Vehicle Stopping Electrical Safety Monitoring System

Abstract

This invention discloses a vehicle electrical safety monitoring system for vehicle stoppage, relating to the field of new energy vehicle control technology. It includes an intelligent sensing layer, a digital twin decision-making layer, a hierarchical execution layer, and a safety escape layer. The intelligent sensing layer comprises a multimodal sensor array for real-time acquisition of physical, chemical, and environmental parameters of the vehicle's electrical system. This invention constructs a high-precision three-dimensional model including the battery compartment geometry and wiring harness layout, embedding an electrolyte leakage model and a wiring harness aging model. The former simulates diffusion paths based on fluid dynamics and predicts short-circuit risks, while the latter combines vibration fatigue and insulation material aging analysis to achieve fault evolution prediction based on physical mechanisms. This overcomes the lag of traditional threshold alarms. A dynamic threshold table is generated by combining ambient temperature, state of charge, and historical fault data, solving the problem that traditional fixed thresholds cannot adapt to complex operating conditions and reducing false alarm and false negative rates.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy vehicle control, and particularly relates to a vehicle blocking and stopping electrical safety monitoring system. BACKGROUND

[0002] With the acceleration of global energy transformation, especially the popularity of new energy electric vehicles such as pure electric and hybrid vehicles, the core power system relies on high-energy density batteries, high-voltage electrical architecture and complex wire harness networks. However, during the rapid development of new energy electric vehicles, electrical system safety problems have become increasingly prominent. Battery thermal runaway, electrolyte leakage, and high-voltage wire harness aging have become technical bottlenecks restricting the development of the industry. According to statistics, about 60% of new energy electric vehicle safety accidents worldwide are directly related to battery system failures, and 30% involve high-voltage electrical circuit abnormalities, exposing the serious shortcomings of traditional safety monitoring technology.

[0003] Published patent: A vehicle high-voltage electrical safety intelligent monitoring system, a monitoring method and a vehicle (publication number: CN116176277A), including a microprocessor controller and a fault detection device; the fault detection device is used to detect the fault information of the high-voltage electrical system, the microprocessor controller acquires the fault information according to the detection frequency set by the priority of the fault detection, processes the fault information according to the divided fault level, determines the power-off command, can realize the safety monitoring of the working state of the vehicle high-voltage fuse, contactor and each connection node, and can realize the real-time monitoring function of the insulation performance of the high-voltage electrical system of the whole vehicle, improves the comprehensiveness of the monitoring of the vehicle high-voltage system, and further improves the safety of the vehicle operation.

[0004] The prior art only relies on a single parameter for monitoring, which cannot effectively identify complex faults, resulting in limited detection capability for complex faults. The fixed threshold strategy leads to high false alarm rate in specific environments. After emergency blocking and stopping, there is a lack of real-time perception ability of the passenger state and the environment, and the dynamic escape assistance mechanism is not integrated, resulting in incomplete safety measures. There is a lack of effective means to monitor key indicators such as battery internal gas precipitation and deformation, making it difficult to timely warn potential risks. SUMMARY

[0005] The purpose of the present application is to solve the problems existing in the prior art, and a vehicle blocking and stopping electrical safety monitoring system is provided.

[0006] In order to achieve the above object, the application adopts the following technical scheme: the vehicle blocking and stopping electric safety monitoring system comprises an intelligent sensing layer, a digital twin decision layer, a hierarchical execution layer and a safety escape layer, the intelligent sensing layer comprises a multi-modal sensor array, which is used for real-time acquisition of physical parameters, chemical parameters and environmental parameters of the vehicle electrical system, the digital twin decision layer is based on a three-dimensional physical model of the vehicle electrical system, and synchronously realizes real-time intelligent sensing layer data and dynamically adjusts fault threshold, the three-dimensional physical model is embedded with an electrolyte leakage model and a wire harness aging model, the hierarchical execution layer triggers a three-level response mechanism according to the diagnosis result of the digital twin decision layer, including local current limiting, high-voltage loop isolation and emergency braking locking, and the safety escape layer integrates a UWB radar, a camera and an emergency battery, and is used for passenger state sensing, environment analysis and hierarchical escape response.

[0007] As a further description of the above technical scheme:

[0008] The multi-modal sensor array is composed of a fiber grating sensor, an ultrasonic sensor, a self-powered composite sensor, a voltage / current sensor and a temperature sensor, the fiber grating sensor is embedded between the battery modules, monitors the micro-deformation caused by thermal expansion, generates a deformation-time curve, the ultrasonic sensor detects the gas precipitation in the battery, generates a gas precipitation spectrum diagram, and the self-powered composite sensor collects energy through piezoelectric-thermoelectric effect and monitors the wire harness vibration amplitude and the temperature difference of the key nodes.

[0009] As a further description of the above technical scheme:

[0010] The electrolyte leakage model simulates the electrolyte diffusion path based on fluid dynamics, predicts the short circuit risk, and the wire harness aging model analyzes the vibration spectrum based on the rain flow counting method and calculates the insulation material aging rate based on the Arrhenius equation, and predicts the remaining life of the wire harness.

[0011] As a further description of the above technical scheme:

[0012] The three-level response mechanism of the hierarchical execution layer includes a first-level response, a second-level response and a third-level response, when a single sensor detects an anomaly, the first-level response is triggered, the fault area current is reduced and the liquid cooling system is started, when multiple sensors jointly alarm, the second-level response is triggered, the high-voltage loop is isolated through the solid-state relay, and the low-voltage system power supply is retained, when the electrolyte leakage model predicts the short circuit risk, the third-level response is triggered, the vehicle high-voltage power supply is cut off, the vehicle is braked in emergency, and the vehicle is forced to stop.

[0013] As a further description of the above technical scheme:

[0014] The UWB radar detects the breathing frequency and heartbeat signal of the occupant through Doppler effect, the camera identifies the occupant posture and environmental obstacles, including the seat belt jamming state and the door deformation degree, the emergency battery supplies power for the double CAN bus, the electromagnetic pulse window breaking device, the miniature blasting device, the UWB radar, the camera, the sound, the electronic lock of the door and the emergency lighting lamp in the vehicle, and ensures continuous work after power failure.

[0015] As a further description of the above technical solution:

[0016] The electromagnetic pulse window breaking device emits a high-energy electromagnetic pulse to shatter the window closest to the occupant, and the miniature blasting device is a backup window breaking scheme, which is started when the electromagnetic pulse window breaking device fails, and is provided with a double CAN bus, and the main control system transmits instructions through two independent buses, and one can still transmit data when the other fails.

[0017] As a further description of the above technical solution:

[0018] The hierarchical escape mechanism of the safe escape layer includes a first escape response and a second escape response, the first escape response is triggered when the occupant is awake and the door / window is not severely deformed, the escape path is prompted by voice and the door is automatically unlocked, the second escape response is started when the occupant is detected to be unconscious or the door fails, and the electromagnetic pulse window breaking and emergency lighting are triggered.

[0019] As a further description of the above technical solution:

[0020] The system operation process is as follows:

[0021] S1, data acquisition

[0022] The fiber grating sensor monitors the thermal expansion micro-deformation of the battery module, generates a deformation-time curve, and converts the deformation amount through the wavelength shift amount;

[0023] The ultrasonic sensor scans the internal gas state of the battery every 5 seconds, emits ultrasonic waves, generates a gas emission spectrum through the reflected wave signal, and calculates the gas emission amount;

[0024] The self-powered composite sensor synchronously collects the vibration acceleration of the high-voltage wire harness and the temperature difference of the key node, and generates a vibration spectrum by using the piezoelectric effect and the Seebeck effect;

[0025] The voltage / current sensor collects the voltage and current dynamic data in the battery charging and discharging process in real time;

[0026] The temperature sensor records the temperature data of the battery monomer and module, and compensates the influence of temperature on the internal resistance of the battery;

[0027] S2, data preprocessing

[0028] The noise interference of the sensor data is eliminated by Kalman filtering to extract effective signals. The battery health index is constructed by combining the deformation variable, gas evolution rate, vibration spectrum, and temperature difference data, which provides input for subsequent modeling.

[0029] S3, modeling

[0030] The digital twin decision layer receives deformation variables, gas evolution spectrum, gas type, gas evolution rate, wire harness vibration acceleration and temperature difference, voltage and current, battery monomer and module temperature data, and constructs a high-precision three-dimensional model based on sensor data and battery physical characteristics. The high-precision three-dimensional model embeds an electrolyte leakage model and a wire harness aging model.

[0031] The electrolyte leakage model simulates the electrolyte diffusion path by fluid dynamics, and predicts the short circuit risk by combining thermodynamic and electrochemical models.

[0032] The wire harness aging model analyzes the metal fatigue life caused by vibration based on the rain flow counting method, calculates the thermal aging rate of insulating materials using the Arrhenius equation, and generates a wire harness aging coefficient by weighting.

[0033] S4, data analysis

[0034] Electrolyte leakage risk diagnosis: Fusion of deformation data and gas evolution spectrum to judge thermal runaway risk; predict the short circuit probability after 3 seconds by the electrochemical model.

[0035] Wire harness aging diagnosis: Combine vibration spectrum, temperature difference data and aging coefficient to evaluate contact failure risk and predict remaining life.

[0036] Dynamic threshold adjustment: Generate a dynamic threshold table according to the environmental temperature, state of charge and historical fault records to improve the diagnosis accuracy.

[0037] S5, fault diagnosis

[0038] Thermal runaway risk: Trigger condition is deformation variable exceeding limit and abnormal gas evolution rate;

[0039] Wire harness anomaly: Trigger condition is vibration amplitude > 2g or temperature difference > 10℃;

[0040] Electrolyte leakage: Trigger condition is digital twin model predicting short circuit risk;

[0041] S6, fault classification response execution

[0042] Through a three-level response mechanism, the safety protection operation is dynamically controlled:

[0043] First level response: Potential risk, single sensor anomaly, reduce fault area current, directional enhance coolant flow;

[0044] Secondary response: moderate fault, multiple sensor joint alarm, cut off the high voltage loop, maintain low voltage power supply, enter the limp mode;

[0045] Tertiary response: emergency fault, predict electrolyte leakage, immediately cut off the high voltage bus power supply, trigger the whole vehicle power-off and emergency braking;

[0046] S7, escape response

[0047] Passenger state perception:

[0048] UWB radar: detect passenger breathing frequency, heartbeat signal and centimeter level positioning;

[0049] Camera: analyze passenger posture, seat belt state and door / window deformation degree;

[0050] Trigger hierarchical escape:

[0051] Primary response: active escape, when the passenger is conscious and the door is available, display the escape path and release the electronic lock;

[0052] Secondary response: mechanical auxiliary escape, when the passenger is unconscious or the door is deformed, trigger the electromagnetic pulse window breaking or micro-explosive device, the LED light is lit and the voice guidance is continued.

[0053] The present application has the following beneficial effects:

[0054] 1、In the present application, the three-dimensional architecture of "intelligent perception layer-digital twin decision layer-hierarchical execution layer-safety escape layer" is constructed, which breaks through the limitation of traditional single monitoring or execution system, and each layer is connected through data closed loop, realizes the whole process coverage from risk monitoring to safety disposal, forms the complete safety closed loop of "monitoring-diagnosis-execution-escape", through the innovative combination of "hierarchical architecture+multi-mode perception+digital twin+hierarchical response+active escape", breaks through the limitation of single point monitoring, static threshold alarm and passive safety disposal of traditional vehicle electrical safety system, realizes the whole cycle safety protection from "after response" to "before prediction-during control-after guarantee", significantly improves the reliability and passenger survivability of new energy vehicle electrical system, has the effects of high technical integration, strong scene adaptability, high safety redundancy and the like.

[0055] 2、In the application, the safety escape layer is equipped with emergency battery and double CAN bus, which ensures that the key escape function can still run continuously after the main system power failure, solves the safety blind area of traditional system power failure, improves the survival ability in extreme scenarios, adopts multi-modal sensors such as fiber grating, ultrasonic wave, self-powered composite sensor, etc., respectively monitors parameters such as battery micro-deformation, internal gas precipitation, wire harness vibration and temperature difference, breaks through the limitation of single parameter monitoring, constructs battery health index through data fusion analysis, improves early fault identification accuracy, UWB radar and camera fusion, accurately judges the passenger's wakefulness and escape path availability, solves the problem of traditional escape system relying on manual operation or single sensor misjudgment, according to the state of the passenger, triggers a hierarchical escape response, when the passenger is awake, triggers a first-level response, voice / screen guide escape path and automatically unlock the door, retain the ability of autonomous escape, when the passenger is unconscious or the door is invalid, triggers a second-level response, electromagnetic pulse window breaking and miniature explosion double redundancy, cooperates with emergency lighting and voice instructions, realizes the upgrade from "passive monitoring" to "active intervention", and breaks through the randomness and environmental adaptability of traditional window breaking device.

[0056] 3、In the application, a high-precision three-dimensional model containing the geometry of the battery compartment and the layout of the wire harness is constructed, and an electrolyte leakage model and a wire harness aging model are embedded, the former simulates the diffusion path based on fluid dynamics and predicts the short circuit risk, and the latter analyzes the vibration fatigue and insulation material aging, realizes the fault evolution prediction based on the physical mechanism, breaks through the hysteresis of traditional threshold alarm, generates a dynamic threshold table combined with environmental temperature, state of charge, historical fault data, solves the problem that traditional fixed threshold cannot adapt to complex working conditions, reduces the false alarm rate and the missing alarm rate, sets up a three-level response mechanism, which dynamically adjusts the intervention intensity according to the fault severity, breaks through the rigid response of traditional "on-off", and takes into account safety and functional availability, combines cross-disciplinary technologies such as fiber sensing, digital twinning, energy harvesting, and biometric detection, to build a technology closed loop of "physical perception-digital mapping-intelligent decision-making-mechanical execution", break the single technology dependence of traditional automotive safety systems, record data before and after the fault for model iteration, correct model parameters through historical cases, dynamically update the algorithm combined with aging history data, realize the system self-learning ability, solve the precision decay problem of traditional fixed algorithm after long-term operation. BRIEF DESCRIPTION OF DRAWINGS

[0057] Fig. 1 The system architecture of the application is shown in the figure;

[0058] Fig. 2 The system flowchart of the application is shown in the figure. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0060] With reference to Figs. 1-2 An embodiment provided by the present application is a vehicle stopping safety monitoring system, which comprises an intelligent sensing layer, a digital twin decision layer, a hierarchical execution layer and a safety escape layer. The intelligent sensing layer comprises a multi-modal sensor array, which is used to collect physical parameters, chemical parameters and environmental parameters of a vehicle electrical system in real time. The digital twin decision layer is based on a three-dimensional physical model of the vehicle electrical system, synchronizes the data of the intelligent sensing layer in real time, and dynamically adjusts a fault threshold. The three-dimensional physical model is embedded with an electrolyte leakage model and a wire harness aging model. The hierarchical execution layer triggers a three-level response mechanism according to the diagnosis result of the digital twin decision layer, including local current limiting, high-voltage loop isolation and emergency braking locking. The safety escape layer integrates a UWB radar, a camera and an emergency battery, and is used for passenger state sensing, environmental analysis and hierarchical escape response.

[0061] The multi-modal sensor array is composed of a fiber grating sensor, an ultrasonic sensor, a self-powered composite sensor, a voltage / current sensor and a temperature sensor. The fiber grating sensor is embedded between battery modules to monitor micro-deformation caused by thermal expansion, generate a deformation-time curve, and the ultrasonic sensor detects gas evolution in the battery to generate a gas evolution spectrum. The self-powered composite sensor collects energy through piezoelectric-thermoelectric effect, monitors wire harness vibration amplitude and key node temperature difference, the electrolyte leakage model simulates electrolyte diffusion path based on fluid dynamics to predict short circuit risk, and the wire harness aging model analyzes vibration spectrum based on rain flow counting method and calculates insulation material aging rate based on Arrhenius equation to predict wire harness remaining life. The three-level response mechanism of the hierarchical execution layer includes a first-level response, a second-level response and a third-level response. When a single sensor detects an anomaly, the first-level response is triggered to reduce the fault area current and start the liquid cooling system. When multiple sensors jointly alarm, the second-level response is triggered to isolate the high-voltage loop through a solid-state relay and retain low-voltage system power supply. When the electrolyte leakage model predicts short circuit risk, the third-level response is triggered to cut off the vehicle high-voltage power supply to make the vehicle perform emergency braking and force the vehicle to stop.

[0062] The UWB radar detects the breathing frequency and heartbeat signal of the occupant through the Doppler effect, the camera recognizes the occupant's posture and environmental obstacles, including the safety belt jamming state and the degree of deformation of the vehicle door, the emergency battery is powered by the dual CAN bus, the electromagnetic pulse window breaking device, the miniature explosive device, the UWB radar, the camera, the sound, the electronic lock of the vehicle door and the emergency lighting in the vehicle, to ensure continuous operation after power failure, the electromagnetic pulse window breaking device sends a high-energy electromagnetic pulse to shatter the vehicle window closest to the occupant, the miniature explosive device is a backup window breaking scheme, which is started when the electromagnetic pulse window breaking device fails, and is provided with a dual CAN bus, the main control system transmits instructions through two independent buses, one of which can still transmit data when the other fails, the hierarchical escape mechanism of the safety escape layer includes a first escape response and a second escape response, when the occupant is conscious and the vehicle door / window is not severely deformed, the first escape response is triggered, the voice prompts the escape path and automatically unlocks the vehicle door, when the occupant is unconscious or the vehicle door fails, the second escape response is started, triggering the electromagnetic pulse window breaking and emergency lighting.

[0063] The workflow of the intelligent perception layer includes three stages of data acquisition, signal processing and data transmission, a multi-modal sensor array is composed of fiber grating sensors, ultrasonic sensors, self-powered composite sensors, voltage / current sensors and temperature sensors, physical and chemical parameters of the vehicle electrical system are collected in real time through the multi-modal sensor array, advanced sensing technology is combined to realize high-precision monitoring, and data basis is provided for subsequent fault diagnosis and decision-making, the fiber grating sensor monitors the thermal expansion micro-deformation and stress distribution between the battery modules in real time, generates a deformation-time curve, forms a grating structure through periodic refractive index changes, when the battery deforms due to temperature changes or internal pressure, the period of the grating changes, the wavelength shift is detected through a demodulator and converted into a deformation, the formula is ΔL=k·Δλ, ΔL is the thermal expansion micro-deformation of the battery module, Δλ is the wavelength shift of the fiber grating, and k is the deformation-wavelength conversion coefficient, which is determined by the grating material characteristics and the demodulator calibration, when the thermal expansion deformation of the battery module caused by temperature rise exceeds the set value, a warning signal is triggered, the ultrasonic sensor scans the battery internal gas state every 5 seconds, monitors the battery internal gas evolution, generates a gas evolution spectrum, judges the gas type through a pattern matching algorithm, emits ultrasonic waves with a frequency range of 20-200 kHz, reflects when encountering a gas / liquid interface after penetrating the battery shell, receives the reflected wave signal, calculates the gas evolution amount through the time difference method, and determines the electrolyte leakage risk when the gas evolution rate is greater than the set value, the self-powered composite sensor monitors the vibration amplitude of the high-voltage wire harness and the temperature difference of the key nodes, synchronously collects the wire harness vibration acceleration and temperature difference, generates a vibration spectrum, when the wire harness vibrates, the piezoelectric material generates an electric charge through the piezoelectric effect, which is converted into a voltage signal, the Seebeck effect is used to generate electricity through the temperature difference between the two ends of the wire harness, and the built-in super capacitor is charged, the comprehensive formula of the Seebeck effect is V 输出 =β·ΔT, V输出 is the voltage of the sensor output, β is the Seebeck coefficient determined by the temperature difference characteristics of the materials at both ends of the wire harness, ΔT is the temperature difference of the key nodes of the wire harness, supports continuous operation for a period of time after power failure, when the vibration amplitude > 2g or the temperature difference > 10℃, it is marked as an abnormal node, the voltage / current sensor collects voltage and current data during the charging and discharging process of the battery in real time, monitors dynamic changes, the temperature sensor is embedded in the battery monomer and the wire harness node, and the temperature data of the battery monomer and the module are recorded synchronously, which is used to compensate the influence of temperature on the internal resistance of the battery, the data collected by the multi-modal sensor array is processed, the noise interference is eliminated by Kalman filtering, and the formula is is the state estimation value after denoising at the kth moment, is the predicted state value at the kth moment, K k is the Kalman gain, which controls the weight of the sensor data and the predicted value, z k is the original observation value of the sensor at the kth moment, H is the observation matrix, which maps the state to the sensor measurement space, combines deformation, gas, vibration data, and judges abnormalities through multiple sensor data, when deformation and gas anomalies occur, it is determined as thermal runaway risk, when vibration and temperature difference anomalies occur, it is determined as wire harness aging or poor contact, the data is uploaded to the digital twin decision layer through the CAN bus, supporting real-time synchronization and offline caching two modes, the self-powered sensor maintains data transmission through the super capacitor after power failure.

[0064] The digital twin decision layer is the key link of the intelligent management of the entire vehicle electrical system, which is mainly responsible for receiving the data of the intelligent perception layer, and using various technologies and models for analysis, diagnosis and prediction to provide decision basis for the hierarchical execution layer, receiving the deformation, gas evolution spectrum, gas type, gas evolution rate, wire harness vibration acceleration and temperature difference, voltage and current, temperature data of the battery monomer and module collected and preprocessed by the intelligent perception layer, and combining the state of charge and health state data of the battery, to prepare for subsequent analysis, combining the physical characteristics of the vehicle electrical system, including the positive and negative electrode materials of the battery, the electrolyte composition, the spacing between the battery modules, the position of the pressure relief valve, the mechanical fatigue life of the copper conductor, and the deformation characteristics of the insulating material under temperature difference, using simulation tools to build a high-precision three-dimensional model, the three-dimensional model is embedded with an electrolyte leakage model and a wire harness aging model, inputting the wire harness material properties and wire harness vibration amplitude parameters, analyzing the vibration spectrum based on the rain flow counting method, to calculate the fatigue life of the metal conductor, the formula is Δσ is the stress amplitude caused by vibration, which is extracted from vibration spectrum analysis, C, m is the material constant determined by the fatigue characteristics of the wire harness metal, captures mechanical fatigue signals, evaluates thermal stress, uses the Arrhenius equation to evaluate the aging rate of the insulating material on the surface of the wire harness, and then performs weighted comprehensive operation on the metal fatigue life and the insulating aging rate to obtain the wire harness aging coefficient, the formula is C老化 = w1 L 金属疲劳 + w2 a 绝缘老化 , C 老化 is a wire harness aging coefficient, used to quantify the overall aging degree of the wire harness, L 金属疲劳 is the fatigue life of the metal conductor, calculated by the rainflow counting method, a 绝缘老化 is the aging rate of the insulation material, calculated by the Arrhenius equation, w1, w2 are weight coefficients, determined by historical wire harness aging data optimization, satisfying w1 + w2 = 1, input wire harness material properties and wire harness vibration amplitude parameters, based on the rainflow counting method to analyze the metal fatigue caused by vibration, calculate the thermal aging rate of the wire harness insulation material through temperature difference data, use historical wire harness aging data to dynamically update the aging threshold, thus constructing a wire harness aging model to predict the aging rate and contact failure risk caused by vibration and temperature difference, get the remaining life prediction of the wire harness, and analyze the vibration stress concentration area according to the wire harness layout in the three-dimensional model, input battery pack structure data and electrolyte physical property parameters, simulate the flow path of electrolyte in the battery cabin through fluid dynamics, predict the influence of local temperature rise on adjacent modules after leakage through thermodynamic analysis, evaluate the short circuit current characteristics of electrolyte after contacting with the electrode through the electrochemical model, fuse the gas evolution data monitored by the ultrasonic sensor and the deformation data of the fiber Bragg grating sensor, and correct the model parameters through historical failure cases, thus constructing an electrolyte leakage model to predict the diffusion path, short circuit risk and spatiotemporal evolution law after electrolyte leakage, predict the short circuit risk after 3 seconds, the electrolyte leakage model is based on the battery cabin geometry structure in the three-dimensional model to determine the leakage diffusion boundary conditions, the three-dimensional model updates the input parameters of the electrolyte leakage model and the wire harness aging model in the three-dimensional model according to the data collected by the real-time access intelligent sensing layer, the battery internal resistance change data will trigger the electrochemical short circuit prediction of the electrolyte leakage model, when the current occurs step change, calculate the battery internal resistance through voltage response, the calculation formula is internal resistance = voltage change value / current change value, calculate the voltage change value and current change value through the voltage and current data of the battery, since the battery internal resistance decreases with the increase of temperature, the temperature threshold will be increased in low temperature environment, the three-dimensional model real-time access sensor data, analyze the sensor data, compare the sensor data with the three-dimensional model, judge whether the data is abnormal or not, and constantly update the input parameters of the electrolyte leakage and wire harness aging model, wherein the battery internal resistance change data in the three-dimensional model will trigger the electrochemical short circuit prediction of the electrolyte leakage model, mark the electrolyte diffusion path and the high risk area of wire harness aging in the three-dimensional model, assist engineers in intuitive diagnosis, and record the data 10 minutes before and after the failure for accident analysis and model optimization, the battery internal resistance change data will trigger the electrochemical short circuit prediction of the electrolyte leakage model, the formula is R is the density of the electrolyte defined by the physical parameters of the electrolyte, u is the flow velocity vector of the electrolyte, which is solved by the boundary conditions of the battery cabin geometry, t is the time, the fault threshold is adjusted according to the real-time environmental parameters temperature and state of charge, and the dynamic threshold table is generated based on the environmental temperature, state of charge, and historical fault records, to provide more accurate judgment basis for fault diagnosis and realize dynamic fault diagnosis.

[0065] The hierarchical execution layer dynamically controls the safety protection operation of the vehicle electrical system through a three-level response mechanism based on the data input of the intelligent perception layer and the digital twin decision layer, realizes the step-by-step response from early warning to emergency stop, matches the response level according to the sensor abnormal type, number and digital twin prediction result, and gradually improves the response intensity from local current limiting to whole vehicle power-off, balances safety and functional availability, and potential risks are first-level response, the triggering condition is single sensor collected data anomaly, reduces the current of the fault area through power electronic devices, suppresses the risk of thermal runaway, and directionally enhances the cooling liquid flow of the abnormal battery monomer, the moderate fault is second-level response, the triggering condition is multi-sensor joint alarm, executes high-voltage loop isolation, cuts off the fault high-voltage loop through solid-state relays, maintains low-voltage power supply functions such as vehicle window unlocking and light illumination, supports the vehicle to enter the limp mode, and the emergency fault is third-level response, the triggering condition is that the digital twin model predicts electrolyte leakage, immediately cuts off the high-voltage bus power supply, and the whole vehicle high-voltage is powered off, so that the vehicle is braked urgently and forced to stop, and at the same time the vehicle door electronic lock is opened, the first-level response retains the vehicle power function, the second-level response limits the power output, and the third-level response completely cuts off the power, the response level automatically upgrades with the fault severity, and in the third-level response, the high-voltage power-off is prior to the mechanical brake, avoiding the delay of power-off leading to secondary accidents.

[0066] The safe escape layer quickly identifies the state of the passengers and the environmental obstacles when the vehicle is in collision or electrical failure through real-time state perception and hierarchical response mechanism, dynamically triggers the escape operation to ensure the safe evacuation of the passengers, combines the penetrating positioning of the UWB radar and the visual analysis of the camera to accurately judge the vital signs of the passengers and the environmental obstacles, dynamically selects the escape path according to the consciousness state of the passengers, the availability of the doors / windows, independently supplies power and communicates through the double CAN bus to ensure that the escape function continues to operate after power failure, the UWB radar monitors the breathing frequency and heartbeat signal of the passengers through the Doppler effect, scans the small movements of the passengers to judge whether the passengers are in coma or lose the ability to act, has a centimeter-level positioning accuracy, tracks the position of the passengers in the vehicle in real time, the camera analyzes the posture of the passengers, detects the safety belt blocking state, the head injury condition, identifies whether the window is blocked by obstacles, and the deformation degree of the door, and is provided with a hierarchical response escape mechanism, the first level response is active escape, the triggering condition is that the passengers are conscious, the breathing frequency is normal, the motion response detection is passed, the camera determines that the door / window has no serious deformation, the escape path is displayed through the vehicle audio or screen, the electronic lock is automatically released, and the passengers can manually open the door to evacuate, the second level response is mechanical auxiliary escape, the triggering condition is that the passengers are in coma, the breathing frequency is less than 8 times per minute, and there is no motion response, the camera determines that the door is seriously deformed or the electronic lock is invalid, the electromagnetic pulse window breaking device is triggered to impact and separate the nearest window of the passengers, if the electromagnetic pulse window breaking device fails, the window is broken through the micro-explosive device, the blasting force is controllable, the fragment splash range is less than 30 cm, the in-vehicle LED light is automatically turned on to assist in escaping in the dark environment, the instructions such as "please escape from the left window" are continuously broadcast, the emergency battery supplies power for the UWB radar, the camera, the window breaking device, the emergency lighting, the audio, the display screen, the electromagnetic pulse window breaking device, the micro-explosive device, and the double CAN bus, to ensure that the system continues to work for more than 5 minutes after power failure, the power of the window breaking device and the CAN bus is preferentially guaranteed, the escape system and the main control system transmit instructions through two independent buses, if one bus fails, the other bus can still transmit key instructions such as window breaking and unlocking.

[0067] The system operation process is as follows:

[0068] S1, data acquisition

[0069] The fiber grating sensor monitors the thermal expansion and micro deformation of the battery module, generates a deformation-time curve, and converts the deformation amount through the wavelength shift;

[0070] The ultrasonic sensor scans the internal gas state of the battery every 5 seconds, emits ultrasonic waves, generates a gas emission spectrum through the reflected wave signal, and calculates the gas emission amount;

[0071] The self-powered composite sensor synchronously collects the vibration acceleration of the high-voltage wire harness and the temperature difference of the key nodes, generates a vibration spectrum through the piezoelectric effect and the Seebeck effect;

[0072] Voltage / current sensor collects voltage and current dynamic data in real time during battery charging and discharging process;

[0073] Temperature sensor records temperature data of battery monomer and module, compensates the influence of temperature on battery internal resistance;

[0074] S2, data preprocessing

[0075] Through Kalman filtering, the noise interference of sensor data is eliminated, and the effective signal is extracted. Combined with deformation, gas evolution rate, vibration spectrum and temperature difference data, battery health index is constructed to provide input for subsequent modeling;

[0076] S3, modeling

[0077] The digital twin decision layer receives deformation, gas evolution spectrum, gas type, gas evolution rate, wire harness vibration acceleration and temperature difference, voltage and current, temperature data of battery monomer and module, based on sensor data and battery physical characteristics, to build a high-precision three-dimensional model, which embeds electrolyte leakage model and wire harness aging model;

[0078] The electrolyte leakage model simulates the diffusion path of electrolyte through fluid dynamics, and predicts the short circuit risk by combining thermodynamic and electrochemical models;

[0079] The wire harness aging model analyzes the metal fatigue life caused by vibration based on the rain flow counting method, calculates the thermal aging rate of insulating materials using the Arrhenius equation, and generates the wire harness aging coefficient by weighting;

[0080] S4, data analysis

[0081] Electrolyte leakage risk diagnosis: fusion of deformation data and gas evolution spectrum, judge thermal runaway risk; Through the electrochemical model, predict the short circuit probability after 3 seconds;

[0082] Wire harness aging diagnosis: combined with vibration spectrum, temperature difference data and aging coefficient, evaluate the risk of contact failure and predict the remaining life;

[0083] Dynamic threshold adjustment: according to the environmental temperature, state of charge and historical fault records, generate dynamic threshold table, improve the diagnosis accuracy;

[0084] S5, fault diagnosis

[0085] Thermal runaway risk: the trigger condition is that the deformation exceeds the limit and the gas evolution rate is abnormal;

[0086] Wire harness anomaly: the trigger condition is that the vibration amplitude is greater than 2g or the temperature difference is greater than 10℃;

[0087] Electrolyte leakage: the trigger condition is that the digital twin model predicts the short circuit risk;

[0088] S6, fault classification response execution

[0089] Safety protection operation is dynamically controlled through a three-level response mechanism:

[0090] Primary response: potential risk, single sensor anomaly, reduce fault area current, directional enhance coolant flow;

[0091] Secondary response: moderate fault, multiple sensor joint alarm, cut off fault high voltage loop, maintain low voltage power supply, enter limp mode;

[0092] Tertiary response: emergency fault, predict electrolyte leakage, immediately cut off high voltage bus power, trigger vehicle power-off and emergency braking;

[0093] S7, escape response

[0094] Passenger state perception:

[0095] UWB radar: detect passenger breathing frequency, heartbeat signal and centimeter-level positioning;

[0096] Camera: analyze passenger posture, seat belt status and degree of deformation of doors / windows;

[0097] Triggered hierarchical escape:

[0098] Primary response: active escape, passenger is conscious and doors are available, display escape path and release electronic lock;

[0099] Secondary response: mechanical assisted escape, passenger is unconscious or doors are deformed, trigger electromagnetic pulse window breaking or micro-explosive device, LED light is on and continuous voice guidance is triggered.

[0100] Finally, it should be noted that the above only for the preferred embodiments of the present application, and not for the purpose of limiting the present application, although the foregoing embodiments of the present application are described in detail, for those skilled in the art, it still can be modified, or part of the technical features of the equivalent replacement, within the spirit and principles of the present application, any modification, equivalent replacement, improvement, etc., should be included within the scope of the present application.

Claims

1. Vehicle immobilization electrical safety monitoring system, characterized in that: The intelligent perception layer includes a multi-modal sensor array for real-time collection of physical parameters, chemical parameters and environmental parameters of the vehicle electrical system, the digital twin decision layer is based on a three-dimensional physical model of the vehicle electrical system, real-time synchronization of the intelligent perception layer data, dynamic adjustment of the fault threshold, the three-dimensional physical model has embedded electrolyte leakage model and wire harness aging model, the hierarchical execution layer triggers a three-level response mechanism according to the diagnosis result of the digital twin decision layer, including local current limiting, high-voltage loop isolation and emergency braking locking, and the safety escape layer integrates UWB radar, camera and emergency battery for passenger state perception, environment analysis and hierarchical escape response; The system operation process is as follows: S1, data acquisition The fiber grating sensor monitors the thermal expansion micro-deformation of the battery module, generates a deformation-time curve, and converts the wavelength shift into a deformation variable; The ultrasonic sensor scans the internal gas state of the battery every 5 seconds, emits ultrasonic waves, and generates a gas emission spectrum through the reflected wave signal to calculate the gas emission amount; The self-powered composite sensor synchronously collects the vibration acceleration of the high-voltage wire harness and the temperature difference of the key nodes, and generates a vibration spectrum by using the piezoelectric effect and the Seebeck effect; The voltage / current sensor real-time collects the voltage and current dynamic data in the process of battery charging and discharging; The temperature sensor records the temperature data of the battery monomer and module, and compensates the influence of temperature on the internal resistance of the battery; S2, data preprocessing Through Kalman filtering, the noise interference of the sensor data is eliminated, the effective signal is extracted, the battery health index is constructed by combining the deformation variable, gas emission rate, vibration spectrum and temperature difference data, and the input for subsequent modeling is provided; S3, modeling The digital twin decision layer receives the deformation variable, gas emission spectrum, gas type, gas emission rate, wire harness vibration acceleration and temperature difference, voltage and current, temperature data of the battery monomer and module, constructs a high-precision three-dimensional model based on sensor data and battery physical characteristics, and the high-precision three-dimensional model has embedded electrolyte leakage model and wire harness aging model; The electrolyte leakage model simulates the electrolyte diffusion path through fluid dynamics, predicts the short circuit risk by combining thermodynamic and electrochemical models; The wire harness aging model analyzes the metal fatigue life caused by vibration based on the rain flow counting method, calculates the thermal aging rate of insulating materials by using the Arrhenius equation, and generates a wire harness aging coefficient by weighting; S4, data analysis Electrolyte leakage risk diagnosis: fuse deformation data and gas emission spectrum to judge thermal runaway risk; predict the short circuit probability after 3 seconds through the electrochemical model; Wire harness aging diagnosis: combine vibration spectrum, temperature difference data and aging coefficient to evaluate contact failure risk and predict remaining life; Dynamic threshold adjustment: generate a dynamic threshold table according to the environmental temperature, state of charge and historical fault records to improve the diagnosis accuracy; S5, fault diagnosis Thermal runaway risk: the trigger condition is that the deformation variable is out of limit and the gas emission rate is abnormal; Wire harness anomaly: the trigger condition is that the vibration amplitude is greater than 2g or the temperature difference is greater than 10℃; Electrolyte leakage: the trigger condition is that the digital twin model predicts the short circuit risk; S6, fault hierarchical response execution Dynamic control of safety protection operation through three-level response mechanism: Primary response: potential risk, single sensor anomaly, reduce fault area current, directional enhance cooling fluid flow; Secondary response: moderate fault, multiple sensor joint alarm, cut off fault high voltage loop, maintain low voltage power supply, enter limp mode; Tertiary response: emergency fault, predict electrolyte leakage, immediately cut off high voltage bus power, trigger vehicle power off and emergency braking; S7, escape response Occupant state perception: UWB radar: detect occupant breathing frequency, heartbeat signal and centimeter level positioning; Camera: analyze occupant posture, seat belt state and door / window deformation degree; Triggered hierarchical escape: Primary response: active escape, occupant is conscious and door is available, display escape path and release electronic lock; Secondary response: mechanical assisted escape, occupant is unconscious or door is deformed, trigger electromagnetic pulse window breaking or micro-explosive device, LED light is on and continuous voice guidance.

2. The vehicle holdback electrical safety monitoring system of claim 1, wherein: The multi-modal sensor array is composed of fiber grating sensors, ultrasonic sensors, self-powered composite sensors, voltage / current sensors and temperature sensors. The fiber grating sensors are embedded between the battery modules to monitor the micro-deformation caused by thermal expansion, generate a deformation-time curve, the ultrasonic sensors detect the gas evolution inside the battery, generate a gas evolution spectrum, the self-powered composite sensors collect energy through piezoelectric-thermoelectric effect, monitor the vibration amplitude of the wire harness and the temperature difference of the key nodes.

3. The vehicle holdback electrical safety monitoring system of claim 1, wherein: The electrolyte leakage model simulates the electrolyte diffusion path based on fluid dynamics, predicts the short circuit risk, the wire harness aging model analyzes the vibration spectrum based on the rain flow counting method and calculates the insulation material aging rate based on the Arrhenius equation, predicts the remaining life of the wire harness.

4. The vehicle holdback electrical safety monitoring system of claim 1, wherein: The three-level response mechanism of the hierarchical execution layer includes primary response, secondary response and tertiary response. When a single sensor detects an anomaly, the primary response is triggered to reduce the fault area current and start the liquid cooling system. When multiple sensors jointly alarm, the secondary response is triggered to isolate the high voltage loop through solid state relays, leaving the low voltage system powered. When the electrolyte leakage model predicts a short circuit risk, the tertiary response is triggered to cut off the vehicle high voltage power, making the vehicle emergency brake and forcing the vehicle to stop.

5. The vehicle holdback electrical safety monitoring system of claim 1, wherein: The UWB radar detects the occupant's breathing frequency and heartbeat signal through the Doppler effect, the camera identifies the occupant's posture and environmental obstacles, including seat belt jamming state and door deformation degree, the emergency battery powers the dual CAN bus, electromagnetic pulse window breaking device, micro-explosive device, UWB radar, camera, audio, vehicle door electronic lock and vehicle emergency lighting, ensuring continuous operation after power failure.

6. The vehicle holdback electrical safety monitoring system of claim 5, wherein: The electromagnetic pulse window breaking device emits a high-energy electromagnetic pulse to shatter the window closest to the occupant, and the micro-explosive device serves as a backup window breaking scheme and is activated when the electromagnetic pulse window breaking device fails. It is equipped with a dual CAN bus, and the main control system transmits commands through two independent buses. One fails, but the other can still transmit data.

7. The vehicle holdback electrical safety monitoring system of claim 1, wherein: The hierarchical escape mechanism of the safety escape layer includes a first escape response and a second escape response. The first escape response is triggered when the occupant is conscious and the door / window is not severely deformed, the voice prompts the escape path and automatically unlocks the door. The second escape response is started when the occupant is unconscious or the door is invalid, the electromagnetic pulse window breaking and emergency lighting are triggered.

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