Battery capacity estimation method, self-moving device, electronic device and storage medium

Abstract

The invention provides a battery capacity estimation method, a self-moving device, an electronic device and a storage medium. The method comprises the following steps: acquiring working parameters of a battery of the self-moving equipment; determining the residual electric quantity of the battery based on the working parameters of the battery; the step of determining the residual electric quantity of the battery based on the working parameters of the battery comprises the step of determining the residual electric quantity based on the terminal voltage of the battery and a preset first mapping relation when the battery is in a charging state. By using the method, the estimation cost and the estimation complexity of the electric quantity of the battery can be reduced.

Description

Technical Field

[0001] This application relates to the technical field of battery power estimation, and particularly to a battery power estimation method, a self-mobile device, an electronic device, and a storage medium. Background Art

[0002] To ensure the normal operation of a self-mobile device, it is often necessary to estimate the battery power of the self-mobile device for timely charging. In the related art, the battery power is usually estimated by the following two methods. The first estimation method is to rely on an independent fuel gauge chip to estimate the battery power. The second method is to implant a micro control unit (MCU) inside the battery, design a corresponding hardware circuit, and supplement it with a software algorithm to estimate the battery power.

[0003] These two battery power estimation methods are not only complex in operation but also increase the estimation cost. Summary of the Invention

[0004] In view of the above, it is necessary to provide a battery power estimation method, a self-mobile device, an electronic device, and a storage medium, which can solve the technical problems of complex estimation operation and high estimation cost of battery power.

[0005] On the one hand, this application provides a battery power estimation method, which includes: obtaining the working parameters of the battery of the self-mobile device, and determining the remaining power of the battery based on the working parameters of the battery. Determining the remaining power of the battery based on the working parameters of the battery includes: when the battery is in a charging state, determining the remaining power based on the terminal voltage of the battery and a preset first mapping relationship.

[0006] On the other hand, this application provides a self-mobile device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the self-mobile device implements the battery power estimation method described above. On the other hand, this application provides an electronic device, which includes: a storage device, a processing device, and a computer program stored on the storage device and executable on the processing device. When the processing device executes the computer program, the electronic device implements the battery power estimation method described above. On the other hand, this application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor in a self-mobile device, it implements the battery power estimation method described above, or when it is executed by a processing device in an electronic device, it implements the battery power estimation method described above.

[0007] In the battery power estimation solution of this embodiment, since the operating parameters of the battery can accurately reflect the actual state of the battery, the remaining power of the battery can be quickly and accurately determined according to the mapping relationship between the operating parameters of the battery (for example, the terminal voltage) and the corresponding one. In this way, the dependence on hardware resources and complex algorithms can be reduced, thereby reducing the estimation cost and complexity of the battery power. Description of the Drawings

[0008] Figure 1 It is a schematic diagram of a self-mobile device provided by an embodiment of the present application.

[0009] Figure 2 It is a flowchart of a battery power estimation method provided by an embodiment of the present application.

[0010] Figure 3 It is a schematic structural diagram of a self-mobile device provided by an embodiment of the present application.

[0011] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0012] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be described in detail below with reference to the drawings and specific embodiments.

[0013] It should be noted that "at least one" in the present application means one or more, and "a plurality" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B may be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the description, claims, and drawings of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0014] In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0015] To ensure the normal operation of a self - moving device, it is often necessary to estimate the battery power of the self - moving device for timely charging. In related technologies, there are usually two ways to estimate the battery power. The first way is to rely on an independent fuel gauge chip to estimate the battery power. The second way is to implant a micro - control unit (MCU) inside the battery, design a corresponding hardware circuit, and supplement it with a software algorithm to estimate the battery power.

[0016] These two methods of estimating battery power not only have complex operations but also increase the estimation cost.

[0017] To solve the above - mentioned technical problems, this application provides a method for estimating battery power, which can reduce the estimation cost and complexity of battery power.

[0018] The method for estimating battery power provided by the embodiments of this application can be applied to one or more self - moving devices. The self - moving devices can be lawn mowing robots, cleaning robots, de - icing robots, cruise robots, etc. This application does not limit the specific types of self - moving devices.

[0019] For example, as Figure 1 shown, it is a schematic diagram of a self - moving device provided by an embodiment of this application. Figure 1 The self - moving device in

[0020] Figure 1 is a lawn mower, and the lawn mower can determine the remaining battery power according to the working parameters of the internal battery.

[0021] The lawn mower shown is only an example of a self - moving device. In actual applications, the self - moving device can also be a cleaning robot or other devices.

[0022] In other embodiments, the method for estimating battery power provided by the embodiments of this application can be applied to one or more electronic devices. The electronic devices can be communicatively connected to the self - moving devices. The electronic devices can obtain the working parameters of the batteries inside the self - moving devices from the self - moving devices, and thus determine the remaining battery power of the batteries inside the self - moving devices.

[0023] To more clearly illustrate the battery power estimation method provided by the embodiments of the present application, the battery power estimation method will be described below by taking an application to a self-mobile device as an example.

[0024] As Figure 2 shown, it is a flowchart of the battery power estimation method provided by an embodiment of the present application. According to different requirements, the order of each step in this flowchart can be adjusted according to actual requirements, and some steps can be omitted. The method is applied to a self-mobile device.

[0025] S11, obtain the operating parameters of the battery of the self-mobile device.

[0026] In some embodiments, the operating parameters include but are not limited to: terminal voltage, current. Among them, the current can be the current output by the battery. An analog-to-digital converter can be integrated inside the self-mobile device, so the self-mobile device can obtain operating parameters such as the current and terminal voltage of the battery through the analog-to-digital converter (ADC).

[0027] In other embodiments, after obtaining the operating parameters, the self-mobile device can perform preprocessing operations such as denoising on the operating parameters. For example, the self-mobile device can use the mean filtering algorithm to filter and denoise the operating parameters of the battery.

[0028] S12, based on the operating parameters of the battery, determine the remaining power of the battery of the self-mobile device.

[0029] In some embodiments, when the battery is in the charging state, the self-mobile device determines the remaining power of the battery based on the operating parameters of the battery, including: determining the remaining power of the battery based on the terminal voltage of the battery and a preset first mapping relationship.

[0030] Among them, the self-mobile device can determine whether the battery is in the charging state through various methods, and the present application does not limit the detection method of the charging state. For example, when one or more of the following conditions are met, it can be determined that the battery is in the charging state: detecting that current flows into the battery (such as the current value > 0, with the battery as the reference direction), detecting that the voltage of the battery shows a continuous upward trend.

[0031] The remaining power can be represented by the state of charge (SOC) value.

[0032] The first mapping relationship is the corresponding relationship between the terminal voltage of the battery in the charging state and the remaining power. Exemplarily, the self-mobile device can collect multiple remaining powers (SOC values) of the battery in the charging state and the corresponding terminal voltage for each remaining power, and use a fitting algorithm to fit the functional corresponding relationship between the multiple remaining powers and the corresponding terminal voltages of the battery in the charging state as the first mapping relationship. Among them, the type of the fitting algorithm is not limited in this application. For example, the fitting algorithm can be polynomial fitting, least squares fitting, neural network fitting, etc.

[0033] Exemplarily, the self-mobile device can use the first mapping relationship to calculate the terminal voltage of the battery, so as to obtain the remaining power of the battery.

[0034] During the battery charging process, since the specification parameters of charging devices such as chargers are fixed, the charging current remains constant, so that the charging working condition presents stable characteristics. Based on this characteristic, in this embodiment, if the battery is in the charging state, according to the terminal voltage of the battery and using the first mapping relationship that can reflect the change law of the terminal voltage of the battery with the remaining power in the charging state, the remaining power of the battery can be determined quickly and accurately.

[0035] In some embodiments, when the battery is in a stationary state or the current of the battery is less than the current threshold, the self-mobile device determines the remaining power of the battery based on the working parameters of the battery, including: obtaining the remaining power based on the terminal voltage of the battery and a preset second mapping relationship. Among them, the self-mobile device can determine whether the battery is in a stationary state through various methods, and the detection method of the stationary state is not limited in this application. For example, when it is detected that there is no current flowing into and out of the battery, the self-mobile device can determine that the battery is in a stationary state. The current threshold can be set customarily, and this application does not limit this. For example, the current threshold can be 0.05C, where C represents the rated capacity of the battery. Exemplarily, if the rated capacity of the battery is 100 milliamperes per hour (mAh), the current threshold can be 5 mA = 0.05 x 100. In order to reduce the estimation error of the remaining power, the current threshold can be set smaller.

[0036] The second mapping relationship is the corresponding relationship between the open circuit voltage of the battery in the stationary state and the remaining power. The self-mobile device can collect multiple open circuit voltages (Open Circuit Voltage, OCV) of the battery after a preset time of stationary and the corresponding remaining power (SOC value) for each open circuit voltage, and use a fitting algorithm to fit the functional corresponding relationship between the multiple open circuit voltages and the corresponding remaining powers as the second mapping relationship. Among them, the preset time can be set customarily, and this application does not limit this. For example, the preset time can be 4 hours.

[0037] Exemplarily, the self - moving device can utilize the second mapping relationship to calculate the terminal voltage of the battery, thereby obtaining the remaining power of the battery. Among them, when the battery is in a static state, the terminal voltage of the battery is the open - circuit voltage.

[0038] Considering that when the battery is in a static state or the current of the battery is less than the current threshold, the internal polarization effect of the battery (such as concentration polarization and electrochemical polarization) is significantly weakened (for example, through experiments, it can be obtained that for a lithium iron phosphate battery, after standing for 4 hours, the polarization voltage can decay to within 5 mV). At this time, the terminal voltage of the battery will be relatively close to the open - circuit voltage of the battery. Therefore, in this embodiment, if the battery is in a static state or the current of the battery is less than the current threshold, according to the terminal voltage of the battery, using the second mapping relationship that can reflect the variation law of the open - circuit voltage of the battery with the remaining power in the static state, the remaining power of the battery can be determined quickly and accurately.

[0039] In some embodiments, when the self - moving device is in the powered - on and non - working state, the self - moving device determines the remaining power of the battery based on the working parameters of the battery, including: obtaining the remaining power based on the terminal voltage of the battery and a preset third mapping relationship.

[0040] Among them, for the convenience of description, the powered - on and non - working state will be abbreviated as the standby state hereinafter. The self - moving device can determine whether the self - moving device is in the standby state through various methods, and this application does not limit the detection method of the standby state. For example, when the current of the battery is within a preset current range, it can be determined that the self - moving device is in the standby state. Among them, the preset current range can be determined by the current fluctuation range of the battery in the standby state.

[0041] The third mapping relationship can be the corresponding relationship between the terminal voltage and the remaining power of the battery in the standby state. The self - moving device can collect multiple remaining powers (SOC values) of the battery in the standby state and the corresponding terminal voltage for each remaining power, and use the fitting algorithm to fit the functional corresponding relationship between the multiple remaining powers and the corresponding terminal voltages of the battery in the standby state as the third mapping relationship.

[0042] Exemplarily, the self - moving device can utilize the third mapping relationship to calculate the terminal voltage of the battery, thereby obtaining the remaining power of the battery.

[0043] Considering that when the self - moving device is in the standby state, the current consumed by the self - moving device is small, and it is difficult to calculate the effective remaining power based on the current of the battery. Therefore, in this embodiment, if the self - moving device is in the standby state, according to the terminal voltage of the battery, using the third mapping relationship that can reflect the variation law of the terminal voltage of the battery with the remaining power in the standby state, the remaining power of the battery can be determined quickly and accurately.

[0044] In some embodiments, when the self - moving device is in the working state, the self - moving device determines the remaining battery power based on the working parameters of the battery, including: calculating the power consumption of the self - moving device during operation based on the battery current and the working duration of the self - moving device, and determining the current remaining battery power according to the power consumption during operation and the remaining battery power of the battery calculated most recently before the self - moving device starts working and closest to the current time.

[0045] Among them, the self - moving device can determine whether it is in the working state through various methods, and this application does not limit the detection method of the working state. For example, under one or more of the following conditions, it can be determined that the battery is in the working state: detecting that the battery current is greater than the current range corresponding to the standby state, detecting that the moving speed of the self - moving device is greater than the first preset value, and detecting that the sensor sampling rate is greater than the first preset value.

[0046] Exemplarily, the self - moving device can determine the power consumption of the self - moving device during operation based on the battery current and the working duration of the self - moving device by using the ampere - hour integration method. For example, the calculation method of the current remaining battery power can refer to the following formula (1): ; (1) Among them, represents the current remaining battery power, represents the remaining battery power of the battery calculated most recently before the self - moving device starts working and closest to the current time, represents the power consumption of the self - moving device during operation, represents the rated capacity of the battery, represents the working duration of the self - moving device, represents the Coulomb efficiency during the charge - discharge process of the battery, represents the battery current.

[0047] Considering that when the self - moving device is in the working state, the load inside the self - moving device changes frequently, and the static condition required to obtain the open - circuit voltage cannot be satisfied. Therefore, in this embodiment, if the self - moving device is in the working state and the battery current fluctuates greatly, using the ampere - hour integration method based on the battery current and the working duration of the self - moving device can quickly and accurately determine the remaining battery power.

[0048] In other embodiments, the self - moving device can obtain the total power consumption for charging the battery from the empty - battery state (for example, the battery level is 0%) to the full - battery state (for example, the battery level is 100%), determine the maximum capacity of the battery according to the total power consumption, and determine the battery percentage based on the remaining battery power and the maximum capacity of the battery.

[0049] For example, if it takes 2.8 Ah to charge the battery from 0% to 100% of its power, the maximum capacity of the battery can be determined to be 2.8 Ah.

[0050] For example, if the nominal capacity of the battery is 3 Ah, the current remaining power of the battery is 60%, and the maximum capacity of the battery is 2.8 Ah, the battery power percentage can be 56% = (2.8 x 60 / 3)%.

[0051] Considering that due to factors such as aging and temperature changes, the actual maximum capacity of the battery will decay. Therefore, in this embodiment, the total power consumption for charging the battery from the empty state to the full state is used to determine the actual maximum capacity of the battery, so that the actual power percentage of the battery can be accurately determined as the actual remaining power of the battery based on the maximum capacity and the remaining capacity of the battery.

[0052] In other embodiments, the self - moving device can collect the ambient temperature and adjust the maximum capacity of the battery according to the ambient temperature.

[0053] For example, the self - moving device can calculate the difference between the collected ambient temperature and the standard temperature (e.g., 25°C), take the product of the difference, a preset coefficient, and the maximum capacity of the battery as the correction amount, and determine the sum of the maximum capacity of the battery and the correction amount as the updated maximum capacity.

[0054] Considering that the ambient temperature will affect the actual maximum capacity of the battery, therefore, in this embodiment, adjusting the maximum capacity of the battery according to the collected ambient temperature can improve the accuracy of the adjusted maximum capacity.

[0055] In the battery power estimation scheme of this embodiment, since the working parameters of the battery can accurately reflect the actual state of the battery, the remaining power of the battery can be quickly and accurately determined according to the mapping relationship between the working parameters of the battery (e.g., terminal voltage) and the corresponding one. Thus, the dependence on hardware resources and complex algorithms can be reduced, and the estimation cost and complexity of the battery power can be lowered.

[0056] For example, as Figure 3 shown, is a schematic structural diagram of a self - moving device provided by an embodiment of the present application. Figure 3 In it, the self - moving device 1 includes a body and a memory 11, a processor 12, a power supply 13, a sensor 14, a working mechanism 15, a communication module 16, a positioning module 17, a driving wheel 18, and a bus 19 arranged on the body. The processor 12 is respectively coupled to the memory 11, the power supply 13, the sensor 14, the working mechanism 15, the communication module 16, the positioning module 17, and the driving wheel 18 through the bus 19.

[0057] The memory 11 may include one or more random access memories (RAMs) and one or more non-volatile memories (NVMs). The random access memory can be directly read and written by the processor 12, and can be used to store the operating system or executable programs of other running programs (such as machine instructions), and can also be used to store user and application data, etc. The random access memory can include static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc.

[0058] The non-volatile memory can also store executable programs and store user and application data, etc., and can be pre-loaded into the random access memory for direct reading and writing by the processor 12. The non-volatile memory can include disk storage devices and flash memory.

[0059] The memory 11 is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processor 12. The one or more computer programs include a plurality of instructions, and when the plurality of instructions are executed by the processor 103, a battery power estimation method executed on the self-mobile device 1 can be realized.

[0060] In other embodiments, the self-mobile device 1 further includes an external memory interface for connecting to an external memory to implement the expansion of the storage capacity of the self-mobile device 1.

[0061] Processor 12 may include one or more processing units. For example, processor 12 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated in one or more processors.

[0062] Processor 12 provides computing and control capabilities. For example, processor 12 is used to execute the computer program stored in memory 11 to implement the above-mentioned battery power estimation method.

[0063] Power supply 13 is used to supply power to the self-mobile device. In an embodiment of the present application, power supply 13 may include any one or more of power supply devices such as a battery, a fuel generator, a solar power generation module, and a wind power generation module.

[0064] Sensor 14 is used to obtain information for the self-mobile device 1, such as obtaining environmental information and movement information of the self-mobile device 1. In an embodiment of the present application, sensor 14 may include one or more of sensors such as lidar, a camera device, an infrared sensor, and an encoder.

[0065] The working mechanism 15 is used to perform corresponding working tasks, such as mowing, deicing, cruising, cleaning, and spraying pesticides, etc. In some embodiments, the working mechanism 15 may include mechanisms such as a motor, a transmission mechanism, and a cutter head. When the self-mobile device is a lawn mower, the motor can drive the cutter head to rotate through the transmission mechanism to achieve the mowing function. The motor can also control the movement of the blade to adjust the mowing height and the mowing area.

[0066] The communication module 16 is used to realize the communication between the self-mobile device and other devices. In an embodiment of the present application, the communication module 16 may perform data interaction with other devices based on wired communication and / or wireless communication. The above-mentioned wireless communication may include one or more combinations of communication methods such as Bluetooth communication, Wi-Fi communication, and Near Field Communication (NFC).

[0067] The positioning module 17 is used to determine the position of the self - moving device. In some embodiments, the positioning module 17 may include one or more of positioning modules such as the Global Positioning System (GPS), inertial navigation system, Real - time kinematic (RTK) carrier phase differential system, etc.

[0068] The drive wheels 18 are used to enable the self - moving device to move. In some embodiments, the drive wheels 18 can implement the moving function of the self - moving device under the control of the processor 12. In some embodiments, the drive wheels 18 may include a left drive wheel and a right drive wheel.

[0069] The bus 19 is at least used to provide a communication channel for mutual communication between the memory 11, processor 12, power supply 13, sensor 14, working mechanism 15, communication module 16, positioning module 17, and drive wheels 18 in the self - moving device 1.

[0070] In other embodiments, the self - moving device 1 may further include an anti - collision part and a steering component, etc. The anti - collision part can be used to prevent the drive wheels 18 from colliding with obstacles in front of the self - moving device. The steering component can be used to adjust the driving direction of the drive wheels 18.

[0071] It can be understood that the structure schematically shown in the embodiments of the present application does not constitute a specific limitation on the self - moving device 1. In other embodiments of the present application, the self - moving device 1 may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or have different component arrangements. The illustrated components can be implemented in hardware, software, or a combination of software and hardware.

[0072] As Figure 4 shown, it is a schematic structural diagram of an electronic device provided by an embodiment of the present application. In Figure 4 it, the electronic device 2 may include a communication module 21, a storage device 22, a processing device 23, an Input / Output (I / O) interface 24, and a bus 25. The processing device 23 is respectively coupled to the communication module 21, the storage device 22, and the input / output interface 24 through the bus 25.

[0073] The communication module 21 may include a wired communication module and / or a wireless communication module. The wired communication module may provide one or more of the solutions for wired communication such as universal serial bus (USB), Controller Area Network (CAN), etc. The wireless communication module may provide one or more of the solutions for wireless communication such as wireless fidelity (Wi-Fi), Bluetooth (BT), mobile communication network, frequency modulation (FM), near field communication (NFC), infrared (IR), etc.

[0074] The storage device 22 may include one or more random access memories (RAM) and one or more non-volatile memories (NVM). The random access memory can be directly read and written by the processing device 23, and can be used to store executable programs (such as machine instructions) of other running programs, and can also be used to store user and application data, etc. The random access memory may include static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc.

[0075] The non-volatile memory can also store executable programs and store user and application data, etc., and can be pre-loaded into the random access memory for direct reading and writing by the processing device 23. The non-volatile memory may include disk storage devices, flash memory.

[0076] The storage device 22 is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processing device 23. The one or more computer programs include a plurality of instructions, and when the plurality of instructions are executed by the processing device 23, a battery power estimation method executable on the electronic device 2 can be realized.

[0077] In other embodiments, such asFigure 4 The electronic device 2 shown also includes an external memory interface for connecting to an external memory to expand the storage capacity of the electronic device 2.

[0078] The processing device 23 may include one or more processing units. For example, the processing device 23 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated in one or more processors.

[0079] The processing device 23 provides computing and control capabilities. For example, the processing device 23 is used to execute the computer program stored in the storage device 22 to implement the above battery power estimation method.

[0080] The input / output interface 24 is used to provide a channel for user input or output. For example, the input / output interface 24 can be used to connect various input / output devices, such as a mouse, a keyboard, a touch device, a display screen, etc., so that the user can input information or visualize information.

[0081] The bus 25 is at least used to provide a communication channel between the communication module 21, the storage device 22, the processing device 23, and the input / output interface 24 in the electronic device 2.

[0082] It can be understood that the structure schematically shown in the embodiments of the present application does not constitute a specific limitation on the electronic device 2. In other embodiments of the present application, the electronic device 2 may include more or fewer components than shown, or combine certain components, or split certain components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0083] The embodiments of the present application also provide a computer-readable storage medium with a computer program stored thereon. The computer program includes program instructions, and the method implemented when the program instructions are executed may refer to the methods in the above various embodiments of the present application.

[0084] Among them, the computer-readable storage medium may be the internal memory of the self-mobile device or the electronic device described in the above embodiments. For example, it may be the hard disk or memory of the self-mobile device or the electronic device. The computer-readable storage medium may also be an external storage device of the self-mobile device or the electronic device. For example, it may be a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a FlashCard, etc., equipped on the self-mobile device or the electronic device.

[0085] In some embodiments, the computer-readable storage medium may include a storage program area and a storage data area. Among them, the storage program area may store an operating system, application programs required for at least one function, etc.; the storage data area may store data created according to the use of the self-mobile device or the electronic device.

[0086] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0087] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0088] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included in the protection scope of this application.

Claims

1. A battery power estimation method, characterized in that: The method comprises: Obtain operating parameters of the battery from the mobile device; Determining the remaining power of the battery based on the operating parameters of the battery; The determining the remaining power of the battery based on the operating parameters of the battery includes: when the battery is in a charging state, determining the remaining power based on the terminal voltage of the battery and a preset first mapping relationship.

2. The battery capacity estimation method according to claim 1, characterized in that: The determining the remaining power of the battery based on the operating parameters of the battery further includes: When the battery is in a stationary state or the current of the battery is less than a current threshold, the remaining power is obtained based on the terminal voltage of the battery and a preset second mapping relationship.

3. The battery capacity estimation method according to claim 1 or 2, characterized in that: The determining the remaining power of the battery based on the operating parameters of the battery further includes: When the self-equipment device is in a powered-on and non-operating state, the remaining power is obtained based on the terminal voltage of the battery and a preset third mapping relationship.

4. The battery capacity estimation method according to any one of claims 1 to 3, characterized in that: The determining the remaining power of the battery based on the operating parameters of the battery further includes: When the self-moving device is in working state, based on the current of the battery and the working time of the self-moving device, the power consumption of the self-moving device during working period is calculated; The current remaining power of the battery is determined according to the power consumption during the working period and the remaining power of the battery calculated most recently before the mobile device starts working.

5. The battery capacity estimation method according to any one of claims 1 to 3, characterized in that: The mapping relationship includes a corresponding relationship between voltage and remaining power.

6. The battery capacity estimation method according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtaining the total power consumption of charging the battery from an empty state to a fully charged state; Determining the maximum capacity of the battery according to the total power consumption; The battery power percentage is determined according to the remaining power and the maximum capacity of the battery.

7. The battery capacity estimation method according to claim 6, characterized in that: The method further comprises: Collect ambient temperature; The maximum capacity of the battery is adjusted according to the ambient temperature.

8. A self-propelled device, characterized in that: The self-mobile device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the self-mobile device implements the battery power estimation method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that: The electronic device comprises: a storage device, a processing device, and a computer program stored on the storage device and executable on the processing device. When the processing device executes the computer program, the electronic device implements the battery power estimation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor in a mobile device or a processing device in an electronic device, the battery power estimation method according to any one of claims 1 to 7 is implemented.

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