WO2022000128A1

WO2022000128A1 - Systems and methods for safety monitoring of electric vehicle

Info

Publication number: WO2022000128A1
Application number: PCT/CN2020/098526
Authority: WO
Inventors: Feng Dai
Original assignee: Beijing Didi Infinity Technology And Development Co., Ltd.
Priority date: 2020-06-28
Filing date: 2020-06-28
Publication date: 2022-01-06
Also published as: CN115151440A

Abstract

A system and method for safety monitoring for an electric vehicle are disclosed. 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 status of the target object based on the parameter values (520). The method may further include obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object (530), wherein the power supply unit provides power for the target object. The method may still further include determining a status of the power supply unit based at least in part on the property values (540).

Description

SYSTEMS AND METHODS FOR SAFETY MONITORING OF ELECTRIC VEHICLE

TECHNICAL FIELD

The present disclosure generally relates to battery management, and more particularly, relates to systems and methods for battery safety evaluation for suspected accidents.

BACKGROUND

Electric vehicles powered by batteries are generally considered environmentally friendly. Their numbers have dramatically increased as a part of the modern transportation system. When an electric vehicle is involved in an accident (e.g., a car crash) , it is possible that one or more batteries in the electric vehicle will be damaged, thus affecting an overall performance of the electric vehicle and even bringing about safety hazard to the driver and the passengers. However, conventional ways to evaluate the effects of the accident on the batteries are often unreliable and inefficient. Thus, it is desirable to develop a system and method for monitoring and evaluating the state of health (SoH) of the batteries in the electric vehicle more accurately and efficiently.

SUMMARY

According to one aspect of the present disclosure, a system may be provided. The system may include at least one storage device including a set of instructions, and at least one processor configured to communicate with the at least one storage device. When executing the set of instructions, the at least one processor may be configured to direct the system 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 status of the target object based on the parameter values; obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and determining a status of the power supply unit based at least in part on the property values.

According to another aspect of the present disclosure, 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 status of the target object based on the parameter values; obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and determining a status of the power supply unit based at least in part on the property values.

According to a further aspect of the present disclosure, a non-transitory computer-readable storage medium including instructions may be provided. When the non-transitory computer-readable storage medium is accessed by at least one processor of a system, the system may be 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 status of the target object based on the parameter values; obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and determining a status of the power supply unit based at least in part on the property values.

In some embodiments, the target object is a vehicle.

In some embodiments, the one or more motion parameters include one or more accelerations each corresponding to each of one or more axial directions of the target object, and an average acceleration of all the accelerations of the one or more axial directions.

In some embodiments, the parameter values of the one or more accelerations are acquired by at least one acceleration sensor coupled to the target object.

In some embodiments, identifying the abnormal status of the target object based on the at least one motion parameter includes determining whether one or more impact conditions associated with the target object are satisfied based on the parameter values; in response to the determination that at least one of the one or more impact conditions associated with the target object is satisfied, determining that the target object is in an abnormal status.

In some embodiments, the one or more impact conditions include any parameter value of the accelerations corresponding to an axial direction is larger than a respective axial direction acceleration threshold; and the parameter value of the average acceleration of all the accelerations of the one or more axial directions is larger than an average acceleration threshold.

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

In some embodiments, the operations further includes obtaining a prior count of abnormal status of the target object; and generating a current count of abnormal status by increasing the prior count by one in response to identifying the abnormal status of the target object.

In some embodiments, determining the status of the power supply unit based at least in part on the property values of one or more performance properties includes determining the status of the power supply unit based on the property values of the one or more performance properties and the current count of the abnormal status.

In some embodiments, the one or more performance properties include one or more voltages each corresponding to each of one or more components of the power supply unit, and an average voltage of all the voltages of the one or more components; one or more temperatures each corresponding to each of one or more components of the power supply unit; and an average temperature of all the temperatures of the one or more components; and an electric resistance of the power supply unit; and an average electric resistance of all the electric resistances of the power supply unit in a time period.

In some embodiments, determining the status of the power supply unit based at least in part on the property values of one or more performance properties includes determining whether one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied based on the property values of the one or more performance properties; in response to the determination that at least one of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit is satisfied, determining an unsafe status of the power supply unit.

In some embodiments, the operations further includes in response to the determination that none of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied, determining a safe status of the power supply unit.

In some embodiments, the one or more safety warning conditions associated with the one or more performance properties 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 electric resistance warning conditions.

In some embodiments, at least one of the one or more safety warning conditions relates to a current count of abnormal status of the target object.

Additional features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or may be learned by production or operation of the examples. The features of the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. The drawings are not to scale. These embodiments are non-limiting exemplary embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary safety monitoring system according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating hardware and/or software components of an exemplary mobile device 300 according to some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating an exemplary process for monitoring a status of a power supply unit according to some embodiments of the present disclosure;

FIG. 6 is a flowchart illustrating an exemplary process for identifying an abnormal status of the target object according to some embodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process for determining a status of a power supply unit of an electric vehicle based at least in part on property values of one or more performance properties of the power supply unit according to some embodiments of the present disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for determining a status of a power supply unit of an electric vehicle based at least in part on property values one or more performance properties of the power supply unit according to some embodiments of the present disclosure; and

FIG. 9 is a flowchart illustrating an exemplary process for determining a status of a power supply unit of an electric vehicle based at least in part on property values one or more performance properties of the power supply unit according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled in the art to make and use the present disclosure, and is provided in the context of a particular application and its requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present disclosure is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the claims.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms “a, ” “an, ” and “the” may be intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprise, ” “comprises, ” and/or “comprising, ” “include, ” “includes, ” and/or “including, ” when used in this disclosure, specify the presence of stated features, integers, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, operations, elements, components, and/or groups thereof.

It will be understood that the term “system, ” “engine, ” “unit, ” “module, ” and/or “block” used herein are one method to distinguish different components, elements, parts, sections or assembly of different levels in ascending order. However, the terms may be displaced by another expression if they achieve the same purpose.

Generally, the word “module, ” “unit, ” or “block, ” as used herein, refers to logic embodied in hardware or firmware, or to a collection of software instructions. A module, a unit, or a block 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, a software module/unit/block may be compiled and linked into an executable program. It will be appreciated that software modules can be callable from other modules/units/blocks or from themselves, and/or may be invoked in response to detected events or interrupts. Software modules/units/blocks configured for execution on computing devices (e.g., processor 220 as illustrated in FIG. 2) may be provided on a computer-readable medium, such as a compact disc, a digital video disc, a flash drive, a magnetic disc, or any other tangible medium, or as a digital download (and can be originally stored in a compressed or installable format that needs installation, decompression, or decryption prior to execution) . Such software code may be stored, partially or fully, on a storage device of the executing computing device, for execution by the computing device. Software instructions may be embedded in firmware, such as an EPROM. It will be further appreciated that hardware modules/units/blocks may be included in connected logic components, such as gates and flip-flops, and/or can be included of programmable units, such as programmable gate arrays or processors. The modules/units/blocks or computing device functionality described herein may be implemented as software modules/units/blocks, but may be represented in hardware or firmware. In general, the modules/units/blocks described herein refer to logical modules/units/blocks that may be combined with other modules/units/blocks or divided into sub-modules/sub-units/sub-blocks despite their physical organization or storage. The description may be applicable to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block is referred to as being “on, ” “connected to, ” or “coupled to, ” another unit, engine, module, or block, it may be directly on, connected or coupled to, or communicate with the other unit, engine, module, or block, or an intervening unit, engine, module, or block may be present, unless the context clearly indicates otherwise. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.

The flowcharts used in the present disclosure illustrate operations that systems implement according to some embodiments of the present disclosure. It is to be expressly understood the operations of the flowcharts may be implemented not in order. Conversely, the operations may be implemented in an inverted order, or simultaneously. Moreover, one or more other operations may be added to the flowcharts. One or more operations may be removed from the flowcharts.

These and other features, and characteristics of the present disclosure, as well as the methods of operations and functions of the related elements of structure and the combination 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 part of this disclosure. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended to limit the scope of the present disclosure. It is understood that the drawings are not to scale.

Moreover, safety monitoring system and method of the present disclosure may be applied to any other kind of transportation system. For example, the safety monitoring system in the present disclosure may be applied to transportation systems in different environments including land, ocean, aerospace, or the like, or any combination thereof. Vehicles of the transportation systems may include a car, a bus, a train, a subway, a vessel, an aircraft, a spaceship, a hot-air balloon, or the like, or any combination thereof. Merely for illustration purposes, the safety monitoring system and method disclosed in the present disclosure are described primarily regarding an electric vehicle. It should be understood that this is only one exemplary embodiment, and not intended to be limiting.

An aspect of the present disclosure 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) may be obtained. The motion parameters may be an acceleration, a velocity, etc., of the target object. An abnormal status, such as a suspected accident, of the target object may be identified based on the parameter values. In response to identifying the abnormal status of the target object, one or more performance properties of a power supply unit that provides power for the target object may be obtained. Exemplary performance properties may include voltage properties, temperature properties, electric resistance properties, or the like, or any combination thereof. Then a status of the power supply unit may be determined based at least in part on the property values of the one or more performance properties. In this case, performance properties of the power supply unit may be monitored effectively upon any suspected accidents of the target object. In addition, a count of suspected accidents occurred in a period of time may be recorded, and the health monitoring of the power supply unit may be conducted in combination with the count of the suspected accidents.

FIG. 1 is a schematic diagram illustrating an exemplary safety monitoring system according to some embodiments of the present disclosure. The safety monitoring system 100 may monitor and evaluate the health of a power supply unit installed in a target object. In some embodiments, the target object may be a moving object, and the power supply unit may provide power for the target object. In some embodiments, the power supply unit may include batteries, 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, or the like. In some embodiments, the target object equipped with the power supply unit may be an electric vehicle. The following descriptions regarding the battery monitoring system are provided, unless otherwise stated expressly, that the target object is an electric vehicle powered by an electric battery. It should be understood, however, that this is only for illustration purposes and not intended to be limiting. Exemplary electric vehicles may include an electric car, an electric bus, an electric truck, an electric cycle, an electric motorbike, an electric train, an electric subway, an electric boat, an electric vessel, an electric aircraft (e.g., an unmanned aerial vehicle (UAV) ) , etc.

The safety 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 status of the electric vehicle 140 based on the parameter values. As another example, the processing device 110 may obtain one or more performance properties of the power supply unit of the electric vehicle 140, and determine a status of the power supply unit based at least in part on the property values of the one or more performance properties. In some embodiments, the processing device 110 may be a single server or a server group. The server group may be centralized, or distributed (e.g., 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. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the processing device 110 may be implemented on a computing device having one or more components illustrated in FIG. 2 in the present disclosure.

In some embodiments, the processing device 112 may include one or more processing engines (e.g., single-core processing engine (s) or multi-core processor (s) ) . Merely by way of example, 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 physics 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, or the like, or any combination thereof.

The network 120 may include any suitable network that can facilitate exchange of information and/or data. In some embodiments, one or more components in the safety monitoring system 100 (e.g., the processing device 110, the user terminal 130, the electric vehicle 140, and/or the storage device 150) may transmit information and/or data to other component (s) in the safety monitoring system 100 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or combination thereof. Merely by way of example, the network 120 may include a cable network, a wireline network, an optical fiber network, a tele communications network, an intranet, an 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 telephone switched 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, a ultra wide band (UWB) network, an infrared ray, or the like, 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 safety monitoring system 100 may be connected to the network 120 to exchange data and/or information.

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

The electric vehicle 140 may be a vehicle used in transportation systems. It is contemplated that the electric vehicle 140 may be a pure electric vehicle that has an electric motor, or a hybrid vehicle that includes 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 electrical 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. The one or more batteries may be connected in series and/or in parallel to provide a relatively large electric power output.

The electric vehicle 140 may have a body and at least one wheel. The body may be of any type, such as a roadster, a sports utility vehicle (SUV) , a coupe, a minivan, a pick-up truck, a station wagon, a cabin, a train carriage, an airframe, or the like. 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., an air injector, at least one propeller, etc. ) that enable the movement of the electric vehicle 140. The electric vehicle 140 may be configured to be all-wheel drive (AWD) , front wheel drive (FWR) , rear wheel drive (RWD) , etc. The electric vehicle 140 may be configured to be operated, e.g., by a driver in the vehicle, by an operator remotely, and/or autonomously.

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 velocity sensor, an acceleration sensor, a spin sensor, etc. ) , at least one electrical sensor (e.g., a voltage sensor, a current sensor, an electric resistance sensor, etc. ) , at least one temperature sensor, at least one pressure sensor, or the like, 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 joints, etc. In some embodiments, the positions and/or types of the plurality of sensors, the manners in which the plurality of sensors are bonded to the electric vehicle 140 or the power supply unit, etc., are not limited in the present disclosure, and may be modified so as to achieve a desirable data/information detection performance.

The storage device 150 may store data and/or instructions. In some embodiments, the storage device 150 may store data/information obtained from 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 that the processing device 110 may execute or use to perform exemplary methods described in the present disclosure. In some embodiments, the storage device 150 may include a mass storage, a removable storage, a volatile read-and-write memory, a read-only memory (ROM) , or the like, or any combination thereof. Exemplary mass storage may include a magnetic 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 zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memory may include a random access memory (RAM) . Exemplary RAM may include a dynamic RAM (DRAM) , a double date rate synchronous dynamic RAM (DDR SDRAM) , a static RAM (SRAM) , a thyristor RAM (T-RAM) , and a zero-capacitor RAM (Z-RAM) , etc. Exemplary ROM may include a mask ROM (MROM) , a programmable ROM (PROM) , an erasable programmable ROM (PEROM) , an electrically erasable programmable ROM (EEPROM) , a compact disk ROM (CD-ROM) , and a digital versatile disk ROM, etc. In some embodiments, the storage device 150 may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, the storage device 150 may be connected to the network 120 to communicate with one or more components in the safety monitoring system 100 (e.g., the processing device 110, the user terminal 130, the electric vehicle 140, etc. ) . One or more components in the safety monitoring system 100 may access the 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 safety 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.

It should be noted that the above description of the safety monitoring system 100 is merely provided for the purposes of illustration, not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, components contained in the safety monitoring system 100 may be combined or adjusted in various ways, or connected with other components as sub-systems, and various variations and modifications may be conducted under the teaching of the present disclosure. However, those variations and modifications may not depart the spirit and scope of this disclosure. For example, the terminal (s) 130 may be part of the processing device 110. As another example, the terminal (s) 130 may be omitted. All such modifications are within the protection scope of the present disclosure.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary computing device according to some embodiments of the present disclosure. In some embodiments, the processing device 110 and/or the user terminal 130 may be implemented on the computing device 200 shown in FIG. 2. For example, the processing device 112 may be implemented on the computing device 200 and configured to perform functions of the processing device 112 disclosed in this disclosure.

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

The computing device 200, for example, may include COM ports 250 connected to and from a network connected thereto to facilitate data communications. The computing device 200 may also include a processor (e.g., the 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 interface circuits and processing circuits therein. The interface circuits may be configured to receive electronic signals from a bus 210, wherein the electronic signals encode structured data and/or instructions for the processing circuits to process. The processing circuits may conduct logic calculations, and then determine a conclusion, a result, and/or an instruction encoded as electronic signals. Then the interface circuits may send out the electronic signals from the processing circuits via the bus 210.

The exemplary computing device may further include program storage and data storage of different forms including, for example, a disk 270, and a read-only memory (ROM) 230, or a random-access memory (RAM) 240, for various data files to be processed and/or transmitted by the computing device. The exemplary computing device may also include program instructions stored in the ROM 230, RAM 240, and/or another type of non-transitory storage medium to be executed by the processor 220. The methods and/or processes of the present disclosure may be implemented as the program instructions. The computing device 200 may also include an I/O component 260, supporting input/output between the computer and other components. The computing device 200 may also receive programming and data via network communications.

Merely for illustration, only one processor is illustrated in FIG. 2. Multiple processors 220 are also contemplated; thus, operations and/or method steps performed by one processor 220 as described in the present disclosure may also be jointly or separately performed by the multiple processors. For example, if in the present disclosure the processor 220 of the computing device 200 executes both step A and step B, it should be understood that step A and step B may also be performed by two different processors 220 jointly or separately in the computing device 200 (e.g., a first processor executes step A and a second processor executes step B or the first and second processors jointly execute steps A and B) .

FIG. 3 is a schematic diagram illustrating hardware and/or software components of an exemplary mobile device 300 according to some embodiments of the present disclosure. As illustrated in FIG. 3, 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 I/O 350, a memory 370, and storage 390. In some embodiments, any other suitable component, 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 360 (e.g., iOS, Android, Windows Phone, etc. ) and one or more applications 380 may be loaded into the memory 370 from the storage 390 in order to be executed by the CPU 340. The applications 380 may include a browser or any other suitable mobile apps for receiving and rendering information relating to data processing or other information from the processing device 110. User interactions with the information stream may be achieved via the I/O 350 and provided to the processing device 110 and/or other components of the safety monitoring system 100 via the network 120.

To implement various modules, units, and their functionalities described in the present disclosure, computer hardware platforms may be used as the hardware platform (s) for one or more of the elements described herein. The hardware elements, operating systems and programming languages of such computers are conventional in nature, and it is presumed that those skilled in the art are adequately familiar therewith to adapt those technologies to generate, e.g., a safety report as described below. A computer with user interface elements may be used to implement a personal computer (PC) or another type of work station or terminal device, although a computer may also act as a server if appropriately programmed. It is believed that those skilled in the art are familiar with the structure, programming and general operation of such computer equipment and as a result, the drawings should be self-explanatory.

FIG. 4 is a block diagram illustrating an exemplary processing device according to some embodiments of the present disclosure. The processing device 110 may include an obtaining module 410, an abnormal identification module 420, and a safety determination module 430. One or more of the modules of the processing device 110 may be interconnected. The connection (s) may be wireless or wired. In some embodiments, at least a portion of the processing device 110 may be implemented on the computing device 200 as illustrated in FIG. 2 or the mobile device 300 as illustrated in FIG. 3.

The obtaining module 410 may obtain data and/or information. The obtaining module 410 may obtain data and/or information from the processing device 110, the terminal (s) 130, the electric vehicle 140, the storage device 150, or any devices or components capable of storing data via the network 120. For example, the obtaining module 410 may obtain data and/or information from a cloud data center (not shown) via the network 120. The obtained data and/or information may include parameter values of one or more motion parameters associated with an electric vehicle 140. In some embodiments, the one or more motion parameters may include one or more acceleration related parameters, one or more velocity related parameters, one or more spin angular velocity related parameters, etc., of the electric vehicle 140. The obtaining module 410 may also obtain property values of one or more performance properties of a power supply unit of the electric vehicle 140. The one or more performance properties may relate to, for example, the short circuit, open circuit, temperature rise, electric resistance increase, etc., of the power supply unit. The processing device 110 may process or analyze the property values of the one or more performance properties so as to evaluate the health of the power supply unit. In some embodiments, the one or more performance properties may include one or more voltage related properties, one or more current related properties, one or more electric resistance related properties, one or more temperature related properties, etc., of the power supply unit. The obtaining module 410 may also obtain processed results, user instructions, algorithms, models, parameters, program codes, other information of the vehicle 140 or the driver of the electric vehicle 140, or the like, or a combination thereof.

The abnormal identification module 420 may identify an abnormal status of the electric vehicle. In some embodiments, the abnormal status of the electric vehicle 140 may be indicative of a suspected accident of the electric vehicle 140. The accident of the electric vehicle 140 may be, for example, a car crash of the electric vehicle 140 at a specific speed (e.g., 80 kilometers per hour, 100 kilometers per hour, 120 kilometers per hour, 150 kilometers per hour, etc. ) . In some embodiments, the abnormal identification module 420 may process the parameter values of the one or more motion parameters of the electric vehicle 140, and identify the abnormal status of the electric vehicle 140 based on the processed parameter values of the one or more motion parameters of the electric vehicle 140.

In some embodiments, the abnormal identification module 420 may determine whether one or more impact conditions associated with the electric vehicle 140 are satisfied based on the parameter values. If at least one of the one or more impact conditions associated with the electric vehicle 140 is satisfied, the abnormal identification module 420 may determine that the electric vehicle 140 is in an abnormal status. If none of the one or more impact conditions associated with the electric vehicle 140 are satisfied, the abnormal identification module 420 may determine that the electric vehicle 140 is in a normal status.

The safety determination module 430 may determine a status of a power supply unit of the electric vehicle 140. In some embodiments, the safety determination module 430 may determine the status of the power supply unit based at least in part on the property values of the one or more performance properties.

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

If at least one of the one or more safety warning conditions for performance properties of at least one type is satisfied, the safety determination module 430 may determine that the power supply unit is in an unsafe status. The unsafe status may indicate that the power supply unit is significantly effected by the suspected accident (e.g., the power supply unit is seriously damaged) to entail risks such as a short circuit, an abrupt temperature rise, a self-ignition, etc., of the power supply unit may exist if the power supply unit continues to provide power for the electric vehicle 140. In this case, the power supply unit may need to be examined and/or repaired. For example, the power supply unit may be discharged using an ultra-fast discharge device (UFDD) . Each component of the power supply unit may be examined so as to identify damaged components. In some embodiments, the damaged components may be replaced or repaired.

If none the one or more safety warning conditions associated with performance properties of all of the types is satisfied, the safety determination module 430 may determine that the power supply unit is in a safe status. The safe status may indicate that the power supply unit is not effected by the suspected accident (e.g., the power supply unit is not damaged or slightly damaged) , and capable of providing power for the electric vehicle 140 normally.

It should be noted that the above description of the processing device 112 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. For example, the processing device 110 may further include a storage module facilitating data storage. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 5 is a flowchart illustrating an exemplary process for monitoring a status of a power supply unit according to some embodiments of the present disclosure. In some embodiments, the process 500 shown in FIG. 5 may be implemented in the battery management system 100 illustrated in FIG. 1. For example, at least a part of the process 500 may be stored in a storage device (e.g., the DISK 270 of the computing device 200) as a form of instructions, and invoked and/or executed by the processing device 110 (e.g., the processor 220 of the computing device 200, one or more modules illustrated in FIG. 4) . In some embodiments, a part of the process 500 may be implemented on a terminal device. The operations of the illustrated process 500 presented below are intended to be illustrative. In some embodiments, the process 500 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process 500 as illustrated in FIG. 5 and described below is not intended to be limiting.

In 510, the processing device 110 (e.g., the obtaining module 410) may obtain parameter values of one or more motion parameters associated with an electric vehicle.

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 the parameter values of the 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 the parameter values of the 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 safety monitoring system 100.

The one or more motion parameters associated with the electric vehicle 140 may be detected using the at least one motion sensor. In some embodiments, the one or more motion parameters may include one or more acceleration related parameters, one or more velocity related parameters, one or more spin angular velocity related parameters, etc., of the electric vehicle 140. As used herein, an acceleration related parameter refers to a parameter relate to an acceleration of the electric vehicle 140, such as an acceleration in a certain direction, an average acceleration (e.g., an arithmetic average acceleration, a weighted average, a harmonic average) in one or more directions, etc. Similarly, a velocity related parameter refers to a parameter relate to a velocity of the electric vehicle 140, such as a velocity (e.g., in a certain direction) , an average velocity in one or more directions, etc. A spin angular velocity related parameter refers to a parameter relate to a spin angular velocity of the electric vehicle 140, such as an angular velocity, an average angular velocity, etc.

In some embodiments, the one or more acceleration related parameters, the one or more velocity related parameters, and the 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 a piezoelectric accelerometer, a piezoresistive accelerometer, a variable capacitance accelerometer, a variable reluctance accelerometer, or the like. Exemplary velocity sensors may include a laser sensor, a radar, or the like. Exemplary spin sensor may include a gyroscope sensor, etc.

In some embodiments, a coordinate system may be established in combination with the electric vehicle 140 in a three-dimensional space where the electric vehicle 140 is located. 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. Merely for illustration purposes, an X axis of the Cartesian coordinate system (also referred to as X axial direction of the electric vehicle 140) may be consistent with a length direction of the electric vehicle 140. A Y axis of the Cartesian coordinate system (also referred to as Y axial direction of the electric vehicle 140) may be consistent with a width direction of the electric vehicle 140. A Z axis of the Cartesian coordinate system (also referred to as Z axial direction of the electric vehicle 140) may be consistent with a height direction of the electric vehicle 140.

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

In some embodiments, each of another part of the one or more motion parameters may correspond to at least two of the axial directions of the electric vehicle 140. In some embodiments, each of another part of the one or more motion parameters may be an average of motion parameters corresponding to at least two of the axial directions of the electric vehicle 140. For example, an average acceleration of the electric vehicle 140 may be the average of accelerations corresponding to all the axial directions of the electric vehicle 140. The average acceleration may be, for example, an arithmetic average of accelerations of the electric vehicle 140 corresponding to the X axial direction, the Y axial direction, and the Z axial direction, respectively. It should be noted that the average of motion parameters is merely provided for illustration purposes, and not intended to be limiting. Instead of the average of the motion parameters, a median, a maximum, a minimum, etc., of the motion parameters corresponding to at least two of the axial directions of the coordinate system may be provided.

In 520, the processing device 110 (e.g., the abnormal identification module 420) may identify an abnormal status of the electric vehicle based on the parameter values.

In some embodiments, the abnormal status of the electric vehicle 140 may be indicative of a suspected accident of the electric vehicle 140. The accident of the electric vehicle 140 may be, for example, a car crash of the electric vehicle 140 at a specific speed (e.g., 80 kilometers per hour, 100 kilometers per hour, 120 kilometers per hour, 150 kilometers per hour, etc. ) . In some embodiments, the processing device 110 may process the parameter values of the one or more motion parameters of the electric vehicle 140, and identify the abnormal status of the electric vehicle 140 based on the processed parameter values of the one or more motion parameters of the electric vehicle 140.

In some embodiments, the processing device 110 may determine whether one or more impact conditions associated with the electric vehicle 140 are satisfied based on the parameter values. If at least one of the one or more impact conditions associated with the electric vehicle 140 is satisfied, the processing device 110 may determine that the electric vehicle 140 is in an abnormal status. If none of the one or more impact conditions associated with the electric vehicle 140 are satisfied, the processing device 110 may determine that the electric vehicle 140 is in a normal status. The one or more impact conditions may characterize or quantify a degree of seriousness of the suspected accident of the electric vehicle 140. In some embodiments, the one or more impact conditions may relate to the parameter values of the one or more motion parameters and at least one threshold. More details regarding the identification of the abnormal status of the electric vehicles may be found elsewhere in the present disclosure, for example, FIG. 6 and the descriptions thereof.

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

In 530, the processing device 110 (e.g., the obtaining module 410) obtain property values of one or more performance properties of the power supply unit in response to identifying the abnormal status of the electric vehicle.

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 a chassis of the electric vehicle 140 in a form of, e.g., a battery assembly block or plate. Therefore, a suspected accident of the electric vehicle 140 may cause a damage to the power supply unit. The damage to the power supply unit may bring about suspected safety hazard for the electric vehicle 140 and the driver. Merely for illustration, if a battery cell of a battery assembly mounted on the electric vehicle 140 is damaged (e.g., a deformation, a crack, or a battery leakage occurs on the battery cell) , the power supply unit may have a risk of a short circuit, an open circuit, a temperature rise, an electric resistance variance, etc.

In some embodiments, the processing device 110 may obtain property values of one or more performance properties of the power supply unit if the electric vehicle is in an abnormal status. The one or more performance properties may relate to, for example, the short circuit, open circuit, temperature rise, electric resistance increase, etc., of the power supply unit. The processing device 110 may process or analyze the property values of the one or more performance properties so as to evaluate the health of the power supply unit.

In some embodiments, the one or more performance properties may include one or more voltage related properties, one or more current related properties, one or more electric resistance related properties, one or more temperature related properties, etc., of the power supply unit. As used herein, a voltage related property refers to a parameter relating to a voltage of one or more components (e.g., battery cells) of the power supply unit of the electric vehicle 140, such as a voltage of a component of the power supply unit, an average voltage (e.g., an arithmetic average voltage) of one or more components of the power supply unit, etc. Similarly, a temperature related property refers to a parameter relate to a temperature of one or more components of the power supply unit of the electric vehicle 140, such as a temperature of a component of the power supply unit, an average temperature (e.g., an arithmetic average temperature) of one or more components of the power supply unit, etc. An electric resistance related property refers to a parameter relate to an electric resistance of the power supply unit of the electric vehicle 140, such as an electric resistance of the power supply unit, an average electric resistance (e.g., an arithmetic average electric resistance) of the power supply unit, etc. As used herein, the electric resistance of the power supply unit refers to an electric resistance between the power supply unit and the body of the electric vehicle 140 or the ground.

The one or more performance properties of the power supply unit may 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 electric resistance sensor, etc. ) , at least one temperature sensor, etc. Exemplary voltage sensors may include a suspected transformer, a Hall voltage sensor, etc. Exemplary current sensors may include a Hall current sensor, a Rogowski current sensor, a fiber-optic current sensor, etc. Exemplary electric resistance sensors may include a photoresistor sensor, a thermistor sensor, etc. Exemplary temperature sensors may include a mercurial thermometer, an infrared thermometer, etc. In some embodiments, each of the exemplified sensors may detect a property value of a performance property of one or more components of the power supply unit or the entire power supply unit. For example, a voltage value of each component of the power supply unit may be detected by a standalone voltage sensor. As another example, components of the power supply unit may be divided into two or more groups, and a temperature of each group may be detected by a temperature sensor. As a further example, an electric resistance of the power supply unit may be detected by one electric resistance sensor.

In 540, the processing device 110 (e.g., the safety determination module 430) may determine a status of the power supply unit based at least in part on the property values of the one or more performance properties.

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

If at least one of the one or more safety warning conditions for performance properties of at least one type is satisfied, the processing device 110 may determine that the power supply unit is in an unsafe status. The unsafe status may indicate that the power supply unit is significantly effected by the suspected accident (e.g., the power supply unit is seriously damaged) to entail risks such as a short circuit, an abrupt temperature rise, a self-ignition, etc., of the power supply unit may exist if the power supply unit continues to provide power for the electric vehicle 140. In this case, the power supply unit may need to be examined and/or repaired. For example, the power supply unit may be discharged using an ultra-fast discharge device (UFDD) . Each component of the power supply unit may be examined so as to identify damaged components. In some embodiments, the damaged components may be replaced or repaired.

If none the one or more safety warning conditions associated with performance properties of all of the types is satisfied, the processing device 110 may determine that the power supply unit is in a safe status. The safe status may indicate that the power supply unit is not effected by the suspected accident (e.g., the power supply unit is not damaged or slightly damaged) , and capable of providing power for the electric vehicle 140 normally. More details regarding the determination of the status of the power supply unit may be found elsewhere in the present disclosure, for example, FIGs. 7-9 and the descriptions thereof.

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

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, these variations and modifications fall in the scope of the present disclosure.

For example, at least a part of the motion sensors may be mounted on the power supply unit of the electric vehicle 140. The processing device 110 may obtain parameter values of motion parameters detected by the at least a part of the motion sensors mounted on the power supply unit. In this case, the processing device 110 (e.g., the abnormal identification module 420) may identify the abnormal status based on the obtained parameter values. In this case, the safety monitoring system and method may be applied in various situations, such as a falling down of the power supply unit, an impact of the power supply unit, etc., in a manufacture process of the power supply unit.

FIG. 6 is a flowchart illustrating an exemplary process for identifying an abnormal status of the target object according to some embodiments of the present disclosure. In some embodiments, the process 600 shown in FIG. 6 may be implemented in the safety monitoring system 100 illustrated in FIG. 1. For example, at least a part of the process 600 may be stored in a storage device (e.g., the DISK 270 of the computing device 200) as a form of instructions, and invoked and/or executed by the processing device 110 (e.g., the processor 220 of the computing device 200, one or more modules illustrated in FIG. 4) . In some embodiments, a part of the process 600 may be implemented on a terminal device. The operations of the illustrated process 600 presented below are intended to be illustrative. In some embodiments, the process 600 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process 600 as illustrated in FIG. 6 and described below is not intended to be limiting. In some embodiments, the operation 520 of the process 500 as illustrated in FIG. 5 may be performed according to the process 600.

In 610, the processing device 110 may obtain parameter values of one or more acceleration related parameters associated with an 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 axial directions of the electric vehicle 140. In some embodiments, the one or more acceleration related parameters may also include an average acceleration (e.g., a root mean square, an arithmetic average, etc. ) of one or more accelerations of one or more axial directions. Merely by way of example, the one or more acceleration related parameters may include an acceleration of the electric vehicle along an axial direction of the electric vehicle 140 at a time point, an average acceleration along an axial direction in a time period, a modulus of accelerations along at least two axial directions of the electric vehicle 140 at a time point, an average of moduli of accelerations along at least two axial directions in a time period, etc.

In 620, the processing device 110 may determine whether one or more impact 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 impact conditions associated with the electric vehicle 140 is satisfied, the process 600 may proceed to 630. If none of the one or more impact conditions associated with the electric vehicle 140 are satisfied, the processing device 110 may determine that the electric vehicle is in a normal status.

In some embodiments, the one or more impact conditions may include first impact conditions and second impact conditions. In some embodiments, the first impact conditions may relate to the parameter value of at least one acceleration corresponding to an axial direction. For example, the first impact conditions may be expressed in Formula (1) :

where a _it denotes a parameter value of an acceleration of the electric vehicle along an i axial direction at a time point t within a time period T, the i axial direction includes, e.g., the X axial direction, the Y axial direction, or the Z axial direction,

denotes a parameter value of an average acceleration along the i axial direction in the time period T, a _N denotes an acceleration threshold corresponding to the i axial direction. In some embodiments, the time period T, the threshold a _N may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the threshold a _N may be an empirical value. Merely by way of example, the time period T may be five minutes, half an hour, an hour, two hours, a day, a week, etc. In some embodiments, the time period T may be from a time point when the electric vehicle 140 starts a journey to a current time point. In some embodiments, n sampling points at which the one or more acceleration related parameters are sampled may be determined within the time period T, and the time point t may correspond to any one of the n sampling points. The parameter value of the average acceleration along the i axial direction

may be determined, for example, according to Formula (2) :

In some embodiments, the second impact conditions may relate to the parameter value of an average acceleration of at least two of the accelerations of the one or more axial directions. For example, the second impact conditions may be expressed in Formula (3) :

where |a _kt| denotes a parameter value of a modulus of accelerations along k axial directions of the coordinate system at a time point t, the k axial directions includes at least two of the X axis, the Y axis, and the Z axis,

denotes a parameter value of an average of moduli of accelerations along k axial directions in a time period T, and a _M denotes at least one threshold of the second impact conditions. In some embodiments, the at least one threshold a _M may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the at least one threshold a _M may be an empirical value. The parameter value of a modulus of accelerations along k axial directions may be determined according to, for example, Formula (4) :

The parameter value of the average of the moduli of accelerations along the k axial directions in the time period T may be determined according to , for example, Formula (5) :

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

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, these variations and modifications fall in the scope of the present disclosure. For example, the first impact conditions may include any parameter value of the accelerations corresponding to an axial direction is larger than a respective axial direction acceleration threshold. As another example, the second impact conditions may include the parameter value of the average acceleration of all the accelerations of the one more axial directions is larger than an average acceleration threshold.

FIG. 7 is a flowchart illustrating an exemplary process for determining a status of a power supply unit of an electric vehicle based at least in part on property values of one or more performance properties of the power supply unit according to some embodiments of the present disclosure. In some embodiments, the process 700 shown in FIG. 7 may be implemented in the safety monitoring system 100 illustrated in FIG. 1. For example, at least a part of the process 700 may be stored in a storage device (e.g., the DISK 270 of the computing device 200) as a form of instructions, and invoked and/or executed by the processing device 110 (e.g., the processor 220 of the computing device 200, one or more modules illustrated in FIG. 4) . In some embodiments, a part of the process 700 may be implemented on a terminal device. The operations of the illustrated process 700 presented below are intended to be illustrative. In some embodiments, the process 700 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process 700 as illustrated in FIG. 7 and described below is not intended to be limiting. In some embodiments, the operation 540 of the process 500 as illustrated in FIG. 5 may be performed according to the process 700.

In 710, the processing device 110 may obtain property values of one or more voltage related properties of the power supply unit of the electric vehicle.

In some embodiments, the one or more voltage related properties of the power supply unit may include voltages of one or more components of the power supply unit. In some embodiments, the one or more voltage related properties of the power supply unit may also include an average voltage of one or more components of the power supply unit in a time period. Merely by way of example, the one or more voltage related properties of the power supply unit may include a voltage of each of one or more components of the power supply unit at a time point, a voltage difference between a maximum voltage value and a minimum voltage value among voltage values of one or more components of the power supply unit at a time point, an average voltage difference in a current time period, an average voltage difference in a previous time period etc. As used herein, the current time period refers to a time period after a suspected accident of the electric vehicle 140 occurs. The previous time period refers to a time period before the suspected accident of the electric vehicle 140 occurs.

In 720, the processing device 110 may determine whether at least one of one or more safety warning conditions associated with the one or more voltage related properties is satisfied based on the property values of the one or more voltage related properties. If at least one of the one or more safety warning conditions for the one or more voltages is satisfied, the process 700 may proceed to 730. If none of the one or more safety warning conditions for the one or more voltages are satisfied, the process 700 may proceed to 740.

In some embodiments, the one or more safety warning conditions associated with the one or more voltage related properties may include first voltage warning conditions and second voltage warning conditions. In some embodiments, the first voltage warning conditions may include a difference between a maximum voltage value and a minimum voltage value among voltages of components of the power supply unit is larger than or equal to a respective maximum voltage difference threshold. For example, the first voltage warning conditions may be expressed in Formula (6) :

V _max-t-V _min-t≥ V _L, (6)

where V _max-t denotes a maximum voltage value among voltage values of all components of the power supply unit at a time point t in a time period T, V _min-t denotes a minimum voltage value among voltage values of all components of the power supply unit at the time point t, and V _L denotes a maximum voltage difference threshold. In some embodiments, the time period T and/or the maximum voltage difference threshold V _L may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the maximum voltage difference threshold V _L may be an empirical value.

In some embodiments, the second voltage warning conditions may include a difference between a property value of an average voltage difference in a current time period and a property value of an average voltage difference in a previous time period is larger than or equal to a product of a respective maximum voltage difference threshold and a health coefficient of the power supply unit. For example, the second voltage warning conditions may be expressed in Formula (7) :

where

denotes a property value of an average voltage difference in a current time period T _cur,

denotes a property value of an average voltage difference in a previous time period T _pre, and H denotes a health coefficient of the power supply unit. The health coefficient of the power supply unit may reflect a health degree of the power supply unit. In some embodiments, the health degree of the power supply unit may relate to the abnormal status of the electric vehicle 140 in a particular time period. In some embodiments, the health degree of the power supply unit may relate to a number or count of abnormal statuses of the electric vehicles in a particular time period Q. Merely for illustration purposes, the health coefficient of the power supply unit H may be represented as (1-min (p/10, 0.5) ) . min (p/10, 0.5) denotes a minimum value of p/10 or 0.5, and p denotes an abnormal parameter. In some embodiments, the abnormal parameter p may indicate a count of abnormal statuses in the particular time period Q (e.g., the current count of abnormal status) . In some embodiment, the abnormal parameter p may be a natural number, such as 0, 1, 2, 3, 5, 10, etc. In some embodiment, the abnormal parameter p may be set to 0 after the electric vehicle 140 and/or the power supply unit is manufactured or repaired. In some embodiment, the abnormal parameter p may be increased by a certain number each time an abnormal status of the electric vehicle 140 is identified. The certain number may be, for example, 1, 2, etc. In some embodiments, the certain number may relate to a serious degree of a suspected accident indicated by the abnormal status. In some embodiments, the current time period T _cur, the previous time period T _pre, and/or the particular time period Q may be specified by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. For example, the particular time period Q may range from a time point when the power supply unit is manufactured to a current time point.

In some embodiments, the average voltage difference in the current time period T _cur may be the average of voltage differences at different time points. Each voltage difference may be a difference between a maximum voltage and a minimum voltage among voltage values of components of the power supply unit at a corresponding time point. For example, the average voltage difference

may be determined according to Formula (8) :

where n denotes sampling points at which property values of the one or more voltages are sampled within the time period T _cur, and the time point t may correspond to any one of the n sampling points. In some embodiments, the average voltage difference

in a previous time period T _pre may be determined similarly.

In 730, the processing device 110 may determine that the power supply unit is in an unsafe status. If at least one of the one or more safety warning conditions associated with the one or more voltage related properties of the power supply unit in Formulas (6) - (8) is satisfied, the processing device 110 may determine that the power supply unit is in an unsafe status

In 740, the processing device 110 may determine that the power supply unit is in a safe status in terms of the voltage related properties. If none of the one or more safety warning conditions associated with the one or more voltage related properties of the power supply unit in Formulas (6) - (8) are satisfied, the processing device 110 may determine that the power supply unit is in a safe status in terms of the voltage related properties.

FIG. 8 is a flowchart illustrating an exemplary process for determining a status of a power supply unit based at least in part on property values of one or more performance properties of the power supply unit according to some embodiments of the present disclosure. In some embodiments, the process 800 shown in FIG. 8 may be implemented in the safety monitoring system 100 illustrated in FIG. 1. For example, at least a part of the process 800 may be stored in a storage device (e.g., the DISK 270 of the computing device 200) as a form of instructions, and invoked and/or executed by the processing device 110 (e.g., the processor 220 of the computing device 200, one or more modules illustrated in FIG. 4) . In some embodiments, a part of the process 800 may be implemented on a terminal device. The operations of the illustrated process 800 presented below are intended to be illustrative. In some embodiments, the process 800 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process 800 as illustrated in FIG. 8 and described below is not intended to be limiting. In some embodiments, the operation 540 of the process 500 as illustrated in FIG. 5 may be performed according to the process 800.

In 810, the processing device 110 may obtain property values of one or more temperature related properties of the power supply unit of the electric vehicle.

In some embodiments, the one or more temperature related properties of the power supply unit may include temperatures 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 an average temperature of one or more components of the power supply unit in a time period. Merely by way of example, the one or more temperature related properties of the power supply unit may include a temperature of each of one or more components of the power supply unit at a time point, an average temperature in a current time period, an average temperature in a previous time period, etc.

In 820, the processing device 110 may determine whether at least one one or more safety warning conditions associated with the one or more temperature related properties is satisfied based on the values of the one or more temperature related properties. If at least one of the one or more safety warning conditions associated with the one or more temperature related properties is satisfied, the process 800 may proceed to 830. If none of the one or more safety warning conditions associated with the one or more temperature related properties are satisfied, the process 800 may proceed to 840.

In some embodiments, the one or more safety warning conditions associated with the one or more temperature related properties may include first temperature warning conditions, second temperature warning conditions, and third temperature warning conditions. In some embodiments, the first temperature warning conditions may include a difference between a maximum temperature value and a minimum temperature value among temperature values of components of the power supply unit is larger than or equal to a respective maximum temperature difference threshold. For example, the first temperature warning conditions may be expressed in Formula (9) :

W _max-t-W _min-t≥ W _L, (9)

where W _max-t denotes a maximum temperature value among temperature values of all components of the power supply unit at a time point t within a time period T, W _min-t denotes a minimum temperature value among temperature values of all components of the power supply unit at the time point t, and W _L denotes a maximum temperature difference threshold. In some embodiments, the time period T and/or the maximum temperature difference threshold W _L may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the maximum temperature difference threshold W _L may be an empirical value.

In some embodiments, the second temperature warning conditions may include a difference between a property value of an average temperature difference in a current time period and a property value of an average temperature difference in a previous time period is larger than or equal to a product of a respective maximum temperature difference threshold and a health coefficient of the power supply unit. For example, the second temperature warning conditions may be expressed in Formula (10) :

where

denotes a property value of an average temperature difference in a current time period T _cur,

denotes a property value of an average temperature difference in a previous time period T _pre, and H denotes a health coefficient of the power supply unit. The health coefficient of the power supply unit may reflect a health degree of the power supply unit. In some embodiments, the health degree of the power supply unit may relate to the abnormal status of the electric vehicle 140 in a particular time period. In some embodiments, the health degree of the power supply unit may relate to a count of abnormal statuses of the electric vehicles in a particular time period Q (e.g., the current count of abnormal status) .. Merely for illustration purposes, the health coefficient of the power supply unit H may be represented as (1-min (p/10, 0.5) ) . min (p/10, 0.5) denotes a minimum value of p/10 or 0.5, and p denotes an abnormal parameter. In some embodiments, the numbers 10, 0.5 may be adjusted according to actual needs. More details regarding the health coefficient of the power supply unit may be described elsewhere in the present disclosure, for example, FIG. 7 and the descriptions thereof. In some embodiments, the current time period T _cur, the previous time period T _pre, and/or the particular time period Q may be specified by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. For example, the particular time period Q may range from a time point when the power supply unit is manufactured to a current time point.

In some embodiments, the average temperature difference in the current time period T _cur may be the average of temperature differences at different time points. Each temperature difference may be a difference between a maximum temperature and a minimum temperature among temperature values of components of the power supply unit at a corresponding time point. For example, the average temperature difference

may be determined according to Formula (11) :

where n denotes sampling points at which property values of the one or more temperatures are sampled within the time period T _cur, and the time point t may correspond to any one of the n sampling points. In some embodiments, the average temperature difference in a previous time period

may be determined similarly.

In some embodiments, the third temperature warning conditions may include a maximum temperature value of components of the power supply unit is larger than or equal to a respective maximum temperature threshold. For example, the third temperature warning conditions may be expressed in Formula (12) :

W _max-t≥ W _ML, (12)

where W _max-t denotes a maximum temperature value among temperature values of all components of the power supply unit at a time point t in a time period T, and W _ML denotes a maximum temperature threshold. In some embodiments, the time period T and/or the maximum temperature threshold W _ML may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the maximum temperature difference threshold W _ML may be an empirical value.

In 830, the processing device 110 may determine that the power supply unit is in an unsafe status. If at least one of the one or more safety warning conditions associated with the one or more temperature related properties of the power supply unit in Formulas (9) - (12) is satisfied, the processing device 110 may determine that the power supply unit is in an unsafe status

In 840, the processing device 110 may determine that the power supply unit is in a safe status in terms of the temperatures. If none the one or more safety warning conditions associated with the one or more temperature related properties of the power supply unit in Formulas (9) - (12) are satisfied, the processing device 110 may determine that the power supply unit is in a safe status in terms of the temperature related properties.

FIG. 9 is a flowchart illustrating an exemplary process for determining a status of a power supply unit based at least in part on property values of one or more performance properties of the power supply unit according to some embodiments of the present disclosure. In some embodiments, the process 900 shown in FIG. 9 may be implemented in the safety monitoring system 100 illustrated in FIG. 1. For example, at least a part of the process 900 may be stored in a storage device (e.g., the DISK 270 of the computing device 200) as a form of instructions, and invoked and/or executed by the processing device 110 (e.g., the processor 220 of the computing device 200, one or more modules illustrated in FIG. 4) . In some embodiments, a part of the process 900 may be implemented on a terminal device. The operations of the illustrated process 900 presented below are intended to be illustrative. In some embodiments, the process 900 may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process 900 as illustrated in FIG. 9 and described below is not intended to be limiting. In some embodiments, the operation 540 of the process 500 as illustrated in FIG. 5 may be performed according to the process 900.

In 910, the processing device 110 may obtain property values of one or more electric resistance related properties of the power supply unit of the electric vehicle.

In some embodiments, the one or more electric resistance related properties of the power supply unit may include an electric resistance of the power supply unit. In some embodiments, the one or more electric resistance related properties of the power supply unit may also include an average electric resistance of the power supply unit in a time period. Merely by way of example, the one or more electric resistance related properties of the power supply unit may include an electric resistance of the power supply unit at a time point, an average electric resistance in a current time period, an average electric resistance in a previous time period etc.

In 920, the processing device 110 may determine whether at least one of one or more safety warning conditions associated with the one or more electric resistance related properties is satisfied based on the property values of the one or more electric resistance related properties. If at least one of the one or more safety warning conditions associated with the one or more electric resistance related properties is satisfied, the process 900 may proceed to 930. If none of the one or more safety warning conditions associated with the one or more electric resistance related properties are satisfied, the process 900 may proceed to 940.

In some embodiments, the one or more safety warning conditions associated with the one or more electric resistance related properties may include first electric resistance warning conditions, second electric resistance warning conditions, and third electric resistance warning conditions. In some embodiments, the first electric resistance warning conditions may include a difference between a first electric resistance value at a first time point and a second electric resistance value at a second time point is larger than or equal to a minimum electric resistance decrement threshold. The minimum electric resistance decrement threshold may be a lower limit of the electric resistance decrement of the power supply unit from the second time point and the first time point. For example, the first electric resistance warning conditions may be expressed in Formula (13) :

R _t+1-R _t≥R _l, (13)

where R _t+1 denotes a first electric resistance value of the power supply unit at a second time point t+1 in a time period T, R _t denotes a second electric resistance value of the power supply unit at a second time point t in the time period T, and R _l denotes a minimum electric resistance decrement 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 electric resistance decrement threshold R _l may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the minimum electric resistance decrement threshold R _l may be an empirical value.

In some embodiments, the second electric resistance warning conditions may include a difference between a property value of an average electric resistance in a current time period and a property value of an average electric resistance in a previous time period is larger than or equal to a product of a respective minimum electric resistance decrement threshold and a health coefficient of the power supply unit. For example, the second electric resistance warning conditions may be expressed in Formula (14) :

where

denotes a property value of an average electric resistance in a current time period T _cur,

denotes a property value of an average electric resistance in a previous time period T _pre, and H denotes a health coefficient of the power supply unit. The health coefficient of the power supply unit may reflect a health degree of the power supply unit. In some embodiments, the health degree of the power supply unit may relate to the abnormal status of the electric vehicle 140 in a particular time period. In some embodiments, the health degree of the power supply unit may relate to a count of abnormal statuses of the electric vehicles in a particular time period Q (e.g., the current count of abnormal status) . Merely for illustration purposes, the health coefficient of the power supply unit H may be represented as (1-min (p/10, 0.5) ) . More details regarding the health coefficient of the power supply unit may be described elsewhere in the present disclosure, for example, FIG. 7 and the descriptions thereof. In some embodiments, the current time period T _cur, the previous time period T _pre, and/or the particular time period Q may be specified by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. For example, the particular time period Q may range from a time point when the power supply unit is manufactured to a current time point.

In some embodiments, the average electric resistance in the current time period T _cur may be the average of property values of electric resistances at different time points in the current time period T _cur. For example, the average electric resistance

may be determined according to Formula (15) :

where n denotes sampling points at which property values of the one or more temperatures are sampled within the time period T _cur, and the time point t may correspond to any one of the n sampling points. In some embodiments, the average electric resistance

in a previous time period T _pre may be determined similarly.

In some embodiments, the third temperature warning conditions may include an electric resistance of the power supply unit is smaller than or equal to than a respective minimum electric resistance threshold. For example, the third electric resistance warning conditions may be expressed in Formula (16) :

R _t≤R _L, (16)

where R _t denotes a resistance value of the power supply unit at a time point t in a time period T, and R _L denotes a minimum electric resistance threshold. In some embodiments, the time period T and/or the minimum electric resistance threshold R _L may be determined by a user (e.g., a technician) , according to default settings of the safety monitoring system 100, etc. In some embodiments, the minimum electric resistance threshold R _L may be an empirical value.

In 930, the processing device 110 may determine that the power supply unit is in an unsafe status. If at least one of the one or more safety warning conditions associated with the one or more electric resistance related properties of the power supply unit in Formulas (13) - (16) is satisfied, the processing device 110 may determine that the power supply unit is in an unsafe status.

In 940, the processing device 110 may determine that the power supply unit is in a safe status in terms of the electric resistance related properties. If none of the one or more safety warning conditions associated with the one or more electric resistance related properties of the power supply unit in Formulas (13) - (16) are satisfied, the processing device 110 may determine that the power supply unit is in a safe status in terms of the electric resistance related properties.

Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure, and are within the spirit and scope of the exemplary embodiments of this disclosure.

Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment, ” “an embodiment, ” and “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc. ) or combining software and hardware implementation that may all generally be referred to herein as a “module, ” “unit, ” “component, ” “device, ” or “system. ” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN) , or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS) .

Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software only solution, e.g., an installation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claim subject matter lie in less than all features of a single foregoing disclosed embodiment.

Claims

A system, comprising:

at least one storage device storing a set of instructions; and

at least one processor configured to communicate with the at least one storage device, wherein when executing the set of instructions, the at least one processor is directed to perform operations including:

obtaining parameter values of one or more motion parameters associated with a target object;

identifying an abnormal status of the target object based on the parameter values;

obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and

determining a status of the power supply unit based at least in part on the property values.
The system of claim 1, wherein the target object is a vehicle.
The system of claim 1 or 2, wherein the one or more motion parameters include one or more accelerations each corresponding to each of one or more axial directions of the target object, and an average acceleration of all the accelerations of the one or more axial directions.
The system of claim 3, wherein the parameter values of the one or more accelerations are acquired by at least one acceleration sensor coupled to the target object.
The system of any one of claims 1-4, wherein identifying the abnormal status of the target object based on the at least one motion parameter includes:

determining whether one or more impact conditions associated with the target object are satisfied based on the parameter values;

in response to the determination that at least one of the one or more impact conditions associated with the target object is satisfied, determining that the target object is in an abnormal status.
The system of claim 5, wherein the one or more impact conditions include:

any parameter value of the accelerations corresponding to an axial direction is larger than a respective axial direction acceleration threshold; and

the parameter value of the average acceleration of all the accelerations of the one or more axial directions is larger than an average acceleration threshold.
The system of any one of claims 1-6, wherein the power supply unit is a battery.
The system of any one of claims 1-7, the operations further including:

obtaining a prior count of abnormal status of the target object; and

generating a current count of abnormal status by increasing the prior count by one in response to identifying the abnormal status of the target object.
The system of claim 8, wherein determining the status of the power supply unit based at least in part on the property values of one or more performance properties including:

determining the status of the power supply unit based on the property values of the one or more performance properties and the current count of the abnormal status.
The system of any one of claims 1-9, wherein the one or more performance properties include:

one or more voltages each corresponding to each of one or more components of the power supply unit, and an average voltage of all the voltages of the one or more components;

one or more temperatures each corresponding to each of one or more components of the power supply unit; and an average temperature of all the temperatures of the one or more components; and

an electric resistance of the power supply unit; and an average electric resistance of all the electric resistances of the power supply unit in a time period.
The system of any one of claims 1-10, wherein determining the status of the power supply unit based at least in part on the property values of one or more performance properties includes:

determining whether one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied based on the property values of the one or more performance properties;

in response to the determination that at least one of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit is satisfied, determining an unsafe status of the power supply unit.
The system of claim 11, the operations further including:

in response to the determination that none of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied, determining a safe status of the power supply unit.
The system of claim 11 or 12, wherein the one or more safety warning conditions associated with the one or more performance properties 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 electric resistance warning conditions.
The system of any one of claims 11-13, wherein at least one of the one or more safety warning conditions relates to a current count of abnormal status of the target object.
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 a target object;

identifying an abnormal status of the target object based on the parameter values;

obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and

determining a status of the power supply unit based at least in part on the property values.
The method of claim 15, wherein the target object is a vehicle.
The method of claim 15 or 16, wherein the one or more motion parameters include one or more accelerations each corresponding to each of one or more axial directions of the target object, and an average acceleration of all the accelerations of the one or more axial directions.
The method of claim 17, wherein the parameter values of the one or more accelerations are acquired by at least one acceleration sensor coupled to the target object.
The method of any one of claims 15-18, wherein identifying the abnormal status of the target object based on the at least one motion parameter includes:

determining whether one or more impact conditions associated with the target object are satisfied based on the parameter values;

in response to the determination that at least one of the one or more impact conditions associated with the target object is satisfied, determining that the target object is in an abnormal status.
The method of claim 19, wherein the one or more impact conditions include:

any parameter value of the accelerations corresponding to an axial direction is larger than a respective axial direction acceleration threshold; and

the parameter value of the average acceleration of all the accelerations of the one or more axial directions is larger than an average acceleration threshold.
The method of any one of claims 15-20, wherein the power supply unit is a battery.
The method of any one of claims 15-21, the operations further including:

obtaining a prior count of abnormal status of the target object; and

generating a current count of abnormal status by increasing the prior count by one in response to identifying the abnormal status of the target object.
The method of claim 22, wherein determining the status of the power supply unit based at least in part on the property values of one or more performance properties including:

determining the status of the power supply unit based on the property values of the one or more performance properties and the current count of the abnormal status.
The method of any one of claims 15-23, wherein the one or more performance properties include:

one or more voltages each corresponding to each of one or more components of the power supply unit, and an average voltage of all the voltages of the one or more components;

one or more temperatures each corresponding to each of one or more components of the power supply unit; and an average temperature of all the temperatures of the one or more components; and

an electric resistance of the power supply unit; and an average electric resistance of all the electric resistances of the power supply unit in a time period.
The method of any one of claims 15-24, wherein determining the status of the power supply unit based at least in part on the property values of one or more performance properties includes:

determining whether one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied based on the property values of the one or more performance properties;

in response to the determination that at least one of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit is satisfied, determining an unsafe status of the power supply unit.
The method of claim 25, the operations further including:

in response to the determination that none of the one or more safety warning conditions associated with the one or more performance properties of the power supply unit are satisfied, determining a safe status of the power supply unit.
The method of claim 25 or 26, wherein the one or more safety warning conditions associated with the one or more performance properties 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 electric resistance warning conditions.
The method of any one of claims 25-27, wherein at least one of the one or more safety warning conditions relates to a current count of abnormal status of the target object.
A non-transitory computer-readable storage medium including instructions, that, when accessed by at least one processor of a system, causes the system to perform a method, the method comprising:

obtaining parameter values of one or more motion parameters associated with a target object;

identifying an abnormal status of the target object based on the parameter values;

obtaining property values of one or more performance properties of a power supply unit of the target object in response to identifying the abnormal status of the target object, wherein the power supply unit provides power for the target object; and

determining a status of the power supply unit based at least in part on the property values.