Power supply intelligent management system of AGV

Abstract

The invention discloses a power supply intelligent management system of an AGV trolley, and relates to the technical field of intelligent management, during operation of the system, data monitoring is performed through various sensors, measuring equipment and a battery management system BMS, and internal resistance data, battery capacity attenuation conditions and battery charging and discharging conditions of a battery of the AGV trolley are acquired in real time; the battery health index is comprehensively calculated through the battery internal resistance coefficient, the battery capacity attenuation coefficient and the battery charging and discharging efficiency coefficient, the output power of the battery is dynamically adjusted, the charging and discharging process of the battery is automatically adjusted according to data collected in real time and a load evaluation result, and intelligent scheduling is achieved according to needs. By analyzing the health data, the charging and discharging behaviors and the working environment of the battery, the battery fault is predicted in time, automatic fault detection and early warning are supported, system shutdown or performance reduction caused by the battery fault is avoided, an interactive interface between a user and the system is provided, and remote monitoring and control are supported at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management, and particularly to a power intelligent management system for an AGV vehicle. Background Art

[0002] With the rapid development of automation technology, the automatic guided vehicle (AGV), as an important part of the intelligent logistics system, has been widely used in manufacturing, warehousing, and other logistics industries. The AGV vehicle relies on batteries to provide power and undertakes tasks such as item handling and transportation. Due to the complex operating environment and changing loads of the AGV vehicle, battery management has become a key factor affecting its operating efficiency and service life. The battery not only needs to cope with the high-frequency charge and discharge process but also maintain a stable energy supply under different loads and working conditions. Therefore, the traditional battery management method gradually fails to meet the high requirements of modern AGV vehicles for battery performance and management.

[0003] In the traditional battery management of AGV vehicles, simple charging control and periodic maintenance methods are usually adopted, which are difficult to effectively cope with challenges brought by factors such as battery performance degradation and load fluctuations. This traditional management mode ignores the real-time assessment of the battery health status, resulting in problems such as increased internal resistance, capacity attenuation, and decreased charge and discharge efficiency of the battery during long-term use, which are difficult to detect in a timely manner. Especially in the case of high loads or long-term continuous use, the battery performance deteriorates relatively rapidly. If not intervened in a timely manner, it is easy to cause battery failures or the shutdown of the AGV vehicle. In addition, the traditional battery management system has a relatively single optimization for the charging process and cannot dynamically adjust the charging strategy according to different working environments and load conditions, resulting in a large amount of energy waste during the battery charging process. In severe cases, overcharging or over-discharging may occur, which will damage the battery and affect its service life. Therefore, the traditional management system cannot achieve comprehensive health monitoring and intelligent scheduling of the battery, nor can it meet the requirements of AGV vehicles for efficient and stable battery management. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a power intelligent management system for an AGV vehicle, which solves the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A power intelligent management system for an AGV vehicle includes a data acquisition module, a battery status monitoring module, a health assessment module, a power management module, a fault warning module, and a remote monitoring module; The data acquisition module is used to monitor data through a variety of sensors, measuring devices, and the battery management system BMS, and collect in real-time the internal resistance data of the AGV vehicle battery, the battery capacity attenuation situation, and the battery charge and discharge situation; The battery status monitoring module is used to evaluate the operating status, performance degradation, and efficiency during the charging and discharging processes of the battery by real-time monitoring of various battery parameters, and to monitor the battery temperature in real time; The health assessment module is used to evaluate the load condition of the AGV vehicle and its energy consumption during operation, and to comprehensively calculate the battery health index BHI through the internal resistance coefficient IRC, battery capacity decay coefficient CDC, and battery charge and discharge efficiency coefficient CDEC of the battery, and dynamically adjust the output power of the battery; The power management module is used to automatically adjust the charging and discharging processes of the battery according to the real-time collected data and the load assessment results, and to achieve intelligent scheduling as needed; The fault warning module is used to timely predict the upcoming faults of the battery by analyzing the health data, charging and discharging behaviors, and working environment of the battery, and to provide fault warnings and regular maintenance suggestions, supporting automated fault detection and early warning; The remote monitoring module is used to provide an interaction interface between the user and the system, support the visual display of battery status, charging and discharging data, and maintenance records, and the user interface also supports remote monitoring and control.

[0006] Preferably, the data acquisition module includes an internal resistance acquisition unit, a battery capacity decay acquisition unit, and a battery charge and discharge status acquisition unit; The internal resistance acquisition unit is used to monitor the change of the internal resistance of the AGV vehicle battery in real time, monitor the voltage drop and current change of the battery under different working conditions through the built-in voltage and current sensors, and obtain: the original internal resistance value R int , the real-time measured battery temperature T b and the battery charge and discharge rate Crate, and transmit the internal resistance measurement results to the battery management system BMS in real time to perform temperature compensation on the internal resistance value to avoid the interference of environmental temperature changes on the internal resistance measurement results; The battery capacity decay acquisition unit is used to monitor the capacity decay of the AGV vehicle battery in real time, monitor the charging and discharging processes, cycle times, and remaining battery capacity of the battery, use the battery voltage and current data, combine with the battery discharge curve, track each charging and discharging cycle through the battery management system BMS, record the charging and discharging cycle times of the battery, monitor the deep discharge condition of the battery, and obtain: the remaining battery capacity C remain , the current charging and discharging cycle times N cycle and the deep discharge DoD, and transmit the relevant data to the battery management system BMS for analysis; The battery charge and discharge status acquisition unit is used to monitor the charge and discharge status of the AGV vehicle battery in real time through current sensors and voltage sensors, including the charging current, voltage, and discharge rate of the battery, monitor whether there are abnormal behaviors such as overcharging, over-discharging, and overheating during the charging and discharging processes, and obtain: the charging efficiency charge 、Discharge efficiency d ischarge and self-discharge rate S discharge 。

[0007] Preferably, the battery state monitoring module includes a battery temperature monitoring unit, a battery state analysis unit, and a charge and discharge efficiency monitoring unit; The battery temperature monitoring unit is used to install temperature sensors at key positions of the battery pack, including NTC temperature sensors and PT100 sensors, for real-time monitoring of the working temperature of the battery. Too high or too low battery temperature will affect the charge and discharge efficiency, internal resistance, and capacity of the battery; The battery state analysis unit is used to continuously monitor the changes in the internal resistance and capacity of the battery through the battery management system BMS, including the performance degradation, internal resistance change, and capacity loss of the battery. Combining temperature, charge and discharge data, and battery life data, using an algorithm model to evaluate the operating state of the battery, analyzing the degradation trend of the battery based on historical data and real-time data, and predicting the remaining service life of the battery; The charge and discharge efficiency monitoring unit is used to monitor the efficiency of the battery during the charging and discharging processes, evaluate the energy conversion efficiency of the battery charging and discharging. The charge and discharge efficiency of the battery directly affects the energy utilization rate and overall operating efficiency of the battery. Through real-time monitoring and analysis of the charging current, charging voltage, discharging current, discharging voltage, and temperature, ensure that the charging and discharging processes of the battery are in an optimal state.

[0008] Preferably, the health assessment module includes a battery health index calculation unit; The battery health index calculation unit is used to real-time monitor the load condition of the AGV vehicle, and calculate the required energy consumption according to the load data, calculate and obtain: the internal resistance coefficient of the battery IRC, according to the remaining capacity of the battery, the number of cycles, and the deep discharge condition, calculate and obtain: the capacity attenuation coefficient of the battery CDC, according to the real-time monitoring of the current, voltage, and discharge rate during the charging and discharging processes of the battery, calculate and obtain: the charge and discharge efficiency coefficient of the battery CDEC. Through the internal resistance coefficient of the battery IRC, the capacity attenuation coefficient of the battery CDC, and the charge and discharge efficiency coefficient of the battery CDEC, comprehensively calculate the battery health index BHI; The internal resistance coefficient of the battery IRC is calculated and obtained through the following formula: ; In the formula, R int,comp represents the internal resistance value after temperature compensation, R int represents the original internal resistance value, α represents the temperature coefficient, T b represents the real-time measured battery temperature, T nominal represents the standard operating temperature of the battery, β represents the charge and discharge rate coefficient, and Crate represents the charge and discharge rate.

[0009] Preferably, the battery capacity decay coefficient CDC is obtained by calculating through the following formula: ; In the formula, C remain represents the remaining capacity of the battery, C nominal represents the rated capacity of the battery, γ represents the capacity decay factor, N cycle represents the current charge and discharge cycle number, N max represents the maximum charge and discharge cycle number of the battery, δ represents the deep discharge decay factor, and DoD represents deep discharge.

[0010] Preferably, the battery charge and discharge efficiency coefficient CDEC is obtained by calculating through the following formula: ; In the formula, CDEC represents the battery charge and discharge efficiency coefficient, c harge represents the charge efficiency, d ischarge represents the discharge efficiency, E charge represents the electric energy input during the charging process, E discharge represents the electric energy output during the discharging process, S discharge represents the self-discharge rate, that is, the electric energy loss rate of the battery in the static state, E total represents the total electric energy of the battery; The battery health index BHI is obtained by calculating through the following formula: ; In the formula, respectively represent the weight coefficients, indicating the contribution ratio of each coefficient to the total index, IRC represents the battery internal resistance coefficient, CDC represents the battery capacity decay coefficient, and CDEC represents the battery charge and discharge efficiency coefficient.

[0011] Preferably, the power management module includes a charge and discharge regulation unit, a battery state optimization unit, and an intelligent scheduling unit; The charge and discharge regulation unit is used to adjust the charge or discharge mode according to the load evaluation result and the battery health index BHI by collecting the charging current, voltage, and remaining capacity data of the battery in real time, automatically regulate the charging power and the discharging power, and control the working modes of the battery including the charging, discharging, and standby modes. According to the health state of the battery and the load demand, by optimizing the charge and discharge rate, the battery life and the efficient operation of the system are ensured; The battery state optimization unit is used to evaluate the current state of the battery by analyzing the real-time data, including the battery internal resistance, temperature, and charging rate, make predictive adjustments in combination with the indicators of battery capacity decay and charge and discharge efficiency, and dynamically adjust the working mode of the battery according to the load change, working environment, and battery performance decline, so as to extend the battery service life and reduce the energy loss; The intelligent scheduling unit is used to provide real-time feedback on the load and battery health status. Through an optimization algorithm, the intelligent scheduling unit can determine when the battery enters the charging, standby, or discharging state, and at the same time dynamically adjust the switching frequency and transition time of each working mode. The scheduling result is updated in real time and fed back to the battery management system BMS.

[0012] Preferably, the fault warning module includes a fault prediction unit, a grade evaluation unit, and an alarm unit; The fault prediction unit is used to analyze the real-time monitoring data of the battery, including internal resistance, voltage, current, and temperature, and uses an intelligent algorithm to predict the fault risk of the battery, and detects in real time the abnormal behaviors that will occur during the charging and discharging processes of the battery, including overcharging, over-discharging, and overheating, and gives an early warning of the impending fault; The grade evaluation unit is used to obtain the battery health status based on the battery operation data, including capacity attenuation, number of cycles, and self-discharge rate, and obtains a grade evaluation plan by comparing the battery health index BHI with a preset first qualified threshold M and a second qualified threshold N; When BHI≥M, the first evaluation grade is obtained, and the battery status is rated as qualified. Within this range, the health status, capacity, and charge and discharge efficiency of the battery are all within the normal range, the system continues to operate normally, the operation mode of the battery is maintained, no special adjustment is required, and the charging cycle is optimized according to the workload to avoid overcharging; When N≤BHI<M, the second evaluation grade is obtained, and the battery status is rated as unqualified. The performance of the battery deteriorates. According to the health status of the battery, the charging current and discharge power are reduced to avoid overloading operation, the increase of internal resistance and capacity attenuation are reduced, the maximum charging power limit is set to avoid overcharging, and in the case of high load, a more stable discharge method is recommended. It is recommended to conduct regular inspections on the battery and increase the maintenance frequency of the battery once a month; When BHI<N, the third evaluation grade is obtained, and the battery status is rated as the fault warning grade, which causes problems such as the AGV cart stopping or its performance degrading. Immediate intervention is required. The battery must immediately stop being used under high load or high-frequency charging and discharging conditions, and the operation frequency of the AGV cart is suspended or reduced to avoid further damage caused by overuse.

[0013] Preferably, the alarm unit triggers the alarm mechanism of the system according to the fault prediction result and health assessment data, notifies the maintenance personnel for timely handling, generates a detailed fault report according to the fault type, and provides different levels of early warnings according to the severity of the battery fault, and automatically executes part of the fault detection program according to the real-time monitoring data to reduce human intervention.

[0014] Preferably, the remote monitoring module includes a data visualization unit, a remote monitoring unit, and a remote control unit; The data visualization unit is used to display the key information of the battery's real-time status, charge and discharge data, temperature, capacity, and health index in the form of charts and dashboards, provide a user interface that allows users to view historical data, prediction results, and system warnings according to their needs, and help users quickly grasp the battery health status; The remote monitoring unit is used to remotely monitor the battery system through the Internet, receive battery status data in real time, and allow users to remotely monitor the charge and discharge process of the battery through an application or a web interface. Users can view the battery operation status at any time, adjust the battery working mode, or conduct fault troubleshooting; The remote control unit is used to remotely control the battery system, including functions such as adjusting the charge and discharge mode, setting the charging time window, and controlling the battery standby state. It allows users to remotely adjust the working state of the battery according to the system operation status and task requirements to optimize the battery operation efficiency and service life, and supports regular automatic update of system parameters.

[0015] The present invention provides a power intelligent management system for an AGV vehicle, which has the following beneficial effects:

[0016] (2)The intelligent power management system of the AGV vehicle in the present invention effectively realizes the comprehensive and real-time management of the AGV vehicle battery by integrating a data acquisition module, a battery status monitoring module, a health assessment module, a power management module, a fault warning module, and a remote monitoring module. The data acquisition module can accurately collect multiple key data such as the internal resistance of the battery, the attenuation of the battery capacity, and the charge and discharge status, ensuring the real-time monitoring of the battery health status. The battery status monitoring module further combines indicators such as temperature, internal resistance, and capacity to comprehensively evaluate the performance decline and charge and discharge efficiency of the battery, ensuring that the battery is always in the best working state. The health assessment module effectively optimizes the charge and discharge process of the battery and improves the energy utilization efficiency by calculating the battery health index BHI and dynamically adjusting the output power of the battery. Finally, the system can realize the real-time assessment, intelligent scheduling, and optimization adjustment of the battery health status, significantly improving the operation efficiency and battery service life of the AGV vehicle.

[0017] (3)Compared with the existing traditional battery management systems, the intelligent power management system of the present invention has significant advantages. Traditional battery management systems often rely on regular maintenance and preset charging strategies, failing to fully consider the changing working environment and load requirements of the battery during actual use, resulting in frequent occurrences of battery performance decline, overcharging, and over-discharging. However, by introducing real-time monitoring and data analysis, this system can accurately calculate the battery health index and dynamically adjust the charging and discharging modes according to data such as load, temperature, and charge and discharge efficiency. The system can detect the changes in battery internal resistance, capacity attenuation, and charge and discharge efficiency in real time, avoiding the problem of slow response to battery health changes in traditional methods, thus significantly reducing the risk of system downtime caused by battery failures and avoiding excessive battery life loss and energy waste.

[0018] (4)By introducing a fault warning module and a remote monitoring module, the present invention enables the system to timely predict and diagnose potential battery fault problems, further optimizing the operation efficiency and reliability of the AGV vehicle. Based on the analysis of battery health data, the fault warning module can monitor the operation status of the battery in real time, identify potential battery fault risks in advance, and issue warnings to help maintenance personnel intervene in a timely manner to avoid the further aggravation of faults. The remote monitoring module provides real-time battery health data and charge and discharge status, enabling users to adjust the battery operation mode at any time and remotely conduct fault troubleshooting and maintenance management. These innovative functions improve the intelligent level of the system, enabling the AGV vehicle to operate in an efficient and stable state, reducing the operation cost, and greatly improving the reliability and economy of the overall system by extending the battery service life and reducing the failure rate. Description of the Drawings

[0019] Figure 1This is a block diagram of the power intelligent management system for an AGV cart of the present invention. Specific embodiments

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] Embodiment 1 The present invention provides a power intelligent management system for an AGV cart. Please refer to Figure 1 , which includes a data acquisition module, a battery status monitoring module, a health assessment module, a power management module, a fault warning module, and a remote monitoring module; The data acquisition module is used to monitor data through a variety of sensors, measurement devices, and the battery management system BMS, and collect the internal resistance data of the AGV cart battery, the battery capacity attenuation, and the battery charge and discharge conditions in real time; The battery status monitoring module is used to evaluate the operating status of the battery, performance attenuation, and efficiency during the charging and discharging process by real-time monitoring of various battery parameters, and monitor the battery temperature in real time; The health assessment module is used to evaluate the load condition of the AGV cart and its energy consumption during operation, and comprehensively calculate the battery health index BHI through the internal resistance coefficient IRC of the battery, the capacity attenuation coefficient CDC of the battery, and the charge and discharge efficiency coefficient CDEC of the battery, and dynamically adjust the output power of the battery; The power management module is used to automatically adjust the charging and discharging process of the battery according to the real-time collected data and the load assessment result, and achieve intelligent scheduling as needed; The fault warning module is used to predict the upcoming faults of the battery in time by analyzing the health data, charge and discharge behavior, and working environment of the battery, and provide fault warnings and regular maintenance suggestions, supporting automatic fault detection and early warning; The remote monitoring module is used to provide an interaction interface between the user and the system, support the visual display of the battery status, charge and discharge data, and maintenance records, and the user interface also supports remote monitoring and control.

[0022] In this embodiment, data monitoring is carried out through a variety of sensors, measurement devices and battery management system BMS. The internal resistance data, battery capacity attenuation and charge-discharge conditions of the AGV car battery are collected in real time. By real-time monitoring of various battery parameters, the operating state, performance attenuation and efficiency during the charge-discharge process of the battery are evaluated. The battery temperature is monitored in real time, the working temperature of the battery is obtained through a temperature sensor, the influence of temperature change on battery performance is analyzed, the load condition of the AGV car and its energy consumption during operation are evaluated. Through the internal resistance coefficient IRC, battery capacity attenuation coefficient CDC and charge-discharge efficiency coefficient CDEC of the battery, the battery health index BHI is comprehensively calculated, and the output power of the battery is dynamically adjusted. According to the real-time collected data and load evaluation results, the charge-discharge process of the battery is automatically adjusted, the usage mode of the battery is optimized, and the charging, discharging and standby modes are automatically switched. Intelligent scheduling is realized according to needs. By analyzing the health data, charge-discharge behavior and working environment of the battery, the impending battery failures are predicted in time, and fault warnings and regular maintenance suggestions are provided, supporting automatic fault detection and early warning, avoiding system downtime or performance degradation caused by battery failures, providing an interaction interface between users and the system, supporting the visual display of battery status, charge-discharge data and maintenance records, and the user interface also supports remote monitoring and control to ensure the efficient operation of the AGV car in different working environments.

[0023] Embodiment 2 This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The data acquisition module includes an internal resistance acquisition unit, a battery capacity attenuation acquisition unit and a battery charge-discharge state acquisition unit; The internal resistance acquisition unit is used to monitor the change of the internal resistance of the AGV car battery in real time. By monitoring the voltage drop and current change of the battery under different working states through the built-in voltage and current sensors, the following are obtained: the original internal resistance value R int , the battery temperature T b measured in real time and the battery charge-discharge rate Crate. The internal resistance measurement results are transmitted to the battery management system BMS in real time, and temperature compensation is performed on the internal resistance value to avoid the interference of environmental temperature change on the internal resistance measurement results; The battery capacity attenuation acquisition unit is used to monitor the capacity attenuation of the AGV car battery in real time. By monitoring the charge-discharge process, cycle times and remaining battery capacity of the battery, using the battery voltage and current data, combined with the battery discharge curve, the battery management system BMS tracks each charge-discharge cycle, counts the charge-discharge cycle times of the battery, monitors the deep discharge condition of the battery, and obtains: the remaining battery capacity C remain , the current charge-discharge cycle times N cycle and the deep discharge DoD, and transmits the relevant data to the battery management system BMS for analysis; The battery charge and discharge state acquisition unit is used to monitor the charge and discharge state of the AGV car battery in real time through a current sensor and a voltage sensor, including the charging current, voltage and discharge rate of the battery, monitor whether there are abnormal behaviors such as overcharging, over-discharging and overheating during the charge and discharge process, and obtain: charging efficiency c harge , discharge efficiency d ischarge and self-discharge rate S discharge .

[0024] In this embodiment, through the collaborative work of the internal resistance acquisition unit, the battery capacity attenuation acquisition unit and the battery charge and discharge state acquisition unit, the data acquisition module can comprehensively and real-time monitor the key parameters of the AGV car battery, ensuring an accurate grasp of the battery health state. The internal resistance acquisition unit eliminates the interference of ambient temperature changes on the internal resistance measurement results through temperature compensation technology, providing more accurate battery state data; the battery capacity attenuation acquisition unit can track the charge and discharge cycles, capacity attenuation and deep discharge conditions of the battery, so as to accurately evaluate the remaining service life of the battery; the battery charge and discharge state acquisition unit monitors the efficiency changes during the charge and discharge process in real time, discovers abnormal conditions such as overcharging, over-discharging and overheating in time, and improves the safety and efficiency of the battery. Through the real-time acquisition and analysis of these data, the battery management system can perform more accurate health assessment and management, thereby effectively extending the battery service life and improving the overall operation efficiency and reliability of the AGV car.

[0025] Embodiment 3 This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The battery state monitoring module includes a battery temperature monitoring unit, a battery state analysis unit and a charge and discharge efficiency monitoring unit; The battery temperature monitoring unit is used to install temperature sensors at key positions of the battery pack, including NTC temperature sensors and PT100 sensors, for real-time monitoring of the working temperature of the battery. Too high or too low battery temperature will affect the charge and discharge efficiency, internal resistance and capacity of the battery; The battery state analysis unit is used to continuously monitor the changes in the internal resistance and capacity of the battery through the battery management system BMS, including the performance attenuation, internal resistance change and capacity loss of the battery, combine temperature, charge and discharge data and battery life data, use an algorithm model to evaluate the operating state of the battery, analyze the decline trend of the battery based on historical data and real-time data, and predict the remaining service life of the battery; The charge-discharge efficiency monitoring unit is used to monitor the efficiency of the battery during the charging and discharging processes, evaluate the energy conversion efficiency of the battery charging and discharging. The charge-discharge efficiency of the battery directly affects the energy utilization rate and the overall operation efficiency of the battery. By monitoring and analyzing the charging current, charging voltage, discharging current, discharging voltage, and temperature in real time, it ensures that the charge-discharge process of the battery is in an optimal state.

[0026] The health assessment module includes a battery health index calculation unit; The battery health index calculation unit is used to monitor the load condition of the AGV vehicle in real time, calculate the required energy consumption according to the load data, calculate and obtain: the internal resistance coefficient IRC of the battery, calculate and obtain: the capacity decay coefficient CDC of the battery according to the remaining battery capacity, number of cycles, and depth of discharge, calculate and obtain: the charge-discharge efficiency coefficient CDEC of the battery according to the current, voltage, and discharge rate monitored in real time during the charge-discharge process of the battery. The battery health index BHI is comprehensively calculated through the internal resistance coefficient IRC, capacity decay coefficient CDC, and charge-discharge efficiency coefficient CDEC of the battery; The internal resistance coefficient IRC of the battery is calculated and obtained through the following formula: ; In the formula, R int,comp represents the internal resistance value after temperature compensation, R int represents the original internal resistance value, α represents the temperature coefficient, T b represents the battery temperature measured in real time, T nominal represents the standard operating temperature of the battery, β represents the charge-discharge rate coefficient, and Crate represents the charge-discharge rate.

[0027] The capacity decay coefficient CDC of the battery is calculated and obtained through the following formula: ; In the formula, C remain represents the remaining battery capacity, C nominal represents the rated capacity of the battery, γ represents the capacity decay factor, N cycle represents the current number of charge-discharge cycles, N max represents the maximum number of charge-discharge cycles of the battery, δ represents the depth of discharge decay factor, and DoD represents the depth of discharge.

[0028] The charge-discharge efficiency coefficient CDEC of the battery is calculated and obtained through the following formula: ; In the formula, CDEC represents the charge-discharge efficiency coefficient of the battery, c harge represents the charging efficiency, d ischarge represents the discharging efficiency, E chargeRepresents the electrical energy input during the charging process, E discharge Represents the electrical energy output during the discharging process, S discharge Represents the self-discharge rate, that is, the electrical energy loss rate of the battery in the static state, E total Represents the total electrical energy of the battery; The battery health index BHI is obtained by calculating through the following formula: ; In the formula, respectively represent the weight coefficients, indicating the contribution ratio of each coefficient to the total index, IRC represents the battery internal resistance coefficient, CDC represents the battery capacity attenuation coefficient, and CDEC represents the battery charge and discharge efficiency coefficient.

[0029] In this embodiment, the battery status monitoring module effectively improves the accuracy and safety of battery management through the collaborative work of the battery temperature monitoring unit, the battery status analysis unit, and the charge and discharge efficiency monitoring unit. The battery temperature monitoring unit monitors the battery operating temperature in real time through a high-precision temperature sensor to ensure that the battery always operates within the ideal temperature range, thereby avoiding efficiency reduction or damage caused by abnormal temperature; the battery status analysis unit can continuously evaluate the operating status, performance degradation trend, and remaining service life of the battery by combining real-time monitoring data and algorithm models, and give early warnings of potential problems in advance; the charge and discharge efficiency monitoring unit ensures that the energy conversion during the charge and discharge process of the battery is in the optimal state, optimizes the energy utilization rate of the battery, and improves the overall operating efficiency. Through these monitoring and evaluation means, the system can not only extend the service life of the battery, but also significantly improve the performance stability of the battery, ensuring the efficient and safe operation of the AGV cart.

[0030] Embodiment 4 This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: The power management module includes a charge and discharge regulation unit, a battery status optimization unit, and an intelligent scheduling unit; The charge and discharge regulation unit is used to adjust the charge or discharge mode by collecting the charging current, voltage, and remaining capacity data of the battery in real time, adjust the charging power and discharge power automatically according to the load evaluation result and the battery health index BHI, and control the working modes of the battery including charging, discharging, and standby modes. According to the health status of the battery and the load demand, by optimizing the charge and discharge rate, it ensures the battery life and the efficient operation of the system; The battery status optimization unit is used to evaluate the current status of the battery by analyzing real-time data, including battery internal resistance, temperature, and charging rate, make predictive adjustments by combining indicators such as battery capacity attenuation and charge and discharge efficiency, and dynamically adjust the working mode of the battery according to load changes, working environment, and battery performance degradation, extend the battery service life, and reduce energy loss; The intelligent scheduling unit is used to provide real-time feedback on the load and battery health status. Through an optimization algorithm, the intelligent scheduling unit can determine when the battery enters the charging, standby, or discharging state, and simultaneously dynamically adjust the switching frequency and transition time of each working mode. The scheduling results are updated and fed back to the battery management system BMS in real time.

[0031] The fault warning module includes a fault prediction unit, a level evaluation unit, and an alarm unit; The fault prediction unit is used to analyze the real-time monitoring data of the battery, including internal resistance, voltage, current, and temperature, and uses an intelligent algorithm to predict the fault risk of the battery, and real-time detects abnormal behaviors that are about to occur during the charging and discharging processes of the battery, including overcharging, over-discharging, and overheating, and gives early warnings about upcoming faults; The level evaluation unit is used to obtain the battery health condition based on the battery operation data, including capacity attenuation, cycle times, and self-discharge rate, and obtains a level evaluation plan by comparing the battery health index BHI with a preset first qualified threshold M and a second qualified threshold N; When BHI≥M, the first evaluation level is obtained, and the battery status is rated as qualified. Within this range, the health condition, capacity, and charge and discharge efficiency of the battery are all within the normal range, and the system continues to operate normally, maintaining the battery operation mode without special adjustment, and optimizing the charging cycle according to the workload to avoid overcharging; When N≤BHI<M, the second evaluation level is obtained, and the battery status is rated as unqualified. The performance of the battery deteriorates. According to the health status of the battery, reduce the charging current and discharge power, avoid overloading operation, reduce the increase in internal resistance and capacity attenuation, set a maximum charging power limit to avoid overcharging, and in the case of high load, it is recommended to adopt a more stable discharge method, and it is recommended to conduct regular inspections on the battery and increase the monthly maintenance frequency of the battery; When BHI<N, the third evaluation level is obtained, and the battery status is rated as the fault warning level, which causes problems such as the AGV vehicle stopping or performance degradation. Immediate intervention is required. The battery must immediately stop being used under high load or high-frequency charging and discharging, suspend or reduce the operation frequency of the AGV vehicle, and avoid further damage caused by overuse.

[0032] The alarm unit triggers the alarm mechanism of the system according to the fault prediction results and health assessment data, and notifies the maintenance personnel for timely handling, generates a detailed fault report according to the fault type, and provides different levels of warnings according to the severity of the battery fault, and automatically executes some fault detection procedures according to the real-time monitoring data, reducing human intervention.

[0033] In this embodiment, the collaborative work of the power management module and the fault warning module greatly improves the management ability of the AGV car battery and the system reliability. Through the combination of the charge and discharge regulation unit, the intelligent scheduling unit and the battery state optimization unit, the system can adjust the charge and discharge mode in real time according to the battery health status and load demand, dynamically optimize the working mode of the battery, extend the battery life and improve the overall operation efficiency. The intelligent scheduling unit ensures that the battery always operates in the optimal state by real-time feedback of the load and battery health status, avoiding overloading or energy waste. The fault warning module analyzes the real-time data of the battery through intelligent algorithms, predicts and warns the battery fault risks in advance, including abnormal conditions such as overcharging, over-discharging, and overheating, thus effectively preventing the occurrence of potential faults and ensuring the safe and stable operation of the system. The level evaluation unit provides a precise assessment of the battery health status by comparing the battery health index BHI with the preset threshold, helping the management personnel to adjust the charging mode or perform maintenance in time, thereby reducing unnecessary battery damage. Overall, through the intelligent battery management and fault warning mechanism, the system not only optimizes the battery usage efficiency, but also greatly reduces the risk of equipment failure, improving the overall operation efficiency and reliability of the AGV car.

[0034] Embodiment 5 This embodiment is an explanatory illustration based on Embodiment 1. Please refer to Figure 1 , specifically: The remote monitoring module includes a data visualization unit, a remote monitoring unit, and a remote control unit; The data visualization unit is used to display the key information of the battery's real-time status, charge and discharge data, temperature, capacity, and health index in the form of charts and dashboards, provide a user interface that allows users to view historical data, prediction results, and system warnings according to their needs, and help users quickly grasp the battery health status; The remote monitoring unit is used to remotely monitor the battery system through the Internet, receive the battery status data in real time, and allow users to remotely monitor the charge and discharge process of the battery through an application or a web interface. Users can view the battery operation status at any time, adjust the battery working mode, or perform fault troubleshooting; The remote control unit is used to remotely control the battery system, including functions such as adjusting the charge and discharge mode, setting the charging time window, and controlling the battery standby state, allowing users to remotely adjust the working state of the battery according to the system operation status and task requirements to optimize the battery operation efficiency and service life, and supporting regular automatic update of system parameters.

[0035] In this embodiment, the remote monitoring module provides users with comprehensive battery status monitoring and management capabilities through the collaborative action of the data visualization unit, remote monitoring unit, and remote control unit. The data visualization unit displays the real-time status, charge and discharge data, temperature, capacity, and health index of the battery through charts and dashboards, intuitively presenting the key performance indicators of the battery, helping users quickly understand the health status and prediction results of the battery, and thus making timely decisions. The remote monitoring unit realizes real-time remote monitoring of the battery system through Internet technology. Users can view the operating status of the battery anytime and anywhere, and can adjust the charge and discharge process of the battery as needed, optimize the battery performance, and conduct fault troubleshooting in a timely manner. The remote control unit further improves the intelligent level of the system, allowing users to remotely adjust the charge and discharge mode, set the charging time window, and control the standby state of the battery, ensuring the efficient operation of the battery and the extension of its service life. Overall, the application of the remote monitoring module makes battery management more flexible and intelligent, improves the operation convenience and response speed, reduces the need for human intervention, and significantly improves the operation efficiency and safety of the system.

[0036] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power intelligent management system for an AGV cart, characterized in that: It includes a data acquisition module, a battery status monitoring module, a health assessment module, a power management module, a fault warning module, and a remote monitoring module; The data acquisition module is used to monitor data through a variety of sensors, measuring devices, and the battery management system BMS, and to collect in real time the internal resistance data of the AGV car battery, the battery capacity attenuation, and the battery charge and discharge conditions; The battery status monitoring module is used to evaluate the operating status, performance attenuation, and efficiency during the charge and discharge process of the battery by real-time monitoring of various battery parameters, and to monitor the battery temperature in real time; The health assessment module is used to evaluate the load condition of the AGV car and its energy consumption during operation, and to comprehensively calculate the battery health index BHI through the internal resistance coefficient IRC, the battery capacity attenuation coefficient CDC, and the charge and discharge efficiency coefficient CDEC of the battery, and dynamically adjust the output power of the battery; The power management module is used to automatically adjust the charge and discharge process of the battery according to the real-time collected data and the load assessment results, and to achieve intelligent scheduling as needed; The fault warning module is used to predict in a timely manner the upcoming faults of the battery by analyzing the health data, charge and discharge behavior, and working environment of the battery, and to provide fault warnings and regular maintenance suggestions, and to support automated fault detection and early warning; The remote monitoring module is used to provide an interactive interface between the user and the system, support the visual display of the battery status, charge and discharge data, and maintenance records, and the user interface also supports remote monitoring and control.

2. The intelligent power management system for an AGV cart according to claim 1, wherein: The data acquisition module includes an internal resistance acquisition unit, a battery capacity attenuation acquisition unit, and a battery charge and discharge status acquisition unit; The internal resistance acquisition unit is used to monitor the change of the internal resistance of the AGV car battery in real time. By means of the built-in voltage and current sensors, it monitors the voltage drop and current change of the battery under different working conditions, and obtains the original internal resistance value R int , the battery temperature T measured in real time b and the battery charge and discharge rate Crate, and transmits the internal resistance measurement result to the battery management system BMS in real time to perform temperature compensation on the internal resistance value to avoid the interference of environmental temperature change on the internal resistance measurement result; The battery capacity attenuation acquisition unit is used to monitor the capacity attenuation of the AGV car battery in real time. By monitoring the charging and discharging process, cycle times, and remaining battery capacity of the battery, using battery voltage and current data, combined with the battery discharge curve, tracking each charge and discharge cycle through the battery management system BMS, counting the charge and discharge cycle times of the battery, monitoring the deep discharge of the battery, and obtaining: the remaining battery capacity C remain , the current charge and discharge cycle times N cycle and the deep discharge DoD, and transmitting the relevant data to the battery management system BMS for analysis; The battery charge and discharge state acquisition unit is used to monitor the charge and discharge state of the AGV car battery in real time through current sensors and voltage sensors, including the charging current, voltage and discharge rate of the battery, monitor whether there are abnormal behaviors such as overcharging, over-discharging and overheating during the charge and discharge process, and obtain: charging efficiency c harge , discharge efficiency d ischarge and self-discharge rate S discharge .

3. The intelligent power management system for an AGV cart according to claim 1, wherein: The battery status monitoring module includes a battery temperature monitoring unit, a battery status analysis unit, and a charge and discharge efficiency monitoring unit; The battery temperature monitoring unit is used to install temperature sensors at key positions of the battery pack, including NTC temperature sensors and PT100 sensors, to monitor the working temperature of the battery in real time. Too high or too low battery temperature will affect the charge and discharge efficiency, internal resistance, and capacity of the battery; The battery status analysis unit is used to continuously monitor the changes in the internal resistance and capacity of the battery through the battery management system BMS, including the performance attenuation, internal resistance change, and capacity loss of the battery, and to evaluate the battery operating status using an algorithm model by combining temperature, charge and discharge data, and battery life data, and to analyze the degradation trend of the battery based on historical data and real-time data, and to predict the remaining service life of the battery; The charge and discharge efficiency monitoring unit is used to monitor the efficiency of the battery during the charge and discharge process, evaluate the energy conversion efficiency of the battery charge and discharge. The charge and discharge efficiency of the battery directly affects the energy utilization rate and the overall operating efficiency of the battery. By real-time monitoring and analysis of the charging current, charging voltage, discharging current, discharging voltage, and temperature, ensure that the charge and discharge process of the battery is in an optimal state.

4. The intelligent power management system for an AGV cart according to claim 1, wherein: The health assessment module includes a battery health index calculation unit; The battery health index calculation unit is used to monitor the load condition of the AGV vehicle in real time, calculate the required energy consumption according to the load data, and calculate and obtain: the internal resistance coefficient IRC of the battery, calculate and obtain: the capacity decay coefficient CDC of the battery according to the remaining capacity, number of cycles and deep discharge condition of the battery, calculate and obtain: the charge-discharge efficiency coefficient CDEC of the battery according to the current, voltage and discharge rate during the charge and discharge process of the battery in real time, and comprehensively calculate the battery health index BHI through the internal resistance coefficient IRC, capacity decay coefficient CDC and charge-discharge efficiency coefficient CDEC of the battery; The internal resistance coefficient IRC of the battery is calculated and obtained through the following formula: ； Wherein, R int,comp represents the internal resistance value after temperature compensation, R int represents the original internal resistance value, α represents the temperature coefficient, T b represents the battery temperature measured in real time, T nominal represents the standard operating temperature of the battery, β represents the charge and discharge rate coefficient, and Crate represents the charge and discharge rate; The capacity decay coefficient CDC of the battery is calculated and obtained through the following formula: ； Wherein, C remain represents the remaining capacity of the battery, C nominal represents the rated capacity of the battery, γ represents the capacity attenuation factor, N cycle represents the current charge-discharge cycle number, N max represents the maximum charge-discharge cycle number of the battery, δ represents the deep discharge attenuation factor, and DoD represents deep discharge; The charge-discharge efficiency coefficient CDEC of the battery is calculated and obtained through the following formula: ； Wherein, CDEC represents the battery charge-discharge efficiency coefficient, c harge represents the charging efficiency, d ischarge represents the discharging efficiency, E charge represents the electric energy input during the charging process, E discharge represents the electric energy output during the discharging process, S discharge represents the self-discharge rate, that is, the electric energy loss rate of the battery in the static state, E total represents the total electric energy of the battery; The battery health index BHI is calculated and obtained through the following formula: ； In the formula, respectively represent the weight coefficients, indicating the contribution ratio of each coefficient to the total index. IRC represents the internal resistance coefficient of the battery, CDC represents the capacity attenuation coefficient of the battery, and CDEC represents the charge-discharge efficiency coefficient of the battery.

5. The intelligent power management system for an AGV vehicle according to claim 1, wherein: The power management module includes a charge-discharge regulation unit, a battery state optimization unit and an intelligent scheduling unit; The charge-discharge regulation unit is used to adjust the charge or discharge mode according to the load evaluation result and the battery health index BHI by collecting the charging current, voltage and remaining capacity data of the battery in real time, automatically adjust the charging power and discharge power, and control the working mode of the battery including charging, discharging and standby modes. According to the health state of the battery and the load demand, by optimizing the charge and discharge rate, the battery life and the efficient operation of the system are guaranteed; The battery state optimization unit is used to evaluate the current state of the battery by analyzing real-time data, including battery internal resistance, temperature and charging rate, make predictive adjustments in combination with indicators such as battery capacity decay and charge-discharge efficiency, and dynamically adjust the working mode of the battery according to load changes, working environment and battery performance degradation, so as to extend the battery service life and reduce energy loss; The intelligent scheduling unit is used to feedback the load and battery health status in real time. Through an optimization algorithm, the intelligent scheduling unit can determine when the battery enters the charging, standby or discharging state, and at the same time dynamically adjust the switching frequency and transition time of each working mode. The scheduling result is updated and fed back to the battery management system BMS in real time.

6. The power intelligent management system of an AGV cart according to claim 1, wherein: The fault warning module includes a fault prediction unit, a grade evaluation unit and an alarm unit; The fault prediction unit is used to analyze the real-time monitoring data of the battery, including internal resistance, voltage, current and temperature, predict the fault risk of the battery by using an intelligent algorithm, and detect in real time the abnormal behaviors that will occur during the charge and discharge process of the battery, including overcharging, over-discharging and overheating, and give an early warning of the upcoming fault; The grade evaluation unit is used to obtain the battery health condition according to the operation data of the battery, including capacity decay, number of cycles and self-discharge rate, and obtain a grade evaluation scheme by comparing the battery health index BHI with the preset first qualified threshold M and second qualified threshold N; When BHI ≥ M, obtain the first evaluation level, and the battery status is rated as qualified. Within this range, the health condition, capacity, and charge and discharge efficiency of the battery are all within the normal range. The system continues to operate normally, maintains the battery's operating mode, and does not require special adjustment. Optimize the charging cycle according to the workload to avoid overcharging; When N ≤ BHI < M, obtain the second evaluation level, and the battery status is rated as unqualified. The performance of the battery deteriorates. According to the health status of the battery, reduce the charging current and discharge power to avoid overloading operation, reduce the increase in internal resistance and capacity attenuation, set the maximum charging power limit to avoid overcharging. In the case of high load, it is recommended to adopt a more stable discharge method, and it is recommended to conduct regular inspections on the battery to increase the maintenance frequency of the battery once a month; When BHI < N, obtain the third evaluation level, and the battery status is rated as the fault warning level, which causes problems such as the AGV vehicle stopping or its performance declining. Immediate intervention is required. The battery must immediately stop being used under high load or high-frequency charge and discharge conditions. Pause or reduce the operating frequency of the AGV vehicle to avoid further damage caused by overuse.

7. The intelligent power management system for an AGV vehicle according to claim 6, characterized in that: The alarm unit triggers the alarm mechanism of the system according to the fault prediction result and health assessment data, and notifies the maintenance personnel for timely handling. Generate a detailed fault report according to the fault type, and provide different levels of warnings according to the severity of the battery fault. Automatically execute part of the fault detection program according to the real-time monitored data to reduce human intervention.

8. The intelligent power management system for an AGV vehicle according to claim 1, characterized in that: The remote monitoring module includes a data visualization unit, a remote monitoring unit, and a remote control unit; The data visualization unit is used to display the key information of the battery's real-time status, charge and discharge data, temperature, capacity, and health index in the form of charts and dashboards, and provides a user interface to allow users to view historical data, prediction results, and system warnings according to their needs, helping users quickly master the battery health status; The remote monitoring unit is used to remotely monitor the battery system through the Internet, receive the battery status data in real time, and allow users to remotely monitor the charge and discharge process of the battery through an application or a web interface. Users can view the battery operating status at any time, adjust the battery working mode, or conduct fault troubleshooting; The remote control unit is used to remotely control the battery system, including functions such as adjusting the charge and discharge mode, setting the charging time window, and controlling the battery standby state. It allows users to remotely adjust the working state of the battery according to the system operating conditions and task requirements to optimize the operating efficiency and service life of the battery, and supports regular automatic update of system parameters.

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