Elevator emergency power supply power monitoring method and system

Abstract

The present invention relates to the technical field of power supply power monitoring, and in particular to a method and system for monitoring the power supply of an elevator emergency power supply. The method comprises the following steps: collecting emergency state start time data; performing real-time battery power measurement of the emergency power supply battery through the emergency state start time data to obtain emergency power supply power measurement data; performing a step pulse power supply test on the elevator emergency lighting to obtain multiple groups of pulse response data of the lamp; performing real-time lamp working state judgment based on the multiple groups of pulse response data of the lamp, and periodically updating the emergency power supply power measurement data to obtain emergency power supply power monitoring data; performing gradual brightness control based on the emergency power supply power monitoring data to obtain an intelligent elevator emergency dimming strategy. The present invention realizes dynamic adjustment of the elevator emergency lighting brightness by intelligently monitoring the remaining power of the elevator emergency power supply to extend the lighting time.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply and electric quantity monitoring, and in particular to a method and system for monitoring the electric quantity of an elevator emergency power supply. Background Art

[0002] As an indispensable vertical transportation tool in modern buildings, the safe operation of elevators is of vital importance. When a sudden power outage occurs, the emergency power supply system of the elevator will play a key role in providing the trapped passengers with necessary guarantees such as lighting, ventilation and communication until rescue arrives. Traditional elevator emergency lighting systems are usually based on a single battery emergency power supply. For example, lead-acid batteries or nickel-cadmium batteries are usually used as energy storage devices, and their power is limited. When the external power supply is interrupted, the emergency power supply will directly start the lighting fixtures to provide temporary lighting. Most of these systems operate in a constant brightness output mode, that is, the emergency lamps continue to work at a fixed brightness until the power supply is exhausted. Although this method can provide sufficient lighting in a short time, it ignores the actual demand for lighting brightness in different situations, which is easy to cause a waste of electricity. Especially in the case of long-term power outages or delayed rescue, the limited emergency power is completely consumed before the rescue is completed, resulting in trapped people facing a dangerous situation without lighting. Summary of the invention

[0003] Based on this, the present invention provides an elevator emergency power supply power monitoring method and system to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a method for monitoring the power of an elevator emergency power supply comprises the following steps:

[0005] Step S1: Acquire the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply power calculation to obtain the emergency power supply power measurement data;

[0006] Step S2: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting to obtain multiple groups of pulse response data of the lamp; perform pulse measurement feature combination according to the multiple groups of pulse response data of the lamp to obtain the pulse measurement feature parameters of the lamp;

[0007] Step S3: Sampling and measuring the working current and voltage of the elevator emergency lighting lamp, and using the lamp pulse measurement characteristic parameters to judge the real-time lamp working state, and generate real-time lamp working state data; based on the real-time lamp working state data, using the power battery charge and discharge model to predict the periodic power consumption, and monitoring the power supply power periodically according to the emergency power supply power measurement data to obtain the emergency power supply power monitoring data;

[0008] Step S4: Set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0009] Preferably, step S1 comprises the following steps:

[0010] Step S11: Obtain the current running status data of the elevator;

[0011] Step S12: judging the emergency state according to the current running state data of the elevator. When the elevator is in the emergency state, real-time data of the start time of the emergency state is collected; when the elevator is not in the emergency state, no data is recorded and a null value is directly returned;

[0012] Step S13: extracting battery parameters of the emergency power supply battery to obtain emergency power supply battery parameters;

[0013] Step S14: constructing a battery charge and discharge model according to the emergency power supply battery parameters to obtain a power supply battery charge and discharge model;

[0014] Step S15: measuring the real-time battery voltage of the emergency power supply battery according to the emergency state start time data, and generating emergency power supply voltage measurement data;

[0015] Step S16: Perform preliminary power supply power calculation on the emergency power supply voltage measurement data using preset battery voltage-power supply mapping data, thereby obtaining emergency power supply power supply measurement data.

[0016] Preferably, step S2 comprises the following steps:

[0017] Step S21: extracting the rated voltage of the elevator emergency lighting lamp to obtain the rated voltage data of the lighting lamp;

[0018] Step S22: Calculating the initial safety voltage value according to the rated voltage data of the lighting lamp, and performing step pulse sequence processing to obtain step pulse voltage sequence data;

[0019] Step S23: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting using the step pulse voltage sequence data to obtain multiple groups of pulse response data of the lighting fixture;

[0020] Step S24: performing a lamp starting current peak analysis on multiple groups of lamp pulse response data to obtain starting current peak data;

[0021] Step S25: judging the lighting state of the lamp according to the starting current peak data, and screening the multiple groups of pulse response data of the lamp for effective pulse response data to generate effective pulse response data;

[0022] Step S26: Calculate the average value of the stable working current and voltage according to the effective pulse response data to generate the stable working state parameters of the lamp;

[0023] Step S27: performing pulse voltage end waveform recognition on the effective pulse response data, and calculating the voltage waveform drop slope to obtain the lamp voltage drop parameter;

[0024] Step S28: performing pulse measurement feature combination on the starting current peak data, the lamp stable working state parameters and the lamp voltage drop parameters to obtain the lamp pulse measurement feature parameters.

[0025] Preferably, step S23 includes the following steps:

[0026] Step S231: extracting the voltage pulse test timestamp according to the emergency state start time data to obtain the pulse test start time data;

[0027] Step S232: Perform a step pulse power supply test on the elevator emergency lighting lamp using the step pulse voltage sequence data, and synchronously collect pulse measurement signals based on the pulse test start time data to generate multiple groups of original response current and voltage data;

[0028] Step S233: performing current and voltage waveform processing on the multiple groups of original response current and voltage data to obtain response current waveform data and response voltage waveform data respectively;

[0029] Step S234: extracting waveform feature points according to the response current waveform data and the response voltage waveform data to obtain current and voltage feature point data;

[0030] Step S235: performing time waveform alignment on the response current waveform data and the response voltage waveform data through the current and voltage characteristic point data, and performing pulse waveform response parameter mapping to obtain the lamp pulse response data;

[0031] Step S236: sorting the lamp pulse response data into a test sequence based on the step pulse voltage sequence data, thereby obtaining multiple groups of lamp pulse response data.

[0032] Preferably, step S3 comprises the following steps:

[0033] Step S31: based on the preset elevator emergency sampling period, the working current and voltage of the elevator emergency lighting lamp are sampled and measured to obtain lamp current sampling data and lamp voltage sampling data respectively;

[0034] Step S32: Calculate the operating time of the lamp according to the emergency state start time data to generate the operating time data of the lamp;

[0035] Step S33: Based on the lamp running time data, the lamp current sampling data and the lamp voltage sampling data are subjected to real-time lamp working state judgment through the lamp pulse measurement characteristic parameters to generate real-time lamp working state data;

[0036] Step S34: Calculate the instantaneous power of the lamp according to the lamp current sampling data and the lamp voltage sampling data to obtain the instantaneous power value of the emergency lamp;

[0037] Step S35: Based on the real-time lamp working status data and the instantaneous power value of the emergency lamp, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the remaining battery power is calculated according to the emergency power supply power measurement data to generate the emergency power supply remaining power data;

[0038] Step S36: Based on the preset elevator emergency sampling cycle, the lamp running time data is used to perform a discharge cycle analysis on the emergency state start time data, and the emergency power remaining power data is monitored and the power supply power is periodically updated to obtain the emergency power supply power monitoring data.

[0039] Preferably, step S33 includes the following steps:

[0040] Step S331: extracting lamp reference current according to lamp stable working state parameters to obtain lamp current reference data;

[0041] Step S332: using the lamp current reference data to perform real-time current deviation calculation on the lamp current sampling data to generate real-time current deviation data;

[0042] Step S333: analyzing the expected voltage value of the lamp according to the running time data of the lamp and the voltage drop parameter of the lamp to obtain the expected voltage value of the lamp;

[0043] Step S334: using the expected voltage value of the lamp to perform real-time voltage deviation calculation on the lamp voltage sampling data to generate real-time voltage deviation data;

[0044] Step S335: performing real-time current and voltage state judgment on the real-time voltage deviation data and the real-time current deviation data by using a preset current and voltage deviation threshold value to obtain real-time lamp current and voltage state data;

[0045] Step S336: performing lamp startup status analysis on the lamp current sampling data by using the startup current peak data to generate lamp startup status data;

[0046] Step S337: Perform comprehensive working status analysis based on the real-time lamp current and voltage status data and the lamp startup status data to generate real-time lamp working status data.

[0047] Preferably, step S35 includes the following steps:

[0048] Step S351: Calculate the power consumption of the emergency lamps during the sampling period according to the preset elevator emergency sampling period, and generate periodic lamp power consumption data;

[0049] Step S352: Analyze the power consumption rate according to the periodic lamp energy consumption data to obtain power consumption rate data;

[0050] Step S353: predicting the power consumption of the next cycle using the power battery charge and discharge model based on the power consumption rate data to generate power consumption prediction data for the next cycle;

[0051] Step S354: performing nonlinear power consumption correction processing on the next cycle power consumption prediction data using the real-time lamp working status data to generate corrected next cycle power consumption data;

[0052] Step S355: Calculate the remaining battery power of the modified next cycle power consumption data using the emergency power supply power monitoring data to generate the remaining battery power data of the emergency power supply.

[0053] Preferably, step S354 includes the following steps:

[0054] Identify the working mode of the lamp according to the real-time working status data of the lamp to obtain the working mode data of the lamp;

[0055] Perform working mode power consumption coefficient analysis on the working mode data of the lamps and generate the working mode power consumption coefficient;

[0056] Use the power consumption coefficient of the operation mode to perform linear weighted power consumption correction on the power consumption forecast data of the next cycle to obtain preliminary corrected power consumption data;

[0057] Extract nonlinear characteristic parameters of the power battery charge and discharge model to obtain the battery nonlinear characteristic parameters;

[0058] The nonlinear power consumption characteristic correction is performed on the preliminary corrected power consumption data based on the nonlinear characteristic parameters of the battery, thereby obtaining the corrected power consumption data for the next cycle.

[0059] Preferably, step S4 comprises the following steps:

[0060] Step S41: Evaluate the remaining lighting time according to the emergency power supply power monitoring data, match the brightness adjustment level, and generate initial dimming level data;

[0061] Step S42: Calculate the ambient light intensity of the elevator car using the ambient light sensor to generate ambient light intensity data;

[0062] Step S43: setting the brightness value of the lamp according to the initial dimming level data, and performing adaptive brightness compensation according to the ambient light intensity data to obtain adaptive brightness value data;

[0063] Step S44: performing brightness-target PWM duty cycle value mapping according to the adaptive brightness value data to obtain brightness-PWM duty cycle value mapping data;

[0064] Step S45: performing a gradual dimming process on the brightness-PWM duty cycle value mapping data using a preset duty cycle adjustment step, thereby obtaining a gradual PWM control signal;

[0065] Step S46: Use the gradual PWM control signal to gradually adjust the brightness of the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0066] Preferably, the present invention further provides an elevator emergency power supply power monitoring system, which executes the elevator emergency power supply power monitoring method as described above, and the elevator emergency power supply power monitoring system comprises:

[0067] The power supply quantity measurement module is used to obtain the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply quantity calculation to obtain the emergency power supply quantity measurement data;

[0068] The emergency lamp pulse test module is used to turn on the elevator emergency lamp based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lamp to obtain multiple groups of lamp pulse response data; perform pulse measurement feature combination based on the multiple groups of lamp pulse response data to obtain the lamp pulse measurement feature parameters;

[0069] The power prediction and update module is used to sample and measure the working current and voltage of the elevator emergency lighting, and use the characteristic parameters of the lamp pulse measurement to judge the real-time working state of the lamp, and generate real-time lamp working state data; based on the real-time lamp working state data, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the power supply is monitored periodically according to the emergency power supply measurement data to obtain the emergency power supply monitoring data;

[0070] The brightness adaptive control module is used to set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0071] The beneficial effect of the present invention is that by acquiring the elevator operation status and the start time of the emergency state in real time, combined with an accurate battery charge and discharge model, the emergency power supply power is accurately monitored. This method does not simply measure the battery voltage for a rough estimate, but performs a dynamic power calculation based on the battery parameters and the charge and discharge model, thereby more accurately reflecting the actual available power of the battery. The present invention introduces a step pulse power supply test and a pulse measurement feature combination to achieve real-time judgment of the working state of the elevator emergency lighting. By analyzing the response of the lamp to different pulse signals and extracting the characteristic parameters of the lamp, the working state of the lamp can be accurately judged, such as whether it is damaged or aged. This provides additional safety for the system, and can detect lamp failures in time to avoid lighting failure in emergency situations. At the same time, real-time monitoring of the working state of the lamp also provides more accurate input parameters for power consumption prediction, further improving the accuracy of power monitoring. Through periodic power consumption prediction, combined with real-time updated power supply power monitoring data, the system can dynamically adjust the brightness of the lamp to maximize the emergency lighting time. In the early stage of power outage, the system can provide a higher brightness to facilitate passengers to observe the environment and conduct necessary communication; as time goes by, the system will gradually reduce the brightness to save power and ensure that the necessary lighting is provided for a longer period of time. This adaptive dimming strategy avoids the waste of electric energy in the traditional constant brightness output mode, especially in the case of long-term power outages or rescue delays, it can maximize the emergency lighting time and significantly improve the safety and comfort of trapped people. The adopted gradual brightness control method avoids the visual discomfort caused by sudden changes in brightness and enhances the experience of trapped passengers. The gradual dimming process is more natural and gentle, and will not cause additional pressure and panic to passengers. Therefore, a method for monitoring the amount of emergency power supply of an elevator of the present invention realizes accurate measurement of the amount of emergency power supply by collecting the start time data of the elevator emergency state in real time, extracting the battery parameters of the emergency power supply battery, and constructing a battery charge and discharge model. The response characteristics of the emergency lighting are further analyzed through a stepped pulse power supply test, the working status of the lamp is judged in real time, and the brightness of the lamp is intelligently adjusted according to the lamp working status data and power supply monitoring data to meet the lighting needs in different emergency situations, thereby extending the emergency lighting time and ensuring that the emergency lighting system can still operate reliably in the event of a long power outage. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A schematic diagram of the steps of the elevator emergency power supply power monitoring method of the present invention;

[0073] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0074] Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG. DETAILED DESCRIPTION

[0075] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0076] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0077] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0078] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for monitoring the amount of electricity of an elevator emergency power supply, comprising the following steps:

[0079] Step S1: Acquire the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply power calculation to obtain the emergency power supply power measurement data;

[0080] Step S2: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting to obtain multiple groups of pulse response data of the lamp; perform pulse measurement feature combination according to the multiple groups of pulse response data of the lamp to obtain the pulse measurement feature parameters of the lamp;

[0081] Step S3: Sampling and measuring the working current and voltage of the elevator emergency lighting lamp, and using the lamp pulse measurement characteristic parameters to judge the real-time lamp working state, and generate real-time lamp working state data; based on the real-time lamp working state data, using the power battery charge and discharge model to predict the periodic power consumption, and monitoring the power supply power periodically according to the emergency power supply power measurement data to obtain the emergency power supply power monitoring data;

[0082] Step S4: Set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0083] In the embodiment of the present invention, reference Figure 1 As shown, it is a schematic diagram of the steps of a method for monitoring the power of an elevator emergency power supply according to the present invention. In this embodiment, the method for monitoring the power of an elevator emergency power supply comprises the following steps:

[0084] Step S1: Acquire the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply power calculation to obtain the emergency power supply power measurement data;

[0085] In an embodiment of the present invention, the current operation state data of the elevator is obtained through sensors and status monitoring modules in the elevator control system, including but not limited to the elevator operation mode (normal operation, maintenance mode, emergency mode, etc.), floor position, speed, acceleration, car load, etc. When the elevator control system detects a power outage or other event that triggers the emergency mode, the emergency state start time data is recorded. This time data can be provided by the system real-time clock with an accuracy of seconds. Parameters of the elevator emergency power battery are extracted. Assuming that the battery is a lead-acid battery, the parameters to be extracted include nominal voltage (e.g., 12V), nominal capacity (e.g., 7Ah), internal resistance, etc. These parameters can be obtained from the battery specification sheet. Then, a battery charge and discharge model is constructed based on the extracted battery parameters. A suitable model can be selected, such as a battery model based on the Thevenin equivalent circuit, which includes an ideal voltage source, a series resistor, and a parallel resistor-capacitor network. The model parameters can be obtained by experimental measurement or by consulting the battery specification sheet. For example, the battery terminal voltage under different discharge currents can be measured by a constant current discharge experiment, and these data can be used to fit the model parameters. Assuming that it is experimentally measured that the battery terminal voltage is 11.5V under 0.5A constant current discharge and 11V under 1A constant current discharge, these data can be used to fit the ideal voltage source and series resistance value in the Thevenin model. The real-time battery voltage of the emergency power supply battery is measured through the emergency start time data. The voltage value at both ends of the battery can be collected in real time using a voltage sensor. Assuming that the battery voltage is measured to be 12.1V at the 10th second after the emergency starts. Combined with the constructed battery charge and discharge model and nominal capacity, a preliminary power supply capacity calculation can be performed.

[0086] Step S2: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting to obtain multiple groups of pulse response data of the lamp; perform pulse measurement feature combination according to the multiple groups of pulse response data of the lamp to obtain the pulse measurement feature parameters of the lamp;

[0087] In the embodiment of the present invention, the control system issues a command to turn on the elevator emergency lighting. In order to obtain the pulse response characteristics of the lamp, a step pulse power supply test is performed on the elevator emergency lighting. Set multiple groups of pulse signals with different amplitudes and widths, for example, pulse signals with amplitudes of 5V, 7V, and 9V, and widths of 0.1s, 0.2s, and 0.3s, for a total of 9 groups. Apply these pulse signals to the emergency lighting in turn, and use a light intensity sensor to record the brightness response curve of the lamp. After each group of pulses is applied, it is necessary to wait for enough time to ensure that the brightness of the lamp returns to the initial state before the next group of tests is performed. The rise time, fall time, peak brightness and other characteristics of each group of pulse response curves can be extracted. Assume that under 5V, 0.1s pulse excitation, the lamp brightness rise time is 0.01s, the fall time is 0.02s, and the peak brightness is 100lx; under 9V, 0.3s pulse excitation, the lamp brightness rise time is 0.005s, the fall time is 0.01s, and the peak brightness is 300lx. These features can be combined, for example, rise time and peak brightness can be linearly combined to obtain the lamp pulse measurement characteristic parameters.

[0088] Step S3: Sampling and measuring the working current and voltage of the elevator emergency lighting lamp, and using the lamp pulse measurement characteristic parameters to judge the real-time lamp working state, and generate real-time lamp working state data; based on the real-time lamp working state data, using the power battery charge and discharge model to predict the periodic power consumption, and monitoring the power supply power periodically according to the emergency power supply power measurement data to obtain the emergency power supply power monitoring data;

[0089] In the embodiment of the present invention, a current sensor and a voltage sensor are used to collect the working current and voltage of the lamp respectively. Assume that the measured working current of the lamp is 0.3A and the voltage is 11.8V. The pulse measurement characteristic parameters of the lamp obtained in step S2 are used to judge the working state of the lamp in real time. For example, the real-time measured lamp brightness rise time and peak brightness can be substituted into the characteristic parameter formula to calculate the real-time characteristic parameters. The real-time characteristic parameters are compared with the preset characteristic parameter range under normal working state to judge whether the lamp is in normal working state. Assuming that the preset normal working state characteristic parameter range is 10-20, and the characteristic parameter calculated in real time is 15, it is judged that the lamp is in normal working state. Generate real-time lamp working state data, including lamp working state (normal / abnormal), working current, working voltage, etc. The system will use the power battery charge and discharge model constructed in step S1 to predict the cycle power consumption based on the real-time lamp working state data. Assuming that the current lamp working current is stable at 0.8A, combined with the battery charge and discharge model, the battery power consumption per unit time can be estimated. For example, according to the model calculation, the battery power consumption per minute is 0.02Ah. Then, the system will monitor the power supply power periodically based on the emergency power supply power measurement data, for example, every 5 minutes. Assume that after the last power measurement, after 5 minutes, the system calculates that the battery power actually consumed 0.1Ah, and the current battery power measurement data is 9.4Ah. This data will be used as the basic data for the next prediction. In this way, emergency power supply power monitoring data can be obtained, for example, a power data sequence updated every 5 minutes.

[0090] Step S4: Set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0091] In an embodiment of the present invention, for example, when the battery power is higher than 8Ah, the brightness of the lamp is set to a maximum value of 100%, when the power is between 6Ah and 8Ah, the brightness is set to 70%, when the power is between 4Ah and 6Ah, the brightness is set to 40%, and when the power is lower than 4Ah, the brightness is set to 20%. Assuming that the current emergency power supply power monitoring data is 7.5Ah, the system will set the brightness value to 70% to obtain adaptive brightness value data. Next, the system will perform brightness-target PWM duty cycle value mapping based on the adaptive brightness value data. PWM (pulse width modulation) is a technology that controls the brightness of lamps by adjusting the duty cycle of pulses. The system pre-stores a brightness-PWM duty cycle mapping table, for example, 100% brightness corresponds to a PWM duty cycle of 90%, 70% brightness corresponds to a PWM duty cycle of 60%, 40% brightness corresponds to a PWM duty cycle of 30%, and 20% brightness corresponds to a PWM duty cycle of 15%. According to the above mapping table, the current 70% brightness corresponds to a PWM duty cycle of 60%. Then, the system will use this duty cycle value to control the elevator emergency lighting to achieve gradual brightness control. For example, the system will gradually transition from the current duty cycle to the target duty cycle in a smooth manner. Assuming that the current PWM duty cycle of the lamp is 80%, the system will gradually reduce the duty cycle from 80% to 60% to avoid sudden changes in brightness. Through this process, an intelligent elevator emergency dimming strategy is obtained, which can automatically adjust the brightness of the lamp according to the emergency power supply to maximize the emergency lighting time and effect.

[0092] Step S1 includes the following steps:

[0093] Step S11: Obtain the current running status data of the elevator;

[0094] Step S12: judging the emergency state according to the current running state data of the elevator. When the elevator is in the emergency state, real-time data of the start time of the emergency state is collected; when the elevator is not in the emergency state, no data is recorded and a null value is directly returned;

[0095] Step S13: extracting battery parameters of the emergency power supply battery to obtain emergency power supply battery parameters;

[0096] Step S14: constructing a battery charge and discharge model according to the emergency power supply battery parameters to obtain a power supply battery charge and discharge model;

[0097] Step S15: measuring the real-time battery voltage of the emergency power supply battery according to the emergency state start time data, and generating emergency power supply voltage measurement data;

[0098] Step S16: Perform preliminary power supply power calculation on the emergency power supply voltage measurement data using preset battery voltage-power supply mapping data, thereby obtaining emergency power supply power supply measurement data.

[0099] In an embodiment of the present invention, the state register of the elevator controller is read in real time through the communication bus of the elevator control system, such as the CAN bus. These registers store the floor where the elevator is currently located, the running direction of the elevator (up, down or stationary), the status of people in the elevator car (for example, whether there are passengers, whether it is overloaded), and the power supply status of the elevator main power supply. According to the elevator running status data obtained in step S11, especially the mains power status and the running mode, it is judged whether the elevator is in an emergency state. For example, when the mains power is off or the control system is switched to the emergency mode (for example, the running mode value is 2), it is judged that the elevator enters the emergency state. If the judgment result is an emergency state, the system real-time clock is started to record the start time data of the emergency state with an accuracy of seconds. If the judgment result is a non-emergency state, for example, the elevator is in a normal running mode and the mains power is normally supplied, no data is recorded and a null value is directly returned. If step S12 judges that it is an emergency state, the parameters of the emergency power battery are extracted. Assume that the emergency power battery is a 12V, 7Ah lead-acid battery. The parameters to be extracted include: nominal voltage (12V), nominal capacity (7Ah), internal resistance, and other parameters related to charge and discharge characteristics. A battery model based on the Thevenin equivalent circuit is used. The model includes an ideal voltage source, a series resistor, and a parallel resistor-capacitor network. The model parameters can be fitted by the parameters obtained in step S13 and the discharge test data. Through the emergency state start time data recorded in step S12, the system starts to measure the real-time battery voltage of the emergency power supply battery. The system uses a high-precision analog-to-digital converter (ADC) to periodically sample the terminal voltage of the battery, for example, 10 times per second, to obtain a real-time voltage value. Each sampling will generate a voltage value. For example, 10 seconds after the start of the emergency state, the voltage value read by the system is 12.4V. These real-time voltage data will be recorded by the system as emergency power supply voltage measurement data. The preset battery voltage-power mapping data can be obtained by performing a complete charge and discharge experiment on the battery. For example, the battery is fully charged, then discharged at a constant current, and the remaining power percentage corresponding to different voltage values ​​is recorded. For example, 12.5V corresponds to 100% power, 12.0V corresponds to 90% power, 11.5V corresponds to 80% power, and so on, to form a lookup table or fitting curve. The emergency power supply voltage measurement data obtained in step S15 is combined with the preset battery voltage-power mapping data to perform a preliminary power supply power calculation. For example, if the measured battery voltage is 12.0V, the corresponding power percentage is 90%, and the preliminary calculated emergency power supply power is 7Ah. 90%=6.3Ah. This power value is used as the emergency power supply power measurement data.

[0100] As an example of the present invention, refer to Figure 2 As shown, Figure 1 Detailed implementation steps of step S2 in the embodiment are shown in the flowchart. In this embodiment, step S2 includes:

[0101] Step S21: extracting the rated voltage of the elevator emergency lighting lamp to obtain the rated voltage data of the lighting lamp;

[0102] In the embodiment of the present invention, for example, the parameters of the driving circuit connected to the lamp can be pre-stored in the system memory, or read through the communication interface, or manually entered. Assuming that the system adopts the pre-storage method, when the system is initialized, the rated voltage data of the lamp stored in the memory will be read, for example, the data read is 24V. This 24V data comes from reading the nameplate or specification of the lamp and is manually entered into the system memory.

[0103] Step S22: Calculating the initial safety voltage value according to the rated voltage data of the lighting lamp, and performing step pulse sequence processing to obtain step pulse voltage sequence data;

[0104] In the embodiment of the present invention, usually, the initial safety voltage value is slightly lower than the rated voltage of the lamp, for example, it can be set to 80% to 90% of the rated voltage. The system multiplies the rated voltage of the lamp by a preset safety factor, such as 0.85, to obtain the initial safety voltage value. Assuming that the rated voltage obtained in step S21 is 24V, the initial safety voltage value is 24V. 0.85=20.4V. After obtaining the initial safety voltage value, the system will perform a step pulse sequence process. This process includes determining the parameters of the pulse sequence, such as pulse amplitude, pulse width, and pulse interval. A step pulse sequence refers to a series of pulses with gradually increasing or decreasing amplitudes, which are used to test the response characteristics of lamps under different voltages. The system will generate a pulse sequence based on the initial safety voltage value. The sequence contains multiple pulses with different amplitudes. The amplitude of the pulse starts from an initial value (such as 10% of the initial safety voltage) and gradually increases to the initial safety voltage value. The pulse width and interval can also be set. For example, the pulse width is 1ms and the pulse interval is 2ms. The amplitude of each pulse will increase step by step.

[0105] Step S23: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting using the step pulse voltage sequence data to obtain multiple groups of pulse response data of the lighting fixture;

[0106] In an embodiment of the present invention, the system turns on the elevator emergency lighting. The "turn on" operation here is achieved by controlling the relay or electronic switch connected to the emergency lighting, that is, sending a control signal to the relay to close it, thereby connecting the power supply to the lamp. Next, the system uses the step pulse voltage sequence data generated in step S22 to perform a step pulse power supply test on the elevator emergency lighting. Specifically, the system provides pulse voltage to the lamp in sequence according to a preset pulse sequence, and each pulse lasts for a specific time, such as 1ms. The system uses a high-precision current and voltage sampling circuit to record the voltage and current response of the lamp under each pulse, and generates multiple sets of pulse response data for the lamp. For example, when the system applies the first 2.04V pulse, the system records the current and voltage waveforms of the lamp, assuming that the measured current peak is 0.05A and the voltage peak is 2.0V. When the system applies the second 6.12V pulse, the system records the current and voltage waveforms of the lamp at this time, assuming that the measured current peak is 0.15A and the voltage peak is 6.0V. By analogy, the system will record the current and voltage response waveforms corresponding to each pulse to form multiple sets of pulse response data.

[0107] Step S24: performing a lamp starting current peak analysis on multiple groups of lamp pulse response data to obtain starting current peak data;

[0108] In the embodiment of the present invention, after obtaining multiple groups of pulse response data of the lamp in step S23, it is necessary to analyze these data and extract the peak starting current data of the lamp. The starting current peak refers to the maximum value reached by the lamp current at the moment each pulse voltage is applied. The current value can be measured by connecting a current sensor in series in the lamp circuit, and recording the current change curve under each pulse voltage. Analyze each current change curve, find the peak current, and record it. For example, under a 6V pulse, the measured starting current peak value is 0.1A; under an 8V pulse, the measured starting current peak value is 0.2A; under a 10V pulse, the measured starting current peak value is 0.3A; under a 12V pulse, the measured starting current peak value is 0.4A. These peak current data are recorded as starting current peak data.

[0109] Step S25: judging the lighting state of the lamp according to the starting current peak data, and screening the multiple groups of pulse response data of the lamp for effective pulse response data to generate effective pulse response data;

[0110] In the embodiment of the present invention, the starting current peak data obtained in step S24 is used to determine whether the lamp is lit. A current threshold is preset, for example, 0.05A. If the starting current peak value corresponding to a certain pulse voltage is greater than the threshold value, it is considered that the lamp is successfully lit at this voltage; otherwise, it is considered that the lamp is not lit. For example, assuming that the starting current peak values ​​at 6V, 8V, 10V and 12V are 0.1A, 0.2A, 0.3A and 0.4A respectively, and all values ​​are greater than the threshold value of 0.05A, it is considered that the lamp is successfully lit at all test voltages. According to the result of the judgment on the lighting state of the lamp, the multiple groups of pulse response data of the lamp obtained in step S23 are screened for valid pulse response data. Only the pulse response data when the lamp is successfully lit is retained, and the pulse response data when the lamp is not lit is discarded. In this example, since the lamp is successfully lit at all test voltages, all pulse response data are valid. Assuming in another example, the lamp lights up only under 10V and 12V, then only the pulse response data corresponding to 10V and 12V are retained to constitute the valid pulse response data.

[0111] Step S26: Calculate the average value of the stable working current and voltage according to the effective pulse response data to generate the stable working state parameters of the lamp;

[0112] In an embodiment of the present invention, the effective pulse response data screened out in step S25 is used to calculate the mean of the stable working current and voltage of the lamp under each pulse voltage. For each pulse voltage, within the pulse duration, the current and voltage of the lamp will first experience a short fluctuation and then enter a stable state. For example, in a pulse width of 0.1 seconds, the first 0.02 seconds is the fluctuation stage, and the last 0.08 seconds is the stable stage. Only the data in the stable stage is calculated. The average values ​​of the current and voltage in the stable stage are calculated respectively as the mean values ​​of the stable working current and voltage of the lamp under the pulse voltage. For example, under a 12V pulse, the current values ​​in the stable stage are 0.38A, 0.39A, 0.4A, 0.41A..., then the mean value of the stable working current is the average value of these values, assuming it is 0.4A. Similarly, the mean value of the voltage in the stable stage is calculated, assuming it is 11.9V. The mean values ​​of the stable working current and voltage under all pulse voltages are recorded to form the parameters of the stable working state of the lamp.

[0113] Step S27: performing pulse voltage end waveform recognition on the effective pulse response data, and calculating the voltage waveform drop slope to obtain the lamp voltage drop parameter;

[0114] In an embodiment of the present invention, the waveform changes at the end of the pulse voltage are analyzed for the effective pulse response data screened out in step S25. When the pulse voltage ends, the voltage across the lamp will drop rapidly. It is necessary to identify the starting point and the end point of the voltage drop, and calculate the voltage waveform drop slope. The voltage waveform drop slope can be defined as the voltage drop value divided by the voltage drop time. For example, at the end of the 12V pulse, the voltage drops from 11.9V to 0V in 0.01 seconds, and the voltage drop slope is (11.9V-0V) / 0.01s=1190V / s. The voltage waveform drop slope is calculated for each effective pulse voltage, and these slope values ​​are recorded as the lamp voltage drop parameters.

[0115] Step S28: performing pulse measurement feature combination on the starting current peak data, the lamp stable working state parameters and the lamp voltage drop parameters to obtain the lamp pulse measurement feature parameters.

[0116] In an embodiment of the present invention, a data structure is established to store the starting current peak value, the average value of the stable working current of the lamp, the average value of the stable working voltage of the lamp and the voltage drop parameter of the lamp in the structure. For example, an array or a structure can be used for data storage, and the starting current peak value of 0.5A, the average value of the stable working current of the lamp is 0.41A, the average value of the stable working voltage of the lamp is 20.2V, and the voltage drop parameter of the lamp is -20V / ms. They are stored in an array or in a structure. The structure contains four variables, namely, the starting current peak value, the stable working current average value, the stable working voltage average value and the voltage drop parameter.

[0117] Step S23 includes the following steps:

[0118] Step S231: extracting the voltage pulse test timestamp according to the emergency state start time data to obtain the pulse test start time data;

[0119] Step S232: Perform a step pulse power supply test on the elevator emergency lighting lamp using the step pulse voltage sequence data, and synchronously collect pulse measurement signals based on the pulse test start time data to generate multiple groups of original response current and voltage data;

[0120] Step S233: performing current and voltage waveform processing on the multiple groups of original response current and voltage data to obtain response current waveform data and response voltage waveform data respectively;

[0121] Step S234: extracting waveform feature points according to the response current waveform data and the response voltage waveform data to obtain current and voltage feature point data;

[0122] Step S235: performing time waveform alignment on the response current waveform data and the response voltage waveform data through the current and voltage characteristic point data, and performing pulse waveform response parameter mapping to obtain the lamp pulse response data;

[0123] Step S236: sorting the lamp pulse response data into a test sequence based on the step pulse voltage sequence data, thereby obtaining multiple groups of lamp pulse response data.

[0124] In an embodiment of the present invention, when the elevator enters the emergency state, the system will record the start time of the emergency state. Before performing the step pulse power supply test, it is necessary to determine the start time of the test. In order to ensure that the test data is associated with the emergency state time, the start time of the emergency state plus a preset delay time can be used as the pulse test start time. For example, the delay time is set to 1 second, and this time is recorded as the pulse test start time data. Using the step pulse voltage sequence data generated in step S22 (for example, 6V (0.1s), 8V (0.1s), 10V (0.1s), 12V (0.1s)), the elevator emergency lighting is tested for step pulse power supply. During the test, the current and voltage signals of the lamp are synchronously collected. The current sensor and the voltage sensor can be used to measure the current and voltage of the lamp respectively, and the data acquisition card can be used to record the data at a certain sampling frequency (for example, 1kHz). The collected current and voltage data are synchronized with the pulse test start time data obtained in step S231, that is, the timestamp corresponding to each data point is recorded. The system will use a filtering algorithm to filter the original current and voltage data. For example, a low-pass filter can be used to remove high-frequency noise, or a median filter can be used to remove pulse noise. The system will select appropriate filter parameters to ensure the filtering effect while avoiding signal distortion. For example, the system can use a low-pass filter with a cutoff frequency of 10kHz to remove high-frequency noise. The current data after filtering will be stored by the system as response current waveform data, and the voltage data after filtering will be stored by the system as response voltage waveform data. Extract feature points from the response current waveform data and response voltage waveform data obtained in step S233. Feature points can be peak values, valley values, rising edges, falling edges, etc. of the waveform. For example, the starting peak point of the current waveform and the average value point of the stable phase can be extracted, and the starting point, the average value point and the end point of the voltage waveform can be extracted. The extracted feature points and the corresponding timestamps are recorded as current and voltage feature point data. Using the current and voltage feature point data extracted in step S234, the response current waveform data and the response voltage waveform data are aligned in time waveform. For example, the starting point of each pulse voltage can be aligned to the same time point. Then, based on the aligned waveform data, extract the pulse waveform response parameters, such as rise time, fall time, peak current, stable current, stable voltage, etc. The extracted parameters and the corresponding pulse voltage values ​​are recorded as the lamp pulse response data. According to the step pulse voltage sequence data used in step S22, the lamp pulse response data obtained in step S235 are sorted. For example, the pulse response data corresponding to the four voltages of 6V, 8V, 10V, and 12V are arranged in order from small to large voltage values. In this way, multiple groups of lamp pulse response data sorted according to the test sequence are obtained.

[0125] Step S3 includes the following steps:

[0126] Step S31: based on the preset elevator emergency sampling period, the working current and voltage of the elevator emergency lighting lamp are sampled and measured to obtain lamp current sampling data and lamp voltage sampling data respectively;

[0127] Step S32: Calculate the operating time of the lamp according to the emergency state start time data to generate the operating time data of the lamp;

[0128] Step S33: Based on the lamp running time data, the lamp current sampling data and the lamp voltage sampling data are subjected to real-time lamp working state judgment through the lamp pulse measurement characteristic parameters to generate real-time lamp working state data;

[0129] Step S34: Calculate the instantaneous power of the lamp according to the lamp current sampling data and the lamp voltage sampling data to obtain the instantaneous power value of the emergency lamp;

[0130] Step S35: Based on the real-time lamp working status data and the instantaneous power value of the emergency lamp, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the remaining battery power is calculated according to the emergency power supply power measurement data to generate the emergency power supply remaining power data;

[0131] Step S36: Based on the preset elevator emergency sampling cycle, the lamp running time data is used to perform a discharge cycle analysis on the emergency state start time data, and the emergency power remaining power data is monitored and the power supply power is periodically updated to obtain the emergency power supply power monitoring data.

[0132] In an embodiment of the present invention, the preset elevator emergency sampling cycle can be set according to actual needs, for example, set to 10 minutes. This means that the working current and voltage of the elevator emergency lighting are sampled and measured once every 10 minutes. The real-time current and voltage values ​​of the lamp are collected using a current sensor and a voltage sensor respectively. In each sampling cycle, the system reads the data of the current and voltage sensors and stores these data in the memory. The system needs to calculate the running time of the lamp. The running time of the lamp refers to the length of time the lamp has been working from the start of the emergency state to the current moment. The system reads the internal real-time clock, obtains the current date and time information, and then compares the current time with the start time of the emergency state to calculate the time difference between the two. For example, the time difference between the two can be calculated by calculating the timestamp difference to obtain the running time of the lamp. The real-time working state of the lamp is judged by using the lamp pulse measurement characteristic parameters obtained in step S28, combined with the lamp current sampling data and lamp voltage sampling data collected in step S31, and the lamp running time data calculated in step S32. For example, different characteristic parameters can be selected for comparison according to the running time of the lamp. At the initial stage of lamp startup, the starting current peak value can be used for judgment; in the stable working stage of the lamp, the stable working current and voltage mean value can be used for judgment. Compare the real-time collected current and voltage data with the preset normal working range. If it exceeds the normal range, it is considered that the lamp is faulty. For example, if the stable working current mean value exceeds the preset upper limit, it is judged that the lamp has a short circuit fault. Based on the judgment result, real-time lamp working status data is generated, such as "normal" or "faulty". The instantaneous power of the lamp is calculated using the lamp current sampling data and lamp voltage sampling data collected in step S31. The calculation formula for instantaneous power is: P=I V, where P is the instantaneous power, I is the current value, and V is the voltage value. The system will determine whether the lamp is in normal working condition based on the real-time lamp working status data. If the lamp is in normal working condition, the system will use the instantaneous power value of the emergency lamp, combined with the power battery charging and discharging model, to predict the battery power consumption in the next sampling cycle. For example, assuming that the battery charging and discharging model calculates the power consumption in the next sampling cycle (for example, 10 minutes) to be 0.0002Ah based on the current instantaneous power of 8.442W and the internal resistance of the battery and other parameters, then the predicted value of the power consumption in the next cycle is 0.0002Ah. This calculation process can be performed using the battery model in step S14. If the working state of the lamp is abnormal, the power consumption at this time can be estimated according to the preset abnormal mode. For example, the power consumption will decrease when the lamp is aged, or the power consumption will increase when it is short-circuited. Next, the system will calculate the remaining battery power based on the emergency power supply power measurement data obtained in step S16 and the predicted power consumption value of the next cycle, and generate the emergency power supply remaining power data. Using the running time data of the lamp generated in step S32, the discharge cycle analysis is performed on the emergency state start time data, and the emergency power remaining power data is monitored periodically to update the power supply power, thereby obtaining the emergency power supply power monitoring data. Discharge cycle analysis means that the system will determine how many sampling cycles the battery has gone through from the start of the emergency state to the current moment, so as to determine whether the power monitoring data needs to be updated. The system will calculate how many sampling cycles have passed based on the preset elevator emergency sampling cycle and the running time of the lamp. The system can set a power monitoring cycle update threshold, for example, update the power monitoring data every 3 sampling cycles. If the current sampling cycle count reaches this threshold, the system will use the emergency power remaining power data obtained in step S35 as the latest emergency power monitoring data for periodic updates.

[0133] Step S33 includes the following steps:

[0134] Step S331: extracting lamp reference current according to lamp stable working state parameters to obtain lamp current reference data;

[0135] Step S332: using the lamp current reference data to perform real-time current deviation calculation on the lamp current sampling data to generate real-time current deviation data;

[0136] Step S333: analyzing the expected voltage value of the lamp according to the running time data of the lamp and the voltage drop parameter of the lamp to obtain the expected voltage value of the lamp;

[0137] Step S334: using the expected voltage value of the lamp to perform real-time voltage deviation calculation on the lamp voltage sampling data to generate real-time voltage deviation data;

[0138] Step S335: performing real-time current and voltage state judgment on the real-time voltage deviation data and the real-time current deviation data by using a preset current and voltage deviation threshold value to obtain real-time lamp current and voltage state data;

[0139] Step S336: performing lamp startup status analysis on the lamp current sampling data by using the startup current peak data to generate lamp startup status data;

[0140] Step S337: Perform comprehensive working status analysis based on the real-time lamp current and voltage status data and the lamp startup status data to generate real-time lamp working status data.

[0141] In an embodiment of the present invention, the stable working state parameters of the lamp include the average current and voltage when the lamp is working stably under different pulse voltages. The average stable working current corresponding to the rated voltage is selected as the lamp current reference data. For example, assuming that the rated voltage of the lamp is 12V, and the average stable working current under the 12V pulse voltage measured in S26 is 0.4A, 0.4A is used as the lamp current reference data. Compare the lamp current sampling data collected in step S31 with the lamp current reference data extracted in step S331 to calculate the real-time current deviation. The calculation formula for the real-time current deviation is: Current deviation = (real-time current value - reference current value) / reference current value 100%. The expected voltage value of the lamp is analyzed using the lamp running time data obtained in step S32 and the lamp voltage drop parameter obtained in step S27. Since the battery voltage will gradually decrease during the discharge process, the voltage across the lamp will also decrease accordingly. The expected voltage value of the lamp at the current running time can be estimated based on the battery discharge model and the lamp voltage drop parameter. For example, assuming that the battery discharge model is a linear model, the voltage drop rate is 0.01V / second, the lamp has been running for 15 seconds, and the initial voltage is 12V, then the expected voltage value is 12V-0.01V / second 15 seconds = 11.85V. Compare the lamp voltage sampling data collected in step S31 with the expected lamp voltage value calculated in step S333 to calculate the real-time voltage deviation. The calculation formula for the real-time voltage deviation is: Voltage deviation = (real-time voltage value - expected voltage value) / expected voltage value 100%. For example, assuming the current sampled voltage value is 11.8V and the expected voltage value is 11.85V, the voltage deviation is (11.8V-11.85V) / 11.85V 100%=-0.42%. The current deviation threshold and the voltage deviation threshold are preset, for example, the current deviation threshold is ±10%, and the voltage deviation threshold is ±5%. The real-time current deviation data calculated in step S332 and the real-time voltage deviation data calculated in step S334 are compared with the preset thresholds. If the current deviation or voltage deviation exceeds the threshold range, it is considered that the current or voltage state of the lamp is abnormal. For example, if the real-time current deviation is 12%, which exceeds the current deviation threshold ±10%, it is considered that the current state of the lamp is abnormal. According to the judgment result, real-time lamp current and voltage state data are generated, such as "normal" or "abnormal". The startup state of the lamp is analyzed by using the startup current peak data obtained in step S24 and the lamp current sampling data collected in step S31. For example, it can be judged whether the lamp is in the startup stage and whether the startup process is normal based on the current sampling data. If the peak value of the current in the startup stage is significantly different from the startup current peak value recorded in S24, it is considered that the startup state of the lamp is abnormal. According to the analysis result, the startup state data of the lamp is generated, such as "normal startup", "startup abnormality" or "non-startup stage". Combined with the real-time lamp current and voltage status data obtained in step S335 and the lamp startup status data obtained in step S336, a comprehensive working status analysis is performed. For example, if the lamp current and voltage status are normal, and the startup status is normal, the overall working status of the lamp is considered normal. If the lamp current and voltage status is abnormal or the startup status is abnormal, the overall working status of the lamp is considered abnormal. Based on the analysis results, real-time lamp working status data is generated, such as "normal" or "faulty".

[0142] Step S35 includes the following steps:

[0143] Step S351: Calculate the power consumption of the emergency lamps during the sampling period according to the preset elevator emergency sampling period, and generate periodic lamp power consumption data;

[0144] Step S352: Analyze the power consumption rate according to the periodic lamp energy consumption data to obtain power consumption rate data;

[0145] Step S353: predicting the power consumption of the next cycle using the power battery charge and discharge model based on the power consumption rate data to generate power consumption prediction data for the next cycle;

[0146] Step S354: performing nonlinear power consumption correction processing on the next cycle power consumption prediction data using the real-time lamp working status data to generate corrected next cycle power consumption data;

[0147] Step S355: Calculate the remaining battery power of the modified next cycle power consumption data using the emergency power supply power monitoring data to generate the remaining battery power data of the emergency power supply.

[0148] In the embodiment of the present invention, the instantaneous power value of the emergency lighting calculated in step S34 and the preset elevator emergency sampling period are used to calculate the power consumption within the sampling period. The calculation formula for power consumption is: Power consumption = instantaneous power Sampling period. The power consumption rate refers to the amount of power consumed by the lamp per unit time, usually expressed in ampere-hours per second (Ah / s) or ampere-hours per hour (Ah / h). The system can use a variety of methods to analyze the power consumption rate. For example, it can calculate the average value of the power consumption of the lamp over a period of time, or use methods such as sliding average filtering for smoothing to reduce the impact of instantaneous power fluctuations. For example, the system can take the average value of the power consumption data of the periodic lamps in the most recent N sampling periods as the current power consumption rate. The purpose of the next cycle power consumption prediction is to estimate how much power the battery will consume in the next elevator emergency sampling period. The system will multiply the current power consumption rate data by the length of a sampling period to obtain the estimated power consumption in the next sampling period. The power consumption rate data obtained in step S352 and the power battery charge and discharge model constructed in step S14 are used to predict the power consumption of the next sampling period. For example, the current power consumption rate can be multiplied by the sampling period to obtain the predicted value of power consumption in the next sampling period. The prediction in step S353 is based on the current power consumption rate, assuming that the consumption rate remains unchanged. However, in actual situations, the working state of the lamp will change, resulting in nonlinear changes in power consumption. Therefore, it is necessary to correct the predicted value based on the real-time lamp working state data generated in step S33. For example, if the working state of the lamp changes from "normal" to "faulty", the power consumption will increase. Assuming that a short circuit occurs in the lamp and the current doubles, the predicted power consumption needs to be doubled accordingly. The corrected power consumption is recorded as the corrected next-cycle power consumption data. The remaining battery power is calculated using the emergency power supply power monitoring data periodically updated in step S36 and the corrected next-cycle power consumption data obtained in step S354. The calculation formula for the remaining battery power is: Remaining power = current power - corrected next-cycle power consumption.

[0149] Step S354 includes the following steps:

[0150] Identify the working mode of the lamp according to the real-time working status data of the lamp to obtain the working mode data of the lamp;

[0151] Perform working mode power consumption coefficient analysis on the working mode data of the lamps and generate the working mode power consumption coefficient;

[0152] Use the power consumption coefficient of the operation mode to perform linear weighted power consumption correction on the power consumption forecast data of the next cycle to obtain preliminary corrected power consumption data;

[0153] Extract nonlinear characteristic parameters of the power battery charge and discharge model to obtain the battery nonlinear characteristic parameters;

[0154] The nonlinear power consumption characteristic correction is performed on the preliminary corrected power consumption data based on the nonlinear characteristic parameters of the battery, thereby obtaining the corrected power consumption data for the next cycle.

[0155] In an embodiment of the present invention, the working mode can be divided according to the characteristics of the current, voltage and other parameters of the lamp, for example, it can be divided into "normal mode", "low brightness mode", "flickering mode" and "fault mode". For example, if the real-time lamp working status data shows that the current and voltage are stable within the normal range, it is identified as "normal mode"; if the voltage is normal but the current is significantly lower than the normal value, it is identified as "low brightness mode"; if the current and voltage fluctuate periodically, it is identified as "flickering mode"; if the current or voltage exceeds the normal range by a large margin, it is identified as "fault mode". The identified lamp working mode is recorded as lamp working mode data. For different lamp working modes, the corresponding power consumption coefficient is pre-set. The power consumption coefficient represents the ratio of the actual power consumption of the lamp in this mode to the power consumption in the normal mode. For example, assuming that the power consumption coefficient of the "normal mode" is 1, the power consumption coefficient of the "low brightness mode" is 0.5, the power consumption coefficient of the "flickering mode" is 0.8, and the power consumption coefficient of the "fault mode" (such as short circuit) is 2. These coefficients can be obtained through experimental measurement, for example, measuring the actual power consumption of the lamp in different working modes, and then comparing it with the power consumption in normal mode to calculate the corresponding power consumption coefficient. Using the periodic power consumption prediction data generated in step S353 and the operating mode power consumption coefficient analyzed in step S354, a linear weighted correction is performed on the prediction data. The correction formula is: Preliminary correction power consumption = periodic power consumption prediction data Operation mode power consumption coefficient. The system needs to extract the nonlinear parameters of the battery charge and discharge model so as to correct the nonlinear power consumption characteristics in the subsequent steps. The nonlinear parameters of the battery usually include the relationship between the internal resistance of the battery and the state of charge (SOC), the relationship between the open circuit voltage of the battery and the SOC, and the relationship between the charge and discharge efficiency of the battery and the charge and discharge current. These parameters can be obtained by performing actual charge and discharge tests on the battery, for example, by fitting these nonlinear relationships through charge and discharge tests under different currents. For example, a table lookup method can be used to read the corresponding internal resistance value according to the current SOC value, and then the linear model in the previous step S14 is used for calculation. The system will read the nonlinear parameters of the battery according to the current battery SOC value, for example, read the corresponding internal resistance value, and then use this internal resistance value and the current working current to calculate the voltage drop of the battery. Then use this voltage drop to correct the preliminary power consumption data. For example, assuming that the current SOC of the battery is 50%, the internal resistance obtained by the table lookup is 0.3Ω. If the current working current is 0.4A, the voltage drop is 0.4A. 0.3Ω=0.12V, the power consumption data can be initially corrected according to the difference between the actual working voltage and the ideal voltage of the battery. Alternatively, the system can directly use the nonlinear model to bring in the current SOC, current and other parameters to calculate the power consumption. For example, according to the battery model introduced in step S14, V=V_oc-I R, where V_oc is the open circuit voltage, which can be expressed as a function of SOC, I is the discharge current, and R is the internal resistance, which can be expressed as a function of SOC. After correction, the final corrected cycle power consumption data is obtained.

[0156] As an example of the present invention, refer to Figure 3 As shown, Figure 1 Detailed implementation steps of step S4 in the embodiment are shown in the flowchart. In this embodiment, step S4 includes:

[0157] Step S41: Evaluate the remaining lighting time according to the emergency power supply power monitoring data, match the brightness adjustment level, and generate initial dimming level data;

[0158] In the embodiment of the present invention, the remaining lighting time of the emergency lighting lamp is estimated based on the emergency power supply power monitoring data obtained in step S36 and the current lamp power consumption (which can be estimated based on the instantaneous power value of S34). For example, assuming that the current remaining power of the emergency power supply is 6.2998364Ah and the lamp power consumption is 3.54W, the remaining lighting time is approximately 6.2998364Ah. 12V / 3.54W≈21.4 hours. Determine the initial dimming level based on the preset brightness adjustment level strategy and the estimated remaining lighting time. The brightness adjustment level strategy can be preset. For example, the remaining lighting time can be divided into several intervals, each interval corresponding to a dimming level. For example, if the remaining lighting time is greater than 20 hours, the dimming level is level 1 (100% brightness); if the remaining lighting time is between 10-20 hours, the dimming level is level 2 (75% brightness); if the remaining lighting time is between 5-10 hours, the dimming level is level 3 (50% brightness); if the remaining lighting time is less than 5 hours, the dimming level is level 4 (25% brightness). In this example, since the remaining lighting time is approximately 21.4 hours, the initial dimming level is level 1. The determined dimming level is recorded as the initial dimming level data.

[0159] Step S42: Calculate the ambient light intensity of the elevator car using the ambient light sensor to generate ambient light intensity data;

[0160] In an embodiment of the present invention, an ambient light sensor is installed in the elevator car to detect the ambient light intensity in the car. The ambient light sensor can be a photoresistor, a photodiode, etc. The sensor outputs an analog signal or a digital signal related to the light intensity. The signal output by the sensor is converted into a light intensity value, and the unit can be lux. For example, the sensor output value is 1V, and the light intensity value obtained after conversion is 500lux. The calculated ambient light intensity value is recorded as ambient light intensity data.

[0161] Step S43: setting the brightness value of the lamp according to the initial dimming level data, and performing adaptive brightness compensation according to the ambient light intensity data to obtain adaptive brightness value data;

[0162] In an embodiment of the present invention, the brightness value of the lamp is set according to the initial dimming level data generated in step S41. For example, level 1 corresponds to 100% brightness, level 2 corresponds to 75% brightness, level 3 corresponds to 50% brightness, and level 4 corresponds to 25% brightness. In this example, the initial dimming level is level 1, so the brightness value of the lamp is set to 100%. Then, according to the ambient light intensity data obtained in step S42, the set lamp brightness value is adaptively compensated. The compensation strategy can be preset, for example, the lamp brightness can be adjusted by a certain proportion according to the ambient light intensity. For example, when the ambient light intensity is higher than a preset threshold (for example, 500 lux), the lamp brightness is reduced; when the ambient light intensity is lower than the preset threshold, the lamp brightness is increased. The specific compensation ratio can be adjusted according to the actual situation. For example, assuming that the ambient light intensity is 600 lux, which is higher than the preset threshold of 500 lux, the lamp brightness is reduced by 10%, that is, the final brightness value is 100%-10%=90%.

[0163] Step S44: performing brightness-target PWM duty cycle value mapping according to the adaptive brightness value data to obtain brightness-PWM duty cycle value mapping data;

[0164] In an embodiment of the present invention, a mapping relationship between a brightness value and a PWM duty cycle value is established. A linear mapping or a nonlinear mapping method can be used. Linear mapping refers to a linear relationship between a brightness value and a PWM duty cycle value. For example, 50% brightness corresponds to a 50% duty cycle, and 100% brightness corresponds to a 100% duty cycle. Nonlinear mapping refers to a nonlinear relationship between a brightness value and a PWM duty cycle value. For example, logarithmic mapping or exponential mapping can be used according to the human eye's perception characteristics of brightness. Assuming that a linear mapping method is used, 0% brightness is mapped to 0% duty cycle, and 100% brightness is mapped to 100% duty cycle. According to the adaptive brightness value data obtained in step S43, the corresponding PWM duty cycle value is searched. For example, if the adaptive brightness value data is 90%, the corresponding PWM duty cycle value is 90%. The brightness value and the corresponding PWM duty cycle value are recorded to form brightness-PWM duty cycle value mapping data.

[0165] Step S45: performing a gradual dimming process on the brightness-PWM duty cycle value mapping data using a preset duty cycle adjustment step, thereby obtaining a gradual PWM control signal;

[0166] In an embodiment of the present invention, in order to avoid sudden changes in the brightness of the lamp, it is necessary to gradually adjust the PWM duty cycle. The preset duty cycle adjustment step is set to 5%, for example. According to the current PWM duty cycle value and the target PWM duty cycle value, the number of steps required for adjustment is calculated. For example, assuming that the current PWM duty cycle value is 80%, the target PWM duty cycle value is 90%, and the adjustment step is 5%, the number of steps required for adjustment is (90%-80%) / 5%=2 steps. Then, a PWM control signal is generated at a preset frequency (for example, 1kHz). In each PWM cycle, the PWM duty cycle is gradually adjusted according to the calculated number of steps until the target value is reached. For example, in the first PWM cycle, the duty cycle is 85%; in the second PWM cycle, the duty cycle is 90%. In this way, a gradual PWM control signal is obtained.

[0167] Step S46: Use the gradual PWM control signal to gradually adjust the brightness of the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0168] In an embodiment of the present invention, the system uses a PWM controller to control the power supply circuit of the lamp according to the generated gradual PWM control signal to adjust the brightness of the lamp. The PWM controller generates a corresponding pulse waveform according to the duty cycle of the PWM control signal. This pulse waveform controls the drive circuit to supply power to the lamp, changes the average power of the lamp, and thus adjusts the brightness of the lamp. The system continuously outputs a PWM control signal to maintain the brightness of the lamp at a set level. For example, in step S45, if the target PWM duty cycle value is 70%, the system will start from the current PWM value, such as 50%, and gradually increase to 70%. At the same time, the brightness of the lamp will gradually increase to the brightness value corresponding to 70% brightness, thereby achieving gradual dimming. The system will cyclically execute steps S44 to S46 to ensure that the brightness of the lamp can be dynamically adjusted according to the battery power and ambient light intensity, thereby realizing the emergency dimming strategy of the intelligent elevator.

[0169] The present invention also provides an elevator emergency power supply power monitoring system, which executes the elevator emergency power supply power monitoring method as described above, and the elevator emergency power supply power monitoring system comprises:

[0170] The power supply quantity measurement module is used to obtain the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply quantity calculation to obtain the emergency power supply quantity measurement data;

[0171] The emergency lamp pulse test module is used to turn on the elevator emergency lamp based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lamp to obtain multiple groups of lamp pulse response data; perform pulse measurement feature combination based on the multiple groups of lamp pulse response data to obtain the lamp pulse measurement feature parameters;

[0172] The power prediction and update module is used to sample and measure the working current and voltage of the elevator emergency lighting, and use the characteristic parameters of the lamp pulse measurement to judge the real-time working state of the lamp, and generate real-time lamp working state data; based on the real-time lamp working state data, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the power supply is monitored periodically according to the emergency power supply measurement data to obtain the emergency power supply monitoring data;

[0173] The brightness adaptive control module is used to set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

[0174] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0175] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for monitoring the power of an elevator emergency power supply, characterized in that: The following steps are involved: Step S1: Acquire the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply power calculation to obtain the emergency power supply power measurement data; Step S2: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting to obtain multiple groups of pulse response data of the lighting fixture; Combining pulse measurement characteristics according to multiple groups of pulse response data of the lamp to obtain pulse measurement characteristic parameters of the lamp; Step S3: Sampling and measuring the working current and voltage of the elevator emergency lighting lamp, and using the lamp pulse measurement characteristic parameters to judge the real-time lamp working state, and generate real-time lamp working state data; based on the real-time lamp working state data, using the power battery charge and discharge model to predict the periodic power consumption, and monitoring the power supply power periodically according to the emergency power supply power measurement data to obtain the emergency power supply power monitoring data; Step S4: Set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

2. The elevator emergency power supply power monitoring method according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Obtain the current running status data of the elevator; Step S12: judging the emergency state according to the current running state data of the elevator. When the elevator is in the emergency state, real-time data of the start time of the emergency state is collected; when the elevator is not in the emergency state, no data is recorded and a null value is directly returned; Step S13: extracting battery parameters of the emergency power supply battery to obtain emergency power supply battery parameters; Step S14: constructing a battery charge and discharge model according to the emergency power supply battery parameters to obtain a power supply battery charge and discharge model; Step S15: measuring the real-time battery voltage of the emergency power supply battery according to the emergency state start time data, and generating emergency power supply voltage measurement data; Step S16: Perform preliminary power supply power calculation on the emergency power supply voltage measurement data using preset battery voltage-power supply mapping data, thereby obtaining emergency power supply power supply measurement data.

3. The elevator emergency power supply power monitoring method according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: extracting the rated voltage of the elevator emergency lighting lamp to obtain the rated voltage data of the lighting lamp; Step S22: Calculating the initial safety voltage value according to the rated voltage data of the lighting lamp, and performing step pulse sequence processing to obtain step pulse voltage sequence data; Step S23: Turn on the elevator emergency lighting based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lighting using the step pulse voltage sequence data to obtain multiple groups of pulse response data of the lighting fixture; Step S24: performing a lamp starting current peak analysis on multiple groups of lamp pulse response data to obtain starting current peak data; Step S25: judging the lighting state of the lamp according to the starting current peak data, and screening the multiple groups of pulse response data of the lamp for effective pulse response data to generate effective pulse response data; Step S26: Calculate the average value of the stable working current and voltage according to the effective pulse response data to generate the stable working state parameters of the lamp; Step S27: performing pulse voltage end waveform recognition on the effective pulse response data, and calculating the voltage waveform drop slope to obtain the lamp voltage drop parameter; Step S28: performing pulse measurement feature combination on the starting current peak data, the lamp stable working state parameters and the lamp voltage drop parameters to obtain the lamp pulse measurement feature parameters.

4. The elevator emergency power supply power monitoring method according to claim 3 is characterized in that: Step S23 includes the following steps: Step S231: extracting the voltage pulse test timestamp according to the emergency state start time data to obtain the pulse test start time data; Step S232: Perform a step pulse power supply test on the elevator emergency lighting lamp using the step pulse voltage sequence data, and synchronously collect pulse measurement signals based on the pulse test start time data to generate multiple groups of original response current and voltage data; Step S233: performing current and voltage waveform processing on the multiple groups of original response current and voltage data to obtain response current waveform data and response voltage waveform data respectively; Step S234: extracting waveform feature points according to the response current waveform data and the response voltage waveform data to obtain current and voltage feature point data; Step S235: performing time waveform alignment on the response current waveform data and the response voltage waveform data through the current and voltage characteristic point data, and performing pulse waveform response parameter mapping to obtain the lamp pulse response data; Step S236: sorting the lamp pulse response data into a test sequence based on the step pulse voltage sequence data, thereby obtaining multiple groups of lamp pulse response data.

5. The elevator emergency power supply power monitoring method according to claim 3 is characterized in that: Step S3 includes the following steps: Step S31: based on the preset elevator emergency sampling period, the working current and voltage of the elevator emergency lighting lamp are sampled and measured to obtain lamp current sampling data and lamp voltage sampling data respectively; Step S32: Calculate the operating time of the lamp according to the emergency state start time data to generate the operating time data of the lamp; Step S33: Based on the lamp running time data, the lamp current sampling data and the lamp voltage sampling data are subjected to real-time lamp working state judgment through the lamp pulse measurement characteristic parameters to generate real-time lamp working state data; Step S34: Calculate the instantaneous power of the lamp according to the lamp current sampling data and the lamp voltage sampling data to obtain the instantaneous power value of the emergency lamp; Step S35: Based on the real-time lamp working status data and the instantaneous power value of the emergency lamp, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the remaining battery power is calculated according to the emergency power supply power measurement data to generate the emergency power supply remaining power data; Step S36: Based on the preset elevator emergency sampling cycle, the lamp running time data is used to perform a discharge cycle analysis on the emergency state start time data, and the emergency power remaining power data is monitored and the power supply power is periodically updated to obtain the emergency power supply power monitoring data.

6. The elevator emergency power supply power monitoring method according to claim 5 is characterized in that: Step S33 includes the following steps: Step S331: extracting lamp reference current according to lamp stable working state parameters to obtain lamp current reference data; Step S332: using the lamp current reference data to perform real-time current deviation calculation on the lamp current sampling data to generate real-time current deviation data; Step S333: analyzing the expected voltage value of the lamp according to the running time data of the lamp and the voltage drop parameter of the lamp to obtain the expected voltage value of the lamp; Step S334: using the expected voltage value of the lamp to perform real-time voltage deviation calculation on the lamp voltage sampling data to generate real-time voltage deviation data; Step S335: performing real-time current and voltage state judgment on the real-time voltage deviation data and the real-time current deviation data by using a preset current and voltage deviation threshold value to obtain real-time lamp current and voltage state data; Step S336: performing lamp startup status analysis on the lamp current sampling data by using the startup current peak data to generate lamp startup status data; Step S337: Perform comprehensive working status analysis based on the real-time lamp current and voltage status data and the lamp startup status data to generate real-time lamp working status data.

7. The elevator emergency power supply power monitoring method according to claim 5 is characterized in that: Step S35 includes the following steps: Step S351: Calculate the power consumption of the emergency lamps during the sampling period according to the preset elevator emergency sampling period, and generate periodic lamp power consumption data; Step S352: Analyze the power consumption rate according to the periodic lamp energy consumption data to obtain power consumption rate data; Step S353: predicting the power consumption of the next cycle using the power battery charge and discharge model based on the power consumption rate data to generate power consumption prediction data for the next cycle; Step S354: performing nonlinear power consumption correction processing on the next cycle power consumption prediction data using the real-time lamp working status data to generate corrected next cycle power consumption data; Step S355: Calculate the remaining battery power of the modified next cycle power consumption data using the emergency power supply power monitoring data to generate the remaining battery power data of the emergency power supply.

8. The elevator emergency power supply power monitoring method according to claim 7 is characterized in that: Step S354 includes the following steps: Identify the working mode of the lamp according to the real-time working status data of the lamp to obtain the working mode data of the lamp; Perform working mode power consumption coefficient analysis on the working mode data of the lamps and generate the working mode power consumption coefficient; Use the power consumption coefficient of the operation mode to perform linear weighted power consumption correction on the power consumption forecast data of the next cycle to obtain preliminary corrected power consumption data; Extract nonlinear characteristic parameters of the power battery charge and discharge model to obtain the battery nonlinear characteristic parameters; The nonlinear power consumption characteristic correction is performed on the preliminary corrected power consumption data based on the nonlinear characteristic parameters of the battery, thereby obtaining the corrected power consumption data for the next cycle.

9. The elevator emergency power supply power monitoring method according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: Evaluate the remaining lighting time according to the emergency power supply power monitoring data, match the brightness adjustment level, and generate initial dimming level data; Step S42: Calculate the ambient light intensity of the elevator car using the ambient light sensor to generate ambient light intensity data; Step S43: setting the brightness value of the lamp according to the initial dimming level data, and performing adaptive brightness compensation according to the ambient light intensity data to obtain adaptive brightness value data; Step S44: performing brightness-target PWM duty cycle value mapping according to the adaptive brightness value data to obtain brightness-PWM duty cycle value mapping data; Step S45: performing a gradual dimming process on the brightness-PWM duty cycle value mapping data using a preset duty cycle adjustment step, thereby obtaining a gradual PWM control signal; Step S46: Use the gradual PWM control signal to gradually adjust the brightness of the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

10. An elevator emergency power supply power monitoring system, characterized in that: Used to execute the elevator emergency power supply power monitoring method according to claim 1, the elevator emergency power supply power monitoring system comprises: The power supply quantity measurement module is used to obtain the current operation status data of the elevator; collect the emergency state start time data in real time according to the current operation status data of the elevator; extract the battery parameters of the emergency power supply battery, and construct the battery charge and discharge model to obtain the power supply battery charge and discharge model; measure the battery voltage of the emergency power supply battery in real time according to the emergency state start time data, and perform preliminary power supply quantity calculation to obtain the emergency power supply quantity measurement data; The emergency lamp pulse test module is used to turn on the elevator emergency lamp based on the emergency state start time data, and perform a step pulse power supply test on the elevator emergency lamp to obtain multiple groups of lamp pulse response data; perform pulse measurement feature combination based on the multiple groups of lamp pulse response data to obtain the lamp pulse measurement feature parameters; The power prediction and update module is used to sample and measure the working current and voltage of the elevator emergency lighting, and use the characteristic parameters of the lamp pulse measurement to judge the real-time working state of the lamp, and generate real-time lamp working state data; based on the real-time lamp working state data, the power consumption of the next cycle is predicted using the power battery charge and discharge model, and the power supply is monitored periodically according to the emergency power supply measurement data to obtain the emergency power supply monitoring data; The brightness adaptive control module is used to set the brightness value of the lamp according to the emergency power supply power monitoring data to obtain adaptive brightness value data; perform brightness-target PWM duty cycle value mapping according to the adaptive brightness value data, and perform gradual brightness control on the elevator emergency lighting, thereby obtaining an intelligent elevator emergency dimming strategy.

Images