State of health determination of a battery

Abstract

The present disclosure relates to state of health determination of a battery. A computer-implemented method for improved determination of state of health (SoH) of a device battery can include determining that the device is in a charging state such that a charge of the battery is increased during a charging process; determining that a state of charge (SoC) metric of the battery reported by a battery metering system is increased by a fixed SoC interval; determining a charging time interval in which the SoC metric of the battery has been increased by the fixed SoC interval; and determining a SoH metric indicative of a SoH of the battery based at least in part on the charging time interval; wherein determining the SoH metric is based at least in part on a known relationship between a reference time interval representative of a time required to increase a reference battery by the fixed SoC interval at a full SoH and the charging time interval.

Description

Technical Field

[0001] This disclosure generally relates to determining the health status of a battery. More specifically, this disclosure relates to battery-powered devices, such as wearable devices with improved determination of battery health status. Background Technology

[0002] Rechargeable batteries can be charged to power electronic devices, such as wearable devices. The performance of rechargeable batteries tends to degrade over time, partly due to time (e.g., calendar life) and / or usage (e.g., cycle life). Because of these factors, monitoring the extent of performance degradation of a given battery can be challenging. This can be especially problematic for electronic devices that have been stored for a considerable period or for devices refurbished with batteries of unknown quality. State of Health (SOH) measurement reflects the overall battery health level relative to, for example, a newly manufactured battery or other batteries at their maximum health. Summary of the Invention

[0003] Various aspects and advantages of embodiments of this disclosure will be set forth in part in the description which follows, or may be learned from the description or by practice of the embodiments.

[0004] One example aspect of this disclosure relates to a wearable device having an improved determination of the battery's state of health. The wearable device may include a device housing. The wearable device may include a battery disposed within at least a portion of the device housing. The wearable device may include a battery metering system configured to provide a state of charge (SOC) metric indicating the battery's SOC. The wearable device may include one or more processors. The wearable device may include one or more non-transitory computer-readable media storing instructions that, when implemented, cause the one or more processors to perform operations. The operations may include determining that the wearable device is in a charging state, such that the battery's charge is increased during charging. The operations may include determining that the SOC metric reported by the battery metering system has increased by a fixed SOC interval. The operations may include determining a charging time interval by which the SOC metric of the battery has increased by the fixed SOC interval. The operations may include determining a state of health metric indicating the battery's health state based at least in part on the charging time interval. Determining the state of health metric may be based at least in part on a known relationship between a reference time interval, representing the time required for a reference battery in a fully healthy state to increase the fixed SOC interval, and the charging time interval.

[0005] Another exemplary aspect of this disclosure relates to a computer-implemented method for improved determination of the state of health of a battery in a battery-powered device. This computer-implemented method may include determining, by one or more processors, that the battery is in a charging state, such that the charge of the battery is increased during charging. The computer-implemented method may include determining, by the one or more processors, that a state of charge metric of the battery reported by a battery metering system has increased by a fixed state of charge interval. The computer-implemented method may include determining, by the one or more processors, a charging time interval by which the state of charge metric of the battery has increased by the fixed state of charge interval. The computer-implemented method may include determining, by the one or more processors, a state of health metric indicative of the health state of the battery based at least in part on the charging time interval. Determining the state of health metric may be based at least in part on a known relationship between a reference time interval, representing the time required for a reference battery in a fully healthy state to increase the fixed state of charge interval, and the charging time interval.

[0006] Other aspects of this disclosure relate to various systems, apparatuses, non-transitory computer-readable media, user interfaces, and electronic devices.

[0007] These and other features, aspects, and advantages of the various embodiments of this disclosure will be better understood by referring to the following description and the appended claims. The accompanying drawings, which are incorporated in and form a part of this specification, illustrate exemplary embodiments of the disclosure and, together with the description, serve to explain the relevant principles. Attached Figure Description

[0008] A detailed discussion of embodiments applicable to those skilled in the art is set forth in the description with reference to the accompanying drawings, wherein:

[0009] Figure 1 A perspective view depicting an example wearable device (e.g., an example smartwatch) on a user's wrist according to an example embodiment of the present disclosure is shown.

[0010] Figure 2 A schematic diagram of an example wearable device (e.g., an example smartwatch) according to an example embodiment of the present disclosure is depicted.

[0011] Figure 3 A block diagram of an example battery charging system according to an example embodiment of the present disclosure is depicted.

[0012] Figure 4 A block diagram of an example computing system configured to determine the health status of a battery according to an example embodiment of the present disclosure is depicted.

[0013] Figure 5 A flowchart depicts an example method for improving the determination of the health status of a battery in a wearable device according to an example embodiment of the present disclosure.

[0014] Figure 6 A flowchart depicts an example method for improving the determination of the health status of a battery in a wearable device according to an example embodiment of the present disclosure.

[0015] Repeated reference numerals in multiple figures are intended to identify the same features in various implementations. Detailed Implementation

[0016] Typically, this disclosure relates to determining the health state of a battery. Batteries, such as rechargeable batteries, can be recharged during charging, causing the battery's charge to increase during charging. For example, a battery may be discharged during battery use. During the charging process, the battery can return to a state of increased charge. During the charging process, the battery can be placed in a charging state, such that the battery's charge increases during the charging process while the battery is in the charging state. For example, the battery can be coupled to a battery charger during the charging process. The battery charger can be configured to provide current and / or voltage signals to recharge the battery during the charging process.

[0017] More specifically, this disclosure relates to battery-powered devices, such as wearable devices having improved determination of battery health status. Wearable devices, such as smartwatches, fitness trackers, activity trackers, pedometers, wearable electrocardiogram (ECG or EKG) devices, etc., may include batteries (such as rechargeable batteries). For example, a wearable device may include a device housing. The battery may be disposed within at least a portion of the device housing. For example, the device housing may define an interior and / or the battery may be disposed within the device housing. Battery health status can be expressed as a percentage of the total battery capacity relative to the initial capacity of the battery at the time of initial manufacturing.

[0018] Wearable devices may also include a battery metering system. The battery metering system may be a "fuel metering" system. The battery metering system can be configured to provide a state of charge (SOC) metric indicating the battery's state of charge. For example, the SOC metric may indicate the percentage of charge relative to device usage time (e.g., from 0% empty to 100% fully charged). The battery metering system may be configured to provide the SOC metric based at least in part on one or more battery charge factors. One or more battery charge factors may include factors that affect the battery's SOC, such as, but not limited to, measured battery voltage, reference battery voltage, battery aging, battery temperature, battery current consumption, battery usage, battery transients, battery chemistry, battery model, battery brand, or one or more calibration factors. The SOC metric can be expressed in any suitable manner. In some implementations, for example, the SOC metric is expressed incrementally as a percentage between the battery's fully charged state and its empty state.

[0019] As an example, a battery may have a characteristic curve illustrating the relationship between its voltage and its state of charge (SOC). This characteristic curve can be altered by other battery charge factors, such as temperature. For instance, an idle device may follow a predictable voltage-SOC curve, which provides a unique SOC for each voltage. This curve can be characterized based on battery chemistry, model, etc. However, use of the device draws current, affecting the voltage and making the idle device's curve inaccurate. Furthermore, transients, temperature, aging, and other factors can influence the characteristic curve in a correlated manner. Therefore, based on the characteristic curve, battery voltage, and / or one or more battery charge factors, a battery metering system can estimate the battery's SOC with high accuracy at a given point in time. Additionally and / or alternatively, some battery metering systems can measure the battery's SOC when it is at rest to avoid some battery charge factors (such as transients or use).

[0020] Battery performance degrades due to one or both of these factors: time (e.g., calendar life) and / or use (e.g., cycle life). Because of these factors, it is difficult to determine how much battery performance has degraded. This is especially problematic when devices containing batteries have been stored for a considerable period or when a device has been refurbished with batteries of unknown quality. Some existing methods for estimating battery health may have significant flaws. Some battery management systems attempt to optimize battery performance throughout its entire lifespan. Some systems estimate battery impedance based on pulse measurements, which naturally increases with battery aging. However, impedance measurements can be unreliable because impedance growth with aging can vary depending on the supplier and / or the specific battery. Furthermore, impedance measurements can be sensitive to the temperature of the battery and / or the device. Additionally and / or alternatively, some methods involve additional hardware, which can increase the cost of the device.

[0021] However, in general, battery metering systems can be highly accurate under various battery conditions, including aging, temperature, and usage. Therefore, state-of-charge measurements from battery metering systems can be reliable, including for excessively aged batteries. According to the example aspects of this disclosure, this, in turn, provides a reliable and useful means for estimating the health status of a battery.

[0022] It is worth noting that even if the battery's maximum capacity changes, the state-of-charge (SOC) measurements of the battery metering system can still be accurate. For example, if a new battery has a maximum capacity of 100mAh, but decreases to a maximum capacity of 70mAh over time and / or with use, the battery metering system can provide accurate readings, such as 100% when the battery is fully charged, and / or other accurate incremental SOC measurements, regardless of how much the battery performance has degraded.

[0023] Therefore, the exemplary aspects of this disclosure recognize that, assuming the reported state of charge (SOC) from the battery metering system is as accurate as desired for any particular battery, SOC can be useful in estimating the battery's state of health, even for degraded batteries. Specifically, the battery's state of health can be estimated at least in part based on the time during which a constant-current charger adds a fixed amount to the SOC. Similarly, the battery's state of health can be estimated at least in part based on the increase in SOC measured over a given period of constant-current charging. In particular, when the charger current is constant, the time required to charge the battery during a fixed increase in SOC can be directly related to the battery's maximum capacity, and thus, its state of health.

[0024] For example, compared to a battery with a capacity of 70mAh (e.g., 50% = 35mAh), a fixed increase in state of charge (SOC) (e.g., 50%) for a battery with a maximum capacity of 100mAh (e.g., 50% = 50mAh) will correspond to a larger amount of charge. Furthermore, consider a charger charging at 100mA. In this case, adding 50% SOC (e.g., 50mAh) to a battery with a maximum capacity of 100mAh would take half an hour (e.g., 30 minutes), while adding 50% SOC (e.g., 35mAh) to a battery with a maximum capacity of 70mAh would take 0.35 hours (e.g., 21 minutes). Therefore, by measuring the time required to add a given percentage to the SOC, the total capacity of the battery can be estimated, thus estimating the battery's state of health.

[0025] More generally, exemplary aspects of this disclosure provide determining the health state of a battery as the ratio of the change in state of charge (SOC) of the battery under constant current to the change in SOC of a reference (new battery) under the same constant current. For example, a first rate of SOC change of the battery over time can be determined and compared to a second rate of SOC change of the reference battery over time. The ratio of this first rate to the second rate can be the health state of the battery (e.g., expressed as a percentage). As an example, a first ratio of any SOC change of the battery under constant current to the time required for that SOC change can be compared to a second ratio of any SOC change of the new battery under constant current to the time required for that SOC change. This comparison can be the health state.

[0026] Note that this assumes the charger provides a constant current during the period in which the increase in state of charge is observed. At this point, it may be necessary and / or required to limit the increase in state of charge to a portion of the state of charge during which the charger is charging in constant current mode. For example, some chargers operate by charging at a constant current until the battery reaches a certain maximum permissible voltage, then switching to constant voltage charging (e.g., at the maximum permissible voltage) and gradually decreasing the current until the battery is fully charged. In this case, the method described herein may only be applicable when the battery is charging in constant current mode (e.g., when the battery voltage is below the maximum permissible voltage). However, because the method described herein can be applied to relatively narrow periods of state of charge increase, the exemplary aspects of this disclosure can be applied to multiple devices that are charged with constant current, even over relatively short periods, especially for devices that are charged with constant current (e.g., at or below about 80% SoC) for most of the charging process.

[0027] An exemplary aspect of this disclosure relates to a computer-implemented method for improving the determination of the state of health of a battery in a wearable device. This method can be implemented in any suitable wearable device. As examples, the wearable device may be a smartwatch, wearable fitness tracker, pedometer, wearable electrocardiogram device, activity tracker, and / or any other suitable (e.g., wearable) device, and / or combinations thereof. The wearable device may include one or more processors and one or more non-transitory computer-readable media storing instructions that, when implemented, cause the one or more processors to perform operations for determining the state of health of the battery. Additionally and / or alternatively, the computer-implemented method may be implemented on a computing system separate from the wearable device, such as a charger for the wearable device, a diagnostic system, or any other suitable computing system.

[0028] This method may include determining that the wearable device is in a charging state, such that the battery charge increases during the charging process. For example, the wearable device may confirm that it is connected to a charger and / or is being charged. As an example, in some implementations, determining that the wearable device is in a charging state may include requesting a charging signal from a charger coupled to the battery to be provided to the battery, causing the battery charge to increase over time, and receiving the charging signal from the charger coupled to the battery.

[0029] In some implementations, the state of charge can be a constant current charging state, at least during the charging time interval, such that the battery receives a fixed (e.g., constant) current during the charging time interval. Additionally and / or alternatively, in some implementations, the state of charge is configured to switch from a constant current charging state to a constant voltage charging state during the charging process. The charging time interval can be determined before the switching from the constant current charging state to the constant voltage charging state. For example, the charging time interval can occur while the device is in a constant current charging state, such that a linear relationship between charging time and charge (e.g., current) is maintained.

[0030] Furthermore, the computer-implemented method may include determining that the state-of-charge (SOC) metric of the battery reported by the battery metering system has been increased by a fixed SOC interval. The fixed SOC interval can be any suitable interval, such as 1%, 5%, 10%, 20%, 30%, 50%, etc. Generally, while larger SOC intervals may require more charging time to determine, they can be more accurate for small changes in SOC, etc. However, the exemplary aspects of this disclosure can also be applied to smaller SOC intervals to determine the health status more quickly while maintaining high accuracy.

[0031] In some implementations, determining that the state-of-charge (SOC) metric reported by the battery metering system has increased by a fixed SOC interval may include obtaining a first SOC measurement from the battery metering system at a first time. After obtaining the first SOC measurement, determining that the SOC metric reported by the battery metering system has increased by the fixed SOC interval may include obtaining a second SOC measurement from the battery metering system at a second time. The method may then include determining that the second SOC measurement differs from the first SOC measurement by the fixed SOC interval. For example, the second SOC measurement may be subtracted from the first SOC measurement to determine the current SOC interval, which may be compared with the fixed SOC interval.

[0032] Furthermore, the method may include determining a charging time interval in which the battery's state of charge (SOC) metric has increased by a fixed SOC interval. For example, in some implementations, determining that the charging time interval in which the battery's SOC metric has increased by a fixed SOC interval may include subtracting a first time interval from a second time interval. For example, the charging time interval may be the difference between the first and second time intervals.

[0033] Furthermore, the method may include determining a health status metric indicative of battery health based at least in part on charging time intervals. For example, determining the health status metric may be based at least in part on a known relationship between a reference time interval, representing the time required to increase a reference battery in a fully healthy state of charge by a fixed state of charge interval, and the charging time interval. As an example, the health status metric may be a ratio between the charging time interval and the reference time interval. Therefore, this ratio may represent the ratio between the amount of time required to charge the battery at a fixed state of charge and the time required to charge a fully healthy battery at the same fixed state of charge. Thus, this ratio may be directly related to the health status of the battery.

[0034] In some implementations, the method may also include providing health metrics to the user via one or more processors. These health metrics can be displayed to the user to assess the battery's health. For example, health metrics can be provided to the user to make an informed decision about whether the battery should be replaced or repaired. As another example, the user can monitor the battery's health to measure how long the device can be used continuously after a full charge.

[0035] As another example, health status metrics can be used (e.g., by diagnostic technicians) to determine whether performance issues with a wearable device are due to low battery health and / or other causes. For instance, health status metrics can be communicated to diagnostic systems during the wearable device's service life. Based on these health status metrics, users may be able to make informed decisions about which components of the wearable device (e.g., the battery) need repair to restore it to optimal functionality.

[0036] Another exemplary aspect of this disclosure relates to a computer-implemented method for improving the determination of the state of health of a battery in a wearable device. This method can be implemented in any suitable wearable device. As examples, the wearable device may be a smartwatch, wearable fitness tracker, pedometer, wearable electrocardiogram device, activity tracker, and / or any other suitable wearable device, and / or combinations thereof. The wearable device may include one or more processors and one or more non-transitory computer-readable media storing instructions that, when implemented, cause the one or more processors to perform operations for determining the state of battery health. Additionally and / or alternatively, the computer-implemented method may be implemented on a computing system separate from the wearable device, such as a charger for the wearable device, a diagnostic system, or any other suitable computing system.

[0037] This method may include determining that the wearable device is in a charging state, such that the battery charge increases during the charging process. For example, the wearable device may confirm that it is connected to a charger and / or is being charged. As an example, in some implementations, determining that the wearable device is in a charging state may include requesting a charging signal from a charger coupled to the battery to be provided to the battery, causing the battery charge to increase over time, and receiving the charging signal from the charger coupled to the battery.

[0038] In some implementations, the state of charge can be a constant current charging state, at least during the charging time interval, such that the battery receives a fixed current during the charging time interval. Additionally and / or alternatively, in some implementations, the state of charge is configured to switch from a constant current charging state to a constant voltage charging state during the charging process. The charging time interval can be determined before the switching from the constant current charging state to the constant voltage charging state. For example, the charging time interval can occur while the device is in a constant current charging state, such that a linear relationship between charging time and current is maintained.

[0039] Furthermore, the method may include one or more processors determining that a fixed charging time interval has elapsed during the charging process. For example, once the device is determined to be in a charging state, the device may wait until the fixed charging time interval has elapsed and the device is in a charging state.

[0040] Once a charging time interval has elapsed, the method may include having one or more processors determine the measured increase in state of charge (SOC) in the battery's SOC measurements reported by the battery metering system within the fixed charging time interval. For example, the wearable device may record the battery's SOC at the beginning and / or end of the fixed charging time interval. For example, the method may include obtaining a first SOC measurement after determining that the wearable device is in a charging state. Furthermore, the method may include obtaining a second SOC measurement after determining that the fixed charging time interval has elapsed during the charging process. The method may then include determining the measured SOC increase as the difference between the second SOC measurement and the first SOC measurement.

[0041] The method may include determining a health state metric indicative of the battery's health state by one or more processors, at least in part, based on a measured increase in state of charge. For example, determining the health state metric may be based at least in part on a known relationship between a reference increase in state of charge, representing the expected increase in state of charge over a charging time interval of a reference battery in full health, and the measured increase in state of charge. For example, in some implementations, the health state metric may be or may include a ratio between the measured increase in state of charge and the reference increase in state of charge. This ratio may be related to the battery's health state.

[0042] In some implementations, the method may also include providing health metrics to the user via one or more processors. These health metrics can be displayed to the user to assess the battery's health. For example, health metrics can be provided to the user to make an informed decision about whether the battery should be replaced or repaired. As another example, the user can monitor the battery's health to measure how long the device can be used continuously after a full charge.

[0043] As another example, health status metrics (e.g., by diagnostic technicians) can be used to determine whether a wearable device's performance issues are a result of low battery health and / or other causes. For instance, health status metrics can be communicated to diagnostic systems during the wearable device's service life. Based on this health status metric, users may be able to make informed decisions about which components of the wearable device (e.g., the battery) need repair to restore it to optimal functionality.

[0044] The systems and methods according to the exemplary aspects of this disclosure can provide a variety of technical effects and benefits, including improvements to computational techniques. As an example, determining a health state metric indicative of battery health based at least in part on charging time intervals (e.g., determining the health state metric based at least in part on a known relationship between a reference time interval representing the time required for a reference battery to increase its state of charge to a fixed interval in a fully healthy state and the charging time interval) can provide a reliable and inexpensive method for estimating battery health. For example, the systems and methods according to the exemplary aspects of this disclosure can estimate battery health without requiring any additional hardware (e.g., voltage sensors, current sensors, etc.) that would increase device cost, thus reducing device cost. Additionally and / or alternatively, the exemplary aspects of this disclosure can be implemented without significant computational costs. Additionally and / or alternatively, the systems and methods according to the exemplary aspects of this disclosure can determine battery health within charging intervals shorter than the battery's full charging interval. This can provide a reduction in the time required to determine battery health.

[0045] Exemplary embodiments of this disclosure will now be discussed in more detail with reference to the accompanying drawings.

[0046] Figure 1 A view 100 of an example electronic device 102 worn on a user's arm 104 is illustrated. Electronic devices, such as wearable electronic devices, can interact with the user via a touch-sensitive display 106, one or more mechanical buttons 108, or other input mechanisms known for such purposes. Such devices can also be configured to communicate wirelessly with another computing device, such as a smartphone owned by the user wearing the electronic device. While devices such as smartwatches or fitness trackers are shown, it should be understood that various other types of electronic devices can benefit from the advantages of the various embodiments discussed and suggested herein, and will be apparent to those skilled in the art from the teachings of this disclosure. Electronic device 102 may include a battery (not shown) configured to provide power to various components of electronic device 102.

[0047] Figure 2Another cross-sectional view 200 of the example device is illustrated. In this example, a cover glass 202 covers a display module 204. A gap 206 exists between the display module 204 and the conductive patch 208 for display and touch bending, as well as for the NFC antenna. A patch antenna rear cavity 210 is formed below the conductive patch 208 and above a printed circuit board (PCB) 212, which maintains the resonant mode of the patch antenna. The patch antenna is coupled to a metal housing 222 via a port 201. The port 201 may be a metal spring contact directly coupled from the mating patch to the metal housing 222. In some embodiments, the port 201 may be a lumped element coupled from the conductive patch 208 to the metal housing 222 to adjust the resonant mode of the conductive patch 208. The PCB 212 and PCB shield 214 are located below the patch antenna rear cavity, forming a PCB shield to reduce electromagnetic interference (EMI) from nearby components. A battery holder 218 is used in this case to hold the battery 220 in proper position within the housing relative to the conductive metal housing 222. A slot antenna rear cavity 216 is formed between the PCB shield 214 and the battery bracket 218. In some embodiments, the display window is mechanically coupled to a metal housing. The display window and the metal housing can form a waterproof, sealed enclosure. The device includes a touch module and a display module, the touch module being configured to detect touch input on the display window. The display module is configured to display images or information through the display window.

[0048] Example devices may include component layers on a PCB. Component layers may include any suitable components, such as microprocessors, RAM (Random Access Memory), ROM (Read-Only Memory), ASICs (Application-Specific Integrated Circuits), FPGAs (Field-Programmable Gate Arrays), surface-mount components, integrated circuits, etc. The PCB may provide electronic components and circuitry for guiding and interpreting electrical signals for the device. For example, the PCB may be electrically coupled to a display and touch module to interpret touch input and provide images or information for display. The PCB may include a ground plane portion. The PCB may also include a feed clip portion that does not include conductive elements other than an antenna feed clip mounted on and electrically coupled to the PCB. For example, the PCB may include traces electrically coupling a ground plane region to a feed clip region, and the feed clip electrically coupling to traces in the feed clip region. The ground plane may be provided by a large metallized area, conductive traces in a printed circuit board or flexible printed circuit board, a metal plate and / or surface within a metal housing, etc. The device may also include a vibration motor to provide haptic feedback or otherwise mechanically vibrate the device. The PCB may be grounded to the metal housing via one or more grounding screws that electrically couple the PCB to the metal housing. The battery may be located approximately 0.05 mm below the metal plate. In some embodiments, a layer of non-conductive, low-RF-loss, rigid material may be inserted to attach or otherwise mechanically couple the metal plate to the battery within the 0.05 mm gap. In some embodiments, the battery is located between approximately 0.01 mm and approximately 0.1 mm below the metal plate, between approximately 0.03 mm and approximately 0.7 mm below the metal plate, or between approximately 0.04 mm and approximately 0.06 mm below the metal plate. Between the battery and the module layer, there is a dielectric gap (e.g., air or plastic, or a combination of air and plastic) that creates a back cavity for the slot antenna in a closed metal housing design. The height of the dielectric gap may vary but serves to ensure isolation between the battery and any components on the module layer. The battery may be located approximately 0.48 mm above the module layer. In some embodiments, the battery is located between approximately 0.4 mm and approximately 0.6 mm above the module layer, between approximately 0.42 mm and approximately 0.55 mm above the module layer, or between approximately 0.45 mm and approximately 0.5 mm above the module layer. In some embodiments, as described herein, a plastic bracket may be placed in the gap to support the battery above the component layer of the PCB.

[0049] Figure 3A block diagram of an example battery charging system 300 according to an example embodiment of the present disclosure is depicted. The battery charging system 300 may include a wearable device 310. The wearable device 310 may include one or more processors 312. Additionally, the wearable device 310 may include at least one battery 314. The battery 314, such as a rechargeable battery, may be recharged during charging, such that the charge of the battery 314 increases during charging. For example, the battery 314 may discharge during use of the battery 314 and / or the wearable device 310. The battery 314 may return to a state of increased charge during the charging process. During the charging process, the battery 314 may be placed in a charging state, such that the charge of the battery 314 increases while the battery 314 is in a charging state. For example, the battery 314 may be coupled to a battery charger 320 during the charging process. The battery charger 320 may be configured to provide current and / or voltage signals during the charging process to recharge the battery 314. For example, the processor 312 may request current from the charger 320 to charge the battery 314 as described herein.

[0050] Figure 4 The illustration depicts components of an example tracker system 400 that can be used according to various embodiments. In this example, the device includes at least one processor 402, such as a central processing unit (CPU) or a graphics processing unit (GPU), for executing instructions that can be stored in a memory device 404, such as flash memory or DRAM, among other such options. It will be apparent to those skilled in the art that the device can include various types of memory, data storage, or computer-readable media, such as data storage for program instructions executed by the processor. The same or separate storage can be used for images or data, removable memory can be used to share information with other devices, and any number of communication methods can be used to share information with other devices. The device will typically include some type of display 406, such as a touchscreen, an organic light-emitting diode (OLED), or a liquid crystal display (LCD), although the device may convey information via other means, such as through an audio speaker or a projector.

[0051] The tracker or similar device will include at least one motion detection sensor, such as Figure 4As shown, it may include at least one I / O element 410 of the device. Such a sensor can determine and / or detect the orientation and / or movement of the device. Such an element may include, for example, an accelerometer, inertial sensor, altimeter, or gyroscope, operable to detect the motion of the device (e.g., rotational movement, angular displacement, tilt, position, orientation, movement along a non-linear path, etc.). The orientation determining element may also include an electronic or digital compass, which can indicate the direction the device is pointing (e.g., north or south) (e.g., relative to a main axis or other such aspect). The device may also include I / O element 410 for determining the location of the device (or the user of the device). Such a positioning element may include or contain a GPS or similar positioning element operable to determine the relative coordinates of the device's location. Positioning elements may include wireless access points, base stations, etc., which can broadcast location information or enable signal triangulation to determine the device's location. Other positioning elements may include QR codes, barcodes, RFID tags, NFC tags, etc., that enable the device to detect and receive location information, or identifiers that enable the device to acquire location information (e.g., by mapping the identifier to a corresponding location). Various embodiments may include one or more such elements in any suitable combination. I / O components may also include one or more biosensors, optical sensors, barometric sensors (e.g., altimeters, etc.).

[0052] As described above, some embodiments use elements to track a user's location and / or movement. After determining the initial location of the device (e.g., using GPS), some embodiments of the device may track the device's location by using (multiple) elements, or in some cases by using orientation-determining elements as described above, or combinations thereof. It should be understood that the algorithms or mechanisms used to determine location and / or orientation may depend at least in part on the selection of elements available to the device. The example device also includes one or more wireless components 412 operable to communicate with one or more electronic devices within communication range of a particular wireless channel. The wireless channel can be any suitable channel for enabling the device to communicate wirelessly, such as a Bluetooth, cellular, NFC, or Wi-Fi channel. It should be understood that the device may have one or more conventional wired communication connections known in the art. The device also includes one or more power components 408, such as including a battery operable to be charged by conventional plug-in methods or by other methods, such as capacitive charging by proximity to a power pad or other such device. In some embodiments, the device may include at least one additional input / output device 410 capable of receiving conventional input from a user. Such conventional inputs can include, for example, buttons, touchpads, touchscreens, scroll wheels, joysticks, keyboards, mice, keypads, or any other such devices or elements, allowing the user to input commands to the device. In some embodiments, these I / O devices can even be connected wirelessly via infrared, Bluetooth, or other links. Some devices may also include a microphone or other audio capture element that accepts voice or other audio commands. For example, the device may not include any buttons at all, and may be controlled solely through a combination of visual and audio commands, allowing the user to control the device without physical contact.

[0053] As described above, many embodiments will include at least some combination of one or more transmitters 416 and one or more detectors 418 for measuring data of one or more metrics of a human body (e.g., a person wearing a tracker device). In some embodiments, this may involve at least one imaging element, such as one or more cameras capable of capturing images of the surrounding environment and capable of imaging a user, person, or object near the device. The image capturing element may include any suitable technology, such as a CCD image capturing element with sufficient resolution, focal length, and field of view to capture images of the user as the user operates the device. Methods of capturing images using camera elements with computing devices are well known in the art and will not be discussed in detail herein. It should be understood that image capture can be performed using a single image, multiple images, periodic imaging, continuous image capture, image streaming, etc. Furthermore, the device may include the ability to start and / or stop image capture, such as when receiving a command from a user, application, or other device. Example devices include transmitters 416 and detectors 418 capable of obtaining additional biometric data, which can be used in conjunction with the example circuitry discussed herein.

[0054] If included, display 406 can provide an interface for displaying data such as heart rate (HR), ECG data, blood oxygen saturation (SpO2) levels, and other user measurements. In one embodiment, the device includes a wristband, and the display is configured such that it faces away from the user's wrist when the user wears the device. In other embodiments, the display may be omitted, and data detected by the device can be transmitted to a host computer 422 via at least one network 420 using a wireless network interface via near field communication (NFC), Bluetooth, Wi-Fi, or other suitable wireless communication protocols for analysis, display, reporting, or other such purposes.

[0055] Memory 404 may include RAM, ROM, FLASH memory, or other non-transitory digital data storage, and may include a control program containing a sequence of instructions that, when loaded from memory and executed by processor 402, cause processor 402 to perform the functions described herein. Transmitter 416 and detector 418 may be directly or indirectly coupled to a bus using driver circuitry, and processor 402 may drive optical transmitter 416 and obtain signals from optical detector 418 via the driver circuitry. Host computer 422 communicates with wireless network component 412 via one or more networks 420, which may include one or more local area networks, wide area networks, and / or interconnected networks using any terrestrial or satellite links. In some embodiments, host computer 422 executes control programs and / or applications configured to perform some of the functions described herein.

[0056] In various embodiments, the methods discussed herein can be performed by one or more of the following: firmware running on a monitoring or tracking device or auxiliary device (such as a mobile device paired with the monitoring device), a server, a host computer, etc. For example, the monitoring device can perform operations related to generating signals that are uploaded or otherwise transmitted to a server, which performs operations to remove motion components and create final estimates of physiological measures. Alternatively, the monitoring device can perform operations related to generating monitoring signals and removing motion components to produce final estimates of physiological measures local to the monitoring device. In this case, the final estimate can be uploaded or otherwise transmitted to a server, such as to a host that uses the value to perform other operations.

[0057] Example monitoring or tracker devices can collect one or more types of physiological and / or environmental data from one or more sensors and / or external devices, and transmit or relay such information to other devices (e.g., a host or another server), thus allowing the collected data to be viewed, for example, using a web browser or a web-based application. For example, when worn by a user, a tracker device can perform biometric monitoring by using one or more sensors to calculate and store the user's steps. The tracker device can transmit data representing the user's steps to an account on a web service (e.g., www.fitbit.com), a computer, a mobile phone, and / or a health station, where the data can be stored, processed, and / or visualized by the user. In addition to or in lieu of the user's steps, the tracker device can also measure or calculate other physiological metrics. Such physiological measures may include, but are not limited to: energy expenditure, such as calorie burn; floors ascended and / or descended; heart rate; heart rate waveform; heart rate variability; heart rate recovery; respiration, SpO2, blood volume, blood glucose, skin hydration and skin pigmentation levels, location and / or heading (e.g., via GPS, GLONASS, or similar systems); altitude; walking speed and / or distance traveled; number of swimming laps; swimming stroke type and count detection; cycling distance and / or speed; blood glucose; skin conduction; skin and / or body temperature; muscle status measured by electromyography; brain activity measured by electroencephalography; weight; body fat; calorie intake; nutrient intake from food; drug intake; sleep duration (e.g., clock time, sleep stage, sleep quality, and / or duration); pH value; hydration level; respiratory rate; and / or other physiological measures.

[0058] Example trackers or monitoring devices may also measure or calculate metrics related to the user's surrounding environment (e.g., using one or more environmental sensors), such as air pressure, weather conditions (e.g., temperature, humidity, pollen count, air quality, rain / snow conditions, wind speed), light exposure (e.g., ambient light, ultraviolet (UV) light, time and / or duration spent in darkness), noise exposure, radiation exposure, and / or magnetic fields. Furthermore, the tracker device (and / or a host computer and / or another server) can collect data from one or more sensors on the device and can calculate metrics derived from such data. For example, the tracker device may calculate a user's stress or relaxation level based on a combination of HR variability, skin conduction, noise pollution, and / or sleep quality. In another example, the tracker device may determine the efficacy of a medical intervention (e.g., a medication) based on a combination of data related to medication intake, sleep, and / or activity. In yet another example, the tracker device may determine the efficacy of an allergy medication based on a combination of data related to pollen levels, medication intake, sleep, and / or activity. These examples are provided for illustrative purposes only and are not intended to be limiting or exhaustive.

[0059] Example surveillance devices may include computer-readable storage media readers, communication devices (e.g., modems, network interface cards (wireless or wired), infrared communication devices), and working memory as described above. Computer-readable storage media readers may be connected to or configured to receive computer-readable storage media representing remote, local, fixed, and / or removable storage devices, as well as storage media for temporarily and / or more permanently containing, storing, transmitting, and retrieving computer-readable information. Surveillance systems and various devices typically also include multiple software applications, modules, services, or other elements, including operating systems and applications such as client applications or web browsers, residing within at least one working storage device. It should be understood that alternative embodiments may have many variations different from the embodiments described above. For example, custom hardware may also be used and / or specific elements may be implemented in hardware, software (including portable software, such as applets), or both. Furthermore, connections to other computing devices, such as network input / output devices, may be employed.

[0060] Storage media and other non-transitory computer-readable media used to contain code or code portions may include any suitable media known or used in the art, such as, but not limited to, volatile and non-volatile, removable and non-volatile media implemented in any method or technology for storing information (e.g., computer-readable instructions, data structures, program modules or other data), including RAM, ROM, EEPROM, flash memory or other storage technologies, CD-ROM, digital universal disk (DVD) or other optical storage, magnetic tape, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and is accessible by system devices.

[0061] Figure 5 A flowchart depicts an example method for performing an improved determination of the health state of a wearable device's battery, according to an example embodiment of this disclosure. Although Figure 5 For illustrative and discussion purposes, the steps performed in a specific order are described, but the method of this disclosure is not limited to the specifically described order or arrangement. The steps of method 500 may be omitted, rearranged, combined, and / or modified in various ways without departing from the scope of this disclosure.

[0062] Method 500 may include, at 502, determining that the wearable device is in a charging state, such that the battery charge increases during the charging process. For example, the wearable device may confirm that it is connected to a charger and / or is being charged. As an example, in some implementations, determining that the wearable device is in a charging state may include requesting a charging signal from a charger coupled to the battery to be provided to the battery, causing the battery charge to increase over time, and receiving the charging signal from the charger coupled to the battery.

[0063] In some implementations, the state of charge can be a constant current charging state, at least during the charging time interval, such that the battery receives a fixed (e.g., constant) current during the charging time interval. Additionally and / or alternatively, in some implementations, the state of charge is configured to switch from a constant current charging state to a constant voltage charging state during the charging process. The charging time interval can be determined before the switching from the constant current charging state to the constant voltage charging state. For example, the charging time interval can occur while the device is in a constant current charging state, such that a linear relationship between charging time and charge (e.g., current) is maintained.

[0064] Furthermore, the computer-implemented method 500 may include, at 504, determining that the state-of-charge (SOC) metric of the battery reported by the battery metering system has been increased by a fixed SOC interval. The fixed SOC interval can be any suitable interval, such as 1%, 5%, 10%, 20%, 30%, 50%, etc. Generally, while a larger SOC interval may require more charging time to determine, it can be more accurate for small changes in SOC, etc. However, exemplary aspects of this disclosure can also be applied to smaller SOC intervals to determine the health status more quickly while maintaining high accuracy.

[0065] In some implementations, determining that the state-of-charge (SOC) metric reported by the battery metering system has increased by a fixed SOC interval may include obtaining a first SOC measurement from the battery metering system at a first time. After obtaining the first SOC measurement, determining that the SOC metric reported by the battery metering system has increased by the fixed SOC interval may include obtaining a second SOC measurement from the battery metering system at a second time. The method may then include determining that the second SOC measurement differs from the first SOC measurement by the fixed SOC interval. For example, the second SOC measurement may be subtracted from the first SOC measurement to determine the current SOC interval, which may be compared with the fixed SOC interval.

[0066] Furthermore, method 500 may include, at 506, determining that the battery's state of charge metric has been increased by a fixed state of charge interval during a charging time interval. For example, in some implementations, determining that the battery's state of charge metric has been increased by a fixed state of charge interval during a charging time interval may include subtracting a first time interval from a second time interval. For example, the charging time interval may be the difference between the first time interval and the second time interval.

[0067] Furthermore, method 500 may include, at 508, determining a health status metric indicative of the battery's health status based at least in part on a charging time interval. For example, determining the health status metric may be based at least in part on a known relationship between a reference time interval, representing the time required to increase a reference battery in a fully healthy state of charge by a fixed state of charge interval, and the charging time interval. As an example, the health status metric may be a ratio between the charging time interval and the reference time interval. Therefore, this ratio may represent the ratio between the amount of time required to charge the battery at a fixed state of charge and the time required to charge a fully healthy battery at the same fixed state of charge. Thus, this ratio may be directly related to the battery's health status.

[0068] In some implementations, the method may further include providing health metrics by one or more processors to display to the user. Health metrics can be displayed to the user to assess the battery's health. For example, health metrics can be provided to the user to make an informed decision about whether the battery should be replaced or repaired. As another example, the user can monitor the battery's health to measure how long the device can be used continuously after a full charge.

[0069] As another example, health status metrics (e.g., by diagnostic technicians) can be used to determine whether performance issues with a wearable device are caused by a low battery health and / or other reasons. For instance, health status metrics can be communicated to diagnostic systems during the wearable device's service life. Based on these health status metrics, users may be able to make informed decisions about which components of the wearable device (e.g., the battery) need repair to restore it to optimal functionality.

[0070] Figure 6 A flowchart depicts an example method for performing an improved determination of the health state of a wearable device's battery, according to an example embodiment of this disclosure. Although Figure 6 For illustrative and discussion purposes, the steps performed in a specific order are described, but the method of this disclosure is not limited to the specifically described order or arrangement. The steps of method 600 may be omitted, rearranged, combined, and / or modified in various ways without departing from the scope of this disclosure.

[0071] Method 600 may include, at 602, determining that the wearable device is in a charging state, such that the battery charge increases during the charging process. For example, the wearable device may confirm that it is connected to a charger and / or is being charged. As an example, in some implementations, determining that the wearable device is in a charging state may include requesting a charging signal from a charger coupled to the battery to be provided to the battery, causing the battery charge to increase over time, and receiving the charging signal from the charger coupled to the battery.

[0072] In some implementations, the state of charge can be a constant current charging state, at least during the charging time interval, such that the battery receives a fixed (e.g., constant) current during the charging time interval. Additionally and / or alternatively, in some implementations, the state of charge is configured to switch from a constant current charging state to a constant voltage charging state during the charging process. The charging time interval can be determined before the switching from the constant current charging state to the constant voltage charging state. For example, the charging time interval can occur while the device is in a constant current charging state, such that a linear relationship between charging time and charge (e.g., current) is maintained.

[0073] Furthermore, method 600 may include, at 604, one or more processors determining that a fixed charging time interval has elapsed during the charging process. For example, once the device is determined to be in a charging state, the device may wait until the fixed charging time interval has elapsed and the device is in a charging state.

[0074] Once a charging time interval has elapsed, method 600 may include, at 606, one or more processors determining a measured increase in the state of charge (SOC) of the battery reported by the battery metering system within the fixed charging time interval. For example, the wearable device may record the SOC of the battery at the beginning and / or end of the fixed charging time interval. For example, method 600 may include obtaining a first SOC measurement after determining that the wearable device is in a charging state. Furthermore, method 600 may include obtaining a second SOC measurement after determining that a fixed charging time interval has elapsed during the charging process. The method may then include determining the measured SOC increase as the difference between the second SOC measurement and the first SOC measurement.

[0075] Method 600 may include, at 608, having one or more processors determine a health state metric indicative of the battery's health state based at least in part on a measured increase in state of charge. For example, determining the health state metric may be based at least in part on a known relationship between a reference increase in state of charge, representing an expected increase in state of charge over a charging time interval of a reference battery in full health, and the measured increase in state of charge. For example, in some implementations, the health state metric may be or may include a ratio between the measured increase in state of charge and the reference increase in state of charge. This ratio may be related to the battery's health state.

[0076] In some implementations, method 600 may also include providing health status metrics by one or more processors to display to the user. Health status metrics can be displayed to the user to assess the battery's health. For example, health status metrics can be provided to the user to make an informed decision about whether the battery should be replaced or repaired. As another example, the user can monitor the battery's health status to measure how long the device can be used continuously after being fully charged.

[0077] As another example, health status metrics (e.g., by diagnostic technicians) can be used to determine whether performance issues with a wearable device are caused by a low battery health and / or other reasons. For instance, health status metrics can be communicated to diagnostic systems during the wearable device's service life. Based on these health status metrics, users may be able to make informed decisions about which components of the wearable device (e.g., the battery) need repair to restore it to optimal functionality.

[0078] This article discusses technologies related to servers, databases, software applications, and other computer-based systems, as well as the actions taken and the information sent to and from these systems. The inherent flexibility of computer-based systems allows for a wide variety of possible configurations, combinations, and task and assignment divisions among components. For example, the processes discussed in this article can be implemented using a single device or component, or a combination of multiple devices or components. Databases and applications can be implemented on a single system or distributed across multiple systems. Distributed components can run sequentially or in parallel.

[0079] While the subject matter has been described in detail with respect to various specific example embodiments, each example is provided by way of explanation and not as a limitation of this disclosure. Those skilled in the art, upon gaining an understanding of the foregoing, will readily make changes, variations, and equivalents to these embodiments. Therefore, this disclosure does not exclude the inclusion of such modifications, variations, and / or additions to the subject matter, which will be apparent to those skilled in the art. For example, features shown or described as part of an embodiment may be used with another embodiment to produce yet another embodiment. Therefore, this disclosure is intended to cover such changes, variations, and equivalents.

Claims

1. A wearable device comprising: a device housing; a battery disposed within at least a portion of the device housing; a battery gauging system configured to provide a state-of-charge metric indicative of a state-of-charge of the battery; one or more processors; and one or more non-transitory computer-readable media storing instructions that, when executed, cause the one or more processors to perform operations comprising: determining that the wearable device is in a charging state, the charging state indicating that a charge of the battery is being increased during a charging process; determining that the state-of-charge metric of the battery reported by the battery gauging system has increased by a fixed state-of-charge interval; determining that the state-of-charge metric of the battery has increased by a charge time interval of the fixed state-of-charge interval; and determining, based at least in part on the charge time interval, a health state metric indicative of a health state of the battery; wherein the health state metric is determined based at least in part on a known relationship between a reference time interval representative of a time required for a reference battery in a fully healthy state to increase by the fixed state-of-charge interval and the charge time interval. Determining that the wearable device is in the charging state comprises:

2. The wearable device of claim 1, wherein, sending a request message to a charger coupled to the battery, the request message requesting the charger to provide a charging signal to the battery to cause the charge of the battery to increase over time; and receiving the charging signal from the charger. The charging state comprises a constant current charging state for at least the charge time interval, the constant current charging state indicating that the battery receives a constant current for the charge time interval.

3. The wearable device of claim 1, wherein, The charging state is configured to switch from the constant current charging state to a constant voltage charging state during the charging process, and wherein the charge time interval is determined prior to the charging state switching from the constant current charging state to the constant voltage charging state.

4. The wearable device of claim 3, wherein, The battery gauging system is configured to provide the state-of-charge metric indicative of the state-of-charge of the battery based at least in part on one or more of a set of battery charge factors, the set of battery charge factors comprising: a measured battery voltage, a reference battery voltage, a battery age, a battery temperature, a battery current draw, a battery usage, a battery transience, a battery chemistry, a battery model, a battery brand, and one or more calibration factors.

5. The wearable device of claim 1, wherein, Determining that the state-of-charge metric of the battery reported by the battery gauging system has increased by the fixed state-of-charge interval comprises:

6. The wearable device of claim 1, wherein, obtaining a first state-of-charge measurement from the battery gauging system at a first time; obtaining a second state-of-charge measurement from the battery gauging system at a second time after obtaining the first state-of-charge measurement; and determining that the second state-of-charge measurement differs from the first state-of-charge measurement by the fixed state-of-charge interval. Determining that the state-of-charge metric of the battery has increased by a charge time interval of the fixed state-of-charge interval comprises subtracting the first time from the second time.

7. The wearable device of claim 6, wherein, ​ 8. The wearable device of claim 1, wherein, The state of charge metric is incrementally represented as a percentage between a full state of charge of the battery and an empty state of the battery.

9. The wearable device of claim 1, wherein, The health state metric includes a ratio between the charge time interval and a reference time interval.

10. The wearable device of claim 1, wherein, The wearable device includes at least one of a smart watch, a wearable fitness tracker, a pedometer, a wearable electrocardiogram device, and an activity tracker.

11. A computer-implemented method for determining a health state of a battery of a battery-powered device, the computer-implemented method comprising: determining, by one or more processors, that the battery-powered device is in a charging state, the charging state indicating that a charge of the battery is being increased during a charging process; determining, by the one or more processors, that a state of charge metric of the battery reported by a battery gauge system has increased by a fixed state of charge interval; determining, by the one or more processors, that the state of charge metric of the battery has increased by a charge time interval of the fixed state of charge interval; and determining, by the one or more processors, a health state metric indicative of the health state of the battery based at least in part on the charge time interval; wherein the health state metric is determined based at least in part on a known relationship between a reference time interval representative of a time required for a reference battery in a fully healthy state to increase by the fixed state of charge interval and the charge time interval.

12. The computer-implemented method of claim 11, wherein, Determining that the battery-powered device is in the charging state includes: sending a request message to a charger coupled to the battery, the request message requesting the charger to provide a charging signal to the battery to cause the charge of the battery to increase over time; and receiving the charging signal from the charger.

13. The computer-implemented method of claim 11, wherein, The charging state includes a constant current charging state for at least the charge time interval, the constant current charging state indicating that the battery receives a constant current for the charge time interval.

14. The computer-implemented method of claim 11, wherein, Determining that the state of charge metric of the battery reported by the battery gauge system has increased by the fixed state of charge interval includes: obtaining a first state of charge measurement from the battery gauge system at a first time; obtaining a second state of charge measurement from the battery gauge system at a second time after obtaining the first state of charge measurement; and determining that the second state of charge measurement differs from the first state of charge measurement by the fixed state of charge interval.

15. The computer-implemented method of claim 14, wherein, Determining that the state of charge metric of the battery has increased by the charge time interval of the fixed state of charge interval includes subtracting the first time from the second time.

16. The computer-implemented method of claim 11, further comprising providing, by the one or more processors, the health state metric for display to a user.

17. A computer-implemented method for determining a health state of a battery of a battery-powered device, the computer-implemented method comprising: determining, by one or more processors, that the battery-powered device is in a charging state, the charging state indicating that a charge of the battery is being increased during a charging process; determining, by the one or more processors, that a fixed charging time interval has elapsed during the charging process; determining, by the one or more processors, a measured state of charge increase in state of charge measurements of the battery reported by a battery metering system over the fixed charging time interval; and determining, by the one or more processors, a state of health metric indicative of the state of health of the battery based at least in part on the measured state of charge increase; wherein the state of health metric is determined based at least in part on a known relationship between a reference state of charge increase representative of an expected increase in state of charge over the charging time interval for a reference battery in a fully healthy state and the measured state of charge increase.

18. The computer-implemented method of claim 17, wherein, the state of health metric comprises a ratio between the measured state of charge increase and the reference state of charge increase.

19. The computer-implemented method of claim 17, wherein, the charging state comprises a constant current charging state for at least the fixed charging time interval, the constant current charging state indicating that the battery receives a constant current for the fixed charging time interval.

20. The computer-implemented method of claim 17, further comprising providing, by the one or more processors, the state of health metric for display to a user.

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