16966results about "Fire rescue" patented technology

The invention relates to the technical field of monitoring and early warning, in particular to a fire hydrant monitoring intelligent early warning system based on an anomaly analysis technology, which comprises a flow velocity anomaly identification module, a node collaborative pressure difference detection module, a pressure difference trend independence judgment module, a node degradation feature extraction module and a risk level generation module. According to the method, through correlation judgment of flow velocity deviation and control signals, no-signal recognition of abnormal water taking behaviors and a cooperative analysis mechanism of pressure change of adjacent nodes, a hydraulic disturbance area under non-manual control can be accurately recognized, and through analysis of spatial independence of a pressure response trend, a water flow disturbance area under non-manual control can be accurately recognized. The function degradation level of the device is extracted according to historical data of on-off time delay and response performance, the quantitative evaluation capability of the node function state is enhanced, the capability of finely dividing the risk level is achieved when risk early warning is given out, the risk identification accuracy is improved, and the active discovery capability of early fault hidden dangers is enhanced.

The invention discloses a safety control method based on a knowledge graph, and belongs to the field of safety control, and the method comprises the following steps: crawling various types of data according to keywords through a crawler program to construct a fireproof database; carrying out semantic analysis on data in the fireproof database by using a natural language processing technology, and carrying out data processing on the fireproof database after semantic analysis through word vector modeling and entity relationship extraction; constructing an internal large-scale language model by using the processed fireproof database, and performing hierarchical clustering on the internal large-scale language model by adopting a Leiden technology; establishing a multi-dimensional mapping model based on historic building spatial features, cultural relic features and disaster-inducing factors in a hierarchical clustering result, and constructing a multi-modal dynamic association fireproof knowledge graph by using a knowledge graph technology based on the multi-dimensional mapping model; and dynamically selecting a search mode based on a user query keyword, and generating a security control result according to the query keyword based on the search mode.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

The invention relates to the technical field of communication machine room safety protection, and discloses a communication machine room intelligent fire monitoring and fire extinguishing system based on edge computing, which comprises a fire parameter acquisition module, a temperature characteristic analysis module, a smoke dynamic detection module, a multi-source fusion judgment module, a regulation and control parameter generation module and the like. The fire parameter acquisition module acquires parameters such as temperature gradient, smoke concentration and equipment current, judges fire risk and triggers cooperative monitoring; the temperature characteristic analysis module extracts temperature distribution characteristics and quantitatively evaluates hot spot abnormity; the smoke dynamic detection module analyzes the smoke diffusion trend; the multi-source fusion judgment module is combined with multiple parameters to generate a fire extinguishing or optimizing signal; and the regulation and control parameter generation module is matched with the strategy to generate injection and ventilation parameters. The system also corrects a risk index through an equipment coupling analysis module, and forms closed-loop control by using a dynamic feedback execution module. According to the system, multi-source data fusion monitoring and intelligent fire extinguishing are realized, and the fire prevention and control accuracy of the communication machine room is improved.

An electrified fire fighting vehicle includes a chassis, a front axle coupled to the chassis, a rear axle coupled to the chassis, a water pump, an energy storage system, an engine, an electric motor coupled to the engine and the energy storage system, and a power divider positioned between the electric motor, the water pump, and the rear axle. The power divider facilitates selectively driving the water pump and the rear axle with the engine and the electric motor.

The invention relates to the technical field of data processing and identification, in particular to an intelligent fire fighting equipment fault identification method and system, and the method comprises the steps: carrying out the execution according to a set first period: generating simulation data through a constructed digital twinborn model; acquiring operation data of real equipment through a sensor network; comparing a deviation value between the simulation data and the real equipment data; when the deviation value exceeds a preset threshold value, triggering a causal inference engine; calibrating digital twin model parameters and adjusting equipment operation parameters; the prior art mainly depends on fixed threshold alarm, early progressive faults of equipment are difficult to capture, and response lags behind; according to the scheme, digital twin simulation and active flaw detection are combined, and deep insight of the health state of the equipment is formed by periodically injecting micro-amplitude disturbance signals into the equipment and analyzing the dynamic response characteristics of the equipment; according to the invention, tiny degradation of equipment performance can be captured in a fault incubation period, so that maintenance intervention is triggered in advance, and the advancement and accuracy of fault early warning are remarkably improved.

The invention relates to the technical field of fire-fighting monitoring, in particular to a fire-fighting water system fault detection and early warning method and system based on the fire-fighting Internet of Things, and the method comprises the steps: 1, periodically collecting pressure data through pressure sensors disposed at a fire-fighting water pump outlet, a pipe network main pipe branch point and the most unfavorable tail end; 2, according to the current valve opening degree, the pump state and historical normal working condition data, theoretical pressure expected values and dynamic allowable deviation zones of all nodes are generated; 3, when actually measured pressure deviates from a theoretical pressure expected value and exceeds a dynamic allowable deviation band, marking abnormal nodes, reversely constructing a fault propagation tree along the topological model, and allocating weight factors for associated nodes according to fault types; and 4, triggering graded early warning based on the number of the abnormal nodes, the fault propagation path and the weight factor accumulated value. And the system can automatically take measures when a fault occurs through an equipment linkage function, so that the efficient operation of the fire fighting water system is guaranteed, and the efficiency and safety of fire emergency response are improved.

The invention relates to the technical field of fire-fighting management, and discloses an intelligent fire-fighting service management system, which comprises a data acquisition unit used for acquiring three basic parameters, namely environment data, working condition data and battery data, of a fire-fighting object in an office building, and the system acquires the environment, working condition and battery data of a fire extinguisher through the data acquisition unit; the fusion unit generates a dynamic composite abnormal threshold value, and the adjustment unit executes a three-stage sampling frequency adjustment mechanism according to the threshold value, the battery health degree score and the data deviation degree, which means that the sampling frequency can be reduced to reduce the battery energy consumption when the state of the fire extinguisher is normal and the risk is relatively low, and when the risk is increased or the battery health degree is reduced, the battery energy consumption is reduced. The whole system realizes accurate management and regulation of the battery according to the actual working condition of the fire extinguisher, energy waste is avoided, the service life of the battery is prolonged, the cost of frequently replacing the battery is reduced, and the sustainability of intelligent fire control management is enhanced.

The invention discloses a tunnel fire air curtain smoke prevention control method and system, and relates to the technical field of intelligent fire fighting, and the method comprises the steps: building a digital twinborn prediction model, and generating a fire source position coordinate and a smoke diffusion trend prediction map through multi-physics field coupling simulation; analyzing the stability requirement of the air curtain jet flow through a Brapare-Prandtt boundary layer analysis algorithm, and generating a jet flow enhancement requirement parameter table in combination with temperature gradient correction; optimizing an acoustic vortex main frequency band by adopting a Slodhaar number, and generating an acoustic vortex control parameter set in combination with a matched sound pressure level and a configured resonator phase difference; and converting the acoustic vortex control parameter set into an execution instruction, monitoring the jet velocity, the vortex street stability and the smoke retardation effect in real time, and dynamically correcting the parameters of the digital twinborn prediction model. According to the method, physical quantity outline matching of the blocking intensity and the sound pressure level is achieved through the sound intensity-momentum equivalent method, and the optimal phase configuration is determined in combination with POD modal analysis.

A long-term fire retarding biochemical liquid composition including: a dispersing agent realized in the form of a major amount of water, for dispersing alkali metal ions dissolved in the water; a major amount of a first fire retarding agent realized in the form of a primary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, tripotassium citrate, for providing metal potassium ions dispersed in the water when the at least one alkali metal salt is dissolved in the water to form a mixed retardant solution; a minor amount of a second fire retarding agent realized in the form of a secondary alkali metal salt of a nonpolymeric saturated carboxylic acid, for example, potassium, sodium, calcium and / or magnesium benzoate, for providing benzoate ions dispersed in the water when the secondary alkali metal salt is dissolved in the mixed retardant solution, for functioning as a secondary fire retardant agent.

The invention discloses a multistage fire-fighting and intelligent heat management combined system and method for an energy storage system, a battery cluster is provided with a single fire extinguishing nozzle, a composite detector monitors the state of the battery cluster in real time, and when any battery cluster meets a spraying condition, the fire extinguishing nozzle is triggered to spray a fire extinguishing material; the internal state of the energy storage cabin is monitored in real time through a composite detector, and when the interior of the energy storage cabin meets the spraying condition, a spraying nozzle is automatically started to continuously spray for preset spraying time; according to the centralized liquid cooling unit, a dual-redundancy compressor is combined with an ethylene glycol aqueous solution circulating system to conduct dynamic flow regulation and control, the opening degree of an electromagnetic valve of the dual-redundancy compressor is dynamically adjusted through a composite detector, and the internal temperature of an energy storage cabin is controlled; dynamically distributing flow according to the energy storage time period by adopting an intelligent temperature control algorithm; after the multi-stage fire-fighting module acts, the centralized liquid cooling unit is started for cooling; when the temperature detected by the composite detector exceeds a high-temperature threshold value, the fan is started for air replacement, and the multi-stage fire-fighting module is triggered to act.

The invention discloses a lithium battery thermal runaway control and safety response strategy system, which realizes the real-time monitoring and prediction of the internal temperature and voltage state of a battery through thermal-electric coupling modeling and multi-sensing data fusion, and realizes the real-time monitoring and prediction of the internal temperature and voltage state of the battery based on a model prediction control and threshold enhancement strategy. And triggering graded safety response in the early stage of thermal runaway. The system adopts a multi-stage response mechanism including measures of primary early warning, active cooling intervention, emergency power-off fire extinguishing and the like, a gas suppression path and cooling mode switching function is designed, and heat diffusion and spreading and toxic gas harm are effectively suppressed. Compared with a method depending on complex digital twinning or deep learning, the method is simple in structure, rapid in response and low in data dependence, has good system stability and engineering applicability, and can be widely applied to the field of lithium battery safety management of electric vehicle battery packs, energy storage power stations and the like.

A wildfire defense system trailer and method of installing an automated sprinkler¬ based wildfire defense system on a wood (home) building construction site before the starting of the construction phase of a home building project in a wildfire urban interface (WUI) region. The first commissioned automated sprinkler-based wildfire defense system will continue in operation all during the home building construction phase, and will only be decommissioned from operation, and removed from the premises, including the job-site wildfire defense system trailer being removed from the property, when construction of the wood building project is totally completed, and the wood building is ready for occupation. At the same time when the first system is decommissioned, a second permanently-installed automated sprinkler-based wildfire defense system will be completely installed within the new building construction, independent from the first system, and ready for commissioning to provide a new proactive measure of defense against a wildfire storm occurring after wood building construction has been completed, thereby protecting all wood and combustible surfaces on the home and surrounding property, and preventing fire ignition and flame spread until the wildfire storm passes through the WUI region. By virtue of the present invention, it is now possible to significantly reduce the risk of wood building construction projects occurring within a wildfire urban interface (WUI) region, and better support the underwriting of building construction and ownership insurance policies within such regions.

The invention provides a tunnel fire behavior inversion method based on multi-modal fusion and physical constraint, and aims to solve the problem that the position and power of a fire source are difficult to invert accurately in real time in traditional fire behavior monitoring. According to the method, data, temperature distribution images and physical parameters of distributed temperature sensors in a tunnel are collected, and a spatial-temporal feature fusion network is constructed; designing an information leakage prevention training mechanism, and adopting a modal random discarding and sensor shielding technology to avoid overfitting of the model to a specific input mode; a physical constraint loss function is introduced, and the temperature gradient, the maximum temperature rise and the longitudinal attenuation law are combined to ensure the physical rationality of an inversion result; a coarse-fine two-stage position prediction framework is adopted, and meter-scale precision positioning of the position of a fire source is achieved. According to the invention, the power and position of the fire source can be inversed accurately in real time, and reliable technical support is provided for intelligent monitoring and emergency rescue of tunnel fire.

The invention relates to the technical field of fire protection and security, in particular to a security and disinfection integrated multi-modal fusion embedded edge calculation method and system, and provides a security and disinfection integrated multi-modal fusion embedded edge calculation method which comprises the following steps: constructing a data set; the AI visual recognition model uses an improved YOLOv8 model to train a data set and execute target detection, meanwhile, an optical flow method is adopted to extract motion features of flames or smog in continuous key frame images in a monitoring video, and a spreading prediction model is established to send out an early warning signal in advance; and the fusion processing module establishes a dynamic threshold adjustment model based on the environmental parameters to optimize an early warning trigger threshold, and transmits the early warning trigger threshold to the fire-fighting linkage control module to verify and trigger fire-fighting linkage operation. AI intelligent analysis and fire-fighting linkage disposal of fire hazards are realized, false alarm of early warning information is effectively prevented, the discovery and disposal efficiency of the fire hazards is improved, and the fire hazards are eliminated in the bud.

The invention provides a blast suppression method and system for an underground cavity of a pumped storage power station. The method comprises the following steps: configuring and deploying a multispectral gas sensor array; carrying out gas explosion limit calculation and risk assessment; calculating the risk level of explosion by using the prediction model; performing graded explosion suppression operation by using a graded explosion suppression execution module; combustible gas is guided to enter an inerting area by utilizing a space flow guide optimization module; and the ignition source blocking module is used for cooperative control to block an ignition source. The technical problems of low mixed gas explosion risk prediction and monitoring precision, low explosion suppression efficiency, slow response speed and relatively high operation and maintenance cost are solved.

A fire suppression system includes an interface control module, and an interface module. The interface control module can activate a fire suppressant discharge system in response to receiving a fire detection signal. The interface module is connected with the interface control module and is connected with at least one of a first optical sensor and an interface expansion module. The interface expansion module is configured to connect with a second optical sensor. The first optical sensor and the second optical sensor are configured to detect a fire condition at an area of interest and provide the first detection signal to the interface control module in response to detecting the fire. The interface module includes light emitting devices corresponding to the first optical sensor and the interface expansion module, the light emitting devices configured to display different colors indicating a status of the first optical sensor and the interface expansion module.

A device, and method for its use, which may be worn by a firefighter for detecting the source of a fire in a smoke-filled or noisy environment, the device having directional infrared sensors for detecting the direction of maximum or minimum intensity of infrared radiation in two or more directions relative to the wearer and reporting at least the direction of maximum or minimum intensity to the wearer by a tactile indicator contacting the skin of the wearer.

The invention relates to the technical field of fire safety, and discloses a partition controller linkage method, device and equipment and a storage medium. The method comprises the following steps: acquiring original fire sensing data acquired by a plurality of fire-fighting sensors in each independent partition, and performing preprocessing of a plurality of sensing types; extracting space-time dimension features from the preprocessed data, generating fire behavior space-time feature vectors, and performing multi-source evidence weight fusion; performing fire abnormal mode identification and evaluation on the fused fire spatio-temporal feature vector to obtain a partition preliminary fire evaluation result, transmitting the partition preliminary fire evaluation result to a main controller, and performing global fire situation fusion based on a building physical structure and a partition connection relationship to obtain an overall fire situation evaluation result; and generating a multi-partition cooperative fire extinguishing execution scheme based on the overall fire situation assessment result, and controlling fire fighting equipment in each partition to perform linkage fire fighting. According to the invention, multi-source data fusion and cross-partition collaborative linkage of building fire are realized, and the fire detection accuracy and the fire-fighting response efficiency are improved.

The invention belongs to the technical field of safety protection, and particularly relates to an energy storage equipment safety protection early warning system applied to an industrial park, which adopts a module-cluster-cabin three-level architecture to realize real-time monitoring and dynamic evaluation of thermal runaway risk, the architecture integrates multi-source data, and when the risk exceeds a preset threshold value, the energy storage equipment safety protection early warning system is used for early warning the thermal runaway risk. The system automatically starts graded fire extinguishing measures and a fire-fighting linkage mechanism, and meanwhile, secondary analysis is carried out on an early warning result through a cloud platform to optimize model parameters, so that the accuracy and the efficiency of the system are ensured; the system constructs an integrated monitoring, response and self-correction prevention and control process, and effectively overcomes the problems of early warning delay, high false alarm rate, single protection means, data islanding and the like in the prior art through a multi-parameter fusion early warning, accurate recognition, graded fire extinguishing and intelligent linkage mechanism. And a solid guarantee is provided for fire safety in a high-density energy storage environment.

The invention relates to the technical field of intelligent fire safety linkage control, in particular to an intelligent locking linkage control system and method based on fire monitoring, and the system comprises an acquisition module, a modeling module, a simulation engine module, a decision center module and an execution module. The acquisition module acquires physical quantity data of a key area of a building, wherein the physical quantity data comprises high-temperature radiation spectrum offset, aerosol particle swarm distribution characteristics and local heat convection intensity. The modeling module generates an environmental interference confidence index through convolutional neural network fusion features, and starts an incremental clustering algorithm to update an interference knowledge base when the confidence is insufficient. And the execution module dynamically compresses the delay window according to the risk map, and triggers a cross-level linkage mechanism through a people flow density threshold. And the environment sampling frequency adjustment coefficient is fed back to the acquisition module, the execution state data reverse drive modeling module iteratively updates the knowledge base, a Bayesian optimizer is combined to screen high-value characteristics to reconstruct simulation parameters, and full-link closed-loop learning and continuous evolution of the false alarm suppression capability are realized.

The invention discloses a multi-modal space-time fusion and distributed cluster fire extinguishing robot cooperative control system, aims to solve the problems of low efficiency and poor precision of multi-machine cooperative fire extinguishing in wide-area fire investigation and flammable and explosive scenes, and provides a whole set of unmanned fire extinguishing technical solution for the multi-mode space-time fusion and distributed cluster fire extinguishing robot cooperative control system. The system comprises four core hardware architectures, namely a cloud dispatching center (A), an unmanned aerial vehicle cluster (B), an unmanned resource guarantee vehicle (C) and a crawler-type fire extinguishing robot cluster (D), and has the following core functions: 1, the cloud dispatching center (A) updates a fire scene model through distributed dispatching by fusing multi-modal sensor data, dynamically allocates tasks and plans a safe approach path; 2, the unmanned aerial vehicle cluster (B) executes the instruction, completes fire global positioning and cluster cooperative sensing, generates a high-precision fire topographic map and feeds back a signal; thirdly, the unmanned resource support vehicle (C) autonomously says for help, and has the functions of automatic mechanical arm water feeding and power supply, environment detection, on-site cleaning after fire extinguishing and communication relay; and fourthly, the crawler-type fire extinguishing robot cluster (D) autonomously navigates and positions the root of a fire source, detects and predicts the drop point of a water column, carries out fire extinguishing feedback evaluation, and interacts with the dispatching center cooperatively to dynamically adjust the strategy, so that closed-loop control is formed, and the fire extinguishing efficiency and accuracy are remarkably improved.

The invention discloses a graded detection method and system for an air-breathing smoke-sensing fire in a complex environment, and relates to the technical field of fire-fighting early warning, and the method comprises the steps: recognizing a ventilation opening of a monitoring region in the complex environment, and arranging air-breathing smoke-sensing equipment on the ventilation opening; state monitoring is conducted on the ventilation opening, and working mode parameters of the ventilation opening are obtained and comprise the ventilation starting and stopping state, the wind speed and the ventilation direction; and analyzing to obtain a self-adaptive strategy matched with the working mode parameters to control the sucking pump to drive the air-breathing smoke sensing equipment to collect smoke gas samples, performing multi-time sequence grading detection, and outputting a fire early warning signal. According to the invention, the technical problem that the existing fire detection technology is difficult to accurately collect smoke samples and give out early warning in time in places with complex ventilation structures and obvious air disturbance is solved, and the air-breathing smoke sensing equipment is arranged at the ventilation opening and the sampling strategy is dynamically adjusted; and the accuracy of smoke collection and the real-time performance of fire early warning are improved.

The invention discloses a fire fighting system intelligent management method and device based on intelligent property management, and relates to the technical field of data management. The intelligent management method and device for the fire fighting system based on the intelligent property management comprises the following steps: S1, dynamically triggering and collecting a multi-source fire fighting data set through multiple protocols, and temporarily storing the multi-source fire fighting data set at the edge in a normalized manner; s2, constructing an event full-period window and a ternary association index of the event, the time sequence data and the original message; s3, performing double-track storage of the semantic analysis data and the original message, and constructing multi-dimensional index association; s4, reconstructing a visual playback alarm process through edge cloud increment synchronization and a multi-dimensional time sequence chain; and S5, performing transient analysis, protocol upgrading and responsibility evidence obtaining based on the cloud data collaborative link and the original message data set. According to the method, the complete acquisition of the fire-fighting data and the reproducibility of the event process are effectively improved, and the problem that in the prior art, only polling recording of single-point alarm is carried out, and an original message is discarded, so that the transient process and message-level evidence is lost is solved.

The invention relates to the field of image processing, in particular to a fire-fighting equipment fault automatic detection method and system based on image processing, and the method comprises the steps: collecting a plurality of images in a plurality of regions at the same time interval, and carrying out the graying of the images; pixel points are classified according to gradient distribution of gray level images in the area, and corrosion probability parameters of the area are obtained; obtaining a water leakage probability parameter according to the time sequence change of pixel points in the suspected corrosion area; and comparing the change conditions of the pixel points of the suspected corrosion area and the non-suspected corrosion area to obtain a water leakage correction parameter, obtaining a fault early warning parameter by combining the parameters, setting a threshold value, comparing the threshold value with the fault early warning parameter, judging whether a water leakage condition exists or not, and completing automatic fault detection of the fire-fighting equipment. The method can effectively distinguish environment condensate water interference and real leakage, and has anti-noise capability.

The invention discloses an aerogel fire extinguishing agent for fire fighting, a fire extinguishing device and a releasing method.The aerogel fire extinguishing agent for fire fighting is prepared from, by mass, 8-12 parts of silicon dioxide aerogel powder, 40-45 parts of perfluorohexanone, 1.5-2 parts of zinc molybdate, 0.8-1.2 parts of nano cerium oxide, 2-3 parts of hyperbranched polysiloxane and 0.2-0.3 part of 18-crown-6 ether. Solid-phase silicon dioxide aerogel powder is matched with liquid-phase perfluorohexanone, zinc molybdate, nano cerium oxide, hyperbranched polysiloxane, 18-crown-6 ether and the like are compounded to serve as auxiliaries, efficient fire extinguishing can be conducted on precise electrical elements, residues are few, loss of instruments and equipment is small, and the fire extinguishing agent is suitable for being applied to the electrical field.

The disclosure is directed to a fire suppression system that includes all control components in a single integrated panel. It further contemplates and may include a chamber configured to maintain an interior inert atmosphere and to enclose and establish a nonflammable workspace for a pyrophoric workpiece. A temperature sensor may also be included and mounted proximate the workspace, along with an oxygen concentration sensor configured to detect an interior oxygen concentration of the atmosphere. The system also includes a dispenser configured to discharge an antipyrophoric granular material onto the workpiece responsive to automatic detection proximate the workpiece of at least one of a predetermined temperature and oxygen concentration. In variations, the chamber is configured as a glove box having viewing windows and a plurality of sealed glove ports positioned to enable user manipulation of the workpiece about the workspace.

The invention relates to the technical field of unmanned aerial vehicle inspection, and provides an unmanned aerial vehicle-based forest fire prevention inspection and disposal method, device and system. When an inspection unmanned aerial vehicle equipped with a multi-modal sensor is deployed to cruise according to a preset route, a visible light camera of the inspection unmanned aerial vehicle continuously collects forest region videos and transmits the videos to edge computing equipment of an inspection airport; fire hazards are analyzed in real time through a target recognition algorithm, and when a fire source is detected, position information is reported to a background terminal immediately; the system automatically dispatches the nearest fire extinguishing airport to dispatch the fire extinguishing unmanned aerial vehicle, and secondary accurate positioning is performed on a fire source by using the airborne infrared vision module, so that accurate throwing of the fire extinguishing bomb is ensured. The whole system enhances the real-time analysis capability through the edge computing device, breaks through the single-machine computing power limitation, also realizes the full-process automation from fire behavior recognition to fire extinguishing treatment, and significantly improves the response efficiency and treatment safety of forest fire prevention.

The invention relates to the technical field of lithium ion battery safety, and discloses a lithium ion battery thermal runaway multi-cascade emergency response prevention system. The system comprises a thermal signal monitoring module, a thermal diffusion prediction module, an emergency suppression module, a pressure balance module and a multi-mode linkage module. The thermal signal monitoring module obtains multi-dimensional temperature data, identifies abnormity and generates a thermal runaway early warning signal; the thermal diffusion prediction module combines the early warning signal and the battery module structure parameters to calculate the thermal propagation path and rate and generate a prediction result; the emergency suppression module matches a suppression medium according to a prediction result, and calculates a dose putting strategy to form a suppression scheme; the pressure balance module obtains pressure data, analyzes the change rate and distribution, adjusts a pressure release valve strategy in combination with a suppression scheme, and generates a pressure regulation and control instruction; and the multi-mode linkage module integrates data and a scheme, and generates a system-level emergency response instruction based on a pressure regulation and control instruction to realize thermal runaway multi-level joint prevention.

An electrified vehicle includes a front subframe, a rear subframe, and a body that connects the front subframe to the rear subframe so that forces acting on the front subframe and the rear subframe are transmitted through the body. The vehicle also includes a housing coupled to an underside of the body between the front subframe and the rear subframe. An energy storage system is enclosed in the housing and includes a battery and a battery interface configured to electrically couple the battery to at least one component of the electrified vehicle.