3857results about "Secondary cells testing" patented technology

The invention relates to the technical field of battery management, and discloses a battery energy balanced distribution and optimization method, device and equipment and a storage medium. The method comprises the following steps: performing multi-source parameter acquisition and feature decoupling on each single battery in a target battery pack to obtain a single battery state data set, and performing multi-band excitation scanning and impedance spectrum fitting to obtain internal features of the battery and decompose an attenuation trend to generate equivalent circuit model parameters; performing state mapping and capacity calculation based on the model parameters to obtain a performance evaluation result of the battery pack, and constructing an energy transfer network and identifying unbalanced propagation characteristics through performance difference analysis and consistency calculation; and temperature coupling calculation and compensation matrix reconstruction are carried out based on propagation characteristics, multi-path parallel balance control is realized, and an optimization result of the battery pack is obtained through voltage deviation calculation and polarization compensation. According to the method, the multi-dimensional characteristic parameters and the dynamic change characteristics are combined, and accurate control over battery pack equalization is achieved.

The invention relates to the technical field of battery management, in particular to a battery module early abnormality early warning method and system fused with a time sequence knowledge graph, and the method comprises the steps: obtaining static parameters and dynamic sensor data of each battery node in a battery module, and constructing the time sequence knowledge graph; performing node-relation importance evaluation of topology embedding, and screening out key nodes and relations; constructing heterogeneous knowledge unified mapping of multi-manifold representation, and projecting battery voltage, temperature and state manifolds to a unified representation space; performing spectrogram-driven adaptive Transform structure optimization on the data of the uniform representation space, and performing spectrogram-driven adaptive Transform structure optimization on the data of the uniform representation space; bidirectional coupling graph-sequence information flow cooperative processing is realized, graph structure information is converted into sequence representation, and a graph structure is fed back and updated; carrying out multi-scale feature hierarchy fusion and integration, and integrating hierarchy feature information of a battery monomer, a module and a system; and evaluating the health state of the battery module based on the multi-scale fusion feature information, and generating early warning information in an abnormal state or an abnormal state.

The present invention is a hybrid energy storage battery status monitoring method and system based on big data processing. The method aims at the non-linear and difficult online evaluation problems of the hybrid energy storage battery status. It is set up to collect charging sample information and discharge sample information in sequence. Steps include data sorting and fusion steps, hybrid energy storage battery SOH estimation steps, and hybrid energy storage battery health level evaluation steps to implement business hybrid energy storage battery status monitoring. Among them, the sample data information elements include voltage and current in the charge and discharge state, power, temperature, internal resistance, through data collection and fusion processing, and data prediction through preset models, it can fully cover the hybrid energy storage battery status, conduct a comprehensive assessment, and improve the accuracy of the assessment.

The invention discloses a distributed electrochemical energy storage fire alarm system based on an intelligent algorithm, and relates to the technical field of energy storage battery safety monitoring. Technical processes of multi-source data acquisition and preprocessing, key health factor extraction, multi-modal feature fusion, depth model detection, cross-system intervention and adaptive strategy optimization are provided; a high-quality data stream is generated through real-time synchronous sampling and noise filtering, weak fault symptoms such as internal short circuit or material deterioration are highlighted by applying a multi-dimensional feature structure, a deep learning model is utilized to accurately recognize and output early warning, and then load reduction, isolation and temperature control measures are carried out in cooperation with a BMS, an EMS and a fire fighting system. An evolutionary algorithm or a reinforcement learning continuous iteration intervention strategy is introduced in a simulation environment, high-sensitivity capture and rapid suppression of latent risks under multi-scene complex working conditions are achieved, the rate of missing report and false report can be remarkably reduced, and the overall safety of the system is remarkably enhanced.

The invention belongs to the technical field of battery detection, and particularly provides a mine lithium battery charging and discharging detection method, which comprises the following steps: acquiring mine environment parameters and lithium battery state parameters in real time; obtaining a historical construction log, and calculating a corresponding construction stage of the mine environment parameter based on the historical construction log through time sequence analysis according to the mine environment parameter; inputting the mine environment parameters and the corresponding construction stage into a trained environment risk assessment model to output a current environment risk level; according to the lithium battery state parameters and the current environment risk level, the battery detection frequency and the charge and discharge protection threshold are dynamically adjusted, and a control instruction containing adjustment parameters is generated; switching a communication protocol based on the environmental risk level and sending the control instruction to the battery management system; by calculating the environmental risk level, corresponding measures can be taken according to the risk level; and the environmental risk level is added as a switching condition, so that the communication reliability and stability in different environments are ensured.

The invention relates to the technical field of circuit control, in particular to a control method and system of a bidirectional charging and discharging circuit. The method comprises the following steps: collecting current monitoring data and voltage monitoring data of a bidirectional charging and discharging circuit in real time; performing arc characteristic analysis on the current monitoring data and the voltage monitoring data to obtain arc characteristic data; analyzing a high-frequency harmonic component and a current ripple fluctuation amplitude of the bidirectional charging and discharging circuit based on the arc characteristic data; performing direct-current arc detection on the bidirectional charging and discharging circuit according to the high-frequency harmonic component and the current ripple fluctuation amplitude to generate a direct-current arc fault judgment result; and calculating the instantaneous current change rate of the current monitoring data, and carrying out short-circuit detection on the bidirectional charging and discharging circuit through the instantaneous current change rate. By monitoring current and voltage data in real time, arc and short circuit characteristics are accurately analyzed, relay control is optimized, an accurate control instruction is generated, and the safety and reliability of the two-way charging and discharging circuit 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.

An X-ray inspection device according to one embodiment of the present disclosure includes: an X-ray output portion irradiating X-rays to a battery including a cathode, a separator, and an anode in a stacking direction of the cathode and the anode; an X-ray detection portion acquiring a plurality of gray values based the X-rays that have transmitted through the battery; a signal processing portion acquiring an X-ray image including the plurality of gray values; and an inspection portion determining whether the battery is defective based on a distance between a first edge of an anode area including gray values representing the anode layer and a second edge of a cathode area including gray values representing the cathode layer in the X-ray image.

According to the acoustics-based battery thermal runaway early warning and positioning method, system and equipment and the medium, judgment is performed based on the action sound of the safety valve in the early stage of thermal runaway, and early warning of thermal runaway can be realized so as to facilitate early intervention; the positioning algorithm combining the sound time difference of arrival and the particle filtering can realize accurate positioning of the thermal runaway battery cell monomers, and can display the specific positions of the abnormal battery cell monomers, so that thermal runaway treatment can be accurate to the specific battery cell monomers.

The invention discloses a full-immersion type liquid cooling energy storage system and a control method thereof, and relates to the technical field of energy storage control, and the method comprises the steps: installing multiple sensors in a liquid immersion tank, carrying out the calibration, collecting the state data of a battery module and cooling liquid in real time through the calibrated multiple sensors, and obtaining the state data of the battery module and the cooling liquid; the state data of the battery module and the cooling liquid are preprocessed and uploaded to a control center, a Transform model is constructed in the control center, historical state data of the battery module and the cooling liquid are used for training, the trained Transform model is obtained, the preprocessed state data of the battery module and the cooling liquid are input into the trained Transform model, and the state data of the battery module and the cooling liquid are obtained. And obtaining prediction results of the high-risk area position and the expected temperature change value. The invention provides an intelligent control strategy and a multi-sensor network based on a Transform model, and local cooling is realized by monitoring the temperature change of the liquid cooling energy storage equipment in real time and adjusting the flow and path of the cooling liquid in real time.

The invention relates to the technical field of electronic equipment battery management, and discloses a battery charging management method and an electric quantity accurate display method based on electronic equipment. The dynamic adjusting module generates a multi-dimensional strategy through a staged charging control unit (including a fast, balanced and trickle charging sub-unit), a parameter transition processing layer and a global charging state pooling layer; the environment adaptation module adjusts the charging power and the temperature threshold according to the environment data, and has the functions of environment feature extraction, self-adaptive compensation and anti-interference switching; and the strategy fusion module outputs a control instruction in a weighted manner, and is additionally provided with an exception handling and wireless charging optimization mechanism. When the electric quantity is displayed, the collected data is dynamically calibrated to compensate polarization errors, and the capacity is fused with a matching historical curve to generate a high-precision electric quantity percentage which is dynamically rendered and displayed. According to the scheme, the charging safety, efficiency and electric quantity display precision are improved.

The invention relates to the technical field of battery packs, and discloses a battery pack intelligent pairing and integrated optimization method, system and device and a storage medium. The method comprises the following steps: performing parameter acquisition and orthogonal feature extraction on single batteries in a battery pack to obtain a battery pack orthogonal parameter characteristic matrix; performing feature deep learning to obtain a battery pack pairing prediction model; a battery attribute similarity graph and a battery pack topological graph are constructed, and a battery pack intelligent pairing structure is obtained through double-graph structure alignment operation; executing parallel multi-population particle swarm optimization calculation to obtain a battery pack optimization pairing scheme; inputting a hierarchical model prediction controller to carry out energy storage boundary analysis to obtain an upper-layer power distribution parameter and a lower-layer charging and discharging current parameter; and closed-loop control operation is carried out based on the upper-layer power distribution parameters and the lower-layer charging and discharging current parameters to obtain battery pack pairing control optimization parameters, and real-time monitoring and dynamic adjustment of the battery pack performance parameters are achieved.

The invention relates to the technical field of battery pack BMS, and discloses a battery pack BMS control power distribution method and system, and the method comprises the steps: collecting a voltage value, a current value, a temperature value and a state-of-charge value of each battery unit in a battery pack, and calculating the number of subsystems; performing spectral clustering operation on the battery units in the system state matrix to obtain a hypergraph Laplacian matrix; performing multilayer hypergraph convolution operation and ReLU activation function processing on the hypergraph Laplacian matrix to obtain an initial power feature matrix; calculating a target power characteristic matrix between the battery unit node and the corresponding power transmission path; establishing a dual-constraint optimization model to obtain a battery pack state quantity and a battery pack observed quantity; and carrying out iterative calculation until the difference value of the power distribution schemes of two adjacent iterations is smaller than a preset threshold value, and outputting a target power distribution scheme, thereby improving the accuracy and rationality of power distribution.

The invention relates to the technical field of battery state monitoring, in particular to an intelligent online capacity checking management system for a storage battery pack, which comprises a jump sensing module, a lag correlation module, a starting point confirmation module, a state diagnosis module and a correction output module. According to the invention, the method achieves the precise recognition of a voltage hysteresis effect through the positioning of the difference value of a current sudden change point, the tracking of a fluctuation convergence interval, the construction of a dynamic sudden change buffer structure, the enhancement of the capturing capability of a key change behavior, the extraction of a response time point in combination with the change trend of a voltage derivative, and the combined binding of a charge state based on the voltage difference value and current sampling. The real-time performance and the pertinence of capacity evaluation are improved, the sudden change period is identified through the charge state difference value, a synchronous mark is established through voltage stability analysis, correction mapping is carried out according to the state difference, a capacity correction path with continuity, traceability and dynamic adaptability is formed, and the precision and the stability of capacity management of the storage battery pack are effectively improved.

The present invention relates to a hybrid energy storage battery state monitoring method and system based on big data processing. According to the method, for the problems of the states of hybrid energy storage batteries being non-linear and being difficult to evaluate online, a charging sample information collection step, a discharging sample information collection step, a data collation and fusion step, a hybrid energy storage battery SOH estimation step, and a hybrid energy storage battery health level evaluation step are provided in sequence for achieving state monitoring of service hybrid energy storage batteries, wherein sample data information elements comprise voltage, current, power, temperature and internal resistance in the charging and discharging state, data is collated and fused, data prediction is carried out by means of a preset model, the states of the hybrid energy storage batteries can be covered in all directions, comprehensive evaluation is carried out, so that the evaluation accuracy is improved.

An energy storage apparatus includes: an external terminal 51; an energy storage cell 62; a current interruption device 53 that has one end electrically connected to the external terminal 51 and the other end electrically connected to the energy storage cell 62; a discharge circuit 110 that discharges electricity from the energy storage cell 62 via a path that does not pass through the current interruption device 53; and a failure diagnosis device 150. The failure diagnosis device 150 discharges electricity from the energy storage cell 62 using the discharge circuit 110, and diagnoses a failure of the current interruption device 53 based on a change in voltage ΔV1 of the external terminal 51 before and after discharging electricity.

An aspect of the current disclosure includes a battery module charge and discharge inspection system. The battery module charge and discharge inspection system may include a supporting member configured to support a battery module and transfer the battery module, a first fixing member provided on a top of one side of the supporting member, a second fixing member provided at a bottom of one side of the supporting member, a connecting pin disposed to pass through the first fixing member, the supporting member, and the second fixing member, respectively, and a charge and discharge inspection part configured to inspect whether or not the battery module is abnormal through charging and discharging of the battery module. The first fixing member may be configured to be connected to a first wire harness extending from the battery module.

The invention discloses an unmanned aerial vehicle energy-power conversion system, and relates to the technical field of unmanned aerial vehicle energy, and the system comprises a battery module which is formed by combining a plurality of single batteries in a series connection or parallel connection manner, and is responsible for providing electric energy required by the flight of an unmanned aerial vehicle. And the energy management module performs real-time monitoring, optimal distribution and intelligent regulation and control on energy use of the unmanned aerial vehicle through an integrated sensor, algorithm and control technology, and comprises a data acquisition unit, a charging management unit and a power conversion unit. The charging management unit is used for managing an unmanned aerial vehicle battery charging process, externally connecting a charging power supply and controlling an unmanned aerial vehicle battery charging strategy according to the battery power reserve level; and the power conversion unit adopts a dynamic power distribution strategy, implements closed-loop control based on the real-time power spectrum characteristics of the driving module, and realizes on-demand power output adjustment. And the configuration of longer endurance time of the same power supply weight or fewer batteries under the same endurance time is realized.

The invention provides a bidirectional parallel storage battery capacity checking system and method, and relates to the field of battery capacity checking, and the system comprises a station control system, a plurality of direct current buses, an alternating current bus, a plurality of storage battery packs, a battery optimizer and a bidirectional charging and discharging module, and is used for realizing storage, charging and discharging management and online capacity checking of storage batteries. The storage battery pack comprises a plurality of battery modules connected in parallel, and each battery module comprises storage batteries managed in pairs and a charging and discharging control circuit and is used for managing the charging and discharging states of the storage batteries. According to the capacity checking system and method provided by the invention, capacity checking is allowed to be carried out on a single battery pack, the storage batteries needing capacity checking can exit independently, and other battery packs continue to supply power normally under the condition that the overall power supply is not influenced, so that the parallel connection mode not only avoids power interruption and resource waste, but also realizes fine management of the battery packs, and the power supply efficiency is improved. The service life of the storage battery is prolonged, and the continuity and the stability of a power system are ensured.

The invention relates to the technical field of energy storage technology, integrated circuit design and battery management systems, and discloses a passport-sensing integrated battery management chip and a battery management system architecture, battery information is collected based on the passport-sensing integrated battery management chip, and unique battery passport information is generated. And then real-time interaction with the BMS main control module is carried out through the daisy chain communication module, so that the health state of the battery is evaluated and managed. The battery cell state data acquisition and traceability functions are realized through the battery cell slave board, the BMS master control module has a fine management function on the battery state, battery safety early warning and daisy chain communication channels are provided to realize real-time interaction between the battery cell slave board information and the BMS master control module information, online and offline information disclosure modes are fused, a collaborative management architecture is established, and the battery cell state data acquisition and traceability functions are realized. Intelligent management and data tracking of the whole life cycle of the battery are realized, and the safety, reliability and traceability of the battery are improved.

The invention relates to the technical field of battery intelligent charging, in particular to an intelligent charging system for a solid-state lead battery energy storage power station. The method comprises the following steps: acquiring a real-time impedance characteristic parameter set and a real-time battery operation parameter set, and determining a multi-dimensional battery state data set according to the real-time impedance characteristic parameter set and the real-time battery operation parameter set; obtaining a renewable energy power generation data set, and based on the renewable energy power generation data set and according to the multi-dimensional battery state data set, carrying out evolution analysis on solid electrolyte impedance fluctuation, and constructing a solid electrolyte impedance evolution model; determining an adaptive battery charging strategy according to the solid electrolyte impedance evolution model; and according to the self-adaptive battery charging strategy, power station charging parameters are adjusted, and a charging adjustment report is determined and output. The passivation speed of the solid electrolyte in the solid lead battery can be slowed down under the condition of intermittent fluctuation of renewable energy power generation, and the service life of the battery is prolonged.

Disclosed is a BMS-based battery energy storage safety management system. The system comprises a BMS module, a control center module, an evaluation analysis module, a coupling analysis module, a prediction module, and a data storage module. The BMS module collects monitoring data of a battery under different operation states and then, according to the monitoring data, performs initial monitoring of a real-time health state of the battery. The evaluation analysis module, according to a change in data indicators in the monitoring data, evaluates and analyzes all fault analysis models in the BMS module to obtain an evaluation analysis result. Then the coupling analysis module combines the evaluation analysis result with the data indicators of the monitoring data to retrieve multidimensional spatio-temporal data, and constructs a coupling field model to perform coupling analysis on battery operation state. The prediction module then constructs a fault prediction model by using a coupling data set as training data, accurately locates coupling faults of different coupling surfaces, and implements comprehensive analysis and location of coupling faults.

The invention belongs to the field of battery testing, and particularly relates to a method for judging SEI film performance difference, battery formation and aging time and a lithium ion battery. The judgment method comprises the following steps of: testing the Rct resistance value of the battery and judging the voltage drop by using an EIS; the larger the Rct resistance value and the larger the voltage drop of the EIS test are, the poorer the performance of the SEI film is; the smaller the Rct resistance value and the smaller the voltage drop are, the better the SEI film performance is. The method is high in accuracy and feasibility, the difference of different formation processes and the shortest time of the aging process are effectively judged while the performance and quality of the battery are guaranteed, the production efficiency of the battery is improved, and the production cost of the battery is reduced.

A durability evaluation method of a secondary battery includes a durability step of continuing to apply an alternating current voltage of a durability frequency to a first secondary battery for evaluation over a durability test period, and an evaluation step of evaluating durability of an associated battery reaction associated with the durability frequency from among battery reactions of the first secondary battery. A temperature and a state of charge of the first secondary battery are adjusted to a first temperature and a first state of charge, respectively.

The present invention relates to a method for analyzing a cathode active material, a cathode active material, a cathode and a lithium secondary battery, and, to: a method for analyzing a cathode active material; a cathode active material having a slope, obtained through the analysis method, of 0.00110-0.00130; a cathode comprising same; and a lithium secondary battery, the method comprising the steps of: (S1) preparing a cathode active material that comprises a layer-structured lithium-rich manganese-based oxide, which comprises both a Li2MnO3 phase and a LiMO2 (here, M is an element comprising at least one selected from Ni and Mn) phase, and manufacturing a lithium secondary battery that comprises a cathode comprising a cathode active material layer comprising 80 wt% or more of the cathode active material on the basis of the total weight of the cathode active material layer; (S2) obtaining a specific capacity-voltage graph (x-axis: specific capacity (mAh / g), and y-axis: voltage (V)) by activating the lithium secondary battery at a 0.1C-rate at 45°C ; and (S3) obtaining a slope by linearly fitting, in a section of the graph, data in which a voltage is 4.40-4.65 V.

A test method, system, apparatus and device for an energy storage control system, and a storage medium. The test method comprises: receiving test indication information (S201); on the basis of the test indication information, simulating an associated device connected to a device to be tested in an energy storage control system, and determining simulation-associated parameters (S202); and on the basis of the simulation-associated parameters and the test indication information, testing the device to be tested, and receiving a test result of the device to be tested (S203). A test device (104) can implement the simulation of any device associated with a device to be tested in an energy storage control system. Specifically, interface implementations and function execution logic implementations of any device can be simulated, and the simulated interface implementations or function implementations are implemented by means of simulation-associated parameters. Therefore, the test process is not limited to testing a specific type of device to be tested, and multiple types of tests can be implemented, thereby improving the applicability of the test method to a certain extent.

The present application provides a battery thermal runaway detection method and apparatus. The method comprises: acquiring a time series signal generated when a gas sensor identifies a gas component released by a battery, and converting the time series signal into an image signal, so as to strength key features in the signal; processing the image signal by means of a target detection model, so as to predict a gas type and a gas concentration; and then determining a thermal runaway risk of the battery on the basis of a prediction result. Therefore, by introducing a machine learning algorithm, simple gas identification requirements are met, and complex data analysis and prediction can be carried out, thereby accurately predicting the thermal runaway risk of lithium batteries, and effectively improving the early warning precision of thermal runaway.

To provide an information collection device and a battery pack which improve the sealing performance of a signal collection device.SOLUTION: The present disclosure relates to the field of battery technologies, and provides an information collection device and a battery pack. The information collection device includes a casing, an air pressure sensor, and a sealing member. The casing has a first installation hole. The air pressure sensor is installed inside the casing, and at least a part of the air pressure sensor is snap-fitted into the first installation hole to acquire an air pressure parameter outside the casing. The sealing member seals the first installation hole, and the sealing member is used to allow gas to pass through and prevent liquid from passing through. Thereby, the information collection device can be arranged in a battery cell, and can collect information in an environment of electrolyte, thus capable of mitigating the technical problems of complex structure and insufficient reliability of a cover plate of the battery cell caused by external arrangement of the information collection device.SELECTED DRAWING: Figure 1

The present disclosure discloses a testing system, a battery production line, and a testing method. The testing system includes a control device and a test device. The test device includes at least two probe card adjustment assemblies. The control device is connected to the test device and configured to adjust the probe card adjustment assemblies according to an adjustment strategy, and drive the adjusted probe card adjustment assemblies to test the battery module currently to be tested. The adjustment strategy is determined based on current module information corresponding to the battery module and historical module information. The historical module information is the module information of a battery module tested last time. The technical solution provided by the embodiments of the present disclosure can quickly adjust the probe card adjustment assemblies to adapt to different battery modules.

The invention discloses an intelligent scheduling method and system for a battery energy storage system, and the method comprises the steps: generating a multi-dimensional operation state matrix through obtaining the charge state, charge-discharge rate and temperature data of a battery unit, and combining the power grid load and power market price information; according to the multi-dimensional operation state matrix, calculating an electric energy distribution proportion of each battery unit by adopting a preset state-of-charge threshold and charge-discharge rate constraint, and generating an initial electric energy distribution scheme; if a battery unit whose charge-discharge rate exceeds a safety range exists in the initial electric energy distribution scheme, predicting a performance attenuation trend based on historical operation data, and adjusting a distribution proportion to generate a corrected electric energy distribution scheme; according to the corrected electric energy distribution scheme, real-time temperature data are obtained, the local overheating risk is judged, and a temperature adjustment instruction set containing heat dissipation power adjustment parameters is generated. The operation efficiency and the economic benefit of the battery energy storage system can be effectively improved, and meanwhile the safety and the stability of the system are guaranteed.