Method and apparatus for predicting power of battery of electronic shelf label
By obtaining the full battery charge value and dynamic power consumption constant of the electronic shelf label, and combining the power consumption state relationship, the duration of the power consumption state is dynamically determined, thus solving the error problem of electronic shelf label battery power prediction and realizing accurate estimation of battery life.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- HANSHOW TECH CO LTD
- Filing Date
- 2025-11-06
- Publication Date
- 2026-05-15
AI Technical Summary
Existing technologies for electronic price tags have significant errors in predicting battery power, making it impossible to accurately estimate battery life and resulting in inaccurate battery management.
By acquiring the full battery charge value, current dynamic power consumption constant, and power consumption behavior trigger time of the electronic price tag, and combining the pre-established relationship between the power consumption constant and the power consumption value under the state, the duration of the power consumption state is dynamically determined, and the remaining battery charge value is calculated.
It enables accurate prediction of electronic price tag battery level, improves the accuracy of battery life estimation, and guides battery replacement frequency and timing.
Smart Images
Figure CN2025133126_15052026_PF_FP_ABST
Abstract
Description
Battery power prediction method and device for electronic price tags
[0001] Related applications
[0002] This application claims priority to Chinese Patent Application No. 202411573552.1, filed on November 6, 2024, and incorporates the disclosure of the aforementioned patent application as part of this application. Technical Field
[0003] This application relates to the field of electronic price tag technology, and in particular to a method and apparatus for predicting the battery power of an electronic price tag. Background Technology
[0004] This section is intended to provide background or context for the embodiments of this application set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.
[0005] Currently, electronic shelf labels, besides displaying regular information, can be used for many other applications, such as rapid order picking, out-of-stock management, quick inventory checks, and human-computer interaction with users. Limited by battery capacity, electronic shelf labels spend most of their time in a deep sleep state, only waking up periodically to receive radio frequency signals from the base station; this periodic wake-up cycle is called the listening frame cycle. Electronic shelf labels are low-power devices, and achieving a lifespan of several years with two button batteries presents a significant challenge in accurately estimating and managing their battery power.
[0006] Existing methods for predicting the battery level of electronic shelf labels involve periodically collecting battery voltage data from the label and reporting it to a cloud server. The cloud server then estimates the battery level based on the voltage values, thereby estimating the battery's lifespan. However, because battery voltage fluctuates significantly under different operating conditions of the electronic shelf label, the estimated battery level has a large error.
[0007] Existing methods for predicting the battery life of electronic shelf labels include estimating the power consumption required for processing business. For example, some systems can use cloud servers to record the number of updates during electronic shelf label processing (e.g., the number of updates when processing data update packets) or the number of flashing lights (e.g., the number of flashing lights required when performing product recognition) to predict the power consumption of the electronic shelf label. This prediction method limits the power consumption of the electronic shelf label to the power consumption required in a single business scenario. Therefore, this method of predicting the battery life of electronic shelf labels also has a relatively large error. Summary of the Invention
[0008] This application provides a method for predicting the battery level of an electronic shelf label, which is used to accurately predict the battery level of the electronic shelf label. The method includes:
[0009] Obtain the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test;
[0010] Based on multiple current dynamic power consumption constants of the electronic shelf label battery under test, and the pre-established relationship between the power consumption constants and the power consumption values of the electronic shelf label battery under different power consumption states, the power consumption value corresponding to each current dynamic power consumption constant of the electronic shelf label battery under test is determined for each power consumption state.
[0011] Based on the trigger time of each different power consumption behavior of the electronic price tag under test, the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic price tag under test is dynamically determined.
[0012] Based on the full battery charge value of the electronic shelf label under test, the power consumption value under each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant, the remaining battery charge value of the electronic shelf label under test is determined.
[0013] This application also provides a battery power prediction device for electronic price tags, used to accurately predict the battery power of electronic price tags. The device includes:
[0014] The acquisition unit is used to acquire the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test.
[0015] The power consumption value determination unit is used to determine the power consumption value of each current dynamic power consumption constant of the electronic shelf label battery under test, based on multiple current dynamic power consumption constants of the battery under test and the pre-established relationship between the power consumption constants and the power consumption values of the electronic shelf label battery under different power consumption states.
[0016] The duration determination unit is used to dynamically determine the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic price tag under test, based on the trigger time of each different power consumption behavior of the electronic price tag under test.
[0017] The prediction unit is used to determine the remaining battery capacity of the electronic shelf label under test based on the full battery capacity of the electronic shelf label under test, the power consumption value of each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant.
[0018] This application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned battery power prediction method for electronic price tags.
[0019] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-mentioned battery power prediction method for electronic price tags.
[0020] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned battery power prediction method for electronic price tags.
[0021] In this embodiment, the battery power prediction scheme for electronic shelf labels, compared with existing technologies that estimate battery power by voltage or by estimating the power consumed by the electronic shelf label for processing business, involves: obtaining the full battery power value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test; determining the battery power of the electronic shelf label under test based on the multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the pre-established relationship between the power consumption constants and the power consumption values of the battery under different power consumption states of the electronic shelf label. The system calculates the power consumption value of the battery under test for each current dynamic power consumption constant under each power consumption state. Based on the trigger time of each different power consumption behavior of the electronic shelf label under test, it dynamically determines the duration of each power consumption state corresponding to each current dynamic power consumption constant. Based on the full charge value of the battery under test, the power consumption value of each current dynamic power consumption constant under each power consumption state, and the duration of each current dynamic power consumption constant under each power consumption state, it determines the remaining battery charge value of the electronic shelf label under test. This allows for accurate prediction of the battery charge of the electronic shelf label, improving the prediction accuracy of the battery charge of the electronic shelf label. Attached Figure Description
[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:
[0023] Figure 1 is a flowchart illustrating the battery power prediction method for electronic price tags in this embodiment of the present application.
[0024] Figure 2 is a schematic diagram of the battery power prediction principle of the electronic price tag in the embodiments of this application;
[0025] Figure 3 is a flowchart illustrating the battery power prediction method for electronic price tags in another embodiment of this application;
[0026] Figure 4 is a schematic diagram of the battery power prediction device for electronic price tags in an embodiment of this application.
[0027] Figure 5 is a schematic diagram of a computer device structure according to an embodiment of this application;
[0028] Figure 6 is a schematic diagram showing the relationship between the power consumption constant and the power consumption value of the electronic price tag battery under different power consumption states in the embodiments of this application. Detailed Implementation
[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and descriptions of this application are used to explain this application, but are not intended to limit this application.
[0030] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.
[0031] To overcome the technical problem of inaccurate battery life estimation by simply collecting battery voltage, this application mainly adopts a new method for measuring and estimating battery power consumption and life of electronic price tags, thereby improving the accuracy of battery life estimation and obtaining a more accurate remaining battery life to guide administrators on the frequency and / or time of battery replacement.
[0032] Meanwhile, existing methods for predicting the battery life of electronic shelf tags (ESTs) by estimating the power consumption required for processing business operations have significant errors. This is because the power consumption of ESTs is not limited to the power consumed by business operations; it also includes the power consumed by the ESTs themselves to maintain normal operation. For example, the process of an EST reconnecting to the network after losing synchronization, and the process of re-registering during roaming, are not business-level processes but rather power consumption required for the ESTs to maintain normal operation. Therefore, the battery life prediction method for ESTs provided in this application starts from several different power consumption states of the ESTs themselves. The ESTs themselves record the duration of several major power consumption states, thereby more accurately calculating their own power consumption. A detailed introduction follows.
[0033] Figure 1 is a flowchart illustrating the battery power prediction method for electronic price tags in this embodiment of the present application. As shown in Figure 1, the method includes the following steps:
[0034] Step 101: Obtain the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test.
[0035] Step 102: Based on the multiple current dynamic power consumption constants of the electronic shelf label battery under test, and the pre-established relationship between the power consumption constants and the power consumption values of the electronic shelf label battery under different power consumption states, determine the power consumption value corresponding to each current dynamic power consumption constant of the electronic shelf label battery under test under each power consumption state.
[0036] Step 103: Based on the trigger time of each different power consumption behavior of the electronic shelf label under test, dynamically determine the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic shelf label under test;
[0037] Step 104: Based on the full battery charge value of the electronic shelf label under test, the power consumption value under each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant, determine the remaining battery charge value of the electronic shelf label under test.
[0038] The battery power prediction method for electronic shelf labels provided in this application includes the following steps: acquiring the full battery power value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery, and the trigger time of each different power consumption behavior of the electronic shelf label under test; determining the power consumption value of each current dynamic power consumption constant corresponding to each power consumption state of the battery under test based on the multiple current dynamic power consumption constants of the battery and the pre-established relationship between the power consumption constants and the power consumption values of the battery under different power consumption states; dynamically determining the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery under test based on the trigger time of each different power consumption behavior of the battery under test; and determining the remaining battery power value of the electronic shelf label under test based on the full battery power value of the battery, the power consumption value of each current dynamic power consumption constant corresponding to each power consumption state, and the duration of each current dynamic power consumption constant corresponding to each power consumption state.
[0039] Compared with existing technologies that estimate the battery power of electronic shelf labels by voltage or predict the battery power by estimating the power consumption required for processing business, the battery power prediction method for electronic shelf labels provided in this application can accurately predict the battery power of electronic shelf labels, thus improving the prediction accuracy. The battery power prediction method for electronic shelf labels will be described in detail below with reference to Figures 2 and 3. Figure 2 is a schematic diagram of the battery power prediction principle of electronic shelf labels in an embodiment of this application, and Figure 3 is a flowchart of the battery power prediction method for electronic shelf labels in another embodiment of this application.
[0040] In practical implementation, the battery power prediction method for electronic shelf labels in this application embodiment can be applied to electronic shelf labels, that is, the battery power prediction device for electronic shelf labels mentioned below can be installed inside the electronic shelf label. Of course, the battery power prediction method for electronic shelf labels can also be applied to a server, but the electronic shelf label needs to periodically report all these statistical time lengths and other parameters to the server.
[0041] The battery power prediction method for electronic shelf labels provided in this application embodiment includes a screen module, a main circuit module, a battery module, and a casing as its main hardware components. The main circuit module contains a main control chip, which can acquire the battery voltage via an ADC (Analog-to-Digital Converter). The battery power prediction method for electronic shelf labels provided in this application embodiment includes the following steps:
[0042] In step 101 above, determining whether the electronic shelf label is fully charged is the anchor point for the entire precise calculation. The key is determining whether the battery is fully charged. Each time the main control chip starts, its internal startup circuit determines whether the startup is a restart after the battery has been recharged following a power outage. If the main control chip detects that the local startup is a restart after the battery has been recharged, and the battery voltage is the highest value (Battery_FULL) for N consecutive tests (N is a positive integer greater than 1), then it considers the battery to be fully charged (Battery_FULL_VAL) and records this battery level in the non-volatile memory of the main circuit module, such as Flash or NFC EEPROM. The battery usage is then periodically reported according to the configured cycle. When the battery is found to be in a low-battery mode during a restart or periodic reporting, a low-battery icon is displayed according to a pre-configured strategy, and the system is reported as having a low-battery status. After system confirmation or after several consecutive days in this mode, the shelf label enters a low-power state.
[0043] As can be seen from the above, in one embodiment, the battery power prediction method for the electronic shelf label further includes: determining the full battery power value of the electronic shelf label to be tested according to the following method:
[0044] Each time the main control chip of the electronic price tag is started, the startup circuit inside the main control chip detects whether the startup is a restart after the battery has been disconnected and then reconnected.
[0045] If so, and the battery voltage is consistently at its highest value after multiple consecutive checks, the battery is determined to be fully charged, and this fully charged value is taken as the battery's full charge value.
[0046] As can be seen from the above, in one embodiment, the electronic shelf label under test is used to: periodically report the battery usage of the electronic shelf label according to the configuration cycle; when it is restarted or when it is found to be in a low battery state during the period of reporting according to the configuration cycle, it displays a low battery icon and reports its own status as low battery state to the server; after the server confirms or when it is in a low battery state for several consecutive days, the electronic shelf label enters a low power consumption state.
[0047] In step 101 above, as shown in Figure 2, the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the electronic shelf label battery under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test can be sent to the battery power prediction device of the electronic shelf label provided in this application embodiment, or the electronic shelf label can report to the server, and the server can predict the battery power. The specific power consumption constants can be dynamically determined, and can be determined according to different electronic shelf label types or usage scenarios. For example, the dynamic power consumption constant of the electronic shelf label under test of type A application in scenario B can be: the power consumption constant of the model including different working power consumption states such as RX_CURRENT and TX_CURRENT in Figure 6, or the power consumption constant of the size including the screen refresh (SCREEN_CURRENT) power consumption state.
[0048] In step 102 above, determining the power consumption constants of several inherent different states of an electronic shelf label is the foundation of the entire calculation. The method for obtaining these power consumption constants in different states is explained in detail below. It should be noted that the different states mentioned here are distinguished according to the different power consumption of the electronic shelf label's hardware and software operation, and do not correspond one-to-one with the types of business the electronic shelf label can perform. For a specific model (power consumption constant of the main control chip model of the electronic shelf label), during the R&D and testing phase, multiple measurements and calibrations are performed to obtain the power consumption values of the main control chip in different operating states. These include, for example, the power consumption value RX_CURRENT for wireless signal reception, the power consumption value TX_CURRENT for wireless signal transmission, the power consumption value MCU_CURRENT for the main control chip not receiving or transmitting, and the power consumption value DEEPSLEEP_CURRENT for the main control chip in deep sleep. Of course, as shown in Figure 6, it can also include the power consumption value DEEPSLEEP_CURRENT for shallow sleep. For multiple electronic shelf labels with different display sizes, even if the main control chip is the same, the power consumption value for screen refresh will be different. Therefore, it is necessary to obtain the average power consumption value SCREEN_CURRENT for the refresh screen of the electronic shelf label corresponding to this display size during the R&D and testing phase. The basic power consumption value of each screen is affected by the basic parameters of the electronic shelf label itself, such as display size, color, and temperature, and its power consumption model is different. When a new (new type) product (which generates a new type of power consumption constant) is generated or there are anomalies, it can be resolved later through system distribution. That is, in one embodiment, the above-mentioned electronic shelf label battery power prediction method also includes: when a new type of power consumption constant appears, updating the relationship between the power consumption constant and the power consumption value of the electronic shelf label battery under different power consumption states, and writing the new type of power consumption constant into the non-volatile memory inside the shelf label. Of course, the new type of power consumption constant can also be distributed to the electronic shelf label under test through the server, dynamically changing the originally stored constant, and further improving the accuracy of the electronic shelf label battery power prediction.
[0049] In addition, electronic shelf labels also have a flashing light service, so it is also necessary to test and obtain the average power consumption value of the flashing light, LED_CURRENT. That is, the battery power prediction method for electronic shelf labels provided in this application embodiment can also consider the power consumption value under the power consumption state determined by the power consumption required by the electronic shelf label service (such as the flashing light service), such as the average power consumption value of the flashing light service, LED_CURRENT. Each electronic shelf label uses a battery with a battery capacity rating corresponding to the aforementioned Battery_FULL_VAL, for example, 1000mAh, and also a self-consumption coefficient, Battery_Rate, for example, 0.01% per day. During the production of each electronic shelf label, the corresponding battery parameters, such as Battery_FULL_VAL (full battery capacity) and Battery_Rate (battery self-discharge coefficient), including main control chip parameters RX_CURRENT, TX_CURRENT, MCU_CURRENT, DEEPSLEEP_CURRENT, and overall power consumption parameters (constants) SCREEN_CURRENT and LED_CURRENT, are written into the non-volatile memory of the main circuit module, such as Flash and NFC EEPROM. This data is then used by the subsequent battery power prediction device of the electronic shelf label. When this device is set up on a cloud server, as shown in Figure 2, subsequent electronic shelf labels can actively predict battery power according to a pre-configured cycle. These parameters are reported either by sending a parameter reporting command to the price tag controller via the server, or by forwarding the parameter reporting command to the ESL (electronic price tag, or electronic shelf label). After receiving the command, the electronic price tag reports its full charge value, power consumption constant, and the trigger time of each recorded power consumption behavior (such as the wake-up time, the time before sleep, and the power consumption behavior time of individual states such as receiving or transmitting, as mentioned below) to the server. After receiving the full charge value, power consumption constant, and the trigger time of each recorded power consumption behavior (the power consumption behavior corresponding to each power consumption state, such as the power consumption behavior corresponding to the wireless signal receiving state, the power consumption behavior corresponding to the wireless signal transmitting state, etc.), the server executes the battery power prediction method for electronic price tags provided in this application embodiment, such as steps 101-104.
[0050] In practical implementation, the server service in Figure 2 can specify the power consumption data parameters and models for each price tag to be issued or updated, and can predict the service life based on the data reported by each price tag. As shown in Figure 2, this embodiment of the application may also include a price tag controller, which issues various commands, instructions, and data from the server to the price tags and reports the parameters and data of the price tags to the server, thus playing the role of uploading and downloading. The ESls (Electronic Shelf Labels) in Figure 2 represent an electronic price tag cluster, including multiple ESLs. This cluster can include different types of electronic price tags, electronic price tags of different models, sizes, colors, etc. Each electronic price tag can dynamically update its power consumption icon according to its own lifespan and report detailed power consumption data in a timely manner, as well as multiple current dynamic power consumption constants and the trigger time of each different power consumption behavior of the electronic price tag under test (the trigger time of each power consumption behavior recorded by the electronic price tag itself).
[0051] As can be seen from the above, in one embodiment, the multiple current dynamic power consumption constants of the electronic shelf label under test may include: any combination of the main control chip model of the electronic shelf label and its own basic parameters.
[0052] The power consumption values corresponding to the main control chip model of the electronic price tag under the power consumption state can include one or any combination of the following: power consumption value in wireless signal receiving state, power consumption value in wireless signal transmitting state, power consumption value in the state where the main control chip is neither receiving nor transmitting, and power consumption value in the state where the main control chip is in deep sleep.
[0053] The power consumption value corresponding to the basic parameters of the electronic price tag under power consumption status can include one or any combination of the average power consumption value of the refresh screen under different sizes, colors, and temperatures of the electronic price tag.
[0054] As can be seen from the above, in one embodiment, the multiple current dynamic power consumption constants of the electronic price tag under test may also include: the power consumption value corresponding to the power consumption state of the power consumption constant consumed in the service, such as the power consumption constant of the flashing light service LED_CURRENT.
[0055] In step 102 above, multiple current dynamic power consumption constants obtained from the electronic shelf label can be matched with a pre-established relationship between power consumption constants and power consumption values under different power consumption states of the electronic shelf label battery. This yields the power consumption value for each current dynamic power consumption constant of the electronic shelf label battery under test corresponding to each power consumption state. This relationship can be a table as shown in Figure 6, which may also include power consumption constants such as model, color temperature, etc. Alternatively, it can be a neural network model. The input of this model is multiple current dynamic power consumption constants, and the output can be the power consumption value for each current dynamic power consumption constant of the electronic shelf label battery under test corresponding to each power consumption state.
[0056] In step 103 above, accurately recording the duration of each state during the normal continuous operation of the electronic price tag is crucial to the entire calculation. Once the electronic price tag has its battery installed, it begins continuous operation. Each time the electronic price tag wakes up from deep sleep, the cumulative duration of deep sleep (DEEPSLEEP_TIME) is recorded, which is the length of the sleep timer for that current session. If a 16-second sleep period is configured before the current session, and the actual sleep duration is indeed 16 seconds (the actual duration of the electronic price tag's deep sleep state), then 16 seconds are accumulated in DEEPSLEEP_TIME (the actual duration of the deep sleep state). If the current session is interrupted by an external event before 16 seconds have elapsed, then a length similar to the actual sleep duration, such as 7.8 seconds (the actual duration of the deep sleep state), is recorded in DEEPSLEEP_TIME. After an electronic shelf label completes a synchronization signal reception or data reception process from a base station, it accumulates the following durations: MCU_TIME (duration of the inactive state), RX_TIME (duration of wireless signal reception), and TX_TIME (duration of wireless signal transmission). After a screen refresh or light flash, in addition to the aforementioned durations, it also accumulates SCREEN_TIME (duration of screen refresh) and LED_TIME (duration of light flash). The actual duration of each reception or transmission, screen refresh, or light flash varies. Therefore, the electronic shelf label software needs to read the system timer in the chip before each action begins and read it again at the end of the action to obtain the duration of that action. Note that since the time the software spends running should be included in MCU_TIME, this time length is actually the remaining value obtained by subtracting the time length of individual states such as receiving or transmitting from the total time length from the time point when the electronic price tag wakes up each time to the time point before the next sleep state (which can be determined according to the power consumption behavior of individual states such as receiving or transmitting).
[0057] As can be seen from the above, in one embodiment, the duration of each power consumption state corresponding to each current dynamic power consumption constant of the electronic shelf label battery under test is dynamically determined based on the trigger time of each different power consumption behavior of the electronic shelf label under test, including:
[0058] Determine the actual duration of the deep sleep state of electronic price tags;
[0059] After the electronic price tag completes a process of receiving a synchronization signal or receiving data, the duration of the wireless signal receiving state and the duration of the wireless signal transmitting state are accumulated. The actual duration of each reception or transmission is a variable value. The timer in the main control chip of the electronic price tag is read before each power-consuming behavior begins, and the timer in the main control chip of the electronic price tag is read again at the end of each power-consuming behavior, so as to obtain the duration of each power-consuming behavior.
[0060] After an electronic price tag completes one refresh, the cumulative duration of the screen refresh status is recorded, where the actual duration of each refresh is a variable value.
[0061] The duration of the electronic price tag in a state of neither receiving nor sending signals is determined based on the duration of wireless signal reception, the duration of wireless signal transmission, the duration of screen refresh, and the total time from the time point when the electronic price tag is woken up each time to the time point before the next sleep.
[0062] In step 103 above, the electronic shelf label can calculate power consumption according to a predetermined rhythm of days. The estimated residual power is obtained by the following formula. In one embodiment, the residual power value of the electronic shelf label under test is determined based on the full battery capacity of the electronic shelf label under test, the power consumption value of each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant. This includes determining the residual power value of the electronic shelf label's battery according to the following residual power prediction model:
[0063] Battery_VAL=Battery_FULL_VAL–RX_CURRENT RX_TIME
[0064] –TX_CURRENT TX_TIME –MCU_CURRENT MCU_TIME
[0065] –DEEPSLEEP_CURRENT DEEPSLEEP_TIME
[0066] –SCREEN_CURRENT SCREEN_TIME
[0067] –LED_CURRENT LED_TIME-Battery_Rate TOTAL_DAYS;
[0068] Among them, Battery_VAL is the remaining battery power of the electronic shelf label, Battery_FULL_VAL is the full battery power of the electronic shelf label under test, RX_CURRENT is the power consumption value of the wireless signal receiving state, RX_TIME is the duration of the wireless signal receiving state, TX_CURRENT is the power consumption value of the wireless signal transmitting state, TX_TIME is the duration of the wireless signal transmitting state, MCU_CURRENT is the power consumption value of the main control chip when it is neither transmitting nor receiving, MCU_TIME is the duration of the main control chip when it is neither transmitting nor receiving, and DEEPSLEEP_CURRENT is the power consumption value of the main control chip in deep sleep mode. The power consumption values are as follows: DEEPSLEEP_TIME is the duration of the main control chip's deep sleep state; SCREEN_CURRENT is the average power consumption value of the electronic price tag's screen refresh state; SCREEN_TIME is the duration of the electronic price tag's screen refresh state; LED_CURRENT is the average power consumption value of the electronic price tag's flashing light state; LED_TIME is the duration of the electronic price tag's flashing light state; Battery_Rate is the self-consumption coefficient of the electronic price tag's battery; and TOTAL_DAYS is the total time length from when the electronic price tag determines that the battery has been reloaded and started to this calculation (this cycle).
[0069] In practice, the above Battery_VAL calculation formula can be a prediction model for the remaining battery power of electronic price tags.
[0070] After each calculation of the remaining battery power, the electronic shelf label determines the battery indicator icon to be displayed in a predetermined small area on its screen based on the percentage obtained from Battery_VAL / Battery_FULL_VAL. The icon can provide three different prompts: GOOD, MEDIAN, and LOW, improving user experience. In one embodiment, the battery power prediction method for the electronic shelf label further includes: sending a battery display command to the electronic shelf label after each determination of its remaining battery power; the electronic shelf label determines the type of battery indicator icon to be displayed in the predetermined small area on its screen based on the ratio of its full battery power to its remaining battery power. Furthermore, the electronic shelf label proactively reports Battery_VAL to the cloud control center (server in Figure 2) via the uplink, facilitating statistical analysis and providing low battery prompts to management personnel for certain shelf labels. In one embodiment, the battery power prediction method for the electronic shelf label further includes: sending a low battery prompt to the management personnel terminal corresponding to the electronic shelf label when it is confirmed that the electronic shelf label is in a low battery state. Furthermore, when it is determined that the electronic shelf label under test is in a low battery state, the server can, for example, control the electronic shelf label to enter a sleep state and record the identifier and low battery warning information of the electronic shelf label to send to the management terminal, and / or control the electronic shelf label to issue an alarm to remind staff to replace the battery as soon as possible.
[0071] Electronic shelf labels can also calculate the remaining lifespan of their batteries based on TOTAL_DAYS and the percentage of remaining charge. Specifically, in one embodiment, as shown in Figure 3, the battery charge prediction method for the electronic shelf label further includes step 105: predicting the remaining lifespan of the electronic shelf label battery based on the remaining charge value and the self-discharge rate of the battery. For example, the remaining lifespan of the electronic shelf label battery can be predicted using the following formula:
[0072] Battery_Life_Remain=(Battery_VAL / (Battery_FULL_VAL-Battery_VAL))×TOTAL_DAYS;
[0073] In practical implementation, regarding the self-discharge rate of the aforementioned electronic shelf label battery, as shown in the denominator of the Battery_Life_Remain calculation formula above, the denominator represents the amount of electricity already consumed by the battery. Therefore, the prediction of the remaining lifespan of the electronic shelf label battery includes the factor of the battery's self-discharge rate. Thus, the Battery_Life_Remain calculation formula can linearly estimate the remaining battery lifespan, improving the accuracy of predicting the remaining lifespan of the electronic shelf label battery.
[0074] When the e - price tag calculates that Battery_Life_Remain < Remain_Thread (the remaining service life threshold), it indicates that a low - power alarm should be given. On the one hand, the icon LOW is displayed, and on the other hand, the cloud server (the server in Figure 3) is reported, and the cloud server gives a low - power prompt to the management staff.
[0075] In summary, the battery power prediction method of the e - price tag provided by the embodiment of this application achieves:
[0076] 1. A method for an e - price tag to estimate its total power consumption and thus estimate (predict) the battery life according to the cumulative time length (duration) of all e - price tags in different power - consuming states after restarting from re - loading the battery, and according to the power - consuming values measured and recorded in advance for different power - consuming states, as well as the full - load power of the battery itself (the battery full - power value) and the self - power - consumption rate.
[0077] 2. The average power - consuming value measured and recorded for different power - consuming states is written into the non - volatile memory of each e - price tag during the production of each e - price tag.
[0078] 3. The main control chip of the e - price tag can start recalculating the cumulative time length of all states by detecting whether the battery is re - added and starts working.
[0079] 4. The power - consumption calculation mode, such as the algorithm (the relationship between the pre - established power - consumption constant and the power - consuming values of the e - price tag battery in different power - consuming states) and parameters (dynamic power - consumption constant), is sent to the terminal product, such as the e - price tag, through the wireless transceiver by the background system.
[0080] 5. The e - price tag estimates the subsequent service life according to the configured period and the previously used model.
[0081] In the embodiment of this application, a battery power prediction device for an e - price tag is also provided, as described in the following embodiments. Since the principle of this device for solving problems is similar to the battery power prediction method of the e - price tag, the implementation of this device can refer to the implementation of the battery power prediction method of the e - price tag, and the repeated parts will not be described again.
[0082] Figure 4 is a schematic structural diagram of the battery power prediction device of the e - price tag in the embodiment of this application. As shown in Figure 4, the device includes:
[0083] An acquisition unit 01, configured to acquire the battery full - power value of the e - price tag to be measured, multiple current dynamic power - consumption constants of the battery of the e - price tag to be measured, and the trigger time of each different power - consuming behavior of the e - price tag to be measured;
[0084] The power consumption value determination unit 02 is used to determine the power consumption value of each current dynamic power consumption constant of the electronic price tag battery under test, based on multiple current dynamic power consumption constants of the battery under test and the pre-established relationship between the power consumption constants and the power consumption values of the electronic price tag battery under different power consumption states.
[0085] The duration determination unit 03 is used to dynamically determine the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic price tag under test, based on the trigger time of each different power consumption behavior of the electronic price tag under test.
[0086] Prediction unit 04 is used to determine the remaining battery capacity of the electronic shelf label under test based on the full battery capacity value of the electronic shelf label under test, the power consumption value of each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant.
[0087] In one embodiment, the multiple current dynamic power consumption constants of the electronic shelf label under test include: the main control chip model of the electronic shelf label and any combination of the electronic shelf label's own basic parameters;
[0088] The power consumption values of the main control chip model of the electronic price tag under the power consumption state include: power consumption value of wireless signal receiving state, power consumption value of wireless signal transmitting state, power consumption value of main control chip not receiving or transmitting state, and power consumption value of main control chip in deep sleep state, or any combination thereof.
[0089] The power consumption values corresponding to the basic parameters of the electronic price tag under different power consumption states include one or any combination of the average power consumption values of the refresh screen under different sizes, colors, and temperatures of the electronic price tag.
[0090] In one embodiment, the battery power prediction device for the electronic shelf label further includes a full charge value determination unit, configured to: determine the full charge value of the battery of the electronic shelf label to be tested according to the following method:
[0091] Each time the main control chip of the electronic price tag is started, the startup circuit inside the main control chip detects whether the startup is a restart after the battery has been disconnected and then reconnected.
[0092] If so, and the battery voltage is consistently at its highest value after multiple consecutive checks, the battery is determined to be fully charged, and this fully charged value is taken as the battery's full charge value.
[0093] In one embodiment, the electronic shelf label under test is used to: periodically report the battery usage of the electronic shelf label according to the configuration cycle; when it is restarted or when it is found to be in a low battery state during the period of reporting according to the configuration cycle, it displays a low battery icon and reports its own status as low battery state to the server; after the server confirms or when it is in a low battery state for several consecutive days, the electronic shelf label enters a low power consumption state.
[0094] In one embodiment, the battery power prediction device for the electronic shelf label further includes a prompting unit, used to: send a low battery prompt message to the management terminal corresponding to the electronic shelf label when it is confirmed that the electronic shelf label under test is in a low battery state.
[0095] In one embodiment, the battery power prediction device for the electronic shelf label further includes a display control unit, configured to: send a power display command to the electronic shelf label under test after each determination of the remaining battery power value; the electronic shelf label under test is configured to determine the type of power indicator icon displayed on a predetermined small area of the screen of the electronic shelf label based on the ratio of the full battery power value to the remaining battery power value.
[0096] In one embodiment, the battery power prediction device for the electronic shelf label further includes a lifespan prediction unit, used to predict the remaining lifespan of the electronic shelf label battery based on the remaining battery power value of the electronic shelf label under test and the self-discharge rate of the electronic shelf label battery.
[0097] In one embodiment, the battery power prediction device for the electronic shelf label further includes an update unit, configured to: update the relationship between the power consumption constant and the power consumption value of the electronic shelf label battery under different power consumption states when a new type of power consumption constant appears, and write the new type of power consumption constant into the non-perishable memory inside the shelf label.
[0098] In one embodiment, the duration determination unit is specifically used for:
[0099] Determine the actual duration of the deep sleep state of electronic price tags;
[0100] After the electronic price tag completes a process of receiving a synchronization signal or receiving data, the duration of the wireless signal receiving state and the duration of the wireless signal transmitting state are accumulated. The actual duration of each reception or transmission is a variable value. The timer in the main control chip of the electronic price tag is read before each power-consuming behavior begins, and the timer in the main control chip of the electronic price tag is read again at the end of each power-consuming behavior, so as to obtain the duration of each power-consuming behavior.
[0101] After an electronic price tag completes one screen refresh, the cumulative duration of the screen refresh status is a variable value, and the actual duration of each screen refresh is a variable value.
[0102] The duration of the electronic price tag in a state of neither receiving nor sending signals is determined based on the duration of wireless signal reception, the duration of wireless signal transmission, the duration of screen refresh, and the total time from the time point when the electronic price tag is woken up each time to the time point before the next sleep.
[0103] Based on the aforementioned application concept, as shown in Figure 5, this application also proposes a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, it implements the aforementioned electronic price tag battery power prediction method.
[0104] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-mentioned battery power prediction method for electronic price tags.
[0105] This application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-mentioned battery power prediction method for electronic price tags.
[0106] In this embodiment, the battery power prediction scheme for electronic shelf labels, compared with existing technologies that estimate battery power by voltage or by estimating the power consumed by the electronic shelf label for processing business, involves: obtaining the full battery power value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test; determining the battery power of the electronic shelf label under test based on the multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the pre-established relationship between the power consumption constants and the power consumption values of the battery under different power consumption states of the electronic shelf label. The system calculates the power consumption value of the battery under test for each current dynamic power consumption constant under each power consumption state. Based on the trigger time of each different power consumption behavior of the electronic shelf label under test, it dynamically determines the duration of each power consumption state corresponding to each current dynamic power consumption constant. Based on the full charge value of the battery under test, the power consumption value of each current dynamic power consumption constant under each power consumption state, and the duration of each current dynamic power consumption constant under each power consumption state, it determines the remaining battery charge value of the electronic shelf label under test. This allows for accurate prediction of the battery charge of the electronic shelf label, improving the prediction accuracy of the battery charge of the electronic shelf label.
[0107] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0108] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more flowchart illustrations and / or one or more block diagrams.
[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.
[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.
[0111] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for predicting the battery level of an electronic shelf label, characterized in that, The method includes: Obtain the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test; Based on multiple current dynamic power consumption constants of the electronic shelf label battery under test, and the pre-established relationship between the power consumption constants and the power consumption values of the electronic shelf label battery under different power consumption states, the power consumption value corresponding to each current dynamic power consumption constant of the electronic shelf label battery under test is determined for each power consumption state. Based on the trigger time of each different power consumption behavior of the electronic shelf label under test, the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic shelf label under test is dynamically determined; and Based on the full battery charge value of the electronic shelf label under test, the power consumption value under each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant, the remaining battery charge value of the electronic shelf label under test is determined.
2. The method as described in claim 1, characterized in that, The current dynamic power consumption constants of the electronic shelf label under test include: the main control chip model of the electronic shelf label and any combination of the electronic shelf label's own basic parameters; The power consumption values corresponding to the main control chip model of the electronic price tag under various power consumption states include: power consumption value in wireless signal receiving state, power consumption value in wireless signal transmitting state, power consumption value in the main control chip's neither receiving nor transmitting state, and power consumption value in the main control chip's deep sleep state, or any combination thereof; and The power consumption values corresponding to the basic parameters of the electronic price tag under different power consumption states include one or any combination of the average power consumption values of the refresh screen under different sizes, colors, and temperatures of the electronic price tag.
3. The method as described in claim 1, characterized in that, Also includes: Determine the full battery capacity of the electronic shelf label to be tested using the following method: Each time the main control chip of the electronic price tag is started, the startup circuit inside the main control chip detects whether the startup is a restart after the battery has been disconnected and then reconnected. as well as If so, and the battery voltage is consistently at its highest value after multiple consecutive checks, it is determined that the battery is currently fully charged, and the fully charged value is taken as the battery's full charge value.
4. The method as described in claim 3, characterized in that, The electronic shelf label under test is used to: periodically report the battery usage of the electronic shelf label according to the configuration cycle; when it is restarted or when it is found to be in a low battery state during the period of reporting according to the configuration cycle, it displays a low battery icon and reports its status as low battery to the server; after the server confirms or when it is in a low battery state for several consecutive days, the electronic shelf label enters a low power consumption state.
5. The method as described in claim 4, characterized in that, Also includes: When it is confirmed that the electronic shelf label under test is in a low battery state, a low battery reminder message is sent to the terminal of the corresponding management personnel of the electronic shelf label.
6. The method as described in claim 1, characterized in that, Also includes: After determining the remaining battery power of the electronic shelf label under test each time, a power display command is sent to the electronic shelf label under test; the electronic shelf label under test is used to determine the type of power indicator icon to be displayed in a predetermined small area on the screen of the electronic shelf label based on the ratio of the full battery power value to the remaining battery power value.
7. The method as described in claim 1, characterized in that, Also includes: Based on the remaining battery charge of the electronic shelf label under test and the self-discharge rate of the electronic shelf label battery, the remaining service life of the electronic shelf label battery is predicted.
8. The method as described in claim 1, characterized in that, Also includes: When a new type of power consumption constant appears, the relationship between the power consumption constant and the power consumption value of the electronic tag battery under different power consumption states is updated, and the new type of power consumption constant is written into the non-perishable memory inside the tag.
9. The method as described in claim 1, characterized in that, Based on the trigger time of each different power consumption behavior of the electronic shelf label under test, the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic shelf label under test is dynamically determined, including: Determine the actual duration of the deep sleep state of electronic price tags; After the electronic price tag completes a process of receiving a synchronization signal or receiving data, the duration of the wireless signal receiving state and the duration of the wireless signal transmitting state are accumulated. The actual duration of each reception or transmission is a variable value. The timer in the main control chip of the electronic price tag is read before each power-consuming behavior begins, and the timer in the main control chip of the electronic price tag is read again at the end of each power-consuming behavior, so as to obtain the duration of each power-consuming behavior. After an electronic price tag completes one screen refresh, the cumulative duration of the screen refresh status is recorded, where the actual duration of each screen refresh is a variable value; and The duration of the electronic price tag in a state of neither receiving nor sending signals is determined based on the duration of wireless signal reception, the duration of wireless signal transmission, the duration of screen refresh, and the total time from the time point when the electronic price tag is woken up each time to the time point before the next sleep.
10. A battery power prediction device for an electronic price tag, characterized in that, include: The acquisition unit is used to acquire the full battery charge value of the electronic shelf label under test, multiple current dynamic power consumption constants of the battery of the electronic shelf label under test, and the trigger time of each different power consumption behavior of the electronic shelf label under test. The power consumption value determination unit is used to determine the power consumption value of each current dynamic power consumption constant of the electronic shelf label battery under test, based on multiple current dynamic power consumption constants of the battery under test and the pre-established relationship between the power consumption constants and the power consumption values of the electronic shelf label battery under different power consumption states. The duration determination unit is used to dynamically determine the duration of each power consumption state corresponding to each current dynamic power consumption constant of the battery of the electronic price tag under test, based on the trigger time of each different power consumption behavior of the electronic price tag under test. as well as The prediction unit is used to determine the remaining battery capacity of the electronic shelf label under test based on the full battery capacity of the electronic shelf label under test, the power consumption value of each power consumption state corresponding to each current dynamic power consumption constant, and the duration of each power consumption state corresponding to each current dynamic power consumption constant.
11. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 9.
12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.
13. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.