Multifunctional navigation mark and energy online monitoring system thereof

Abstract

The present application belongs to the technical field of navigation mark energy monitoring, and specifically relates to a multifunctional navigation mark and an energy online monitoring system thereof, which comprises a data acquisition module, a transmission module, a data storage module, a calibration module, an analysis and comparison module, an evaluation module and a control module. By acquiring information such as single-body voltage, total current, cell pole temperature, internal resistance and SOC of the navigation mark energy and processing the information through the calibration module, the analysis and comparison module, the evaluation module and the control module, the energy state can be monitored in real time, an alarm signal can be generated in time, the monitored navigation marks can be classified and managed according to monitoring levels, the decay trend of the corresponding navigation mark energy can be predicted, and the remaining life of the navigation mark energy can be provided according to the prediction result, thereby providing an important basis for accurately and efficiently managing the navigation mark energy.

Description

Technical Field

[0001] This invention belongs to the field of navigation mark energy monitoring technology, specifically relating to a multifunctional navigation mark and its online energy monitoring system. Background Technology

[0002] Navigational aids are a type of marker used to indicate the direction, boundaries, and obstructions of a waterway. They include river crossing markers, bank markers, guide markers, transitional guide markers, bow and stern guide markers, flank markers, port and starboard navigation markers, position markers, flood markers, and bridge and culvert markers. They are man-made markers used to guide ships, determine their position, and indicate obstructions and warnings.

[0003] Currently, most navigation aids used in maritime areas are powered by batteries. Therefore, the stable and continuous power supply of batteries is indispensable for the normal operation of navigation aids. Generally, navigation aid stations activate emergency response mechanisms to repair malfunctioning navigation aids upon receiving an alarm indicating abnormal voltage. According to incomplete statistics, approximately 50% of the annual mileage mileage for navigation aid vessels and inspection vehicles is incurred during emergency response missions, and repairing navigation aid power system malfunctions is a highly representative aspect of these missions.

[0004] For the reasons mentioned above, the ability to monitor the status of navigational aid energy systems in real time, efficiently, and accurately, transforming reactive repairs into proactive maintenance, is a crucial aspect of improving emergency navigational aid support. Based on this, this invention proposes an online energy monitoring system and a multifunctional navigational aid utilizing this system. Summary of the Invention

[0005] The purpose of this invention is to provide a multifunctional online monitoring system for navigation aids and their energy. By collecting information such as individual cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC) of the navigation aid's energy, and processing this information through calibration, analysis and comparison, evaluation, and control modules, the system can not only monitor the energy status in real time and generate alarm signals promptly, but also classify and manage the monitored navigation aids according to their monitoring levels, predict the energy decay trend of the corresponding navigation aids, and provide the remaining lifespan of the navigation aid's energy based on the prediction results. This provides an important basis for the precise and efficient management of navigation aid energy.

[0006] The specific technical solution adopted by this invention is as follows:

[0007] An online energy monitoring system includes a data acquisition module, a transmission module, a data storage module, a calibration module, an analysis and comparison module, an evaluation module, and a control module.

[0008] The data acquisition module is used to collect energy parameter information, including individual cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC).

[0009] The transmission module is used to transmit the collected energy parameter information to the workstation monitoring system;

[0010] The data storage module is used to store relevant data information, including the collected energy parameter information;

[0011] The calibration module is used to calibrate the parameter information acquired by the data acquisition module and obtain calibration parameter information.

[0012] The analysis and comparison module is used to compare and analyze the calibration parameter information with the critical parameter threshold, and obtain the usage status based on the analysis results, wherein the usage status includes alarm status and continuous status.

[0013] The evaluation module is used to assess the changing trend of the energy system when the analysis and comparison module obtains the usage status as sustainable based on the analysis results, and to determine the preset time and monitoring level for the energy system to reach the critical parameter threshold based on the changing trend.

[0014] The control module is used to control the system flow, receive and process relevant data, and send relevant instructions.

[0015] In a preferred embodiment of the present invention, the analysis and comparison module compares and analyzes calibration parameter information with critical parameter thresholds, and obtains the usage status based on the analysis results as follows:

[0016] Compare the calibration parameter information with the critical parameter threshold;

[0017] If the calibration parameter information exceeds the critical parameter threshold, the control module will immediately output an alarm signal to generate an alarm status.

[0018] If the calibration parameter information does not exceed the critical parameter threshold, the control module outputs a sustainable state.

[0019] In a preferred embodiment of the present invention, the evaluation module is used to assess the changing trend of the energy system when the analysis and comparison module obtains that the usage status is sustainable based on the analysis results, and to determine the preset time and monitoring level for the energy system to reach the critical parameter threshold based on the changing trend.

[0020] The calibration parameter information is input into the evaluation module, and the trend change value of the calibration parameter information is obtained according to the trend evaluation function of the evaluation module.

[0021] If the trend change value of the calibration parameter information is greater than the standard trend change value, it indicates that the battery performance is deteriorating faster. The battery should be classified as a red monitoring level, and the preset time for the battery performance to reach the critical parameter threshold should be analyzed accordingly.

[0022] If the trend change value of the calibration parameter information is less than the standard trend change value, it indicates that the rate of battery performance degradation has slowed down. The battery should be included in the green monitoring level, and the preset time for the battery to reach the critical parameter threshold should be analyzed accordingly.

[0023] If the trend change value of the calibration parameter information is equal to the standard trend change value, it indicates that the rate of battery performance degradation is normal, and the battery should be classified as a yellow monitoring level and monitored according to the normal cycle of battery performance reaching the critical parameter threshold.

[0024] In a preferred embodiment of the present invention, the calibration module is used to calibrate the parameter information acquired by the data acquisition module. The steps for obtaining the calibration parameter information are as follows:

[0025] Obtain several battery test samples with the same quality conditions, acquire multiple monitoring parameter information values ​​and measured parameter information values ​​at the same time intervals, and summarize the monitoring parameter information values ​​and measured parameter information values ​​into the database;

[0026] A calibration function is obtained between the measured parameter information values ​​and the monitored parameter information values ​​based on the monitoring parameter information values ​​in the database.

[0027] The calibration parameter information value is obtained by inputting the monitoring parameter information value into the calibration function.

[0028] In the preferred embodiment of the present invention, the specific steps for inputting calibration parameter information into the evaluation module and obtaining the trend change value of the calibration parameter information based on the trend evaluation function of the evaluation module are as follows:

[0029] Several battery test samples of equal quality were obtained, a monitoring period was constructed, multiple monitoring time points with equal intervals were set within the monitoring period, and monitoring parameter information values ​​were obtained at each monitoring time point. All monitoring parameter information values ​​were corrected by a calibration function to obtain corrected parameter information values. All corrected parameter information values ​​and their corresponding monitoring time points were summarized into a database. The monitoring period covered the entire cycle of the battery from the optimal parameter value to the critical parameter threshold.

[0030] A trend assessment model is obtained based on several calibration parameter information values ​​in the database and the corresponding monitoring time points. A trend assessment function is obtained based on the assessment model, and the trend change value is obtained through the trend assessment function.

[0031] In a preferred embodiment of the present invention, the trend evaluation function is:

[0032] ,

[0033] Where Q represents the trend change value, f represents the compensation coefficient, i represents the information value number of a certain type of parameter, n represents the total number of monitoring times of a certain type of parameter, X represents the specific parameter information value, and t represents the interval between each monitoring.

[0034] In a preferred embodiment of the present invention, the step of analyzing the preset time for the battery performance to reach the critical parameter threshold is as follows:

[0035] Obtain several battery samples with the same quality conditions, and analyze the trend change value of each group of battery samples and the time when the battery samples reach the critical parameter threshold.

[0036] Several trend change values ​​and their corresponding times of reaching the critical parameter threshold are summarized, and correlation analysis is performed with standard trend change values ​​and their corresponding times of reaching the critical parameter threshold, and a correlation model is obtained accordingly.

[0037] The correlation function is obtained through the correlation model, and the preset time is obtained based on the correlation function.

[0038] In a preferred embodiment of the present invention, the correlation function is:

[0039] ,

[0040] Where S represents the preset time, M represents the standard trend change value, Q represents the trend change value, T represents the time required for the battery performance to degrade to the critical parameter threshold under the standard trend change value, K is the compensation coefficient, t represents the interval between each monitoring, and n represents the total number of monitoring times.

[0041] In the preferred embodiment of the present invention, the priority of the energy parameter information during comparison is as follows: SOC > cell voltage > internal resistance > cell electrode temperature > total current.

[0042] A multifunctional navigational aid, comprising a buoy, a top beacon, a light, an anchorage, an energy unit, and an online energy monitoring system as claimed in any one of claims 1-5.

[0043] The technical effects achieved by this invention are as follows:

[0044] This invention collects information such as individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC of navigation beacon energy, and processes this information through calibration, analysis and comparison, evaluation, and control modules. This not only enables real-time monitoring of energy status and timely generation of alarm signals, but also allows for the classification and management of monitored navigation beacons by monitoring level, prediction of the corresponding energy decay trend, and provision of the remaining lifespan of the navigation beacon energy based on the prediction results. This provides an important basis for the precise and efficient management of navigation beacon energy. Attached Figure Description

[0045] Figure 1This is a system flowchart of the present invention.

[0046] Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0047] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0048] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0050] Example 1

[0051] Please see Figure 1 and Figure 2 This invention provides an online energy monitoring system, including a data acquisition module, a transmission module, a data storage module, a calibration module, an analysis and comparison module, an evaluation module, and a control module;

[0052] The data acquisition module is used to collect energy parameter information, including individual cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC).

[0053] The transmission module is used to transmit the collected energy parameter information to the workstation monitoring system;

[0054] The data storage module is used to store relevant data information, including the collected energy parameter information;

[0055] The calibration module is used to calibrate the parameter information acquired by the data acquisition module and obtain calibration parameter information.

[0056] The analysis and comparison module is used to compare and analyze the calibration parameter information with the critical parameter threshold, and obtain the usage status based on the analysis results, wherein the usage status includes alarm status and continuous status.

[0057] The evaluation module is used to assess the changing trend of the energy system when the analysis and comparison module obtains the usage status as sustainable based on the analysis results, and to determine the preset time and monitoring level for the energy system to reach the critical parameter threshold based on the changing trend.

[0058] The control module is used to control the system flow, receive and process relevant data, and send relevant instructions.

[0059] The energy online monitoring system in this invention is mainly used for monitoring the energy system of navigation aids. Currently, navigation aids primarily use batteries, such as lithium iron phosphate batteries. These batteries experience a degradation cycle during use, which is the period from initial use until the battery becomes unusable. During this cycle, the battery's performance parameters change significantly. The most indicative performance parameters are cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC). Therefore, this invention includes a data acquisition module to effectively collect information on these parameters and transmit it to the monitoring system at the workstation. Transmission methods can include 4G, BeiDou, etc. The monitoring system then compares the collected information with critical parameter thresholds (the threshold values ​​for cell voltage, total current, cell terminal temperature, internal resistance, and SOC when the battery becomes unusable; these threshold values ​​are obtained through numerous experiments to achieve an average value). Simultaneously, the standard trend change value and its corresponding time from the initial use of the battery to reaching the critical parameter threshold can be obtained from relevant data and compared. During the comparison, the priority order is SOC, single cell voltage, internal resistance, cell terminal temperature, and total current. An alarm signal is generated as soon as any value exceeds the critical parameter threshold. It should be noted that the single cell voltage, total current, cell terminal temperature, internal resistance, and SOC change as follows during the entire decay cycle: single cell voltage gradually decreases; total current gradually decreases; cell terminal temperature gradually increases; internal resistance gradually increases; and SOC gradually decreases. Therefore, those skilled in the art should understand that exceeding the critical parameter threshold in this invention does not necessarily mean greater than the critical parameter threshold, but rather that the value exceeds the range of normal use. For example, for single cell voltage, total current, and SOC that show a decreasing trend, an alarm signal should be generated when the monitored value is less than or equal to the critical parameter threshold; for cell terminal temperature and internal resistance that gradually increase, an alarm signal should be generated when the monitored value is greater than or equal to the critical parameter threshold. Before comparing the monitored values ​​with the critical parameter thresholds, the collected parameter information needs to be calibrated through the calibration module to reduce the error of the collected data, so as to conduct more accurate comparison and analysis. The usage status is obtained based on the comparison and analysis results, which includes alarm status and sustainable status. When the analysis result is alarm status, the system immediately issues an alarm signal to prompt the staff to maintain the navigation beacon energy system. When the analysis result is sustainable status, the system further analyzes the attenuation trend of the energy system through the evaluation module to obtain the trend change value, and obtains the preset time based on the trend change value (the preset time here refers to the remaining time when the energy system can no longer be used normally). Through the above analysis, not only can the energy status be monitored in real time and effectively, but the attenuation of the normal energy system can also be evaluated and the preset time can be obtained, providing an effective basis for subsequent accurate monitoring.

[0060] It needs further explanation that the acquisition of individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC values ​​in the energy system uses conventional techniques. For example, individual cell voltage is sampled using a battery sampling chip (STM8S003F3P6); current is sampled using a magnetic balance current sensor sampling circuit; the DS18B20 temperature sensor with a wide temperature measurement range and high resolution is selected for temperature monitoring; internal resistance monitoring is achieved by generating a sinusoidal signal through an excitation signal circuit, which is connected to the battery through capacitor isolation. The voltage and current signals obtained through voltage and current acquisition are input to the FPGA through an AD sampling circuit. In the FPGA, the internal resistance value is calculated by filtering using the synchronous integration method and amplitude taking using the sampling integration method, and finally by Ohm's law. An ampere-hour integration method combined with the open-circuit voltage method is used for estimation to improve the accuracy of SOC estimation. The ampere-hour integration method updates the SOC value of the battery in real time during operation, while the open-circuit voltage method is used to calibrate the SOC during battery downtime or each time the battery system is started to eliminate charge accumulation errors and solve the initial SOC assessment problem of the ampere-hour integration method. The above examples of collecting data on individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC values ​​are merely illustrative and not intended to limit the collection method. Those skilled in the art should be aware that other collection methods exist.

[0061] In a preferred embodiment, the calibration module is used to calibrate the parameter information acquired by the data acquisition module. The steps for obtaining the calibration parameter information are as follows:

[0062] Obtain several battery test samples with the same quality conditions, acquire multiple monitoring parameter information values ​​and measured parameter information values ​​at the same time intervals, and summarize the monitoring parameter information values ​​and measured parameter information values ​​into the database;

[0063] Based on the monitoring parameter information values ​​and measured parameter information values ​​in the database, obtain the calibration function between the measured parameter information values ​​and the monitoring parameter information values;

[0064] The calibration parameter information value is obtained by inputting the monitoring parameter information value into the calibration function.

[0065] In this implementation, several battery test samples with identical quality conditions are selected, such as lithium iron phosphate batteries. The same time interval is chosen, such as 3 days (not specifically limited, can be randomly set as needed). The individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC value of the batteries are monitored and measured online in sequence, and the corresponding data are acquired. Monitoring stops when the battery degrades to the point of being unusable. The data for the entire cycle is summarized to provide data support for subsequent monitoring. Based on this, a mapping relationship between the measured data and the monitored data is obtained, thus deriving a calibration function. When subsequently monitoring the individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC values, the monitored parameter information values ​​are simply input into the calibration function to obtain calibrated parameter information values, correcting the monitored data and ensuring data accuracy. The calibration function is... , where Z is the calibrated parameter information value (measured value), j is the monitoring parameter information value, a is the first compensation coefficient, and b is the second compensation coefficient, where a and b are both constants.

[0066] In a preferred embodiment, the analysis and comparison module compares and analyzes the calibration parameter information with the critical parameter threshold, and obtains the usage status based on the analysis results as follows:

[0067] Compare the calibration parameter information with the critical parameter threshold;

[0068] If the calibration parameter information exceeds the critical parameter threshold, the control module will immediately output an alarm signal to generate an alarm status.

[0069] If the calibration parameter information does not exceed the critical parameter threshold, the control module outputs a sustainable state.

[0070] In this embodiment, by comparing the calibrated parameter information value with the critical parameter threshold, if the critical parameter threshold is exceeded, it means that the battery is in a state of being unusable. The system then outputs an alarm state and sends an alarm signal to notify the navigation beacon maintenance personnel to maintain the navigation beacon energy system, thus turning passive maintenance into active maintenance. When the calibrated parameter information value does not exceed the critical parameter threshold when compared with it, the system outputs a sustainable state, indicating that the navigation beacon energy system is in a stable state.

[0071] In a preferred embodiment, the evaluation module is used to assess the energy system's change trend when the analysis and comparison module determines the preset time and monitoring level for the energy system to reach the critical parameter threshold based on the change trend when the usage status is determined to be sustainable.

[0072] The calibration parameter information is input into the evaluation module, and the trend change value of the calibration parameter information is obtained according to the trend evaluation function of the evaluation module.

[0073] If the trend change value of the calibration parameter information is greater than the standard trend change value, it indicates that the battery performance is deteriorating faster. The battery should be classified as a red monitoring level, and the preset time for the battery performance to reach the critical parameter threshold should be analyzed accordingly.

[0074] If the trend change value of the calibration parameter information is less than the standard trend change value, it indicates that the rate of battery performance degradation has slowed down. The battery should be included in the green monitoring level, and the preset time for the battery to reach the critical parameter threshold should be analyzed accordingly.

[0075] If the trend change value of the calibration parameter information is equal to the standard trend change value, it indicates that the rate of battery performance degradation is normal, and the battery should be classified as a yellow monitoring level and monitored according to the normal cycle of battery performance reaching the critical parameter threshold.

[0076] In this embodiment, after we obtain the sustainable status of the energy system through monitoring and comparative analysis, in order to further accurately understand the status of the navigation beacon's energy, we can further evaluate the degradation trend of the navigation beacon's energy battery, obtain the trend change value of the energy system, and classify the energy system according to the analysis and comparison of the trend change value and the standard trend change value. This facilitates classified management by staff, highlights key points, optimizes management efficiency, and obtains the preset time for the battery to reach the critical parameter threshold based on the trend change value, providing a basis for accurately grasping the changes in battery status in the future.

[0077] It should be further explained that the specific steps for inputting the calibration parameter information into the evaluation module and obtaining the trend change value of the calibration parameter information based on the trend evaluation function of the evaluation module are as follows:

[0078] Several battery test samples of equal quality were obtained, a monitoring period was constructed, multiple monitoring time points with equal intervals were set within the monitoring period, and monitoring parameter information values ​​were obtained at each monitoring time point. All monitoring parameter information values ​​were corrected by a calibration function to obtain corrected parameter information values. All corrected parameter information values ​​and their corresponding monitoring time points were summarized into a database. The monitoring period covered the entire cycle of the battery from the optimal parameter value (the optimal parameter value is the parameter value when the battery is first used) to the critical parameter threshold.

[0079] A trend assessment model is obtained based on several calibration parameter values ​​and corresponding monitoring time points in the database. A trend assessment function is then derived from the model, and the trend change value is obtained through this function. The trend assessment function is as follows:

[0080] ,

[0081] Where Q represents the trend change value, f represents the compensation coefficient, i represents the information value number of a certain type of parameter, n represents the total number of monitoring times of a certain type of parameter, X represents the specific parameter information value, and t represents the interval between each monitoring.

[0082] It should be noted that, since this invention determines battery status by monitoring five parameters: single-cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC), all statements regarding data collection or monitoring / measuring of relevant parameters refer to the simultaneous acquisition of these five parameters. Furthermore, the trend changes of the aforementioned parameters are calculated separately for each of the five parameters, and a comprehensive evaluation is performed based on these trend changes.

[0083] In a preferred embodiment, the step of analyzing the preset time for the battery performance to reach the critical parameter threshold is as follows:

[0084] Obtain several battery samples with the same quality conditions, and analyze the trend change value of each group of battery samples and the time when the battery samples reach the critical parameter threshold.

[0085] Several trend change values ​​and their corresponding times to reach the critical parameter threshold are summarized, and correlation analysis is performed with the standard trend change values ​​and their corresponding times to reach the critical parameter threshold. Based on this, a correlation model is obtained, a correlation function is obtained through the correlation model, and a preset time is obtained based on the correlation function.

[0086] In this embodiment, multiple battery samples of equal quality are obtained, and the trend change value and the time when the battery reaches the critical parameter threshold are acquired for each group of battery samples. This data is then summarized and correlated with the standard trend change value and the time when the battery reaches the critical parameter threshold to obtain a correlation function. In subsequent energy system monitoring, energy system parameter information, such as data from the past six months, is monitored, and the trend change value of the energy system parameter information is obtained. The degradation rate of the energy system is determined based on the trend change value, and then a preset time is obtained according to the correlation function, where the correlation function is... Where S represents the preset time, M represents the standard trend change value, Q represents the trend change value, T represents the time required for battery performance to degrade to the critical parameter threshold under the standard trend change value, K is the compensation coefficient, t represents the interval between each monitoring, and n represents the total number of monitoring times. By obtaining the preset time, staff can be reminded of the remaining battery life, providing data support for precise battery management.

[0087] Example 2

[0088] The present invention also provides a multifunctional navigation mark, which includes a buoy, a top beacon, a light, an anchor, an energy unit, and the above-described online monitoring system for monitoring the energy unit.

[0089] This invention collects information such as individual cell voltage, total current, cell terminal temperature, internal resistance, and SOC of navigation beacon energy, and processes this information through calibration, analysis and comparison, evaluation, and control modules. This not only enables real-time monitoring of energy status and timely generation of alarm signals, but also allows for the classification and management of monitored navigation beacons by monitoring level, prediction of the corresponding energy decay trend, and provision of the remaining lifespan of the navigation beacon energy based on the prediction results. This provides an important basis for the precise and efficient management of navigation beacon energy.

[0090] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. An online energy monitoring system, characterized in that: include The data acquisition module is used to collect energy parameter information, including cell voltage, total current, cell terminal temperature, internal resistance, and state of charge (SOC). The transmission module transmits the collected energy parameter information to the workstation monitoring system; The data storage module is used to store data information, including the collected energy parameter information; The calibration module is used to calibrate the collected parameter information and obtain calibration parameter information. The analysis and comparison module is used to compare and analyze the calibration parameter information with the critical parameter threshold, and obtain the usage status based on the analysis results, which includes alarm status and continuous status. The assessment module is used to assess the changing trend of the energy system when the analysis and comparison module obtains the usage status as sustainable based on the analysis results, and to determine the preset time and monitoring level for the energy system to reach the critical parameter threshold based on the changing trend. The control module is used to control system flow and to receive and send relevant instructions; The steps for inputting calibration parameter information into the evaluation module and obtaining the trend change value of the calibration parameter information based on the trend evaluation function of the evaluation module are as follows: Several battery samples of equal mass were obtained, a monitoring period was constructed, multiple monitoring time points with equal intervals were set within the monitoring period, and monitoring parameter information values ​​were obtained at each monitoring time point. The monitoring parameter information values ​​were then corrected by a calibration function to obtain corrected parameter information values. The corrected parameter information values ​​and the corresponding monitoring time points were summarized into the database. The monitoring period is the entire cycle of the battery from the optimal parameter value to the critical parameter threshold. A trend assessment model is obtained based on several calibration parameter information values ​​in the database and the corresponding monitoring time points. A trend assessment function is obtained based on the assessment model. The trend change value is obtained through the trend assessment function. The trend evaluation function is: ， Where Q represents the trend change value, f represents the compensation coefficient, i represents the value number of a certain type of parameter, n represents the total number of monitoring times for a certain type of parameter, and X represents the value of X. i This represents the specific parameter information value, and t represents the interval between each monitoring session; The steps for analyzing the preset time when the battery performance reaches the critical parameter threshold are as follows: Obtain several battery samples with the same quality conditions, and analyze the trend change value of each group of battery samples and the time when the battery samples reach the critical parameter threshold. Several trend change values ​​and their corresponding times of reaching the critical parameter threshold are summarized, and correlation analysis is performed with standard trend change values ​​and their corresponding times of reaching the critical parameter threshold, and a correlation model is obtained accordingly. The correlation function is obtained through the correlation model, and the preset time is obtained based on the correlation function. The correlation function is: ， Where S represents the preset time, M represents the standard trend change value, Q represents the trend change value, T represents the time required for the battery performance to degrade to the critical parameter threshold under the standard trend change value, K is the compensation coefficient, t represents the interval between each monitoring, and n represents the total number of monitoring times.

2. The energy online monitoring system according to claim 1, characterized in that: The analysis and comparison module is used to compare and analyze calibration parameter information with critical parameter thresholds, and to obtain the usage status based on the analysis results. The steps are as follows: Compare the calibration parameter information with the critical parameter threshold; If the calibration parameter information exceeds the critical parameter threshold, the control module will immediately output an alarm signal to generate an alarm status. If the calibration parameter information does not exceed the critical parameter threshold, the control module outputs a sustainable state.

3. The energy online monitoring system according to claim 1, characterized in that: The evaluation module is used to assess the energy system's change trend when the analysis and comparison module determines the usage status as sustainable based on the analysis results. The steps for determining the preset time and monitoring level for the energy system to reach the critical parameter threshold are as follows: If the trend change value of the calibration parameter information is greater than the standard trend change value, it indicates that the battery performance is degrading faster. The battery should be classified as a red monitoring level, and the preset time for the battery performance to reach the critical parameter threshold should be analyzed accordingly. If the trend change value of the calibration parameter information is less than the standard trend change value, it indicates that the rate of battery performance degradation has slowed down. The battery should be included in the green monitoring level, and the preset time for the battery to reach the critical parameter threshold should be analyzed accordingly. If the trend change value of the calibration parameter information is equal to the standard trend change value, it indicates that the rate of battery performance degradation is normal. The battery should be classified as yellow monitoring level and monitored according to the normal cycle when the battery performance reaches the critical parameter threshold.

4. The energy online monitoring system according to claim 1, characterized in that: The calibration module is used to calibrate the parameter information acquired by the data acquisition module. The steps to obtain the calibration parameter information are as follows: Obtain several battery test samples with the same quality conditions, acquire multiple monitoring parameter information values ​​and measured parameter information values ​​at the same time intervals, and summarize the monitoring parameter information values ​​and measured parameter information values ​​into the database; Based on the monitoring parameter information values ​​and measured parameter information values ​​in the database, obtain the calibration function between the measured parameter information values ​​and the monitoring parameter information values; The calibration parameter information value is obtained by inputting the monitoring parameter information value into the calibration function.

5. The energy online monitoring system according to claim 1, characterized in that: The priority of the energy parameter information during comparison is as follows: SOC > cell voltage > internal resistance > cell terminal temperature > total current.

6. A multifunctional navigational aid, characterized in that: It includes a buoy, a top beacon, a light fixture, an anchorage, an energy unit, and an online energy monitoring system according to any one of claims 1-5.

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