A safety monitoring method and system for a two-wheeled electric vehicle battery swap station
By implementing multi-dimensional monitoring and real-time risk management, the problem of monitoring blind spots during the plugging and unplugging transient process of two-wheeled electric vehicle battery swapping stations has been solved. This enables accurate identification and real-time interception of electrical anomalies and physical hazards, thereby improving the safety and reliability of the battery swapping process.
Patent Information
- Application Number
- CN202610373424.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-25
- Publication Date
- 2026-06-12
Smart Images
Figure CN122193761A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of battery swapping safety technology for two-wheeled electric vehicles, specifically involving a safety monitoring method, system, and computer storage medium for battery swapping stations for two-wheeled electric vehicles. It is particularly suitable for monitoring high-risk blind spots during the transient insertion and removal of terminals during the battery swapping process, achieving specialized and precise monitoring, rapid risk interception, and rigid safety protection in this stage. Background Technology
[0002] In recent years, battery swapping for two-wheeled electric vehicles has become widely adopted in short-distance travel due to its advantages of quick swapping and efficient energy replenishment. The safe and stable operation of battery swapping stations is directly related to the safety of users' lives and property, as well as the public environment. Industry practice has verified that the transient insertion and removal of the battery and the swapping compartment terminals during the swapping process is the highest-risk core node in the entire process. This stage is highly susceptible to transient electrical anomalies that can cause terminal sparking and short circuits, and in severe cases, trigger major safety accidents such as battery thermal runaway and explosions, posing significant safety hazards. Currently, most mainstream safety monitoring solutions for two-wheeled electric vehicle battery swapping stations only monitor conventional parameters such as battery steady-state voltage, steady-state current, and the temperature and humidity of the swapping compartment environment. They have significant technical shortcomings in monitoring this high-risk blind spot of insertion and removal transients, making it difficult to meet actual safety management needs. This severely restricts the standardized and safe development of the two-wheeled electric vehicle battery swapping industry. Therefore, there is an urgent need in this field for a safety monitoring solution specifically designed for the high-risk blind spot of insertion and removal transients, with accurate detection, rapid response, and robust handling, to address the pain points of existing technologies. Summary of the Invention
[0003] This invention aims to overcome the defects and deficiencies of existing technologies and provide a safety monitoring method and system for the battery swapping process of two-wheeled electric vehicles. It focuses on the blind spot of the highest risk in the entire battery swapping process, namely the transient monitoring of plugging and unplugging, to carry out special detection. It realizes real-time acquisition, rapid judgment and rigid locking of transient risks of plugging and unplugging, intercepts high-risk electrical hazards from the source, and maximizes the safety and reliability of the battery swapping process of two-wheeled electric vehicles.
[0004] The technical solution adopted in this invention is as follows: In a first aspect, the present invention provides a safety monitoring method for a two-wheeled electric vehicle battery swapping station. A safety monitoring method for a two-wheeled electric vehicle battery swapping station includes the following steps: Step 1, Baseline Calibration: The no-load electrical parameters of the battery swapping station pole docking position are collected by the high-frequency monitoring module to establish the transient electrical safety threshold and arc reference signal adapted to the on-site working conditions. The influence of various interference factors such as electromagnetic and equipment interference on the battery swapping station is eliminated. After the calibration process is completed, the system automatically triggers the subsequent steps. There is no manual intervention or delay throughout the entire process. Step 2, High-frequency acquisition: Control the battery swapping robotic arm to perform the pre-connection action of the pole, and simultaneously start the real-time high-frequency acquisition of multi-dimensional data. At the microsecond sampling frequency, acquire three types of core data: transient current and voltage during pole insertion and removal, dangerous arc signal, and conductive foreign objects at the pole position, to provide accurate data support for risk assessment. Step 3, Risk Assessment: Based on the collected real-time multi-dimensional data, the safety risk assessment of the insertion and removal transient is completed. If all three types of data meet the preset safety standards, the insertion and removal transient detection is deemed qualified, and the battery swapping formal docking operation is unlocked. If any type of data is abnormal, the insertion and removal transient detection is deemed unqualified. The abnormality type is assessed according to the preset rules for level 1, level 2, and level 3 risk classification, and the corresponding risk elimination strategy is matched. Step 4, Risk Management and Interlocking: If the risk elimination operation is completed and all verification and testing data are qualified, the system abnormal warning is lifted and subsequent battery swapping operations continue; if the risk cannot be eliminated or the verification and testing results are still unqualified, the system immediately triggers the interlocking command, refuses to execute all subsequent battery swapping actions, and simultaneously generates the corresponding type of precise abnormal alarm information to achieve rigid interception of the risk.
[0005] Furthermore, the no-load electrical parameters in step 1 include no-load reference voltage and no-load reference current. During the acquisition process, electromagnetic interference data and equipment static error data from the normal operating environment of the battery swapping station are combined to ensure that the calibrated safety threshold and the arc reference signal are adapted to the actual working conditions on site.
[0006] Furthermore, the specific process for determining the graded risk in step 3 includes: Step 3.1, Level 1 Risk Assessment: If a continuous arcing or open flame-like dangerous arc is detected at the pole, it is determined to be a Level 1 high-risk electrical fault caused by poor pole contact or insulation damage. This type of risk involves hardware failure or persistent hidden dangers, and there are no effective automated handling methods. Forced handling may easily cause short circuits or deflagration accidents. The system immediately triggers an interlocking and blocking command, refuses to execute all subsequent battery swapping actions, and simultaneously generates corresponding precise abnormal alarm information. If this type of risk is not detected, proceed to the Level 2 Risk Assessment step. Step 3.2, Level 2 Risk Assessment: Image information is collected from the electrode post area. If foreign objects are detected around the electrode post, it is assessed as a Level 2 risk. The type of foreign object is further identified using image recognition technology. If the foreign object is a stubborn conductive foreign object such as metal debris or solidified oil stains that cannot be removed by conventional purging or drying methods, this type of risk indicates a hardware hazard or persistent fault. The system immediately triggers an interlocking command, refusing to execute any subsequent battery swapping actions, and simultaneously generates a corresponding type of precise abnormal alarm information. If the foreign object is a easily cleanable foreign object such as dust or water stains, purging and drying operations are performed to eliminate the risk. After the operation is completed, a verification test is conducted. If all verification test data is qualified, the abnormal warning is lifted and the subsequent process continues. If the verification test fails, an interlocking command is immediately triggered, refusing to execute any subsequent battery swapping actions. If no foreign object is detected, the process proceeds to the Level 3 risk assessment step. Step 3.3, Level 3 Risk Assessment: Collect transient current and transient voltage data at the terminal end. If the values deviate from the preset standard range, it is judged as a Level 3 risk. The risk level is further refined based on the degree of exceedance and the duration of fluctuation. If the transient current / voltage exceeds the standard significantly and the fluctuation duration is >100ms, it is judged as a continuous electrical abnormality caused by a battery cell failure or a hidden short circuit in the circuit. This type of risk has hardware failure or stubborn hidden dangers and there is no effective automated elimination method. The system immediately triggers an interlocking lockout command and refuses to execute all subsequent battery swapping actions. If the transient current / voltage exceeds the standard slightly and the fluctuation duration is ≤100ms, it is judged as a temporary electrical fluctuation caused by environmental electromagnetic interference or instantaneous static electricity in the equipment. Perform transient parameter recalibration, restart the high-frequency acquisition unit, and filter out static electricity and electromagnetic interference. After standing still for 1 second, recheck the transient electrical parameters. If all the rechecked test data are qualified, the abnormality warning is lifted and the subsequent battery swapping process continues. If the recheck test is unqualified, the interlocking lockout command is immediately triggered and all subsequent battery swapping actions are refused.
[0007] The risk levels of Level 1, Level 2, and Level 3 risks decrease sequentially. Level 1 risk is the highest level of high risk, and interlocking is triggered immediately upon discovery. Levels 2 and 3 are medium-risk risks, and the specific type of risk needs to be further determined. Standardized handling strategies are implemented for risks that can be eliminated, while interlocking is triggered for risks that cannot be eliminated.
[0008] Furthermore, when risks cannot be eliminated, the abnormal alarm information uploaded by the system includes the type of abnormality, the time of occurrence, the battery swapping compartment number, and real-time abnormality monitoring data, which facilitates operation and maintenance personnel to accurately trace the source and quickly troubleshoot.
[0009] Furthermore, the real-time high-frequency acquisition in step 2 is at the microsecond level, with a sampling frequency of not less than 1MHz. During the acquisition process, a noise filtering algorithm is simultaneously activated to eliminate high-frequency noise interference caused by the operation of the battery swapping equipment and the surrounding electromagnetic environment, thereby ensuring the accuracy and effectiveness of transient data acquisition.
[0010] Furthermore, for risks that can be eliminated at levels two and three, two consecutive rounds of verification and testing are conducted after the risk elimination operation is performed. The system abnormality warning can only be lifted when the data from both rounds of testing meet the standards and there is no fluctuation deviation. If either round of verification and testing fails, the interlocking and locking command is directly triggered to avoid missed risk detection due to a single verification deviation.
[0011] Secondly, this invention provides a safety monitoring system for a two-wheeled electric vehicle battery swapping station. A safety monitoring system for a two-wheeled electric vehicle battery swapping station, used to execute the aforementioned safety monitoring method for a two-wheeled electric vehicle battery swapping station, includes a main control unit, a high-frequency monitoring module, a transient high-frequency monitoring module, an arc detection module, a foreign object identification module, an anomaly determination module, a strategy generation module, a risk elimination module, an interlocking module, and a cloud-based operation and maintenance module; the main control unit is electrically connected to each of the other modules, serving as the core of the system to coordinate and manage the entire process of detection timing, data processing, anomaly determination, and risk elimination operations.
[0012] Furthermore, the specific functions of each module are as follows: High-frequency monitoring module: used to collect no-load electrical parameters such as no-load reference voltage and no-load reference current at the pole docking position of the battery swapping station. Combined with electromagnetic interference and equipment static error data at the battery swapping station, it completes transient electrical safety threshold calibration and arc reference signal establishment, eliminates environmental and equipment interference, and provides accurate data reference for subsequent transient monitoring. Transient high-frequency monitoring module: It is used to automatically start after the benchmark calibration process is completed. In conjunction with the pre-connection action of the pole of the battery swapping robotic arm, it collects transient current and transient voltage data of the pole connection position in real time at a microsecond sampling frequency, and transmits them synchronously to the main control unit and the anomaly judgment module, providing core data support for electrical anomaly judgment. Arc detection module: Used to monitor arc signals in real time during pole docking and insertion / removal. It uses signal recognition algorithms to identify real dangerous arcs such as continuous arcing and open flames, accurately distinguishes between interference signals and dangerous arc signals, and transmits the detection results to the anomaly judgment module in real time to achieve accurate identification of high-risk arc risks. Foreign object identification module: used to acquire high-definition images and intelligently identify the pole and surrounding area, detect whether there are conductive foreign objects at the pole position, and identify the type of foreign object through image feature analysis, accurately distinguish between stubborn conductive foreign objects and easy-to-clean foreign objects, and transmit the identification results to the anomaly judgment module in real time. Anomaly Detection Module: This module receives real-time data transmitted from each monitoring module, completes the qualification judgment of the insertion and removal transient detection according to the preset safety standards and classification judgment rules, performs first-level, second-level and third-level risk classification judgment for abnormal data, clarifies the risk type, risk level and fault cause, and transmits the judgment results to the strategy generation module. Strategy generation module: Based on the risk classification results output by the anomaly judgment module, it matches the corresponding risk handling strategy, generates standardized elimination instructions for eliminateable risks, and generates interlocking and precise alarm instructions for non-eliminable risks, and transmits them synchronously to the corresponding execution module. Risk elimination module: Used to receive elimination instructions from the strategy generation module. For risks that can be eliminated, such as floating dust, water stains, and temporary electrical fluctuations, it performs corresponding disposal operations such as purging and drying, parameter recalibration, electrostatic filtration, and restarting of the acquisition unit. After the operation is completed, it automatically triggers the verification and testing process. Interlocking module: Used to receive the interlocking command issued by the strategy generation module, immediately cut off the docking power of the battery swapping robotic arm, lock all battery swapping actuators, refuse all subsequent battery swapping actions, and trigger local audible and visual alarms to prevent the risk from escalating and causing safety accidents. The cloud-based operation and maintenance module is used to receive abnormal alarm information and risk handling data generated by the system, integrate information such as abnormality type, occurrence time, battery swapping station number, real-time abnormal data, and risk elimination results, and realize cloud storage, remote push and visualization of data to help operation and maintenance personnel remotely monitor and accurately troubleshoot, thereby improving the operation and maintenance efficiency of battery swapping stations.
[0013] Furthermore, the main control unit has built-in timing linkage logic, which can realize the synchronous start and stop of the high-frequency monitoring module, the transient high-frequency monitoring module, the arc detection module, and the foreign object identification module, and the synchronous data acquisition, ensuring the timing consistency of multi-dimensional monitoring data, avoiding misjudgments caused by data misalignment, and improving the accuracy of risk assessment.
[0014] Thirdly, the present invention provides a computer storage medium. A computer storage medium storing an executable program, wherein when the executable program is executed by a processor, it implements any of the above-described safety monitoring methods for two-wheeled electric vehicle battery swapping stations.
[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. Highly targeted monitoring, accurately covering high-risk blind spots: This invention abandons conventional redundant monitoring schemes and focuses only on the core high-risk link of battery swapping and plugging / unplugging transients. It builds a multi-dimensional monitoring system of "electrical parameters + arc signals + conductive foreign objects", simultaneously collecting three types of core data, taking into account both electrical anomalies and physical hazards, and completely solving the problems of single monitoring dimensions and high false negative rate of existing technologies, achieving full capture of plugging / unplugging transient hazards; 2. Excellent monitoring accuracy and extremely fast response with no delay: It adopts a microsecond-level high-frequency acquisition mode with a sampling frequency of no less than 1MHz. Combined with noise filtering algorithms, it effectively eliminates on-site interference and can accurately capture transient and subtle anomalies. The benchmark calibration process is fully automated, with no manual intervention or delay. The monitoring process starts synchronously with the calibration process, and data acquisition and risk assessment are carried out in parallel. The response speed is fast and the delay in handling hidden dangers is eliminated. 3. Risk classification and control, rigid and safer handling: The innovative approach classifies the transient risks of plugging and unplugging into three levels, and formulates differentiated handling strategies for different risk levels and different types of hidden dangers. Eliminable hidden dangers can be automatically handled through standardized operations, while hidden dangers that cannot be eliminated will immediately trigger interlocking and blocking commands to rigidly intercept the battery swapping action, thereby eliminating accidents such as short circuits, sparks, and explosions caused by forced docking from the source, and making safety protection more thorough. 4. Convenient operation and maintenance traceability, and higher management efficiency: The abnormal alarm information generated by the system is accurate and detailed, covering core contents such as abnormality type, occurrence time, warehouse number, and real-time monitoring data. It is also uploaded to the cloud operation and maintenance module at the same time, realizing one-click traceability and visualization of abnormal information. This makes it easier for operation and maintenance personnel to quickly locate faults and accurately investigate potential problems, greatly reducing the operation and maintenance difficulty of the battery swapping station and helping the battery swapping station to operate safely and efficiently. Attached Figure Description
[0016] The present invention will be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating the safety monitoring method for two-wheeled electric vehicle battery swapping stations according to the present invention. Figure 2 This is a schematic diagram of the architecture of the two-wheeled electric vehicle battery swapping station safety monitoring system of the present invention. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0018] It should be noted that the terms "first-level risk", "second-level risk", "third-level risk", "interlocking", etc. in the specification, claims and drawings of this invention are only used to describe specific embodiments and are not intended to limit the scope of protection of this invention.
[0019] This invention addresses the technical pain points of existing safety monitoring technologies for two-wheeled electric vehicle battery swapping stations, namely the lack of monitoring, insufficient data acquisition accuracy, and delayed risk handling during the high-risk transient process of pole insertion and removal. It designs a multi-dimensional, high-frequency, and hierarchical safety monitoring solution specifically for this transient process. Its core innovation lies in focusing on the highest-risk pole insertion and removal transient process in the entire battery swapping process. Through a full-process design including no-load benchmark calibration, microsecond-level multi-dimensional data acquisition, hierarchical risk assessment, differentiated handling, and rigid interlocking, it achieves accurate capture, rapid assessment, and source interception of transient risks. This technically solves the problems of existing monitoring solutions, such as single-dimensionality monitoring, high false negative rates, slow response, and weak protection. The following detailed embodiments illustrate the technical solution of this invention. These embodiments are only for illustrative purposes and are not intended to limit the scope of protection of this invention.
[0020] Currently, mainstream safety monitoring solutions for battery swapping stations on the market primarily focus on monitoring battery steady-state operating parameters and swapping compartment environmental parameters. These solutions can only achieve routine data collection at the second level or even lower frequencies. They have significant technical shortcomings in monitoring the critical high-risk blind spot of terminal insertion and removal during the swapping process, which has become a key issue restricting the safe development of the battery swapping industry. Specifically, this manifests in three aspects: First, the low acquisition frequency of conventional monitoring equipment makes it impossible to capture microsecond-level transient overcurrent, transient overvoltage, and weak arc signals. These transient electrical anomalies are direct causes of terminal sparking and short circuits. If not identified in time, they can easily lead to subsequent battery thermal runaway, explosions, etc. First, existing solutions lack specific detection units for conductive foreign objects at the electrode docking points. Conductive foreign objects such as metal shavings, water stains, mud, and solidified oil easily adhere to the electrode contact surface, increasing the probability of transient electrical faults. Furthermore, existing equipment lacks automated foreign object cleaning and identification capabilities, failing to proactively identify physical hazards. Second, current technologies lack robust and immediate interlocking mechanisms for handling anomalies. Even when minor transient anomalies are detected, there are issues of delayed response and ineffective interception. Some solutions only provide risk warnings through alarm prompts, lacking the function of automatically locking the battery swapping actuator, thus failing to prevent the spread of risks at the source, resulting in insufficient rigidity and effectiveness of safety protection. Based on these industry pain points, the safety monitoring method, system, and computer storage medium for two-wheeled electric vehicle battery swapping stations proposed in this invention can achieve specialized, accurate, and efficient monitoring of the insertion and removal transient process. It is adaptable to the equipment upgrades and new deployments of various mainstream two-wheeled electric vehicle battery swapping stations and has broad industry application prospects.
[0021] Example 1 This embodiment provides a safety monitoring method for a two-wheeled electric vehicle battery swapping station, such as... Figure 1As shown, this method upgrades the existing hardware architecture of the battery swapping station without requiring the addition of a large amount of core hardware. It can be achieved through software algorithm optimization and modular hardware adaptation, adapting to battery swapping scenarios for various two-wheeled electric vehicle batteries such as lead-acid and lithium batteries, and adapting to various battery swapping station deployment environments such as outdoor, indoor, and open-air charging piles. The specific steps include: Step 1, Baseline Calibration: The no-load electrical parameters of the battery swapping station pole docking position are collected by the high-frequency monitoring module, including no-load reference voltage and no-load reference current. Combined with data such as electromagnetic interference and equipment static error in the normal operating environment of the battery swapping station, the transient electrical safety threshold and arc reference signal adapted to the on-site working conditions are established to eliminate the influence of various interference factors on subsequent monitoring data. After calibration, the system automatically triggers the next step without manual intervention or delay. Step 2, High-frequency acquisition: Following the completion of the benchmark calibration, the main control unit sends a command to control the battery swapping robotic arm to perform the pre-docking action of the battery terminals. The pre-docking action of the battery terminals is a trial docking action before the formal docking of the battery swapping. The physical contact and electrical conduction of the battery terminals are not completed. The battery terminals and the battery swapping compartment terminals are only adjusted to the preset docking distance to avoid the expansion of risks caused by the formal docking.
[0022] While the pre-connection of the pole is being performed, the main control unit simultaneously initiates real-time high-frequency acquisition of multi-dimensional data. Through the coordinated work of the transient high-frequency monitoring module, the arc detection module, and the foreign object identification module, three core data types are acquired simultaneously at a microsecond-level sampling frequency: transient current and voltage during pole insertion and removal, dangerous arc signals, and conductive foreign objects at the pole position. The sampling frequency for microsecond-level acquisition is no less than 1MHz, and can be adjusted to higher frequencies such as 2MHz and 5MHz according to the safety level requirements of the battery swapping station to meet the monitoring needs of battery swapping scenarios with different risk levels.
[0023] During the data acquisition process, a noise filtering algorithm is activated simultaneously. Through a combination of digital filtering, adaptive filtering, and other algorithms, high-frequency noise interference caused by the operation of the battery swapping equipment, the surrounding electromagnetic environment, and vibrations in the field environment is filtered out, ensuring the accuracy and effectiveness of transient data acquisition. Furthermore, the acquisition of the three types of core data is carried out synchronously and sequentially to ensure the consistency of data timestamps and avoid misjudgments of risk assessment due to misalignment of data acquisition timing.
[0024] Step 3, Risk Assessment: The anomaly assessment module receives real-time multi-dimensional data transmitted from each monitoring module and performs a comprehensive assessment of the safety risks during plug-in / plug-out transients based on preset safety standards. If the transient current and voltage, dangerous arc signal, and conductive foreign object at the terminal position all meet the preset safety standards, the insertion and removal transient detection is deemed qualified. The main control unit sends a command to unlock the formal battery swapping docking operation, and the battery swapping robotic arm executes the subsequent formal terminal docking, battery replacement and other processes. If any type of data is abnormal, the insertion / removal transient detection is deemed unqualified, and all actions of the battery swapping robotic arm are immediately suspended. The anomaly determination module performs a level 1, level 2, or level 3 risk classification based on the anomaly type according to preset rules, and transmits the determination results to the strategy generation module, which then matches the corresponding risk elimination strategy.
[0025] The specific process for risk assessment is a progressive assessment; only after a risk at the next higher level is not detected will the assessment proceed to the next level. This process includes: Step 3.1, Level 1 Risk Assessment Level 1 risk is the highest level of high-risk electrical fault risk, with no effective automated handling means; once detected, interlocking is triggered.
[0026] If the arc detection module detects a continuous arc or open flame-like dangerous arc on the battery terminal, and the duration of the arc signal exceeds a preset threshold (e.g., 5ms, 10ms), it can be identified as a Level 1 high-risk electrical fault caused by poor terminal contact, insulation damage, or battery terminal deformation. Such risks involve hardware failures or persistent hidden dangers. Forcibly performing a battery swapping operation can easily lead to major safety accidents such as short circuits, deflagration, and battery thermal runaway. There are no effective automated handling methods. The system will immediately trigger an interlocking command to prohibit all subsequent battery swapping actions and simultaneously generate corresponding precise abnormal alarm information. The alarm information should at least include the abnormality type, occurrence time, battery swapping compartment number, and real-time abnormality monitoring data.
[0027] If no continuous arcing or open flame-like real dangerous arc is detected, or only a momentary interfering arc signal (not a real dangerous arc) is detected, then proceed to the secondary risk assessment step.
[0028] Step 3.2, Secondary Risk Assessment Level 2 risk is a medium-risk physical hazard, requiring identification of the type of foreign object and differentiation between eliminable and non-eliminable hazards.
[0029] The foreign object detection module acquires high-definition images of the pole and surrounding area. Image recognition and feature extraction algorithms are used to analyze the acquired images. If foreign objects are detected around the pole or on the contact surface, it is classified as a level two risk. Further image feature matching algorithms are used to identify the type of foreign object, distinguishing between stubborn conductive foreign objects and easily cleanable foreign objects. If the foreign objects are stubborn conductive foreign objects such as metal shavings, solidified oil stains, metal wires, or welding slag, these foreign objects cannot be removed by conventional purging or drying methods. They pose hardware hazards or stubborn faults. Forced disposal may cause risks such as poor contact of the poles or short circuits. The system will immediately trigger an interlocking and locking command to prohibit all subsequent battery swapping actions and generate corresponding precise abnormal alarm information at the same time. If the foreign objects are easily cleaned, such as floating dust, water stains, ordinary dust, or light flocculent matter, and these foreign objects have no hardware damage or persistent malfunctions, the strategy generation module will issue instructions to control the risk elimination module to perform purging and drying operations to eliminate the risks. The purging operation can be carried out by high-pressure gas purging, negative pressure adsorption, etc., and the drying operation can be carried out by hot air drying, room temperature air drying, etc. After the operation is completed, the verification and testing process will be automatically triggered. If no foreign objects are detected around the pole, proceed to the Level 3 risk assessment step.
[0030] Step 3.3, Level 3 Risk Assessment Level 3 risk refers to low-risk electrical parameter abnormality risk. The risk level needs to be refined according to the degree of exceeding the standard and the duration of fluctuation, and to distinguish between continuous electrical abnormalities and temporary electrical fluctuations.
[0031] The transient current and transient voltage data at the terminal of the electrode are collected by the transient high-frequency monitoring module. If the values deviate from the transient electrical safety threshold range established in step 1, it is judged as a level three risk. The risk level is further refined according to the degree of exceeding the standard (e.g., exceeding the standard by 10%, 20%, 50%) and the duration of fluctuation. If the transient current / voltage exceeds the standard significantly (the excess ratio can be preset, such as ≥30%) and the fluctuation duration is >100ms, it can be determined as a continuous electrical abnormality caused by internal battery cell failure, hidden short circuit in the circuit, battery protection board failure, etc. Such risks have hardware failures or stubborn hidden dangers, and there are no effective automated elimination methods. The system immediately triggers the interlocking and locking command to prohibit the execution of all subsequent battery swapping actions and simultaneously generates the corresponding type of accurate abnormal alarm information. If the transient current / voltage slightly exceeds the standard (the excess ratio can be preset, such as <30%) and the fluctuation duration is ≤100ms, it can be determined as a temporary electrical fluctuation caused by environmental electromagnetic interference, instantaneous static electricity of equipment, on-site voltage fluctuation, etc. Such anomalies are risks that can be eliminated. The strategy generation module issues an instruction to control the risk elimination module to perform transient parameter recalibration, restart the high-frequency acquisition unit, and filter out static electricity and electromagnetic interference. After the operation is completed, let it stand still for 1 second (the standing time can be adjusted according to the actual working conditions) and then check the transient electrical parameters again. If the transient current / voltage data does not deviate from the preset safety standard range, the plug-in / plug-out transient detection is deemed qualified, and the battery swapping formal docking operation is unlocked.
[0032] This step is the execution phase after risk assessment. Differentiated operations are performed based on the risk type and the outcome of the handling. The core principle is that risks that can be eliminated continue the process after verification and approval, while risks that cannot be eliminated are immediately and rigidly locked down. For risks that can be eliminated at levels two and three, after the risk elimination operation is performed, each monitoring module conducts two consecutive rounds of verification tests. The time interval between the two rounds of tests can be preset (e.g., 50ms, 100ms). Only when the data from both rounds of verification tests meet the standards and there is no fluctuation deviation (the fluctuation deviation can be preset, e.g., ≤±5%), can the main control unit issue a command to remove the system abnormality warning and continue to execute the subsequent battery swapping operation. If any round of verification tests fails, an interlocking lockout command is directly triggered, prohibiting the execution of all subsequent battery swapping actions. For risks that cannot be eliminated, such as Level 1 and Level 2 non-eliminable and Level 3 persistent electrical anomalies, the system immediately triggers an interlocking command. The interlocking module cuts off the docking power of the battery swapping robotic arm and locks all battery swapping actuators (including the robotic arm, battery compartment door, and terminal docking mechanism), prohibiting the execution of all subsequent battery swapping actions. At the same time, it generates corresponding accurate anomaly alarm information and uploads the alarm information to the local alarm terminal and the cloud operation and maintenance module to achieve dual early warning of local audible and visual alarms and remote alarms. When risks cannot be eliminated, the abnormal alarm information uploaded by the system must include core information such as the type of abnormality, the time of occurrence, the battery swapping compartment number, real-time abnormality monitoring data, and risk assessment process data, so as to facilitate operation and maintenance personnel to accurately trace the source and quickly troubleshoot.
[0033] In this embodiment, all preset thresholds (such as sampling frequency, arc duration, current and voltage exceedance ratio, fluctuation duration, and verification detection interval) can be flexibly adjusted according to the safety level of the battery swapping station, battery type, and deployment environment without modifying the core algorithm architecture, thus adapting to the personalized needs of various two-wheeled electric vehicle battery swapping scenarios.
[0034] Example 2 This embodiment provides a safety monitoring system for a two-wheeled electric vehicle battery swapping station, used to execute the safety monitoring method for a two-wheeled electric vehicle battery swapping station described in Embodiment 1. This system features a modular architecture design, allowing seamless integration with the main control system of existing battery swapping stations. It supports modular disassembly, upgrades, and maintenance, and is compatible with various mainstream battery swapping station hardware platforms, such as... Figure 2 As shown, the system includes a main control unit, a high-frequency monitoring module, a transient high-frequency monitoring module, an arc detection module, a foreign object identification module, an anomaly determination module, a strategy generation module, a risk elimination module, an interlocking module, and a cloud-based operation and maintenance module. The main control unit is electrically connected to each of the other modules and serves as the core of the system to coordinate and manage the entire process of detection timing, data processing, anomaly determination, and risk elimination. The modules cooperate with each other and communicate data to achieve full automation and intelligence of the entire process of plug-in transient monitoring.
[0035] The specific functions of each module are as follows, and each module can be implemented using conventional hardware in this field, without any special hardware limitations: The main control unit is the core control module of the system. It can be equipped with hardware such as PLC, microcontroller, or industrial control computer. It has built-in timing linkage logic algorithm and data interaction protocol, which can realize the synchronous start and stop, synchronous data acquisition and timing calibration of high-frequency monitoring module, transient high-frequency monitoring module, arc detection module and foreign object identification module, ensuring the timing consistency of multi-dimensional monitoring data and avoiding misjudgment due to data misalignment. At the same time, it is responsible for the instruction transmission, data interaction and process control between modules, receiving the transmitted data from each module, issuing various control instructions, and coordinating the monitoring, judgment and handling operations of the whole process. The program can be upgraded and the parameters adjusted according to the operation requirements of the battery swapping station.
[0036] The high-frequency monitoring module can use hardware carriers such as voltage sensors, current sensors, and electromagnetic interference detectors to collect no-load electrical parameters such as no-load reference voltage and no-load reference current at the battery swapping station pole docking point. At the same time, it collects interference data such as electromagnetic interference, equipment static error, and ambient temperature and humidity at the battery swapping station site. Through data fusion and algorithm compensation, it completes transient electrical safety threshold calibration and establishes arc reference signal, eliminating environmental and equipment interference and providing accurate data reference for subsequent transient monitoring. This module can realize timed automatic acquisition and triggered acquisition to adapt to different calibration requirements.
[0037] The transient high-frequency monitoring module can employ hardware carriers such as high-speed current sensors, high-speed voltage sensors, and data acquisition cards. Its sampling frequency is no less than 1MHz and supports frequency adjustment. It is triggered by the main control unit after the benchmark calibration process is completed. In conjunction with the pre-connection action of the battery swapping robotic arm, it collects transient current and transient voltage data at the electrode connection point in real time at a microsecond-level sampling frequency. The data is synchronously transmitted to the main control unit and the anomaly judgment module through a high-speed data transmission protocol, providing core data support for electrical anomaly judgment. The module has a built-in noise filtering algorithm that can filter out high-frequency noise interference in real time to ensure data acquisition accuracy.
[0038] The arc detection module can employ hardware such as arc sensors, photoelectric sensors, and signal acquisition and analysis instruments to monitor arc signals during pole docking and insertion / removal in real time. Through signal recognition and feature matching algorithms, it can distinguish between continuous arcing and real dangerous arcs such as open flames, accurately differentiate between interference signals (such as false arc signals generated by electromagnetic interference) and dangerous arc signals, and transmit the detection results (including arc signal type, duration, intensity, etc.) to the anomaly judgment module in real time to achieve accurate identification of high-risk arc risks. The detection sensitivity of this module can be adjusted according to the safety level requirements of the battery swapping station.
[0039] The foreign object identification module can use hardware carriers such as high-definition industrial cameras, vision sensors, and image recognition processors to perform high-definition image acquisition and intelligent identification of the pole and surrounding area. The resolution of the acquired images is no less than the preset standard to ensure that the features of foreign objects are clearly identifiable. At the same time, it detects whether there are conductive foreign objects at the pole position through image feature analysis and pattern matching algorithms, identifies the type of foreign object, accurately distinguishes between stubborn conductive foreign objects and easily cleanable foreign objects, and transmits the identification results (including whether the foreign object exists, the type of foreign object, and the location of the foreign object) to the anomaly judgment module in real time. This module supports image acquisition and identification in various environments such as backlight, strong light, and weak light, and is suitable for the complex environment of outdoor battery swapping stations.
[0040] The anomaly detection module can be implemented using hardware such as embedded processors or industrial control computers. It has a built-in preset safety standard database and hierarchical judgment rule algorithm. It receives real-time data transmitted from each monitoring module and performs a pass / fail judgment on the insertion and removal transient detection based on the preset safety standards and hierarchical judgment rules. It conducts level 1, level 2, and level 3 risk classification judgments on the abnormal data, clarifies the risk type, risk level, and cause of failure, and transmits the judgment results to the strategy generation module in real time. This module can realize real-time analysis and rapid judgment of abnormal data, with a judgment response time of no more than microseconds, ensuring the timeliness of risk judgment.
[0041] The strategy generation module can be implemented using hardware such as microcontrollers or embedded processors. It has a built-in risk management strategy database and automatically matches the corresponding risk management strategy based on the risk classification results, risk type, and fault cause output by the anomaly judgment module. For risks that can be eliminated, it generates standardized elimination instructions, which include the management operation type, execution parameters, and review and testing requirements. For risks that cannot be eliminated, it generates interlocking and precise alarm instructions and transmits all kinds of instructions synchronously to the corresponding execution modules through the main control unit. This module supports the updating and expansion of the strategy database and can add corresponding management strategies according to new risk types.
[0042] The risk elimination module is an execution module that can use hardware carriers such as high-pressure purging devices, hot air drying devices, electrostatic eliminators, and data calibration units. It receives elimination instructions from the strategy generation module and performs corresponding handling operations such as purging and drying, parameter recalibration, electrostatic filtration, and data acquisition unit restart for risks that can be eliminated, such as floating dust, water stains, and temporary electrical fluctuations. After the operation is completed, it automatically sends a signal to the main control unit to trigger the verification and detection process, realizing the automated handling of risks that can be eliminated.
[0043] The interlocking module is an execution module that can use hardware carriers such as relays, solenoid valves, and motor drivers. It receives interlocking commands from the strategy generation module, immediately cuts off the docking power of the battery swapping robotic arm, and locks all battery swapping actuators (including the robotic arm, battery compartment door, and terminal docking mechanism), prohibiting all subsequent battery swapping actions. At the same time, it triggers local audible and visual alarm devices (such as buzzers and warning lights) to achieve local risk warning and prevent the risk from escalating and causing safety accidents. This module is a hard interlocking module. Once the command is triggered, there is no manual unlocking authority. It can only be unlocked by maintenance personnel with dedicated permissions after troubleshooting, ensuring the rigidity and effectiveness of the interlocking.
[0044] The cloud-based operation and maintenance module can utilize hardware and software carriers such as cloud servers, cloud computing platforms, and IoT platforms. It connects to the local system via wireless communication protocols (such as 4G, 5G, WiFi, and Bluetooth) to receive abnormal alarm information and risk handling data generated by the system. It integrates information such as abnormality type, occurrence time, battery swapping station number, real-time abnormal data, risk assessment process, and risk elimination results, enabling cloud storage, remote push, and visualization of the data. Operation and maintenance personnel can remotely view the monitoring data, abnormal information, and handling results of the battery swapping station via computers, mobile phones, tablets, and other terminals, achieving remote supervision and precise troubleshooting, thus improving the operation and maintenance efficiency and intelligence level of the battery swapping station. This module supports centralized management and control of multiple battery swapping stations, enabling statistical analysis of abnormal data and fault pattern mining, providing data support for the daily maintenance and safety optimization of the battery swapping station.
[0045] In this embodiment, the electrical connection between the modules can be a wired connection (such as Ethernet, CAN bus, RS485 bus) or a wireless connection (such as 4G, 5G, WiFi), which can be flexibly selected according to the deployment environment and hardware architecture of the battery swapping station. Each module has a fault self-diagnosis function. If a module fails, it can send a fault signal to the main control unit in real time to realize timely early warning of module failure and ensure the reliability of system operation.
[0046] Example 3 This embodiment provides a computer storage medium, which is a non-volatile computer-readable storage medium, including but not limited to USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), solid-state drives (SSD), optical discs, etc., which stores an executable program. The executable program is a computer program. When the computer program is executed by a processor (such as a CPU, MCU, or embedded processor), it can implement all the steps of the safety monitoring method for two-wheeled electric vehicle battery swapping stations described in Embodiment 1.
[0047] The computer storage medium in this embodiment can be applied to the main control equipment (such as PLC or industrial control computer) of the swapping station. The computer program is executed by the processor to realize automated and intelligent safety monitoring of the plugging and unplugging transients. No additional hardware costs are required. The software of the existing swapping station's main control system can be directly upgraded to adapt to the equipment upgrade and transformation of the existing swapping station. Moreover, the computer program can be written in a variety of programming languages and is compatible with different processor platforms, with good compatibility and portability.
[0048] Furthermore, the executable program can also be configured as a modular program, with each program module corresponding to the steps in Example 1. This allows for independent upgrades and modifications of the program modules without requiring overall modifications to the program architecture, facilitating subsequent functional expansion and algorithm optimization. At the same time, the program provides a parameter configuration interface, through which various preset thresholds (such as sampling frequency, arc duration, current and voltage exceedance ratio, etc.) can be flexibly adjusted to adapt to the personalized needs of various two-wheeled electric vehicle battery swapping scenarios.
[0049] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A safety monitoring method for a two-wheeled electric vehicle battery swapping station, characterized in that, include: The system collects the no-load electrical parameters of the battery swapping compartment pole docking position, establishes the transient electrical safety threshold and arc reference signal adapted to the field working conditions, and automatically triggers subsequent steps after calibration. The robot arm is controlled to perform pre-connection of the poles, and real-time high-frequency acquisition of three types of multi-dimensional data: transient current and voltage, dangerous arc signal, and conductive foreign objects at the pole position during insertion and removal. Risk assessment is based on the collected real-time data: if all three types of data meet the preset safety standards, the plug-in / plug-out transient detection is deemed qualified, and the battery swapping formal docking operation is unlocked. If the data is abnormal, the test is deemed unqualified. The risk is classified according to the type of abnormality, and the corresponding risk elimination strategy is implemented. If the risk elimination operation is completed and all verification and testing data are qualified, the abnormal warning is lifted and subsequent battery swapping operations continue; if the risk cannot be eliminated or the verification and testing are still unqualified, the system immediately triggers an interlocking and blocking command, refuses to execute all subsequent battery swapping actions, and simultaneously generates corresponding type of precise abnormal alarm information.
2. The safety monitoring method for a two-wheeled electric vehicle battery swapping station according to claim 1, characterized in that, The no-load electrical parameters include no-load reference voltage and no-load reference current, and are collected in conjunction with electromagnetic interference data and equipment static error data from the normal operating environment of the battery swapping station.
3. The safety monitoring method for a two-wheeled electric vehicle battery swapping station according to claim 1, characterized in that, The specific process for risk assessment includes: If a continuous arcing or open flame-like dangerous electric arc is detected on the pole, it is determined to be a Level 1 high-risk electrical fault risk caused by poor pole contact or insulation damage. The system will immediately trigger an interlocking command, refuse to execute all subsequent battery swapping actions, and simultaneously generate a corresponding type of precise abnormal alarm information; if no such risk is detected, proceed to the next step. The system collects image information of the electrode post area. If foreign objects are detected around the electrode post, it is classified as a level 2 risk and the type of foreign object is identified: if it is a stubborn conductive foreign object that cannot be removed by conventional purging and drying, the system immediately triggers interlocking, refuses subsequent battery swapping actions, and generates corresponding precise alarm information; if it is an easily cleanable foreign object, purging and drying operations are performed to eliminate the risk. After the operation is completed, a review test is carried out. If the review is qualified, the warning is lifted and the subsequent process continues; if the review is unqualified, the interlocking is triggered and subsequent battery swapping actions are refused. The system collects transient current and voltage data at the terminal of the electrode. If the values deviate from the preset standard range, it is classified as a Level 3 risk and the risk level is further refined: if the transient current / voltage exceeds the standard significantly and the fluctuation duration is >100ms, it is classified as a continuous electrical anomaly, and the system immediately triggers interlocking and blocks the circuit, refusing subsequent battery swapping actions; if the transient current / voltage exceeds the standard slightly and the fluctuation duration is ≤100ms, it is classified as a temporary electrical fluctuation, and the system performs transient parameter recalibration, restarts the high-frequency acquisition unit, and filters out static electricity and electromagnetic interference. After a 1-second pause, the system re-verifies the data. If the re-verification is successful, the warning is lifted and the subsequent process continues; if the re-verification is unsuccessful, the system triggers interlocking and blocks the circuit, refusing subsequent battery swapping actions.
4. The safety monitoring method for a two-wheeled electric vehicle battery swapping station according to claim 3, characterized in that, When the risk cannot be eliminated, the abnormal alarm information uploaded by the system includes the abnormality type, occurrence time, battery swapping compartment number, and real-time abnormality monitoring data.
5. The safety monitoring method for a two-wheeled electric vehicle battery swapping station according to claim 1, characterized in that, The real-time high-frequency acquisition is at the microsecond level, with a sampling frequency of no less than 1MHz. During the acquisition process, a noise filtering algorithm is simultaneously activated to eliminate high-frequency noise interference caused by the operation of the battery swapping equipment and the surrounding electromagnetic environment, thus ensuring the accuracy of transient data acquisition.
6. The safety monitoring method for a two-wheeled electric vehicle battery swapping station according to claim 3, characterized in that, For risks that can be eliminated at levels two and three, two consecutive rounds of verification and testing shall be carried out after the risk elimination operation is performed. The abnormal warning can only be lifted when the data from both rounds of testing meet the standards and there is no fluctuation deviation. If either round of verification and testing fails, the interlocking and locking command will be triggered directly.
7. A safety monitoring system for a two-wheeled electric vehicle battery swapping station, characterized in that, The method for performing the safety monitoring of a two-wheeled electric vehicle battery swapping station as described in any one of claims 1-6 includes a main control unit, a high-frequency monitoring module, a transient high-frequency monitoring module, an arc detection module, a foreign object identification module, an anomaly determination module, a strategy generation module, a risk elimination module, an interlocking module, and a cloud-based operation and maintenance module. The main control unit is electrically connected to each of the other modules and coordinates the detection timing, data processing, anomaly determination, and risk elimination operations throughout the entire process.
8. The safety monitoring system for a two-wheeled electric vehicle battery swapping station according to claim 7, characterized in that, The high-frequency monitoring module is used to collect the no-load electrical parameters of the battery swapping station pole docking position, and combine them with the electromagnetic interference and equipment static error data at the battery swapping station site to complete the transient electrical safety threshold calibration and establish the arc reference signal. The transient high-frequency monitoring module is activated after the benchmark calibration is completed. It works in conjunction with the pre-connection action of the battery swapping robotic arm to collect transient current and transient voltage data at the electrode connection point in real time at a microsecond sampling frequency, and transmits them synchronously to the main control unit and the anomaly judgment module. The arc detection module is used to monitor the arc signal during the electrode docking and insertion process in real time, identify real dangerous arcs such as continuous arcing and open flame, distinguish between interference signals and dangerous arc signals, and transmit the detection results to the anomaly judgment module in real time. The foreign object identification module is used to acquire and intelligently identify images of the pole and surrounding area, detect whether there are conductive foreign objects at the pole position, identify the type of foreign object and distinguish between stubborn conductive foreign objects and easy-to-clean foreign objects, and transmit the identification results to the anomaly judgment module in real time. The anomaly determination module is used to receive real-time data transmitted by each monitoring module, complete the qualification determination of the insertion and removal transient detection according to the preset safety standards and graded determination rules, and carry out first-level, second-level and third-level risk classification determination for abnormal data to clarify the risk type, risk level and fault cause. The strategy generation module is used to match the corresponding risk handling strategy according to the risk classification result output by the anomaly judgment module, generate standardized elimination instructions for eliminateable risks, generate interlocking and precise alarm instructions for non-eliminable risks, and transmit them synchronously to the corresponding execution module. The risk elimination module is used to receive elimination instructions issued by the strategy generation module, and perform corresponding handling operations such as purging and drying, parameter recalibration, electrostatic and interference filtering, and acquisition unit restart for risks that can be eliminated. After the operation is completed, the verification and detection process is triggered. The interlocking module is used to receive the interlocking command issued by the strategy generation module, immediately cut off the docking power of the battery swapping robotic arm, lock all battery swapping actuators, refuse subsequent battery swapping actions, and trigger a local alarm at the same time. The cloud-based operation and maintenance module is used to receive abnormal alarm information and risk handling data generated by the system, integrate all relevant information to achieve cloud storage, remote push and visualization display, and support operation and maintenance personnel to remotely monitor and accurately troubleshoot.
9. A safety monitoring system for a two-wheeled electric vehicle battery swapping station according to claim 7, characterized in that, The main control unit has built-in timing linkage logic to realize the synchronous start and stop of the high-frequency monitoring module, transient high-frequency monitoring module, arc detection module and foreign object identification module and the synchronous data acquisition, so as to ensure the timing consistency of multi-dimensional monitoring data and avoid misjudgment caused by data misalignment.
10. A computer storage medium, characterized in that, The computer storage medium stores an executable program, which, when executed by a processor, implements the safety monitoring method for a two-wheeled electric vehicle battery swapping station as described in any one of claims 1 to 6.