A battery charge judgment and prediction method for IoT stand-alone smoke detectors

Abstract

The present invention provides a battery power judgment and prediction method for an IOT stand-alone smoke detector, which can accurately judge and predict the battery power, and then combine voltage and temperature to control the operation of the communication module to achieve the purpose of controlling power consumption and ensuring that the stand-alone smoke detector can work for a long time. It is characterized by comprising the following steps: Step 1, before the smoke detector turns on the communication module each time, it enters the power judgment and prediction process and updates the battery power percentage SOC BAT ; Step 2, collect ambient temperature T AMB and the battery voltage V BAT , and combined with the battery charge percentage SOC BAT Determine whether the communication module is turned on; if so, continue to step 3, otherwise return to data collection; Step 3, turn on the communication module and calculate the power consumption Q of the communication module COMnew ; Step 4, according to the power consumption Q of this communication module COMnew Update battery charge percentage SOC BAT .

Description

Technical Field

[0001] The present invention relates to the technical field related to photoelectric smoke detectors, and in particular to a method for judging and predicting the battery charge level of an IOT stand-alone smoke detector. Background Art

[0002] Photoelectric smoke detectors are categorized as point-type and stand-alone smoke detectors based on their communication mode. Point-type smoke detectors typically use a wired connection, with the cable providing both power and communication. Stand-alone smoke detectors use a wireless connection to the host computer. Detectors designed for IoT (Internet of Things) applications typically utilize wireless communication methods such as NB-IoT, Lora, Bluetooth, and ZigBee. Because of this wireless connection, stand-alone smoke detectors require a built-in disposable battery for power.

[0003] Standalone smoke detectors require sufficient power to sustain continuous operation for at least three years, and the batteries they use must have high durability. Therefore, lithium-manganese batteries, lithium-substrate batteries (collectively referred to as disposable lithium batteries), or similar high-reliability non-rechargeable batteries are the preferred choice for standalone smoke detectors. To ensure long-term operation, power consumption and the ability to determine and predict battery charge levels are key considerations for standalone smoke detector designers.

[0004] Regarding power consumption: The working modes of stand-alone smoke detectors are divided into periodic data acquisition mode and periodic data communication mode: the average working current of the periodic data acquisition mode is very low, and the typical power consumption is less than 10uA; in the periodic data communication mode, the communication module will consume a lot of battery power. This is because when using wireless communication modules such as NB-IOT, Lora, Bluetooth and ZigBee, the communication current generally ranges from a few mA to several hundred mA.

[0005] Regarding the judgment and prediction of battery power: First, the voltage of a disposable lithium battery will decrease as the ambient temperature decreases. Therefore, if the battery voltage is used as the judgment condition for the battery power, it is very easy to misjudge. The use of battery fuel meter chips in the existing technology also has problems: one is that it increases costs, and the other is that it increases additional static power consumption; secondly, the power of a disposable lithium battery will decay over time, and the self-discharge current of the battery will lose some power. Although the self-discharge current is very low, it cannot be ignored for products that require long-term power supply; then the output voltage of a disposable lithium battery is related to the load current. In particular, when the battery power becomes low, using a communication module will lower the battery voltage while the output current increases. If the battery voltage is very low, it will affect the power supply of other circuits and even cause the detector to be unable to collect data.

[0006] Therefore, for the application scenario of stand-alone smoke detectors, we need to design a low-cost, low-power method for judging and predicting the power level of disposable lithium batteries to control power consumption and ensure that the stand-alone smoke detector can work for a long time. Summary of the Invention

[0007] In order to solve the problems mentioned above, the present invention provides a battery power judgment and prediction method for an IOT stand-alone smoke detector, which can accurately judge and predict the battery power, and then combine voltage and temperature to control the operation of the communication module, thereby controlling power consumption and ensuring that the stand-alone smoke detector can work for a long time.

[0008] The technical solution is as follows:

[0009] A method for determining and predicting the battery level of an IoT standalone smoke detector, comprising the following steps:

[0010] Step 1: Before turning on the communication module each time, the smoke detector enters the power judgment and prediction process and updates the battery power percentage SOC BAT ;

[0011] Step 2: Collect ambient temperature T AMB and the battery voltage V BAT , and combined with the battery charge percentage SOC BAT Determine whether the communication module is turned on; if so, continue to step 3, otherwise return to data collection;

[0012] Step 3: Turn on the communication module and calculate the power consumption Q of this communication module COMnew ;

[0013] Step 4: Based on the power consumption Q of the communication module COMnew Update battery charge percentage SOC BAT .

[0014] Furthermore, in step 1, the battery power percentage SOC is updated BAT Specifically: First update the past power consumption Q CON , Q CON =I Q ×ΔT+Q COM , where I Q is the static average current of the smoke detector, that is, the average current in the periodic data acquisition mode, ΔT is the cumulative working time of the smoke detector, Q COM The accumulated power consumption of the smoke detector's communication module is updated with the battery power percentage SOC. BAT , SOC BAT =(Q BAT -QCON )÷Q BAT , where Q BAT The effective battery level.

[0015] Furthermore, the step 2 includes the following steps:

[0016] Step 2-1: Collect ambient temperature T AMB And battery voltage information V BAT If the battery charge percentage SOC BAT If ≤10%, the communication module will not be turned on and step 2-5 will be executed; otherwise, step 2-2 will be executed;

[0017] Step 2-2, if V BAT ≥V TH , then the communication module is turned on and steps 2-5 are executed, otherwise steps 2-3 are executed; where V TH is the threshold voltage, which is between 2.6V and 2.7V;

[0018] Step 2-3, if T AMB ≥-10℃, then the communication module will not be turned on and steps 2-5 will be executed; otherwise, step 2-4 will be executed;

[0019] Step 2-4: If -20℃≤T AMB <-10℃ and SOC BAT ≥20%, the communication module is turned on and steps 2-5 are executed; otherwise, the communication module is not turned on and steps 2-5 are executed;

[0020] Step 2-5: Based on the result of determining whether the communication module is turned on, if yes, proceed to step 3; otherwise, return to data collection in the periodic data collection mode.

[0021] Furthermore, the power consumption Q of the communication module is calculated in step 3. COMnew Specifically: Assume that the sending working time of the communication module is T TX , the unit is s; the average current of the sending operation is I TX , the unit is mA; the receiving working time is T RX , the unit is s; the average current of the receiving operation is I RX , the unit is mA; then the power consumption of this communication module is Q COMnew =(T TX ×I TX +T RX ×I RX )÷3600, the unit is mAh.

[0022] Furthermore, assuming that the signal quality of the communication module is divided into five levels according to the signal strength, the corresponding current intensity coefficient K=[K1,K2,K3,K4,K5], then I TXN =I TX ×K,I RXN =I RX ×K,Q COMnew =(T TX ×I TXN +T RX ×I RXN )÷3600, where I TXN is the average current of the transmission operation after coefficient compensation, I RXN The K factor is the average receiving current after coefficient compensation. Signal strength can generally be obtained by reading the status of the communication module and is divided into five levels. The K factor can be obtained empirically through experiments.

[0023] Furthermore, in step 4, the power consumption Q of the communication module is COMnew Update battery charge percentage SOC BAT Specifically: First, the power consumption of the communication module Q COMnew The accumulated power consumption value Q added to the communication module COM Then update the past power consumption Q CON , Q CON =I Q ×ΔT+Q COM ;Last updated battery percentage AOC BAT , SOC BAT =(Q BAT -Q CON )÷Q BAT .

[0024] Furthermore, the effective battery power Q BAT =Q Rating ×M, where Q Rating is the rated capacity of the battery, and M is the margin factor, which ranges from 85% to 95%.

[0025] The beneficial effects of the present invention are:

[0026] 1. The method of the present invention determines and predicts the battery charge by accumulating the operating time of the smoke detector's periodic data acquisition mode and the power consumption of the communication module. It then uses voltage and temperature to comprehensively determine and control the operation of the communication module. The communication module is only considered to be turned on when the battery is sufficient, thereby achieving power consumption control and ensuring the long-term operation of the stand-alone smoke detector.

[0027] 2. The method of the present invention does not increase additional hardware costs and power consumption; the battery voltage can be monitored using the processor's built-in analog-to-digital conversion circuit, with an acquisition accuracy better than ±0.1V; the ambient temperature can be collected using a low-cost NTC temperature sensor and the processor's built-in analog-to-digital conversion circuit, with an acquisition accuracy better than ±3°C; these designs have relatively low requirements and can all be completed using low-cost devices, and do not require real-time acquisition, only on-demand acquisition is required. Compared with solutions using battery fuel meters or current sensors, both costs and system power consumption are saved.

[0028] 3. The battery charge obtained by the method of the present invention is not affected by sudden temperature changes, so the device can calmly cope with different environmental conditions and avoid false alarms caused by ambient temperature changes. In addition, considering that the self-discharge current of the battery will cause partial loss of power, a margin coefficient is set in this method, and the effective battery power is used to calculate the remaining power percentage. In addition, considering that the signal quality of the communication module corresponds to different current intensities, a current intensity coefficient is set to compensate for the power consumption of the communication module each time according to different signal strengths. The above designs further ensure the accurate estimation of the battery charge of the stand-alone smoke detector.

[0029] 4. Since there is no linear relationship between battery voltage and battery charge, the present invention does not use a single voltage monitoring judgment method. Instead, it fully considers different scenarios that affect battery voltage: low temperature environment, low battery charge and large load current, etc., and uses the comprehensive judgment criteria in the method of the present invention to reduce misjudgment and improve the accuracy of judgment; and the present invention also includes special treatment for low temperature. When the ambient temperature is below -20℃, the effective capacity of the battery is already very low and cannot meet the environment of large output current, such as driving the communication module. At this time, the detector only works in the normal periodic data acquisition mode, ensuring that the independent smoke detector can work for a long time.

[0030] 5. Compared with mainstream smoke detectors on the market that are only marked with operating environments of -10℃ to 55℃ or 60℃, the method of the present invention can greatly improve the accuracy of battery power estimation, and is also beneficial for operation and maintenance; the independent smoke detector itself has the ability to communicate and interact with the background server, and can synchronize with the background data and information while reporting the status. After the background has mastered the batch equipment operation data, it can make targeted equipment operation improvements and even feedback to the R&D end to improve product performance.

[0031] 6. The method of the present invention is applicable to all lithium battery powered system equipment and has good portability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 Schematic diagram of the method of the present invention.

[0033] Figure 2 Schematic diagram of the method flow of step 2 in the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below with reference to the embodiments.

[0035] The following examples are intended to illustrate the present invention but are not intended to limit the scope of protection of the present invention. The conditions in the examples may be further adjusted according to specific conditions. Simple improvements to the method of the present invention within the scope of the present invention are also within the scope of protection claimed in the present invention.

[0036] The working modes of smoke detectors are divided into periodic data collection mode and periodic data communication mode: periodic data collection mode means that the detector collects data periodically. At this time, the detector is in ultra-low power mode, and the typical average power consumption is ≤10uA; periodic data communication mode means that the detector periodically turns on the communication module to send status information and report data. The typical reporting cycle is 1 to 7 days.

[0037] like Figure 1 As shown, a battery power judgment and prediction method for an IOT stand-alone smoke detector is characterized by including the following steps.

[0038] Step 1: Before turning on the communication module each time, the smoke detector enters the power judgment and prediction process and updates the battery power percentage SOC BAT ; Specifically: First update the past power consumption Q CON , Q CON =I Q ×ΔT+Q COM , where I Q is the static average current of the smoke detector, that is, the average current in the periodic data acquisition mode, ΔT is the cumulative working time of the smoke detector, Q COM The accumulated power consumption of the smoke detector's communication module is updated with the battery power percentage SOC. BAT , SOC BAT =(Q BAT -Q CON )÷Q BAT , where Q BAT is the effective battery capacity. ΔT and Q COM All of them are accumulated by the program of the smoke detector and stored in a non-volatile memory along with other variables in the present invention. This is a conventional technical means and will not be described in detail here.

[0039] Step 2: Collect ambient temperature T AMB and the battery voltage V BAT , and combined with the battery charge percentage SOCBAT Determine whether the communication module is turned on; if so, continue to step 3, otherwise return to data collection. Figure 2 As shown, the specific steps include:

[0040] Step 2-1: Collect ambient temperature T AMB And battery voltage information V BAT To monitor the battery voltage, you can use the processor's built-in analog-to-digital conversion circuit with an acquisition accuracy better than ±0.1V; to collect the ambient temperature, you can use a low-cost NTC temperature sensor and the processor's built-in analog-to-digital conversion circuit with an acquisition accuracy better than ±3°C; if the battery power percentage SOC BAT If the battery level is ≤10%, the device is running low on power. In this case, the communication module is disabled and steps 2-5 are executed. Otherwise, step 2-2 is executed. When the battery level is low, the communication module is disabled to preserve battery life. From a system design perspective, when the battery level is about to fall below the level required to enable the communication module, the server can be proactively notified of the battery level and the communication module can be discontinued.

[0041] Step 2-2, if V BAT ≥V TH , regardless of the temperature T AMB If the value is V, the battery is considered to be fully charged, then the communication module is turned on and steps 2-5 are executed, otherwise steps 2-3 are executed; TH is the threshold voltage, which is between 2.6V and 2.7V.

[0042] Step 2-3, if T AMB ≥-10℃, indicating that the device is working within the normal operating range and the battery is insufficient, then the communication module is not turned on and steps 2-5 are performed. Otherwise, steps 2-4 are performed.

[0043] Step 2-4: If -20℃≤T AMB <-10℃ and SOC BAT ≥20%, indicating that the device is working under low temperature conditions and has sufficient power, then the communication module is turned on and steps 2-5 are executed; otherwise, the communication module is not turned on and steps 2-5 are executed. AMBIf the temperature is <-20°C, it indicates the device is operating in extremely low temperatures. At this time, the battery voltage is very low, requiring only normal data acquisition mode, and the device will not activate the communication module. For example, EVE Energy's disposable CR17450 lithium-manganese dioxide battery measures 17*45mm, has a capacity of 2200-2400mAh, a voltage of 3V, and a discharge cut-off voltage of 2.0V. These specifications are at room temperature. As the ambient temperature decreases, the battery capacity, voltage, and discharge current decrease, especially below -20°C. Therefore, the smoke detector's battery charge management, determination, and prediction must take these various conditions into account. When the battery is low or the device is in extremely low temperatures, the communication module will not be activated, and the device will only operate in normal data acquisition mode.

[0044] Step 2-5: Based on the result of determining whether the communication module is turned on, if yes, proceed to step 3; otherwise, return to data collection in the periodic data collection mode.

[0045] Step 3: Turn on the communication module and calculate the power consumption Q of this communication module COMnew ; Specifically: Assume that the sending working time of the communication module is T TX , the unit is s; the average current of the sending operation is I TX , the unit is mA; the receiving working time is T RX , the unit is s; the average current of the receiving operation is I RX , the unit is mA; then the power consumption of this communication module is Q COMnew =(T TX ×I TX +T RX ×I RX )÷3600, the unit is mAh.

[0046] Signal strength can generally be obtained by reading the status of the communication module and is divided into five levels. Preferably, assuming the signal quality of the communication module is divided into five levels based on signal strength, the corresponding current strength coefficient K = [K1, K2, K3, K4, K5]. K1 to K5 are divided into five equal parts, corresponding to signal strengths of 0%-100%, with K1 corresponding to the worst signal quality (0%-20%) and K5 corresponding to the best signal quality (80%-100%). K5 = 1 indicates normal current, with K1 > K2 > K3 > K4 > K5. The worse the signal quality, the higher the current. The current strength coefficient is the proportional coefficient of the current corresponding to different signal strengths tested during R&D relative to the current at the best signal quality. The current strength coefficient can be calibrated for each signal strength range using an RF shielding box. It is an empirical value and serves as a default constant. For simplicity of calculation, the transmit and receive current strengths use the same coefficients by default for simple estimation of the communication module's power consumption. The default current intensity coefficient is 20% increments, that is, K = [K1, K2, K3, K4, K5] = [2.1, 1.7, 1.4, 1.2, 1.0]. After coefficient compensation, I TXN =I TX ×K,I RXN =I RX ×K,Q COMnew =(T TX ×I TXN +T RX ×I RXN )÷3600, where I TXN is the average current of the transmission operation after coefficient compensation, I RXN It is the average current of receiving operation after coefficient compensation.

[0047] Step 4: Based on the power consumption Q of the communication module COMnew Update battery charge percentage SOC BAT Specifically: First, the power consumption of the communication module Q COMnew The accumulated power consumption value Q added to the communication module COM Then update the past power consumption Q CON , Q CON =I Q ×ΔT+Q COM ;Last updated battery charge percentage SOC BAT , SOC BAT =(Q BAT -Q CON )÷Q BAT .

[0048] Taking into account the battery's self-discharge attenuation and the deviation of power calculation, the effective battery power Q BAT =Q Rating ×M, where Q Ratingis the rated capacity of the battery, M is the margin factor, the value range is 85%-95%, and the default is 90%.

[0049] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for judging and predicting the battery level of an IOT stand-alone smoke detector, characterized in that The following steps are involved: Step 1: Before turning on the communication module each time, the smoke detector enters the power judgment and prediction process and updates the battery power percentage SOC BAT ; Step 2: Collect ambient temperature T AMB and the battery voltage V BAT , and combined with the battery charge percentage SOC BAT Determine whether the communication module is turned on; if so, proceed to step 3, otherwise return to data acquisition; Step 3: Turn on the communication module and calculate the power consumption Q of this communication module COMnew ; Step 4: Based on the power consumption Q of the communication module COMnew Update battery charge percentage SOC BAT ;The battery used in the smoke detector is a disposable lithium battery; The step 2 comprises the following steps: Step 2-1: Collect ambient temperature T AMB And battery voltage information V BAT If the battery charge percentage SOC BAT If ≤10%, the communication module will not be turned on and steps 2-5 will be executed; otherwise, step 2-2 will be executed. Step 2-2, if V BAT ≥V TH , then the communication module is turned on and steps 2-5 are executed, otherwise steps 2-3 are executed; where V TH is the threshold voltage, which is between 2.6V and 2.7V; Step 2-3, if T AMB ≥-10℃, then the communication module will not be turned on and steps 2-5 will be executed; otherwise, step 2-4 will be executed; Step 2-4: If -20℃≤T AMB <-10℃ and SOC BAT ≥20%, the communication module is turned on and steps 2-5 are executed; otherwise, the communication module is not turned on and steps 2-5 are executed; Step 2-5: Based on the result of determining whether the communication module is turned on, if yes, proceed to step 3; otherwise, return to data collection in the periodic data collection mode; The power consumption of this communication module is Q COMnew Specifically: Assume that the sending working time of the communication module is T TX , the unit is s; the average current of the sending operation is I TX , the unit is mA; the receiving working time is T RX , the unit is s; the average current of receiving operation is I RX , the unit is mA; then the power consumption of this communication module is Q COMnew =(T TX × I TX + T RX × I RX )÷3600, the unit is mAh.

2. The method for determining and predicting battery charge level of an IOT stand-alone smoke detector according to claim 1, wherein: In step 1, the battery capacity percentage SOC is updated BAT Specifically: First update the past power consumption Q CON , Q CON = I Q × ΔT + Q COM , where I Q is the static average current of the smoke detector, that is, the average current in the periodic data acquisition mode, ΔT is the cumulative working time of the smoke detector, Q COM The accumulated power consumption of the smoke detector's communication module is updated with the battery power percentage SOC. BAT , SOC BAT = ( Q BAT -Q CON ) ÷Q BAT , where Q BAT The effective battery level.

3. The method for determining and predicting the battery level of an IOT stand-alone smoke detector according to claim 1, wherein: Assuming that the signal quality of the communication module is divided into five levels according to the signal strength, the corresponding current intensity coefficient K=[K l ,K2,K3,K4,K5], then I TXN =I TX ×K,I RXN = I RX ×K,Q COMnew =(T TX ×I TXN +T RX ×I RXN )÷3600, where I TXN is the average current of the transmission operation after coefficient compensation, I RXN It is the average current of receiving operation after coefficient compensation.

4. The method for determining and predicting battery charge level of an IOT stand-alone smoke detector according to claim 2, wherein: In step 4, the power consumption Q of the communication module is calculated based on the power consumption Q of the communication module. COMnew Update battery charge percentage SOC BAT Specifically: First, the power consumption of the communication module Q COMnew The accumulated power consumption value Q added to the communication module COM middle; Then update the past power consumption Q CON , Q CON =I Q ×∆T + Q COM ;Last updated battery charge percentage SOC BAT , SOC BAT =(Q BAT -Q CON )÷Q BAT .

5. The method for determining and predicting battery charge level of an IOT stand-alone smoke detector according to claim 4, wherein: The effective battery capacity Q BAT = Q Rating ×M, where Q Rating is the rated capacity of the battery, and M is the margin coefficient, which ranges from 85% to 95%.

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