3657 results about "Thermal runaway" patented technology

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.

The invention discloses a multi-modal fusion lithium iron phosphate battery thermal runaway early warning method and system, and the method comprises the steps: collecting multi-source heterogeneous data, such as temperature, voltage, gas concentration and shell strain pressure, in real time through deploying a heterogeneous sensor network, and carrying out the noise reduction and time sequence feature extraction through employing a sub-linear time low-rank approximation algorithm of a Hankel matrix; constructing a cross-modal feature association network by applying a secondary time algorithm of a maximum weight sparse subgraph problem, inputting a fused feature vector into a Bayesian network health degree evaluation model for probabilistic reasoning calculation to obtain a battery health degree score and a thermal runaway risk level, generating a graded early warning signal through multi-level early warning threshold comparison, and performing early warning on the battery health degree score and the thermal runaway risk level. And corresponding prevention and control suggestions are matched. The method solves the technical problems that single physical quantity monitoring is difficult to comprehensively reflect the complex change in the battery and the response delay of a centralized processing architecture causes the early warning lag, and achieves the timely capture and accurate early warning of the early weak characteristics of thermal runaway.

The invention discloses a charging pile cooling control method and system based on AI prediction reinforcement learning, and relates to the technical field of cooling control. The charging pile cooling control method and system based on AI prediction reinforcement learning comprises the following steps: S1, collecting charging heat dissipation data of a charging pile, and preprocessing the charging heat dissipation data; s2, constructing a time sequence characteristic matrix, inputting the time sequence characteristic matrix into a temperature prediction model, outputting a temperature prediction sequence of a controlled target, evaluating a thermal runaway risk in a prediction stage, and constructing a thermal risk identification sequence; s3, constructing a cooling strategy optimization model, inputting the real-time state vector into the cooling strategy optimization model, outputting an adjustment instruction, and issuing and executing the adjustment instruction; and S4, the execution deviation of the adjustment instruction is evaluated, the cooling strategy is adjusted based on the evaluation result, and a cooling strategy feedback sample is generated. The problems of energy consumption waste and cooling imbalance caused by lack of real-time prediction and self-adaptive regulation and control capabilities in the cooling control process of the existing charging pile are solved.

The invention discloses a dynamic thermal management and risk pre-judgment system for a lithium battery energy storage system, and relates to the technical field of lithium battery energy storage, and the system comprises a thermal field monitoring module which generates a real-time three-dimensional thermal field distribution map of a battery pack; the dynamic regulation and control module is used for self-adaptively regulating the heat dissipation power and the refrigerant flow in combination with the charging and discharging states of the battery and the environmental parameters; the risk assessment module is used for constructing a thermal runaway risk grade assessment model and generating a risk probability value; the early warning response module triggers a multi-stage early warning mechanism according to the risk probability value, and is linked with the dynamic regulation and control module to execute an emergency heat dissipation strategy to generate a risk disposal scheme; and the data archiving module is used for storing data. According to the invention, the whole-process intelligent design of monitoring, regulation and control, evaluation, early warning and archiving is provided, the thermal management precision, the risk prevention and control capability and the operation economy of the lithium battery energy storage system are comprehensively improved, and a key technical guarantee is provided for large-scale energy storage application.

The invention discloses a quantum somatosensory-driven active protection method and system for thermal runaway of a charging pile, and relates to the technical field of charging pile protection. Comprising the following steps of S1, collecting quantum thermal runaway data in real time, performing data preprocessing, quantifying thermal risk sensitivity, and constructing a thermal runaway risk data set; s2, constructing a thermal runaway space-time matrix, constructing a thermal runaway risk principal component extraction model on the basis of the thermal runaway space-time matrix, and constructing a risk trend prediction model in combination with the thermal runaway space-time matrix and the thermal runaway risk principal component extraction model; s3, the thermal runaway risk is comprehensively judged, and early discovery and active protection of the thermal runaway risk are achieved; and S4, a safety threshold is judged, graded protection response of thermal runaway is carried out, and closed-loop optimization of the protection capability is realized. The problem that the existing traditional charging pile thermal runaway monitoring technology is difficult to timely and accurately discover, prevent and control the hidden danger of thermal runaway, and then the operation safety of the charging pile is affected is solved.

The invention discloses a battery fault diagnosis method and device, and belongs to the technical field of battery management. The method comprises the following steps: synchronously acquiring multi-dimensional signals in a battery operation process through a multi-modal sensor array; performing encoding processing on the multi-dimensional signal through a pulse encoder to obtain a standardized pulse time sequence; based on a federated transfer learning framework, training the quantum pulse neural network in combination with a physical constraint loss function to obtain a trained battery fault diagnosis model; inputting the standardized pulse time sequence into the battery fault diagnosis model, and calculating a battery fault category and a thermal runaway probability through quantum inference; and triggering a corresponding security policy according to the thermal runaway probability and a preset threshold. By adopting the technical means of multi-mode signal fusion, quantum calculation acceleration and distributed learning, accurate and rapid diagnosis of battery faults is realized, and the method has the advantages of high precision, low delay and low power consumption.

The invention discloses a lithium battery thermal runaway risk dynamic regulation and control method and system, and the method comprises the steps: collecting temperature data in a new energy automobile battery module, and constructing a temperature field matrix; judging whether the lithium battery has a temperature risk based on the temperature field matrix; when the temperature risk exists in the lithium battery, risk grades are divided; and based on the divided risk levels, dynamically regulating and controlling the thermal runaway risk of the lithium battery. The differential cooling parameters are determined according to the risk level and the hot spot position, and the control strategy is optimized in real time through feedback data, so that the flow velocity adjustment and heat dissipation power distribution of the liquid cooling system are more scientific and effective, the overall performance of battery thermal management is improved, the risk of thermal runaway of the lithium battery is effectively reduced, and the service life of the lithium battery is prolonged. The method has wide application prospects in the fields of new energy automobiles and the like, and stable operation of the system and personnel safety guarantee can be remarkably enhanced.

The invention relates to the technical field of batteries, and discloses an explosion-proof valve and a battery cell. The explosion-proof valve comprises a valve body; the number of the nicks is n, the nicks are arranged on the valve body, the nicks are located on any side of the valve body in the thickness direction of the valve body, the residual thicknesses of the nicks are sequentially decreased from the first nick to the nth nick, and n is larger than or equal to 2. According to the explosion-proof valve, the plurality of nicks are arranged on the valve body, and the residual thicknesses of different nicks are different, so that positions corresponding to different nicks can be broken under different pressures, the explosion-proof valve can be opened from different positions under different pressures, a multi-stage exhaust passage is formed, effective exhaust and pressure relief during thermal runaway of a battery cell are facilitated, and the explosion-proof effect is improved. The problem that the explosion-proof valve cannot be opened due to deformation of the battery cell or unstable gas production rate in the traditional design form of a single nick is avoided, effective exhaust and pressure relief when the safety of the battery cell fails are facilitated, and the safety of the battery cell is improved.

The invention discloses a lithium iron phosphate battery grading active fire control method and system, and the method comprises the steps: collecting multi-mode perception data through deploying a multi-source sensor network and a BMS data interface, and constructing a battery thermal runaway risk assessment model through employing a Lyapunov fixed time stability theory; a hierarchical prevention and control strategy is dynamically generated in combination with a historical case sensitivity scoring mechanism, and linkage response of first-level early warning heat dissipation, second-level aerosol inhibition and third-level perfluorohexanone fire extinguishing is achieved. According to the invention, the problem that the prior art lacks self-adaptability and BMS deep collaboration is solved, the technical transformation from passive response to active prevention and control is realized, and the accuracy and timeliness of thermal runaway early warning are remarkably improved.

The invention belongs to the technical field of electrochemical energy storage, and provides an immersed energy storage system and a thermal management method thereof, the immersed energy storage system comprises a sealed cabin, a battery module, an immersion liquid, a liquid cooling unit, a cooling liquid, a liquid cooling pipeline, a temperature sensor, an electrical device and a thermal management controller; the non-conductive immersion liquid with the conductivity smaller than 10 <-6 > S / m and the flash point larger than 200 DEG C is adopted to completely wrap the battery module, it is ensured that the energy storage battery cells are located in the same temperature physical environment, the temperature consistency of the system is greatly improved, the problem of uneven heat dissipation is fundamentally solved, the service life of the energy storage cabinet is directly prolonged, the immersion liquid has the flame-retardant characteristic, and the service life of the energy storage cabinet is prolonged. Thermal runaway of a battery cell can be effectively restrained, fire and explosion risks are reduced from the source, system operation safety is guaranteed, meanwhile, the type selection standard of cooling liquid is defined, the design of a sealed cabin is optimized, the heat exchange efficiency is improved through a double-circulation branch of a liquid cooling unit, the key bottleneck of an immersed cooling technology in energy storage system integration is thoroughly solved, and the energy storage system integration efficiency is improved. And full landing of technical advantages is realized.

The invention relates to the technical field of battery safety, and particularly provides a battery safety boundary dynamic prediction method, which comprises the following steps of: acquiring multi-source data in real time and preprocessing the multi-source data; constructing a scene feature vector based on the multi-source data, and identifying a current scene type through a machine learning algorithm; inputting the scene type into the security boundary prediction model, and outputting a dynamic security boundary set; a time window rolling mechanism is adopted, the scene type, the dynamic safety boundary set, the overall internal parameters of the battery pack and the environment state parameters are input into a safety boundary prediction model, and the overall safety boundary change trend of the battery pack within preset time is predicted; and setting multi-stage early warning thresholds, performing association analysis based on the overall internal parameters of the battery pack, generating an early warning signal according to an analysis result, and generating a control strategy according to the early warning signal. The safety management level of the whole life cycle of the battery is improved, and a systematic solution is provided for preventing thermal runaway, prolonging the service life of the battery and guaranteeing reliable operation under complex working conditions.

The invention provides a lithium-sulfur battery thermal runaway monitoring method and system based on a neural network. The lithium-sulfur battery thermal runaway monitoring method comprises the steps that S1, single battery state data, group-level heat dissipation data and temperature data in a battery cabin are collected and preprocessed; s2, respectively constructing a double-branch gating network, a multi-head attention enhancement mechanism and a multi-scale residual error enhancement network, and sequentially extracting a bimodal battery characteristic, a battery heterogeneity characteristic and a deep heterogeneity characteristic; s3, extracting temperature field correlation characteristics through a temperature field correlation gating fusion mechanism; extracting monomer-overall temperature field conjugate characteristics; s4, cross-dimension fusion features are extracted through a double-feature inherent association dynamic weighting mechanism; calculating an abnormal heat value and an overall thermal runaway risk level of each single battery; and S5, performing visual display at the monitoring terminal, and triggering an early warning signal. The method can solve the problem that a traditional method cannot fuse monomer heterogeneity and overall temperature field correlation, so that local overheating is caused, and missed judgment is easily caused.

The invention discloses a rapid thermal simulation method and system for a semiconductor power assembly, and relates to the technical field of semiconductors, and the method comprises the steps: collecting a voltage V (t) signal and a current I (t) signal of the semiconductor power assembly in real time through a voltage and current sampling circuit, constructing a power pulse input sequence A, and carrying out the hot carrier accumulation analysis according to the power fluctuation change amplitude; introducing a transient thermal resistance function Zth (t), fitting the transient thermal resistance function Zth (t) with a hot carrier pulse response index Mcx after numerical integration to analyze junction temperature change caused by power pulse, and evaluating an equivalent junction temperature dynamic change rate; when the analysis result is that the thermal drift out-of-control trend exists, thermal risk analysis is carried out, and thermal risk state assessment is generated; the simulation model optimizes thermal model parameters and outputs thermal control suggestions through a rollback correction path, and the working state of the semiconductor power assembly is automatically adjusted. According to the method, real-time monitoring and effective prevention and control of thermal runaway can be realized, and the reliability and safety of the semiconductor power assembly are improved.

The invention discloses a battery box and a battery pack for battery cell thermal runaway optimization management, and relates to the field of battery pack thermal runaway optimization, the battery box for battery cell thermal runaway optimization management comprises an outer box body; the battery cell placing space is formed in a cavity of the outer box body, the smoke exhaust channel is communicated with the battery cell placing space, an explosion-proof assembly is arranged on the outer box body, and the explosion-proof assembly comprises a first explosion-proof valve communicated with the smoke exhaust channel and a second explosion-proof valve which is communicated with the cavity of the outer box body and is different from the first explosion-proof valve in opening pressure; when the battery cell aluminum shell is damaged, high-temperature flue gas can be guided to be discharged in order, the influence of the high-temperature flue gas on a high-pressure part is reduced, and a safe pressure relief path is ensured, so that the safety redundancy and reliability of a battery system are greatly improved.

The invention relates to the technical field of new energy automobile and battery safety, and discloses a power battery thermal runaway risk early warning method, which comprises the following steps: synchronously acquiring battery internal resistance dynamic change, characteristic gas concentration and temperature gradient distribution through a multi-physics field coupling sensor network, and constructing an electrochemical-thermal-gas ternary early criterion; the internal resistance mutation rate is calculated through self-adaptive sliding window differential, the gas precipitation rate and the temperature space heterogeneity index are combined and input into a multi-branch fusion neural network containing a gating attention mechanism, the continuous thermal runaway risk probability is output, and corresponding early warning is triggered according to grading threshold values. The system comprises an internal resistance, gas and temperature monitoring module and a multi-modal fusion evaluation and grading early warning execution module. According to the method, the traditional early warning logic singly depending on a temperature threshold value is abandoned, a ternary early criterion system with the internal resistance abrupt change rate, the characteristic gas precipitation rate and the temperature space heterogeneity index as the core is constructed for the first time, and electrochemical and physical field anomalies caused by thermal runaway precursor events such as lithium dendrite piercing of a diaphragm and SEI membrane rupture can be effectively captured.

The invention relates to the technical field of intelligent fire extinguishing control of energy storage power stations, in particular to a method and system for plasma protection of thermal runaway of an air-cooled energy storage power station. The method comprises the following steps: processing real-time data acquired by a multi-source sensor through a dynamic risk assessment model to obtain a risk level and an early warning level; an initial control instruction for the plasma generator and the air cooling and refrigerating system is formed according to the risk level and the early warning level; the initial control instruction is processed to form a driving control signal; a control signal is subjected to cooperative execution processing to obtain a high-energy active particle jet flow, a forced airflow and a refrigeration effect. The system comprises an air cooling box body, a battery, a fan, a plasma generator, an ejector, an intelligent controller, a compressor, a gas-liquid separator, a heat exchanger, an electronic expansion valve, a drying filter, a gas sensor and a pressure sensor valve. The safety and reliability of the energy storage power station are improved.

The utility model provides a cover plate assembly, a battery and electric equipment. The cover plate assembly comprises a terminal and a body, the body comprises a first connecting part and a second connecting part, the first connecting part is connected with the terminal, the second connecting part is connected to the side, away from the terminal, of the first connecting part, and an explosion-proof structure is formed at the joint of the first connecting part and the second connecting part. According to the cover plate assembly, when the battery is subjected to thermal runaway, the terminal can be separated from the collector plate of the battery, so that the battery can be powered off, the situation that the thermal runaway is aggravated due to the fact that the battery is still discharged when being subjected to thermal runaway can be avoided, and the safety of the battery is improved.

The invention relates to the technical field of immersed temperature control and thermal runaway prevention of a power battery of a new energy automobile. The technical problems to be solved are clearly reflected that the non-uniform heat dissipation and spontaneous combustion of the power battery are two technical problems of a new energy automobile, and the technology provided by the invention can enable the heat dissipation of the power battery to be good and prevent spontaneous combustion. The technical scheme for solving the problem is characterized in that a buffer material is used for protecting the bottom of a battery pack, a circulating temperature control system is filled with fluorinated liquid, elements such as battery cells in the battery pack are soaked in the fluorinated liquid, and according to the temperature requirement of the battery cells, the fluorinated liquid exchanges heat with a heat pump system, a heater and a driving motor, so that the battery pack is heated. The fluorinated liquid is recycled to raise or lower the temperature of elements such as the battery pack. When the battery cell is abnormally high in temperature or thermal runaway, the battery cell is extinguished and cooled by means of quick discharge, water injection into the battery pack and the like. The device is used for heating or circularly cooling elements such as a power battery and preventing spontaneous combustion of a power battery pack.

The lithium secondary battery comprises a positive electrode, a negative electrode, a diaphragm and a polymer electrolyte, the polymer electrolyte contains the flame-retardant microcapsule, the flame-retardant microcapsule has a core-shell structure, a copolymer material containing one or more of an amide group, an ester group and an ether group is taken as a shell layer, and a flame retardant is taken as a core; the rupture collapse temperature of the flame-retardant microcapsule shell material is 60-120 DEG C, the melting point of the flame retardant is 20-120 DEG C, and the rupture collapse temperature of the copolymer material is higher than the melting point of the flame retardant. The lithium secondary battery disclosed by the invention has excellent flame retardance, the flame-retardant microcapsule added in the lithium secondary battery can be broken and collapsed when the battery is in thermal runaway, and the flame retardant is quickly released, so that the thermal runaway is actively defended in advance from the interior of the battery, and the electrochemical performance of the battery is not reduced.

The invention discloses a real-time emergency prevention and control system and method for an electrochemical energy storage system based on digital twinning, and belongs to the field of energy storage safety. The system comprises a multi-source sensing unit, a digital twin deduction unit and a visual emergency decision unit. The sensing unit collects multi-source data to form a state vector; the deduction unit outputs a future thermal runaway evolution path containing a temperature field, a gas concentration field and a fire blast risk probability and uncertainty measurement thereof in real time through a pre-trained Gaussian process regression agent model; and the decision-making unit performs three-dimensional visual rendering, jointly determines a high-confidence risk area based on the risk level and the uncertainty level, and generates an emergency prevention and control instruction with accurate spatial positioning. The problems that in the prior art, disaster evolution paths cannot be predicted in real time, and prevention and control measures are extensive are solved, millisecond-level online deduction and accurate active prevention and control of the thermal runaway process are achieved, and the safety of an energy storage system is remarkably improved.

The invention provides a battery pack and electric equipment, the battery pack comprises a plurality of batteries, each battery is provided with a first surface, the first surface is provided with a pressure relief piece and a pole, and the pressure relief piece is provided with a weak part; the busbars are connected with the pole posts in a welding manner to form welding parts; a guard; the shortest distance between the weak part and the pole is D, the overlapping area of the orthographic projection of the area defined by the weak part on the first surface and the orthographic projection of the protection piece on the first surface is A, the overlapping area of the orthographic projection of the pole on the first surface and the orthographic projection of the protection piece on the first surface is B, and the area of the protection piece is S2, the shortest distance between every two adjacent welding parts is M, A + B = S1, S1 / S2 = Y, and 3.2 mm < 2 > < = D * Y * M < = 8897 mm < 2 >. Compared with the prior art, the method has the advantages that the formula value is limited in the preset range, the polar column can be prevented from being influenced by the pressure relief part, the thermal runaway risk of the adjacent battery is reduced, and meanwhile, the pressure relief part can timely relieve pressure.

The invention relates to the technical field of battery thermal management, in particular to an energy storage battery module multi-mode heat flow field coupling early warning cooling decision system and method, which comprises a multi-sensor acquisition module, an infrared thermal imaging preprocessing module, a battery pack thermal diffusion mechanism model module, a data fusion model module and a cooling decision module, the core innovation lies in that a battery pack thermal diffusion mechanism model is constructed based on a differential geometry theory, a battery pack surface temperature field is regarded as a Riemannian manifold embedded in a three-dimensional space, early prediction of thermal runaway is realized by analyzing topological structure change of a heat flow field, and a system acquires temperature, pressure, vibration and other multi-modal data of an energy storage battery module and performs thermal runaway prediction on the energy storage battery module. The method comprises the following steps: preprocessing infrared thermal imaging data, generating three-dimensional thermal diffusion data, constructing an electric-thermal-flow multi-physical field dynamic model, identifying a critical point and a topological structure in a thermal flow field, generating thermal field characteristic data, fusing multi-source data to generate a thermal diffusion imbalance criterion, and optimizing cooling parameters by adopting a reinforcement learning algorithm.

The invention provides a battery and an electric device. A positive plate comprises a positive active material, and the positive active material is doped and / or coated with a lanthanum element; the surface of the diaphragm is coated with a ceramic coating; the electrolyte comprises a first solvent, a second solvent, a first additive and a second additive; the first solvent comprises a cyclic carbonate compound, the second solvent comprises a chain fluorosulfonamide compound, the first additive comprises mannitol carbonate sulfate, and the second additive comprises succinonitrile; the lanthanum element is doped / coated on the positive active material, so that the release of lattice oxygen at high voltage or high temperature can be effectively inhibited, and the exothermic reaction activity at the thermal runaway initial temperature is reduced; the first additive and the second additive in the electrolyte respectively form a compact CEI film and an SEI film with high thermal stability on the surfaces of the positive electrode and the negative electrode; the diaphragm ceramic coating provides a physical barrier, the thermal shrinkage temperature of the diaphragm is increased, and internal short circuit is prevented.

The invention discloses a multi-terminal linkage control method and system for a fire alarm scene, and relates to the technical field of energy storage system fire safety, and the method comprises the steps: configuring a composite cluster-level detector for each cluster of batteries of a target energy storage system, and collecting cluster-level external environment data; the method comprises the following steps: acquiring internal state data of a battery pack through a BMS, and uploading the two types of data to an edge calculation unit; the edge calculation unit performs fire risk assessment on the data and determines fire risk assessment parameters of the battery cluster; and determining a battery cluster fire extinguishing decision result, and finally performing multi-end linkage fire extinguishing control on the fire extinguishing device through the result. The technical problems that a traditional fire detection and fire extinguishing control scheme is slow in response, high in false alarm and missing alarm rate and incapable of giving consideration to internal and external states when dealing with thermal runaway of the energy storage system are solved, and the technical effects of early-stage accurate early warning and rapid linkage fire extinguishing and effective improvement of the fire safety level of the energy storage system are achieved.

The invention provides a multi-modal coupled lithium battery thermal runaway multi-stage early warning method and system in the technical field of lithium battery safety monitoring. The method comprises the following steps: S1, collecting a large amount of historical multi-modal monitoring data in a lithium battery operation process to construct a data set; s2, creating a thermal runaway monitoring model based on a time-frequency feature extraction module, a feature fusion module, a reconstruction decoding module, a physical simulation module, a multi-source information fusion module and a report output module, and training and deploying the thermal runaway monitoring model through a data set; s3, collecting real-time multi-mode monitoring data of the lithium battery, inputting the real-time multi-mode monitoring data into the deployed thermal runaway monitoring model, and obtaining a monitoring report carrying a temperature average value, a temperature standard deviation, a voltage average value and a voltage standard deviation; and S4, performing thermal runaway early warning on the lithium battery based on the monitoring report. The lithium battery thermal runaway early warning method has the advantages that the accuracy, the working condition adaptability and the reliability of lithium battery thermal runaway early warning are greatly improved.

The invention provides a power battery passport management method and device, electronic equipment and a storage medium. A data system covering the whole life cycle of a battery is constructed; obtaining power battery multi-source data reported by suppliers at all levels, binding the power battery multi-source data with a unique identifier of the power battery, and realizing evidence storage and verification through a block chain consensus mechanism; constructing a digital twin engine based on a preset battery electrochemical model and a thermal runaway model, performing working condition prediction on the battery operation state, and generating working condition early warning threshold data; and filling a preset passport template with the multi-source data and the working condition early warning threshold data, generating a power battery electronic passport, and performing versioning maintenance and uplink release. Unified management, credible evidence storage and traceability of power battery full life cycle data are realized, normalization and dynamism of passport generation are improved, prospective early warning of battery operation risks is realized in combination with digital twinborn prediction, and integrity, safety and compliance of the electronic passport are guaranteed.

The invention discloses a battery pack thermal runaway prediction method and device, and relates to the technical field of power battery thermal runaway fault early warning, and the method comprises the steps: generating a dynamic weighted graph of a battery pack based on the physical connection relation between single cells in the battery pack, so as to obtain the spatial characteristics of the battery pack; according to the improved Transform model and in combination with the spatial features, obtaining long-term features of the battery pack; fusing the spatial features and the long-term features to obtain space-time fusion abnormal features; inputting the time-space fusion abnormal features into a classifier to obtain the fault occurrence probability of each single battery cell so as to predict the fault battery and the fault time; wherein a fault sensitive mask matrix is added into the improved Transform model before standard self-attention calculation, and temperature gradient information used for representing battery state parameters is added into position codes. According to the method, the limitation of single dimension in the prediction process is overcome, and the overall accuracy of prediction is improved.

The invention discloses an energy storage battery thermal diffusion modeling method based on P2D-solid heat transfer coupling, and relates to the technical field of energy storage battery thermal management. The method comprises the following steps: constructing a pseudo two-dimensional (P2D) electrochemical model and a three-dimensional heat conduction model of a single battery, and calculating lithium ion concentration, potential and corresponding heat source distribution; mapping the obtained heat source as a volume heat source to a thermal model and realizing bidirectional feedback; setting a thermal runaway triggering condition to simulate temperature rise abrupt change; battery SOH state modeling is introduced, and the aging process is dynamically corrected and reflected through material parameters; finally, time domain simulation is carried out, and temperature field evolution and safety behavior prediction in the whole life cycle are obtained. According to the method, the coupling process of the microelectrochemical reaction and the macroscopic temperature change of the battery can be captured at the same time, the thermal diffusion characteristics of different decline stages are accurately described, and visual modeling of thermal runaway behaviors is supported. The method has the remarkable advantages of high precision, high applicability, perfect safety assessment capability and the like.

The invention discloses a lithium battery thermal runaway prediction and multistage response system based on AI intelligent evaluation, and the system comprises a multi-sensing monitoring module, an AI prediction evaluation module, a thermal runaway risk evaluation module, a safety response control module, and a safety execution module. Through fusion of multi-dimensional sensing data and an artificial intelligence algorithm, real-time prediction and evaluation of the thermal runaway risk of the battery are realized, and graded safety response measures are actively triggered at the early stage of thermal runaway. And aiming at different risk levels, the system automatically executes corresponding multi-level protection actions. The system also has online learning and model adaptive optimization capabilities, and can continuously improve the prediction accuracy and response efficiency along with the change of the state of the battery. And the thermal runaway early warning sensitivity and the response timeliness are remarkably improved, and the method has an intelligent level and engineering practicability 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.

The invention discloses a new energy automobile power battery thermal runaway early warning method and system, and belongs to the technical field of new energy automobile battery safety monitoring. The method comprises the steps of multi-dimensional parameter acquisition and feature cascade fusion, battery state time sequence prediction and residual error anomaly detection based on an attention-enhanced long-short-term memory network, thermal runaway multi-stage state transition estimation based on a hidden Markov model, model parameter dynamic updating based on online adaptive learning, and dynamic state transition estimation based on the hidden Markov model. And multi-stage early warning and emergency disposal graded linkage response are carried out, and accurate early warning of thermal runaway is realized through deep coupling closed-loop cooperation among the steps.