A real-time online monitoring method for power supply of highway electromechanical equipment

Abstract

The application relates to the technical field of electric digital data processing, in particular to a real-time online monitoring method for a power supply for highway electromechanical equipment, which comprises the following steps: collecting and storing multi-dimensional data during operation of a backup power supply system, and pre-processing the multi-dimensional data; obtaining a health index of a battery pack at different target time points; obtaining a battery charging demand degree at different target time points; determining a historical reference time point of the target time point; obtaining a generator power rising speed; based on the generator power rising speed, the generator power is lifted to a target power; according to a change trend of a generator current with time, a generator stable operation evaluation value is obtained; according to a change trend of the battery charging demand degree with time, an unstable growth index is obtained; based on the generator stable operation evaluation value and the unstable growth index, a backup power supply early warning index is obtained. The application can improve the accuracy of real-time online monitoring of the power supply for the highway electromechanical equipment.

Description

Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, specifically to a method for real-time online monitoring of power supplies for highway electromechanical equipment. Background Technology

[0002] The electromechanical equipment in highway tunnels, including lighting, ventilation, monitoring, and toll collection systems, is a critical infrastructure for ensuring road safety and smooth operation. Its normal operation heavily relies on a continuous and stable power supply. Normally, this equipment is directly powered by the municipal power grid. When the municipal power supply is interrupted or malfunctions, a backup power system must immediately take over the power supply to ensure uninterrupted operation of the equipment. Therefore, the reliability of the backup power system (typically including diesel generator sets and uninterruptible power supplies, UPS) is directly related to the operational safety of the highway, making effective and accurate real-time online monitoring crucial.

[0003] Currently, the monitoring methods for backup power systems typically involve testing the generator and UPS separately: remotely controlling the generator to start and stop, running the generator under no-load conditions to test whether the generator can operate normally; and relying on maintenance personnel to perform deep discharge tests on the UPS regularly.

[0004] However, during actual testing, backup power systems may experience anomalies such as bus aging and failure. These anomalies will cause changes in load characteristics when mains power is actually interrupted, resulting in dynamic fluctuations in the actual charging demand of the battery pack. Existing testing methods are conducted under simplified conditions that deviate from actual operating conditions. Therefore, existing testing methods cannot simulate the dynamic and step loads faced by the backup power supply when it actually takes over, leading to discrepancies between online monitoring results and actual load capacity, and insufficient monitoring accuracy. Summary of the Invention

[0005] This invention provides a method for real-time online monitoring of power supplies for highway electromechanical equipment to solve existing problems.

[0006] The present invention provides a method for real-time online monitoring of power supplies for highway electromechanical equipment, which adopts the following technical solution:

[0007] One embodiment of the present invention provides a method for real-time online monitoring of power supplies for electromechanical equipment on highways, the method comprising the following steps:

[0008] Collect and store multidimensional data of the backup power system during operation, and preprocess the multidimensional data; wherein, the multidimensional data includes at least generator-side data and BMS-side data; generator-side data includes at least generator output current and power; BMS-side data includes at least battery pack remaining capacity, DC side charging current and battery pack temperature;

[0009] The health index of the battery pack at different target times is obtained based on the preprocessed BMS side data; where the target time is the time after completing at least one charging process.

[0010] By utilizing the battery pack's health index at different target times, the battery charging demand at those target times can be obtained.

[0011] Based on the battery pack's health index at different target times, the battery charging demand at different target times, and the pre-processed BMS-side data, the historical reference time for the target time is determined.

[0012] By using the preprocessed generator-side data, the battery charging demand at the target time and its historical reference time, the rate of increase of the generator output power at the target time is obtained;

[0013] Based on the rate of increase of generator output power at the target time, the generator output power is increased to the target power at the target time.

[0014] Based on the trend of generator output current change over time after the generator output power is increased to the target power at the target time, the stable operation evaluation value of the generator during this charging is obtained.

[0015] Based on the changing trend of battery charging demand over time after the generator output power is increased to the target power at the target time, the unstable growth index of this charging is obtained.

[0016] Based on the generator's stable operation assessment value during this charging period and the instability growth index during this charging period, an early warning index for the backup power supply is obtained.

[0017] Furthermore, the specific steps for obtaining the battery pack's health index at different target times based on preprocessed BMS-side data are as follows:

[0018] The time interval between the two nearest adjacent charges to the target time is obtained based on the charging current on the DC side, and the maximum time interval between all two adjacent charges before the target time is reached.

[0019] The charging speed of the most recent charge before the target time is obtained based on the remaining battery power.

[0020] Based on the DC-side charging current, the mean variance of the DC-side charging current during all charging processes before the target cutoff time is obtained, as well as the variance of the DC-side charging current during the most recent charging process before the target time.

[0021] Multiply the time interval by the charging speed, then divide by the maximum time interval to get the ratio. Multiply the ratio by the mean variance and then divide by the variance to get the health index of the battery pack at the target time.

[0022] Obtain the health index of the battery pack at different target times.

[0023] Furthermore, the specific steps for obtaining the charging speed of the most recent charge based on the remaining battery power of the battery pack are as follows:

[0024] First, calculate the difference between the remaining power at the end of the most recent charge and the remaining power at the beginning of the current charge. Then, divide the difference by the duration of the current charge to obtain the charging speed of the most recent charge from the target time.

[0025] Furthermore, the specific steps for obtaining the battery charging demand at different target times by utilizing the battery pack's health index include the following:

[0026] Obtain the battery pack's health index at the first moment; where the first moment is the moment when the first charge ends.

[0027] Subtract the remaining battery charge at the target time from 1 to get the difference. Then multiply the battery health index at the first time by the difference to get the product. Finally, divide the product by the battery health index at the target time to get the battery charging demand at the target time.

[0028] Obtain the battery charging demand at different target times.

[0029] Furthermore, the specific steps for determining the historical reference time for the target time based on the battery pack's health index at different target times, the battery charging demand at different target times, and the preprocessed BMS-side data are as follows:

[0030] Obtain the battery charging demand level at historical time points, and determine the absolute value of the difference between the normalized value of the battery charging demand level at the target time and the normalized value of the battery charging demand level at historical time points as the battery charging demand difference between the target time and historical time points; where historical time points are any target time points before the target time point.

[0031] Obtain the battery pack temperature at the historical time and the target time, and determine the absolute value of the difference between the battery pack temperature at the target time and the battery pack temperature at the historical time as the temperature difference between the target time and the historical time.

[0032] Obtain the health index of the battery pack at historical time points, and determine the absolute value of the difference between the normalized value of the health index of the battery pack at the target time point and the normalized value of the health index of the battery pack at historical time points as the health index difference between the target time point and the historical time point.

[0033] The first product is obtained by multiplying the differences in battery charging demand, temperature, and health index between the target time and historical time.

[0034] The function value with the natural constant e as the base and the negative first product as the exponent is determined as the similarity between the control requirements at the target time and the historical time.

[0035] If the similarity of the regulation demand is greater than the preset similarity threshold, then the historical moment will be determined as the historical reference moment of the target moment.

[0036] Furthermore, the specific steps for obtaining the generator output power increase rate at the target time using preprocessed generator-side data, the battery charging demand at the target time and its historical reference times are as follows:

[0037] The rate of increase of generator output power at each historical reference time at the target time is obtained based on the generator output power.

[0038] Using the similarity between the control demand at the target time and each historical reference time as the weight, the rate of increase of the generator output power at each historical reference time is calculated by weighted average to obtain the first velocity;

[0039] Calculate the mean of the normalized values ​​of battery charging demand at all historical reference times, and determine the mean as the first mean;

[0040] If the normalized value of the battery charging demand at the target time is greater than or equal to the first mean, then add 1 to the normalized value of the battery charging demand at the target time to get the sum, and then multiply the sum by the first speed to get the generator output power increase rate at the target time.

[0041] If the normalized value of the battery charging demand at the target time is less than the first mean, then subtract the normalized value of the battery charging demand at the target time from 1 to obtain the difference, and then multiply the difference by the first speed to obtain the rate of increase of the generator output power at the target time.

[0042] Furthermore, the target power at the target time is the product of the generator's rated output power and the normalized value of the battery charging demand at the target time.

[0043] Furthermore, the specific steps for obtaining the generator stable operation evaluation value during this charging period based on the change trend of the generator output current over time after the generator output power is increased to the target power at the target time include the following:

[0044] Arrange the generator currents after the second time step according to the time sequence to obtain the current time sequence; where the second time step is the time when the generator power is increased to the target power at the target time step.

[0045] The first difference sequence is obtained by performing a first-order difference calculation on the current time series;

[0046] Calculate the mean of all differences in the first difference sequence, and calculate the absolute value of the ratio of each difference to the mean;

[0047] The first moment corresponding to the difference segment where the absolute value of the ratio is continuously less than the preset ratio threshold is determined as the stable moment of this charging.

[0048] The start time of this charging is obtained based on the generator output power, and the duration from the start time to the stable time is determined as the stable duration.

[0049] The charging process corresponding to each historical reference time of the target time is defined as the historical reference process;

[0050] Obtain the stationary duration of each historical reference process and calculate the average stationary duration of all historical reference processes;

[0051] The absolute value of the mean of all difference values ​​in the first difference sequence is determined as the first absolute value;

[0052] Calculate the mean of all differences in each historical reference process, then calculate the mean of the mean of differences in all historical reference processes, and determine the absolute value of the mean of the difference as the second absolute value;

[0053] Calculate the ratio of the average stable duration to the total stable duration, then multiply the ratio by the second absolute value to obtain the product, and finally divide the product by the first absolute value to obtain the generator stable operation evaluation value during this charging.

[0054] Furthermore, the specific steps for obtaining the unstable growth index of this charging based on the changing trend of battery charging demand over time after the generator output power is increased to the target power at the target time include the following:

[0055] Arrange the normalized values ​​of battery charging demand after the second time step according to the time sequence to obtain the time sequence of battery charging demand.

[0056] The first-order difference calculation is performed on the time series of battery charging demand to obtain the second difference series;

[0057] The difference values ​​greater than 0 in the second difference sequence are marked as abnormal growth values, and the continuous abnormal growth value segments are identified as abnormal growth intervals;

[0058] Calculate the length of each abnormal growth interval and the average length of all abnormal growth intervals;

[0059] Calculate the length of the second difference sequence and the number of abnormal growth intervals;

[0060] Calculate the average of all abnormal growth values ​​within each abnormal growth interval, and determine the average of the average of the abnormal growth values ​​across all abnormal growth intervals as the second average.

[0061] The ratio is obtained by dividing the length mean by the length of the second difference sequence. Then, the ratio is multiplied by the number of abnormal growth intervals to obtain the product. Finally, the product is multiplied by the second mean to obtain the unstable growth index of this charge.

[0062] Furthermore, the specific steps for obtaining the early warning index of the backup power supply based on the generator's stable operation assessment value during this charging and the instability growth index during this charging are as follows:

[0063] Obtain the generator stability operation assessment value for each historical reference process, and calculate the average generator stability operation assessment value for all historical reference processes;

[0064] The average generator stable operation assessment value is divided by the generator stable operation assessment value during this charging to obtain the ratio. Then, the ratio is multiplied by the instability growth index of this charging to obtain the early warning index of the backup power supply.

[0065] The beneficial effects of the technical solution of the present invention are as follows: The embodiments of the present invention propose a real-time online monitoring method for power supply of highway electromechanical equipment. It obtains the charging demand of the battery based on real-time monitoring and analysis, and charges the battery by testing the generator to meet the needs of testing and power replenishment. Then, it analyzes the operating stability of the generator based on the conversion degree of different loads of the generator in the battery pack, and further evaluates the effective health of the bus capacitor of the backup power supply based on the abnormal output fluctuation of the generator, thereby improving the accuracy of real-time online monitoring of power supply of highway electromechanical equipment. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 This is a flowchart illustrating the steps of a real-time online monitoring method for power supplies used in highway electromechanical equipment according to the present invention.

[0068] Figure 2 This is a schematic diagram of the power supply system for highway electromechanical equipment according to the present invention. Detailed Implementation

[0069] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a real-time online monitoring method for power supply of highway electromechanical equipment proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0071] The following description, in conjunction with the accompanying drawings, details the specific scheme of a real-time online monitoring method for power supply of electromechanical equipment on highways provided by the present invention.

[0072] It should be noted that the main purpose of this invention is to adjust the output power of the generator based on the actual charging needs of the backup power system, thereby charging the battery pack, and to evaluate the health index of the bus capacitor based on the stability of the generator output power during the charging process, so as to provide timely early warning of abnormal conditions of the current backup power and improve the accuracy of online monitoring of power supply for highway electromechanical equipment.

[0073] This invention proposes a real-time online monitoring method for the power supply of electromechanical equipment on highways. The method monitors the backup power system, obtains the dynamic charging demand of the battery pack based on the monitoring data, and adjusts the output power of the generator based on the charging demand to match the actual charging demand of the battery pack. The method also obtains the early warning index of the current backup power system based on the abnormal fluctuations during the matching process, thereby providing timely early warning of abnormal states of the backup power system.

[0074] Please see Figure 1 The diagram illustrates a flowchart of a real-time online monitoring method for power supply of electromechanical equipment on highways, according to an embodiment of the present invention. The method includes the following steps:

[0075] Step S001: Collect and store multidimensional data of the backup power system during operation, and preprocess the multidimensional data; wherein, the multidimensional data includes at least generator-side data and BMS-side data; the generator-side data includes at least generator output current and power; the BMS-side data includes at least the remaining battery capacity, DC charging current and battery temperature.

[0076] It should be noted that: Figure 2This is a schematic diagram of the power supply system for highway electromechanical equipment according to the present invention. The power supply structure for highway electromechanical equipment typically includes a main power module (responsible for daily power supply), a generator unit (responsible for outputting AC power when the mains power is interrupted), and an energy storage and conversion unit (responsible for converting the AC power output from the generator into DC power and switching the main power supply and backup power supply), etc. The specific structure is as follows: Figure 2 As shown.

[0077] Real-time monitoring of the power supply system of electromechanical equipment on a highway was conducted to acquire multi-dimensional data. This multi-dimensional data included generator-side data, BMS-side data, and bus-side data.

[0078] Generator-side data: Monitors the operating status of the generator body, collected through the generator controller, including electrical parameters such as output voltage, current, frequency, and real-time power, as well as the generator start-up and shutdown status.

[0079] BMS (Battery Management System) side data: reflects the battery pack's own status, including the remaining battery charge, DC charging current, and battery temperature obtained by the temperature sensor.

[0080] Bus-side data: The energy conversion center of the monitoring power supply system, obtained by the UPS (Uninterruptible Power Supply) rectifier module, including DC bus voltage, input AC power and output DC power.

[0081] The acquired data is transmitted to the data processing unit (including processor, memory, etc.) via wireless communication technology. Nearly a week's worth of data is cached, and the rest is transmitted to the cloud platform for storage. The collected data is then preprocessed (including timestamp alignment, Gaussian denoising, etc.).

[0082] Step S002: Obtain the health index of the battery pack at different target times based on the preprocessed BMS side data; wherein, the target time is the time after completing at least one charging process.

[0083] It should be noted that existing methods only perform static testing on the generator and battery pack in the backup power system, and cannot perform dynamic testing on different loads. Therefore, the output power and power boosting speed of the generator are determined based on the actual dynamic charging needs of the battery pack. That is, the stability of the backup power system is evaluated by actively charging and discharging the battery pack and dynamically detecting the charging and discharging process, thereby providing early warning and improving the accuracy of online monitoring.

[0084] Because the backup power supply requires the engine to meet the dynamic charging needs of the battery pack during actual operation, and the battery pack may deteriorate due to long-term use (such as periodic charging and discharging), resulting in increased internal resistance of individual cells, which leads to decreased charging efficiency. For example, the current stability during charging is poor, the charging speed is reduced, and the charging frequency is increased, which changes the battery's demand on the generator output. Therefore, the actual charging needs of the battery pack are analyzed in combination with the battery health status and remaining power.

[0085] Taking the monitoring data obtained at a certain target time (e.g., target time t) as an example, analyze the health index of the battery pack at that time: Read the historical charging data of the battery pack (using the monitoring data obtained in the past year as historical data, which can be adjusted according to the actual backup power supply replenishment cycle, including at least 3 complete replenishment cycles). If, up to the target time t, the charging frequency of the battery pack has increased (i.e., the time interval between two adjacent charging is shortened) and its charging speed has decreased significantly, and the current is becoming increasingly difficult to maintain a stable state during the charging process, then the current health index of the battery pack is low.

[0086] Step S002 further includes steps S0021-S0025:

[0087] Step S0021: Based on the charging current on the DC side, obtain the time interval between the two nearest adjacent charges to the target time, and the maximum value of the time interval between all two adjacent charges before the target time.

[0088] It should be noted that: based on continuously monitored and recorded battery DC-side charging current timing data, by detecting the complete process of the charging current significantly rising from the standby level, maintaining a high value, and then falling back to the standby level, all historical charging events and their start and end timestamps are identified. Based on this, the most recent completed charging event before the target time is located, and its previous adjacent charging event is traced back. The time difference between the start (or end) times of the two events is calculated, thus obtaining the required charging time interval. Furthermore, the maximum time interval between all two adjacent charging events before the target time can be obtained.

[0089] The interval between the most recent charge and the previous charge from the target time t is the time interval between the two most recent adjacent charges from the target time. It is the maximum time interval between two consecutive charging in the historical data, that is, the maximum time interval between all two consecutive charging before the target time.

[0090] Step S0022: Obtain the charging speed of the most recent charge before the target time based on the remaining battery power.

[0091] Specifically, this involves: first calculating the difference between the remaining charge at the end of the most recent charge and the remaining charge at the beginning of the current charge; then dividing the difference by the duration of the current charge to obtain the charging speed of the most recent charge from the target time.

[0092] It should be noted that the formula for calculating the charging speed of the most recent charge before the target time is as follows:

[0093] ;

[0094] in, Let k be the charging speed of the most recent charge (the kth charge) before the target time t. The remaining battery power at the end of the k-th charge. The remaining battery power at the start of the k-th charge. The time taken for the kth charge.

[0095] Step S0023: Based on the DC side charging current, obtain the mean variance of the DC side charging current during all charging processes before the target cutoff time, and the variance of the DC side charging current during the most recent charging process before the target time.

[0096] It should be noted that: based on historical time-series data of DC-side charging current, by identifying the complete waveform of the charging current continuously rising from the standby value to a stable high value and finally falling back, all charging events occurring before the target cutoff time are determined. For each charging event, the charging current sequence during its duration is extracted, and the variance of each sequence is calculated. The arithmetic mean of the variances of all charging events is then calculated to obtain the historical charging current variance mean. Simultaneously, the charging event closest in time to the target time is selected from these charging events, and the variance of the charging current sequence during that charging process is calculated separately; this is the current variance of the most recent charging event.

[0097] It is the variance of the charging current on the battery pack during the most recent charging process from the target time t, that is, the variance of the DC charging current during the most recent charging process (the kth charging process) from the target time t. This represents the mean variance of the charging current on the battery pack side during each historical charging process, specifically the mean variance of the DC charging current during all charging processes up to the target time t.

[0098] Step S0024: Multiply the time interval by the charging speed, then divide by the maximum time interval to obtain the ratio. Multiply the ratio by the mean variance and then divide by the variance to obtain the health index of the battery pack at the target time.

[0099] It should be noted that the formula for calculating the battery pack's health index at the target time is as follows:

[0100] ;

[0101] in, This represents the health index of the battery pack at the target time t. The larger the value, the greater the increase in the current charging frequency; The larger the size, the less stable the charging.

[0102] Based on the Min-Max (Min-Max Normalization) method Normalize to (0, 1), and denote the normalization result as .

[0103] Step S0025: Obtain the health index of the battery pack at different target times.

[0104] Step S003: Utilize the battery pack's health index at different target times to obtain the battery charging demand at those different target times.

[0105] Step S003 further includes steps S0031-S0033:

[0106] Step S0031: Obtain the health index of the battery pack at the first moment; where the first moment is the end of the first charge.

[0107] It should be noted that when the target time coincides with the end of the first charge, the calculated health index is the health index of the battery pack at the first moment. This refers to the health index of the battery pack at the end of the first charge in historical data, i.e., the health index of the battery pack at the first moment.

[0108] Step S0032: Subtract the remaining battery charge at the target time from 1 to get the difference. Then multiply the battery health index at the first time by the difference to get the product. Finally, divide the product by the battery health index at the target time to get the battery charging demand at the target time.

[0109] It should be noted that the lower the current battery health assessment, the greater the impact on its charging efficiency. Furthermore, the smaller the remaining capacity of the battery pack, the higher the current battery charging demand. The formula for calculating the battery charging demand at the target time is as follows:

[0110] ;

[0111] in, The battery charging demand at the target time t. The remaining charge of the battery pack at the target time t. The larger the value, the faster the current battery health deteriorates.

[0112] Based on Min-Max Normalize to (0, 1), and denote the normalization result as .

[0113] Step S0033: Obtain the battery charging demand at different target times.

[0114] Step S004: Determine the historical reference time for the target time based on the battery pack's health index at different target times, the battery charging demand at different target times, and the preprocessed BMS-side data.

[0115] It should be noted that, as the above analysis shows, after the mains power fails, the battery pack in the backup power system quickly takes over the power supply to the highway electromechanical equipment. However, the generator needs to adjust its output power to the corresponding range and stabilize its output according to the current power supply demand of the battery pack before the rectifier module converts its output AC power into DC power to charge the battery pack.

[0116] Normally, after the generator's output power is increased, it can quickly return to a stable state. When its stability is poor, the output AC power recovers to a stable state more slowly and the fluctuation amplitude is larger. Therefore, the output power is adjusted according to the battery charging demand at different times, and the generator's stability is analyzed based on the fluctuation of the generator's output current after adjustment.

[0117] The generator output power should be adjusted according to the actual power supply demand of the battery. That is, the greater the battery charging demand at a certain target time (e.g., target time t), the greater the corresponding generator output power should be.

[0118] The above analysis shows that, to ensure the stable operation of the backup power system, the generator's output power needs to be gradually increased. Therefore, the current power adjustment speed needs to be determined based on the adjustment speed under similar historical conditions. If the target time t is similar to a certain historical time (if it is time t...), then... When the charging needs of the generators are similar (i.e., the required load increase of the generators is similar), the battery temperatures are similar (the internal resistance states are similar), and the battery health levels are similar, then the regulation requirements of the generator output power at the target time t are similar to those at that historical time.

[0119] Step S004 further includes steps S0041-S0046:

[0120] Step S0041: Obtain the battery charging demand level at historical time points, and determine the absolute value of the difference between the normalized value of the battery charging demand level at the target time point and the normalized value of the battery charging demand level at historical time points as the battery charging demand difference between the target time point and the historical time point; wherein, the historical time point is any target time point before the target time point.

[0121] It should be noted that for the target moment in the current analysis, any previous target moment is considered a historical moment. Normalized value of battery charging demand at target time t With historical moments Normalized value of battery charging demand The absolute value of the difference between the target time t and the historical time t, i.e. Differences in battery charging requirements.

[0122] Step S0042: Obtain the battery pack temperature at the historical time and the target time, and determine the absolute value of the difference between the battery pack temperature at the target time and the battery pack temperature at the historical time as the temperature difference between the target time and the historical time.

[0123] It should be noted that: Let the target time t and the historical time be... Temperature differences.

[0124] Step S0043: Obtain the health index of the battery pack at historical time points, and determine the absolute value of the difference between the normalized value of the health index of the battery pack at the target time point and the normalized value of the health index of the battery pack at historical time points as the health index difference between the target time point and the historical time point.

[0125] It should be noted that: The normalized value of the health index of the battery pack at the target time t. With the battery pack at a historic moment Normalized values ​​of the health index The absolute value of the difference between the target time t and the historical time t, i.e. Differences in health indices.

[0126] Step S0044: Multiply the differences in battery charging demand, temperature, and health index between the target time and historical time to obtain the first product.

[0127] It should be noted that: It is denoted as the first product.

[0128] Step S0045: The function value with the natural constant e as the base and the negative first product as the exponent is determined as the similarity of the control demand between the target time and the historical time.

[0129] It should be noted that the formula for calculating the similarity between the control requirements at the target time and historical times is as follows:

[0130] ;

[0131] in, Let the target time t and the historical time be... The similarity of regulatory needs.

[0132] Step S0046: If the similarity of the control demand is greater than the preset similarity threshold, then the historical time is determined as the historical reference time of the target time.

[0133] It should be noted that the preset similarity threshold is set according to the specific situation, and 0.5 is preferred here.

[0134] Will Time values ​​greater than 0.5 are marked as historical reference times for the target time t.

[0135] Step S005: Using the preprocessed generator-side data, the battery charging demand at the target time and its historical reference time, obtain the generator output power increase rate at the target time.

[0136] Step S005 further includes steps S0051-S0055:

[0137] Step S0051: Obtain the rate of increase of generator output power at each historical reference time at the target time based on the generator output power.

[0138] It should be noted that: based on the generator output power time-series curve stored in the historical monitoring data, for each historical reference moment, the complete charging process to which it belongs is first located; in this process, the starting moment when the generator output power begins to rise significantly from the no-load or low-load state, and the moment when the power first reaches the target power of this charge are accurately identified; the time difference between these two moments is calculated as the rise time, and the difference between the target power and the starting power is divided by this time to obtain the generator output power rise rate corresponding to the historical reference moment.

[0139] Step S0052: Using the similarity between the control demand at the target time and each historical reference time as the weight, calculate the weighted average of the generator output power increase rate at each historical reference time to obtain the first speed.

[0140] It should be noted that a weighted average is obtained by multiplying the rate of increase of generator output power at each historical reference time by its corresponding similarity weight, summing the results, and then dividing by the sum of all weights. That is, the first velocity.

[0141] Step S0053: Calculate the mean of the normalized values ​​of battery charging demand at all historical reference times, and determine the mean as the first mean.

[0142] It should be noted that each historical reference time corresponds to a normalized value of battery charging demand, and then the average value is calculated. The mean of the normalized values ​​of battery charging demand at all historical reference times f corresponding to the target time t is the first mean.

[0143] Step S0054: If the normalized value of the battery charging demand at the target time is greater than or equal to the first mean, then add 1 to the normalized value of the battery charging demand at the target time to obtain a sum, and then multiply the sum by the first speed to obtain the generator output power increase rate at the target time.

[0144] It should be noted that: if the target time t is If the target output power needs to be adjusted significantly compared to the historical reference time, then the rate of increase of the generator output power at the target time t is... It should be: .

[0145] Step S0055: If the normalized value of the battery charging demand at the target time is less than the first mean, then subtract the normalized value of the battery charging demand at the target time from 1 to obtain the difference, and then multiply the difference by the first speed to obtain the generator output power increase rate at the target time.

[0146] It should be noted that: if the target time t is If the required adjustment for the output power at the target time is smaller compared to the historical reference time, then the rate of increase of the generator output power at the target time t is... It should be: .

[0147] Step S006: Based on the rate of increase of generator output power at the target time, increase the generator output power to the target power at the target time.

[0148] The target power at the target time is the product of the generator's rated output power and the normalized value of the battery charging demand at the target time.

[0149] It should be noted that the formula for calculating the target power at the target time is as follows:

[0150] ;

[0151] in, Let be the target power at the target time t. This is the generator's rated output power. Based on... Increase the generator's output power to The specific adjustment range must not exceed the adjustment limit of the actual physical equipment.

[0152] Step S007: Based on the trend of generator output current change over time after the generator output power is increased to the target power at the target time, obtain the generator stable operation evaluation value during this charging.

[0153] It should be noted that if the generator's output power is increased to the target power, the output AC current is difficult to keep stable (under normal circumstances, after the generator's output power is increased, the output AC current fluctuates, but can recover to stability relatively quickly). However, when there is an abnormality, the time it takes to recover to a stable state is longer, and the fluctuation amplitude is larger. In this case, the generator's ability to operate stably during charging is worse.

[0154] Step S007 further includes steps S0070-S0079:

[0155] Step S0070: Arrange the generator current after the second time step according to the time sequence to obtain the current time sequence; where the second time step is the time when the generator power is increased to the target power at the target time step.

[0156] It should be noted that the moment when the generator's output power first reaches the target power during this charging is marked as the second moment. The current on the generator's AC side after this moment is arranged in time sequence to obtain the current time sequence.

[0157] Step S0071: Perform first-order difference calculation on the current time series to obtain the first difference series.

[0158] It should be noted that by subtracting the current value of the previous moment from the current value of the next moment in the current time series, a new difference series is obtained, namely the first difference series.

[0159] Step S0072: Calculate the mean of all difference values ​​in the first difference sequence, and calculate the absolute value of the ratio of each difference value to the mean.

[0160] It should be noted that: It is denoted as the absolute value of the ratio of each difference to the mean.

[0161] Step S0073: Determine the first moment corresponding to the difference segment where the absolute value of the ratio is continuously less than the preset ratio threshold as the stable moment of this charging.

[0162] It should be noted that the preset ratio threshold is set according to the specific situation, and is preferably 0.5 here.

[0163] If there are three or more consecutive time correspondences If the first moment of the difference value segment that satisfies the condition is marked as the stable moment of this charging, then the stable moment of this charging is marked.

[0164] Step S0074: Obtain the start time of this charging based on the generator output power, and determine the duration from the start time to the stable time as the stable duration.

[0165] It should be noted that: based on the continuously monitored generator output power time-series data, a power threshold that is significantly higher than that under no-load conditions is set as the judgment standard. When the system issues a test command, the moment when the generator output power is first detected to continuously exceed the threshold and enter a stable rising phase is identified and recorded as the start time of this charging process.

[0166] The duration from the start of charging (i.e., the moment the generator begins to bear load) to the steady-state moment is recorded as the steady-state duration. .

[0167] Step S0075: Determine the charging process corresponding to each historical reference time of the target time as the historical reference process.

[0168] It should be noted that: for the target moment of the current charging process, the system first filters out the corresponding set of historical reference moments based on the similarity of states; then it traces the complete charging cycle to which each historical reference moment belongs. If the cycle has been successfully completed and includes the stage of "power increase to the target value" (i.e., it also has a clear target moment), then the complete charging cycle is determined as the historical reference process.

[0169] Step S0076: Obtain the stationary duration of each historical reference process and calculate the average stationary duration of all historical reference processes.

[0170] It should be noted that: firstly, the charging start time is identified by analyzing the generator power time-series curve of the historical reference process, and the stable time when the output stabilizes is determined by the current differential sequence analysis. The time difference between the two is calculated to obtain the stable duration of the process. Then, the stable duration of all historical reference processes is summed and divided by the total number of processes to obtain the average stable duration of the historical reference process.

[0171] This is the average stable duration of all historical reference processes corresponding to this charging.

[0172] Step S0077: Determine the absolute value of the mean of all difference values ​​in the first difference sequence as the first absolute value.

[0173] It should be noted that: This is the absolute value of the mean of all difference values ​​in the difference sequence corresponding to this charging, i.e., the first absolute value.

[0174] Step S0078: Calculate the mean of all difference values ​​in each historical reference process, then calculate the mean of the mean of the difference values ​​in all historical reference processes, and determine the absolute value of the mean of the difference values ​​as the second absolute value.

[0175] It should be noted that: This is the absolute value of the mean of the mean of all difference values ​​for all historical reference processes corresponding to this charging, i.e., the second absolute value.

[0176] Step S0079: Calculate the ratio of the average stable duration to the stable duration, then multiply the ratio by the second absolute value to obtain the product, and finally divide the product by the first absolute value to obtain the generator stable operation evaluation value during this charging.

[0177] It should be noted that if the stable duration of this charging session is significantly longer than that of all historical reference sessions, and the fluctuation amplitude is also more pronounced compared to historical reference sessions, then the generator stable operation assessment value will be smaller. The formula for calculating the generator stable operation assessment value during this charging session is as follows:

[0178] ;

[0179] in, This is the evaluation value for the stable operation of the generator during this charging (the r-th charging).

[0180] Based on Min-Max Normalize to (0, 1), and denote the normalization result as Thus, the stable operation evaluation value of the generator during a single charging process is obtained.

[0181] Step S008: Based on the trend of battery charging demand over time after the generator output power is increased to the target power at the target time, obtain the unstable growth index of this charging.

[0182] It should be noted that during normal operation of the backup power system, its DC bus capacitor can buffer fluctuations in generator output power. That is, once the generator's output power is adjusted to the target power, its stable operation capability is usually high and remains stable (although inherent mechanical fluctuations and other factors may cause a temporary decrease in stable operation capability). However, when the DC bus capacitor is abnormal, its ability to balance generator output fluctuations is poor, resulting in significant abnormal fluctuations. Therefore, the health of the backup power system's DC bus capacitor is assessed based on the fluctuations in generator output stability during charging.

[0183] Taking the current charging process as an example, if the generator's ability to operate stably during a certain charging process is significantly lower than that of the historical reference process, and the battery charging demand still shows unstable growth after the generator power is adjusted to the target power (i.e., there are still output fluctuations that are not buffered by the DC bus capacitor), then the current backup power supply's DC bus health level is low, and the corresponding warning index is higher.

[0184] Step S008 further includes steps S0081-S0087:

[0185] Step S0081: Arrange the normalized values ​​of battery charging demand after the second time step according to the time sequence to obtain the time sequence of battery charging demand.

[0186] It should be noted that the battery charging demand after the generator output power is adjusted to the target power during the current charging process is arranged in time sequence. That is, the normalized value of the battery charging demand level at each target time after the second time moment is sorted to obtain the time sequence of battery charging demand level.

[0187] Step S0082: Perform first-order difference calculation on the time series of battery charging demand to obtain the second difference series.

[0188] Step S0083: Mark the difference values ​​greater than 0 in the second difference sequence as abnormal growth values, and determine the continuous abnormal growth value segments as abnormal growth intervals.

[0189] Step S0084: Calculate the length of each abnormal growth interval and the average length of all abnormal growth intervals.

[0190] It should be noted that the interval length is the number of values ​​contained in the interval. This is the average length of all abnormally growing intervals during this charging process.

[0191] Step S0085: Calculate the length of the second difference sequence and the number of abnormal growth intervals.

[0192] It should be noted that the length of the second difference sequence is the number of values ​​it contains. This is the length of the second differential sequence during this charging process (i.e., the total time from when the generator output power is adjusted to the target power until the end of this charging process - 1). This represents the total number of abnormal growth intervals during this charging process.

[0193] Step S0086: Calculate the average of all abnormal growth values ​​within each abnormal growth interval, and determine the average of the average of the abnormal growth values ​​of all abnormal growth intervals as the second average.

[0194] It should be noted that: It is the mean of all abnormal growth values ​​within all abnormal intervals, i.e., the second mean.

[0195] Step S0087: Divide the length mean by the length of the second difference sequence to obtain the ratio, then multiply the ratio by the number of abnormal growth intervals to obtain the product, and finally multiply the product by the second mean to obtain the unstable growth index of this charge.

[0196] It should be noted that during this charging process, the battery charging demand, even after the generator output power is adjusted to the target power, still exhibits an unstable growth index. The formula for calculating this unstable growth index is as follows:

[0197] ;

[0198] in, This is the unstable growth index for this charging.

[0199] Step S009: Based on the generator stable operation assessment value during this charging and the instability growth index of this charging, obtain the early warning index of the backup power supply.

[0200] Specifically, it includes:

[0201] Obtain the generator stability operation assessment value for each historical reference process, and calculate the average generator stability operation assessment value for all historical reference processes.

[0202] The average generator stable operation assessment value is divided by the generator stable operation assessment value during this charging to obtain the ratio. Then, the ratio is multiplied by the instability growth index of this charging to obtain the early warning index of the backup power supply.

[0203] It should be noted that the formula for calculating the early warning index of backup power is as follows:

[0204] ;

[0205] in, This serves as an early warning index for backup power supplies. This is the average generator stable operation capability across all historical reference processes corresponding to this charging process, i.e., the average generator stable operation assessment value across all historical reference processes.

[0206] The larger the value, the more significantly the generator's ability to operate stably during this charging process is reduced compared to historical reference processes.

[0207] Based on Min-Max Normalize to (0, 1), and denote the normalization result as Thus, the early warning index of the backup power supply was obtained.

[0208] Then, based on the output device, an early warning is issued for abnormal status of the backup power supply.

[0209] The backup power system is monitored and stored in real time. The monitored values ​​are read and the actual charging demand of the battery pack in the backup power system is obtained in the data processing unit. The output power of the generator is adjusted according to the actual charging demand. Based on the obtained target power and the rate of increase of output power, the control command is generated based on the BMS and transmitted to the generator controller to gradually increase the output power.

[0210] After adjusting the generator output power to the target power and maintaining stable output, the health of the bus capacitor is analyzed based on abnormal output fluctuations to obtain the corresponding early warning index, which is then transmitted to the output device.

[0211] Based on the output device, warning information is output: If the generator fails to increase its output power to the target power, corresponding warning information is output to the staff based on the output device. When the backup power supply's warning index... In this case, a warning is issued to the staff (and the corresponding output is provided). value).

[0212] In summary, in this embodiment of the invention, the backup power system is monitored, the dynamic charging demand of the battery pack is obtained based on the monitoring data, and the output power of the generator is adjusted based on the charging demand to match the actual charging demand of the battery pack. The early warning index of the current backup power system is obtained based on the abnormal fluctuations during the matching process, thereby providing timely early warning of abnormal states of the backup power system.

[0213] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for real-time online monitoring of power supply for electromechanical equipment on highways, characterized in that, The method includes the following steps: Collect and store multidimensional data of the backup power system during operation, and preprocess the multidimensional data; wherein, the multidimensional data includes at least generator-side data and BMS-side data; generator-side data includes at least generator output current and power; BMS-side data includes at least battery pack remaining capacity, DC side charging current and battery pack temperature; The health index of the battery pack at different target times is obtained based on the preprocessed BMS side data; where the target time is the time after completing at least one charging process. By utilizing the battery pack's health index at different target times, the battery charging demand at those target times can be obtained. Based on the battery pack's health index at different target times, the battery charging demand at different target times, and the pre-processed BMS-side data, the historical reference time for the target time is determined. By using the preprocessed generator-side data, the battery charging demand at the target time and its historical reference time, the rate of increase of the generator output power at the target time is obtained; Based on the rate of increase of the generator output power at the target time, the generator output power is increased to the target power at the target time. Based on the trend of generator output current change over time after the generator output power is increased to the target power at the target time, the stable operation evaluation value of the generator during this charging is obtained. Arrange the generator currents after the second time step according to the time sequence to obtain the current time sequence; where the second time step is the time when the generator power is increased to the target power at the target time step. The first difference sequence is obtained by performing a first-order difference calculation on the current time series; Calculate the mean of all differences in the first difference sequence, and calculate the absolute value of the ratio of each difference to the mean; The first moment corresponding to the difference segment where the absolute value of the ratio is continuously less than the preset ratio threshold is determined as the stable moment of this charging. The start time of this charging is obtained based on the generator output power, and the duration from the start time to the stable time is determined as the stable duration. The charging process corresponding to each historical reference time of the target time is defined as the historical reference process; Obtain the stationary duration of each historical reference process and calculate the average stationary duration of all historical reference processes; The absolute value of the mean of all difference values ​​in the first difference sequence is determined as the first absolute value; Calculate the mean of all differences in each historical reference process, then calculate the mean of the mean of differences in all historical reference processes, and determine the absolute value of the mean of the difference as the second absolute value; Calculate the ratio of the average stable duration to the stable duration, then multiply the ratio by the second absolute value to obtain the product, and finally divide the product by the first absolute value to obtain the generator stable operation evaluation value during this charging. Based on the trend of battery charging demand over time after the generator output power is increased to the target power at the target time, the unstable growth index of this charging is obtained. Based on the generator's stable operation assessment value during this charging period and the instability growth index during this charging period, an early warning index for the backup power supply is obtained.

2. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The specific steps for obtaining the battery pack's health index at different target times based on preprocessed BMS-side data are as follows: The time interval between the two nearest adjacent charges to the target time is obtained based on the charging current on the DC side, and the maximum time interval between all two adjacent charges before the target time is reached. The charging speed of the most recent charge before the target time is obtained based on the remaining battery power. Based on the DC-side charging current, the mean variance of the DC-side charging current during all charging processes before the target cutoff time is obtained, as well as the variance of the DC-side charging current during the most recent charging process before the target time. Multiply the time interval by the charging speed, then divide by the maximum time interval to get the ratio. Multiply the ratio by the mean variance and then divide by the variance to get the health index of the battery pack at the target time. Obtain the health index of the battery pack at different target times.

3. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 2, characterized in that, The specific steps for obtaining the charging speed from the most recent charge time based on the remaining battery power are as follows: First, calculate the difference between the remaining power at the end of the most recent charge and the remaining power at the beginning of the current charge. Then, divide the difference by the duration of the current charge to obtain the charging speed of the most recent charge from the target time.

4. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The specific steps involved in obtaining the battery charging demand at different target times by utilizing the battery pack's health index are as follows: Obtain the battery pack's health index at the first moment; where the first moment is the moment when the first charge ends. Subtract the remaining battery charge at the target time from 1 to get the difference. Then multiply the battery health index at the first time by the difference to get the product. Finally, divide the product by the battery health index at the target time to get the battery charging demand at the target time. Obtain the battery charging demand at different target times.

5. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The specific steps for determining the historical reference time for the target time based on the battery pack's health index at different target times, the battery charging demand at different target times, and preprocessed BMS-side data are as follows: Obtain the battery charging demand level at historical time points, and determine the absolute value of the difference between the normalized value of the battery charging demand level at the target time and the normalized value of the battery charging demand level at historical time points as the battery charging demand difference between the target time and historical time points; where historical time points are any target time points before the target time point. Obtain the battery pack temperature at the historical time and the target time, and determine the absolute value of the difference between the battery pack temperature at the target time and the battery pack temperature at the historical time as the temperature difference between the target time and the historical time. Obtain the health index of the battery pack at historical time points, and determine the absolute value of the difference between the normalized value of the health index of the battery pack at the target time point and the normalized value of the health index of the battery pack at historical time points as the health index difference between the target time point and the historical time point. The first product is obtained by multiplying the differences in battery charging demand, temperature, and health index between the target time and historical time. The function value with the natural constant e as the base and the negative first product as the exponent is determined as the similarity between the control requirements at the target time and the historical time. If the similarity of the regulation demand is greater than the preset similarity threshold, then the historical moment will be determined as the historical reference moment of the target moment.

6. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The specific steps for obtaining the generator output power increase rate at the target time by utilizing preprocessed generator-side data, the battery charging demand at the target time and its historical reference times are as follows: The rate of increase of generator output power at each historical reference time at the target time is obtained based on the generator output power. Using the similarity between the control demand at the target time and each historical reference time as the weight, the rate of increase of the generator output power at each historical reference time is calculated by weighted average to obtain the first velocity; Calculate the mean of the normalized values ​​of battery charging demand at all historical reference times, and determine the mean as the first mean; If the normalized value of the battery charging demand at the target time is greater than or equal to the first mean, then add 1 to the normalized value of the battery charging demand at the target time to get the sum, and then multiply the sum by the first speed to get the generator output power increase rate at the target time. If the normalized value of the battery charging demand at the target time is less than the first mean, then subtract the normalized value of the battery charging demand at the target time from 1 to obtain the difference, and then multiply the difference by the first speed to obtain the rate of increase of the generator output power at the target time.

7. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The target power at the target time is the product of the generator's rated output power and the normalized value of the battery charging demand at the target time.

8. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The process of obtaining the unstable growth index of this charging operation based on the changing trend of battery charging demand over time after the generator output power is increased to the target power at the target time includes the following specific steps: Arrange the normalized values ​​of battery charging demand after the second time step according to the time sequence to obtain the time sequence of battery charging demand. The first-order difference calculation is performed on the time series of battery charging demand to obtain the second difference series; The difference values ​​greater than 0 in the second difference sequence are marked as abnormal growth values, and the continuous abnormal growth value segments are identified as abnormal growth intervals; Calculate the length of each abnormal growth interval and the average length of all abnormal growth intervals; Calculate the length of the second difference sequence and the number of abnormal growth intervals; Calculate the average of all abnormal growth values ​​within each abnormal growth interval, and determine the average of the average of the abnormal growth values ​​across all abnormal growth intervals as the second average. The ratio is obtained by dividing the length mean by the length of the second difference sequence. Then, the ratio is multiplied by the number of abnormal growth intervals to obtain the product. Finally, the product is multiplied by the second mean to obtain the unstable growth index of this charge.

9. The method for real-time online monitoring of power supply for highway electromechanical equipment according to claim 1, characterized in that, The specific steps for obtaining the early warning index of the backup power supply based on the generator's stable operation assessment value and the instability growth index during this charging period are as follows: Obtain the generator stability operation assessment value for each historical reference process, and calculate the average generator stability operation assessment value for all historical reference processes; The average generator stable operation assessment value is divided by the generator stable operation assessment value during this charging to obtain the ratio. Then, the ratio is multiplied by the instability growth index of this charging to obtain the early warning index of the backup power supply.

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