Method and electronic device for managing vehicle charging

Abstract

The embodiment of the invention provides a method for managing vehicle charging and electronic equipment. The method comprises the steps that during charging of the vehicle, a current thermal runaway characteristic value related to state information of a charged battery of the vehicle is determined, and the state information of the charged battery at least comprises the temperature of the charged battery; determining confidence target information related to the vehicle according to target image data about the vehicle acquired from an image acquisition module, wherein the confidence target information comprises a confidence value; in response to determining that the current thermal runaway characteristic value is in the fusion interval, comparing a plurality of confidence values in the detection period with a first confidence threshold respectively; and outputting the target image data and the confidence target information via an output unit in response to determining that at least part of the confidence values in the plurality of confidence values in the detection period are respectively greater than a first confidence threshold. In this way, the thermal runaway condition can be judged more accurately in combination with the state information of the charged battery and the target image data.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of vehicle charging, and more particularly, to a method and electronic device for managing vehicle charging. Background Art

[0002] As the performance of electric vehicles continues to improve, the application of high-current charging and high-capacity lithium-ion batteries in electric vehicles has become popular. Due to the characteristics of the materials of lithium-ion batteries themselves, they will encounter thermal problems during the charging process and there is a risk of thermal runaway. In addition, there are many brands of new energy vehicles and charging piles with varying quality. Spontaneous combustion accidents caused by thermal runaway of batteries during charging of electric vehicles have occurred frequently, which has attracted widespread attention.

[0003] If a vehicle spontaneously ignites during charging at a charging station and is not discovered and dealt with in a timely manner, it will cause greater casualties and property losses and bring huge operating risks to the charging station. Therefore, it is imperative to deploy a thermal runaway alarm system at the charging station. Summary of the invention

[0004] The first aspect of the present disclosure provides a method for managing vehicle charging. The method includes: during charging of the vehicle, determining a current thermal runaway characteristic value related to the state information of a charged battery of the vehicle, the state information of the charged battery at least including the temperature of the charged battery; determining confidence target information related to the vehicle based on target image data about the vehicle acquired from an image acquisition module, the confidence target information at least including a confidence value; in response to determining that the current thermal runaway characteristic value is in a fusion interval, comparing multiple confidence values ​​within a detection cycle with a first confidence threshold respectively; and in response to determining that at least some of the confidence values ​​of the multiple confidence values ​​within the detection cycle are respectively greater than the first confidence threshold, outputting the target image data and the confidence target information via an output unit.

[0005] In some embodiments, the confidence target information also includes at least one of target type and target circumscribed rectangle coordinate information.

[0006] In some embodiments, the method further includes: in response to determining that the current thermal runaway characteristic value is greater than the maximum value of the fusion interval, outputting at least the battery jump temperature via an output unit.

[0007] In some embodiments, the method further includes: in response to determining that the confidence is greater than a second confidence threshold, outputting the target image data and the confidence target information via an output unit, the second confidence threshold being greater than the first confidence threshold.

[0008] In some embodiments, the method also includes: in response to determining that the current thermal runaway characteristic value is in a fusion interval and determining that all confidence values ​​within a detection cycle are not greater than a first confidence threshold, comparing the confidence value after the detection cycle with a second confidence threshold, and the second confidence threshold is greater than the first confidence threshold.

[0009] In some embodiments, the method further includes: acquiring target image data from an image acquisition module associated with a charging pile for charging the vehicle among the plurality of image acquisition modules.

[0010] In some embodiments, the method further includes: associating a charging post in a field of view of each of the plurality of image acquisition modules with the corresponding image acquisition module.

[0011] In some embodiments, the method further includes: determining a current thermal runaway characteristic value based at least on a temperature rise rate of the charged battery and a current battery temperature.

[0012] In some embodiments, the method further includes: determining the battery jump temperature based on the current battery temperature of the charged battery and the average temperature of the battery in the calculation cycle where the current battery temperature belongs.

[0013] In some embodiments, the confidence target information is determined based on a smoke and fire detection model constructed by a deep learning network.

[0014] The second aspect of the present disclosure provides an electronic device. The electronic device includes: at least one processing unit; and at least one memory, which is coupled to the at least one processing unit and stores machine executable instructions, and when the instructions are executed by the at least one processing unit, the electronic device performs an action, the action including: during charging of the vehicle, determining a current thermal runaway characteristic value related to the state information of the charged battery of the vehicle, the state information of the charged battery at least including the temperature of the charged battery; determining confidence target information related to the vehicle according to the target image data about the vehicle collected from the image acquisition module, the confidence target information at least including the confidence value; in response to determining that the current thermal runaway characteristic value is in the fusion interval, comparing multiple confidence values ​​within the detection cycle with a first confidence threshold respectively; and in response to determining that at least some of the confidence values ​​of the multiple confidence values ​​within the detection cycle are respectively greater than the first confidence threshold, outputting the target image data and the confidence target information via an output unit.

[0015] According to the method for managing vehicle charging provided by the present disclosure, by analyzing the status information of the charging battery and the current target image data in the charging station, the thermal runaway and thermal runaway risk in the charging station can be warned. By judging the fusion strategy of the status information of the charging battery and the current target image data, the accuracy of the warning can be improved, and effective monitoring and protection can still be achieved in scenarios such as the vehicle BMS system transmitting invalid battery data or the vehicle being left idle for a long time after charging is completed and catching fire.

[0016] The third aspect of the present disclosure provides a computer storage medium on which the computer program product is stored, the computer program product comprising machine executable instructions, which, when executed, enable a machine to perform the steps of the method in the first aspect of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0018] Figure 1 A simplified schematic diagram of a control system according to an embodiment of the present disclosure is shown;

[0019] Figure 2 A flowchart of a method for managing vehicle charging according to an embodiment of the present disclosure; and

[0020] Figure 3 A schematic block diagram of an electronic device suitable for implementing an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0021] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0022] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0023] The principles of the present disclosure will be described below with reference to several example embodiments shown in the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that these embodiments are described only to enable those skilled in the art to better understand and implement the present disclosure, and are not intended to limit the scope of the present disclosure in any way.

[0024] In addition, the term "in response to" as used herein refers to a state in which a corresponding event occurs or a condition is satisfied. It will be understood that the timing of executing a subsequent action executed in response to the event or condition is not necessarily strongly related to the time when the event occurs or the condition is satisfied. For example, in some cases, the subsequent action may be executed immediately when the event occurs or the condition is satisfied; while in other cases, the subsequent action may be executed after a period of time after the event occurs or the condition is satisfied.

[0025] As mentioned above, with the popularity of electric vehicles, charging piles have become one of the important infrastructures for electric vehicles. Many parking lots (hereinafter referred to as charging stations) have set up a large number of charging piles to meet the charging problems of electric vehicles. There are also a large number of cameras distributed in the parking lot to report the situation in the parking lot to users in real time, making it convenient for users to maintain and manage the parking lot.

[0026] During the charging process of electric vehicles, due to the characteristics of the materials of the charged batteries themselves, they will encounter heat problems and there is a risk of thermal runaway. In order to monitor and warn of thermal runaway phenomena that may occur during the charging process, in existing electric vehicles, during the charging of electric vehicles, the charging pile communicates with the vehicle battery management system (BMS) system in real time to obtain the current battery temperature, voltage and other status information, and transmit it to the calculation unit in real time to analyze whether thermal runaway occurs or there is a risk of thermal runaway.

[0027] However, the above monitoring method also has some disadvantages. For example, on the one hand, due to the lack of obvious early characteristics of thermal runaway, the computing unit may falsely report thermal runaway, resulting in premature intervention of control actions and unnecessary economic losses; on the other hand, this solution is not suitable for static fires after a long time after charging; on the other hand, due to the large number of brands and models of electric vehicles being charged, the status information of the charged battery obtained by the charging pile during the charging process varies greatly, thus affecting the accuracy and stability of the thermal runaway warning.

[0028] In order to solve or at least partially solve the above-mentioned problems or other potential problems of traditional charging piles, an embodiment of the present disclosure provides a method, which simultaneously analyzes the state information of the charged battery obtained by the charging pile and the target image data obtained by the internal monitoring camera of the charging station, and strategically fuses the two analysis results to judge the thermal runaway situation inside the charging station as a whole. The accuracy and stability of thermal runaway judgment are improved by strategically fusing the battery data analysis results with the image analysis results. And because the two sets of data analysis are independent of each other, the reliability of thermal runaway judgment is also improved.

[0029] The present disclosure also provides an electronic device. In some embodiments, the electronic device may be a control system of a charging station or a control unit, a processing unit or a computing unit of a control platform. Figure 1 A brief schematic diagram of the control system is shown in Figure 2. Figure 1 As shown, the control system 4 generally includes a data acquisition unit 1, an algorithm analysis unit 2 and an alarm output unit 3. The data acquisition unit 1 sends the collected data of the electric vehicle when charging in the charging station (including the status information of the charged battery and the target image data of the vehicle and the corresponding charging pile) to the algorithm analysis unit 2. In some embodiments, the algorithm analysis unit 2 may be a computing unit (also referred to as an electronic device) or a part of a computing unit of the control system mentioned above. After the algorithm analysis unit 2 processes and analyzes the data, it outputs the situation that thermal runaway has occurred or there is a risk of thermal runaway to the alarm output unit 3. The alarm output unit 3 alarms the user in an appropriate manner and reports to the user information such as the specific location of the thermal runaway in the charging station. These three units will be described in detail below.

[0030] The data acquisition unit 1 includes a battery status acquisition module 11 and an image acquisition module 12. The battery status acquisition module 11 is suitable for collecting the status information of the battery being charged during the charging process of the electric vehicle. In some embodiments, the status information of the battery being charged may include the current battery temperature (T i ), voltage, etc. In some embodiments, the battery status acquisition module 11 may be integrated in a charging pile in a charging station. When the charging pile charges the charged battery of the electric vehicle, the battery status acquisition module 11 communicates with the battery management system (BMS) of the charged battery to obtain the status information of the charged battery of the electric vehicle. The battery status acquisition module 11 may also send the acquired status information of the charged battery to the algorithm analysis unit 2 for processing by the algorithm analysis unit 2.

[0031] The image acquisition module 12 is suitable for collecting target image data of the charging pile and the electric vehicle in the parking space corresponding to the charging pile. For example, the target image data can be a set of photos taken at fixed intervals, or a video of a period of time. In some embodiments, the image acquisition module 12 can be a surveillance camera arranged in the charging station. The surveillance camera can take photos of the charging pile and the parking space corresponding to the charging pile at fixed intervals (when there is an electric vehicle charging in the parking space, the surveillance camera can take pictures of the charging pile and the electric vehicle being charged), and the image acquisition module 12 can also send the current target image data to the algorithm analysis unit 2.

[0032] In some embodiments, a plurality of surveillance cameras are installed in the charging station, and a plurality of charging piles and corresponding parking spaces are within the shooting field of each surveillance camera. Therefore, before the surveillance camera sends the target image data to the algorithm analysis unit 2, the surveillance camera needs to be initialized so that the target image data obtained by each surveillance camera is associated with the corresponding charging pile.

[0033] In some embodiments, multiple groups of surveillance cameras can be numbered, and the number of the surveillance camera is used as the key, and the number of the charging piles in different areas within the field of view of the surveillance camera is used as the value for mapping. For example: camera_id_1: [charge_id_1, charge_id_2, charge_id_3] means that the field of view of the camera numbered camera_id_1 includes the charging piles numbered charge_id_1, charge_id_2, and charge_id_3. When the position of the surveillance camera or charging pile in the charging station changes, the calibration file can be adjusted to modify the mapping relationship between the camera and the charging pile in the strategy fusion module 23 to adapt.

[0034] In some alternative embodiments, there is only one surveillance camera within the field of view of each surveillance camera in the charging station, and each surveillance camera may also be directly associated with a charging pile within the field of view of the surveillance camera.

[0035] The algorithm analysis unit 2 includes a battery algorithm analysis module 21, an image analysis module 22, and a strategy fusion module 23. As mentioned above, the battery status acquisition module 11 sends the status information of the charged battery to the algorithm analysis unit 2. More specifically, the battery status acquisition module 11 sends the status information of the charged battery to the battery algorithm analysis module 21, and the battery algorithm analysis module 21 processes the data of the status information.

[0036] In some embodiments, the battery algorithm analysis module 21 calculates the acquired multiple battery temperatures to obtain at least a battery jump temperature (T cSpecifically, the battery jump temperature is based on the current battery temperature (T i ) and the truncated mean of all battery temperatures in the calculation cycle (t) where the current battery temperature is located. The truncated mean refers to the average temperature (T) calculated by removing the highest and lowest temperatures from all battery temperatures in the calculation cycle. m ).

[0037] For example, in some embodiments, the calculation cycle is set to 30s, and all battery temperatures within the calculation cycle include all battery temperatures received from 15s before the current battery temperature to 15s after the current battery temperature. After removing the maximum and minimum values ​​of this batch of data, the average temperature (T m ), which is the trimmed mean.

[0038] In some embodiments, the battery jump temperature T can be determined according to the following formula (1): c .

[0039] T c =T i -T m (1)

[0040] In some embodiments, the battery algorithm analysis module 21 calculates the battery jump temperature T c Further processing can also determine the temperature rise rate (C i ).

[0041] For example, the battery temperature rise rate C is determined according to the following formula (2): i .

[0042]

[0043] Furthermore, in some embodiments, the battery algorithm analysis module 21 can also calculate the temperature rise rate C i Further processing is performed to determine the current thermal runaway characteristic value (W i ).

[0044] For example, the current thermal runaway characteristic value W is obtained according to the following formula (3): i .

[0045] W i =α*C i *T i (3)

[0046] Among them, α is the amplification factor, through which the value of the current thermal runaway characteristic value Wi can be proportionally amplified, thereby improving the accuracy of the subsequent comparison. The value of α can be a constant greater than 1, for example, it can be 10, 50, 100, etc.

[0047] The battery algorithm analysis module 21 can directly compare the obtained current thermal runaway characteristic value with the first thermal runaway threshold and the second thermal runaway threshold (wherein the first thermal runaway threshold is less than the second thermal runaway threshold, and the interval formed by the first thermal runaway threshold and the second thermal runaway threshold is also called a fusion interval). According to the comparison result, the result is output to the strategy fusion module 23 or the alarm output unit 3.

[0048] The selection of outputting the result to the policy fusion module 23 or the alarm output unit 3 specifically includes the following situations.

[0049] If the current thermal runaway characteristic value is greater than the second thermal runaway threshold, the battery algorithm analysis module 21 confirms that thermal runaway has occurred and sends an alarm to the alarm output unit 3, and the T c The alarm is transmitted to the alarm output unit 3 and provided to the user.

[0050] If the current thermal runaway characteristic value is less than or equal to the first thermal runaway threshold, the battery algorithm analysis module 21 confirms that the charging station operates normally.

[0051] If the current thermal runaway characteristic value is within the fusion interval (ie, the current thermal runaway value is greater than the first thermal runaway threshold and less than or equal to the second thermal runaway threshold), the fusion strategy module is triggered. The fusion strategy module will be explained below.

[0052] Back to the image analysis module 22, in the image analysis module 22, the image analysis module 22 uses the smoke and fire detection model constructed according to the deep learning network to process the current target image data collected by the image acquisition module 12 in real time, and outputs the current target image data and the confidence information of the current target image data detection to the strategy fusion module 23, and the confidence information at least includes the confidence value. The confidence value represents the credibility of the presence of smoke and / or fire in the detected target image data, which is between 0 and 1, where 0 is completely untrustworthy and 1 is completely trustworthy.

[0053] In some embodiments, the image analysis module 22 can use a smoke and fire detection model constructed by a deep learning network. In some embodiments, the deep learning network can be a yolov5 deep learning network or other appropriate deep learning networks. The specific implementation steps of model construction are as follows. First, enough (for example, more than 10,000) pictures containing smoke and fire can be collected first. The pictures can be any appropriate sampling data from the Internet, real accident video sampling, self-smoke, arson simulation video, etc. After obtaining enough pictures, the collected pictures are then labeled according to the smoke and fire categories using appropriate image annotation tools (such as VIA annotation tools). For example, the smoke and fire annotation rules adopted are as follows.

[0054] If the flame instance has a clear outline, the minimum circumscribed rectangle of the flame can be framed. Fire instances that are smaller than 10% to 20% of the screen ratio (for example, 10%, 12%, 14%, 16%, 18%, 20%) will not be marked. For smoke instances, the selection and marking of smoke instances can follow the following rules. First, the smoke instance must have a clear outline. If the outline is not clear, it will not be marked. Secondly, for light smoke with a clear outline, if the area is seriously disturbed by other background targets, it will not be marked. In addition, if the obscured part of the smoke occupies more than 10% to 30% of the framed area (for example, 12%, 16%, 20%, 24%, 28%), it will not be marked. In addition, if the smoke instance is smaller than 10% to 20% of the screen ratio (for example, 10%, 12%, 14%, 16%, 18%, 20%), it will not be marked. By adopting the above rules, the interference of erroneous information such as water and transparent plastic bags that may appear in the picture can be effectively eliminated. For images containing smoke and fire instances that do not conform to the above labeling rules, they are directly deleted and not used for model training.

[0055] After the data is labeled, the data is divided into a training set and a validation set in a ratio of 9:1 or other appropriate ratios for model training, and finally the fireworks detection model used in this system is obtained.

[0056] In some embodiments, the confidence information may also include target type and / or target bounding rectangle coordinate information, etc. For example, the target type may include a smoke instance or a flame instance determined by a smoke and fire detection model. The specific fire location in the field of view of the surveillance camera may be more accurately located based on the target bounding rectangle coordinate information. The target bounding rectangle coordinate information may reflect the size of the target.

[0057] In some embodiments, based on the association between the target image data acquired by each surveillance camera and the corresponding charging pile introduced above, the specific number of the charging pile where thermal runaway occurs can also be confirmed based on the coordinate information of the target circumscribed rectangle, so as to accurately locate the location where the thermal runaway occurs.

[0058] The image analysis module 22 may compare the obtained confidence value with the first confidence threshold and the second confidence threshold (where the first confidence threshold is less than the second confidence threshold), and based on the comparison result, select to output the result to the strategy fusion module 23 or the alarm output unit 3.

[0059] The selection of outputting the result to the policy fusion module 23 or the alarm output unit 3 specifically includes the following situations.

[0060] If the confidence value is greater than the second confidence threshold, the image analysis module 22 confirms that thermal runaway has occurred and sends an alarm to the alarm output unit 3. The image analysis module 22 transmits the current target image data and its confidence information to the alarm output unit 3, and notifies the user thereby.

[0061] As mentioned above, if the current thermal runaway characteristic value is within the fusion interval, the fusion strategy module is triggered. The strategy fusion module 23 obtains the current thermal runaway characteristic value and the battery jump temperature T from the battery algorithm analysis module 21. c The current target image data and its confidence information are obtained from the image analysis module 22. The confidence information includes: target type, confidence value, target circumscribed rectangle coordinate information, etc. The fusion strategy module performs fusion strategy judgment, including the following situations.

[0062] If the current thermal runaway characteristic value is within the fusion interval, find the camera that has a mapping relationship with the charging pile that triggers the fusion strategy, and in the subsequent detection cycle (T s , for example, within 30s, 60s, etc.), the data generated by the camera through the image analysis module 22 is analyzed with a first confidence threshold.

[0063] If the confidence value is greater than the first confidence threshold, the fusion strategy module determines that thermal runaway occurs and sends an alarm to the alarm output unit 3, and transmits the current target image data and confidence information to the alarm output unit 3. During this period, the output data of other cameras through the image analysis module 22 is still analyzed according to the second confidence threshold. When outputting the confidence information, the target circumscribed rectangle coordinate information and other information can be provided to the user in the form of pictures and texts, where the target (smoke or fire) can be clearly indicated by a highlighted frame in the picture for easy viewing by the user.

[0064] If the built-in confidence value is always less than or equal to the first confidence threshold value during the detection period, the judgment of the fusion strategy is released.

[0065] It should be understood that in some embodiments, the detection period (T s ) should be greater than or equal to the calculation period (t), and the interference of the target image data in the calculation period of the current moment on the judgment of the fusion strategy should be avoided. For example, if the calculation period is 30s, the detection period can be 30s, 40s, 60s, etc.

[0066] In the above judgment rules, the current thermal runaway characteristic value judged by the battery algorithm analysis module 21 is greater than the second thermal runaway threshold and the confidence value judged by the image analysis module 22 is greater than the second confidence threshold, which can ensure the independence of the battery analysis module and the image analysis module 22, and ensure effective monitoring and protection in the two scenarios of the vehicle BMS system transmitting invalid battery data or the vehicle being left idle for a long time after charging is completed and catching fire.

[0067] The strategy fusion module 23 can lower the data judgment threshold of the image analysis module 22 within a certain period of time according to the thermal runaway characteristic value output by the battery analysis module, and provide a backup for the missed reports of the battery analysis module. At the same time, it can improve the sensitivity of system detection without generating too many false alarms, ensuring that thermal runaway events can be recalled in the early stages.

[0068] Figure 2 A flow chart of a method for managing vehicle charging according to an embodiment of the present disclosure is shown. In some embodiments, the method may be implemented by a processing unit or a computing unit of a control system of a charging station or a control platform. For ease of understanding, the specific examples, numbers, or values ​​mentioned in the following description are merely exemplary and are not intended to limit the scope of protection of the present disclosure. It should be understood that the steps indicated by the following boxes (such as box 201 and box 202) may not be strictly executed in the order shown in the figure. For example, the steps indicated by box 201 and box 202 may be executed simultaneously, or the steps indicated by box 202 may be executed first, and then the steps indicated by box 201 may be executed.

[0069] like Figure 2 As shown, in box 201, during the charging of the vehicle, the processing unit determines the current thermal runaway characteristic value related to the state information of the battery being charged of the vehicle, and the state information of the battery being charged includes at least the temperature of the battery being charged. In box 202, the processing unit also determines the confidence target information related to the vehicle based on the target image data about the vehicle collected from the image collection module, and the confidence target information includes at least the confidence value.

[0070] Next, in block 203, the processing unit compares the multiple confidence values ​​in the detection period with the first confidence threshold in response to determining that the current thermal runaway characteristic value is in the fusion interval. Finally, in block 204, the processing unit outputs the target image data and the confidence target information via the output unit in response to determining that at least some of the confidence values ​​in the multiple confidence values ​​in the detection period are respectively greater than the first confidence threshold.

[0071] In some embodiments, the processing unit may further output at least the battery jump temperature via the output unit in response to determining that the current thermal runaway characteristic value is greater than the maximum value of the fusion interval.

[0072] In some embodiments, the processing unit may also output the target image data and the confidence target information via the output unit in response to determining that the confidence is greater than a second confidence threshold, and the second confidence threshold is greater than the first confidence threshold.

[0073] In some embodiments, the processing unit may also compare the confidence value after the detection cycle with a second confidence threshold in response to determining that the current thermal runaway characteristic value is in a fusion interval and determining that all confidence values ​​within the detection cycle are not greater than a first confidence threshold, and the second confidence threshold is greater than the first confidence threshold.

[0074] In some embodiments, the processing unit may acquire target image data from an image acquisition module associated with a charging pile for charging the vehicle among multiple image acquisition modules.

[0075] In some embodiments, the processing unit may further associate the charging pile in the field of view of each of the multiple image acquisition modules with the corresponding image acquisition module.

[0076] In some embodiments, the processing unit may also determine the current thermal runaway characteristic value based at least on the temperature rise rate of the charged battery and the current battery temperature.

[0077] In some embodiments, the processing unit may also determine the battery jump temperature based on the current battery temperature of the charged battery and the average temperature of the battery in the calculation cycle where the current battery temperature belongs.

[0078] In some embodiments, the confidence target information is determined based on a smoke and fire detection model constructed by a deep learning network.

[0079] Figure 3 A schematic block diagram of an electronic device 300 suitable for implementing an embodiment of the present disclosure is shown. The electronic device 300 may be a server or a processing unit of the charging pile itself or other appropriate device mentioned above that communicates with the charging pile. As shown in the figure, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 302 or computer program instructions loaded from a storage unit to a random access memory (RAM) 303. In RAM 303, various programs and data required for device operation can also be stored. CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0080] A number of components in the device are connected to the I / O interface 305, including: an input unit 306, such as a touch screen, buttons, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0081] The various processes and processing described above, such as the processes mentioned above, can be performed by the processing unit 301. For example, in some embodiments, the processes 201, 202, 203 and 204 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed on the device via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the CPU 301, one or more actions of the processes 203 and 204 described above can be performed.

[0082] Embodiments of the present disclosure relate to methods, electronic devices, and / or computer program products. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present disclosure.

[0083] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, (but not limited to) an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0084] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0085] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0086] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0087] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0088] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0089] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0090] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for managing vehicle charging, comprising: During charging of the vehicle, determining a current thermal runaway characteristic value associated with state information of a charged battery of the vehicle, the state information of the charged battery including at least a temperature of the charged battery; Determining confidence target information related to the vehicle according to target image data about the vehicle acquired from an image acquisition module, wherein the confidence target information at least includes a confidence value; In response to determining that the current thermal runaway characteristic value is in a fusion interval, comparing the plurality of confidence values ​​within a detection period with a first confidence threshold respectively; as well as In response to determining that at least some of the confidence values ​​of the plurality of confidence values ​​within the detection period are respectively greater than the first confidence threshold, the target image data and the confidence target information are output via an output unit. 2 . The method according to claim 1 , wherein the confidence target information further includes at least one of target type and target circumscribed rectangle coordinate information.

3. The method according to claim 1, further comprising: In response to determining that the current thermal runaway characteristic value is greater than the maximum value of the fusion interval, at least the battery jump temperature is output via the output unit.

4. The method according to any one of claims 1 to 3, further comprising: In response to determining that the confidence is greater than a second confidence threshold, the target image data and the confidence target information are output via the output unit, and the second confidence threshold is greater than the first confidence threshold.

5. The method according to any one of claims 1 to 3, further comprising: In response to determining that the current thermal runaway characteristic value is in the fusion interval and determining that all the confidence values ​​within the detection cycle are not greater than the first confidence threshold, the confidence value after the detection cycle is compared with a second confidence threshold, and the second confidence threshold is greater than the first confidence threshold.

6. The method according to any one of claims 1 to 3, further comprising: The target image data is acquired from an image acquisition module (12) associated with a charging post for charging the vehicle among a plurality of image acquisition modules (12).

7. The method according to claim 6, further comprising: The charging pile in the field of view of each image acquisition module (12) among the plurality of image acquisition modules (12) is associated with the corresponding image acquisition module (12).

8. The method according to any one of claims 1 to 3 and 7, further comprising: The current thermal runaway characteristic value is determined based at least on the temperature rise rate of the charged battery and the current battery temperature.

9. The method according to claim 3, further comprising: The battery jump temperature is determined based on the current battery temperature of the charged battery and the average temperature of the battery in a calculation period where the current battery temperature belongs.

10. The method according to any one of claims 1-3, 7 and 9, wherein the confidence target information is determined according to a smoke and fire detection model constructed by a deep learning network.

11. An electronic device, comprising: at least one processing unit; as well as At least one memory coupled to the at least one processing unit and storing machine executable instructions, when the instructions are executed by the at least one processing unit, the electronic device performs actions, the actions comprising: During charging of the vehicle, determining a current thermal runaway characteristic value associated with state information of a charged battery of the vehicle, the state information of the charged battery including at least a temperature of the charged battery; Determining confidence target information related to the vehicle according to target image data about the vehicle acquired from an image acquisition module, wherein the confidence target information at least includes a confidence value; In response to determining that the current thermal runaway characteristic value is in a fusion interval, comparing the plurality of confidence values ​​within a detection period with a first confidence threshold respectively; and In response to determining that at least some of the confidence values ​​of the plurality of confidence values ​​within the detection period are respectively greater than the first confidence threshold, the target image data and the confidence target information are output via an output unit. 12 . The electronic device according to claim 11 , wherein the confidence target information further comprises at least one of target category and target circumscribed rectangle coordinate information.

13. The electronic device according to claim 11, wherein the actions further comprise: In response to determining that the current thermal runaway characteristic value is greater than the maximum value of the fusion interval, at least the battery jump temperature is output via the output unit.

14. The electronic device according to any one of claims 11 to 13, wherein the action further comprises: In response to determining that the confidence is greater than a second confidence threshold, the target image data and the confidence target information are output via the output unit, and the second confidence threshold is greater than the first confidence threshold.

15. The electronic device according to any one of claims 11 to 13, wherein the action further comprises: In response to determining that the current thermal runaway characteristic value is in the fusion interval and determining that all the confidence values ​​within the detection cycle are not greater than the first confidence threshold, the confidence value after the detection cycle is compared with a second confidence threshold, and the second confidence threshold is greater than the first confidence threshold.

16. The electronic device according to any one of claims 11 to 13, wherein the action further comprises: The target image data is acquired from an image acquisition module (12) associated with a charging post for charging the vehicle among a plurality of image acquisition modules (12).

17. The electronic device according to any one of claims 16, wherein the actions further comprise: The charging pile in the field of view of each image acquisition module (12) among the plurality of image acquisition modules (12) is associated with the corresponding image acquisition module (12).

18. The electronic device according to any one of claims 11-13 and 17, wherein the actions further comprise: The current thermal runaway characteristic value is determined based at least on the temperature rise rate of the charged battery and the current battery temperature.

19. The electronic device of claim 13, wherein the actions further comprise: The battery jump temperature is determined based on the current battery temperature of the charged battery and the average temperature of the battery in a calculation period where the current battery temperature belongs.

20. The electronic device according to any one of claims 11-13, 17 and 19, wherein the confidence target information is determined according to a smoke and fire detection model constructed by a deep learning network.

21. A computer storage medium comprising a computer program product stored thereon, the computer program product comprising machine executable instructions which, when executed, cause a machine to perform the steps of the method according to any one of claims 1 to 10.

Images