Battery power supply device

Abstract

A battery powered device is disclosed comprising a battery and a voltage sensor arranged to measure a terminal voltage of the battery. The battery powered device is arranged to: a) determine a current flowing into or out of the battery; b) predicting a terminal voltage of the battery using the current and the estimated state of charge of the battery; c) measuring an actual terminal voltage of the battery using a voltage sensor; d) comparing the predicted terminal voltage with the actual terminal voltage, and e) updating the estimated state of charge of the battery based on the comparison The battery powered device is arranged to repeat steps (a)-(e) at one or more subsequent times determined based on the operating state of the battery powered device.

Description

Background Art

[0001] The present invention relates to evaluating the state of charge of a battery in a battery powered device such as an Internet of Things (IoT) device.

[0002] Battery-powered devices are very common. Being able to assess the state of charge (SOC) of the batteries in such devices is very useful, for example, to estimate how long the device can operate before the energy stored in the battery is exhausted. Accurately estimating the battery SOC is particularly useful for devices in remote and / or difficult to access locations, such as IoT sensors, because physical repairs to replace or recharge the battery can be planned in advance before the battery is completely exhausted. This can improve reliability and cost efficiency. In some devices, operation-level decisions are made based on the estimated SOC, so estimation errors can have a large impact on device operation.

[0003] The power requirements of a battery-powered device can vary over time (e.g., as the device performs different functions and / or enters different operating modes and / or operates under different environmental conditions). This can make it difficult to accurately assess the energy used by the device and the SOC of the battery at a given moment.

[0004] Existing techniques for assessing battery SOC may not be suitable or accurate enough for certain applications, and may use relatively much energy, which is not ideal for small-capacity batteries, such as those used in IoT devices. An improved approach may be needed. Summary of the invention

[0005] According to a first aspect of the present invention, there is provided a battery powered device, comprising: Batteries; and a voltage sensor configured to measure a terminal voltage of the battery; Wherein, the battery powered device is configured as follows: a) determine the current flowing into or out of the battery; b) predicting the terminal voltage of the battery using the current and the estimated state of charge of the battery; c) Use a voltage sensor to measure the actual terminal voltage of the battery; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating an estimated state of charge of the battery based on the comparison; and Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating state of the battery-powered device.

[0006] According to a second aspect of the present invention, there is provided a method for evaluating a charge state of a battery in a battery-powered device, the method comprising: a) determine the current flowing into or out of the battery; b) predicting the terminal voltage of the battery using the current and the estimated state of charge of the battery; c) Measure the actual terminal voltage of the battery; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating an estimated state of charge of the battery based on the comparison; and Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating state of the battery-powered device.

[0007] According to a third aspect of the invention there is provided computer software comprising instructions which, when executed by a processor of a battery powered device, cause the processor to: a) determine the current flowing into or out of a battery in a battery-powered device; b) predicting the terminal voltage of the battery using the current and the estimated state of charge of the battery; c) receiving data indicating an actual terminal voltage of the battery; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating an estimated state of charge of the battery based on the comparison; and Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating state of the battery-powered device.

[0008] Therefore, those skilled in the art will appreciate that, because steps (a)-(e) are dynamically repeated based on the operating state of the device, the battery's state of charge can be accurately estimated throughout the device's operation without using excessive power. In some embodiments, steps (a)-(e) are repeated at a time corresponding to a fixed repetition interval, where the repetition interval depends on the operating state of the battery-powered device. For example, when the device is operating in a state with high and / or varying current flow (e.g., drawing a high discharge current while actively performing radio communications), the device may repeat steps (a)-(e) to update its estimate of the state of charge more frequently, and when the device is operating in a state with a lower and / or more stable current flow (e.g., drawing a low discharge current during a lower power sleep mode), the device may repeat steps (a)-(e) less frequently.

[0009] In one set of embodiments, the battery powered device is configured to operate in a first operating state and a second operating state. The first operating state may correspond to an awake mode (e.g., in which the device performs one or more primary functions, such as data logging, data processing, or RF communication). The second operating state may correspond to a sleep mode (e.g., in which the primary functions of the battery powered device are not performed).

[0010] In one set of embodiments, steps (a)-(e) are repeated at a first rate when the battery powered device is in a first operating state. When the device is in the first operating state, the device may draw a high and / or less predictable current, which means that the estimated state of charge may need to be updated regularly.

[0011] In one set of embodiments, when the battery powered device is in the second operating state, steps (a)-(e) are repeated at a lower second rate. For example, in sleep mode, the device may be expected to draw very little current from the battery. When the device is in sleep mode, less frequent updates of the estimated state of charge of the battery may be acceptable because absolute changes in the battery SOC may be expected to be lower and / or more predictable.

[0012] In some embodiments, the device is configured to operate in one or more operating states in which steps (a)-(e) are not performed. For example, a battery-powered device may be configured not to repeat steps (a)-(e) when in a second operating state (e.g., sleep mode).

[0013] In some embodiments, steps (a)-(e) are repeated at a time corresponding to a transition between the first operating state and the second operating state. For example, the battery-powered device may perform steps (a)-(e) when (or shortly before or shortly after) the device transitions to the first operating state after operating in the second operating state for a period of time (e.g., when awakening from a sleep period). In embodiments where steps (a)-(e) are repeated when moving to the first state after a period of operation in the second state, the determined current may include current flowing into or out of the device during the period of operation in the second state (e.g., current drawn from a battery during a sleep mode prior to the current wake-up mode).

[0014] One or more times for repeating steps (a)-(e) may also be based on other considerations. For example, the performance of many batteries may change at different levels of state of charge. For example, when the state of charge of a battery is low (e.g., less than 10% of the theoretical full state of charge), it may exhibit an internal resistance that is significantly different from a battery in a fully charged state. This may result in increased uncertainty in the estimated state of charge. Therefore, in one set of embodiments, one or more times for repeating steps (a)-(e) are determined based on the estimated state of charge of the battery. The interval between repetitions may decrease monotonically with the estimated state of charge (i.e., if all other parameters remain unchanged). In other words, when the battery is estimated to have a lower state of charge, steps (a)-(e) may be repeated more regularly.

[0015] Battery performance may also be affected by temperature. In one set of embodiments, additionally or alternatively, one or more times to repeat steps (a)-(e) may be determined based on the temperature of the battery-powered device (e.g., the temperature of the battery). The interval between repetitions may decrease monotonically with temperature (i.e., if all other parameters remain constant). In other words, steps (a)-(e) may be repeated more regularly when the temperature is lower. The battery-powered device may include a temperature sensor that is configured to measure the temperature of the battery-powered device (e.g., the temperature of the battery).

[0016] The current may include current flowing into the battery (charging current) or current flowing out of the battery (discharging current). The current may include an average current flowing into or out of the battery since the state of charge of the battery was previously estimated (e.g., since the last time steps (a)-(e) were performed). The current may include an instantaneous current flowing into or out of the battery (e.g., when the state of charge was most recently estimated).

[0017] The initial estimate of the battery's state of charge (i.e., the first time steps (a)-(e) are performed) may include a predetermined state of charge (e.g., retrieved from a memory) or a state of charge calculated based on an initial set of battery parameters (e.g., calculated based on initial sensor measurements and / or assumptions).

[0018] In one set of embodiments, determining the current flowing into or out of the battery comprises measuring the current. Thus, the battery powered device may be arranged to determine the current flowing into or out of the battery by measuring the current flowing into or out of the battery. The battery powered device may comprise a current sensor arranged to measure the current flowing into or out of the battery. The current sensor may be arranged to measure the charging current and the discharging current.

[0019] However, it may be difficult to accurately measure the battery current in certain situations. For example, when a device uses a very small amount of current (e.g., in sleep mode), the current may be close to the noise floor of a current sensor that is sized to measure a larger operating current. Using a current sensor with a large dynamic range may be costly. In one set of embodiments, the current flowing into or out of the battery is determined based on an operating state of the battery-powered device. The inventors have recognized that under certain operating conditions, a device may experience a reasonably predictable current flow, which can be used to determine an estimate of the current without having to make a direct measurement.

[0020] In some embodiments, determining the current includes retrieving a stored current corresponding to an operating state of the battery powered device. Thus, the battery powered device may be configured to determine the current flowing into or out of the battery by retrieving a stored current corresponding to an operating state of the battery powered device from a memory (e.g., from an internal or external memory). The stored current may be an expected charge or discharge current for the operating state (e.g., based on design specifications and / or previously measured currents). In one set of embodiments, the current of the battery is estimated to be equal to the expected current for the operating state of the battery powered device. The current may be determined using a combination (e.g., a weighted sum) of the measured current and the stored current.

[0021] Different methods of determining the current may be used at different times, for example based on the operating state of the battery powered device. For example, the battery powered device may be configured to determine the current based solely or partially on the measured current during or after an operating period in a first operating state (e.g., a higher current mode such as an active mode). The battery powered device may be configured to determine the current based solely or partially on the operating state of the battery powered device during or after an operating period in a second operating state (e.g., a low current mode such as a sleep mode).

[0022] In one set of embodiments, predicting the terminal voltage includes (i.e., in addition to the current and the estimated state of charge of the battery, also) using the temperature of the battery-powered device, such as the temperature measured by a temperature sensor. As mentioned above, battery performance can also be affected by temperature, so it can be advantageous to consider temperature when predicting battery behavior.

[0023] Predicting the terminal voltage of the battery may include using a model of the battery. The model may include an equivalent circuit model (ECM). In some embodiments, the battery is modeled as an open circuit voltage connected in series with an internal resistance and at least one RC network. The model may include one or more parameters. These parameters may correspond to one or more physical properties of the battery (e.g., the size of the components in the internal resistance and / or the RC network) and / or one or more operating conditions (e.g., temperature). The one or more parameters may be estimates of the physical properties of the battery. The battery-powered device may be configured to retrieve one or more parameters of the battery model from a memory (e.g., from an internal or external memory). For example, one or more parameters may be retrieved by looking up one or more parameters corresponding to the current operating conditions and / or physical properties of the battery.

[0024] The battery powered device may be arranged to determine one or more parameters of the model. The battery powered device may be arranged to determine one or more parameters of the model by simply retrieving one or more stored parameters and / or by modifying one or more stored parameters (e.g., by interpolating between and / or extrapolating from stored parameters).

[0025] One or more parameters of the model may be determined based on battery characterization information (e.g., determined from characterization tests performed for various battery chemistries and at various battery temperatures). For example, one or more parameters of the model may be determined based on the chemistry of the battery. One or more parameters of the model may be determined based on the temperature of the battery. One or more parameters of the model may be determined based on an estimated state of charge of the battery. In some embodiments, one or more parameters of the model may be determined by interpolating stored parameters (e.g., if the current battery temperature falls between two temperatures tested in the characterization test).

[0026] In one set of embodiments, one or more parameters of the model (e.g., internal resistance) may be determined using one or more values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery. For example, the device may be arranged to determine one or more parameters of the model using an instantaneous determination of the current flowing into or out of the battery and / or an instantaneous measurement of the actual terminal voltage.

[0027] However, using a single instantaneous value of voltage and / or current to determine one or more parameters may not be sufficiently accurate or reliable. Therefore, in one set of embodiments, the device is configured to use multiple values ​​of current flowing into or out of the battery and / or the actual terminal voltage to determine one or more parameters of the model. For example, the device may be configured to determine (or estimate) the change of the terminal voltage and / or current over time (e.g., the voltage and / or current time gradient), and use the determined change to determine one or more parameters of the model.

[0028] The apparatus may be arranged to determine a change between the current and / or the measured terminal voltage determined at a current iteration of steps (a)-(e) and a previous iteration (eg a previous iteration of steps (a)-(e)).

[0029] In one set of embodiments, the model includes an internal resistance parameter (e.g., an estimate of the internal resistance of the battery). In such embodiments, the device may be arranged to determine the internal resistance parameter by dividing a terminal voltage value (e.g., an instantaneous terminal voltage measurement or a change in terminal voltage) by a current value (e.g., an instantaneous current or a change in current). In other words, the device may be arranged to determine the internal resistance using the voltage value and the current value according to Ohm's law.

[0030] Using values ​​of actual terminal voltage and / or battery current to determine one or more parameters of a model may be useful in situations where other methods for determining parameters of the model are unavailable or unreliable. For example, battery characterization information may not be available or reliable for all conditions under which a battery-powered device operates. For example, at low temperatures (e.g., near or below 0°C), the internal resistance of many batteries may become extremely nonlinear, thereby reducing the usefulness of previously stored characterization test results.

[0031] Instantaneous measurements of voltage and / or current may have large uncertainties, which may cause noise in the determined parameters. Therefore, in some embodiments, the device is configured to adjust the value of the voltage and / or current before using the value of the voltage and / or current to determine one or more parameters. For example, the device can be configured to filter out one or more values ​​of the voltage and / or current, that is, only use the values ​​of the voltage and / or current that meet one or more filtering criteria to determine one or more parameters. For example, the device can be configured to only use current and / or voltage values ​​that are within an expected (e.g., practical) range (e.g., within an expected distance of a previous current and / or voltage value).

[0032] One or more parameters of the model may change between repetitions of steps (a)-(e), for example as the temperature and / or the estimated state of charge changes. In other words, predicting the terminal voltage of the battery may be performed in different ways at different times. The battery-powered device may be configured to update one or more parameters of the model based on a comparison between the predicted terminal voltage and the actual terminal voltage. For example, if the difference between the predicted terminal voltage and the actual terminal voltage is greater than a threshold value (e.g. >100 mV), the model may be updated. One or more parameters of the model may be updated based on the estimated state of charge. For example, if the estimated state of charge drops below a threshold value (e.g. 20%), the model may be updated. The threshold may correspond to a state of charge where battery nonlinearity dominates.

[0033] In some embodiments, one or more parameters (e.g., internal resistance) of the model are updated by using updated values ​​for the terminal voltage of the battery and / or the current flowing into or out of the battery. In other words, the device can be configured to repeatedly determine one or more parameters using one or more values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery, i.e., updating the determined parameters as the voltage and current values ​​change.

[0034] In some embodiments, the device is configured to adjust the parameters determined using the values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery before using the values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery in the model. For example, the device can be configured to filter out one or more of the determined parameters. For example, the device can be configured to use in the model only those parameter values ​​that are within an expected (e.g., practical) range of previous values ​​of the parameter.

[0035] Additionally or alternatively, the device may be configured to use a moving average of one or more determined parameters in the model. The moving average may include a simple moving average (i.e., an unweighted average of a fixed number of recent parameter values). Alternatively, the moving average includes a weighted moving average, in which different weights are applied to different determinations of the parameter. For example, updated values ​​of a parameter may be weighted more highly than earlier values. In one set of embodiments, the device is configured to use an exponential moving average of the parameter in the equivalent circuit battery model (i.e., in which the weight applied to the parameter value decreases exponentially as the parameter value ages). In one set of embodiments, the device is configured to use a double exponential moving average (DEMA) of the parameter in the equivalent circuit battery model.

[0036] In one set of embodiments, the device is arranged to set the parameters of the model in different ways at different times. For example, under a first set of operating conditions (e.g., when the temperature is in a first temperature range and / or the state of charge is in a first state of charge range), the device may be arranged to retrieve one or more parameters of the battery model from a memory. Under a second set of operating conditions (e.g., when the temperature is in a second temperature range and / or the state of charge is in a second state of charge range), the device may be arranged to determine one or more parameters of the model using one or more values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery.

[0037] For example, the inventors have recognized that at low temperatures, previously stored characteristic information of the internal resistance of the battery may be unavailable, unreliable, or inaccurate. Therefore, in one set of embodiments, the device is configured to retrieve the internal resistance parameters of the model from the memory when the temperature is above a temperature threshold. Conversely, the device may be configured to determine the internal resistance parameters of the model using one or more values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery (e.g., using Ohm's law) when the temperature is below the temperature threshold. The temperature threshold may be 0°C or close to 0°C (e.g., between -15°C and +15°C, between -10°C and +10°C, between -5°C and +5°C, or between -2°C and +2°C).

[0038] The device may include one or more sensors (e.g., temperature sensors) arranged to detect whether the device is in a first set of operating conditions or a second set of operating conditions (e.g., whether the temperature is below or above a threshold). The sensor may control the manner in which one or more parameters are set by the device based on said detection.

[0039] A model may have an associated modeling uncertainty (i.e., modeling noise). This may reflect the quality of the model. The battery powered device may be configured to estimate the modeling noise. The battery powered device may be configured to update an estimate of the modeling noise (e.g., if the predicted terminal voltage differs significantly from the actual terminal voltage and / or if the estimated state of charge drops below a threshold). The estimate of the modeling noise may be used when predicting the terminal voltage of the battery and / or updating the estimated state of charge of the battery.

[0040] Sensor measurements used in some embodiments (e.g., terminal voltage, current, and / or temperature) may have associated measurement uncertainties (i.e., measurement noise). The battery powered device may be configured to estimate the measurement noise associated with one or more sensor measurements. The battery powered device may be configured to update an estimate of the measurement noise (e.g., if the predicted terminal voltage is significantly different from the actual terminal voltage and / or if the estimated state of charge is below a threshold). The estimate of the measurement noise may be used when predicting the terminal voltage of the battery and / or when updating the estimated state of charge of the battery.

[0041] In some embodiments, steps (a)-(e) include a Kalman filter algorithm. Some embodiments may use an extended Kalman filter algorithm (ie, a nonlinear Kalman filter) to estimate the state of charge of the battery. The state of charge of the battery may include state variables in the Kalman filter algorithm.

[0042] In some embodiments, the battery is a rechargeable battery, such as a nickel-cadmium battery, a nickel-metal hydride battery, or a lithium-ion battery. It is recognized that the present invention may be particularly applicable to batteries with relatively small capacities. The battery may include a nominal capacity of 10 Wh or less, such as 5 Wh or less, 1 Wh or less, 0.5 Wh or less, or even 0.1 Wh or less. The battery may have a nominal no-load terminal voltage of less than 20 V, less than 10 V, or less than 5 V (e.g., 3.7 V or 3.8 V).

[0043] The battery powered device may include a processor. The battery powered device may include a memory storing software instructions that, when executed by the processor, cause the processor to perform one or more of steps (a)-(e). The processor may also be configured to perform one or more other functions of the battery powered device (e.g., application functions such as RF communication).

[0044] One or more sensors (e.g., voltage sensors, current sensors, and / or temperature sensors) of the battery-powered device may be analog sensors, i.e., arranged to generate an analog signal indicative of a sensed measurement (e.g., voltage, current, or temperature). Additionally or alternatively, one or more sensors of the battery-powered device may be digital sensors, arranged to generate a digital signal indicative of a sensed measurement.

[0045] The processor may be configured to receive signals directly from one or more sensors (e.g., from a voltage sensor, a current sensor, and / or a temperature sensor). In some embodiments, in addition or alternatively, the battery-powered device includes a power management integrated circuit (PMIC) configured to receive signals from one or more sensors and send the signals or information obtained from the signals to the processor. In one set of embodiments, the PMIC is configured to receive signals from a voltage sensor and send the signals or terminal voltage information obtained from the signals to the processor. For example, the PMIC may include one or more analog-to-digital converters configured to convert analog signals generated by one or more sensors into digital signals that can be processed by the processor. In other words, the PMIC can act as a sensor interface.

[0046] Features of any aspect or embodiment described herein may be applied to any other aspect or embodiment described herein where appropriate.When different embodiments are mentioned, it should be understood that these embodiments are not necessarily different, but may overlap. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] One or more non-limiting examples will now be described, by way of example only, and with reference to the accompanying drawings, in which: Figure 1 A battery powered device according to an embodiment of the present invention is shown; Figure 2 is a block diagram of an equivalent circuit model for an embodiment of the present invention; and Figure 3 It shows the evaluation Figure 1 A flow chart of a method for determining a charge status of a battery in a battery-powered device. DETAILED DESCRIPTION

[0048] The battery powered device 100 includes a battery 102 , a microprocessor 104 , a memory 105 , a voltage sensor 106 , a current sensor 108 , a temperature sensor 110 , and a power management integrated circuit (PMIC) 112 . The battery 102 provides power to the battery powered device 100 .

[0049] The voltage sensor 106 senses the terminal voltage V of the battery 102. The current sensor 108 senses the instantaneous current I flowing into or out of the battery 102. The temperature sensor 110 senses the temperature T of the battery 102. The voltage sensor 106, the current sensor 108, and the temperature sensor 110 are connected to the PMIC 112, which converts the sensed information into digital measurement data (e.g., using one or more analog / digital converters (ADCs)). The PMIC 112 sends the measurement data to the microprocessor 104.

[0050] The battery powered device 100 is operable in an awake mode, in which the microprocessor 104 controls various normal device functions, such as data collection or RF communications. The device 100 is also operable in a sleep mode, in which many normal device functions are suspended to conserve power.

[0051] One of the functions performed by the microprocessor 104 is to estimate the state of charge (SOC) of the battery 102 using measurements from the sensors 106 , 108 , 110 and a model of the battery 102 .

[0052] The model of the battery 102 used by the microprocessor 104 is Figure 2 . In the model, the battery 102 includes a voltage source 202 having an open circuit voltage OCV. OCV is a function of the charge state Z of the battery 102 and the current temperature T that varies with time. The model of the battery 102 also includes an internal series resistor 204 having a resistance R0, a first RC element 206, and a second RC element 208. The internal series resistor 204 models the instantaneous polarization of the battery voltage, while the first RC element 206 and the second RC element 208 model the diffusion voltage characteristics of the battery 102. The first RC element 206 includes a first resistor 210 having a resistance R1, connected in parallel with a first capacitor 212 having a capacitance C1. Similarly, the second RC element 208 includes a second resistor 214 having a resistance R2, connected in parallel with a second capacitor 216 having a capacitance C2. The resistance and capacitance of the RC elements 206, 208 and the OCV function are selected based on characteristic tests performed at different temperatures.

[0053] The battery current flowing through the internal series resistor 204 is I(t) (this can be positive or negative, depending on whether it is a discharge current or a charge current). The currents flowing through the first resistor 210 and the second resistor 214 are I(t) and I(t) respectively. R1 (t) and I R2 (t). The terminal voltage of the battery 102 is V(t).

[0054] The microprocessor 104 uses an extended Kalman filter technique to estimate the state of charge of the battery 102. In the following equation, Z[N] is the battery state of charge at time step N, Δt is the length of each time step, Q(T) is the total battery capacity at temperature T, β is the Faraday efficiency, and I[N] is the current flowing into or out of the battery at time step N.

[0055] The charge state at time step N+1 is given as: At time step N+1, the current flowing through the first resistor 210 and the second resistor 214 is: The voltage at the modeled terminal at time step N depends on the value of the state vector equation: Now refer to Figure 3 The flowchart 300 in FIG. 1 explains the operation of the battery powered device 100 for estimating the state of charge of the battery 102. The battery powered device 100 estimates the state of charge of the battery 102 using an extended Kalman filter method.

[0056] In a first iteration of the method 300 , in an initial step 302 , an initial terminal voltage V0 is measured using the voltage sensor 106 , an initial current I0 is measured using the current sensor 108 , and a battery temperature T is measured using the temperature sensor 110 . The microprocessor 104 retrieves battery parameter values ​​associated with the battery temperature T (e.g., resistance and capacitance of the RC elements 206 , 208 ) from the memory 105 .

[0057] An initial estimate of the open circuit voltage OCV0 of the battery 102 is calculated according to OCV0=V0+R0(T)I0. Using a lookup table stored in the memory 105, the microprocessor 104 determines an initial estimate of the battery SOC Z0 based on OCV0 and T. The microprocessor 104 also retrieves expected measurement and modeling noise values ​​(i.e., uncertainties) from the memory 105. If the battery parameters and / or initial state of charge are not available for exact values ​​of OCV0 and T, the microprocessor 104 can interpolate between the stored data.

[0058] In step 304, at time step N, a prediction of the state of charge of the battery 102 is calculated. In a first iteration, the predicted SOC Z[N] is calculated using the initial estimated SOC Z0 of the battery determined in step 302. In subsequent iterations, step 304 may involve updating model parameters and then calculating a prediction of Z[N] based on the previous state estimate and the updated model (explained in more detail below).

[0059] In step 306 , the state covariance of the predicted SOC Z[N] is calculated based on Z[N] and measurement and modeling uncertainties.

[0060] In step 308, the device determines the current I (i.e., the charging or discharging current) flowing into or out of the battery 102. When the device 100 is operating in the awake mode (and not charging), it determines the current by measuring the current I flowing out of the battery 102 using the current sensor 108. When the device 100 has just transitioned from the sleep mode to the awake mode, a predetermined sleep current is used as the current I. This can be more accurate than actively measuring the low current used during sleep.

[0061] In step 310, the microprocessor 104 uses the current I and Z[N] in equations (2)-(4) to predict the terminal voltage V est [N].

[0062] In step 312, the Kalman gain is calculated based on the measurement and modeling uncertainties and the state covariance.

[0063] In step 314, the voltage sensor 106 is used to measure the actual terminal voltage V actual [N].

[0064] In step 316, the actual terminal voltage V actual [N] and predicted terminal voltage V est [N] is compared. This is used together with the Kalman gain to generate an updated state estimate of SOC Z[N]. In step 318, the device calculates an updated estimate of the state covariance.

[0065] In step 320 , the device waits until the next iteration of the method starts. The next iteration of the method starts at a time that depends on the operating state of the device 100 .

[0066] In the awake mode, the SOC estimation method 300 is repeated at a fixed rate, such as once per second. The SOC estimation process 300 is not performed when the device 100 is in the sleep mode, but is performed when the device 100 next transitions from the sleep mode to the awake mode.

[0067] In step 322 , the next iteration of the method begins at time step N+1 (e.g., because a fixed interval has passed in the awake mode, or because the device has just transitioned from the sleep mode to the awake mode). The device makes a new temperature measurement T using the temperature sensor 110 and retrieves the battery parameter value associated with the battery temperature T from the memory 105 .

[0068] The device may also update various aspects of the filter in step 322. For example, when the previously estimated state of charge Z[N] is below a certain threshold (e.g., 25%), or when the measured terminal voltage V actual [N] and the terminal voltage V predicted in the previous iteration est When [N] is significantly different, device 100 can update the modeling and measurement uncertainties.

[0069] In step 304, the apparatus 100 calculates an updated prediction of SOC Z[N+1] using the updated model parameters. The remainder of the process then repeats as described above.

[0070] Thus, device 100 maintains an accurate estimate of the state of charge of battery 102 throughout operation while still conserving energy in sleep mode.

[0071] In the above example, the parameter values ​​used in the model of battery 102 are determined based on the characterization test results that are predetermined and stored in memory 105. However, in some examples, device 100 operates in a temperature range where appropriate characterization test information is not available or reliable. For example, at low or negative temperatures (i.e., temperatures below 0°C), the internal resistance of many batteries may become extremely nonlinear, thereby reducing the usefulness of previously stored characterization test results.

[0072] Therefore, in another example, the microprocessor 104 is configured to set some parameter values ​​of the model differently at different temperatures.

[0073] When the temperature is higher than a threshold value (eg, 0° C.), the microprocessor 104 retrieves parameter values ​​(including the internal resistance R0 ) corresponding to appropriate characteristic test results for the current temperature T from the memory 105 (ie, the above-described method).

[0074] However, when the temperature is below the threshold, the temperature sensor 110 triggers the microprocessor 104 to set the internal resistance R0 of the model in a different manner. When the temperature is below the threshold, at time t, the microprocessor 104 uses the battery terminal voltage V measured by the voltage sensor 106 and the current I measured by the current sensor 108 to calculate the internal resistance R0(t) of the battery 102 (i.e., dynamically determine R0). The internal resistance R0(t) at time t is calculated based on the changes in the voltage and current measured in a short time window between the previous time t-1 and the current time t:

[0075] This estimate of the internal resistance R0 may not be as accurate as an estimate determined from a characterization test at a higher temperature, but this approach allows the battery model and the remaining methods to be used even when a predetermined characterization test is unavailable or unreliable. The remaining operations of the battery-powered device 100 to estimate the state of charge of the battery 102 continue as described above, with the internal resistance R0 used in the model being updated appropriately based on the temperature and the measured current and voltage. In some examples, a moving average (e.g., a double exponential moving average or DEMA) of the internal resistance R0 is used in the model.

[0076] Although the present invention has been described in detail in conjunction with only a limited number of embodiments, it should be readily understood that the present invention is not limited to these disclosed embodiments. On the contrary, the present invention may be modified to include any number of variants, changes, substitutions, or equivalent arrangements that have not been described heretofore but are commensurate with the scope of the present invention. In addition, although various embodiments of the present invention have been described, it should be understood that various aspects of the present invention may include only some of the embodiments described. Therefore, the present invention should not be considered to be limited by the foregoing description, but only by the scope of the appended claims.

Claims

1. A battery-powered device comprising: Battery; and a voltage sensor configured to measure a terminal voltage of the battery; Wherein, the battery powered device is configured as: a) determining the current flowing into or out of the battery; b) predicting a terminal voltage of the battery using the current and an estimated state of charge of the battery; c) measuring the actual terminal voltage of the battery using the voltage sensor; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating the estimated state of charge of the battery based on the comparison; and Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating status of the battery-powered device.

2. A battery powered device according to claim 1, arranged to operate in a first operating state and a second operating state, the first operating state corresponding to an awake mode and the second operating state corresponding to a sleep mode.

3. A battery-powered device according to claim 2, which is configured to: repeat steps (a)-(e) at a first rate when the battery-powered device is in the first operating state; and repeat steps (a)-(e) at a lower second rate when the battery-powered device is in the second operating state.

4. A battery powered device according to claim 2 or 3, arranged to repeat steps (a) to (e) at times corresponding to transitions between the first and second operating states.

5. A battery powered device according to any preceding claim, arranged to operate in one or more operating states in which steps (a) to (e) are not performed.

6. A battery powered device according to any preceding claim, wherein: The one or more times for repeating steps (a)-(e) are determined based on the estimated state of charge of the battery.

7. A battery powered device according to any preceding claim, comprising a temperature sensor arranged to measure the temperature of the battery powered device.

8. A battery powered device according to any preceding claim, wherein: The one or more times for repeating steps (a)-(e) are determined based on a temperature of the battery powered device.

9. A battery powered device according to any preceding claim, comprising a current sensor arranged to measure current flowing into or out of the battery.

10. A battery powered device according to any preceding claim, arranged to determine the current flowing into or out of the battery by measuring the current flowing into or out of the battery.

11. A battery powered device as claimed in any preceding claim, arranged to determine the current flowing into or out of the battery by retrieving a stored current corresponding to an operating state of the battery powered device.

12. A battery powered device as claimed in any preceding claim arranged to use the temperature of the battery powered device to predict the terminal voltage of the battery.

13. A battery powered device according to any preceding claim, arranged to predict the terminal voltage of the battery using an equivalent circuit model of the battery.

14. A battery powered device according to claim 13, arranged to retrieve one or more parameters of the model from a memory.

15. A battery powered device according to claim 13 or 14, arranged to use one or more values ​​of the actual terminal voltage of the battery and / or the current flowing into or out of the battery to determine one or more parameters of the model.

16. A battery powered device according to claim 15, arranged to: determine a change in terminal voltage and / or current over time; and use the determined change to determine one or more parameters of the model.

17. A battery-powered device according to claim 15 or 16, which is configured to: repeatedly determine one or more parameters using one or more values ​​of the terminal voltage of the battery and / or the current flowing into or out of the battery; and use a moving average of one or more determined parameters in the model.

18. A battery powered device according to any one of claims 13 to 17, wherein: In a first set of operating conditions, the apparatus is arranged to retrieve one or more parameters of the model from a memory; and Under a second set of operating conditions, the apparatus is arranged to determine one or more parameters of the model using one or more values ​​of the terminal voltage of the battery and / or the current flowing into or out of the battery.

19. The battery powered device of claim 18, wherein: The model includes an internal resistance parameter; and The device is configured to: When the temperature is higher than a temperature threshold, retrieving an internal resistance parameter of the model from a memory; as well as When the temperature is lower than the temperature, an internal resistance parameter of the model is determined using one or more values ​​of an actual terminal voltage of the battery and / or the current flowing into or out of the battery.

20. The battery powered device of claim 19, wherein: The temperature threshold is between -5°C and +5°C.

21. A battery powered device according to any one of claims 13 to 20, arranged to update one or more parameters of the model based on a comparison between a predicted terminal voltage and the actual terminal voltage.

22. A battery powered device according to any one of claims 13 to 21, wherein: Steps (a)-(e) include a Kalman filter algorithm.

23. A battery powered device according to any preceding claim, comprising a processor and memory storing software instructions which, when executed by the processor, cause the processor to perform one or more of steps (a) to (e).

24. The battery powered device of claim 23, wherein: The processor is configured to perform one or more other functions of the battery powered device.

25. A battery powered device according to claim 23 or 24, comprising a power management integrated circuit, the power management integrated circuit being arranged to receive a signal from the voltage sensor and to send the signal or terminal voltage information obtained from the signal to the processor.

26. A battery powered device according to any preceding claim, wherein: The battery is a rechargeable battery.

27. A method for evaluating a state of charge of a battery in a battery powered device, the method comprising: a) determining the current flowing into or out of the battery; b) predicting a terminal voltage of the battery using the current and an estimated state of charge of the battery; c) measuring the actual terminal voltage of the battery; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating the estimated state of charge of the battery based on the comparison; as well as Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating status of the battery-powered device.

28. Computer software comprising instructions which, when executed by a processor of a battery powered device, cause the processor to: a) determining the current flowing into or out of a battery of said battery powered device; b) predicting a terminal voltage of the battery using the current and an estimated state of charge of the battery; c) receiving data indicative of an actual terminal voltage of said battery; d) comparing the predicted terminal voltage with the actual terminal voltage; e) updating the estimated state of charge of the battery based on the comparison; as well as Steps (a)-(e) are repeated at one or more subsequent times, the one or more subsequent times being determined based on an operating status of the battery-powered device.

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