Automatic power saving mode battery pack

Abstract

The present invention relates to an automatic power-saving mode switching battery pack capable of reducing unnecessary power consumption and minimizing the self-discharge rate to extend the effective life of a battery by detecting whether the equipment is operating and the current flow status, and automatically switching to standby or power-saving mode when use is stopped. The present invention may include a status detection sensor that detects whether the equipment is operating and the current flow status, and a power control unit that collects status data from the status detection sensor and cuts off the power to the battery or switches to standby mode or power-saving mode.

Description

Technology Field

[0001] The present invention relates to an automatic power saving mode switching battery pack, and more specifically, to an automatic power saving mode switching battery pack that detects whether equipment is operating and the current flow status, and automatically switches to standby or power saving mode when use is stopped, thereby reducing unnecessary power consumption and minimizing the self-discharge rate to extend the effective life of the battery. Background Technology

[0002] Various electronic devices and industrial equipment utilize battery packs as their primary power source; however, unnecessary power consumption occurs if users fail to disconnect the power or if the equipment is not used for extended periods. This unnecessary energy consumption reduces device efficiency and shortens the overall lifespan of the battery.

[0003] Conventional battery packs continuously experience a certain level of self-discharge while connected to equipment, which leads to battery performance degradation and stored energy loss when not in use for extended periods. Existing battery packs lack the ability to actively respond to this self-discharge problem.

[0004] While some Battery Management Systems (BMS) provide overcharge and over-discharge protection, intelligent control functions that cut off unnecessary standby power or switch to power-saving mode when equipment is not in use are not sufficiently implemented. As a result, unnecessary energy waste still occurs.

[0005] Since the operating environment of a battery pack varies depending on diverse current load characteristics and equipment operation patterns, an algorithm capable of automatically determining the power-saving mode according to the situation is required. Existing systems often require users to manually cut off the power or input separate external control signals, resulting in poor user convenience.

[0006] Therefore, a structure is required in which the battery pack can independently detect the equipment's operation status and current flow, and automatically switch between standby and power-saving modes depending on given conditions. This necessitates a new technical solution capable of preventing unnecessary energy loss, minimizing self-discharge rates, and extending the battery's effective lifespan. Prior art literature

[0007] Korean Patent Publication No. 10-2011-0133127 (December 12, 2011) The problem to be solved

[0008] Accordingly, the present invention has been developed to solve the aforementioned problems, and the purpose of the present invention is to provide an automatic power saving mode switching battery pack that can reduce unnecessary power consumption and minimize the self-discharge rate to extend the effective life of the battery by detecting the operation status and current flow status of the equipment and automatically switching to standby or power saving mode when use is stopped.

[0009] In addition, another objective of the present invention is to provide an automatic power-saving mode switching battery pack that can extend the effective life of the battery, delay the overall battery replacement cycle, reduce maintenance costs, and enable eco-friendly energy management.

[0010] Other objects of the present invention will become more apparent through the embodiments described below. means of solving the problem

[0011] An automatic power saving mode switching battery pack according to one embodiment of the present invention may include a state detection sensor that detects whether the equipment is operating and the current flow status, and a power control unit that collects state data from the state detection sensor and cuts off the power of the battery or switches to standby mode or power saving mode.

[0012] Additionally, the state detection sensor includes a current detection sensor, a voltage detection sensor, and an equipment operation detection sensor, and the power control unit determines whether to cut off the battery power, switch to standby mode, or switch to power saving mode by combining the state data of the current detection sensor, the voltage detection sensor, and the equipment operation detection sensor. The battery power is cut off when the voltage detection sensor detects the battery voltage below a predetermined threshold while current is not detected by the current detection sensor and there is no operation signal from the equipment operation detection sensor; the system switches to standby mode when current flow is detected below a predetermined threshold while there is no operation signal from the equipment operation detection sensor; and the system switches to power saving mode when the state in which current is not detected by the current detection sensor and there is no operation signal from the equipment operation detection sensor persists for a predetermined period of time or longer, and the battery voltage is detected within a normal range by the voltage detection sensor.

[0013] In addition, the power control unit further includes a detection cycle control circuit that variably controls the detection cycle of a current detection sensor, a voltage detection sensor, and an equipment operation detection sensor, and a temperature correction circuit for correcting the analog signals of the current detection sensor, the voltage detection sensor, and the equipment operation detection sensor in real time. The detection cycle control circuit extends the detection cycle as the remaining capacity of the battery decreases and shortens the detection cycle when a vibration signal is detected from the equipment operation detection sensor, and the temperature correction circuit dynamically corrects the resistance value of the current detection sensor and the reference potential of the voltage detection sensor according to the internal temperature change of the battery pack.

[0014] Additionally, the system further includes a non-volatile monitoring memory unit connected to a power control unit, which stores detection history data of each sensor and records the pattern of change in detection values ​​of each sensor, and prioritizes the output of a power saving switching signal corresponding to the power saving condition when the same power saving condition occurs repeatedly. The non-volatile monitoring memory unit applies weighted importance to detection history data over time by progressively reducing the reference weight of the detection history data as the recording time of the stored detection value elapses, in order to prioritize the reflection of the most recent detection history data among the detection history data of each sensor. It also adjusts the output priority of the power saving switching signal in multiple stages according to the frequency of occurrence of each power saving condition, the detection duration, and the remaining battery level. The multi-stage adjustment may be characterized by using an analog comparison circuit to lower the output threshold of the power saving switching signal as the remaining battery level decreases.

[0015] In addition, the power control unit calculates an idle consistency index, which is a quantified indicator of how consistently the equipment maintains an idle state, by combining the ratio of equipment operation detected in a certain observation period, the coefficient of variability of the current detection signal, and the normalized value of the battery average voltage; if the idle consistency index is below or above a preset idle threshold, it determines the transition to standby mode or power saving mode; the ratio of equipment operation detected in a certain observation period is calculated by collecting signals indicating whether the equipment is operating from the operation detection sensor per unit time, setting a certain period as the observation period, and dividing the number of periods in which the collected operation signals indicate operation within the certain observation period by the total number of periods; the coefficient of variability of the current detection signal is calculated by collecting current values ​​from the current detection sensor per unit time, calculating the current average and standard deviation of the certain period, dividing the standard deviation by the average, multiplying by the sensitivity control coefficient of current variability, and converting it into a negative exponential function; and the normalized value of the battery average voltage is calculated by collecting voltage values ​​from the voltage detection sensor per unit time, calculating the voltage average of the certain period, and normalizing the voltage average by dividing it by the battery's reference voltage. It can be characterized.

[0016] In addition, the power control unit may calculate a short-term consumption rate index by taking a time-weighted sum of the difference values ​​of the increased current and dividing the result by the sum of the recovery time elapsed since the last current flow occurred and a stabilization constant, and multiplying the result by a temperature or load environment correction factor, and may be characterized by cutting off the battery power or switching to standby mode if the short-term consumption rate index exceeds a preset consumption rate threshold. Effects of the invention

[0017] The automatic power saving mode switching battery pack according to an embodiment of the present invention provides the following effects.

[0018] The present invention has the effect of reducing unnecessary power consumption and minimizing the self-discharge rate to extend the effective life of the battery by detecting whether the equipment is operating and the current flow status, and automatically switching to standby or power-saving mode when use is stopped.

[0019] The present invention has the effect of extending the effective life of a battery, thereby delaying the overall battery replacement cycle, reducing maintenance costs, and enabling eco-friendly energy management.

[0020] The effects of the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below. Brief explanation of the drawing

[0021] FIG. 1 is a schematic diagram illustrating an automatic power saving mode switching battery pack according to one embodiment of the present invention. FIG. 2 is a block diagram illustrating an automatic power saving mode switching battery pack according to an embodiment of the present invention. FIG. 3 is a block diagram illustrating an automatic power saving mode switching battery pack according to another embodiment of the present invention. Specific details for implementing the invention

[0022] Hereinafter, various embodiments are described in more detail with reference to the attached drawings. The embodiments described in this specification may be modified in various ways. Specific embodiments may be depicted in the drawings and described in detail in the detailed description. However, specific embodiments disclosed in the attached drawings are intended only to facilitate understanding of various embodiments. Accordingly, the technical concept is not limited by specific embodiments disclosed in the attached drawings, and it should be understood that it includes all equivalents or substitutions that fall within the spirit and scope of the invention.

[0023] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but these components are not limited by the aforementioned terms. The aforementioned terms are used solely for the purpose of distinguishing one component from another.

[0024] Functions related to artificial intelligence according to the present disclosure are operated through a processor and memory. The processor may be composed of one or more processors. In this case, the one or more processors may be general-purpose processors such as CPUs, APs, and DSPs (Digital Signal Processors), graphics-dedicated processors such as GPUs and VPUs (Vision Processing Units), or artificial intelligence-dedicated processors such as NPUs. The one or more processors control the processing of input data according to predefined operation rules or artificial intelligence models stored in memory. Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0025] The predefined rules of operation or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a basic artificial intelligence model is trained using a number of training data by a learning algorithm, thereby creating predefined rules of operation or artificial intelligence models configured to perform desired characteristics (or objectives). Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is executed, or it may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0026] An artificial intelligence model can be composed of multiple neural network layers. Each of the multiple neural network layers has multiple nodes and weight values, and performs neural network operations through calculations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, multiple weights can be updated so that the loss value or cost value obtained by the artificial intelligence model during the learning process is reduced or minimized. Additionally, to minimize the loss value or cost value, multiple weights can be updated in a direction that minimizes the gradient associated with the loss value or cost value. Artificial neural networks may include deep neural networks (DNNs), such as Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Restricted Boltzmann Machines (RBMs), Deep Belief Networks (DBNs), Bidirectional Recurrent Deep Neural Networks (BRDNNs), or Deep Q-Networks, but are not limited to the examples mentioned above.

[0027] A network is a network that serves as a transmission path for web pages; it may be a closed network such as a LAN (Local Area Network) or WAN (Wide Area Network), but it is desirable for it to be an open network such as the Internet. The Internet refers to a global open computer network structure that provides the TCP / IP protocol and various services existing at its upper layers, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), SNMP (Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service).

[0028] The terminal can be implemented in various forms. For example, the terminal described in this specification may be a mobile terminal such as a smartphone, tablet PC, PDA (Personal Digital Assistant), PMP (Portable Multimedia Player), or MP3 Player, as well as a fixed terminal such as a smart TV or desktop computer.

[0029] In this specification, terms such as “comprising” or “having” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. When a component is described as being “connected” or “connected” to another component, it should be understood that it may be directly connected to or connected to that other component, or that there may be other components in between. On the other hand, when a component is described as being “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

[0030] Meanwhile, a "module" or "part" for a component as used in this specification performs at least one function or operation. Furthermore, a "module" or "part" may perform a function or operation by hardware, software, or a combination of hardware and software. Additionally, a plurality of "modules" or a plurality of "parts," excluding a "module" or "part" that must be performed on specific hardware or on at least one processor, may be integrated into at least one module. A singular expression includes a plural expression unless the context clearly indicates otherwise.

[0031] In addition, power, power transmission, and control therefor for the following assembly configurations and embodiments, including "by control," follow conventional technology including terminals, applications, hardware control modules, etc., so they are omitted to avoid redundancy.

[0032] In addition, the operation embodiments and configurations described in a general manner without being explained in detail below follow the prior art and are omitted in order to focus on describing the purpose of the present invention and the resulting effects.

[0033] Furthermore, in describing the present invention, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the invention, such detailed description is abbreviated or omitted.

[0034] An automatic power saving mode switching battery pack according to embodiments of the present invention will be described in detail below with reference to FIGS. 1 to 3.

[0035] FIG. 1 is a schematic diagram illustrating an automatic power saving mode switching battery pack according to one embodiment of the present invention, and FIG. 2 is a block diagram for explaining an automatic power saving mode switching battery pack according to one embodiment of the present invention.

[0036] Referring to FIGS. 1 and 2, the automatic power saving mode switching battery pack (100) may include a state detection sensor (110) and a power control unit (120).

[0037] The status detection sensor (110) can comprehensively monitor the operating status and current flow of the equipment being operated by the automatic power saving mode switching battery pack (100). The status detection sensor (110) can detect in real time whether the equipment is actually operating, whether current is flowing, and the voltage is being maintained, and can provide reference information so that the power control unit (120) can select an appropriate power cutoff, standby mode, or power saving mode.

[0038] The state detection sensor (110) includes a current detection sensor (111), a voltage detection sensor (112), and an equipment operation detection sensor (113), and can convert the state data collected from each sensor into a single integrated data stream and transmit it to the power control unit (120). This configuration allows the battery state to be determined based on the interrelationship between multiple detection factors, rather than relying on the outlier value of a single variable.

[0039] The current sensing sensor (111) can detect whether and how much current is flowing from the automatic power saving mode switching battery pack (100) to the equipment, thereby providing a primary reference signal for power saving control. The current sensing sensor (111) is connected in series between the battery terminal and the input terminal of the equipment to detect the magnitude of the current by converting it into a voltage drop.

[0040] The current detection sensor (111) can determine the characteristics of the load by going beyond determining the presence or absence of current and by accumulating and analyzing the detected current pattern over a certain period of time. For example, the current detection sensor (111) can determine that if a specific current is repeated in a short period, it is a standby operation of the equipment, and if a no-current state persists for a long time, it can recognize it as a power saving condition.

[0041] The current sensing sensor (111) is linked with the temperature correction circuit (122) to automatically correct measurement errors caused by changes in resistance values. That is, the current sensing sensor (111) can maintain constant detection precision by dynamically adjusting the reference resistance value according to temperature to prevent the problem of the current sensing value being underestimated as the detection resistance increases as the internal temperature rises.

[0042] Additionally, the current sensing sensor (111) may include a noise filtering function to prevent short-term signals caused by instantaneous current spikes or electromagnetic interference from being mistaken for the actual load current. To this end, the current sensing sensor (111) may average the detected current signal over a certain sampling time to recognize only the current that persists above a certain standard as valid data.

[0043] The voltage detection sensor (112) can detect the terminal voltage of the automatic power saving mode switching battery pack (100) in real time to determine the remaining battery capacity, load status, and whether there is an abnormal voltage. The voltage detection sensor (112) can detect a voltage drop or an abnormal rise by setting a reference potential and continuously comparing the potential difference between the battery terminals. The voltage detection sensor (112) can determine whether to cut off the power by determining whether the battery voltage is detected to be below a predetermined threshold value at the time of switching to the power saving mode.

[0044] The voltage sensing sensor (112) is linked with the temperature correction circuit (122) to correct the reference potential so that it does not fluctuate according to temperature changes. For example, the voltage sensing sensor (112) can ensure the stability of the measurement value by dynamically correcting the internal reference potential to offset the phenomenon where the reference potential of the semiconductor device decreases when the temperature rises.

[0045] In one embodiment, the voltage detection sensor (112) can detect a short circuit, reverse current inflow, or abnormal charging state of the battery load. In this case, the voltage detection sensor (112) can store the detected voltage pattern in the non-volatile monitoring memory unit (230) described in FIG. 3 so that if the same voltage abnormality is repeated, the power control unit (120) can immediately perform a protection operation.

[0046] The equipment motion detection sensor (113) can detect whether the equipment is in physical motion and determine whether it is actually in use. The equipment motion detection sensor (113) can distinguish whether the equipment is in operation or in a stationary state by detecting vibration, acceleration, or position change of the equipment.

[0047] In the present invention, the equipment operation detection sensor (113) is not limited to a simple vibration detection sensor, but is configured to operate in a plurality of detection modes. For example, the equipment operation detection sensor (113) may recognize low-frequency vibrations as micro-vibrations while the equipment is stopped, and determine that the equipment is actually in operation if high-frequency vibrations persist for a certain period of time or longer.

[0048] The equipment motion detection sensor (113) can automatically adjust the detection frequency by linking with the detection cycle control circuit (121). The equipment motion detection sensor (113) can increase the response speed by detecting at a short cycle when the equipment is actively operating, and minimize unnecessary power consumption by increasing the detection cycle when the equipment is in a stationary state for a long time.

[0049] The equipment motion detection sensor (113) may include a reference sensitivity adjustment function that filters out vibrations below a certain level to prevent false detection caused by ambient vibrations or external shocks. Accordingly, the equipment motion detection sensor (113) can minimize the possibility of malfunction caused by environmental factors such as vehicle vibrations and external shocks.

[0050] The state detection sensor (110) may include an internal reference potential circuit for standardizing the signal output range of each sensor. The reference potential circuit converts the analog signal detected by each sensor into a digital signal to minimize noise interference and can correct detection errors that may occur due to disturbance factors such as temperature, electromagnetic interference, and contact resistance in real time.

[0051] Additionally, the state detection sensor (110) can automatically adjust the detection sensitivity according to the load characteristics of the equipment or the usage environment. For example, the state detection sensor (110) can prevent malfunction by automatically expanding the internal threshold range to ignore currents below the reference sensitivity when there is a minute current leakage while the equipment is in a stationary state.

[0052] The state detection sensor (110) can go beyond a simple current monitoring function and recognize the actual operating state of the equipment, the energy consumption trend of the battery, and the voltage maintenance characteristics in an integrated manner, thereby supporting the power control unit (120) to perform more precise power saving control.

[0053] The power control unit (120) can collect status data input from the status detection sensor (110) and make a comprehensive judgment to cut off the power of the battery or switch to standby mode or power saving mode.

[0054] The power control unit (120) can perform multi-stage power saving control based on the combination logic of the state data. The power control unit (120) can cut off the battery power according to the voltage level from the voltage detection sensor (112) when no current is detected from the current detection sensor (111) and no operation signal is received from the equipment operation detection sensor (113), that is, when the battery voltage is detected below a predetermined threshold value from the voltage detection sensor (112). Additionally, the power control unit (120) switches to standby mode when the current flow is detected below a predetermined threshold value from the current detection sensor (111) and no operation signal is received from the equipment operation detection sensor (113), and switches to power saving mode when the state in which no current is detected from the current detection sensor (111) and no operation signal is received from the equipment operation detection sensor (113) persists for a predetermined period of time or longer and the battery voltage is detected within a normal range from the voltage detection sensor (112).

[0055] The power control unit (120) may further include a detection cycle control circuit (121) and a temperature correction circuit (122). The power control unit (120) is connected to the detection cycle control circuit (121) and the temperature correction circuit (122) to correct the detection conditions of the sensor in real time according to the internal state of the battery and changes in the external environment. Through this, the power control unit (120) can increase the accuracy of the determination to enter power saving mode and prevent equipment malfunction caused by unnecessary power cutoff.

[0056] The detection cycle control circuit (121) can dynamically control the detection cycle of the current detection sensor (111), voltage detection sensor (112), and motion detection sensor (113). The detection cycle control circuit (121) can minimize the power consumption of the entire system by analyzing the remaining capacity of the battery and the operating status of the equipment in real time and efficiently adjusting the detection cycle. For example, the detection cycle control circuit (121) can reduce the number of sensor operations by extending the detection cycle as the remaining capacity of the battery decreases, and maintain fast responsiveness by shortening the detection cycle when a vibration signal is detected by the equipment motion detection sensor (113).

[0057] The detection cycle control circuit (121) internally includes a timer circuit and a comparison circuit, and can receive a detection cycle setting value from the power control unit (120) and adjust it in real time. In addition, the detection cycle control circuit (121) can apply an adaptive algorithm that compares the detection signal cycles of each sensor and automatically adjusts the detection cycle when the frequency of abnormal detection by a specific sensor increases.

[0058] The detection cycle control circuit (121) can monitor changes in state more accurately by temporarily shortening the detection cycle just before entering power saving mode, and minimize overall power consumption by lengthening the detection cycle after entering power saving mode.

[0059] The temperature correction circuit (122) can correct the analog signals of the current sensing sensor (111), voltage sensing sensor (112), and equipment operation sensing sensor (113) in real time according to the internal temperature fluctuation of the automatic power saving mode switching battery pack (100). The temperature correction circuit (122) can minimize measurement errors by correcting the resistance value of the current sensing sensor (111) and the reference potential of the voltage sensing sensor (112) in real time.

[0060] The temperature correction circuit (122) collects an internal temperature value from a temperature sensor (not shown) of the automatic power saving mode switching battery pack (100) and calculates a corresponding correction coefficient to minimize distortion of the detected value due to a rise or fall in temperature and maintain constant measurement accuracy.

[0061] In a high-temperature environment, the resistance of the current sensing sensor (111) may rise, causing the sensing current to be underestimated, and in a low-temperature environment, the reference potential of the voltage sensing sensor (112) may rise, causing the voltage sensing to be overestimated. Therefore, the temperature correction circuit (122) may have a mutual correction structure that corrects both of these phenomena simultaneously.

[0062] The temperature compensation circuit (122) can respond to rapid temperature fluctuations by applying not only a simple linear compensation method but also a non-linear compensation method based on the rate of temperature change.

[0063] The power control unit (120) can perform learning-type control by utilizing detection history data transmitted from the non-volatile monitoring memory unit (230) described in FIG. 3 to prioritize the reflection of power saving patterns under the same conditions when they are repeated. Through this, power saving mode switching logic optimized for the usage environment can be automatically established.

[0064] The power control unit (120) can calculate an idle consistency index, which is a numerical indicator of how consistently the equipment maintains an idle state. Since it is not possible to distinguish between momentary stoppage and continuous idleness based solely on no-current detection, and an index is required that reflects long-term idleness and voltage integrity by combining activity frequency, variability of current signals, and normality of voltage, the present invention can calculate an idle consistency index. That is, the idle consistency index is an indicator for quantitatively determining the inactive state of the equipment, and can be used to automatically determine the appropriate time for switching to power saving mode by comprehensively reflecting whether the equipment is operating, the stability of the current, and the level of normalization of the battery voltage.

[0065] The idle consistency index can be calculated by combining the ratio of equipment operation detected in a certain observation interval, the variability coefficient of the current detection signal, and the normalized value of the average battery voltage. The power control unit (120) can determine the transition to standby mode or power saving mode if the idle consistency index is below or above a preset idle threshold. The idle consistency index increases as the equipment operation ratio is low, current variability is small, and voltage is normal, thereby indicating the degree to which the equipment remains in a continuously idle state.

[0066] For example, the power control unit (120) can determine that the idle consistency index is 0.8 or higher, the state is a complete standby or power-saving suitable state, and switch to a power-saving mode; determine that the state is 0.5 or higher but less than 0.79, the state is an unstable standby state, and continue standby mode and fluctuation monitoring; determine that the state is 0.3 or higher but less than 0.49, the state is a load unstable or intermittent operation, and put on hold the power-saving mode; and maintain the power state in a clear active state when the index is less than 0.3.

[0067] The ratio of equipment operation detected within a certain observation period can be calculated by collecting signals indicating whether the equipment is operating per unit time from a motion detection sensor, setting a certain period as the observation period, and dividing the number of periods in which the collected signals indicate operation by the total number of periods. The operation signal can be output as 1 if the equipment is operating and 0 if it is not operating. The ratio of equipment operation detected within a certain observation period can indicate how much the equipment actually operated during the observation period. In other words, the lower the ratio of equipment operation detected within a certain observation period, the more likely it is to be in an idle state.

[0068] The variability coefficient of the current detection signal can be calculated by collecting current values ​​per unit time from the current detection sensor, determining the average and standard deviation of the current over a specific interval, dividing the standard deviation by the average, multiplying by the sensitivity control coefficient of the current variability, and converting the result into a negative exponential function. Since a smaller value for the variability coefficient of the current detection signal indicates that the current is being maintained at a constant level, it can be determined that the equipment is likely to be stopped or in an idle state. The sensitivity control coefficient of the current variability can be calculated by dividing the average value of the variability coefficients measured in the most recent observation interval by the system-configured reference variability coefficient and multiplying by a correction coefficient specific to the usage mode. The system-configured reference variability coefficient can be set by averaging the current variability coefficients measured in various past operating modes. For example, the correction coefficient specific to the usage mode can be adjusted to respond more sensitively to equipment with smaller current fluctuations, and can be set to 0.8 for power saving priority mode and 1.0 for general mode.

[0069] The normalized value of the average battery voltage can be calculated by collecting voltage values ​​from a voltage sensing sensor at a unit time interval, determining the average voltage over a certain interval, and normalizing the voltage average by dividing it by the battery's reference voltage.

[0070] Various examples of calculating idle consistency metrics are as follows.

[0071] Examples Equipment operation rate Current variability coefficient Sensitivity coefficient Voltage normalized value Idle consistency indicator Evaluation results Example 1 0.10 0.20 0.3 0.98 0.871 stable atmosphere Example 2 0.05 0.10 0.2 0.99 0.902 Conditions for entering power saving mode are met Example 3 0.40 0.25 0.3 0.97 0.612 Need to maintain standby Example 4 0.20 0.50 0.4 0.95 0.444 Power saving mode delay required Example 5 0.80 0.10 0.2 1.00 0.180 Disable power saving mode (maintain normal operation)

[0072] Comparing Examples 1 and 2, the equipment operation ratio and current variability coefficient decreased, resulting in an increase in the idle consistency index; this can be interpreted as the equipment being stable and having low current fluctuations, thus approaching power saving conditions. Comparing Examples 2 and 3, the equipment operation ratio and current variability coefficient increased, resulting in a decrease in the idle consistency index; this can be interpreted as the equipment operation being detected intermittently, thereby delaying entry into power saving. Comparing Examples 3 and 4, the current variability coefficient increased, resulting in a decrease in the idle consistency index; this can be interpreted as the need for a delay in power saving due to load instability being detected. Comparing Examples 4 and 5, the idle consistency index decreased as the equipment operation rate increased, which can be interpreted as meaning that the equipment is in an active state and requires a ban on switching to power-saving mode. Since the idle consistency index is calculated by integrating multiple data of current, voltage, and operation detection rather than using a single current threshold method, the probability of misjudgment regarding environmental noise (temperature, noise, load deviation, etc.) can be significantly reduced. Furthermore, the equipment operation rate and the current variability coefficient are calculated as statistics sampled in real-time within a specific observation interval (e.g., 60-second intervals), so they are based on actual measurement data rather than arbitrary values. Additionally, the sensitivity control coefficient for current variability is an empirical coefficient calculated through regression analysis by measuring the frequency of mode switching according to current fluctuations, thus proving that it is a valid variable based on experimental data. In other words, the idle consistency index is a quantitative indicator based on sensor measurement, and each variable is a physical quantity that can be actually measured; therefore, this mathematical formula can be proven to be a statistical judgment formula verified by actual measurement data rather than an arbitrarily created theoretical formula.

[0073] According to the present embodiment, unlike the conventional method that simply considers the moment when the current value becomes zero as the power saving condition, the timing of when the actual equipment switches to an idle state can be determined without misjudgment by considering the operation frequency, current variability, and voltage status together. Furthermore, by switching to a power saving mode only when the idle consistency index value is above a certain threshold, unnecessary power cutoff caused by malfunction or sensor noise can be prevented and battery consumption during standby can be minimized. Additionally, since it reflects relative changes in current, voltage, and operation signals, power saving control can be performed by flexibly responding to external environmental factors such as equipment load conditions, temperature changes, and battery aging.

[0074] The selection of individual variables for calculating the idle consistency indicator described above has the following specific background and reasons, which supports the fact that the present invention is a systematic approach rather than a simple combination of data.

[0075] Ratio of equipment operation detected within a specific observation interval: Determining how frequently equipment actually operates within a specific interval is the most intuitive indicator for evaluating the actual idleness of a system. If one judges only the state of having no momentary operation signal, there is a risk of misidentifying situations where the equipment operates intermittently (e.g., periodic control, sensor updates, etc.) as inactive. Therefore, calculating and averaging the ratio of the time during which operation is detected within a specific observation interval (e.g., 60 seconds) allows for the temporal stabilization of the equipment's actual operating pattern, thereby eliminating the influence of transient noise or errors. A lower ratio of equipment operation detected within an observation interval clearly reflects the equipment's actual stopped state, leading to more accurate timing for switching to power-saving mode. Furthermore, time-based averaging improves tolerance to transient signal anomalies (such as sensor spikes or load vibrations), which consequently increases the reliability of the idle state when calculating idle consistency metrics.

[0076] Coefficient of Variability of Current Sensing Signals: If the power-saving state is determined solely based on the absolute value of the current, there is a problem where the system overreacts to minute current fluctuations caused by noise or load changes. The coefficient of current variability is a statistical measure representing the relative variability of the current, calculated by dividing the standard deviation of the current signal by its mean. Since this value can objectively reflect load instability, vibration, or sensor noise, it can be used as a basis for quantitatively adjusting the sensitivity of power-saving judgments. A higher coefficient of current variability indicates that the system is in an unstable state, delaying entry into power-saving mode; conversely, a lower coefficient indicates that the system is recognized as a stable idle state, facilitating entry into power-saving mode. This significantly reduces the rate of false judgments regarding power-saving mode, and by using the coefficient of current variability together with a sensitivity adjustment factor, individually optimized control tailored to the current characteristics of each piece of equipment (load size, operating cycle, etc.) becomes possible.

[0077] Normalized Value of Average Battery Voltage: The battery's remaining capacity or voltage status is a key indicator reflecting the equipment's actual power state. Even under the same current conditions, if the battery voltage drops, the equipment may temporarily interrupt the current supply or perform controls to prevent overcurrents. Therefore, by normalizing and reflecting voltage stability along with the current status when determining power saving, the overall state of the power system can be evaluated more accurately. Normalization eliminates the influence of absolute value fluctuations caused by battery aging or temperature by dividing the current voltage by a reference voltage. Since a normalized value of the average battery voltage closer to 1 indicates a normal voltage state, it can be used as an energy stability indicator when determining conditions for entering power saving mode. Furthermore, by temporarily delaying the transition to power saving mode during voltage drop periods, it can prevent data loss or component damage caused by power cutoff in unstable conditions.

[0078] The power control unit (120) can calculate a short-term consumption rate index by taking a time-weighted sum of the difference values ​​of the increased current and dividing the result by the sum of the recovery time elapsed since the last current flow occurred and the stabilization constant, and then multiplying the result by a temperature or load environment correction factor. Since the accumulation of instantaneous current spikes affects the battery voltage and SOC (State of Charge), the power control unit (120) can calculate a short-term consumption rate index by summing the frequency and magnitude of the current spikes into a single value to reflect in the power cutoff and standby judgment.

[0079] For example, the power control unit (120) can operate normally with a low risk of short-term consumption when the short-term consumption rate indicator is less than 0.01, increase monitoring in standby mode in the observation stage when it is 0.01 or more but less than 0.1, recommend load distribution and output limiting in standby mode in the caution stage when it is 0.1 or more but less than 0.5, and control power cutoff, alarm, and safety mode in the stage requiring immediate response when it is 0.5 or more.

[0080] The difference value of the increase in current can be collected by recording only the positive values ​​of the increase in current from time t to time t+1 in the continuous current sample time series and treating the negative values ​​as 0. For example, when the continuous current sample time series is [0.10, 0.12, 0.11, 0.50, 0.45] A, the power control unit (120) can store only the positive values ​​[0.02, 0, 0.39, 0] among the differences [―, 0.02, -0.01, 0.39, -0.05].

[0081] The time weights applied to each positive difference value can be calculated by comparing the occurrence time of each event with the current time from current time series and timestamp data to determine the elapsed time of the event, and by converting the elapsed time of the event into a negative exponential function, higher values ​​can be set for more recent events.

[0082] The recovery time elapsed since the last current flow occurred is calculated by subtracting the last time when the current was measured to be at or above a significant current threshold of 0.01A from the current time series and timestamp data from the current time, and a larger value can lower the value of the short-term consumption rate indicator. In other words, if recent current activity is low, the short-term consumption rate indicator can be lowered.

[0083] The stabilization constant can be secured as a minimum value to prevent the denominator from becoming zero, and can be set by considering the sampling period for collecting sensor data and event statistics (median, etc.). Excessive sensitivity or insensitivity can be prevented by adjusting the stabilization constant according to the operating environment. For example, the stabilization constant can simply be fixed to a predetermined small positive value of 1.

[0084] A temperature or load environment correction factor can be calculated by subtracting a reference temperature (e.g., 25 degrees) from the temperature measured by a temperature sensor (not shown) and multiplying the result by an experimentally determined temperature factor (e.g., 0.01) and adding 1, and by calculating a load correction factor by subtracting a reference load (e.g., 1A) from the system load level and multiplying the result by an experimentally determined load factor (e.g., 0.05) and adding 1. The temperature or load environment correction factor is calculated as the sum of the temperature correction factor and the load correction factor, and if it is greater than 1, the short-term consumption rate indicator may increase due to the correction. For example, if the temperature or load environment correction factor is greater than 1, it may reflect that the consumption effect is significant due to increased internal resistance at high temperatures.

[0085] Various examples of calculating short-term consumption rate indicators are as follows.

[0086] Examples Event(positive difference value, elapsed time) Each event time weight Weighted sum (A) Recovery time(s) Stabilization constant Temperature or load environment correction factor Short-term consumption rate indicator Example 1 0.02(10s), 0.01(30s) 0.3679, 0.0498 0.00786 10 1 1.00 (T=25°C) 0.000714 Example 2 0.50(2s), 0.20(8s), 0.10(20s) 0.8187, 0.4493, 0.1353 0.51276 2 1 1.05 (T=30°C) 0.17947 Example 3 0.05(1s), 0.05(3s), 0.05(5s), 0.05(7s), 0.05(9s) 0.9048, 0.7408, 0.6065, 0.4966, 0.4066 0.15777 1 1 1.15 (T=40°C) 0.09072 Example 4 2.0(60s) 0.00248 0.00496 60 1 1.00 (T=25°C) 0.0000813 Example 5 1.0(0.5s), 0.8(2s), 0.4(5s) 0.9512, 0.8187, 0.6065 1.84883 0.5 1 1.20 (T=45°C) 1.47906

[0087] Example 1 has only minor spikes in the past and a short-term consumption rate indicator that is negligible, and it has the effect of maintaining stable standby and reducing malfunctions by avoiding unnecessary power saving and shutdown. Example 2 has frequent large current rises recently, requiring immediate monitoring and load limiting recommendations, output limiting or notifications when necessary, and has the effect of preventing voltage drop due to rapid consumption, protecting the system, and improving safety.

[0088] Example 3 recommends suppressing excessive power saving entry and shortening the monitoring cycle in a state where frequent small increases have accumulated, and has the effect of reducing errors and data loss through accumulated transient management.

[0089] Example 4 has the effect of maintaining normal operation by suppressing unnecessary emergency response, as a major event occurred a long time ago and has little impact now.

[0090] Example 5 is effective in preventing battery damage and system failure, and enabling the implementation of emergency charging and power saving policies, as well as reflecting high temperature correction and taking immediate load cutoff and safety measures, and reflecting high temperature correction, when large-scale events occur frequently in succession recently.

[0091] It can be demonstrated that while a simple absolute current value criterion misinterprets instantaneous spikes and noise, the short-term consumption rate metric reflects spike magnitude, timing (recency), cumulative nature, and environmental conditions to more accurately identify actual risks. Furthermore, as demonstrated in the embodiments, it can be proven that system availability (uptime) is improved by automatically ignoring old events or minor fluctuations to reduce unnecessary shutdowns. Additionally, applying load balancing or delayed power saving / shutdown policies based on the short-term consumption rate metric can quantitatively demonstrate the effect of extending battery life by reducing power loss and battery degradation (cycle damage) caused by unnecessary repetitive power on / off cycles. Moreover, reproducibility can be claimed by showing that the same risk level can be determined under various temperature and load conditions by correcting for temperature or load environment correction factors and time weights using regression analysis and field data. Finally, monitoring the long-term trend of the short-term consumption rate metric allows for the early detection of repetitive and increasing transient patterns, enabling the pre-detection of defects such as component abnormalities and poor wiring contacts.

[0092] The short-term consumption rate indicator uses actual measured values ​​of current time series, event timestamps, and field temperatures as raw data. The parameters are derived and calculated through experimental calibration (lab and field tests and regression analysis), proving that it is a judgment formula with reproducible and statistical grounds, rather than being arbitrarily generated.

[0093] According to the present embodiment, the short-term consumption rate indicator is calculated by reflecting the current change pattern during a certain time interval with time weights and environmental correction coefficients, thereby having the effect of early detection of abnormal power consumption of the equipment, unstable state due to sudden load surges, and degradation or overload response of the battery cell. Through the short-term consumption rate indicator, the battery pack (100) detects short-term rapid current events in real time, and when necessary, the power control unit (120) switches to automatic power saving, cutoff, or load redistribution mode, thereby simultaneously obtaining the effect of extending the battery life and ensuring equipment stability.

[0094] The selection of individual variables for calculating the above short-term consumption rate indicator is based on the following specific background and reasons, which supports the fact that the present invention is a systematic approach rather than a simple combination of data.

[0095] Positive difference value of increased current: Instantaneous surges in current serve as direct indicators of equipment load fluctuations, motor start-ups, and control circuit malfunctions. By calculating this as a positive difference, the change in the direction of current increase can be quantified. In other words, unlike the stable current in normal ranges, this is intended to distinguish whether there is a short-term load surge by extracting only the sudden increase pattern. The positive difference value of increased current reduces the influence of noise by eliminating unnecessary negative changes (decrease periods) and improves the accuracy of abnormal event detection by detecting only the actual surge period.

[0096] Temporal Weighting: The importance of current spike events varies over time. Since recent spikes more directly reflect the current system state, exponentially decaying weights were applied to give greater weight to recent data. For example, the impact of older spikes is naturally allowed to diminish. By increasing detection sensitivity for temporally closer events, real-time responsiveness and preemptive anomaly detection can be ensured. Additionally, this prevents false positives caused by noise accumulated over long periods.

[0097] Recovery time elapsed since the last current flow: Load recovery performance is evaluated by measuring the time it takes for the current to return to a stable state after the current surge. Even with the same current surge, a system with faster recovery is stable, whereas if recovery is delayed, there is a high possibility of thermal or electrical abnormalities. By reflecting recovery time data, not only the magnitude of the current but also the resilience of the battery pack (100) can be evaluated simultaneously. This is effective for diagnosing the condition of the battery and evaluating load stability.

[0098] Stabilization Constant: If the recovery time is very short or a value close to zero appears due to measurement noise, the denominator of the calculation formula may converge to zero, potentially causing errors. To prevent this, a stabilization constant has been introduced. Additionally, the stabilization constant is a coefficient that can be experimentally corrected based on environmental and equipment characteristics. By ensuring the numerical stability of the formula, errors or unstable results can be prevented even in real-time computation environments, and calculation reliability is improved.

[0099] Temperature or Load Environment Correction Factors: Current consumption patterns are sensitive to external environmental factors such as temperature, humidity, and load resistance. For example, high temperatures can lead to a temporary increase in current due to a decrease in internal resistance. Therefore, the influence of external environments is normalized by multiplying by temperature or load correction terms. This filters out unintended current fluctuations caused by ambient temperature or changes in load conditions, enabling the calculation of precise indicators that reflect only the actual operating state of the equipment. Consequently, false positive rates are reduced, and diagnostic reliability is improved.

[0100] The short-term consumption rate indicator enables much more precise status assessment than conventional single-current monitoring methods by simultaneously considering not only changes in current magnitude but also temporal occurrence patterns, recovery performance, and environmental correction factors. Therefore, the short-term consumption rate indicator can be utilized as a key decision factor for current-sensing-based automatic power saving systems, battery management systems (BMS), or anomaly detection algorithms. Furthermore, since it is composed of measurable variables based on collected data, it can be objectively asserted that it is a model based on valid physical quantities rather than an arbitrarily created formula.

[0101] FIG. 3 is a block diagram illustrating an automatic power saving mode switching battery pack according to another embodiment of the present invention.

[0102] Referring to FIG. 3, the automatic power saving mode switching battery pack (200) according to the present embodiment may include a state detection sensor (210), a power control unit (220), and a non-volatile monitoring memory unit (230). Since the state detection sensor (210) and the power control unit (220) are identical in configuration to the state detection sensor (110) and the power control unit (120) described in FIG. 1 and FIG. 2, a detailed description is omitted.

[0103] The non-volatile monitoring memory unit (230) is connected to the power control unit (220) to store detection history data collected from the current detection sensor (211), voltage detection sensor (212) and equipment operation detection sensor (213), and to record the detection value fluctuation pattern of each sensor so that when the same power saving condition occurs repeatedly, a power saving switching signal corresponding to the power saving condition can be output preferentially.

[0104] The non-volatile monitoring memory unit (230) can improve the power saving response speed by prioritizing the output of a power saving switching signal corresponding to the condition when the power saving condition is repeated identically.

[0105] The non-volatile monitoring memory unit (230) may apply a weighted decay algorithm that gradually reduces the reference weight as the recording time of the stored data elapses, in order to increase the reliability of the recent detection history. That is, the non-volatile monitoring memory unit (230) may apply a weighted decay algorithm that gradually reduces the reference weight of the detection history data as the recording time of the stored detection value elapses, in order to prioritize the reflection of the recent detection history data among the detection history data of each sensor. Through this, the non-volatile monitoring memory unit (230) can prioritize the reflection of the latest status information and prevent misjudgment caused by old data.

[0106] Additionally, the non-volatile monitoring memory unit (230) can adjust the priority of the power saving switching signal in multiple stages by comprehensively considering the frequency of occurrence of power saving conditions, the duration of detection, and the remaining battery level. For example, the non-volatile monitoring memory unit (230) can use an analog comparison circuit to lower the threshold of the power saving switching signal as the remaining battery level decreases, thereby allowing the device to switch to power saving mode more quickly.

[0107] As a result, the non-volatile monitoring memory unit (230) can function as an intelligent memory module that learns past detection patterns and reflects them in control logic, rather than being a simple data storage unit.

[0108] Although the present invention has been described above with reference to one embodiment, those skilled in the art will understand that various modifications and changes can be made to the invention without departing from the spirit and scope of the invention as described in the following claims. Explanation of the symbols

[0109] 100, 200: Automatic power saving mode switching battery pack 110, 210: Status detection sensors 120, 220: Power control unit 230: Non-volatile monitoring memory section

Claims

Claim 1 An automatic power saving mode switching battery pack comprising: a state detection sensor that detects whether equipment is operating and the current flow status; and a power control unit that collects state data from the state detection sensor and cuts off the battery power or switches to standby mode or power saving mode, wherein the state detection sensor includes a current detection sensor, a voltage detection sensor, and an equipment operation detection sensor, and the power control unit determines whether to cut off the battery power, switch to standby mode, or switch to power saving mode by combining the state data of the current detection sensor, the voltage detection sensor, and the equipment operation detection sensor, wherein the battery power is cut off when the current is not detected by the current detection sensor and there is no operation signal from the equipment operation detection sensor, and the battery voltage is detected by the voltage detection sensor to be below a predetermined threshold value; the battery is switched to standby mode when the current flow is detected by the current detection sensor to be below a predetermined threshold value and there is no operation signal from the equipment operation detection sensor; and the battery is switched to power saving mode when the current is not detected by the current detection sensor and there is no operation signal from the equipment operation detection sensor for a period of time or longer, and the battery voltage is detected by the voltage detection sensor to be within a normal range. Claim 2 delete Claim 3 The battery pack for automatic power saving mode switching according to claim 1, wherein the power control unit further comprises a detection cycle control circuit for variably controlling the detection cycle of the current detection sensor, the voltage detection sensor, and the equipment operation detection sensor, and a temperature correction circuit for correcting the analog signals of the current detection sensor, the voltage detection sensor, and the equipment operation detection sensor in real time, wherein the detection cycle control circuit extends the detection cycle as the remaining capacity of the battery decreases and shortens the detection cycle when a vibration signal is detected from the equipment operation detection sensor, and the temperature correction circuit dynamically corrects the resistance value of the current detection sensor and the reference potential of the voltage detection sensor according to the internal temperature change of the battery pack. Claim 4 The automatic power saving mode switching battery pack according to claim 1, further comprising a non-volatile monitoring memory unit connected to the power control unit, storing detection history data of each sensor and recording the detection value fluctuation pattern of each sensor, and prioritizing the output of a power saving switching signal corresponding to the power saving condition when the same power saving condition occurs repeatedly; wherein the non-volatile monitoring memory unit applies weighted importance to the detection history data over time by progressively decreasing the reference weight of the detection history data as the recording time of the stored detection value elapses in order to prioritize the reflection of the most recent detection history data among the detection history data of each sensor, and adjusts the output priority of the power saving switching signal in multiple stages according to the frequency of occurrence of each power saving condition, the detection duration, and the remaining battery amount, and wherein the multi-stage adjustment is characterized by using an analog comparison circuit to lower the output threshold of the power saving switching signal as the remaining battery amount is lower. Claim 5 In claim 1, the power control unit calculates an idle consistency index, which is a numerical indicator of how consistently the equipment maintains an idle state, by combining the ratio of equipment operation detected in a certain observation period, the coefficient of variability of the current detection signal, and the normalized value of the battery average voltage; and determines a transition to standby mode or power saving mode when the idle consistency index is below or above a preset idle threshold; the ratio of equipment operation detected in the certain observation period is calculated by collecting a signal indicating whether the equipment is operating from the operation detection sensor per unit time, setting a certain period as the observation period, and dividing the number of periods in which the collected operation signal indicates operation within the certain observation period by the total number of periods; the coefficient of variability of the current detection signal is calculated by collecting current values ​​from the current detection sensor per unit time, calculating the current average and standard deviation of the certain period, dividing the standard deviation by the average, multiplying by a sensitivity control coefficient for current variability, and converting to a negative exponential function; and the normalized value of the battery average voltage is calculated by collecting voltage values ​​from the voltage detection sensor per unit time, calculating the voltage average of the certain period, and the voltage average An automatic power saving mode switching battery pack characterized by calculating the result by dividing by the battery's reference voltage and normalizing it. Claim 6 An automatic power saving mode switching battery pack, wherein, in claim 1, the power control unit calculates a short-term consumption rate index by multiplying a value obtained by a time-weighted sum of the difference values ​​of the increased current and the sum of the recovery time elapsed since the last current flow occurred and a stabilization constant by a temperature or load environment correction coefficient, and cuts off the battery power or switches to standby mode when the short-term consumption rate index exceeds a preset consumption rate threshold.

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