voltage adapted to the test battery based on the application scenario, and construct a simulated control environment corresponding to the test battery based on the initial regulation voltage;

[0142] The deviation value calculation module 202 is used to monitor the real-time current data under the simulated control environment, extract the current fluctuation details in the real-time current data, and calculate the current deviation values of the test battery under different operating conditions based on the current fluctuation details;

[0143] The system construction module 203 is configured to formulate a voltage regulation strategy corresponding to the test battery based on the current deviation value, perform multiple rounds of load testing on the test battery based on the voltage regulation strategy, obtain multiple rounds of test records, calculate the current load index corresponding to each record in the multiple rounds of test records, and construct a performance control system corresponding to the test battery based on the current load index;

[0144] The element identification module 204 is configured to analyze the discharge response of the test battery under different load mutation conditions based on the performance control system, query the voltage change trend of the test battery during the discharge process based on the discharge response, and identify the core change elements in the voltage change trend;

[0145] The scheme generation module 205 is used to test connect the preset intelligent feedback adjustment unit with the test battery based on the core change elements to form a test battery group, collect dynamic current data of the test battery group during operation, and screen the controllable current nodes in the dynamic current data, and generate a current control scheme corresponding to the test battery based on the controllable current nodes.

[0146] In detail, the modules in the intelligent voltage-regulated battery output current control system 200 according to the embodiment of the present invention are used in the same manner as above. Figure 1 The intelligent voltage-regulated battery output current control method described in the preceding claims has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0147] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0148] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent voltage-regulated battery output current control method, characterized in that: The method comprises: Obtaining load demand information corresponding to a test battery, analyzing an application scenario corresponding to the test battery based on the load demand information, setting an initial regulation voltage adapted for the test battery based on the application scenario, and constructing a simulated control environment corresponding to the test battery based on the initial regulation voltage; monitoring real-time current data under the simulated control environment, extracting detailed current fluctuation values from the real-time current data, and calculating current deviation values of the test battery under different operating conditions based on the detailed current fluctuation values; Based on the current deviation value, a voltage regulation strategy corresponding to the test battery is formulated. Based on the voltage regulation strategy, multiple rounds of load testing are performed on the test battery to obtain multiple rounds of test records. The current load index corresponding to each record in the multiple rounds of test records is calculated. The current load index is a quantitative indicator used to measure the closeness of the relationship between the output current of the battery and the load demand during the load test. The current load index comprehensively considers the size and nature of the load, as well as the size and stability of the actual output current of the battery under the load. Based on the current load index, a performance control system corresponding to the test battery is constructed. The construction of the performance control system corresponding to the test battery based on the current load index includes: Analyzing the index fluctuation range corresponding to the current load index; Based on the index fluctuation range, the current load index is classified into intervals to obtain index classification intervals; Identifying energy efficiency variation patterns corresponding to indices in the index classification interval; Integrating the energy efficiency change rules to obtain an energy efficiency integration set; Based on the energy efficiency integration set, a performance control system corresponding to the test battery is constructed. The performance control system refers to a comprehensive system built on the energy efficiency integration set and includes monitoring, judgment, and regulation functions. The system can monitor the current load index in real time, quickly determine the index classification range to which it belongs, and automatically trigger regulation measures based on the corresponding energy efficiency change pattern. Based on the performance control system, analyzing the discharge response effect of the test battery under different load mutation conditions, querying the voltage change trend of the test battery during the discharge process based on the discharge response effect, and identifying the core change factors in the voltage change trend; Based on the core change elements, the preset intelligent feedback adjustment unit is tested and connected to the test battery to form a test battery group. The dynamic current data of the test battery group during operation is collected, and the controllable current nodes in the dynamic current data are screened. Based on the controllable current nodes, the current control scheme corresponding to the test battery is generated.

2. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The analyzing, based on the load demand information, the application operating scenario corresponding to the test battery includes: Collecting current peak and valley data in the load demand information; Dividing the load time interval corresponding to the load demand information based on the current peak and valley data; Extracting the load duration and load frequency corresponding to the load time period; Determining a load operating mode corresponding to the test battery based on the load duration and the load frequency; Based on the load operating mode, the application operating scenario corresponding to the test battery is analyzed.

3. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The step of constructing a simulated control environment corresponding to the test battery based on the initial adjustment voltage includes: querying a key regulation point in the initial regulation voltage; Calculating the regulated power consumption value corresponding to the key regulation point; Determining a power consumption adjustment direction corresponding to the test battery based on the adjusted power consumption value; Analyze the power consumption control scenario corresponding to the battery under the power consumption adjustment direction; Based on the power consumption control scenario, a simulated control environment corresponding to the test battery is constructed.

4. The intelligent voltage-regulated battery output current control method according to claim 3, wherein: The calculating the regulated power consumption value corresponding to the key regulation point includes: The regulated power consumption value corresponding to the key regulation point is calculated using the following formula: in, Indicates the regulated power consumption value corresponding to the key regulation point, represents the voltage value corresponding to the key regulation point, Indicates at time The current value corresponding to the battery is and Respectively represent the start time and end time of the power consumption measurement period, Indicates the internal resistance of the battery. Indicates the load equivalent resistance.

5. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The monitoring of real-time current data under the simulated control environment includes: Deploy intelligent sensing nodes in the simulated control environment; collecting a current sensing signal from the intelligent sensing node; Converting the current sensing signal into a digital signal code; generating a current data sequence corresponding to the digital signal code; Dividing the data subsequences corresponding to the current data sequence; Based on the data subsequence, real-time current data in the simulated control environment is monitored.

6. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The calculating, based on the current fluctuation detailed value, the current deviation value of the test battery under different operating conditions includes: The current deviation value of the test battery under different working conditions is calculated using the following formula: in, Indicates the current deviation value of the test battery under different working conditions, Indicates the total number of detailed values corresponding to the current fluctuation detailed value, Indicates the quantity index corresponding to the current fluctuation detailed value, Indicates the The weight coefficient corresponding to the current fluctuation value is: Indicates the The normalized value corresponding to the current fluctuation value, Indicates the total number of working conditions corresponding to different working conditions, Indicates the quantity index corresponding to different working conditions, Indicates the The current adjustment value under each working condition is: Represents the normalization constant.

7. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The step of performing multiple rounds of load testing on the test battery based on the voltage regulation strategy to obtain multiple rounds of test records includes: Based on the voltage regulation strategy, setting the initial load parameters corresponding to the test battery; Based on the initial load parameters, performing a first round of testing on the test battery to obtain the first round of load parameters; Based on the first round of load parameters, optimizing and adjusting the load test environment of the test battery to obtain a load optimized environment; Based on the load optimization environment, multiple rounds of load testing are performed on the test battery to obtain multiple rounds of test records.

8. The intelligent voltage-regulated battery output current control method according to claim 1, wherein: The querying of a voltage change trend of the test battery during the discharge process based on the discharge response effect includes: querying a response highlight node in the discharge response effect; sorting out the discharge highlight phase corresponding to the response highlight node; Analyzing the voltage change wave value corresponding to the discharge highlight stage; Extracting the influence factors of the change in the voltage change wave value; Based on the change influencing factors, the voltage change trend of the test battery during the discharge process is queried.

9. An intelligent voltage-regulated battery output current control system, characterized in that: The system comprises: An environment construction module is used to obtain load demand information corresponding to a test battery, analyze an application operating scenario corresponding to the test battery based on the load demand information, set an initial regulation voltage adapted for the test battery based on the application operating scenario, and construct a simulated control environment corresponding to the test battery based on the initial regulation voltage; a deviation value calculation module, configured to monitor real-time current data under the simulated control environment, extract detailed current fluctuation values from the real-time current data, and calculate current deviation values of the test battery under different operating conditions based on the detailed current fluctuation values; A system construction module is used to formulate a voltage regulation strategy corresponding to the test battery based on the current deviation value, perform multiple rounds of load testing on the test battery based on the voltage regulation strategy, obtain multiple rounds of test records, and calculate the current load index corresponding to each record in the multiple rounds of test records, wherein the current load index refers to a quantitative indicator used to measure the closeness of the relationship between the output current of the battery and the load demand during the load test, which comprehensively considers the size and nature of the load and the size and stability of the actual output current of the battery under the load. Based on the current load index, a performance control system corresponding to the test battery is constructed. The construction of the performance control system corresponding to the test battery based on the current load index includes: Analyzing the index fluctuation range corresponding to the current load index; Based on the index fluctuation range, the current load index is classified into intervals to obtain index classification intervals; Identifying energy efficiency variation patterns corresponding to indices in the index classification interval; Integrating the energy efficiency change rules to obtain an energy efficiency integration set; Based on the energy efficiency integration set, a performance control system corresponding to the test battery is constructed. The performance control system refers to a comprehensive system built on the energy efficiency integration set and includes monitoring, judgment, and regulation functions. The system can monitor the current load index in real time, quickly determine the index classification range to which it belongs, and automatically trigger regulation measures based on the corresponding energy efficiency change pattern. an element identification module, configured to analyze, based on the performance control system, the discharge response effect of the test battery under different load mutation conditions, query the voltage change trend of the test battery during the discharge process based on the discharge response effect, and identify the core change element in the voltage change trend; A scheme generation module is used to test connect the preset intelligent feedback adjustment unit with the test battery based on the core change elements to form a test battery group, collect dynamic current data of the test battery group during operation, and screen the controllable current nodes in the dynamic current data, and generate a current control scheme corresponding to the test battery based on the controllable current nodes.

Images