Electric vehicle safety monitoring system and method

Abstract

The present application is intended to provide a system and method for safety monitoring of electric vehicles. The method may include obtaining parameter values ​​of one or more motion parameters associated with a target object (510). The method may also include identifying an abnormal state of the target object based on the parameter values ​​(520). The method may also include obtaining attribute values ​​of one or more performance attributes of a power supply unit of the target object in response to identifying the abnormal state of the target object (530), wherein the power supply unit provides power to the target object. The method may also include determining a state of the power supply unit based at least in part on the attribute values ​​(540).

Description

Technical Field

[0001] The present invention relates generally to battery management and, more particularly, to systems and methods for battery safety assessment of suspected incidents. Background Art

[0002] Electric vehicles powered by batteries are generally considered to be environmentally friendly. As part of the modern transportation system, their number has increased dramatically. When an electric vehicle is involved in an incident (e.g., a car accident), one or more batteries in the electric vehicle may be damaged, which may affect the overall performance of the electric vehicle and even pose a safety hazard to the driver and passengers. However, traditional methods for evaluating the impact of accidents on batteries are often unreliable and inefficient. Therefore, it is necessary to develop a system and method for more accurately and effectively monitoring and evaluating the state of health (SoH) of batteries in electric vehicles. Summary of the invention

[0003] According to one aspect of the present specification, a system may be provided. The system may include at least one storage device storing an instruction set; and at least one processor that may be configured to communicate with the at least one storage device. When executing the instruction set, the at least one processor may be instructed to perform the following operations. The following operations may include obtaining parameter values ​​of one or more motion parameters associated with a target object; identifying an abnormal state of the target object based on the parameter values; in response to identifying the abnormal state of the target object, obtaining attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; and determining the state of the power supply unit based at least in part on the attribute values.

[0004] According to another aspect of the present specification, a method implemented on a computing device having a processor and a computer-readable storage device may be provided. The method may include obtaining parameter values ​​of one or more motion parameters associated with a target object; identifying an abnormal state of the target object based on the parameter values; in response to identifying the abnormal state of the target object, obtaining attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; and determining a state of the power supply unit based at least in part on the attribute values.

[0005] According to another aspect of the present specification, a non-transitory computer-readable storage medium may be provided. When at least one processor of the system accesses the instructions, the system is caused to perform a method. The method may include obtaining parameter values ​​of one or more motion parameters associated with a target object; identifying an abnormal state of the target object based on the parameter values; in response to identifying the abnormal state of the target object, obtaining attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; and determining a state of the power supply unit based at least in part on the attribute values.

[0006] In some embodiments, the target object is a vehicle.

[0007] In some embodiments, the one or more motion parameters include one or more accelerations, and an average acceleration of all accelerations in one or more axes, wherein each acceleration corresponds to each of the one or more axes of the target object.

[0008] In some embodiments, the one or more acceleration parameter values ​​are acquired by at least one acceleration sensor coupled to the target object.

[0009] In some embodiments, identifying the abnormal state of the target object based on the one or more motion parameters includes: determining whether one or more collision conditions associated with the target object are satisfied based on the parameter values; and determining that the target object is in an abnormal state in response to determining that at least one of the one or more collision conditions associated with the target object is satisfied.

[0010] In some embodiments, the one or more collision conditions include: a parameter value corresponding to acceleration in any axial direction is greater than a corresponding axial acceleration threshold; and a parameter value of an average acceleration of all accelerations in the one or more axial directions is greater than an average acceleration threshold.

[0011] In some embodiments, the power supply unit is a battery.

[0012] In some embodiments, the operation further includes: acquiring a priori count of abnormal states of the target object; and in response to identifying the abnormal state of the target object, generating a current count of the abnormal state by increasing the priori count by 1.

[0013] In some embodiments, determining the state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes includes determining the state of the power supply unit based on the attribute values ​​of the one or more performance attributes and a current count of the abnormal state.

[0014] In some embodiments, the one or more performance attributes include: one or more voltages, and an average voltage of all voltages of one or more components of the power supply unit, wherein each voltage corresponds to each of the one or more components; one or more temperatures, and an average temperature of all temperatures of one or more components of the power supply unit, wherein each temperature corresponds to each of the one or more components; and the resistance of the power supply unit, and the average resistance of all resistances of the power supply unit over a time period.

[0015] In some embodiments, determining the state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes includes: determining whether one or more safety warning conditions associated with the one or more performance attributes of the power supply unit are satisfied based on the attribute values ​​of the one or more performance attributes; and determining an unsafe state of the power supply unit in response to determining that at least one of the one or more safety warning conditions associated with the one or more performance attributes of the power supply unit is satisfied.

[0016] In some embodiments, the operations further include determining a security state of the power supply unit in response to determining that any of the one or more security warning conditions associated with the one or more performance attributes of the power supply unit are not satisfied.

[0017] In some embodiments, the one or more safety warning conditions associated with the one or more performance attributes of the power supply unit include at least one of one or more voltage warning conditions, one or more temperature warning conditions, or one or more resistance warning conditions.

[0018] In some embodiments, at least one of the one or more safety warning conditions is related to a current count of abnormal states of the target object.

[0019] Some additional features of the present application may be described in the following description. Some additional features of the present application will be apparent to those skilled in the art through study of the following description and the corresponding drawings or understanding of the production or operation of the embodiments. The features of the present application may be realized and achieved through practice or use of the methods, means and combinations of various aspects of the specific embodiments described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present application will be further described by exemplary embodiments. These exemplary embodiments will be described in detail by the accompanying drawings. The accompanying drawings are not drawn to scale. These embodiments are non-limiting exemplary embodiments, in which the same numbers in each figure represent similar structures, wherein:

[0021] Figure 1is a schematic diagram of an exemplary security monitoring system according to some embodiments of the present specification;

[0022] Figure 2 is a schematic diagram of exemplary hardware and / or software components of an exemplary computing device according to some embodiments of the present specification;

[0023] Figure 3 is a schematic diagram of hardware and / or software components of an exemplary mobile device 300 according to some embodiments of the present specification;

[0024] Figure 4 is a block diagram of an exemplary processing device according to some embodiments of the present specification;

[0025] Figure 5 is a flowchart of an exemplary process for monitoring the status of a power supply unit according to some embodiments of the present specification;

[0026] Figure 6 is a flowchart of an exemplary process for identifying an abnormal state of a target object according to some embodiments of this specification;

[0027] Figure 7 is a flowchart of an exemplary process for determining a state of a power unit of an electric vehicle based at least in part on attribute values ​​of one or more performance attributes of the power unit according to some embodiments of the present specification;

[0028] Figure 8 is a flowchart of an exemplary process for determining a state of a power unit of an electric vehicle based at least in part on attribute values, the attribute values ​​being one or more performance attributes of the power unit, according to some embodiments of the present specification; and

[0029] Fig. 9 is a flowchart of an exemplary process for determining a state of a power unit of an electric vehicle based at least in part on attribute values, the attribute values ​​being one or more performance attributes of the power unit, according to some embodiments of the present specification. DETAILED DESCRIPTION

[0030] The following description is intended to enable a person of ordinary skill in the art to implement and utilize the present application, and the description is provided in the context of a specific application scenario and its requirements. It will be apparent to a person of ordinary skill in the art that various changes may be made to the disclosed embodiments, and that the general principles defined in the present application may be applied to other embodiments and application scenarios without departing from the principles and scope of the present application. Therefore, the present application is not limited to the described embodiments, but should be given the broadest scope consistent with the claims.

[0031] The terms used in this application are only for the purpose of describing specific example embodiments and are not restrictive. As used in this application, the singular forms "a", "an" and "the" may also include plural forms unless the context clearly indicates an exception. It is further understood that the terms "include" and / or "comprise", when used in this specification, specify the presence of the features, integers, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, operations, elements, components and / or combinations thereof.

[0032] It should be understood that the terms "system", "engine", "unit", "module" and / or "block" used herein are a method of distinguishing different components, elements, parts, portions or assemblies at different levels in ascending order. However, these terms may also be replaced by other expressions if the same purpose can be achieved.

[0033] Generally, the terms "module", "unit" or "block" as used herein refer to logic embodied in hardware or firmware, or a collection of software instructions. The modules, units or blocks described herein may be implemented as software and / or hardware, and may be stored in any type of non-transitory computer-readable medium or another storage device. In some embodiments, software modules / units / blocks may be compiled and linked into an executable program. It should be understood that software modules may be called from other modules / units / blocks or from themselves, and / or may be called in response to detected events or interrupts. Configuration for use in a computing device (e.g., such as Figure 2 The software modules / units / blocks executed on the processor 220 shown in the figure can be set on a computer-readable medium, such as an optical disk, a digital video disk, a flash drive, a disk or any other tangible medium, or as a digital download (which can be initially stored in a compressed or installable format, which needs to be installed, decompressed or decrypted before execution). The software code here can be stored in part or in whole in the storage device of the computing device performing the operation and applied in the operation of the computing device. The software instructions can be embedded in firmware, such as EPROM. It should also be understood that the hardware modules / units / blocks can be included in connected logical components, such as gates and triggers, and / or can include programmable units, such as programmable gate arrays or processors. The modules / units / blocks or computing device functions described here can be implemented as software modules / units / blocks, but can be represented by hardware or firmware. Generally, the modules / units / blocks described here refer to logical modules / units / blocks, which can be combined with other modules / units / blocks or divided into sub-modules / sub-units / sub-blocks, although they are physical organizations or storage devices. This description can be applicable to the system, engine or part thereof.

[0034] It is understood that, unless the context clearly indicates otherwise, when a unit, engine, module, or block is referred to as being "on," "connected," or "coupled to" another unit, engine, module, or block, it may be directly on, connected, coupled, or in communication with the other unit, engine, module, or block, or there may be intermediate units, engines, modules, or blocks. In this application, the term "and / or" may include any one or more of the relevant listed items or combinations thereof.

[0035] The flowcharts used in this application illustrate the operations performed by the systems shown in some embodiments of this specification. It should be clearly understood that the operations of the flowcharts may not be performed in order. Instead, these operations may be implemented in the reverse order, or simultaneously. At the same time, one or more other operations may also be added to these flowcharts. One or more operations may also be deleted from the flowcharts.

[0036] These and other features, characteristics, and methods of operation and functions of structurally related elements of the present invention, as well as combinations of parts and economies of manufacture may become more apparent upon consideration of the following description with reference to the accompanying drawings, all of which form a part of this invention. It should be understood, however, that the drawings are for illustration and description purposes only and are not intended to limit the scope of the present application. It should be understood that the drawings are not drawn to scale.

[0037] In addition, the safety monitoring system and method of the present invention can be applied to any other type of transportation system. For example, the safety monitoring system in the present invention can be applied to transportation systems in different environments, including land, sea, aerospace, etc., or any combination thereof. The vehicles of the transportation system may include cars, buses, trains, subways, ships, airplanes, spacecraft, hot air balloons, etc., or any combination thereof. For illustrative purposes only, the safety monitoring system and method of the present invention specification are mainly described for electric vehicles. It should be understood that this is only an exemplary embodiment and is not intended to be limiting.

[0038] One aspect of the present invention relates to a safety monitoring system and method. According to the method, parameter values ​​of one or more motion parameters associated with a target object (e.g., an electric vehicle) can be obtained. The motion parameter can be the acceleration, velocity, etc. of the target object. An abnormal state of the target object, such as a suspected accident, can be identified based on the parameter value. In response to identifying the abnormal state of the target object, one or more performance attributes of a power supply unit that supplies power to the target object can be obtained. Exemplary performance attributes may include voltage characteristics, temperature characteristics, resistance characteristics, etc., or any combination thereof. Then, the state of the power supply unit can be determined based at least in part on the attribute values ​​of one or more performance attributes. In this case, the performance attributes of the power supply device can be effectively monitored when any suspected accident occurs to the target object. In addition, the count of suspected accidents occurring over a period of time can be recorded, and the health monitoring of the power supply device can be performed in combination with the count of suspected accidents.

[0039] Figure 1 1 is a schematic diagram showing an exemplary security monitoring system according to some embodiments of the present specification. The security monitoring system 100 can monitor and evaluate the health of a power supply unit installed in a target object. In some embodiments, the target object may be a mobile object, and the power supply unit may provide power to the target object. In some embodiments, the power supply unit may include a battery, such as a lithium battery, a lead-acid battery, a fuel cell battery, etc. The target object may be an electric vehicle, an electric toy, a mobile terminal (e.g., a mobile phone), a smart wearable device, etc. In some embodiments, the target object equipped with a power supply unit may be an electric vehicle. Unless otherwise expressly stated, the following description of the battery monitoring system is provided, and the target object is an electric vehicle powered by a battery. However, it should be understood that this is for illustrative purposes only and is not intended to be limiting. Exemplary electric vehicles may include electric vehicles, electric buses, electric trucks, electric bicycles, electric motorcycles, electric trains, electric subways, electric ships, electric ships, electric aircraft (e.g., unmanned aerial vehicles (UAV)), etc.

[0040] The security monitoring system 100 may include a processing device 110, a network 120, a user terminal 130, an electric vehicle 140, and a storage device 150. The processing device 110 may be configured to process information related to the electric vehicle 140. For example, the processing device 110 may obtain parameter values ​​of one or more motion parameters of the electric vehicle 140, and identify an abnormal state of the electric vehicle 140 based on the parameter values. As another example, the processing device 110 may obtain one or more performance attributes of a power supply unit of the electric vehicle 140, and determine the state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes. In some embodiments, the processing device 110 may be a single server or a server group. The server group may be centralized or distributed (for example, the processing device 110 may be a distributed system). In some embodiments, the processing device 110 may be local or remote. For example, the processing device 110 may access information and / or data stored in the user terminal 130 and / or the storage device 150 via the network 120. As another example, the processing device 110 may be directly connected to the user terminal 130 and / or the storage device 150 to access information and / or data. In some embodiments, the processing device 110 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc., or any combination thereof. In some embodiments, the processing device 110 may be implemented on a cloud platform having the present invention. Figure 2 One or more components shown in the figure are implemented on a computing device.

[0041] In some embodiments, the processing device 112 may include one or more processing engines (e.g., a single-core processing engine or a multi-core processor). By way of example only, the processing device 112 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction set processor (ASIP), a graphics processing unit (GPU), a physical processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, etc., or any combination thereof.

[0042] The network 120 may include any suitable network that can facilitate the exchange of information and / or data. In some embodiments, one or more components in the security monitoring system 100 (e.g., the processing device 110, the user terminal 130, the electric vehicle 140, and / or the storage device 150) may send information and / or data to other components in the security monitoring system 100 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or any combination thereof. By way of example only, the network 120 may include a wired network, a cable network, an optical fiber network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, a global system for mobile communications (GSM) network, a code division multiple access (CDMA) network, a time division multiple access (TDMA) network, a general packet radio service (GPRS) network, an enhanced data rate for GSM evolution (EDGE) network, a wideband code division multiple access (WCDMA) network, a high speed downlink packet access (HSDPA) network, a long term evolution (LTE) network, a user datagram protocol (UDP) network, a transmission control protocol / internet protocol (TCP / IP) network, a short message service (SMS) network, a wireless application protocol (WAP) network, an ultra-wideband (UWB) network, infrared, etc., or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include wired or wireless network access points, such as base stations and / or Internet exchange points 120-1, 120-2, ..., through which one or more components of the security monitoring system 100 can connect to the network 120 to exchange data and / or information.

[0043] In some embodiments, the user terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, a desktop computer 130-4, etc., or any combination thereof. In some embodiments, the mobile device 130-1 may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, etc., or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart foot, a smart glass, a smart helmet, a smart watch, a smart clothing, a smart backpack, a smart accessory, etc., or any combination thereof. In some embodiments, the smart mobile device may include a smart phone, a personal digital assistant (PDA), a gaming device, a navigation device, a point of sale (POS), etc., or any combination thereof. In some embodiments, the virtual reality device and / or the augmented reality device may include a virtual reality helmet, virtual reality glasses, virtual reality goggles, an augmented reality helmet, augmented reality glasses, augmented reality goggles, etc., or any combination thereof. For example, the virtual reality device and / or the augmented reality device may include Google Glass, Oculus Rift, Hololens, Gear VR, etc. In some embodiments, the terminal 130 may remotely operate one or more components of the security monitoring system 100. In some embodiments, the terminal 130 may receive information and / or instructions input by a user, and send the received information and / or instructions to the processing device 110 through the network 120. In some embodiments, the terminal 130 may receive data and / or information from the processing device 110. For example, a user (e.g., a driver) may obtain the status of the power supply unit of the electric vehicle 140 determined by the processing device 110 through the user terminal 130.

[0044] The electric vehicle 140 may be a vehicle used in a transportation system. It is contemplated that the electric vehicle 140 may be a pure electric vehicle with an electric motor, or a hybrid vehicle including an internal combustion engine and at least one electric motor (e.g., for driving the vehicle at different speeds). The electric vehicle 140 may include a power supply unit (not shown) for providing power to the electric motor. In some embodiments, the power supply unit may be or include a battery assembly. In some embodiments, the battery assembly may have one or more batteries. One or more batteries may be connected in series and / or in parallel to provide a relatively large power output.

[0045] The electric vehicle 140 may have a body and at least one wheel. The body may be of any type, such as a convertible, a sport utility vehicle (SUV), a coupe, a minivan, a pickup truck, a station wagon, a cabin, a train car, a fuselage, etc. In some embodiments, the electric vehicle 140 may include a pair of front wheels and a pair of rear wheels. It is contemplated that the electric vehicle 140 may have more or less wheels or equivalent structures (e.g., air jets, at least one propeller, etc.) to enable the electric vehicle 140 to move. The electric vehicle 140 may be configured as all-wheel drive (AWD), front-wheel drive (FWR), rear-wheel drive (RWD), etc. The electric vehicle 140 may be configured to be remotely and / or autonomously operated, for example, by a driver, an operator in the vehicle.

[0046] In some embodiments, the electric vehicle 140 may be equipped with a plurality of sensors (not shown) for detecting data / information of the electric vehicle 140 and / or the power supply unit. The plurality of sensors may include, for example, at least one motion sensor (e.g., a speed sensor, an acceleration sensor, a rotation sensor, etc.), at least one electrical sensor (e.g., a voltage sensor, a current sensor, a resistance sensor, etc.), at least one temperature sensor, at least one pressure sensor, etc., or any combination thereof. In some embodiments, the plurality of sensors may be mounted on the electric vehicle 140 or the power supply unit using various bonding mechanisms. Exemplary bonding mechanisms may include screws, adhesives, welding, snap-fit ​​joints, etc. In some embodiments, the location and / or type of the plurality of sensors, the manner in which the plurality of sensors are connected to the electric vehicle 140 or the power supply unit, etc. are not limited by the present invention and may be modified to achieve the desired data / information detection performance.

[0047] The storage device 150 may store data and / or instructions. In some embodiments, the storage device 150 may store data / information obtained from the processing device 110, the user terminal 130, the electric vehicle 140, etc. In some embodiments, the storage device 150 may store data and / or instructions, and the processing device 110 may execute or use these data and / or instructions to perform the exemplary methods described in this specification. In some embodiments, the storage device 150 may include a mass storage, a removable storage, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. Exemplary mass storage may include a disk, an optical disk, a solid-state drive, etc. Exemplary removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a compressed disk, a tape, etc. Exemplary volatile read-write memory may include a random access memory (RAM). Exemplary RAM may include a dynamic random access memory (DRAM), a double data rate synchronous dynamic random access memory (DDR SDRAM), a static random access memory (SRAM), a thyristor random access memory (T-RAM), and a zero capacitance random access memory (Z-RAM), etc. Exemplary ROMs may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (PEROM), electrically erasable programmable ROM (EEPROM), compact disk ROM (CD-ROM), and digital versatile disk ROM, etc. In some embodiments, the storage device 150 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc., or any combination thereof.

[0048] In some embodiments, the storage device 150 may be connected to the network 120 to communicate with one or more components in the security monitoring system 100 (e.g., the processing device 110, the user terminal 130, the electric vehicle 140, etc.). One or more components in the security monitoring system 100 may access data or instructions stored in the storage device 150 via the network 120. In some embodiments, the storage device 150 may be directly connected to or communicate with one or more components in the security monitoring system 100 (e.g., the processing device 110, the user terminal 130, the electric vehicle 140, etc.). In some embodiments, the storage device 150 may be part of the processing device 110.

[0049] It should be noted that the description of the above-mentioned security monitoring system 100 is for illustrative purposes only and is not intended to limit the scope of the present invention. For those of ordinary skill in the art, the components included in the security monitoring system 100 can be combined or adjusted in various ways, or connected to other components as a subsystem, and various changes and modifications can be made under the teachings of the present invention. However, these changes and modifications may not deviate from the spirit and scope of the present invention. For example, the terminal 130 may be a part of the processing device 110. As another example, the terminal 130 may be omitted. All of these modifications are within the scope of protection of the present invention.

[0050] Figure 2 is a schematic diagram of exemplary hardware and / or software components of an exemplary computing device according to some embodiments of the present specification. In some embodiments, Figure 2 The processing device 110 and / or the user terminal 130 are implemented on the illustrated computing device 200. For example, the processing device 112 may be implemented on the computing device 200 and configured to perform the functions of the processing device 112 described in this application.

[0051] The computing device 200 may be used to implement any component of the security monitoring system 100 as described herein. For example, the processing device 112 may be implemented on the computing device 200 by its hardware, software program, firmware, or a combination thereof. Although only one such computer is shown, for convenience, the computer functions described herein may be implemented in a distributed manner across multiple similar platforms to distribute the processing load.

[0052] For example, the computing device 200 may include a communication port 250 connected to a network to enable data communication. The computing device 200 may also include a processor (e.g., processor 220) in the form of one or more processors (e.g., logic circuits) for executing program instructions. For example, the processor 220 may include an interface circuit and a processing circuit therein. The interface circuit may be configured to receive an electrical signal from the bus 210, wherein the electrical signal encodes structured data and / or instructions processed by the processing circuit. The processing circuit may perform logical calculations and then encode conclusions, results, and / or instructions into electrical signals. The interface circuit may then send an electrical signal from the processing circuit via the bus 210.

[0053] The exemplary computing device may also include different forms of program storage and data storage, for example, including a disk 270 and a read-only memory (ROM) 230 or a random access memory (RAM) 240 for various data files processed and / or transmitted by the computing device. The exemplary computing device may also include program instructions stored in ROM 230, RAM 240 and / or other forms of non-transitory storage media that can be executed by the processor 220. The methods and / or processes of the present application may be implemented in the form of program instructions. The computing device 200 may also include an I / O 260 that supports input / output between the computer and other components. The computing device 200 may also receive programming and data via network communications.

[0054] For illustration purposes only, Figure 2 Only one processor is described in the present invention, and multiple processors 220 may also be considered. Therefore, as described in the present invention, the operations and / or method steps performed by one processor 220 may also be performed jointly or individually by multiple processors. For example, if in the present invention, the processor 220 of the computing device 200 performs step A and step B simultaneously, it should be understood that step A and step B may also be performed jointly or individually by two different processors 220 in the computing device 200 (for example, the first processor performs step A, the second processor performs step B, or the first and second processors jointly perform steps A and B).

[0055] Figure 3 is a schematic diagram of hardware and / or software components of an exemplary mobile device 300 according to some embodiments of the present specification. Figure 3 As shown, the mobile device 300 may include a communication module 310, a display 320, a graphics processing unit (GPU) 330, a central processing unit (CPU) 340, an input / output 350, a memory 360, and a storage 390. In some embodiments, any other suitable components, including but not limited to a system bus or a controller (not shown), may also be included in the mobile device 300. In some embodiments, a mobile operating system 370 (e.g., iOS, Android, Windows Phone, etc.) and one or more applications 380 may be loaded from the storage 390 into the memory 360 for execution by the CPU 340. The application 380 may include a browser or any other suitable mobile application for receiving and presenting information related to data processing or other information from the processing device 110. User interaction with the information flow may be implemented through the input / output 350 and provided to the processing device 110 and / or other components of the security monitoring system 100 through the network 120.

[0056] In order to implement the various modules, units and functions thereof described in this application, a computer hardware platform can be used as a hardware platform for one or more components described herein. The hardware components, operating systems and programming languages ​​of such computers are conventional in nature, and it is assumed that those skilled in the art are sufficiently familiar with these technologies to adapt these technologies to generate safety reports such as those described below. A computer with user interface elements can be used to implement a personal computer (PC) or other type of workstation or terminal device, although if properly programmed, the computer can also serve as a server. It is believed that those skilled in the art are familiar with the structure, programming and general operation of such computer devices, and therefore, the drawings should be self-explanatory.

[0057] Figure 4 1 is a block diagram of an exemplary processing device according to some embodiments of the present specification. The processing device 110 may include an acquisition module 410, an abnormality identification module 420, and a safety determination module 430. One or more modules of the processing device 110 may be interconnected. The connection may be wireless or wired. In some embodiments, at least a portion of the processing device 110 may be connected to a network such as a wireless network. Figure 2 The computing device 200 shown or Figure 3 The mobile device 300 is shown as being implemented.

[0058] The acquisition module 410 can acquire data and / or information. The acquisition module 410 can acquire data and / or information from the processing device 110, the terminal 130, the electric vehicle 140, the storage device 150, or any device or component capable of storing data via the network 120. For example, the acquisition module 410 can acquire data and / or information from a cloud data center (not shown) via the network 120. The acquired data and / or information may include parameter values ​​of one or more motion parameters associated with the electric vehicle 140. In some embodiments, the one or more motion parameters may include one or more acceleration-related parameters, one or more speed-related parameters, one or more spin angular velocity-related parameters, and the like of the electric vehicle 140. The acquisition module 410 can also acquire attribute values ​​of one or more performance attributes of the power supply unit of the electric vehicle 140. One or more performance attributes may be related to a short circuit, an open circuit, a temperature rise, an increase in resistance, and the like of the power supply unit. The processing device 110 can process or analyze the attribute values ​​of one or more performance attributes to assess the health of the power supply unit. In some embodiments, the one or more performance attributes may include one or more voltage-related characteristics, one or more current-related characteristics, one or more resistance-related characteristics, one or more temperature-related characteristics, and the like of the power supply unit. The acquisition module 410 may also acquire processing results, user instructions, algorithms, models, parameters, program codes, other information of the driver of the vehicle 140 or the electric car 140 , etc., or any combination thereof.

[0059] The abnormality identification module 420 may identify an abnormal state of the electric vehicle. In some embodiments, the abnormal state of the electric vehicle 140 may indicate a suspected accident of the electric vehicle 140. For example, the accident of the electric vehicle 140 may be a car accident of the electric vehicle 140 at a specific speed (e.g., 80 km / h, 100 km / h, 120 km / h, 150 km / h, etc.). In some embodiments, the abnormality identification module 420 may process parameter values ​​of one or more motion parameters of the electric vehicle 140, and identify an abnormal state of the electric vehicle 140 based on the processed parameter values ​​of the one or more motion parameters of the electric vehicle 140.

[0060] In some embodiments, the abnormality identification module 420 may determine whether one or more collision conditions associated with the electric vehicle 140 are satisfied based on the parameter value. If at least one of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the abnormality identification module 420 may determine that the electric vehicle 140 is in an abnormal state. If none of the one or more collision conditions associated with the electric vehicle 140 are satisfied, the abnormality identification module 420 may determine that the electric vehicle 140 is in a normal state.

[0061] The safety determination module 430 may determine the status of the power unit of the electric vehicle 140. In some embodiments, the safety determination module 430 may determine the status of the power unit based at least in part on attribute values ​​of one or more performance attributes.

[0062] In some embodiments, the safety determination module 430 may determine whether one or more safety warning conditions associated with each type of performance attribute (e.g., voltage-related characteristics, resistance-related characteristics, temperature-related characteristics, etc.) are satisfied based on characteristic values ​​of one or more performance attributes. In some embodiments, one or more safety warning conditions associated with each type of performance attribute may be used to characterize or quantify the health (e.g., stability) of the power supply unit.

[0063] If at least one of the one or more safety warning conditions of at least one type of performance attribute is met, the safety determination module 430 can determine that the power supply unit is in an unsafe state. The unsafe state may indicate that the power supply unit is seriously affected by a suspected accident (for example, the power supply unit is seriously damaged). If the power supply unit continues to supply power to the electric vehicle 140, there may be risks of power supply unit short circuit, sudden temperature rise, spontaneous combustion, etc. In this case, it may be necessary to inspect and / or repair the power supply unit. For example, an ultrafast discharge device (UFDD) can be used to discharge the power supply unit. Each component of the power supply unit can be checked to identify damaged components. In some embodiments, damaged components can be replaced or repaired.

[0064] If one or more safety warning conditions associated with all types of performance attributes are not met, the safety determination module 430 may determine that the power supply unit is in a safe state. The safe state may indicate that the power supply unit is not affected by the suspected accident (e.g., the power supply unit is not damaged or slightly damaged) and is able to supply power to the electric vehicle 140 normally.

[0065] It should be noted that the above description of the processing device 112 is provided for illustrative purposes only and is not intended to limit the scope of the present invention. For those of ordinary skill in the art, various changes and modifications can be made according to the description of this specification. For example, the processing device 110 may also include a storage module that facilitates data storage. However, these changes and modifications do not depart from the scope of the present application.

[0066] Figure 5 is a flowchart of an exemplary process for monitoring the status of a power supply unit according to some embodiments of the present specification. In some embodiments, Figure 5 The process 500 shown may be performed at Figure 1 For example, at least a portion of the process 500 may be stored in a storage device (e.g., a disk 270 of the computing device 200) as an instruction and executed by a processing device 110 (e.g., a processor 220 of the computing device 200, Figure 4 In some embodiments, a portion of process 500 may be implemented on a terminal device. The operations of process 500 presented below are intended to be illustrative. In some embodiments, process 500 may be completed with one or more additional operations not described, and / or without one or more of the operations discussed. Figure 5 The order in which the operations of process 500 are illustrated and described below is not intended to be limiting.

[0067] In 510 , the processing device 110 (eg, the acquisition module 410 ) may acquire parameter values ​​of one or more motion parameters associated with the electric vehicle.

[0068] In some embodiments, the electric vehicle (e.g., the electric vehicle 140) may be equipped with at least one motion sensor for sensing the motion of the electric vehicle 140. In some embodiments, the processing device 110 may obtain parameter values ​​of one or more motion parameters associated with the electric vehicle 140 from the at least one motion sensor. In some embodiments, the processing device 110 may obtain parameter values ​​of one or more motion parameters associated with the electric vehicle 140 from a storage device (e.g., the storage device 150, the disk 270, etc.) of the security monitoring system 100.

[0069] At least one motion sensor may be used to detect one or more motion parameters associated with the electric vehicle 140. In some embodiments, the one or more motion parameters may include one or more acceleration-related parameters, one or more speed-related parameters, one or more spin angular velocity-related parameters, and the like of the electric vehicle 140. As used herein, acceleration-related parameters refer to parameters related to the acceleration of the electric vehicle 140, such as acceleration in a specific direction, average acceleration in one or more directions (e.g., arithmetic mean acceleration, weighted average, harmonic average), and the like. Similarly, speed-related parameters refer to parameters related to the speed of the electric vehicle 140, such as speed (e.g., in a certain direction), average speed in one or more directions, and the like. Spin angular velocity-related parameters refer to parameters related to the spin angular velocity of the electric vehicle 140, such as angular velocity, average angular velocity, and the like.

[0070] In some embodiments, one or more acceleration-related parameters, one or more velocity-related parameters, and one or more spin angular velocity-related parameters may be detected by at least one acceleration sensor, at least one velocity sensor, and at least one spin sensor, respectively. Exemplary acceleration sensors may include piezoelectric accelerometers, piezoresistive accelerometers, variable capacitance accelerometers, variable magnetoresistive accelerometers, etc. Exemplary velocity sensors may include laser sensors, radars, etc. Exemplary spin sensors may include gyroscope sensors, etc.

[0071] In some embodiments, a coordinate system may be established in the three-dimensional space where the electric vehicle 140 is located in conjunction with the electric vehicle 140. The coordinate system may be a Cartesian coordinate system, a polar coordinate system, etc. In some embodiments, the coordinate system may be a Cartesian coordinate system. For illustration purposes only, the X-axis of the Cartesian coordinate system (also referred to as the X-axis direction of the electric vehicle 140) may be consistent with the length direction of the electric vehicle 140. The Y-axis of the Cartesian coordinate system (also referred to as the Y-axis direction of the electric vehicle 140) may be consistent with the width direction of the electric vehicle 140. The Z-axis of the Cartesian coordinate system (also referred to as the Z-axis direction of the electric vehicle 140) may be consistent with the height direction of the electric vehicle 140.

[0072] In some embodiments, each of at least a portion of the one or more motion parameters may correspond to an axial direction of the electric vehicle 140. For example, acceleration-related parameters of the electric vehicle 140 (e.g., acceleration at a time point, average acceleration at different time points) may correspond to one of the X-axis direction, the Y-axis direction, or the Z-axis direction.

[0073] In some embodiments, each of the one or more motion parameters may correspond to at least two axes of the electric vehicle 140. In some embodiments, each of the one or more motion parameters may be an average value of the motion parameters corresponding to at least two axes of the electric vehicle 140. For example, the average acceleration of the electric vehicle 140 may be an average value of the accelerations corresponding to all axes of the electric vehicle 140. For example, the average acceleration may be the arithmetic mean of the accelerations of the electric vehicle 140 corresponding to the X-axis direction, the Y-axis direction, and the Z-axis direction, respectively. It should be noted that the average value of the motion parameter is for illustrative purposes only and is not intended to be limiting. Instead of the average value of the motion parameter, a median, maximum value, minimum value, etc. of the motion parameter corresponding to at least two axes of the coordinate system may be provided.

[0074] In 520 , the processing device 110 (eg, the abnormality identification module 420 ) may identify an abnormal state of the electric vehicle based on the parameter value.

[0075] In some embodiments, the abnormal state of the electric vehicle 140 may indicate a suspected accident of the electric vehicle 140. For example, the accident of the electric vehicle 140 may be a car accident that occurs when the electric vehicle 140 is traveling at a specific speed (e.g., 80 km / h, 100 km / h, 120 km / h, 150 km / h, etc.). In some embodiments, the processing device 110 may process parameter values ​​of one or more motion parameters of the electric vehicle 140, and identify the abnormal state of the electric vehicle 140 based on the processed parameter values ​​of the one or more motion parameters of the electric vehicle 140.

[0076] In some embodiments, the processing device 110 may determine whether one or more collision conditions associated with the electric vehicle 140 are satisfied based on the parameter values. If at least one of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the processing device 110 may determine that the electric vehicle 140 is in an abnormal state. If none of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the processing device 110 may determine that the electric vehicle 140 is in a normal state. The one or more collision conditions may characterize or quantify the severity of a suspected accident of the electric vehicle 140. In some embodiments, the one or more collision conditions may involve parameter values ​​of one or more motion parameters and at least one threshold value. More details on the identification of abnormal states of electric vehicles can be found elsewhere in the present invention, for example Figure 6 and its description.

[0077] In some embodiments, the safety monitoring system 100 may record the count of abnormal states (e.g., the total number of abnormal states) within a period of time into a storage device (e.g., storage device 150, disk 270, etc.) of the safety monitoring system 100. The time period may be from the time point when the power supply unit is manufactured or repaired to the current time point. In some embodiments, at the time point when the power supply unit is manufactured or repaired, the count of abnormal states may be set to zero. In some embodiments, in order to record the count of abnormal states within the time period, the safety monitoring system 100 may obtain a priori count of abnormal states of the electric vehicle 140, and generate a current count of abnormal states by increasing the priori count of abnormal states by 1 in response to identifying a new abnormal state. The abnormal state priority count refers to the total number of abnormal states identified before a suspected accident of the electric vehicle occurs. The current count of abnormal states may be recorded as a count of abnormal states to be stored in a storage device. In some embodiments, the current count of abnormal states may be used to assess the health of the power supply unit. For example, the current count of abnormal states may be used to determine the state of the power supply unit (e.g., a safe state or an unsafe state).

[0078] In 530 , the processing device 110 (eg, the acquisition module 410 ) acquires attribute values ​​of one or more performance attributes of the power supply unit in response to identifying the abnormal state of the electric vehicle.

[0079] In some embodiments, the power supply unit of the electric vehicle 140 may be mounted on the electric vehicle 140. For example, the power supply unit may be mounted on the chassis of the electric vehicle 140 in the form of, for example, a battery assembly block or plate. Therefore, a suspected accident of the electric vehicle 140 may result in damage to the power supply unit. Damage to the power supply unit may pose a suspected safety hazard to the electric vehicle 140 and the driver. For example only, if the battery cell of the battery assembly installed on the electric vehicle 140 is damaged (for example, deformation, cracks, or battery leakage occurs on the battery cell), the power supply unit may be at risk of short circuit, open circuit, temperature rise, resistance change, etc.

[0080] In some embodiments, if the electric vehicle is in an abnormal state, the processing device 110 may obtain attribute values ​​of one or more performance attributes of the power supply unit. The one or more performance attributes may be related to a short circuit, an open circuit, a temperature rise, an increase in resistance, etc. of the power supply unit. The processing device 110 may process or analyze the attribute values ​​of the one or more performance attributes to evaluate the health of the power supply unit.

[0081] In some embodiments, the one or more performance attributes may include one or more voltage-related characteristics, one or more current-related characteristics, one or more resistance-related characteristics, one or more temperature-related characteristics, etc. of the power unit. As used herein, voltage-related characteristics refer to parameters related to the voltage of one or more components (e.g., battery cells) of the power unit of the electric vehicle 140, such as the voltage of a component of the power unit, the average voltage of one or more components of the power unit (e.g., arithmetic mean voltage), etc. Similarly, temperature-related characteristics refer to parameters related to the temperature of one or more components of the power unit of the electric vehicle 140, such as the temperature of a component of the power unit, the average temperature of one or more components of the power unit (e.g., arithmetic mean temperature), etc. Resistance-related characteristics refer to parameters related to the resistance of the power unit of the electric vehicle 140, such as the resistance of the power unit, the average resistance of the power unit (e.g., arithmetic mean resistance), etc. As used herein, the resistance of the power unit refers to the resistance between the power unit and the body of the electric vehicle 140 or the ground.

[0082] One or more performance attributes of the power supply unit can be detected by using, for example, at least one electrical sensor (e.g., at least one voltage sensor, at least one current sensor, at least one resistance sensor, etc.), at least one temperature sensor, etc. Exemplary voltage sensors may include suspicious transformers, Hall voltage sensors, etc. Exemplary current sensors may include Hall current sensors, Rogowski current sensors, fiber optic current sensors, etc. Exemplary resistance sensors may include photoresistor sensors, thermistor sensors, etc. Exemplary temperature sensors may include mercury thermometers, infrared thermometers, etc. In some embodiments, each example sensor can detect the property value of the performance attribute of one or more components of the power supply unit or the entire power supply unit. For example, the voltage value of each component of the power supply unit can be detected by an independent voltage sensor. As another example, the components of the power supply unit can be divided into two or more groups, and the temperature of each group can be detected by a temperature sensor. As yet another example, the resistance of the power supply unit can be detected by a resistance sensor.

[0083] At 540 , the processing device 110 (eg, the safety determination module 430 ) may determine a state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes.

[0084] In some embodiments, the processing device 110 may determine whether one or more safety warning conditions associated with each type of performance attribute (e.g., voltage-related characteristics, resistance-related characteristics, temperature-related characteristics, etc.) are satisfied based on characteristic values ​​of the one or more performance attributes. In some embodiments, the one or more safety warning conditions associated with each type of performance attribute may be used to characterize or quantify the health (e.g., stability) of the power supply unit.

[0085] If at least one of the one or more safety warning conditions of at least one type of performance attribute is met, the processing device 110 can determine that the power supply unit is in an unsafe state. The unsafe state may indicate that the power supply unit is seriously affected by a suspected accident (for example, the power supply unit is seriously damaged). If the power supply unit continues to power the electric vehicle 140, there may be risks of power supply unit short circuit, sudden temperature rise, spontaneous combustion, etc. In this case, it may be necessary to inspect and / or repair the power supply unit. For example, an ultrafast discharge device (UFDD) can be used to discharge the power supply unit. Each component of the power supply unit can be checked to identify damaged components. In some embodiments, damaged components can be replaced or repaired.

[0086] If one or more safety warning conditions associated with all types of performance attributes are not met, the processing device 110 can determine that the power supply unit is in a safe state. The safe state may indicate that the power supply unit has not been affected by the suspected accident (e.g., the power supply unit is not damaged or slightly damaged) and is able to power the electric vehicle 140 normally. More details on determining the state of the power supply unit can be found elsewhere in this application, for example, Figure 7-9 and its description.

[0087] In some embodiments, the processing device 110 may determine that the power supply unit is in a safe state if one or more safety warning conditions associated with all types of performance attributes (e.g., voltage-related characteristics, resistance-related characteristics, temperature-related characteristics, etc.) are satisfied. In some embodiments, the one or more safety warning conditions may vary according to one or more types of available performance attributes. For example, if the electric vehicle 140 is only equipped with at least one voltage sensor, the processing device 110 may determine that the power supply unit is in a safe state if one or more safety warning conditions are associated with voltage-related characteristics.

[0088] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of the present application. For those of ordinary skill in the art, various changes and modifications can be made according to the description of this specification. However, these changes and modifications belong to the scope of the present invention.

[0089] For example, at least a portion of the motion sensor may be mounted on a power supply unit of the electric vehicle 140. The processing device 110 may obtain parameter values ​​of motion parameters detected by at least a portion of the motion sensor mounted on the power supply unit. In this case, the processing device 110 (e.g., the abnormality identification module 420) may identify an abnormal state based on the obtained parameter values. In this case, the safety monitoring system and method may be applied to various situations, such as during the manufacturing process of the power supply unit, the fall of the power supply unit, the impact of the power supply unit, etc.

[0090] Figure 6 is a flowchart of an exemplary process for identifying an abnormal state of a target object according to some embodiments of this specification. In some embodiments, Figure 6 The process 600 shown may be performed at Figure 1 For example, at least a portion of the process 600 may be stored in a storage device (e.g., a disk 270 of the computing device 200) as an instruction and executed by a processing device 110 (e.g., a processor 220 of the computing device 200, Figure 4 In some embodiments, a portion of process 600 may be implemented on a terminal device. The operations of process 600 presented below are intended to be illustrative. In some embodiments, process 600 may be performed with one or more additional operations not described, and / or without one or more of the operations discussed. Figure 6 The order of the operations of process 600 shown and described below is not intended to be limiting. In some embodiments, the following operations may be performed according to process 600: Figure 5 Operation 520 of process 500 is shown.

[0091] In 610, the processing device 110 may obtain parameter values ​​of one or more acceleration-related parameters associated with the electric vehicle. In some embodiments, the one or more acceleration-related parameters may include one or more accelerations. Each of the one or more accelerations may correspond to each of one or more axes of the electric vehicle 140. In some embodiments, the one or more acceleration-related parameters may also include an average acceleration (e.g., root mean square, arithmetic mean, etc.) of one or more accelerations of one or more axes. By way of example only, the one or more acceleration-related parameters may include the acceleration of the electric vehicle along the axis of the electric vehicle 140 at a certain point in time, the average acceleration along the axis over a period of time, the acceleration modulus of the electric vehicle 140 along at least two axes at a certain point in time, the average acceleration modulus along at least two axes over a period of time, etc.

[0092] At 620, the processing device 110 may determine whether one or more collision conditions associated with the electric vehicle 140 are satisfied based on the parameter values ​​of the one or more acceleration-related parameters. If at least one of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the process 600 may continue to 630. If none of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the processing device 110 may determine that the electric vehicle is in a normal state.

[0093] In some embodiments, the one or more collision conditions may include a first collision condition and a second collision condition. In some embodiments, the first collision condition may be related to a parameter value corresponding to at least one acceleration in the axial direction. For example, the first collision condition may be expressed by formula (1):

[0094]

[0095] Among them, a it represents the parameter value of the acceleration of the electric vehicle at time point t within time period t along the i-axis direction, where the i-axis direction includes, for example, the X-axis direction, the Y-axis direction or the Z-axis direction, The parameter value representing the average acceleration along the i-axis in the time period t, a N Represents the acceleration threshold corresponding to the i-axis. In some embodiments, the time period T and the threshold may be determined by a user (e.g., a technician) according to the default settings of the safety monitoring system 100. In some embodiments, the threshold may be an empirical value. As an example only, the time period T may be five minutes, half an hour, one hour, two hours, one day, one week, etc. In some embodiments, the time period T may be from the time point when the electric vehicle 140 starts to travel to the current time point. In some embodiments, n sampling points for sampling one or more acceleration-related parameters may be determined within the time period T, and the time point T may correspond to any one of the n sampling points. For example, the parameter value of the average acceleration along the i-axis may be determined according to formula (2):

[0096]

[0097] In some embodiments, the second collision condition may be related to a parameter value of an average acceleration of at least two accelerations in one or more axes. For example, the second collision condition may be expressed by formula (3):

[0098]

[0099] Among them, |a kt | represents the parameter value of the acceleration modulus along the k-axis direction of the coordinate system at the time point t, where the k-axis direction includes at least two of the X-axis, the Y-axis and the Z-axis, represents the parameter value of the average value of the acceleration modulus along the k-axis direction in the time period t, and a M In some embodiments, the at least one threshold value may be determined by a user (e.g., a technician) according to a default setting of the safety monitoring system 100. In some embodiments, the at least one threshold value may be an empirical value. The parameter value of the acceleration modulus along the k-axis direction may be determined according to formula (4):

[0100]

[0101] The parameter value of the average value of the acceleration modulus along the k-axis direction within the time period T can be determined according to, for example, formula (5):

[0102]

[0103] In 630, if at least one of the one or more collision conditions associated with the electric vehicle 140 is satisfied, the processing device 110 may determine that the electric vehicle 140 is in an abnormal state. In some embodiments, the processing device 110 may determine whether at least one of the first collision condition or the second collision condition is satisfied according to formulas (1)-(5).

[0104] It should be noted that the above description is provided for illustrative purposes only and is not intended to limit the scope of the present application. For those of ordinary skill in the art, various changes and modifications can be made according to the description of this specification. However, these changes and modifications belong to the scope of the present invention. For example, the first collision condition may include any parameter value of the acceleration corresponding to the axial direction being greater than the corresponding axial acceleration threshold. As another example, the second collision condition may include a parameter value of the average acceleration of all accelerations of one or more axial directions being greater than the average acceleration threshold.

[0105] Figure 7 1 is a flowchart of an exemplary process for determining a state of a power unit of an electric vehicle based at least in part on attribute values ​​of one or more performance attributes of the power unit according to some embodiments of the present specification. Figure 7 The process 700 shown may be performed at Figure 1 For example, at least a portion of process 700 may be stored in a storage device (e.g., disk 270 of computing device 200) as an instruction and executed by processing device 110 (e.g., processor 220 of computing device 200, Figure 4 In some embodiments, a portion of process 700 may be implemented on a terminal device. The operations of process 700 presented below are intended to be illustrative. In some embodiments, process 700 may be performed with one or more additional operations not described, and / or without one or more of the operations discussed. Figure 7 The order of the operations of process 700 shown and described below is not intended to be limiting. In some embodiments, the following operations may be performed according to process 700: Figure 5 Operation 540 of process 500 is shown.

[0106] In 710 , the processing device 110 may obtain characteristic values ​​of one or more voltage-related characteristics of a power unit of the electric vehicle.

[0107] In some embodiments, one or more voltage-related characteristics of the power supply unit may include the voltage of one or more components of the power supply unit. In some embodiments, one or more voltage-related characteristics of the power supply unit may also include the average voltage of one or more components of the power supply unit within a time period. By way of example only, one or more voltage-related characteristics of the power supply unit may include the voltage of one or more components of the power supply unit at a certain point in time, the voltage difference between the maximum voltage value and the minimum voltage value between the voltage values ​​of one or more components of the power supply unit at a certain point in time, the average voltage difference of the current time period, the average voltage difference of the previous time period, etc. As used herein, the current time period refers to the time period after the suspected accident of the electric vehicle 140 occurs. The previous time period refers to the time period before the suspected accident of the electric vehicle 140 occurs.

[0108] At 720, the processing device 110 may determine whether at least one of the one or more safety warning conditions associated with the one or more voltage-related characteristics is satisfied based on the characteristic values ​​of the one or more voltage-related characteristics. If at least one of the one or more safety warning conditions for the one or more voltages is satisfied, the process 700 may continue to 730. If none of the one or more safety warning conditions for the one or more voltages is satisfied, the process 700 may continue to 740.

[0109] In some embodiments, the one or more safety warning conditions associated with the one or more voltage-related characteristics may include a first voltage warning condition and a second voltage warning condition. In some embodiments, the first voltage warning condition may include that the difference between the maximum voltage value and the minimum voltage value between the voltages of the components of the power supply unit is greater than or equal to the respective maximum voltage difference thresholds. For example, the first voltage warning condition may be expressed by formula (6):

[0110] V max-t -V min-t ≥V L (6)

[0111] Among them, V max-t Represents the maximum voltage value among the voltage values ​​of all components of the power supply unit at time point t in time period t, V min-t Represents the minimum voltage value among the voltage values ​​of all components of the power supply unit at time point t, V L In some embodiments, the time period T and / or the maximum voltage difference threshold V L It can be determined by a user (eg, a technician) according to the default settings of the security monitoring system 100. In some embodiments, the maximum voltage difference threshold V L It can be experience points.

[0112] In some embodiments, the second voltage warning condition may include that the difference between the characteristic value of the average voltage difference in the current time period and the characteristic value of the average voltage difference in the previous time period is greater than or equal to the product of the corresponding maximum voltage difference threshold and the health factor of the power supply unit. For example, the second voltage warning condition can be expressed by formula (7):

[0113]

[0114] in, Indicates the current time period T cur The characteristic value of the average voltage difference, Indicates the previous time period T pre The characteristic value of the average voltage difference in the power supply unit 140, H represents the health factor of the power supply unit. The health factor of the power supply unit can reflect the health of the power supply unit. In some embodiments, the health of the power supply unit may be related to the abnormal state of the electric vehicle 140 in a specific time period. In some embodiments, the health of the power supply unit may be related to the number or count of abnormal states of the electric vehicle in a specific time period Q. For illustration purposes only, the health factor of the power supply unit H can be expressed as (1-min(p / 10,0.5)). min(p / 10,0.5) means that the minimum value is p / 10 or 0.5, and p represents parameter abnormality. In some embodiments, the abnormal parameter p can indicate the abnormal state count (e.g., the current count of abnormal states) in a specific time period Q. In some embodiments, the abnormal parameter p can be a natural number, such as 0, 1, 2, 3, 5, 10, etc. In some embodiments, after the electric vehicle 140 and / or the power supply unit are manufactured or repaired, the abnormal parameter can be set to 0. In some embodiments, each time an abnormal state of the electric vehicle 140 is identified, the abnormal parameter can be increased by a certain number. For example, the specific number can be 1, 2, etc. In some embodiments, the specific number may be related to the severity of the suspected accident indicated by the abnormal state. In some embodiments, the current time period T cur , the previous time period T pre And / or the specific time period Q may be specified by a user (eg, a technician) according to a default setting of the security monitoring system 100, etc. For example, the specific time period Q may be from the time point when the power supply unit is manufactured to the current time point.

[0115] In some embodiments, the current time period T cur The average voltage difference in may be the average value of the voltage differences at different time points. Each voltage difference may be the difference between the maximum voltage and the minimum voltage between the voltage values ​​of the components of the power supply unit at the corresponding time points. For example, the average voltage difference may be determined according to formula (8):

[0116]

[0117] Where n represents the time period T cur The sampling point for sampling the characteristic value of one or more voltages within the time period T, and the time point t may correspond to any one of the n sampling points. In some embodiments, the previous time period T may be similarly determined. pre The average voltage difference in.

[0118] At 730, the processing device 110 may determine that the power supply unit is in an unsafe state. The processing device 110 may determine that the power supply unit is in an unsafe state if at least one of the one or more safety warning conditions associated with the one or more voltage-related characteristics of the power supply unit in equations (6)-(8) is satisfied.

[0119] In 740, the processing device 110 may determine that the power supply unit is in a safe state with respect to the voltage-related characteristics. If none of the one or more safety warning conditions associated with one or more voltage-related characteristics of the power supply unit in equations (6)-(8) are satisfied, the processing device 110 may determine that the power supply unit is in a safe state with respect to the voltage-related characteristics.

[0120] Figure 8 1 is a flowchart of an exemplary process for determining a state of a power supply unit based at least in part on attribute values ​​of one or more performance attributes of the power supply unit according to some embodiments of the present specification. Figure 8 The process 800 shown may be performed at Figure 1 For example, at least a portion of the process 800 may be stored in a storage device (e.g., a disk 270 of the computing device 200) as an instruction and executed by a processing device 110 (e.g., a processor 220 of the computing device 200, Figure 4 In some embodiments, a portion of process 800 may be implemented on a terminal device. The operations of process 800 presented below are intended to be illustrative. In some embodiments, process 800 may be performed with one or more additional operations not described, and / or without one or more of the operations discussed. Figure 8 The order of the operations of process 800 shown and described below is not intended to be limiting. In some embodiments, the following operations may be performed according to process 800: Figure 5 Operation 540 of process 500 is shown.

[0121] In 810 , the processing device 110 may obtain characteristic values ​​of one or more temperature-related characteristics of a power unit of the electric vehicle.

[0122] In some embodiments, the one or more temperature-related properties of the power supply unit may include the temperature of one or more components of the power supply unit. In some embodiments, the one or more temperature-related properties of the power supply unit may also include the average temperature of one or more components of the power supply unit over a time period. By way of example only, the one or more temperature-related properties of the power supply unit may include the temperature of each of the one or more components of the power supply unit at a certain point in time, the average temperature of the current time period, the average temperature of the previous time period, etc.

[0123] At 820, the processing device 110 may determine whether at least one or more security warning conditions associated with the one or more temperature-related characteristics are satisfied based on the values ​​of the one or more temperature-related characteristics. If at least one of the one or more security warning conditions associated with the one or more temperature-related characteristics is satisfied, the process 800 may continue to 830. If any of the one or more security warning conditions associated with the one or more temperature-related characteristics is not satisfied, the process 800 may continue to 840.

[0124] In some embodiments, one or more safety warning conditions associated with one or more temperature-related characteristics may include a first temperature warning condition, a second temperature warning condition, and a third temperature warning condition. In some embodiments, the first temperature warning condition may include that the difference between the maximum temperature value and the minimum temperature value between the temperature values ​​of the components of the power supply unit is greater than or equal to the respective maximum temperature difference thresholds. For example, the first temperature warning condition may be expressed by formula (9):

[0125] W max-t -W min-t ≥W L (9)

[0126] Among them, W max-t represents the maximum temperature value among the temperature values ​​of all components of the power supply unit at time point t within time period t, W min-t represents the minimum temperature value among the temperature values ​​of all components of the power supply unit at time point t, W L In some embodiments, the time period T and / or the maximum temperature difference threshold W L It can be determined by a user (e.g., a technician) according to the default settings of the security monitoring system 100. In some embodiments, the maximum temperature difference threshold W L It can be experience points.

[0127] In some embodiments, the second temperature warning condition may include that the difference between the characteristic value of the average temperature difference of the current time period and the characteristic value of the average temperature difference of the previous time period is greater than or equal to the product of the respective maximum temperature difference threshold and the health factor of the power supply unit. For example, the second temperature warning condition can be expressed by formula (10):

[0128]

[0129] in, Indicates the current time period T cur Characteristic value of the mean temperature difference, Indicates the previous time period T pre The characteristic value of the average temperature difference in the medium, H represents the health coefficient of the power supply unit. The health coefficient of the power supply unit can reflect the health of the power supply unit. In some embodiments, the health of the power supply unit may be related to the abnormal state of the electric vehicle 140 within a specific time period. In some embodiments, the health of the power supply unit may be related to the abnormal state count of the electric vehicle within a specific time period Q (for example, the current count of abnormal states). For illustrative purposes only, the health coefficient of the power supply unit H can be expressed as (1-min(p / 10,0.5)). min(p / 10,0.5) means that the minimum value is p / 10 or 0.5, and p represents a parameter abnormality. In some embodiments, the numbers 10 and 0.5 can be adjusted according to actual needs. More details about the health coefficient of the power supply unit may be described elsewhere in this specification, for example, Figure 7 In some embodiments, the current time period T cur , the previous time period T pre And / or the specific time period Q may be specified by a user (eg, a technician) according to a default setting of the security monitoring system 100, etc. For example, the specific time period Q may be from the time point when the power supply unit is manufactured to the current time point.

[0130] In some embodiments, the current time period T cur The average temperature difference in may be the average of the temperature differences at different time points. Each temperature difference may be the difference between the maximum temperature and the minimum temperature between the temperature values ​​of the power supply unit component at the corresponding time point. For example, the average temperature difference may be determined according to formula (11):

[0131]

[0132] Where n represents the time period T cur The time point t may correspond to any one of the n sampling points for sampling characteristic values ​​of one or more temperatures within a period of time. In some embodiments, the average temperature difference in the previous time period may be similarly determined.

[0133] In some embodiments, the third temperature warning condition may include that the maximum temperature value of the components of the power supply unit is greater than or equal to the respective maximum temperature thresholds. For example, the third temperature warning condition may be expressed by formula (12):

[0134] W max-t ≥W ML (12)

[0135] Among them, W max-t represents the maximum temperature value among the temperature values ​​of all components of the power supply unit at time point t in time period t, W ML In some embodiments, the time period T and / or the maximum temperature threshold W ML It can be determined by a user (e.g., a technician) according to the default settings of the security monitoring system 100. In some embodiments, the maximum temperature difference threshold W ML It can be experience points.

[0136] At 830, the processing device 110 may determine that the power supply unit is in an unsafe state. The processing device 110 may determine that the power supply unit is in an unsafe state if at least one of the one or more safety warning conditions associated with the one or more temperature-related characteristics of the power supply unit in equations (9)-(12) is satisfied.

[0137] In 840, the processing device 110 may determine that the power supply unit is in a safe state with respect to the temperature. If one or more safety warning conditions associated with one or more temperature-related characteristics of the power supply unit in equations (9)-(12) are not satisfied, the processing device 110 may determine that the power supply unit is in a safe state with respect to the temperature-related characteristics.

[0138] Fig. 9 is a flow chart illustrating an exemplary process for determining a state of a power supply unit based at least in part on attribute values ​​of one or more performance attributes of the power supply unit according to some embodiments of the present specification. Fig. 9 The process 900 shown may be performed at Figure 1 For example, at least a portion of the process 900 may be stored in a storage device (e.g., a disk 270 of the computing device 200) as an instruction and executed by a processing device 110 (e.g., a processor 220 of the computing device 200, Figure 4 In some embodiments, a portion of process 900 may be implemented on a terminal device. The operations of process 900 presented below are intended to be illustrative. In some embodiments, process 900 may be completed with one or more additional operations not described, and / or without one or more of the operations discussed. Fig. 9The order of the operations of process 900 shown and described below is not intended to be limiting. In some embodiments, the following operations may be performed according to process 900: Figure 5 Operation 540 of process 500 is shown.

[0139] In 910 , the processing device 110 may obtain characteristic values ​​of one or more resistance-related characteristics of a power unit of the electric vehicle.

[0140] In some embodiments, the one or more resistance-related characteristics of the power supply unit may include the resistance of the power supply unit. In some embodiments, the one or more resistance-related characteristics of the power supply unit may also include the average resistance of the power supply unit over a time period. By way of example only, the one or more resistance-related characteristics of the power supply unit may include the resistance of the power supply unit at a certain point in time, the average resistance of the current time period, the average resistance of the previous time period, etc.

[0141] At 920, the processing device 110 may determine whether at least one of the one or more security warning conditions associated with the one or more resistance-related characteristics is satisfied based on the characteristic values ​​of the one or more resistance-related characteristics. If at least one of the one or more security warning conditions associated with the one or more resistance-related characteristics is satisfied, the process 900 may continue to 930. If none of the one or more security warning conditions associated with the one or more resistance-related characteristics is satisfied, the process 900 may continue to 940.

[0142] In some embodiments, one or more safety warning conditions associated with one or more resistance-related characteristics may include a first resistance warning condition, a second resistance warning condition, and a third resistance warning condition. In some embodiments, the first resistance warning condition may include a difference between a first resistance value at a first time point and a second resistance value at a second time point being greater than or equal to a minimum resistance decay threshold. The minimum resistance decay threshold may be a lower limit of the resistance decay of the power supply unit from the second time point to the first time point. For example, the first resistance warning condition may be represented by formula (13):

[0143] R t+1 -R t ≥R l (13)

[0144] Among them, R t+1 represents the first resistance value of the power supply unit at the second time point t+1 in the time period t, R t represents the second resistance value of the power supply unit at the second time point t in the time period t, R l represents the minimum resistance decay threshold from the second time point t to the first time point t+1. In some embodiments, the time period T and / or the minimum resistance decay threshold R lIt can be determined by a user (eg, a technician) according to the default settings of the security monitoring system 100. In some embodiments, the minimum resistance attenuation threshold R l It can be experience points.

[0145] In some embodiments, the second resistance warning condition may include that the difference between the characteristic value of the average resistance in the current time period and the characteristic value of the average resistance in the previous time period is greater than or equal to the product of the corresponding minimum resistance attenuation threshold and the health factor of the power supply unit. For example, the second resistance warning condition can be expressed by formula (14):

[0146]

[0147] in, Indicates the current time period T cur The characteristic value of the average resistance, Indicates the previous time period T pre The characteristic value of the average resistance in the power supply unit, H represents the health factor of the power supply unit. The health factor of the power supply unit can reflect the health of the power supply unit. In some embodiments, the health of the power supply unit may be related to the abnormal state of the electric vehicle 140 within a specific time period. In some embodiments, the health of the power supply unit may be related to the abnormal state count of the electric vehicle within a specific time period Q (for example, the current count of abnormal states). For illustrative purposes only, the health factor of the power supply unit H can be expressed as (1-min(p / 10,0.5)). For more details about the health factor of the power supply unit, refer to the description elsewhere in this specification, for example, Figure 7 In some embodiments, the current time period T cur , the previous time period T pre And / or the specific time period Q may be specified by a user (eg, a technician) according to a default setting of the security monitoring system 100, etc. For example, the specific time period Q may be from the time point when the power supply unit is manufactured to the current time point.

[0148] In some embodiments, the current time period T cur The average resistance in the current time period T can be cur The average resistance characteristic value at different time points in the equation is:

[0149]

[0150] Where n represents the time period T cur The time point t may correspond to any one of the n sampling points. In some embodiments, the previous time period T may be similarly determined. pre The average resistance in

[0151] In some embodiments, the third temperature warning condition may include the resistance of the power supply unit being less than or equal to the respective minimum resistance threshold. For example, the third resistance warning condition may be expressed by formula (16):

[0152] R t ≤R L (16)

[0153] Among them, R t represents the resistance value of the power supply unit at time point t in time period t, R L In some embodiments, the time period T and / or the minimum resistance threshold R L It can be determined by a user (eg, a technician) according to the default settings of the security monitoring system 100. In some embodiments, the minimum resistance threshold R L It can be experience points.

[0154] At 930, the processing device 110 may determine that the power supply unit is in an unsafe state. The processing device 110 may determine that the power supply unit is in an unsafe state if at least one of the one or more safety warning conditions associated with the one or more resistance-related characteristics of the power supply unit in equations (13)-(16) is satisfied.

[0155] At 940, the processing device 110 may determine that the power supply unit is in a safe state with respect to the resistance-related characteristic. If none of the one or more safety warning conditions associated with one or more resistance-related characteristics of the power supply unit in equations (13)-(16) are satisfied, the processing device 110 may determine that the power supply unit is in a safe state with respect to the resistance-related characteristic.

[0156] The basic concepts have been described above. Obviously, for those of ordinary skill in the art who have read this application, the above invention disclosure is only for example and does not constitute a limitation of this application. Although not explicitly stated here, those of ordinary skill in the art may make various modifications, improvements and amendments to this application. Such modifications, improvements and amendments are suggested in this application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of this application.

[0157] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0158] In addition, it will be appreciated by those skilled in the art that various aspects of the present application may be illustrated and described by a number of patentable categories or situations, including any new and useful process, machine, product, or combination of substances, or any new and useful improvement thereof. Therefore, various aspects of the present invention may be implemented entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in combination with software and hardware, which are generally referred to herein as "modules," "units," "components," "devices," or "systems." In addition, various aspects of the present invention may take the form of a computer program product containing computer-readable program code in one or more computer-readable media.

[0159] A computer readable signal medium may include a propagated data signal containing computer program code, for example, in baseband or as part of a carrier wave. Such propagated signals may be in a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer readable signal medium may be any computer readable medium other than a computer readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on a computer readable signal medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, RF, etc., or any combination of the above.

[0160] The computer program code for performing the operations of various aspects of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python, etc., conventional process programming languages, such as "C" programming language, VisualBasic, Fortran2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages, such as Python, Ruby and Groovy, or other programming languages. The program code can be run completely on the user's computer, or run on the user's computer as an independent software package, or run partly on the user's computer and partly on the remote computer, or run completely on the remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any type of network (including local area network (LAN) or wide area network (WAN)), or can be connected to an external computer (for example, by using the network of a network service provider) or in a cloud computing environment or as a service, for example, software as a service (SaaS).

[0161] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a pure software solution, for example, installation on an existing server or mobile device.

[0162] Similarly, it should be noted that in order to simplify the description disclosed in this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of the present application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this method of the present application should not be interpreted as reflecting the intention that the claimed object material to be scanned requires more features than those explicitly stated in each claim. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

Claims

1. A system comprising: at least one storage device storing an instruction set; as well as At least one processor configured to communicate with the at least one storage device, wherein when executing the instruction set, the at least one processor is instructed to perform the following operations, including: Obtaining parameter values ​​of one or more motion parameters associated with the target object; identifying an abnormal state of the target object based on the parameter value; In response to identifying the abnormal state of the target object, acquiring attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; and Determining a state of the power supply unit based at least in part on the property value includes: A state of the power supply unit is determined based on the attribute values ​​of the one or more performance attributes and a current count of abnormal states, the current count of abnormal states comprising a number of collisions with the target object.

2. The system according to claim 1, characterized in that The target object is a vehicle.

3. The system according to claim 1, characterized in that The one or more motion parameters include one or more accelerations, and an average acceleration of all accelerations in one or more axes, wherein each acceleration corresponds to each of the one or more axes of the target object.

4. The system according to claim 3, characterized in that The one or more acceleration parameter values ​​are acquired by at least one acceleration sensor coupled to the target object.

5. The system according to claim 1, characterized in that Identifying the abnormal state of the target object based on the parameter value includes: determining whether one or more collision conditions associated with the target object are satisfied based on the parameter values; In response to determining that at least one of the one or more collision conditions associated with the target object is satisfied, it is determined that the target object is in an abnormal state.

6. The system according to claim 5, characterized in that The one or more collision conditions include: The parameter value corresponding to any axial acceleration is greater than the corresponding axial acceleration threshold; and A parameter value of an average acceleration of all accelerations in the one or more axes is greater than an average acceleration threshold.

7. The system according to any one of claims 1 to 6, characterized in that: The power supply unit is a battery.

8. The system of claim 1, to generate the current count of the abnormal state, the operations further comprising: Obtaining a priori count of abnormal states of the target object; as well as In response to identifying the abnormal state of the target object, a current count of the abnormal state is generated by increasing a priori count by 1.

9. The system according to claim 1, characterized in that To generate the current count of the abnormal status, the operations further include: Obtaining a priori count of abnormal states of the target object; and In response to identifying the abnormal state of the target object, the current count of the abnormal state is generated by increasing a priori count by a specific amount, the specific amount being related to a severity of the abnormal state.

10. The system according to claim 1, characterized in that The one or more performance attributes include: one or more voltages, and an average voltage of all voltages of one or more components of the power supply unit, wherein each voltage corresponds to each component of the one or more components; one or more temperatures, and an average temperature of all temperatures of one or more components of the power supply unit, wherein each temperature corresponds to each component of the one or more components; and The resistance of a power supply unit, and the average resistance of all resistances of the power supply unit over a period of time.

11. The system according to claim 1, characterized in that Determining a state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes comprises: determining, based on attribute values ​​of the one or more performance attributes, whether one or more safety warning conditions associated with the one or more performance attributes of the power supply unit are satisfied; In response to determining that at least one of the one or more safety warning conditions associated with the one or more performance attributes of the power supply unit is satisfied, an unsafe state of the power supply unit is determined.

12. The system of claim 11, the operations further comprising: In response to determining that any of the one or more security warning conditions associated with the one or more performance attributes of the power supply unit are not satisfied, a security state of the power supply unit is determined.

13. The system according to claim 11 or 12, characterized in that The one or more safety warning conditions associated with the one or more performance attributes of the power supply unit include at least one of one or more voltage warning conditions, one or more temperature warning conditions, or one or more resistance warning conditions.

14. The system according to claim 11, characterized in that At least one of the one or more safety warning conditions is related to a current count of abnormal states of the target object.

15. A method implemented on a computing device having a processor and a computer readable storage device, the method comprising: Obtaining parameter values ​​of one or more motion parameters associated with the target object; identifying an abnormal state of the target object based on the parameter value; In response to identifying the abnormal state of the target object, acquiring attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; as well as Determining a state of the power supply unit based at least in part on the property value includes: A state of the power supply unit is determined based on the attribute values ​​of the one or more performance attributes and a current count of abnormal states, the current count of abnormal states comprising a number of collisions with the target object.

16. The method according to claim 15, characterized in that The target object is a vehicle.

17. The method according to claim 15, characterized in that The one or more motion parameters include one or more accelerations, and an average acceleration of all accelerations in one or more axes, wherein each acceleration corresponds to each of the one or more axes of the target object.

18. The method according to claim 17, characterized in that The one or more acceleration parameter values ​​are acquired by at least one acceleration sensor coupled to the target object.

19. The method according to claim 15, characterized in that Identifying the abnormal state of the target object based on the parameter value includes: determining whether one or more collision conditions associated with the target object are satisfied based on the parameter values; In response to determining that at least one of the one or more collision conditions associated with the target object is satisfied, it is determined that the target object is in an abnormal state.

20. The method according to claim 19, characterized in that The one or more collision conditions include: Any parameter value corresponding to the acceleration in the axial direction is greater than the corresponding axial acceleration threshold value; and A parameter value of an average acceleration of all accelerations in the one or more axes is greater than an average acceleration threshold.

21. The method according to any one of claims 15 to 20, characterized in that: The power supply unit is a battery.

22. The method according to claim 15, in order to generate the current count of the abnormal state, the method further comprises: Obtaining a priori count of abnormal states of the target object; as well as In response to identifying the abnormal state of the target object, a current count of the abnormal state is generated by increasing a priori count by 1.

23. The method according to claim 15, characterized in that To generate the current count of the abnormal status, the method further comprises: Obtaining a priori count of abnormal states of the target object; and In response to identifying the abnormal state of the target object, the current count of the abnormal state is generated by increasing a priori count by a specific amount, the specific amount being related to a severity of the abnormal state.

24. The method according to claim 15, characterized in that The one or more performance attributes include: one or more voltages, and an average voltage of all voltages of one or more components of the power supply unit, wherein each voltage corresponds to each component of the one or more components; one or more temperatures, and an average temperature of all temperatures of one or more components of the power supply unit, wherein each temperature corresponds to each component of the one or more components; and The resistance of a power supply unit, and the average resistance of all resistances of the power supply unit over a period of time.

25. The method according to claim 15, characterized in that Determining a state of the power supply unit based at least in part on the attribute values ​​of the one or more performance attributes comprises: determining, based on attribute values ​​of the one or more performance attributes, whether one or more safety warning conditions associated with the one or more performance attributes of the power supply unit are satisfied; In response to determining that at least one of the one or more safety warning conditions associated with the one or more performance attributes of the power supply unit is satisfied, an unsafe state of the power supply unit is determined.

26. The method according to claim 25, further comprising: In response to determining that any of the one or more security warning conditions associated with the one or more performance attributes of the power supply unit are not satisfied, a security state of the power supply unit is determined.

27. The method according to claim 25 or 26, characterized in that The one or more safety warning conditions associated with the one or more performance attributes of the power supply unit include at least one of one or more voltage warning conditions, one or more temperature warning conditions, or one or more resistance warning conditions.

28. The method according to claim 25, characterized in that At least one of the one or more safety warning conditions is related to a current count of abnormal states of the target object.

29. A non-transitory computer-readable storage medium comprising instructions which, when accessed by at least one processor of a system, cause the system to perform a method comprising: Obtaining parameter values ​​of one or more motion parameters associated with the target object; identifying an abnormal state of the target object based on the parameter value; In response to identifying the abnormal state of the target object, acquiring attribute values ​​of one or more performance attributes of a power supply unit of the target object, wherein the power supply unit provides power to the target object; as well as Determining a state of the power supply unit based at least in part on the property value includes: A state of the power supply unit is determined based on the attribute values ​​of the one or more performance attributes and a current count of abnormal states, the current count of abnormal states comprising a number of collisions with the target object.

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