CN111398827A - Ambient temperature prediction method, battery temperature prediction method and electric quantity calculation method - Google Patents
Ambient temperature prediction method, battery temperature prediction method and electric quantity calculation method Download PDFInfo
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- CN111398827A CN111398827A CN202010192650.6A CN202010192650A CN111398827A CN 111398827 A CN111398827 A CN 111398827A CN 202010192650 A CN202010192650 A CN 202010192650A CN 111398827 A CN111398827 A CN 111398827A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K7/00—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements
- G01K7/16—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using resistive elements
- G01K7/22—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using resistive elements the element being a non-linear resistance, e.g. thermistor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
Abstract
The present disclosure provides an ambient temperature prediction method, including: acquiring the initial time of the battery in the current temperature environment, the initial temperature of the surface of the battery, the final time when the surface temperature of the battery reaches the stable temperature in the current temperature environment and the stable temperature of the surface of the battery; calculating the average heating power of the internal resistance of the battery within the time length at least based on the time length from the initial time to the final time; obtaining the battery temperature variation caused by the heating of the internal resistance of the battery at least based on the average heating power of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based on the initial temperature of the surface of the battery, the stable temperature of the surface of the battery and the temperature variation of the battery caused by the heat generation of the internal resistance of the battery. The disclosure also provides a battery temperature prediction method, a battery electric quantity calculation method, a battery management system and an electronic device.
Description
Technical Field
The present disclosure relates to an ambient temperature prediction method, a battery temperature prediction method, an electric quantity calculation method, a battery management system, and an electronic device, and is particularly suitable for temperature prediction of a lithium battery and electric quantity calculation of the lithium battery.
Background
In personal consumer electronics devices, such as mobile devices like cell phones, wireless headsets, etc., energy sources are usually provided by various chemical energy batteries. During the moving process of such mobile devices, the working environment of the mobile device may be in a drastic change process, including natural environment such as temperature, humidity, pressure, etc., and fluctuation of the load of the mobile device.
Since temperature has a strong influence on the characteristics of batteries, especially lithium batteries. Therefore, it is very important for the battery capacity calculation method to accurately predict the temperature change of the battery during operation.
In practical use, for example, in winter, the difference between indoor and outdoor temperatures is very large, the indoor temperature is generally 25 ℃, and the outdoor environment may exist from 0 ℃ to-40 ℃ according to the respective conditions, and the battery temperature of the mobile device is influenced not only by the characteristics of the mobile device and the heating of the load, but also by sudden environmental changes in two distinct temperature environments, which causes the prediction of the battery temperature based on the existing battery model of the gauge algorithm (gauge algorithm) to deviate, and thus causes the deviation of the battery capacity calculation. Accurate prediction of the temperature change of the battery is directly related to the accuracy of the battery power calculation method.
Existing battery models based on a gauge algorithm (gauge algorithm) are based on the behavior of the open circuit voltage at different temperatures based on the characteristics of the battery itself. During the charging and discharging processes, when a current flows through the inside of the battery due to the internal impedance inside the battery, heat is generated, which directly affects the change of the characteristics of the battery. The general electric quantity calculation method only considers the temperature rise caused by the heat generation of the charging and discharging current on the internal impedance of the battery, but lacks the influence on the temperature change of the battery caused by the change of the environmental temperature. However, a drastic change in the ambient temperature is much more rapid than a change in the battery temperature due to heat generation due to impedance inside the battery. Particularly under low temperature conditions, the internal resistance of the battery also varies greatly with the overall change in temperature.
Disclosure of Invention
In order to solve at least one of the above technical problems, the present disclosure provides an ambient temperature prediction method, a battery temperature prediction method, an electric quantity calculation method, a battery management system, and an electronic device.
The environmental temperature prediction method, the battery temperature prediction method, the electric quantity calculation method, the battery management system and the electronic device are realized through the following technical scheme.
According to an aspect of the present disclosure, there is provided an ambient temperature prediction method including: acquiring the initial time of the battery in the current temperature environment, the initial temperature of the surface of the battery, the final time when the surface temperature of the battery reaches the stable temperature in the current temperature environment and the stable temperature of the surface of the battery; calculating the average heating power of the internal resistance of the battery within the time length at least based on the time length from the initial time to the final time; obtaining the battery temperature variation caused by the heating of the internal resistance of the battery at least based on the average heating power of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based on the initial temperature of the surface of the battery, the stable temperature of the surface of the battery and the temperature variation of the battery caused by the heat generation of the internal resistance of the battery.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the battery surface initial temperature and the battery surface stable temperature are measured by the temperature sensor.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the average heating power of the internal resistance of the battery over the time period is calculated based on at least the internal resistance value of the battery over the time period.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, obtaining the temperature of the current temperature environment based on the battery surface initial temperature, the battery surface stable temperature, and the battery temperature variation amount caused by the heat generation of the battery internal resistance, includes: calculating a battery surface temperature variation amount within a time length based on the battery surface initial temperature and the battery surface stabilization temperature; calculating the difference value of the battery surface temperature variation and the battery temperature variation caused by the heating of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based at least on the difference.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the output voltage of the battery and the surface temperature are measured in real time or at a predetermined time period within a time length; the internal resistance value of the battery within the time period is calculated based on at least the output voltage of the battery and the surface temperature measured in real time or at a predetermined time period.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the output current of the battery is also measured in real time or at a predetermined time period within a time length; calculating an average output power of the battery over a length of time based on the output voltage and the output current of the battery measured in real time or at a predetermined time period; and calculating the average heating power of the internal resistance of the battery within the time length at least based on the average output power of the battery, the output voltage of the battery measured in real time or in a preset time period and the internal resistance value of the battery within the time length.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, obtaining the temperature of the current temperature environment based on at least the difference value includes: the relationship of the difference value to the temperature of the current environment is obtained based on the second law of thermodynamics and a heat transfer model of the battery.
According to still another aspect of the present disclosure, there is provided an ambient temperature prediction method including: acquiring the time length of the surface temperature of the battery changing from a first stable temperature to a second stable temperature; calculating the average heating power of the internal resistance of the battery within the time length; obtaining the battery temperature variation caused by the heating of the internal resistance of the battery at least based on the average heating power of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based on the first stable temperature, the second stable temperature and the battery temperature variation caused by the heat generation of the internal resistance of the battery.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the first stable temperature is a battery surface stable temperature at which the battery is in a first temperature environment, and the second stable temperature is a battery surface stable temperature at which the battery is in a second temperature environment.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the first stable temperature and the second stable temperature are measured by a temperature sensor.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the average heating power of the internal resistance of the battery over the time period is calculated based on at least the internal resistance value of the battery over the time period.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, obtaining the temperature of the current temperature environment based on the first stable temperature, the second stable temperature, and the amount of change in the battery temperature caused by heat generation of the internal resistance of the battery, includes: calculating a battery surface temperature variation amount within a time length based on the first and second stable temperatures; calculating the difference value of the battery surface temperature variation and the battery temperature variation caused by the heating of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based on the difference.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the output voltage of the battery and the surface temperature are measured in real time or at a predetermined time period within a time length; the internal resistance value of the battery within the time period is calculated based on at least the output voltage of the battery and the surface temperature measured in real time or at a predetermined time period.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, the output current of the battery is also measured in real time or at a predetermined time period within a time length; calculating an average output power of the battery over a length of time based on the output voltage and the output current of the battery measured in real time or at a predetermined time period; and calculating the average heating power of the internal resistance of the battery within the time length at least based on the average output power of the battery, the output voltage of the battery measured in real time or in a preset time period and the internal resistance value of the battery within the time length.
According to the ambient temperature prediction method of at least one embodiment of the present disclosure, obtaining the temperature of the current temperature environment based on at least the difference value includes: the relationship of the difference value to the temperature of the current environment is obtained based on the second law of thermodynamics and a heat transfer model of the battery.
According to still another aspect of the present disclosure, there is provided a battery temperature prediction method including: obtaining the temperature of the current temperature environment by using any one of the environmental temperature prediction methods; and calculating a temperature trend of the battery based on at least the temperature of the current temperature environment.
According to still another aspect of the present disclosure, there is provided a battery power calculation method including: predicting the temperature trend of the battery by using the battery temperature prediction method; and calculating a charge trend of the battery based at least on the temperature trend of the battery.
According to still another aspect of the present disclosure, there is provided a battery management system including: a measuring device that measures at least an output voltage of the battery, an output current of the battery, and a surface temperature of the battery; and a processing device that executes any one of the above-described ambient temperature prediction method, the above-described battery temperature prediction method, and/or the above-described battery level calculation method, based on at least the output voltage of the battery, the output current of the battery, and the surface temperature of the battery measured by the measuring device.
According to still another aspect of the present disclosure, there is provided an electronic device including the battery management system described above.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
Fig. 1 is a temperature diagram of two different temperature environments.
Fig. 2 is a schematic diagram of a battery in any situation that may be charging or discharging throughout the rapid movement of a mobile device from one temperature environment area to another.
Fig. 3 is a graph showing the temperature change of the battery itself throughout the movement of the mobile device from one temperature environment region to another.
Fig. 4 is a discharge curve of a battery under a varying temperature environment in a state where the battery is discharged.
Fig. 5 is a graph of the internal resistance of a battery as a function of depth of discharge (DOD) at temperatures of 0 c and 25 c.
Fig. 6 is a schematic diagram of the structure of a preferred battery management system.
Fig. 7 is a simple thermal model of the battery.
Fig. 8 is a heat transfer model of a battery.
Fig. 9 is a battery temperature change curve considering only the internal impedance of the battery during charging and discharging.
Fig. 10 is a schematic flow diagram of an ambient temperature prediction method according to an embodiment of the present disclosure.
Fig. 11 is a flow chart diagram of an ambient temperature prediction method according to yet another embodiment of the present disclosure.
Description of the reference numerals
100 battery management system
10 group battery
11 cell
11A capacitor
11B internal resistance
11C external resistor
12 negative temperature coefficient resistor
20 analog front end chip
21 analog switch
22 buffer
23 analog-to-digital converter
24 communication interface
25 coulometer
26 switch decoding circuit
27 controller
28 random volatile memory
29 nonvolatile memory
31 drive circuit
32 voltage regulator
41 sampling resistor
42 fuse
43 charging MOSFET
44 discharge MOSFET
50 microcontroller
61 data line
62 control line
63 control signal
64 control signal
65 measuring line
66A differential line
66B differential line
200 mobile device
300 outside environment.
Detailed Description
The present disclosure will be described in further detail with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limitations of the present disclosure. It should be further noted that, for the convenience of description, only the portions relevant to the present disclosure are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. Technical solutions of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Unless otherwise indicated, the illustrated exemplary embodiments/examples are to be understood as providing exemplary features of various details of some ways in which the technical concepts of the present disclosure may be practiced. Accordingly, unless otherwise indicated, features of the various embodiments may be additionally combined, separated, interchanged, and/or rearranged without departing from the technical concept of the present disclosure.
The use of cross-hatching and/or shading in the drawings is generally used to clarify the boundaries between adjacent components. As such, unless otherwise noted, the presence or absence of cross-hatching or shading does not convey or indicate any preference or requirement for a particular material, material property, size, proportion, commonality between the illustrated components and/or any other characteristic, attribute, property, etc., of a component. Further, in the drawings, the size and relative sizes of components may be exaggerated for clarity and/or descriptive purposes. While example embodiments may be practiced differently, the specific process sequence may be performed in a different order than that described. For example, two processes described consecutively may be performed substantially simultaneously or in reverse order to that described. In addition, like reference numerals denote like parts.
When an element is referred to as being "on" or "on," "connected to" or "coupled to" another element, it can be directly on, connected or coupled to the other element or intervening elements may be present. However, when an element is referred to as being "directly on," "directly connected to" or "directly coupled to" another element, there are no intervening elements present. For purposes of this disclosure, the term "connected" may refer to physically, electrically, etc., and may or may not have intermediate components.
For descriptive purposes, the present disclosure may use spatially relative terms such as "below … …," below … …, "" below … …, "" below, "" above … …, "" above, "" … …, "" higher, "and" side (e.g., "in the sidewall") to describe one component's relationship to another (other) component as illustrated in the figures. Spatially relative terms are intended to encompass different orientations of the device in use, operation, and/or manufacture in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "below" or "beneath" other elements or features would then be oriented "above" the other elements or features. Thus, the exemplary term "below … …" can encompass both an orientation of "above" and "below". Further, the devices may be otherwise positioned (e.g., rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, when the terms "comprises" and/or "comprising" and variations thereof are used in this specification, the presence of stated features, integers, steps, operations, elements, components and/or groups thereof are stated but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof. It is also noted that, as used herein, the terms "substantially," "about," and other similar terms are used as approximate terms and not as degree terms, and as such, are used to interpret inherent deviations in measured values, calculated values, and/or provided values that would be recognized by one of ordinary skill in the art.
Fig. 1 is a temperature diagram of two different temperature environments, and fig. 1 shows a temperature transition region existing between two temperature environment regions (i.e., region one and region two).
Fig. 2 is a schematic diagram of a battery in any situation that may be charged or discharged throughout the rapid movement of a mobile device from one temperature environment area to another. In fig. 2, curve 1 is the ambient temperature variation curve.
As shown in fig. 1 and 2, mobile devices are generally moved in different places due to their portability. In some scenarios, the environment varies greatly between different locations. Such environmental differences may be due to differences in natural environments or to artificial temperature control. For example, in winter, in an office, a shopping mall or a home environment, the indoor temperature can be controlled to be around 25 ℃ to 26 ℃ by air conditioning. But the outdoor temperature may be as low as-10 c or even lower depending on the environmental and geographical location of the respective region.
Assume that a certain mobile device moves from outdoors to indoors or from indoors to outdoors, during which the mobile device is being used or in the process of being charged. The temperature of the battery may rise due to the resistance inside the battery and the heat generated by the operation of the mobile device, and there are a number of factors that affect the temperature change of the battery during the temperature rise of the battery. If only some of the factors are considered in the battery level calculation method to predict the subsequent battery temperature change (battery temperature trend), the error of the battery level calculation method in estimating the battery level trend may be very large.
Fig. 3 is a graph showing the temperature change of the battery itself during the whole process of moving the mobile device from one temperature environment area to another temperature environment area. In fig. 3, curve 1 is the ambient temperature variation curve, and curve 2 is the temperature variation curve of the battery itself.
As shown in fig. 3, taking a mobile device with a lithium battery as an example, the mobile device moves from region 1 to region 2, and the temperature transition of the lithium battery is similar to curve 2 in fig. 3.
In the first stage, the temperature of the lithium battery is affected by sudden changes in the ambient temperature and drops rapidly. If the mobile device is in a dormant state and the lithium battery itself is not being charged or discharged, the temperature of the lithium battery will gradually approach the ambient temperature in zone two after a sufficient period of time.
However, it is often the case that mobile devices with lithium batteries are in use while in motion. Due to the influence of the heat generation of the mobile device and the heat generation of the battery caused by the internal resistance of the battery, the temperature of the lithium battery is stabilized above the ambient temperature of the second region after a certain time.
In order to correctly predict the change of the temperature of the lithium battery under the complex condition, the battery electric quantity calculation method needs to establish a correct thermal model of the battery.
Fig. 4 is a discharge curve of a battery under a varying temperature environment in a discharged state of the battery.
Fig. 5 is a graph of the internal resistance of a battery as a function of depth of discharge (DOD) at temperatures of 0 c and 25 c.
Fig. 4 shows a discharge voltage curve of a mobile device with a battery, e.g. a lithium battery, during movement from area 1 to area 2.
Taking a lithium battery as an example, when the mobile device is in zone one, the output voltage of the battery is equal to the battery Open Circuit Voltage (OCV) minus the voltage drop produced by the discharge current over the battery internal impedance (Ri).
In the thermal battery model, the battery Open Circuit Voltage (OCV) and the battery internal impedance (Ri) are both non-linear functions related to temperature (T) and depth of discharge (DOD).
As shown in fig. 4, in the discharging phase 2, since the battery is in the temperature transition region, the temperature of the battery varies, and accordingly, the internal impedance Ri of the battery also varies with the variation of the temperature of the battery.
Assuming that the temperature in zone one is 25 deg.C and the temperature in zone two is 0 deg.C. As the ambient temperature rapidly decreases, the temperature of the mobile device rapidly changes as the ambient temperature changes, and the internal impedance of the battery also rapidly increases, as shown in fig. 5. And if the battery is in use, the output voltage of the battery drops due to the flow of discharge current and the change in depth of discharge (DOD).
The change in the internal impedance of the battery due to the temperature change dominates the drop in the output voltage of the battery over a short period of time.
As the device is operated in a new zone (zone two) for a long time, the temperature of the battery tends to stabilize gradually, and the stable temperature of the battery is usually maintained above the ambient temperature due to self-heating of the battery. Eventually, the temperature of the battery in the mobile device forms a steady state in region two. The output voltage of the battery is then varied, mainly determined by the open-circuit voltage of the battery corresponding to the discharge depth of the battery, the internal impedance of the battery, and the load current of the mobile device.
The internal impedance of the battery is a nonlinear variable with parameters of depth of discharge and temperature.
Fig. 6 is a schematic diagram of the structure of a preferred battery management system.
As shown in fig. 6, the battery management system 100 includes an analog front-end chip 20 and a microcontroller 50. The analog front-end chip 20 is used to measure the output voltage of each cell of the battery pack 10 composed of the single cells 11 connected in series, and measure the voltage difference across the sampling resistor 41 through the differential lines 66A and 66B by the coulometer 25.
And measures the temperature of the battery pack 10 through a negative temperature coefficient resistor (NTC)12 or other means of temperature sensor provided inside the battery pack 10.
The analog front end chip 20 has the ability to open a circuit, such as driving MOSFETs or any form of circuit breakers or relays 43, 44 connected in series on the output circuit of the battery pack 10. The driver circuit 31 is integrated inside the analog front-end chip 20, and controls the external circuit breakers 43 and 44 by a control signal 63 and a control signal 64. The discharge MOSFET 44 is used to prevent the battery pack 10 from being discharged to the outside in the event of an accident. The charging MOSFET 43 is used to prevent an external charger from charging the battery pack 10 when an abnormal condition occurs. The fuse 42 is used for redundant protection in extreme cases to prevent irreversible damage to the equipment and the battery.
An analog switch 21 is provided inside the analog front-end chip 20, and a switching signal is controlled by a switching decoding circuit 26 for sequentially measuring the voltage of each cell of the battery pack 10 in a predetermined order. The voltage across the analog switch 21 is provided as an input to the buffer 22. The battery voltage through the buffer 22 serves as an input to an analog-to-digital converter 23. The digital result is stored in the random volatile memory 28 after conversion by the analog-to-digital converter 23. Meanwhile, the coulometer 25 is used to measure the voltage difference across the sampling resistor 41, and enters the measurement port of the coulometer 25 through the differential lines 66A and 66B.
The controller 27 inside the analog front-end chip 20 is, for example, a digital state machine, and is used for controlling the execution of the timing flow and other actions of the internal sampling conversion. In fig. 6, reference numeral 62 denotes a control line, reference numeral 65 denotes a measurement line, and reference numeral 61 denotes a data line.
The non-volatile memory 29 is used for storing configuration values and factory check values to improve measurement accuracy. The external microcontroller 50 writes or reads internal data of the analog front-end chip 20 via a public or private protocol of the communication interface 24, preferably a digital communication interface. Voltage regulator 32 draws power from battery pack 10. The overall battery management system 100 collects information about the underlying battery pack 10, including measuring battery output voltage, output current, and/or battery pack temperature, and may be used in the performance of an ambient temperature prediction method, a battery temperature prediction method, and a battery charge calculation method.
In order to correctly predict the temperature change of the battery pack in a complex real-world environment, fig. 7 shows a simple thermal model of the battery. Assume at an initial time that the mobile device 200 is at a temperature of temperature 1(TEMP1) and the temperature of the environment 300 outside the mobile device 200 is temperature 2(TEMP 2).
The heat exchange between the inside and the outside of the mobile device 200 will be performed according to the second law of thermodynamics. The battery 10 may be a single battery, or may be a battery pack or a battery pack including a plurality of batteries.
The current generated by the mobile device 200 during use causes the battery 10 to self-heat. The heating power of the battery 10 is proportional to the square of the current times the internal impedance of the battery. The heat generation power of the battery 10 can be obtained based on the internal resistance of the battery 10, the output voltage of the battery 10, and the output current of the battery 10 according to the laws of physics. Internal resistance of the battery is represented by Ri(DOD, Temp) is expressed as a function of depth of discharge (DOD) and temperature, as will be understood by those skilled in the art.
Fig. 8 is a heat transfer model of a battery. The relation between the surface temperature, the internal temperature and the external environment temperature of the battery and the heating power of the battery can be obtained according to the physical meaning of the thermal resistance
In FIG. 8, the angle θisRepresents the thermal resistance from the inside of the battery to the surface of the battery, in thetasaRepresents the thermal resistance between the cell surface and the external environment, denoted by TsRepresents the surface temperature of the battery, which can be measured by a temperature sensor, in TiIndicating the internal temperature of the battery by TaRepresenting the ambient temperature.
Surface temperature T of batterysFig. 9 shows a battery temperature change curve (without considering external temperature environment influence) only considering the internal impedance of the battery during charging and discharging.
Based on the understanding of the above, the ambient temperature prediction method, the battery temperature prediction method, and the battery level calculation method of the present disclosure are explained in detail below.
Fig. 10 is a schematic flowchart of an ambient temperature prediction method according to an embodiment of the present disclosure, the ambient temperature prediction method including: s11, acquiring the initial time of the battery in the current temperature environment, the initial temperature of the surface of the battery, the final time when the surface temperature of the battery reaches the stable temperature in the current temperature environment and the stable temperature of the surface of the battery; s12, calculating the average heating power of the internal resistance of the battery within the time length at least based on the time length from the initial time to the final time; s13, obtaining the battery temperature variation caused by the battery internal resistance heating based on at least the average heating power of the battery internal resistance; and S14 obtaining the temperature of the current temperature environment based on the battery surface initial temperature, the battery surface stable temperature, and the battery temperature variation amount caused by heat generation of the battery internal resistance.
For example, the mobile device moves from indoor (first temperature environment) to outdoor (second temperature environment), the current temperature environment in step S11 is the second temperature environment, for example, the mobile device moves from outdoor (second temperature environment) to indoor (first temperature environment), and the current temperature environment in step S11 is the first temperature environment.
The initial time when the battery is in the current temperature environment is preferably obtained based on the change curve of the battery surface temperature. The final time at which the battery surface temperature reaches the stable temperature in the present temperature environment is preferably also obtained based on the change curve of the battery surface temperature. The surface temperature of the battery can be measured.
Preferably, the initial temperature of the surface of the battery and the stable temperature of the surface of the battery are measured by temperature sensors. The temperature sensor may employ a negative temperature coefficient resistor (NTC)12 as shown in fig. 6, although other types of temperature sensors may be employed.
Preferably, the average heat generation power of the internal resistance of the battery over the time period is calculated based on at least the internal resistance value of the battery over the time period from the initial time to the final time.
Internal resistance value R of batteryi(DOD, Temp) can be obtained based on parameters such as size, shape, material, etc. of the battery, or can be obtained by fitting data to a plurality of measured values. Such as the change curve of the internal resistance value of the battery in fig. 5.
Preferably, obtaining the temperature of the current temperature environment based on the initial temperature of the battery surface, the stable temperature of the battery surface, and the amount of change in the battery temperature caused by heat generation of the battery internal resistance includes: calculating a battery surface temperature variation amount within a time length based on the battery surface initial temperature and the battery surface stabilization temperature; calculating the difference value of the battery surface temperature variation and the battery temperature variation caused by the heating of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based at least on the difference.
Here, the battery surface temperature variation amount may be obtained by measurement by a temperature sensor, and the battery temperature variation amount caused by heat generation of the battery internal resistance may be obtained based on, for example, a battery heat transfer model shown in fig. 8 and the heat generation power of the battery.
Preferably, the amount of change in the battery temperature due to heat generation in the internal resistance of the battery is obtained based on the battery heat transfer model shown in fig. 8.
The difference between the amount of change in the surface temperature of the battery and the amount of change in the temperature of the battery due to heat generation in the internal resistance of the battery is caused by a change in the ambient temperature.
Preferably, the output voltage and the surface temperature of the battery are measured in real time or at a predetermined time period within a time length from the initial time to the final time; the internal resistance value of the battery within the time period is calculated based on at least the output voltage of the battery and the surface temperature measured in real time or at a predetermined time period.
Preferably, the output current of the battery is also measured in real time or at a predetermined time period within the time length from the initial time to the final time; calculating an average output power of the battery over a length of time based on the output voltage and the output current of the battery measured in real time or at a predetermined time period; and calculating the average heating power of the internal resistance of the battery within the time length at least based on the average output power of the battery, the output voltage of the battery measured in real time or in a preset time period and the internal resistance value of the battery within the time length.
The average output power of the battery may be obtained based on the output voltage and the output current of the battery measured in real time or at a predetermined time period, among others.
Preferably, obtaining the temperature of the current temperature environment based on at least a difference between the amount of change in the surface temperature of the battery and the amount of change in the temperature of the battery due to heat generation in the internal resistance of the battery includes: the relationship of the difference value to the temperature of the current environment is obtained based on a second law of thermodynamics and a heat transfer model of the battery. Preferably, the temperature of the current environment is obtained based on the second law of thermodynamics and a heat transfer model of the battery such as that shown in fig. 8 by obtaining the relationship of the temperature of the current environment and the above-described difference.
The ambient temperature prediction method of the present embodiment can be executed by the battery management system 100 shown in fig. 6.
Fig. 11 is a schematic flowchart of an ambient temperature prediction method according to another embodiment of the present disclosure, including: s21, acquiring the time length of the surface temperature of the battery changing from the first stable temperature to the second stable temperature; s22, calculating the average heating power of the internal resistance of the battery within the time length; s23, obtaining the battery temperature variation caused by the battery internal resistance heating based on at least the average heating power of the battery internal resistance; and S24 obtaining the temperature of the current temperature environment based on the first stable temperature, the second stable temperature, and the amount of change in the battery temperature caused by heat generation in the internal resistance of the battery.
For example, the mobile device 200 moves from indoors (first temperature environment) to outdoors (second temperature environment), the first stable temperature in step S21 is the stable temperature that the battery surface temperature reaches in the first temperature environment, and the second stable temperature is the stable temperature that the battery surface temperature reaches in the second temperature environment.
Preferably, the first stable temperature is a battery surface stable temperature at which the battery is in a first temperature environment, and the second stable temperature is a battery surface stable temperature at which the battery is in a second temperature environment. The first stable temperature and the second stable temperature may be measured by a temperature sensor.
Preferably, the average heat generation power of the internal resistance of the battery over the time period is calculated at least based on the internal resistance value of the battery over the time period from the first stable temperature to the second stable temperature.
Preferably, obtaining the temperature of the current temperature environment based on the first stable temperature, the second stable temperature, and a battery temperature variation amount caused by heat generation of the internal resistance of the battery includes: calculating a battery surface temperature variation amount within a time length based on the first and second stable temperatures; calculating the difference value of the battery surface temperature variation and the battery temperature variation caused by the heating of the internal resistance of the battery; and obtaining the temperature of the current temperature environment based on the difference.
Preferably, the output voltage of the battery and the surface temperature are measured in real time or at a predetermined time period within a time period of changing from the first stable temperature to the second stable temperature; the internal resistance value of the battery within the time period is calculated based on at least the output voltage of the battery and the surface temperature measured in real time or at a predetermined time period.
Preferably, the output current of the battery is also measured in real time or at a predetermined time period within the length of time from the first stable temperature to the second stable temperature; calculating an average output power of the battery over a length of time based on the output voltage and the output current of the battery measured in real time or at a predetermined time period; and calculating the average heating power of the internal resistance of the battery within the time length at least based on the average output power of the battery, the output voltage of the battery measured in real time or in a preset time period and the internal resistance value of the battery within the time length.
Preferably, obtaining the temperature of the current temperature environment based on at least a difference between the amount of change in the surface temperature of the battery and the amount of change in the temperature of the battery due to heat generation in the internal resistance of the battery includes: the relationship of the difference value to the temperature of the current environment is obtained based on a second law of thermodynamics and a heat transfer model of the battery.
The ambient temperature prediction method of the present embodiment can be executed by the battery management system 100 shown in fig. 6.
According to still another embodiment of the present disclosure, a battery temperature prediction method includes: obtaining the temperature T of the current temperature environment using the environment temperature prediction method of the above embodimentA(ii) a And a temperature T based at least on a current temperature environmentAThe temperature trend of the battery is calculated.
The temperature trend of the battery (or expressed as a predicted battery temperature change curve) obtained by the present embodiment will be more accurate.
According to still another embodiment of the present disclosure, a battery level calculation method includes: predicting the temperature trend of the battery by using the battery temperature prediction method; and calculating a charge trend of the battery based at least on the temperature trend of the battery.
The charge trend of the battery (or expressed as a predicted charge variation curve of the battery) obtained by the embodiment will be more accurate.
According to still another embodiment of the present disclosure, a battery management system includes: a measuring device that measures at least an output voltage of the battery, an output current of the battery, and a surface temperature of the battery; and a processing device that executes the above-described ambient temperature prediction method, the above-described battery temperature prediction method, and/or the above-described battery level calculation method, based on at least the output voltage of the battery, the output current of the battery, and the surface temperature of the battery measured by the measuring device.
Wherein the measuring means is preferably realized by a temperature sensor and an analog front-end chip as shown in fig. 6.
According to still another embodiment of the present disclosure, there is provided an electronic device including the battery management system described above.
The electronic device may be a mobile phone, a tablet computer or other portable devices. The processing means is preferably implemented by the microcontroller 50 in fig. 6.
In the description herein, reference to the description of the terms "one embodiment/mode," "some embodiments/modes," "example," "specific example" or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment/mode or example is included in at least one embodiment/mode or example of the present disclosure. In this specification, the schematic representations of the terms used above are not necessarily intended to be the same embodiment/mode or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/aspects or examples and features of the various embodiments/aspects or examples described in this specification can be combined and combined by one skilled in the art without conflicting therewith.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present disclosure, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of illustration of the disclosure and are not intended to limit the scope of the disclosure. Other variations or modifications may occur to those skilled in the art, based on the foregoing disclosure, and are still within the scope of the present disclosure.
Claims (10)
1. An ambient temperature prediction method, comprising:
acquiring the initial time of the battery in the current temperature environment, the initial temperature of the surface of the battery, the final time when the surface temperature of the battery reaches the stable temperature in the current temperature environment and the stable temperature of the surface of the battery;
calculating the average heating power of the internal resistance of the battery within the time length at least based on the time length from the initial time to the final time;
obtaining the battery temperature variation caused by the heating of the internal resistance of the battery at least based on the average heating power of the internal resistance of the battery; and
and obtaining the temperature of the current temperature environment based on the initial temperature of the surface of the battery, the stable temperature of the surface of the battery and the temperature variation of the battery caused by the heat generation of the internal resistance of the battery.
2. The ambient temperature prediction method according to claim 1, wherein the battery surface initial temperature and the battery surface stable temperature are measured by temperature sensors.
3. The ambient temperature prediction method according to claim 1, characterized in that the average heat generation power of the internal resistance of the battery over the period of time is calculated based on at least the internal resistance value of the battery over the period of time.
4. The method according to claim 1, wherein obtaining the temperature of the current temperature environment based on the battery surface initial temperature, the battery surface stable temperature, and the battery temperature variation amount caused by heat generation of the battery internal resistance comprises:
calculating a battery surface temperature change amount within the time period based on the battery surface initial temperature and the battery surface stable temperature;
calculating the difference value of the battery surface temperature variation and the battery temperature variation caused by the heating of the internal resistance of the battery; and
and obtaining the temperature of the current temperature environment at least based on the difference.
5. The ambient temperature prediction method according to claim 3, characterized in that the output voltage of the battery and the surface temperature are measured in real time or at a predetermined time period within the time length;
calculating the battery internal resistance value within the time length based on at least the output voltage of the battery and the surface temperature measured in real time or at a predetermined time period.
6. The ambient temperature prediction method according to claim 5, characterized in that within the time length, the output current of the battery is also measured in real time or at a predetermined time period;
calculating an average output power of the battery over the length of time based on the output voltage and the output current of the battery measured in real time or at a predetermined time period;
and calculating the average heating power of the internal resistance of the battery within the time length at least based on the average output power of the battery, the output voltage of the battery measured in real time or in a preset time period and the internal resistance value of the battery within the time length.
7. The method of claim 4, wherein obtaining the temperature of the current temperature environment based on at least the difference comprises:
the relationship of the difference value to the temperature of the current environment is obtained based on a second law of thermodynamics and a model of the heat transfer of the battery to the external environment.
8. An ambient temperature prediction method, comprising:
acquiring the time length of the surface temperature of the battery changing from a first stable temperature to a second stable temperature;
calculating the average heating power of the internal resistance of the battery within the time length;
obtaining the battery temperature variation caused by the heating of the internal resistance of the battery at least based on the average heating power of the internal resistance of the battery; and
and obtaining the temperature of the current temperature environment based on the first stable temperature, the second stable temperature and the battery temperature variation caused by the heat generation of the internal resistance of the battery.
9. The ambient temperature prediction method according to claim 8, wherein the first stable temperature is a battery surface stable temperature at which the battery is in a first temperature environment, and the second stable temperature is a battery surface stable temperature at which the battery is in a second temperature environment.
10. The ambient temperature prediction method of claim 8, wherein the first stable temperature and the second stable temperature are measured by a temperature sensor.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113030160A (en) * | 2021-02-05 | 2021-06-25 | 华荣科技股份有限公司 | Method and system for obtaining highest surface temperature value of explosion suppression device |
| TWI773306B (en) * | 2021-05-10 | 2022-08-01 | 加百裕工業股份有限公司 | Method of detecting state of charge of battery |
| CN114879770A (en) * | 2022-04-29 | 2022-08-09 | 广东迅扬科技股份有限公司 | Constant temperature control method based on linear regression prediction |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100138295A (en) * | 2009-06-25 | 2010-12-31 | 현대자동차주식회사 | A method for estimating battery temperature of a vehicle |
| JP5035428B2 (en) * | 2010-04-28 | 2012-09-26 | トヨタ自動車株式会社 | Battery temperature measuring device, battery temperature measuring method, battery manufacturing method |
| CN105206888A (en) * | 2015-08-31 | 2015-12-30 | 浙江工业大学之江学院 | Lithium ion battery internal temperature monitoring method |
| CN105910725A (en) * | 2016-04-25 | 2016-08-31 | 惠州Tcl移动通信有限公司 | Temperature change detection method for environment of battery and temperature change detection device thereof |
| CN108344946A (en) * | 2017-01-22 | 2018-07-31 | 中国科学院空间应用工程与技术中心 | Battery-heating weight testing method and battery-heating amount test device |
| CN108965606A (en) * | 2018-08-22 | 2018-12-07 | 北京小米移动软件有限公司 | Determine the method and device of environment temperature |
| WO2019093627A1 (en) * | 2017-11-07 | 2019-05-16 | 주식회사 엘지화학 | Apparatus and method for estimating battery temperature |
| CN109799005A (en) * | 2018-12-20 | 2019-05-24 | 北京长城华冠汽车科技股份有限公司 | Internal temperature of battery estimation method, device, system and vehicle |
| CN109921111A (en) * | 2019-03-14 | 2019-06-21 | 上海大学 | A kind of internal temperature of lithium ion battery estimating and measuring method and system |
| CN109987000A (en) * | 2019-02-19 | 2019-07-09 | 中国第一汽车股份有限公司 | A kind of temperature of powered cell forecasting system and method |
| CN110501653A (en) * | 2019-07-30 | 2019-11-26 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of battery core method for acquiring temperature, device and control unit for vehicle |
| CN110736566A (en) * | 2019-10-17 | 2020-01-31 | 珠海格力电器股份有限公司 | Method for measuring environmental temperature by using terminal equipment, storage medium and terminal equipment |
| CN110816366A (en) * | 2019-10-31 | 2020-02-21 | 上海交通大学 | Temperature estimation method, system, medium and equipment suitable for interior of single battery |
-
2020
- 2020-03-18 CN CN202010192650.6A patent/CN111398827B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100138295A (en) * | 2009-06-25 | 2010-12-31 | 현대자동차주식회사 | A method for estimating battery temperature of a vehicle |
| JP5035428B2 (en) * | 2010-04-28 | 2012-09-26 | トヨタ自動車株式会社 | Battery temperature measuring device, battery temperature measuring method, battery manufacturing method |
| CN105206888A (en) * | 2015-08-31 | 2015-12-30 | 浙江工业大学之江学院 | Lithium ion battery internal temperature monitoring method |
| CN105910725A (en) * | 2016-04-25 | 2016-08-31 | 惠州Tcl移动通信有限公司 | Temperature change detection method for environment of battery and temperature change detection device thereof |
| CN108344946A (en) * | 2017-01-22 | 2018-07-31 | 中国科学院空间应用工程与技术中心 | Battery-heating weight testing method and battery-heating amount test device |
| WO2019093627A1 (en) * | 2017-11-07 | 2019-05-16 | 주식회사 엘지화학 | Apparatus and method for estimating battery temperature |
| CN108965606A (en) * | 2018-08-22 | 2018-12-07 | 北京小米移动软件有限公司 | Determine the method and device of environment temperature |
| CN109799005A (en) * | 2018-12-20 | 2019-05-24 | 北京长城华冠汽车科技股份有限公司 | Internal temperature of battery estimation method, device, system and vehicle |
| CN109987000A (en) * | 2019-02-19 | 2019-07-09 | 中国第一汽车股份有限公司 | A kind of temperature of powered cell forecasting system and method |
| CN109921111A (en) * | 2019-03-14 | 2019-06-21 | 上海大学 | A kind of internal temperature of lithium ion battery estimating and measuring method and system |
| CN110501653A (en) * | 2019-07-30 | 2019-11-26 | 东软睿驰汽车技术（沈阳）有限公司 | A kind of battery core method for acquiring temperature, device and control unit for vehicle |
| CN110736566A (en) * | 2019-10-17 | 2020-01-31 | 珠海格力电器股份有限公司 | Method for measuring environmental temperature by using terminal equipment, storage medium and terminal equipment |
| CN110816366A (en) * | 2019-10-31 | 2020-02-21 | 上海交通大学 | Temperature estimation method, system, medium and equipment suitable for interior of single battery |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113030160A (en) * | 2021-02-05 | 2021-06-25 | 华荣科技股份有限公司 | Method and system for obtaining highest surface temperature value of explosion suppression device |
| TWI773306B (en) * | 2021-05-10 | 2022-08-01 | 加百裕工業股份有限公司 | Method of detecting state of charge of battery |
| CN114879770A (en) * | 2022-04-29 | 2022-08-09 | 广东迅扬科技股份有限公司 | Constant temperature control method based on linear regression prediction |
| CN114879770B (en) * | 2022-04-29 | 2024-02-20 | 广东迅扬科技股份有限公司 | Constant temperature control method based on linear regression prediction |
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